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Sample records for brain neural basis

  1. Neural Basis of Brain Dysfunction Produced by Early Sleep Problems

    Directory of Open Access Journals (Sweden)

    Jun Kohyama

    2016-01-01

    Full Text Available There is a wealth of evidence that disrupted sleep and circadian rhythms, which are common in modern society even during the early stages of life, have unfavorable effects on brain function. Altered brain function can cause problem behaviors later in life, such as truancy from or dropping out of school, quitting employment, and committing suicide. In this review, we discuss findings from several large cohort studies together with recent results of a cohort study using the marshmallow test, which was first introduced in the 1960s. This test assessed the ability of four-year-olds to delay gratification and showed how this ability correlated with success later in life. The role of the serotonergic system in sleep and how this role changes with age are also discussed. The serotonergic system is involved in reward processing and interactions with the dorsal striatum, ventral striatum, and the prefrontal cortex are thought to comprise the neural basis for behavioral patterns that are affected by the quantity, quality, and timing of sleep early in life.

  2. Neural Basis of Brain Dysfunction Produced by Early Sleep Problems

    Science.gov (United States)

    Kohyama, Jun

    2016-01-01

    There is a wealth of evidence that disrupted sleep and circadian rhythms, which are common in modern society even during the early stages of life, have unfavorable effects on brain function. Altered brain function can cause problem behaviors later in life, such as truancy from or dropping out of school, quitting employment, and committing suicide. In this review, we discuss findings from several large cohort studies together with recent results of a cohort study using the marshmallow test, which was first introduced in the 1960s. This test assessed the ability of four-year-olds to delay gratification and showed how this ability correlated with success later in life. The role of the serotonergic system in sleep and how this role changes with age are also discussed. The serotonergic system is involved in reward processing and interactions with the dorsal striatum, ventral striatum, and the prefrontal cortex are thought to comprise the neural basis for behavioral patterns that are affected by the quantity, quality, and timing of sleep early in life. PMID:26840337

  3. The neural basis of temporal individuation and its capacity limits in the human brain.

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    Naughtin, Claire K; Tamber-Rosenau, Benjamin J; Dux, Paul E

    2017-11-01

    Individuation refers to individuals' use of spatial and temporal properties to register objects as distinct perceptual events relative to other stimuli. Although behavioral studies have examined both spatial and temporal individuation, neuroimaging investigations have been restricted to the spatial domain and at relatively late stages of information processing. Here, we used univariate and multivoxel pattern analyses of functional MRI data to identify brain regions involved in individuating temporally distinct visual items and the neural consequences that arise when this process reaches its capacity limit (repetition blindness, RB). First, we found that regional patterns of blood-oxygen-level-dependent activity across the cortex discriminated between instances where repeated and nonrepeated stimuli were successfully individuated-conditions that placed differential demands on temporal individuation. These results could not be attributed to repetition suppression or other stimulus-related factors, task difficulty, regional activation differences, other capacity-limited processes, or artifacts in the data or analyses. Contrary to current theoretical models, this finding suggests that temporal individuation is supported by a distributed set of brain regions, rather than a single neural correlate. Second, conditions that reflect the capacity limit of individuation-instances of RB-lead to changes in the spatial patterns within this network, as well as amplitude changes in the left hemisphere premotor cortex, superior medial frontal cortex, anterior cingulate cortex, and bilateral parahippocampal place area. These findings could not be attributed to response conflict/ambiguity and likely reflect the core brain regions and mechanisms that underlie the capacity-limited process that gives rise to RB.NEW & NOTEWORTHY We present novel findings into the neural bases of temporal individuation and repetition blindness (RB)-the perceptual deficit that arises when this process

  4. Working Memory after Traumatic Brain Injury: The Neural Basis of Improved Performance with Methylphenidate.

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    Manktelow, Anne E; Menon, David K; Sahakian, Barbara J; Stamatakis, Emmanuel A

    2017-01-01

    Traumatic brain injury (TBI) often results in cognitive impairments for patients. The aim of this proof of concept study was to establish the nature of abnormalities, in terms of activity and connectivity, in the working memory network of TBI patients and how these relate to compromised behavioral outcomes. Further, this study examined the neural correlates of working memory improvement following the administration of methylphenidate. We report behavioral, functional and structural MRI data from a group of 15 Healthy Controls (HC) and a group of 15 TBI patients, acquired during the execution of the N-back task. The patients were studied on two occasions after the administration of either placebo or 30 mg of methylphenidate. Between group tests revealed a significant difference in performance when HCs were compared to TBI patients on placebo [F(1, 28) = 4.426, p working memory network and (b) Methylphenidate improves the cognitive outcomes on a working memory task. Therefore, we conclude that methylphenidate may render the working memory network in a TBI group more consistent with that of an intact working memory network.

  5. Working Memory after Traumatic Brain Injury: The Neural Basis of Improved Performance with Methylphenidate

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    Manktelow, Anne E.; Menon, David K.; Sahakian, Barbara J.; Stamatakis, Emmanuel A.

    2017-01-01

    Traumatic brain injury (TBI) often results in cognitive impairments for patients. The aim of this proof of concept study was to establish the nature of abnormalities, in terms of activity and connectivity, in the working memory network of TBI patients and how these relate to compromised behavioral outcomes. Further, this study examined the neural correlates of working memory improvement following the administration of methylphenidate. We report behavioral, functional and structural MRI data from a group of 15 Healthy Controls (HC) and a group of 15 TBI patients, acquired during the execution of the N-back task. The patients were studied on two occasions after the administration of either placebo or 30 mg of methylphenidate. Between group tests revealed a significant difference in performance when HCs were compared to TBI patients on placebo [F(1, 28) = 4.426, p memory network and (b) Methylphenidate improves the cognitive outcomes on a working memory task. Therefore, we conclude that methylphenidate may render the working memory network in a TBI group more consistent with that of an intact working memory network. PMID:28424597

  6. Neural basis for brain responses to TV commercials: a high-resolution EEG study.

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    Astolfi, Laura; De Vico Fallani, F; Cincotti, F; Mattia, D; Bianchi, L; Marciani, M G; Salinari, S; Colosimo, A; Tocci, A; Soranzo, R; Babiloni, F

    2008-12-01

    We investigated brain activity during the observation of TV commercials by tracking the cortical activity and the functional connectivity changes in normal subjects. The aim was to elucidate if the TV commercials that were remembered by the subjects several days after their first observation elicited particular brain activity and connectivity compared with those generated during the observation of TV commercials that were quickly forgotten. High-resolution electroencephalogram (EEG) recordings were performed in a group of healthy subjects and the cortical activity during the observation of TV commercials was evaluated in several regions of interest coincident with the Brodmann areas (BAs). The patterns of cortical connectivity were obtained in the four principal frequency bands, Theta (3-7 Hz), Alpha (8-12 Hz), Beta (13-30 Hz), Gamma (30-40 Hz) and the directed influences between any given pair of the estimated cortical signals were evaluated by use of a multivariate spectral technique known as partial directed coherence. The topology of the cortical networks has been identified with tools derived from graph theory. Results suggest that the cortical activity and connectivity elicited by the viewing of the TV commercials that were remembered by the experimental subjects are markedly different from the brain activity elicited during the observation of the TV commercials that were forgotten. In particular, during the observation of the TV commercials that were remembered, the amount of cortical spectral activity from the frontal areas (BA 8 and 9) and from the parietal areas (BA 5, 7, and 40) is higher compared with the activity elicited by the observation of TV commercials that were forgotten. In addition, network analysis suggests a clear role of the parietal areas as a target of the incoming flow of information from all the other parts of the cortex during the observation of TV commercials that have been remembered. The techniques presented here shed new light on

  7. Alexia and the Neural Basis of Reading.

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    Benson, D. Frank

    1984-01-01

    The historical background of alexia (loss or impairment of the ability to comprehend written or printed language based on damage to the brain) is reviewed, classification and symptomatology considered, theories on the involvement of right hemisphere reading are noted, and the neural basis of reading is postulated. (CL)

  8. The neural basis of phantom limb pain.

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    Flor, Herta; Diers, Martin; Andoh, Jamila

    2013-07-01

    A recent study suggests that brain changes in amputees may be pain-induced, questioning maladaptive plasticity as a neural basis of phantom pain. These findings add valuable information on cortical reorganization after amputation. We suggest further lines of research to clarify the mechanisms that underlie phantom pain. Copyright © 2013 Elsevier Ltd. All rights reserved.

  9. Neural basis for the brain responses to the marketing messages: an high resolution EEG study.

    Science.gov (United States)

    Babiloni, Fabio; Cincotti, Febo; Mattia, Donatella; Mattiocco, Marco; Bufalari, Simona; De Vico Fallani, Fabrizio; Tocci, Andrea; Bianchi, Luigi; Marciani, Maria Grazia; Meroni, Vittorio; Astolfi, Laura

    2006-01-01

    We investigated the behaviour of the brain during the visualization of commercial videos by tracking the cortical activity and the functional connectivity changes in normal subjects. High resolution EEG recordings were performed in a group of healthy subjects, and the cortical activity during the visualization of standard commercial spots and emotional spots (no profit companies) was estimated by using the solution of the linear inverse problem with the use of realistic head models. The cortical activity was evaluated in several regions of interest (ROIs) coincident with the Brodmann areas. The pattern of cortical connectivity was obtained by using the partial directed coherence (PDC) and investigated in the time and frequency domains, in the principal four frequency bands, namely the theta (4-7 Hz), the alpha (8-12 Hz), the beta (13-30 Hz) and the gamma (above 30 Hz). Results suggest a time-varying engagement of the orbitofrontal circuits that is thought to be involved in the reward value of the stimuli.

  10. The transsexual brain--A review of findings on the neural basis of transsexualism.

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    Smith, Elke Stefanie; Junger, Jessica; Derntl, Birgit; Habel, Ute

    2015-12-01

    Transsexualism describes the condition when a person's psychological gender differs from his or her biological sex and is commonly thought to arise from a discrepant cerebral and genital sexual differentiation. This review intends to give an extensive overview of structural and functional neurobiological correlates of transsexualism and their course under cross-sex hormonal treatment. Research in this field enables insight into the stability or variability of gender differences and their relation to hormonal status. For a number of sexually dimorphic brain structures or processes, signs of feminisation or masculinisation are observable in transsexual individuals, which, during hormonal treatment, partly seem to further adjust to characteristics of the desired sex. Still, it appears the data are quite inhomogeneous, mostly not replicated and in many cases available for male-to-female transsexuals only. As the prevalence of homosexuality is markedly higher among transsexuals than among the general population, disentangling correlates of sexual orientation and gender identity is a major problem. To resolve such deficiencies, the implementation of specific research standards is proposed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. A neural basis for general intelligence

    OpenAIRE

    Duncan, J.; Seitz, R.J.; Kolodny, J.; Bor, D.; Herzog, H; Ahmed, A.; Newell, F. N.; Emslie, H

    2000-01-01

    Universal positive correlations between different cognitive tests motivate the concept of "general intelligence" or Spearman's g. Here the neural basis for g is investigated by means of positron emission tomography. Spatial, verbal, and perceptuo-motor tasks with high-g involvement are compared with matched Low-g control tasks. In contrast to the common view that g reflects a broad sample of major cognitive functions, high-g tasks do not show diffuse recruitment of multiple brain regions. Ins...

  12. Human Brain Basis of Musical Rhythm Perception: Common and Distinct Neural Substrates for Meter, Tempo, and Pattern

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    Michael H. Thaut

    2014-06-01

    Full Text Available Rhythm as the time structure of music is composed of distinct temporal components such as pattern, meter, and tempo. Each feature requires different computational processes: meter involves representing repeating cycles of strong and weak beats; pattern involves representing intervals at each local time point which vary in length across segments and are linked hierarchically; and tempo requires representing frequency rates of underlying pulse structures. We explored whether distinct rhythmic elements engage different neural mechanisms by recording brain activity of adult musicians and non-musicians with positron emission tomography (PET as they made covert same-different discriminations of (a pairs of rhythmic, monotonic tone sequences representing changes in pattern, tempo, and meter, and (b pairs of isochronous melodies. Common to pattern, meter, and tempo tasks were focal activities in right, or bilateral, areas of frontal, cingulate, parietal, prefrontal, temporal, and cerebellar cortices. Meter processing alone activated areas in right prefrontal and inferior frontal cortex associated with more cognitive and abstract representations. Pattern processing alone recruited right cortical areas involved in different kinds of auditory processing. Tempo processing alone engaged mechanisms subserving somatosensory and premotor information (e.g., posterior insula, postcentral gyrus. Melody produced activity different from the rhythm conditions (e.g., right anterior insula and various cerebellar areas. These exploratory findings suggest the outlines of some distinct neural components underlying the components of rhythmic structure.

  13. Human brain basis of musical rhythm perception: common and distinct neural substrates for meter, tempo, and pattern.

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    Thaut, Michael H; Trimarchi, Pietro Davide; Parsons, Lawrence M

    2014-06-17

    Rhythm as the time structure of music is composed of distinct temporal components such as pattern, meter, and tempo. Each feature requires different computational processes: meter involves representing repeating cycles of strong and weak beats; pattern involves representing intervals at each local time point which vary in length across segments and are linked hierarchically; and tempo requires representing frequency rates of underlying pulse structures. We explored whether distinct rhythmic elements engage different neural mechanisms by recording brain activity of adult musicians and non-musicians with positron emission tomography (PET) as they made covert same-different discriminations of (a) pairs of rhythmic, monotonic tone sequences representing changes in pattern, tempo, and meter, and (b) pairs of isochronous melodies. Common to pattern, meter, and tempo tasks were focal activities in right, or bilateral, areas of frontal, cingulate, parietal, prefrontal, temporal, and cerebellar cortices. Meter processing alone activated areas in right prefrontal and inferior frontal cortex associated with more cognitive and abstract representations. Pattern processing alone recruited right cortical areas involved in different kinds of auditory processing. Tempo processing alone engaged mechanisms subserving somatosensory and premotor information (e.g., posterior insula, postcentral gyrus). Melody produced activity different from the rhythm conditions (e.g., right anterior insula and various cerebellar areas). These exploratory findings suggest the outlines of some distinct neural components underlying the components of rhythmic structure.

  14. A neural basis for general intelligence.

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    Duncan, J; Seitz, R J; Kolodny, J; Bor, D; Herzog, H; Ahmed, A; Newell, F N; Emslie, H

    2000-07-21

    Universal positive correlations between different cognitive tests motivate the concept of "general intelligence" or Spearman's g. Here the neural basis for g is investigated by means of positron emission tomography. Spatial, verbal, and perceptuo-motor tasks with high-g involvement are compared with matched low-g control tasks. In contrast to the common view that g reflects a broad sample of major cognitive functions, high-g tasks do not show diffuse recruitment of multiple brain regions. Instead they are associated with selective recruitment of lateral frontal cortex in one or both hemispheres. Despite very different task content in the three high-g-low-g contrasts, lateral frontal recruitment is markedly similar in each case. Many previous experiments have shown these same frontal regions to be recruited by a broad range of different cognitive demands. The results suggest that "general intelligence" derives from a specific frontal system important in the control of diverse forms of behavior.

  15. The neural basis of following advice.

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    Guido Biele

    2011-06-01

    Full Text Available Learning by following explicit advice is fundamental for human cultural evolution, yet the neurobiology of adaptive social learning is largely unknown. Here, we used simulations to analyze the adaptive value of social learning mechanisms, computational modeling of behavioral data to describe cognitive mechanisms involved in social learning, and model-based functional magnetic resonance imaging (fMRI to identify the neurobiological basis of following advice. One-time advice received before learning had a sustained influence on people's learning processes. This was best explained by social learning mechanisms implementing a more positive evaluation of the outcomes from recommended options. Computer simulations showed that this "outcome-bonus" accumulates more rewards than an alternative mechanism implementing higher initial reward expectation for recommended options. fMRI results revealed a neural outcome-bonus signal in the septal area and the left caudate. This neural signal coded rewards in the absence of advice, and crucially, it signaled greater positive rewards for positive and negative feedback after recommended rather than after non-recommended choices. Hence, our results indicate that following advice is intrinsically rewarding. A positive correlation between the model's outcome-bonus parameter and amygdala activity after positive feedback directly relates the computational model to brain activity. These results advance the understanding of social learning by providing a neurobiological account for adaptive learning from advice.

  16. The neural basis of bounded rational behavior

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    Coricelli, Giorgio

    2012-03-01

    Full Text Available Bounded rational behaviour is commonly observed in experimental games and in real life situations. Neuroeconomics can help to understand the mental processing underlying bounded rationality and out-of-equilibrium behaviour. Here we report results from recent studies on the neural basis of limited steps of reasoning in a competitive setting —the beauty contest game. We use functional magnetic resonance imaging (fMRI to study the neural correlates of human mental processes in strategic games. We apply a cognitive hierarchy model to classify subject’s choices in the experimental game according to the degree of strategic reasoning so that we can identify the neural substrates of different levels of strategizing. We found a correlation between levels of strategic reasoning and activity in a neural network related to mentalizing, i.e. the ability to think about other’s thoughts and mental states. Moreover, brain data showed how complex cognitive processes subserve the higher level of reasoning about others. We describe how a cognitive hierarchy model fits both behavioural and brain data.

    La racionalidad limitada es un fenómeno observado de manera frecuente tanto en juegos experimentales como en situaciones cotidianas. La Neuroeconomía puede mejorar la comprensión de los procesos mentales que caracterizan la racionalidad limitada; en paralelo nos puede ayudar a comprender comportamientos que violan el equilibrio. Nuestro trabajo presenta resultados recientes sobre la bases neuronales del razonamiento estratégico (y sus límite en juegos competitivos —como el juego del “beauty contest”. Estudiamos las bases neuronales del comportamiento estratégico en juegos con interacción entre sujetos usando resonancia magnética funcional (fMRI. Las decisiones de los participantes se clasifican acorde al grado de razonamiento estratégico: el llamado modelo de Jerarquías Cognitivas. Los resultados muestran una correlación entre niveles de

  17. Neural basis of economic bubble behavior.

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    Ogawa, A; Onozaki, T; Mizuno, T; Asamizuya, T; Ueno, K; Cheng, K; Iriki, A

    2014-04-18

    Throughout human history, economic bubbles have formed and burst. As a bubble grows, microeconomic behavior ceases to be constrained by realistic predictions. This contradicts the basic assumption of economics that agents have rational expectations. To examine the neural basis of behavior during bubbles, we performed functional magnetic resonance imaging while participants traded shares in a virtual stock exchange with two non-bubble stocks and one bubble stock. The price was largely deflected from the fair price in one of the non-bubble stocks, but not in the other. Their fair prices were specified. The price of the bubble stock showed a large increase and battering, as based on a real stock-market bust. The imaging results revealed modulation of the brain circuits that regulate trade behavior under different market conditions. The premotor cortex was activated only under a market condition in which the price was largely deflected from the fair price specified. During the bubble, brain regions associated with the cognitive processing that supports order decisions were identified. The asset preference that might bias the decision was associated with the ventrolateral prefrontal cortex and the dorsolateral prefrontal cortex (DLPFC). The activity of the inferior parietal lobule (IPL) was correlated with the score of future time perspective, which would bias the estimation of future price. These regions were deemed to form a distinctive network during the bubble. A functional connectivity analysis showed that the connectivity between the DLPFC and the IPL was predominant compared with other connectivities only during the bubble. These findings indicate that uncertain and unstable market conditions changed brain modes in traders. These brain mechanisms might lead to a loss of control caused by wishful thinking, and to microeconomic bubbles that expand, on the macroscopic scale, toward bust. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  18. Brain and language: evidence for neural multifunctionality.

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    Cahana-Amitay, Dalia; Albert, Martin L

    2014-01-01

    This review paper presents converging evidence from studies of brain damage and longitudinal studies of language in aging which supports the following thesis: the neural basis of language can best be understood by the concept of neural multifunctionality. In this paper the term "neural multifunctionality" refers to incorporation of nonlinguistic functions into language models of the intact brain, reflecting a multifunctional perspective whereby a constant and dynamic interaction exists among neural networks subserving cognitive, affective, and praxic functions with neural networks specialized for lexical retrieval, sentence comprehension, and discourse processing, giving rise to language as we know it. By way of example, we consider effects of executive system functions on aspects of semantic processing among persons with and without aphasia, as well as the interaction of executive and language functions among older adults. We conclude by indicating how this multifunctional view of brain-language relations extends to the realm of language recovery from aphasia, where evidence of the influence of nonlinguistic factors on the reshaping of neural circuitry for aphasia rehabilitation is clearly emerging.

  19. The neural circuit basis of learning

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    Patrick, Kaifosh William John

    The astounding capacity for learning ranks among the nervous system's most impressive features. This thesis comprises studies employing varied approaches to improve understanding, at the level of neural circuits, of the brain's capacity for learning. The first part of the thesis contains investigations of hippocampal circuitry -- both theoretical work and experimental work in the mouse Mus musculus -- as a model system for declarative memory. To begin, Chapter 2 presents a theory of hippocampal memory storage and retrieval that reflects nonlinear dendritic processing within hippocampal pyramidal neurons. As a prelude to the experimental work that comprises the remainder of this part, Chapter 3 describes an open source software platform that we have developed for analysis of data acquired with in vivo Ca2+ imaging, the main experimental technique used throughout the remainder of this part of the thesis. As a first application of this technique, Chapter 4 characterizes the content of signaling at synapses between GABAergic neurons of the medial septum and interneurons in stratum oriens of hippocampal area CA1. Chapter 5 then combines these techniques with optogenetic, pharmacogenetic, and pharmacological manipulations to uncover inhibitory circuit mechanisms underlying fear learning. The second part of this thesis focuses on the cerebellum-like electrosensory lobe in the weakly electric mormyrid fish Gnathonemus petersii, as a model system for non-declarative memory. In Chapter 6, we study how short-duration EOD motor commands are recoded into a complex temporal basis in the granule cell layer, which can be used to cancel Purkinje-like cell firing to the longer duration and temporally varying EOD-driven sensory responses. In Chapter 7, we consider not only the temporal aspects of the granule cell code, but also the encoding of body position provided from proprioceptive and efference copy sources. Together these studies clarify how the cerebellum-like circuitry of the

  20. Toward a Neural Basis for Social Behavior

    OpenAIRE

    Stanley, Damian A.; Adolphs, Ralph

    2013-01-01

    Nearly 25 years ago, the shared interests of psychologists and biologists in understanding the neural basis of social behavior led to the inception of social neuroscience. In the past decade, this field has exploded, in large part due to the infusion of studies that use fMRI. At the same time, tensions have arisen about how to prioritize a diverse range of questions and about the authority of neurobiological data in answering them. The field is now poised to tackle some of the most interestin...

  1. The neural basis of maternal bonding.

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    Ming Wai Wan

    Full Text Available BACKGROUND: Accumulating evidence suggests that mothers show a different pattern of brain responses when viewing their own compared to other infants. However, there is inconsistency across functional imaging studies regarding the key areas involved, and none have examined relationships between brain and behavioural responses to infants. We examined the brain regions activated when mothers viewed videos of their own infant contrasted with an unknown infant, and whether these are associated with behavioural and self-reported measures of mother-infant relations. METHOD: Twenty right-handed mothers viewed alternating 30-sec blocks of video of own 4-9 month infant and an unfamiliar matched infant, interspersed with neutral video. Whole brain functional magnetic resonance images (fMRI were acquired on a 1.5T Philips Intera scanner using a TR of 2.55 s. Videotaped mother-infant interactions were systematically evaluated blind to family information to generate behavioural measures for correlational analysis. RESULTS: Enhanced blood oxygenation functional imaging responses were found in the own versus unknown infant contrast in the bilateral precuneus, right superior temporal gyrus, right medial and left middle frontal gyri and left amygdala. Positive mother-infant interaction (less directive parent behaviour; more positive/attentive infant behaviour was significantly associated with greater activation in several regions on viewing own versus unknown infant, particularly the middle frontal gyrus. Mothers' perceived warmth of her infant was correlated with activations in the same contrast, particularly in sensory and visual areas. CONCLUSION: This study partially replicates previous reports of the brain regions activated in mothers in response to the visual presentation of their own infant. It is the first to report associations between mothers' unique neural responses to viewing their own infant with the quality of her concurrent behaviour when

  2. The neural basis of academic achievement motivation.

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    Mizuno, Kei; Tanaka, Masaaki; Ishii, Akira; Tanabe, Hiroki C; Onoe, Hirotaka; Sadato, Norihiro; Watanabe, Yasuyoshi

    2008-08-01

    We have used functional magnetic resonance imaging to study the neural correlates of motivation, concentrating on the motivation to learn and gain monetary rewards. We compared the activation in the brain obtained during reported high states of motivation for learning, with the ones observed when the motivation was based on monetary reward. Our results show that motivation to learn correlates with bilateral activity in the putamen, and that the higher the reported motivation, as derived from a questionnaire that each subject filled prior to scanning, the greater the change in the BOLD signals within the putamen. Monetary motivation also activated the putamen bilaterally, though the intensity of activity was not related to the monetary reward. We conclude that the putamen is critical for motivation in different domains and the extent of activity of the putamen may be pivotal to the motivation that drives academic achievement and thus academic successes.

  3. The neural basis of monitoring goal progress

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    Yael eBenn

    2014-09-01

    Full Text Available The neural basis of progress monitoring has received relatively little attention compared to other sub-processes that are involved in goal directed behavior such as motor control and response inhibition. Studies of error-monitoring have identified the dorsal anterior cingulate cortex (dACC as a structure that is sensitive to conflict detection, and triggers corrective action. However, monitoring goal progress involves monitoring correct as well as erroneous events over a period of time. In the present research, 20 healthy participants underwent fMRI while playing a game that involved monitoring progress towards either a numerical or a visuo-spatial target. The findings confirmed the role of the dACC in detecting situations in which the current state may conflict with the desired state, but also revealed activations in the frontal and parietal regions, pointing to the involvement of processes such as attention and working memory in monitoring progress over time. In addition, activation of the cuneus was associated with monitoring progress towards a specific target presented in the visual modality. This is the first time that activation in this region has been linked to higher-order processing of goal-relevant information, rather than low-level anticipation of visual stimuli. Taken together, these findings identify the neural substrates involved in monitoring progress over time, and how these extend beyond activations observed in conflict and error monitoring.

  4. The neural basis of human tool use

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    Guy A Orban

    2014-04-01

    Full Text Available In this review, we propose that the neural basis for the spontaneous, diversified human tool use is an area devoted to the execution and observation of tool actions, located in the left anterior supramarginal gyrus (aSMG. The aSMG activation elicited by observing tool use is typical of human subjects, as macaques show no similar activation, even after an extensive training to use tools. The execution of tool actions, as well as their observation, requires the convergence upon aSMG of inputs from different parts of the dorsal and ventral visual streams. Non semantic features of the target object may be provided by the posterior parietal cortex (PPC for tool-object interaction, paralleling the well-known PPC input to AIP for hand-object interaction. Semantic information regarding tool identity, and knowledge of the typical manner of handling the tool, could be provided by inferior and middle regions of the temporal lobe. Somatosensory feedback and technical reasoning, as well as motor and intentional constraints also play roles during the planning of tool actions and consequently their signals likewise converge upon aSMG.We further propose that aSMG may have arisen though duplication of monkey AIP and invasion of the duplicate area by afferents from PPC providing distinct signals depending on the kinematics of the manipulative action. This duplication may have occurred when Homo Habilis or Homo Erectus emerged, generating the Oldowan or Acheulean Industrial complexes respectively. Hence tool use may have emerged during hominid evolution between bipedalism and language.We conclude that humans have two parietal systems involved in tool behavior: a biological circuit for grasping objects, including tools, and an artifactual system devoted specifically to tool use. Only the latter allows humans to understand the causal relationship between tool use and obtaining the goal, and is likely to be the basis of all technological developments.

  5. Toward a neural basis for social behavior.

    Science.gov (United States)

    Stanley, Damian A; Adolphs, Ralph

    2013-10-30

    Nearly 25 years ago, the shared interests of psychologists and biologists in understanding the neural basis of social behavior led to the inception of social neuroscience. In the past decade, this field has exploded, in large part due to the infusion of studies that use fMRI. At the same time, tensions have arisen about how to prioritize a diverse range of questions and about the authority of neurobiological data in answering them. The field is now poised to tackle some of the most interesting and important questions about human and animal behavior but at the same time faces uncertainty about how to achieve focus in its research and cohesion among the scientists who tackle it. The next 25 years offer the opportunity to alleviate some of these growing pains, as well as the challenge of answering large questions that encompass the nature and bounds of diverse social interactions (in humans, including interactions through the internet); how to characterize, and treat, social dysfunction in psychiatric illness; and how to compare social cognition in humans with that in other animals. Copyright © 2013 Elsevier Inc. All rights reserved.

  6. Neuronal spike sorting based on radial basis function neural networks

    Directory of Open Access Journals (Sweden)

    Taghavi Kani M

    2011-02-01

    Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.

  7. Application of radial basis neural network for state estimation of ...

    African Journals Online (AJOL)

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    An original application of radial basis function (RBF) neural network for power system state estimation is proposed in this paper. The property of massive parallelism of neural networks is employed for this. The application of RBF neural network for state estimation is investigated by testing its applicability on a IEEE 14 bus ...

  8. The neural basis of task switching changes with skill acquisition.

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    Jimura, Koji; Cazalis, Fabienne; Stover, Elena R S; Poldrack, Russell A

    2014-01-01

    Learning novel skills involves reorganization and optimization of cognitive processing involving a broad network of brain regions. Previous work has shown asymmetric costs of switching to a well-trained task vs. a poorly-trained task, but the neural basis of these differential switch costs is unclear. The current study examined the neural signature of task switching in the context of acquisition of new skill. Human participants alternated randomly between a novel visual task (mirror-reversed word reading) and a highly practiced one (plain word reading), allowing the isolation of task switching and skill set maintenance. Two scan sessions were separated by 2 weeks, with behavioral training on the mirror reading task in between the two sessions. Broad cortical regions, including bilateral prefrontal, parietal, and extrastriate cortices, showed decreased activity associated with learning of the mirror reading skill. In contrast, learning to switch to the novel skill was associated with decreased activity in a focal subcortical region in the dorsal striatum. Switching to the highly practiced task was associated with a non-overlapping set of regions, suggesting substantial differences in the neural substrates of switching as a function of task skill. Searchlight multivariate pattern analysis also revealed that learning was associated with decreased pattern information for mirror vs. plain reading tasks in fronto-parietal regions. Inferior frontal junction and posterior parietal cortex showed a joint effect of univariate activation and pattern information. These results suggest distinct learning mechanisms task performance and executive control as a function of learning.

  9. The neural basis of task switching changes with skill acquisition

    Directory of Open Access Journals (Sweden)

    Koji eJimura

    2014-05-01

    Full Text Available Learning novel skills involves reorganization and optimization of cognitive processing involving a broad network of brain regions. Previous work has shown asymmetric costs of switching to a well-trained task versus a poorly-trained task, but the neural basis of these differential switch costs is unclear. The current study examined the neural signature of task switching in the context of acquisition of new skill. Human participants alternated randomly between a novel visual task (mirror-reversed word reading and a highly practiced one (plain word reading, allowing the isolation of task switching and skill set maintenance. Two scan sessions were separated by two weeks, with behavioral training on the mirror reading task in between the two sessions. Broad cortical regions, including bilateral prefrontal, parietal, and extrastriate cortices, showed decreased activity associated with learning of the mirror reading skill. In contrast, learning to switch to the novel skill was associated with decreased activity in a focal subcortical region in the dorsal striatum. Switching to the highly practiced task was associated with a non-overlapping set of regions, suggesting substantial differences in the neural substrates of switching as a function of task skill. Searchlight multivariate pattern analysis also revealed that learning was associated with decreased pattern information for mirror versus plain reading tasks in fronto-parietal regions. Inferior frontal junction and posterior parietal cortex showed a joint effect of univariate activation and pattern information. These results suggest distinct learning mechanisms task performance and executive control as a function of learning.

  10. On supertaskers and the neural basis of efficient multitasking.

    Science.gov (United States)

    Medeiros-Ward, Nathan; Watson, Jason M; Strayer, David L

    2015-06-01

    The present study used brain imaging to determine the neural basis of individual differences in multitasking, the ability to successfully perform at least two attention-demanding tasks at once. Multitasking is mentally taxing and, therefore, should recruit the prefrontal cortex to maintain task goals when coordinating attentional control and managing the cognitive load. To investigate this possibility, we used functional neuroimaging to assess neural activity in both extraordinary multitaskers (Supertaskers) and control subjects who were matched on working memory capacity. Participants performed a challenging dual N-back task in which auditory and visual stimuli were presented simultaneously, requiring independent and continuous maintenance, updating, and verification of the contents of verbal and spatial working memory. With the task requirements and considerable cognitive load that accompanied increasing N-back, relative to the controls, the multitasking of Supertaskers was characterized by more efficient recruitment of anterior cingulate and posterior frontopolar prefrontal cortices. Results are interpreted using neuropsychological and evolutionary perspectives on individual differences in multitasking ability and the neural correlates of attentional control.

  11. Linguistic Effects on the Neural Basis of Theory of Mind

    Science.gov (United States)

    Frank, C. Kobayashi

    2010-01-01

    “Theory of mind” (ToM) has been described as the ability to attribute and understand other people’s desires and intentions as distinct from one’s own. There has been a debate about the extent to which language influences ToM development. Although very few studies directly examined linguistic influence on the neural basis of ToM, results from these studies indicate at least moderate influence of language on ToM. In this review both behavioral and neurological studies that examined the relationship between language and ToM are selectively discussed. This review focuses on cross-linguistic / cultural studies (especially Japanese vs. American / English) since my colleagues and I found evidence of significant linguistic influence on the neural basis of ToM through a series of functional brain imaging experiments. Evidence from both behavioral and neurological studies of ToM (including ours) suggests that the pragmatic (not the constitutive) aspects of language influence ToM understanding more significantly. PMID:21113278

  12. Neural prostheses and brain plasticity

    Science.gov (United States)

    Fallon, James B.; Irvine, Dexter R. F.; Shepherd, Robert K.

    2009-12-01

    The success of modern neural prostheses is dependent on a complex interplay between the devices' hardware and software and the dynamic environment in which the devices operate: the patient's body or 'wetware'. Over 120 000 severe/profoundly deaf individuals presently receive information enabling auditory awareness and speech perception from cochlear implants. The cochlear implant therefore provides a useful case study for a review of the complex interactions between hardware, software and wetware, and of the important role of the dynamic nature of wetware. In the case of neural prostheses, the most critical component of that wetware is the central nervous system. This paper will examine the evidence of changes in the central auditory system that contribute to changes in performance with a cochlear implant, and discuss how these changes relate to electrophysiological and functional imaging studies in humans. The relationship between the human data and evidence from animals of the remarkable capacity for plastic change of the central auditory system, even into adulthood, will then be examined. Finally, we will discuss the role of brain plasticity in neural prostheses in general.

  13. The neural basis of testable and non-testable beliefs.

    Directory of Open Access Journals (Sweden)

    Jonathon R Howlett

    Full Text Available Beliefs about the state of the world are an important influence on both normal behavior and psychopathology. However, understanding of the neural basis of belief processing remains incomplete, and several aspects of belief processing have only recently been explored. Specifically, different types of beliefs may involve fundamentally different inferential processes and thus recruit distinct brain regions. Additionally, neural processing of truth and falsity may differ from processing of certainty and uncertainty. The purpose of this study was to investigate the neural underpinnings of assessment of testable and non-testable propositions in terms of truth or falsity and the level of certainty in a belief. Functional magnetic resonance imaging (fMRI was used to study 14 adults while they rated propositions as true or false and also rated the level of certainty in their judgments. Each proposition was classified as testable or non-testable. Testable propositions activated the DLPFC and posterior cingulate cortex, while non-testable statements activated areas including inferior frontal gyrus, superior temporal gyrus, and an anterior region of the superior frontal gyrus. No areas were more active when a proposition was accepted, while the dorsal anterior cingulate was activated when a proposition was rejected. Regardless of whether a proposition was testable or not, certainty that the proposition was true or false activated a common network of regions including the medial prefrontal cortex, caudate, posterior cingulate, and a region of middle temporal gyrus near the temporo-parietal junction. Certainty in the truth or falsity of a non-testable proposition (a strong belief without empirical evidence activated the insula. The results suggest that different brain regions contribute to the assessment of propositions based on the type of content, while a common network may mediate the influence of beliefs on motivation and behavior based on the level of

  14. The Neural Basis of Deception in Strategic Interactions

    Directory of Open Access Journals (Sweden)

    Kirsten G Volz

    2015-02-01

    Full Text Available Communication based on informational asymmetries abounds in politics, business, and almost any other form of social interaction. Informational asymmetries may create incentives for the better-informed party to exploit her advantage by misrepresenting information. Using a game-theoretic setting, we investigate the neural basis of deception in human interaction. Unlike in most previous fMRI research on deception, the participants decide themselves whether to lie or not. We find activation within the right temporo-parietal junction (rTPJ, the dorsal anterior cingulate cortex (ACC, the (precuneus (CUN, and the anterior frontal gyrus (aFG when contrasting lying with truth telling. Notably, our design also allows for an investigation of the neural foundations of sophisticated deception through telling the truth—when the sender does not expect the receiver to believe her (true message. Sophisticated deception triggers activation within the same network as plain lies, i.e., we find activity within the rTPJ, the CUN, and aFG. We take this result to show that brain activation can reveal the sender’s veridical intention to deceive others, irrespective of whether in fact the sender utters the factual truth or not.

  15. Bilinguals at the "cocktail party": dissociable neural activity in auditory-linguistic brain regions reveals neurobiological basis for nonnative listeners' speech-in-noise recognition deficits.

    Science.gov (United States)

    Bidelman, Gavin M; Dexter, Lauren

    2015-04-01

    We examined a consistent deficit observed in bilinguals: poorer speech-in-noise (SIN) comprehension for their nonnative language. We recorded neuroelectric mismatch potentials in mono- and bi-lingual listeners in response to contrastive speech sounds in noise. Behaviorally, late bilinguals required ∼10dB more favorable signal-to-noise ratios to match monolinguals' SIN abilities. Source analysis of cortical activity demonstrated monotonic increase in response latency with noise in superior temporal gyrus (STG) for both groups, suggesting parallel degradation of speech representations in auditory cortex. Contrastively, we found differential speech encoding between groups within inferior frontal gyrus (IFG)-adjacent to Broca's area-where noise delays observed in nonnative listeners were offset in monolinguals. Notably, brain-behavior correspondences double dissociated between language groups: STG activation predicted bilinguals' SIN, whereas IFG activation predicted monolinguals' performance. We infer higher-order brain areas act compensatorily to enhance impoverished sensory representations but only when degraded speech recruits linguistic brain mechanisms downstream from initial auditory-sensory inputs. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Exploring the neural basis of real-life joint action: measuring brain activation during joint table setting with functional near-infrared spectroscopy (fNIRS

    Directory of Open Access Journals (Sweden)

    Johanna eEgetemeir

    2011-09-01

    Full Text Available Many everyday life situations require two or more individuals to execute actions together. Assessing brain activation during naturalistic tasks to uncover relevant processes underlying such real-life joint action situations has remained a methodological challenge. In the present study, we introduce a novel joint action paradigm that enables the assessment of brain activation during real-life joint action tasks using functional near-infrared spectroscopy (fNIRS. We monitored brain activation of participants who coordinated complex actions with a partner sitting opposite them. Participants performed table-setting tasks, either alone (solo action or in cooperation with a partner (joint action, or they observed the partner performing the task (action observation. Comparing joint action and solo action revealed stronger activation (higher [oxy-Hb]-concentration during joint action in a number of areas. Among these were areas in the inferior parietal lobule (IPL that additionally showed an overlap of activation during action observation and solo action. Areas with such a close link between action observation and action execution have been associated with action simulation processes. The magnitude of activation in these IPL areas also varied according to joint action type and its respective demand on action simulation. The results validate fNIRS as an imaging technique for exploring the functional correlates of interindividual action coordination in real-life settings and suggest that coordinating actions in real-life situations requires simulating the actions of the partner.

  17. Neural Basis of Tics: A Functional MRI Study

    OpenAIRE

    J Gordon Millichap

    2006-01-01

    Event-related functional MRI (fMRI) was used to study the neural basis of spontaneous motor and vocal tics in 10 patients with Tourette syndrome, at the National Institute of Neurological Disorders and Stroke, Bethesda, MD.

  18. Insights into the neural basis of response inhibition from cognitive and clinical neuroscience.

    Science.gov (United States)

    Chambers, Christopher D; Garavan, Hugh; Bellgrove, Mark A

    2009-05-01

    Neural mechanisms of cognitive control enable us to initiate, coordinate and update behaviour. Central to successful control is the ability to suppress actions that are no longer relevant or required. In this article, we review the contribution of cognitive neuroscience, molecular genetics and clinical investigations to understanding how response inhibition is mediated in the human brain. In Section 1, we consider insights into the neural basis of inhibitory control from the effects of neural interference, neural dysfunction, and drug addiction. In Section 2, we explore the functional specificity of inhibitory mechanisms among a range of related processes, including response selection, working memory, and attention. In Section 3, we focus on the contribution of response inhibition to understanding flexible behaviour, including the effects of learning and individual differences. Finally, in Section 4, we propose a series of technical and conceptual objectives for future studies addressing the neural basis of inhibition.

  19. Neural basis of multisensory looming signals.

    Science.gov (United States)

    Tyll, Sascha; Bonath, Björn; Schoenfeld, Mircea Ariel; Heinze, Hans-Jochen; Ohl, Frank W; Noesselt, Tömme

    2013-01-15

    Approaching or looming signals are often related to extremely relevant environmental events (e.g. threats or collisions) making these signals critical for survival. However, the neural network underlying multisensory looming processing is not yet fully understood. Using functional magnetic resonance imaging (fMRI) we identified the neural correlates of audiovisual looming processing in humans: audiovisual looming (vs. receding) signals enhance fMRI-responses in low-level visual and auditory areas plus multisensory cortex (superior temporal sulcus; plus parietal and frontal structures). When characterizing the fMRI-response profiles for multisensory looming stimuli, we found significant enhancements relative to the mean and maximum of unisensory responses in looming-sensitive visual and auditory cortex plus STS. Superadditive enhancements were observed in visual cortex. Subject-specific region-of-interest analyses further revealed superadditive response profiles within all sensory-specific looming-sensitive structures plus bilateral STS for audiovisual looming vs. summed unisensory looming conditions. Finally, we observed enhanced connectivity of bilateral STS with low-level visual areas in the context of looming processing. This enhanced coupling of STS with unisensory regions might potentially serve to enhance the salience of unisensory stimulus features and is accompanied by superadditive fMRI-responses. We suggest that this preference in neural signaling for looming stimuli effectively informs animals to avoid potential threats or collisions. Copyright © 2012 Elsevier Inc. All rights reserved.

  20. Neural repair in the adult brain

    Science.gov (United States)

    Jessberger, Sebastian

    2016-01-01

    Acute or chronic injury to the adult brain often results in substantial loss of neural tissue and subsequent permanent functional impairment. Over the last two decades, a number of approaches have been developed to harness the regenerative potential of neural stem cells and the existing fate plasticity of neural cells in the nervous system to prevent tissue loss or to enhance structural and functional regeneration upon injury. Here, we review recent advances of stem cell-associated neural repair in the adult brain, discuss current challenges and limitations, and suggest potential directions to foster the translation of experimental stem cell therapies into the clinic. PMID:26918167

  1. Testing for a cultural influence on reading for meaning in the developing brain: the neural basis of semantic processing in Chinese children

    Directory of Open Access Journals (Sweden)

    Tai-Li Chou

    2009-11-01

    Full Text Available Functional magnetic resonance imaging (fMRI was used to explore the neural correlates of semantic judgments in a group of 8- to 15-year-old Chinese children. Participants were asked to indicate if pairs of Chinese characters presented visually were related in meaning. The related pairs were arranged in a continuous variable according to association strength. Pairs of characters with weaker semantic association elicited greater activation in the mid ventral region (BA 45 of left inferior frontal gyrus, suggesting increased demands on the process of selecting appropriate semantic features. By contrast, characters with stronger semantic association elicited greater activation in left inferior parietal lobule (BA 39, suggesting stronger integration of highly related features. In addition, there was a developmental increase, similar to previously reported findings in English, in left posterior middle temporal gyrus (BA 21, suggesting that older children have more elaborated semantic representations. There were additional age-related increases in the posterior region of left inferior parietal lobule and in the ventral regions of left inferior frontal gyrus, suggesting that reading acquisition relies more on the mapping from orthography to semantics in Chinese children as compared to previously reported findings in English.

  2. The Molecular Basis of Human Brain Evolution.

    Science.gov (United States)

    Enard, Wolfgang

    2016-10-24

    Humans are a remarkable species, especially because of the remarkable properties of their brain. Since the split from the chimpanzee lineage, the human brain has increased three-fold in size and has acquired abilities for vocal learning, language and intense cooperation. To better understand the molecular basis of these changes is of great biological and biomedical interest. However, all the about 16 million fixed genetic changes that occurred during human evolution are fully correlated with all molecular, cellular, anatomical and behavioral changes that occurred during this time. Hence, as humans and chimpanzees cannot be crossed or genetically manipulated, no direct evidence for linking particular genetic and molecular changes to human brain evolution can be obtained. Here, I sketch a framework how indirect evidence can be obtained and review findings related to the molecular basis of human cognition, vocal learning and brain size. In particular, I discuss how a comprehensive comparative approach, leveraging cellular systems and genomic technologies, could inform the evolution of our brain in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Patterns recognition of electric brain activity using artificial neural networks

    Science.gov (United States)

    Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

    2017-04-01

    An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

  4. A Neural Basis of Facial Action Recognition in Humans.

    Science.gov (United States)

    Srinivasan, Ramprakash; Golomb, Julie D; Martinez, Aleix M

    2016-04-20

    By combining different facial muscle actions, called action units, humans can produce an extraordinarily large number of facial expressions. Computational models and studies in cognitive science and social psychology have long hypothesized that the brain needs to visually interpret these action units to understand other people's actions and intentions. Surprisingly, no studies have identified the neural basis of the visual recognition of these action units. Here, using functional magnetic resonance imaging and an innovative machine learning analysis approach, we identify a consistent and differential coding of action units in the brain. Crucially, in a brain region thought to be responsible for the processing of changeable aspects of the face, multivoxel pattern analysis could decode the presence of specific action units in an image. This coding was found to be consistent across people, facilitating the estimation of the perceived action units on participants not used to train the multivoxel decoder. Furthermore, this coding of action units was identified when participants attended to the emotion category of the facial expression, suggesting an interaction between the visual analysis of action units and emotion categorization as predicted by the computational models mentioned above. These results provide the first evidence for a representation of action units in the brain and suggest a mechanism for the analysis of large numbers of facial actions and a loss of this capacity in psychopathologies. Computational models and studies in cognitive and social psychology propound that visual recognition of facial expressions requires an intermediate step to identify visible facial changes caused by the movement of specific facial muscles. Because facial expressions are indeed created by moving one's facial muscles, it is logical to assume that our visual system solves this inverse problem. Here, using an innovative machine learning method and neuroimaging data, we identify

  5. Mammalian empathy: behavioural manifestations and neural basis.

    Science.gov (United States)

    de Waal, Frans B M; Preston, Stephanie D

    2017-08-01

    Recent research on empathy in humans and other mammals seeks to dissociate emotional and cognitive empathy. These forms, however, remain interconnected in evolution, across species and at the level of neural mechanisms. New data have facilitated the development of empathy models such as the perception-action model (PAM) and mirror-neuron theories. According to the PAM, the emotional states of others are understood through personal, embodied representations that allow empathy and accuracy to increase based on the observer's past experiences. In this Review, we discuss the latest evidence from studies carried out across a wide range of species, including studies on yawn contagion, consolation, aid-giving and contagious physiological affect, and we summarize neuroscientific data on representations related to another's state.

  6. Neural Basis of Video Gaming: A Systematic Review

    OpenAIRE

    Marc Palaus; Marron, Elena M.; Raquel Viejo-Sobera; Diego Redolar-Ripoll

    2017-01-01

    Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video ga...

  7. Neural Basis of Video Gaming: A Systematic Review

    OpenAIRE

    Palaus, Marc; Marron, Elena M.; Viejo-Sobera, Raquel; Redolar-Ripoll, Diego

    2017-01-01

    Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games. We aim ...

  8. The shared neural basis of music and language.

    Science.gov (United States)

    Yu, Mengxia; Xu, Miao; Li, Xueting; Chen, Zhencai; Song, Yiying; Liu, Jia

    2017-08-15

    Human musical ability is proposed to play a key phylogenetical role in the evolution of language, and the similarity of hierarchical structure in music and language has led to considerable speculation about their shared mechanisms. While behavioral and electrophysioglocial studies have revealed associations between music and linguistic abilities, results from functional magnetic resonance imaging (fMRI) studies on their relations are contradictory, possibly because these studies usually treat music or language as single entities without breaking down to their components. Here, we examined the relations between different components of music (i.e., melodic and rhythmic analysis) and language (i.e., semantic and phonological processing) using both behavioral tests and resting-state fMRI. Behaviorally, we found that individuals with music training experiences were better at semantic processing, but not at phonological processing, than those without training. Further correlation analyses showed that semantic processing of language was related to melodic, but not rhythmic, analysis of music. Neurally, we found that performances in both semantic processing and melodic analysis were correlated with spontaneous brain activities in the bilateral precentral gyrus (PCG) and superior temporal plane at the regional level, and with the resting-state functional connectivity of the left PCG with the left supramarginal gyrus and left superior temporal gyrus at the network level. Together, our study revealed the shared spontaneous neural basis of music and language based on the behavioral link between melodic analysis and semantic processing, which possibly relied on a common mechanism of automatic auditory-motor integration. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  9. Neural Basis of Strategic Decision Making.

    Science.gov (United States)

    Lee, Daeyeol; Seo, Hyojung

    2016-01-01

    Human choice behaviors during social interactions often deviate from the predictions of game theory. This might arise partly from the limitations in the cognitive abilities necessary for recursive reasoning about the behaviors of others. In addition, during iterative social interactions, choices might change dynamically as knowledge about the intentions of others and estimates for choice outcomes are incrementally updated via reinforcement learning. Some of the brain circuits utilized during social decision making might be general-purpose and contribute to isomorphic individual and social decision making. By contrast, regions in the medial prefrontal cortex (mPFC) and temporal parietal junction (TPJ) might be recruited for cognitive processes unique to social decision making. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Identifying Emotions on the Basis of Neural Activation.

    Directory of Open Access Journals (Sweden)

    Karim S Kassam

    Full Text Available We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1 neural activation of the same individual in other trials, 2 neural activation of other individuals who experienced similar trials, and 3 neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing.

  11. Brain basis of communicative actions in language.

    Science.gov (United States)

    Egorova, Natalia; Shtyrov, Yury; Pulvermüller, Friedemann

    2016-01-15

    Although language is a key tool for communication in social interaction, most studies in the neuroscience of language have focused on language structures such as words and sentences. Here, the neural correlates of speech acts, that is, the actions performed by using language, were investigated with functional magnetic resonance imaging (fMRI). Participants were shown videos, in which the same critical utterances were used in different communicative contexts, to Name objects, or to Request them from communication partners. Understanding of critical utterances as Requests was accompanied by activation in bilateral premotor, left inferior frontal and temporo-parietal cortical areas known to support action-related and social interactive knowledge. Naming, however, activated the left angular gyrus implicated in linking information about word forms and related reference objects mentioned in critical utterances. These findings show that understanding of utterances as different communicative actions is reflected in distinct brain activation patterns, and thus suggest different neural substrates for different speech act types. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  12. The neural basis of human dance.

    Science.gov (United States)

    Brown, Steven; Martinez, Michael J; Parsons, Lawrence M

    2006-08-01

    Human dance was investigated with positron emission tomography to identify its systems-level organization. Three core aspects of dance were examined: entrainment, meter and patterned movement. Amateur dancers performed small-scale, cyclically repeated tango steps on an inclined surface to the beat of tango music, without visual guidance. Entrainment of dance steps to music, compared to self-pacing of movement, was supported by anterior cerebellar vermis. Movement to a regular, metric rhythm, compared to movement to an irregular rhythm, implicated the right putamen in the voluntary control of metric motion. Spatial navigation of leg movement during dance, when controlling for muscle contraction, activated the medial superior parietal lobule, reflecting proprioceptive and somatosensory contributions to spatial cognition in dance. Finally, additional cortical, subcortical and cerebellar regions were active at the systems level. Consistent with recent work on simpler, rhythmic, motor-sensory behaviors, these data reveal the interacting network of brain areas active during spatially patterned, bipedal, rhythmic movements that are integrated in dance.

  13. Neural basis of nonanalytical reasoning expertise during clinical evaluation.

    Science.gov (United States)

    Durning, Steven J; Costanzo, Michelle E; Artino, Anthony R; Graner, John; van der Vleuten, Cees; Beckman, Thomas J; Wittich, Christopher M; Roy, Michael J; Holmboe, Eric S; Schuwirth, Lambert

    2015-03-01

    Understanding clinical reasoning is essential for patient care and medical education. Dual-processing theory suggests that nonanalytic reasoning is an essential aspect of expertise; however, assessing nonanalytic reasoning is challenging because it is believed to occur on the subconscious level. This assumption makes concurrent verbal protocols less reliable assessment tools. Functional magnetic resonance imaging was used to explore the neural basis of nonanalytic reasoning in internal medicine interns (novices) and board-certified staff internists (experts) while completing United States Medical Licensing Examination and American Board of Internal Medicine multiple-choice questions. The results demonstrated that novices and experts share a common neural network in addition to nonoverlapping neural resources. However, experts manifested greater neural processing efficiency in regions such as the prefrontal cortex during nonanalytical reasoning. These findings reveal a multinetwork system that supports the dual-process mode of expert clinical reasoning during medical evaluation.

  14. Radial basis function neural network in fault detection of automotive ...

    African Journals Online (AJOL)

    Radial basis function neural network in fault detection of automotive engines. Adnan Hamad, Dingli Yu, JB Gomm, Mahavir S Sangha. Abstract. Fault detection and isolation have become one of the most important aspects of automobile design. A fault detection (FD) scheme is developed for automotive engines in this paper.

  15. Neural basis of scientific innovation induced by heuristic prototype.

    Science.gov (United States)

    Luo, Junlong; Li, Wenfu; Qiu, Jiang; Wei, Dongtao; Liu, Yijun; Zhang, Qinlin

    2013-01-01

    A number of major inventions in history have been based on bionic imitation. Heuristics, by applying biological systems to the creation of artificial devices and machines, might be one of the most critical processes in scientific innovation. In particular, prototype heuristics propositions that innovation may engage automatic activation of a prototype such as a biological system to form novel associations between a prototype's function and problem-solving. We speculated that the cortical dissociation between the automatic activation and forming novel associations in innovation is critical point to heuristic creativity. In the present study, novel and old scientific innovations (NSI and OSI) were selected as experimental materials in using learning-testing paradigm to explore the neural basis of scientific innovation induced by heuristic prototype. College students were required to resolve NSI problems (to which they did not know the answers) and OSI problems (to which they knew the answers). From two fMRI experiments, our results showed that the subjects could resolve NSI when provided with heuristic prototypes. In Experiment 1, it was found that the lingual gyrus (LG; BA18) might be related to prototype heuristics in college students resolving NSI after learning a relative prototype. In Experiment 2, the LG (BA18) and precuneus (BA31) were significantly activated for NSI compared to OSI when college students learned all prototypes one day before the test. In addition, the mean beta-values of these brain regions of NSI were all correlated with the behavior accuracy of NSI. As our hypothesis indicated, the findings suggested that the LG might be involved in forming novel associations using heuristic information, while the precuneus might be involved in the automatic activation of heuristic prototype during scientific innovation.

  16. Neural basis of scientific innovation induced by heuristic prototype.

    Directory of Open Access Journals (Sweden)

    Junlong Luo

    Full Text Available A number of major inventions in history have been based on bionic imitation. Heuristics, by applying biological systems to the creation of artificial devices and machines, might be one of the most critical processes in scientific innovation. In particular, prototype heuristics propositions that innovation may engage automatic activation of a prototype such as a biological system to form novel associations between a prototype's function and problem-solving. We speculated that the cortical dissociation between the automatic activation and forming novel associations in innovation is critical point to heuristic creativity. In the present study, novel and old scientific innovations (NSI and OSI were selected as experimental materials in using learning-testing paradigm to explore the neural basis of scientific innovation induced by heuristic prototype. College students were required to resolve NSI problems (to which they did not know the answers and OSI problems (to which they knew the answers. From two fMRI experiments, our results showed that the subjects could resolve NSI when provided with heuristic prototypes. In Experiment 1, it was found that the lingual gyrus (LG; BA18 might be related to prototype heuristics in college students resolving NSI after learning a relative prototype. In Experiment 2, the LG (BA18 and precuneus (BA31 were significantly activated for NSI compared to OSI when college students learned all prototypes one day before the test. In addition, the mean beta-values of these brain regions of NSI were all correlated with the behavior accuracy of NSI. As our hypothesis indicated, the findings suggested that the LG might be involved in forming novel associations using heuristic information, while the precuneus might be involved in the automatic activation of heuristic prototype during scientific innovation.

  17. The neural basis of visual selective attention: a commentary on Harter and Aine.

    Science.gov (United States)

    Hillyard, S A; Mangun, G R

    1986-12-01

    Harter and Aine (1984) have proposed a 'neural specificity' model of visual selective attention, based primarily on evidence from recordings of event-related brain potentials (ERPs) in human subjects. In this framework, they consider ERP components elicited during visual-spatial attention to reflect selective neural processing in the tectopulvinar-partietal pathway, whereas selection of visual attributes such as pattern, color, and orientation is manifested by ERPs arising from the geniculostriate-inferotemporal projection system. The present article examines the empirical basis for anatomically-specific hypotheses and considers alternative explanations for the observed ERP changes during selective attention.

  18. The neural basis of body form and body action agnosia.

    Science.gov (United States)

    Moro, Valentina; Urgesi, Cosimo; Pernigo, Simone; Lanteri, Paola; Pazzaglia, Mariella; Aglioti, Salvatore Maria

    2008-10-23

    Visual analysis of faces and nonfacial body stimuli brings about neural activity in different cortical areas. Moreover, processing body form and body action relies on distinct neural substrates. Although brain lesion studies show specific face processing deficits, neuropsychological evidence for defective recognition of nonfacial body parts is lacking. By combining psychophysics studies with lesion-mapping techniques, we found that lesions of ventromedial, occipitotemporal areas induce face and body recognition deficits while lesions involving extrastriate body area seem causatively associated with impaired recognition of body but not of face and object stimuli. We also found that body form and body action recognition deficits can be double dissociated and are causatively associated with lesions to extrastriate body area and ventral premotor cortex, respectively. Our study reports two category-specific visual deficits, called body form and body action agnosia, and highlights their neural underpinnings.

  19. The Neural Basis of Typewriting: A Functional MRI Study.

    Directory of Open Access Journals (Sweden)

    Yuichi Higashiyama

    Full Text Available To investigate the neural substrate of typewriting Japanese words and to detect the difference between the neural substrate of typewriting and handwriting, we conducted a functional magnetic resonance imaging (fMRI study in 16 healthy volunteers. All subjects were skillful touch typists and performed five tasks: a typing task, a writing task, a reading task, and two control tasks. Three brain regions were activated during both the typing and the writing tasks: the left superior parietal lobule, the left supramarginal gyrus, and the left premotor cortex close to Exner's area. Although typing and writing involved common brain regions, direct comparison between the typing and the writing task revealed greater left posteromedial intraparietal cortex activation in the typing task. In addition, activity in the left premotor cortex was more rostral in the typing task than in the writing task. These findings suggest that, although the brain circuits involved in Japanese typewriting are almost the same as those involved in handwriting, there are brain regions that are specific for typewriting.

  20. Neural Basis of Video Gaming: A Systematic Review

    Science.gov (United States)

    Palaus, Marc; Marron, Elena M.; Viejo-Sobera, Raquel; Redolar-Ripoll, Diego

    2017-01-01

    Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games. Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass. Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games. Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14% focused on video game related violence. Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies. PMID:28588464

  1. Neural Basis of Video Gaming: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Marc Palaus

    2017-05-01

    Full Text Available Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games.Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass.Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games.Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14% focused on video game related violence.Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies.

  2. Neural Basis of Video Gaming: A Systematic Review.

    Science.gov (United States)

    Palaus, Marc; Marron, Elena M; Viejo-Sobera, Raquel; Redolar-Ripoll, Diego

    2017-01-01

    Background: Video gaming is an increasingly popular activity in contemporary society, especially among young people, and video games are increasing in popularity not only as a research tool but also as a field of study. Many studies have focused on the neural and behavioral effects of video games, providing a great deal of video game derived brain correlates in recent decades. There is a great amount of information, obtained through a myriad of methods, providing neural correlates of video games. Objectives: We aim to understand the relationship between the use of video games and their neural correlates, taking into account the whole variety of cognitive factors that they encompass. Methods: A systematic review was conducted using standardized search operators that included the presence of video games and neuro-imaging techniques or references to structural or functional brain changes. Separate categories were made for studies featuring Internet Gaming Disorder and studies focused on the violent content of video games. Results: A total of 116 articles were considered for the final selection. One hundred provided functional data and 22 measured structural brain changes. One-third of the studies covered video game addiction, and 14% focused on video game related violence. Conclusions: Despite the innate heterogeneity of the field of study, it has been possible to establish a series of links between the neural and cognitive aspects, particularly regarding attention, cognitive control, visuospatial skills, cognitive workload, and reward processing. However, many aspects could be improved. The lack of standardization in the different aspects of video game related research, such as the participants' characteristics, the features of each video game genre and the diverse study goals could contribute to discrepancies in many related studies.

  3. The Neural Basis of Social Influence in a Dictator Decision

    Directory of Open Access Journals (Sweden)

    Zhenyu Wei

    2017-12-01

    Full Text Available Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants’ decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing.

  4. The Neural Basis of Social Influence in a Dictator Decision.

    Science.gov (United States)

    Wei, Zhenyu; Zhao, Zhiying; Zheng, Yong

    2017-01-01

    Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants' decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing.

  5. Reformulated radial basis neural networks trained by gradient descent.

    Science.gov (United States)

    Karayiannis, N B

    1999-01-01

    This paper presents an axiomatic approach for constructing radial basis function (RBF) neural networks. This approach results in a broad variety of admissible RBF models, including those employing Gaussian RBF's. The form of the RBF's is determined by a generator function. New RBF models can be developed according to the proposed approach by selecting generator functions other than exponential ones, which lead to Gaussian RBF's. This paper also proposes a supervised learning algorithm based on gradient descent for training reformulated RBF neural networks constructed using the proposed approach. A sensitivity analysis of the proposed algorithm relates the properties of RBF's with the convergence of gradient descent learning. Experiments involving a variety of reformulated RBF networks generated by linear and exponential generator functions indicate that gradient descent learning is simple, easily implementable, and produces RBF networks that perform considerably better than conventional RBF models trained by existing algorithms.

  6. Neural basis of reinforcement learning and decision making.

    Science.gov (United States)

    Lee, Daeyeol; Seo, Hyojung; Jung, Min Whan

    2012-01-01

    Reinforcement learning is an adaptive process in which an animal utilizes its previous experience to improve the outcomes of future choices. Computational theories of reinforcement learning play a central role in the newly emerging areas of neuroeconomics and decision neuroscience. In this framework, actions are chosen according to their value functions, which describe how much future reward is expected from each action. Value functions can be adjusted not only through reward and penalty, but also by the animal's knowledge of its current environment. Studies have revealed that a large proportion of the brain is involved in representing and updating value functions and using them to choose an action. However, how the nature of a behavioral task affects the neural mechanisms of reinforcement learning remains incompletely understood. Future studies should uncover the principles by which different computational elements of reinforcement learning are dynamically coordinated across the entire brain.

  7. Neural Basis of Reinforcement Learning and Decision Making

    Science.gov (United States)

    Lee, Daeyeol; Seo, Hyojung; Jung, Min Whan

    2012-01-01

    Reinforcement learning is an adaptive process in which an animal utilizes its previous experience to improve the outcomes of future choices. Computational theories of reinforcement learning play a central role in the newly emerging areas of neuroeconomics and decision neuroscience. In this framework, actions are chosen according to their value functions, which describe how much future reward is expected from each action. Value functions can be adjusted not only through reward and penalty, but also by the animal’s knowledge of its current environment. Studies have revealed that a large proportion of the brain is involved in representing and updating value functions and using them to choose an action. However, how the nature of a behavioral task affects the neural mechanisms of reinforcement learning remains incompletely understood. Future studies should uncover the principles by which different computational elements of reinforcement learning are dynamically coordinated across the entire brain. PMID:22462543

  8. Logic Dynamics for Deductive Inference -- Its Stability and Neural Basis

    Science.gov (United States)

    Tsuda, Ichiro

    2014-12-01

    We propose a dynamical model that represents a process of deductive inference. We discuss the stability of logic dynamics and a neural basis for the dynamics. We propose a new concept of descriptive stability, thereby enabling a structure of stable descriptions of mathematical models concerning dynamic phenomena to be clarified. The present theory is based on the wider and deeper thoughts of John S. Nicolis. In particular, it is based on our joint paper on the chaos theory of human short-term memories with a magic number of seven plus or minus two.

  9. Neural and neurochemical basis of reinforcement-guided decision making.

    Science.gov (United States)

    Khani, Abbas; Rainer, Gregor

    2016-08-01

    Decision making is an adaptive behavior that takes into account several internal and external input variables and leads to the choice of a course of action over other available and often competing alternatives. While it has been studied in diverse fields ranging from mathematics, economics, ecology, and ethology to psychology and neuroscience, recent cross talk among perspectives from different fields has yielded novel descriptions of decision processes. Reinforcement-guided decision making models are based on economic and reinforcement learning theories, and their focus is on the maximization of acquired benefit over a defined period of time. Studies based on reinforcement-guided decision making have implicated a large network of neural circuits across the brain. This network includes a wide range of cortical (e.g., orbitofrontal cortex and anterior cingulate cortex) and subcortical (e.g., nucleus accumbens and subthalamic nucleus) brain areas and uses several neurotransmitter systems (e.g., dopaminergic and serotonergic systems) to communicate and process decision-related information. This review discusses distinct as well as overlapping contributions of these networks and neurotransmitter systems to the processing of decision making. We end the review by touching on neural circuitry and neuromodulatory regulation of exploratory decision making. Copyright © 2016 the American Physiological Society.

  10. Exploring the spatio-temporal neural basis of face learning.

    Science.gov (United States)

    Yang, Ying; Xu, Yang; Jew, Carol A; Pyles, John A; Kass, Robert E; Tarr, Michael J

    2017-06-01

    Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150-250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150-250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces.

  11. The neural basis of stereotypic impact on multiple social categorization.

    Science.gov (United States)

    Hehman, Eric; Ingbretsen, Zachary A; Freeman, Jonathan B

    2014-11-01

    Perceivers extract multiple social dimensions from another's face (e.g., race, emotion), and these dimensions can become linked due to stereotypes (e.g., Black individuals → angry). The current research examined the neural basis of detecting and resolving conflicts between top-down stereotypes and bottom-up visual information in person perception. Participants viewed faces congruent and incongruent with stereotypes, via variations in race and emotion, while neural activity was measured using fMRI. Hand movements en route to race/emotion responses were recorded using mouse-tracking to behaviorally index individual differences in stereotypical associations during categorization. The medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) showed stronger activation to faces that violated stereotypical expectancies at the intersection of multiple social categories (i.e., race and emotion). These regions were highly sensitive to the degree of incongruency, exhibiting linearly increasing responses as race and emotion became stereotypically more incongruent. Further, the ACC exhibited greater functional connectivity with the lateral fusiform cortex, a region implicated in face processing, when viewing stereotypically incongruent (relative to congruent) targets. Finally, participants with stronger behavioral tendencies to link race and emotion stereotypically during categorization showed greater dorsolateral prefrontal cortex activation to stereotypically incongruent targets. Together, the findings provide insight into how conflicting stereotypes at the nexus of multiple social dimensions are resolved at the neural level to accurately perceive other people. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Neural Plasticity and Neurorehabilitation: Teaching the New Brain Old Tricks

    Science.gov (United States)

    Kleim, Jeffrey A.

    2011-01-01

    Following brain injury or disease there are widespread biochemical, anatomical and physiological changes that result in what might be considered a new, very different brain. This adapted brain is forced to reacquire behaviors lost as a result of the injury or disease and relies on neural plasticity within the residual neural circuits. The same…

  13. Creating metaphors: The neural basis of figurative language production☆

    Science.gov (United States)

    Benedek, Mathias; Beaty, Roger; Jauk, Emanuel; Koschutnig, Karl; Fink, Andreas; Silvia, Paul J.; Dunst, Beate; Neubauer, Aljoscha C.

    2014-01-01

    Neuroscience research has thoroughly studied how nonliteral language is processed during metaphor comprehension. However, it is not clear how the brain actually creates nonliteral language. Therefore, the present study for the first time investigates the neural correlates of metaphor production. Participants completed sentences by generating novel metaphors or literal synonyms during functional imaging. Responses were spoken aloud in the scanner, recorded, and subsequently rated for their creative quality. We found that metaphor production was associated with focal activity in predominantly left-hemispheric brain regions, specifically the left angular gyrus, the left middle and superior frontal gyri—corresponding to the left dorsomedial prefrontal (DMPFC) cortex—and the posterior cingulate cortex. Moreover, brain activation in the left anterior DMPFC and the right middle temporal gyrus was found to linearly increase with the creative quality of metaphor responses. These findings are related to neuroscientific evidence on metaphor comprehension, creative idea generation and episodic future thought, suggesting that creating metaphors involves the flexible adaptation of semantic memory to imagine and construct novel figures of speech. Furthermore, the left DMPFC may exert executive control to maintain strategic search and selection, thus facilitating creativity of thought. PMID:24384149

  14. Creating metaphors: the neural basis of figurative language production.

    Science.gov (United States)

    Benedek, Mathias; Beaty, Roger; Jauk, Emanuel; Koschutnig, Karl; Fink, Andreas; Silvia, Paul J; Dunst, Beate; Neubauer, Aljoscha C

    2014-04-15

    Neuroscience research has thoroughly studied how nonliteral language is processed during metaphor comprehension. However, it is not clear how the brain actually creates nonliteral language. Therefore, the present study for the first time investigates the neural correlates of metaphor production. Participants completed sentences by generating novel metaphors or literal synonyms during functional imaging. Responses were spoken aloud in the scanner, recorded, and subsequently rated for their creative quality. We found that metaphor production was associated with focal activity in predominantly left-hemispheric brain regions, specifically the left angular gyrus, the left middle and superior frontal gyri-corresponding to the left dorsomedial prefrontal (DMPFC) cortex-and the posterior cingulate cortex. Moreover, brain activation in the left anterior DMPFC and the right middle temporal gyrus was found to linearly increase with the creative quality of metaphor responses. These findings are related to neuroscientific evidence on metaphor comprehension, creative idea generation and episodic future thought, suggesting that creating metaphors involves the flexible adaptation of semantic memory to imagine and construct novel figures of speech. Furthermore, the left DMPFC may exert executive control to maintain strategic search and selection, thus facilitating creativity of thought. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  15. Neural underpinnings of music: the polyrhythmic brain.

    Science.gov (United States)

    Vuust, Peter; Gebauer, Line K; Witek, Maria A G

    2014-01-01

    Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has the remarkable ability to move our minds and bodies. Why do certain rhythms make us want to tap our feet, bop our heads or even get up and dance? And how does the brain process rhythmically complex rhythms during our experiences of music? In this chapter, we describe some common forms of rhythmic complexity in music and propose that the theory of predictive coding can explain how rhythm and rhythmic complexity are processed in the brain. We also consider how this theory may reveal why we feel so compelled by rhythmic tension in music. First, musical-theoretical and neuroscientific frameworks of rhythm are presented, in which rhythm perception is conceptualized as an interaction between what is heard ('rhythm') and the brain's anticipatory structuring of music ('the meter'). Second, three different examples of tension between rhythm and meter in music are described: syncopation, polyrhythm and groove. Third, we present the theory of predictive coding of music, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain's Bayesian minimization of the error between the input to the brain and the brain's prior expectations. Fourth, empirical studies of neural and behavioral effects of syncopation, polyrhythm and groove will be reported, and we propose how these studies can be seen as special cases of the predictive coding theory. Finally, we argue that musical rhythm exploits the brain's general principles of anticipation and propose that pleasure from musical rhythm may be a result of such anticipatory mechanisms.

  16. Towards a neural basis of music-evoked emotions.

    Science.gov (United States)

    Koelsch, Stefan

    2010-03-01

    Music is capable of evoking exceptionally strong emotions and of reliably affecting the mood of individuals. Functional neuroimaging and lesion studies show that music-evoked emotions can modulate activity in virtually all limbic and paralimbic brain structures. These structures are crucially involved in the initiation, generation, detection, maintenance, regulation and termination of emotions that have survival value for the individual and the species. Therefore, at least some music-evoked emotions involve the very core of evolutionarily adaptive neuroaffective mechanisms. Because dysfunctions in these structures are related to emotional disorders, a better understanding of music-evoked emotions and their neural correlates can lead to a more systematic and effective use of music in therapy. Copyright 2010 Elsevier Ltd. All rights reserved.

  17. The neural basis of unwanted thoughts during resting state.

    Science.gov (United States)

    Kühn, Simone; Vanderhasselt, Marie-Anne; De Raedt, Rudi; Gallinat, Jürgen

    2014-09-01

    Human beings are constantly engaged in thought. Sometimes thoughts occur repetitively and can become distressing. Up to now the neural bases of these intrusive or unwanted thoughts is largely unexplored. To study the neural correlates of unwanted thoughts, we acquired resting-state fMRI data of 41 female healthy subjects and assessed the self-reported amount of unwanted thoughts during measurement. We analyzed local connectivity by means of regional homogeneity (ReHo) and functional connectivity of a seed region. More unwanted thoughts (state) were associated with lower ReHo in right dorsolateral prefrontal cortex (DLPFC) and higher ReHo in left striatum (putamen). Additional seed-based analysis revealed higher functional connectivity of the left striatum with left inferior frontal gyrus (IFG) in participants reporting more unwanted thoughts. The state-dependent higher connectivty in left striatum was positively correlated with rumination assessed with a dedicated questionnaire focussing on trait aspects. Unwanted thoughts are associated with activity in the fronto-striatal brain circuitry. The reduction of local connectivity in DLPFC could reflect deficiencies in thought suppression processes, whereas the hightened activity in left striatum could imply an imbalance of gating mechanisms housed in basal ganglia. Its functional connectivity to left IFG is discussed as the result of thought-related speech processes. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  18. Neural basis of increased costly norm enforcement under adversity.

    Science.gov (United States)

    Wu, Yan; Yu, Hongbo; Shen, Bo; Yu, Rongjun; Zhou, Zhiheng; Zhang, Guoping; Jiang, Yushi; Zhou, Xiaolin

    2014-12-01

    Humans are willing to punish norm violations even at a substantial personal cost. Using fMRI and a variant of the ultimatum game and functional magnetic resonance imaging, we investigated how the brain differentially responds to fairness in loss and gain domains. Participants (responders) received offers from anonymous partners indicating a division of an amount of monetary gain or loss. If they accept, both get their shares according to the division; if they reject, both get nothing or lose the entire stake. We used a computational model to derive perceived fairness of offers and participant-specific inequity aversion. Behaviorally, participants were more likely to reject unfair offers in the loss (vs gain) domain. Neurally, the positive correlation between fairness and activation in ventral striatum was reduced, whereas the negative correlations between fairness and activations in dorsolateral prefrontal cortex were enhanced in the loss domain. Moreover, rejection-related dorsal striatum activation was higher in the loss domain. Furthermore, the gain-loss domain modulates costly punishment only when unfair behavior was directed toward the participants and not when it was directed toward others. These findings provide neural and computational accounts of increased costly norm enforcement under adversity and advanced our understanding of the context-dependent nature of fairness preference. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  19. Behavior and neural basis of near-optimal visual search

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    Ma, Wei Ji; Navalpakkam, Vidhya; Beck, Jeffrey M; van den Berg, Ronald; Pouget, Alexandre

    2013-01-01

    The ability to search efficiently for a target in a cluttered environment is one of the most remarkable functions of the nervous system. This task is difficult under natural circumstances, as the reliability of sensory information can vary greatly across space and time and is typically a priori unknown to the observer. In contrast, visual-search experiments commonly use stimuli of equal and known reliability. In a target detection task, we randomly assigned high or low reliability to each item on a trial-by-trial basis. An optimal observer would weight the observations by their trial-to-trial reliability and combine them using a specific nonlinear integration rule. We found that humans were near-optimal, regardless of whether distractors were homogeneous or heterogeneous and whether reliability was manipulated through contrast or shape. We present a neural-network implementation of near-optimal visual search based on probabilistic population coding. The network matched human performance. PMID:21552276

  20. A Neural Basis for the Acquired Capability for Suicide

    Directory of Open Access Journals (Sweden)

    Gopikrishna Deshpande

    2016-08-01

    Full Text Available The high rate of fatal suicidal behavior in men is an urgent issue as highlighted in the public eye via news sources and media outlets. In this study, we have attempted to address this issue and understand the neural substrates underlying the gender differences in the rate of fatal suicidal behavior. The Interpersonal-Psychological Theory of Suicide (IPTS has proposed an explanation for the seemingly paradoxical relationship between gender and suicidal behavior, i.e. greater non-fatal suicide attempts by women but higher number of deaths by suicide in men. This theory states that possessing suicidal desire (due to conditions such as depression alone is not sufficient for a lethal suicide attempt. It is imperative for an individual to have acquired the capability for suicide (ACS along with suicidal desire in order to die by suicide. Therefore, higher levels of ACS in men may explain why men are more likely to die by suicide than women, despite being less likely to experience suicidal ideation or depression. In this study, we used activation likelihood estimation meta-analysis to investigate a potential ACS network that involves neural substrates underlying emotional stoicism, sensation seeking, pain tolerance, and fearlessness of death along with a potential depression network that involves neural substrates that underlie clinical depression. Brain regions commonly found in ACS and depression networks for males and females were further used as seeds to obtain regions functionally and structurally connected to them. We found that the male-specific networks were more widespread and diverse than the female-specific ones. Also, while the former involved motor regions such as the premotor cortex and cerebellum, the latter was dominated by limbic regions. This may support the fact that suicidal desire generally leads to fatal/decisive action in males while in females, it manifests as depression, ideation and generally non-fatal actions. The proposed

  1. The cognitive and neural basis of developmental prosopagnosia.

    Science.gov (United States)

    Towler, John; Fisher, Katie; Eimer, Martin

    2017-02-01

    Developmental prosopagnosia (DP) is a severe impairment of visual face recognition in the absence of any apparent brain damage. The factors responsible for DP have not yet been fully identified. This article provides a selective review of recent studies investigating cognitive and neural processes that may contribute to the face recognition deficits in DP, focusing primarily on event-related brain potential (ERP) measures of face perception and recognition. Studies that measured the face-sensitive N170 component as a marker of perceptual face processing have shown that the perceptual discrimination between faces and non-face objects is intact in DP. Other N170 studies suggest that faces are not represented in the typical fashion in DP. Individuals with DP appear to have specific difficulties in processing spatial and contrast deviations from canonical upright visual-perceptual face templates. The rapid detection of emotional facial expressions appears to be unaffected in DP. ERP studies of the activation of visual memory for individual faces and of the explicit identification of particular individuals have revealed differences between DPs and controls in the timing of these processes and in the links between visual face memory and explicit face recognition. These observations suggest that the speed and efficiency of information propagation through the cortical face network is altered in DP. The nature of the perceptual impairments in DP suggests that atypical visual experience with the eye region of faces over development may be an important contributing factor to DP.

  2. Neural Basis of Enhanced Executive Function in Older Video Game Players: An fMRI Study.

    Science.gov (United States)

    Wang, Ping; Zhu, Xing-Ting; Qi, Zhigang; Huang, Silin; Li, Hui-Jie

    2017-01-01

    Video games have been found to have positive influences on executive function in older adults; however, the underlying neural basis of the benefits from video games has been unclear. Adopting a task-based functional magnetic resonance imaging (fMRI) study targeted at the flanker task, the present study aims to explore the neural basis of the improved executive function in older adults with video game experiences. Twenty video game players (VGPs) and twenty non-video game players (NVGPs) of 60 years of age or older participated in the present study, and there are no significant differences in age (t = 0.62, p = 0.536), gender ratio (t = 1.29, p = 0.206) and years of education (t = 1.92, p = 0.062) between VGPs and NVGPs. The results show that older VGPs present significantly better behavioral performance than NVGPs. Older VGPs activate greater than NVGPs in brain regions, mainly in frontal-parietal areas, including the right dorsolateral prefrontal cortex, the left supramarginal gyrus, the right angular gyrus, the right precuneus and the left paracentral lobule. The present study reveals that video game experiences may have positive influences on older adults in behavioral performance and the underlying brain activation. These results imply the potential role that video games can play as an effective tool to improve cognitive ability in older adults.

  3. Neural Basis of Enhanced Executive Function in Older Video Game Players: An fMRI Study

    Directory of Open Access Journals (Sweden)

    Ping Wang

    2017-11-01

    Full Text Available Video games have been found to have positive influences on executive function in older adults; however, the underlying neural basis of the benefits from video games has been unclear. Adopting a task-based functional magnetic resonance imaging (fMRI study targeted at the flanker task, the present study aims to explore the neural basis of the improved executive function in older adults with video game experiences. Twenty video game players (VGPs and twenty non-video game players (NVGPs of 60 years of age or older participated in the present study, and there are no significant differences in age (t = 0.62, p = 0.536, gender ratio (t = 1.29, p = 0.206 and years of education (t = 1.92, p = 0.062 between VGPs and NVGPs. The results show that older VGPs present significantly better behavioral performance than NVGPs. Older VGPs activate greater than NVGPs in brain regions, mainly in frontal-parietal areas, including the right dorsolateral prefrontal cortex, the left supramarginal gyrus, the right angular gyrus, the right precuneus and the left paracentral lobule. The present study reveals that video game experiences may have positive influences on older adults in behavioral performance and the underlying brain activation. These results imply the potential role that video games can play as an effective tool to improve cognitive ability in older adults.

  4. Neural basis of decision making guided by emotional outcomes

    Science.gov (United States)

    Matsuda, Yoshi-Taka; Fujimura, Tomomi; Ueno, Kenichi; Asamizuya, Takeshi; Suzuki, Chisato; Cheng, Kang; Okanoya, Kazuo; Okada, Masato

    2015-01-01

    Emotional events resulting from a choice influence an individual's subsequent decision making. Although the relationship between emotion and decision making has been widely discussed, previous studies have mainly investigated decision outcomes that can easily be mapped to reward and punishment, including monetary gain/loss, gustatory stimuli, and pain. These studies regard emotion as a modulator of decision making that can be made rationally in the absence of emotions. In our daily lives, however, we often encounter various emotional events that affect decisions by themselves, and mapping the events to a reward or punishment is often not straightforward. In this study, we investigated the neural substrates of how such emotional decision outcomes affect subsequent decision making. By using functional magnetic resonance imaging (fMRI), we measured brain activities of humans during a stochastic decision-making task in which various emotional pictures were presented as decision outcomes. We found that pleasant pictures differentially activated the midbrain, fusiform gyrus, and parahippocampal gyrus, whereas unpleasant pictures differentially activated the ventral striatum, compared with neutral pictures. We assumed that the emotional decision outcomes affect the subsequent decision by updating the value of the options, a process modeled by reinforcement learning models, and that the brain regions representing the prediction error that drives the reinforcement learning are involved in guiding subsequent decisions. We found that some regions of the striatum and the insula were separately correlated with the prediction error for either pleasant pictures or unpleasant pictures, whereas the precuneus was correlated with prediction errors for both pleasant and unpleasant pictures. PMID:25695644

  5. Psycho-neural Identity as the Basis for Empirical Research and Theorization in Psychology: An Interview with Mario A. Bunge

    Science.gov (United States)

    Virues-Ortega, Javier; Hurtado-Parrado, Camilo; Martin, Toby L.; Julio, Flávia

    2012-10-01

    Mario Bunge is one of the most prolific philosophers of our time. Over the past sixty years he has written extensively about semantics, ontology, epistemology, philosophy of science and ethics. Bunge has been interested in the philosophical and methodological implications of modern psychology and more specifically in the philosophies of the relation between the neural and psychological realms. According to Bunge, functionalism, the philosophical stand of current psychology, has limited explanatory power in that neural processes are not explicitly acknowledged as components or factors of psychological phenomena. In Matter and Mind (2010), Bunge has elaborated in great detail the philosophies of the mind-brain dilemma and the basis of the psychoneural identity hypothesis, which suggests that all psychological processes can be analysed in terms of neural and physical phenomena. This article is the result of a long interview with Dr. Bunge on psychoneural identity and brain-behaviour relations.

  6. The neural basis of predicting the outcomes of planned actions

    Directory of Open Access Journals (Sweden)

    Andrew eJahn

    2011-11-01

    Full Text Available A key feature of human intelligence is the ability to predict the outcomes of one’s own actions prior to executing them. Action values are thought to be represented in part in the dorsal and ventral medial prefrontal cortex, yet current studies have focused on the value of executed actions rather than the anticipated value of a planned action. Thus, little is known about the neural basis of how individuals think (or fail to think about their actions and the potential consequences before they act. We scanned individuals with fMRI while they thought about performing actions that they knew would likely be correct or incorrect. Here we show that merely imagining an error, as opposed to imagining a correct outcome, increases activity in the dorsal anterior cingulate cortex, independently of subsequent actions. This activity overlaps with regions that respond to actual error commission. The findings show a distinct network that signals the prospective outcomes of one’s planned actions. A number of clinical disorders such as schizophrenia and drug abuse involve a failure to take the potential consequences of an action into account prior to acting. Our results thus suggest how dysfunctions of the medial prefrontal cortex may contribute to such failures.

  7. Neural basis of individual differences in the response to mental stress: a magnetoencephalography study.

    Science.gov (United States)

    Yamano, Emi; Ishii, Akira; Tanaka, Masaaki; Nomura, Shusaku; Watanabe, Yasuyoshi

    2016-12-01

    Stress is a risk factor for the onset of mental disorders. Although stress response varies across individuals, the mechanism of individual differences remains unclear. Here, we investigated the neural basis of individual differences in response to mental stress using magnetoencephalography (MEG). Twenty healthy male volunteers completed the Temperament and Character Inventory (TCI). The experiment included two types of tasks: a non-stress-inducing task and a stress-inducing task. During these tasks, participants passively viewed non-stress-inducing images and stress-inducing images, respectively, and MEG was recorded. Before and after each task, MEG and electrocardiography were recorded and subjective ratings were obtained. We grouped participants according to Novelty seeking (NS) - tendency to be exploratory, and Harm avoidance (HA) - tendency to be cautious. Participants with high NS and low HA (n = 10) assessed by TCI had a different neural response to stress than those with low NS and high HA (n = 10). Event-related desynchronization (ERD) in the beta frequency band was observed only in participants with high NS and low HA in the brain region extending from Brodmann's area 31 (including the posterior cingulate cortex and precuneus) from 200 to 350 ms after the onset of picture presentation in the stress-inducing task. Individual variation in personality traits (NS and HA) was associated with the neural response to mental stress. These findings increase our understanding of the psychological and neural basis of individual differences in the stress response, and will contribute to development of the psychotherapeutic approaches to stress-related disorders.

  8. Brain tumor segmentation with Deep Neural Networks.

    Science.gov (United States)

    Havaei, Mohammad; Davy, Axel; Warde-Farley, David; Biard, Antoine; Courville, Aaron; Bengio, Yoshua; Pal, Chris; Jodoin, Pierre-Marc; Larochelle, Hugo

    2017-01-01

    In this paper, we present a fully automatic brain tumor segmentation method based on Deep Neural Networks (DNNs). The proposed networks are tailored to glioblastomas (both low and high grade) pictured in MR images. By their very nature, these tumors can appear anywhere in the brain and have almost any kind of shape, size, and contrast. These reasons motivate our exploration of a machine learning solution that exploits a flexible, high capacity DNN while being extremely efficient. Here, we give a description of different model choices that we've found to be necessary for obtaining competitive performance. We explore in particular different architectures based on Convolutional Neural Networks (CNN), i.e. DNNs specifically adapted to image data. We present a novel CNN architecture which differs from those traditionally used in computer vision. Our CNN exploits both local features as well as more global contextual features simultaneously. Also, different from most traditional uses of CNNs, our networks use a final layer that is a convolutional implementation of a fully connected layer which allows a 40 fold speed up. We also describe a 2-phase training procedure that allows us to tackle difficulties related to the imbalance of tumor labels. Finally, we explore a cascade architecture in which the output of a basic CNN is treated as an additional source of information for a subsequent CNN. Results reported on the 2013 BRATS test data-set reveal that our architecture improves over the currently published state-of-the-art while being over 30 times faster. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Neural correlates of apathy in patients with neurodegenerative disorders, acquired brain injury, and psychiatric disorders

    NARCIS (Netherlands)

    Kos, Claire; van Tol, Marie-Jose; Marsman, Jan-Bernard C.; Knegtering, Henderikus; Aleman, Andre

    2016-01-01

    Apathy can be described as a loss of goal-directed purposeful behavior and is common in a variety of neurological and psychiatric disorders. Although previous studies investigated associations between abnormal brain functioning and apathy, it is unclear whether the neural basis of apathy is similar

  10. Neural basis of music knowledge: evidence from the dementias.

    Science.gov (United States)

    Hsieh, Sharpley; Hornberger, Michael; Piguet, Olivier; Hodges, John R

    2011-09-01

    The study of patients with semantic dementia has revealed important insights into the cognitive and neural architecture of semantic memory. Patients with semantic dementia are known to have difficulty understanding the meanings of environmental sounds from an early stage but little is known about their knowledge for famous tunes, which might be preserved in some cases. Patients with semantic dementia (n = 13), Alzheimer's disease (n = 14) as well as matched healthy control participants (n = 20) underwent a battery of tests designed to assess knowledge of famous tunes, environmental sounds and famous faces, as well as volumetric magnetic resonance imaging. As a group, patients with semantic dementia were profoundly impaired in the recognition of everyday environmental sounds and famous tunes with consistent performance across testing modalities, which is suggestive of a central semantic deficit. A few notable individuals (n = 3) with semantic dementia demonstrated clear preservation of knowledge of known melodies and famous people. Defects in auditory semantics were mild in patients with Alzheimer's disease. Voxel-based morphometry of magnetic resonance brain images showed that the recognition of famous tunes correlated with the degree of right anterior temporal lobe atrophy, particularly in the temporal pole. This area was segregated from the region found to be involved in the recognition of everyday sounds but overlapped considerably with the area that was correlated with the recognition of famous faces. The three patients with semantic dementia with sparing of musical knowledge had significantly less atrophy of the right temporal pole in comparison to the other patients in the semantic dementia group. These findings highlight the role of the right temporal pole in the processing of known tunes and faces. Overlap in this region might reflect that having a unique identity is a quality that is common to both melodies and people.

  11. Neural basis of impaired cognitive flexibility in patients with anorexia nervosa.

    Directory of Open Access Journals (Sweden)

    Yasuhiro Sato

    Full Text Available BACKGROUND: Impaired cognitive flexibility in anorexia nervosa (AN causes clinical problems and makes the disease hard to treat, but its neural basis has yet to be fully elucidated. The purpose of this study was to evaluate the brain activity of individuals with AN while performing a task requiring cognitive flexibility on the Wisconsin Card Sorting Test (WCST, which is one of the most frequently used neurocognitive measures of cognitive flexibility and problem-solving ability. METHODS: Participants were 15 female AN patients and 15 age- and intelligence quotient-matched healthy control women. Participants completed the WCST while their brain activity was measured by functional magnetic resonance imaging during the task. Brain activation in response to set shifting error feedback and the correlation between such brain activity and set shifting performance were analyzed. RESULTS: The correct rate on the WCST was significantly poorer for AN patients than for controls. Patients showed poorer activity in the right ventrolateral prefrontal cortex and bilateral parahippocampal cortex on set shifting than controls. Controls showed a positive correlation between correct rate and ventrolateral prefrontal activity in response to set shifting whereas patients did not. CONCLUSION: These findings suggest dysfunction of the ventrolateral prefrontal cortex and parahippocampal cortex as a cause of impaired cognitive flexibility in AN patients.

  12. Neural Basis of Impaired Cognitive Flexibility in Patients with Anorexia Nervosa

    Science.gov (United States)

    Sato, Yasuhiro; Saito, Naohiro; Utsumi, Atsushi; Aizawa, Emiko; Shoji, Tomotaka; Izumiyama, Masahiro; Mushiake, Hajime; Hongo, Michio; Fukudo, Shin

    2013-01-01

    Background Impaired cognitive flexibility in anorexia nervosa (AN) causes clinical problems and makes the disease hard to treat, but its neural basis has yet to be fully elucidated. The purpose of this study was to evaluate the brain activity of individuals with AN while performing a task requiring cognitive flexibility on the Wisconsin Card Sorting Test (WCST), which is one of the most frequently used neurocognitive measures of cognitive flexibility and problem-solving ability. Methods Participants were 15 female AN patients and 15 age- and intelligence quotient-matched healthy control women. Participants completed the WCST while their brain activity was measured by functional magnetic resonance imaging during the task. Brain activation in response to set shifting error feedback and the correlation between such brain activity and set shifting performance were analyzed. Results The correct rate on the WCST was significantly poorer for AN patients than for controls. Patients showed poorer activity in the right ventrolateral prefrontal cortex and bilateral parahippocampal cortex on set shifting than controls. Controls showed a positive correlation between correct rate and ventrolateral prefrontal activity in response to set shifting whereas patients did not. Conclusion These findings suggest dysfunction of the ventrolateral prefrontal cortex and parahippocampal cortex as a cause of impaired cognitive flexibility in AN patients. PMID:23675408

  13. Sex differences in the neural basis of false-belief and pragmatic language comprehension.

    Science.gov (United States)

    Frank, Chiyoko Kobayashi; Baron-Cohen, Simon; Ganzel, Barbara L

    2015-01-15

    Increasing research evidence suggests that women are more advanced than men in pragmatic language comprehension and Theory of Mind (ToM), which is a cognitive component of empathy. We measured the hemodynamic responses of men and women while they performed a second-order false-belief (FB) task and a coherent story (CS) task. During the FB condition relative to the baseline (unlinked sentences [US]), we found convergent activity in ToM network regions, such as the temporoparietal junction (TPJ) bilaterally and precuneus, in both sexes. We also found a greater activity in the left medial prefrontal cortex (mPFC) and a greater deactivation in the ventromedial prefrontal cortex (vmPFC)/orbitofrontal cortex (OFC) bilaterally in women compared to men. However, we did not find difference in the brain activity between the sexes during the FB condition relative to the CS condition. The results suggest a significant overlap between neural bases of pragmatic language comprehension and ToM in both men and women. Taken together, these results are in line with the extreme male brain (EMB) hypothesis by demonstrating sex difference in the neural basis of ToM and pragmatic language, both of which are found to be impaired in individuals with Autism Spectrum Conditions (ASC). In addition, the results also suggest that on average women use both cognitive empathy (dorsal mPFC) and affective empathy (vmPFC) networks more than men for false-belief reasoning. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Inhibition and impulsivity: behavioral and neural basis of response control.

    Science.gov (United States)

    Bari, Andrea; Robbins, Trevor W

    2013-09-01

    In many circumstances alternative courses of action and thoughts have to be inhibited to allow the emergence of goal-directed behavior. However, this has not been the accepted view in the past and only recently has inhibition earned its own place in the neurosciences as a fundamental cognitive function. In this review we first introduce the concept of inhibition from early psychological speculations based on philosophical theories of the human mind. The broad construct of inhibition is then reduced to its most readily observable component which necessarily is its behavioral manifestation. The study of 'response inhibition' has the advantage of dealing with a relatively simple and straightforward process, the overriding of a planned or already initiated action. Deficient inhibitory processes profoundly affect everyday life, causing impulsive conduct which is generally detrimental for the individual. Impulsivity has been consistently linked to several types of addiction, attention deficit/hyperactivity disorder, mania and other psychiatric conditions. Our discussion of the behavioral assessment of impulsivity will focus on objective laboratory tasks of response inhibition that have been implemented in parallel for humans and other species with relatively few qualitative differences. The translational potential of these measures has greatly improved our knowledge of the neurobiological basis of behavioral inhibition and impulsivity. We will then review the current models of behavioral inhibition along with their expression via underlying brain regions, including those involved in the activation of the brain's emergency 'brake' operation, those engaged in more controlled and sustained inhibitory processes and other ancillary executive functions. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. The neural basis of a deficit in abstract thinking in patients with schizophrenia.

    Science.gov (United States)

    Oh, Jooyoung; Chun, Ji-Won; Joon Jo, Hang; Kim, Eunseong; Park, Hae-Jeong; Lee, Boreom; Kim, Jae-Jin

    2015-10-30

    Abnormal abstract thinking is a major cause of social dysfunction in patients with schizophrenia, but little is known about its neural basis. In this study, we aimed to determine the characteristic abstract thinking-related brain responses in patients using a task reflecting social situations. We conducted functional magnetic resonance imaging while 16 patients with schizophrenia and 16 healthy controls performed a theme-identification task, in which various emotional pictures depicting social situations were presented. Compared with healthy controls, the patients showed significantly decreased activity in the left frontopolar and right orbitofrontal cortices during theme identification. Activity in these two regions correlated well in the controls, but not in patients. Instead, the patients exhibited a close correlation between activity in both sides of the frontopolar cortex, and a positive correlation between the right orbitofrontal cortex activity and degrees of theme identification. Reduced activity in the left frontopolar and right orbitofrontal cortices and the underlying aberrant connectivity may be implicated in the patients' deficits in abstract thinking. These newly identified features of the neural basis of abnormal abstract thinking are important as they have implications for the impaired social behavior of patients with schizophrenia during real-life situations. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  16. Estimating Neural Signal Dynamics in the Human Brain

    Directory of Open Access Journals (Sweden)

    Christopher W Tyler

    2011-06-01

    Full Text Available Although brain imaging methods are highly effective for localizing the effects of neural activation throughout the human brain in terms of the blood oxygenation level dependent (BOLD response, there is currently no way to estimate the underlying neural signal dynamics in generating the BOLD response in each local activation region (except for processes slower than the BOLD time course. Knowledge of the neural signal is critical information if spatial mapping is to progress to the analysis of dynamic information flow through the cortical networks as the brain performs its tasks. We introduce an analytic approach that provides a new level of conceptualization and specificity in the study of brain processing by noninvasive methods. This technique allows us to use brain imaging methods to determine the dynamics of local neural population responses to their native temporal resolution throughout the human brain, with relatively narrow confidence intervals on many response properties. The ability to characterize local neural dynamics in the human brain represents a significant enhancement of brain imaging capabilities, with potential application from general cognitive studies to assessment of neuropathologies.

  17. Identification of Sparse Neural Functional Connectivity using Penalized Likelihood Estimation and Basis Functions

    Science.gov (United States)

    Song, Dong; Wang, Haonan; Tu, Catherine Y.; Marmarelis, Vasilis Z.; Hampson, Robert E.; Deadwyler, Sam A.; Berger, Theodore W.

    2013-01-01

    One key problem in computational neuroscience and neural engineering is the identification and modeling of functional connectivity in the brain using spike train data. To reduce model complexity, alleviate overfitting, and thus facilitate model interpretation, sparse representation and estimation of functional connectivity is needed. Sparsities include global sparsity, which captures the sparse connectivities between neurons, and local sparsity, which reflects the active temporal ranges of the input-output dynamical interactions. In this paper, we formulate a generalized functional additive model (GFAM) and develop the associated penalized likelihood estimation methods for such a modeling problem. A GFAM consists of a set of basis functions convolving the input signals, and a link function generating the firing probability of the output neuron from the summation of the convolutions weighted by the sought model coefficients. Model sparsities are achieved by using various penalized likelihood estimations and basis functions. Specifically, we introduce two variations of the GFAM using a global basis (e.g., Laguerre basis) and group LASSO estimation, and a local basis (e.g., B-spline basis) and group bridge estimation, respectively. We further develop an optimization method based on quadratic approximation of the likelihood function for the estimation of these models. Simulation and experimental results show that both group-LASSO-Laguerre and group-bridge-B-spline can capture faithfully the global sparsities, while the latter can replicate accurately and simultaneously both global and local sparsities. The sparse models outperform the full models estimated with the standard maximum likelihood method in out-of-sample predictions. PMID:23674048

  18. Optimal Brain Surgeon on Artificial Neural Networks in

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye; Job, Jonas Hultmann; Klyver, Katrine

    2012-01-01

    It is shown how the procedure know as optimal brain surgeon can be used to trim and optimize artificial neural networks in nonlinear structural dynamics. Beside optimizing the neural network, and thereby minimizing computational cost in simulation, the surgery procedure can also serve as a quick...

  19. An Artificial Neural Network Based Robot Controller that Uses Rat’s Brain Signals

    Directory of Open Access Journals (Sweden)

    Marsel Mano

    2013-04-01

    Full Text Available Brain machine interface (BMI has been proposed as a novel technique to control prosthetic devices aimed at restoring motor functions in paralyzed patients. In this paper, we propose a neural network based controller that maps rat’s brain signals and transforms them into robot movement. First, the rat is trained to move the robot by pressing the right and left lever in order to get food. Next, we collect brain signals with four implanted electrodes, two in the motor cortex and two in the somatosensory cortex area. The collected data are used to train and evaluate different artificial neural controllers. Trained neural controllers are employed online to map brain signals and transform them into robot motion. Offline and online classification results of rat’s brain signals show that the Radial Basis Function Neural Networks (RBFNN outperforms other neural networks. In addition, online robot control results show that even with a limited number of electrodes, the robot motion generated by RBFNN matched the motion generated by the left and right lever position.

  20. The brain basis of emotion: a meta-analytic review.

    Science.gov (United States)

    Lindquist, Kristen A; Wager, Tor D; Kober, Hedy; Bliss-Moreau, Eliza; Barrett, Lisa Feldman

    2012-06-01

    Researchers have wondered how the brain creates emotions since the early days of psychological science. With a surge of studies in affective neuroscience in recent decades, scientists are poised to answer this question. In this target article, we present a meta-analytic summary of the neuroimaging literature on human emotion. We compare the locationist approach (i.e., the hypothesis that discrete emotion categories consistently and specifically correspond to distinct brain regions) with the psychological constructionist approach (i.e., the hypothesis that discrete emotion categories are constructed of more general brain networks not specific to those categories) to better understand the brain basis of emotion. We review both locationist and psychological constructionist hypotheses of brain-emotion correspondence and report meta-analytic findings bearing on these hypotheses. Overall, we found little evidence that discrete emotion categories can be consistently and specifically localized to distinct brain regions. Instead, we found evidence that is consistent with a psychological constructionist approach to the mind: A set of interacting brain regions commonly involved in basic psychological operations of both an emotional and non-emotional nature are active during emotion experience and perception across a range of discrete emotion categories.

  1. Neural substrate expansion for the restoration of brain function

    Directory of Open Access Journals (Sweden)

    Han-Chiao Isaac Chen

    2016-01-01

    Full Text Available Restoring neurological and cognitive function in individuals who have suffered brain damage is one of the principal objectives of modern translational neuroscience. Electrical stimulation approaches, such as deep-brain stimulation, have achieved the most clinical success, but they ultimately may be limited by the computational capacity of the residual cerebral circuitry. An alternative strategy is brain substrate expansion, in which the computational capacity of the brain is augmented through the addition of new processing units and the reconstitution of network connectivity. This latter approach has been explored to some degree using both biological and electronic means but thus far has not demonstrated the ability to reestablish the function of large-scale neuronal networks. In this review, we contend that fulfilling the potential of brain substrate expansion will require a significant shift from current methods that emphasize direct manipulations of the brain (e.g., injections of cellular suspensions and the implantation of multi-electrode arrays to the generation of more sophisticated neural tissues and neural-electric hybrids in vitro that are subsequently transplanted into the brain. Drawing from neural tissue engineering, stem cell biology, and neural interface technologies, this strategy makes greater use of the manifold techniques available in the laboratory to create biocompatible constructs that recapitulate brain architecture and thus are more easily recognized and utilized by brain networks.

  2. Prediction of caspase cleavage sites using Bayesian bio-basis function neural networks.

    Science.gov (United States)

    Yang, Zheng Rong

    2005-05-01

    Apoptosis has drawn the attention of researchers because of its importance in treating some diseases through finding a proper way to block or slow down the apoptosis process. Having understood that caspase cleavage is the key to apoptosis, we find novel methods or algorithms are essential for studying the specificity of caspase cleavage activity and this helps the effective drug design. As bio-basis function neural networks have proven to outperform some conventional neural learning algorithms, there is a motivation, in this study, to investigate the application of bio-basis function neural networks for the prediction of caspase cleavage sites. Thirteen protein sequences with experimentally determined caspase cleavage sites were downloaded from NCBI. Bayesian bio-basis function neural networks are investigated and the comparisons with single-layer perceptrons, multilayer perceptrons, the original bio-basis function neural networks and support vector machines are given. The impact of the sliding window size used to generate sub-sequences for modelling on prediction accuracy is studied. The results show that the Bayesian bio-basis function neural network with two Gaussian distributions for model parameters (weights) performed the best and the highest prediction accuracy is 97.15 +/- 1.13%. The package of Bayesian bio-basis function neural network can be obtained by request to the author.

  3. The neural basis of implicit learning and memory: a review of neuropsychological and neuroimaging research.

    Science.gov (United States)

    Reber, Paul J

    2013-08-01

    Memory systems research has typically described the different types of long-term memory in the brain as either declarative versus non-declarative or implicit versus explicit. These descriptions reflect the difference between declarative, conscious, and explicit memory that is dependent on the medial temporal lobe (MTL) memory system, and all other expressions of learning and memory. The other type of memory is generally defined by an absence: either the lack of dependence on the MTL memory system (nondeclarative) or the lack of conscious awareness of the information acquired (implicit). However, definition by absence is inherently underspecified and leaves open questions of how this type of memory operates, its neural basis, and how it differs from explicit, declarative memory. Drawing on a variety of studies of implicit learning that have attempted to identify the neural correlates of implicit learning using functional neuroimaging and neuropsychology, a theory of implicit memory is presented that describes it as a form of general plasticity within processing networks that adaptively improve function via experience. Under this model, implicit memory will not appear as a single, coherent, alternative memory system but will instead be manifested as a principle of improvement from experience based on widespread mechanisms of cortical plasticity. The implications of this characterization for understanding the role of implicit learning in complex cognitive processes and the effects of interactions between types of memory will be discussed for examples within and outside the psychology laboratory. Copyright © 2013 Elsevier Ltd. All rights reserved.

  4. Neural reuse: a fundamental organizational principle of the brain.

    Science.gov (United States)

    Anderson, Michael L

    2010-08-01

    An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design.

  5. On the nature, modeling, and neural basis of social ties

    NARCIS (Netherlands)

    van Winden, F.; Stallen, M.; Ridderinkhof, K.R.; Houser, D.; McCabe, K.

    2009-01-01

    Purpose This paper addresses the nature, formalization, and neural bases of (affective) social ties and discusses the relevance of ties for health economics. A social tie is defined as an affective weight attached by an individual to the well-being of another individual (‘utility interdependence’).

  6. The neural basis of the speed-accuracy tradeoff

    NARCIS (Netherlands)

    Bogacz, R.; Wagenmakers, E.J.; Forstmann, B.U.; Nieuwenhuis, S.

    2010-01-01

    In many situations, decision makers need to negotiate between the competing demands of response speed and response accuracy, a dilemma generally known as the speed-accuracy tradeoff (SAT). Despite the ubiquity of SAT, the question of how neural decision circuits implement SAT has received little

  7. Temporal phase relation of circadian neural oscillations as the basis ...

    Indian Academy of Sciences (India)

    ... to its known regulation of seasonal gonadal cycles, the relative position of two circadian neural oscillations may also affect the rate of gonadal development during the attainment of puberty in mice. Moreover, the present study provides an experimental paradigm to test the coincidence model of circadian oscillations.

  8. The brain basis of emotion: A meta-analytic review

    Science.gov (United States)

    Lindquist, Kristen A.; Wager, Tor D.; Kober, Hedy; Bliss-Moreau, Eliza; Barrett, Lisa Feldman

    2015-01-01

    Researchers have wondered how the brain creates emotions since the early days of psychological science. With a surge of studies in affective neuroscience in recent decades, scientists are poised to answer this question. In this article, we present a meta-analytic summary of the human neuroimaging literature on emotion. We compare the locationist approach (i.e., the hypothesis that discrete emotion categories consistently and specifically correspond to distinct brain regions) with the psychological constructionist approach (i.e., the hypothesis that discrete emotion categories are constructed of more general brain networks not specific to those categories) to better understand the brain basis of emotion. We review both locationist and psychological constructionist hypotheses of brain–emotion correspondence and report meta-analytic findings bearing on these hypotheses. Overall, we found little evidence that discrete emotion categories can be consistently and specifically localized to distinct brain regions. Instead, we found evidence that is consistent with a psychological constructionist approach to the mind: a set of interacting brain regions commonly involved in basic psychological operations of both an emotional and non-emotional nature are active during emotion experience and perception across a range of discrete emotion categories. PMID:22617651

  9. Radial basis function (RBF) neural network control for mechanical systems design, analysis and Matlab simulation

    CERN Document Server

    Liu, Jinkun

    2013-01-01

    Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design.   This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...

  10. Neural Basis of Enhanced Executive Function in Older Video Game Players: An fMRI Study

    OpenAIRE

    Ping Wang; Ping Wang; Xing-Ting Zhu; Xing-Ting Zhu; Zhigang Qi; Zhigang Qi; Silin Huang; Hui-Jie Li; Hui-Jie Li

    2017-01-01

    Video games have been found to have positive influences on executive function in older adults; however, the underlying neural basis of the benefits from video games has been unclear. Adopting a task-based functional magnetic resonance imaging (fMRI) study targeted at the flanker task, the present study aims to explore the neural basis of the improved executive function in older adults with video game experiences. Twenty video game players (VGPs) and twenty non-video game players (NVGPs) of 60...

  11. Increased neural activity of a mushroom body neuron subtype in the brains of forager honeybees.

    Directory of Open Access Journals (Sweden)

    Taketoshi Kiya

    Full Text Available Honeybees organize a sophisticated society, and the workers transmit information about the location of food sources using a symbolic dance, known as 'dance communication'. Recent studies indicate that workers integrate sensory information during foraging flight for dance communication. The neural mechanisms that account for this remarkable ability are, however, unknown. In the present study, we established a novel method to visualize neural activity in the honeybee brain using a novel immediate early gene, kakusei, as a marker of neural activity. The kakusei transcript was localized in the nuclei of brain neurons and did not encode an open reading frame, suggesting that it functions as a non-coding nuclear RNA. Using this method, we show that neural activity of a mushroom body neuron subtype, the small-type Kenyon cells, is prominently increased in the brains of dancer and forager honeybees. In contrast, the neural activity of the two mushroom body neuron subtypes, the small-and large-type Kenyon cells, is increased in the brains of re-orienting workers, which memorize their hive location during re-orienting flights. These findings demonstrate that the small-type Kenyon cell-preferential activity is associated with foraging behavior, suggesting its involvement in information integration during foraging flight, which is an essential basis for dance communication.

  12. Smart Brain Hemorrhage Diagnosis Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Santosh H. Suryawanshi

    2015-08-01

    Full Text Available Abstract The fundamental motivation behind this study is to identify the brain hemorrhage and to give accurate treatment so that death rate because of brain hemorrhage can be reduced. This project investigates the possibility of diagnosing brain hemorrhage using an image segmentation of CT scan images using watershed method and feeding of the appropriate inputs extracted from the brain CT image to an artificial neural network for classification. The output generated as the type of brain hemorrhages can be used to verify expert diagnosis and also as learning tool for trainee radiologists to minimize errors in current methods.

  13. Neural basis of limb ownership in individuals with body integrity identity disorder.

    Directory of Open Access Journals (Sweden)

    Milenna T van Dijk

    Full Text Available Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis underlying the feeling of limb ownership, since these individuals have a feeling of disownership for a limb in the absence of apparent brain damage. Here we directly compared brain activation between limbs that do and do not feel as part of the body using functional MRI during separate tactile stimulation and motor execution experiments. In comparison to matched controls, individuals with BIID showed heightened responsivity of a large somatosensory network including the parietal cortex and right insula during tactile stimulation, regardless of whether the stimulated leg felt owned or alienated. Importantly, activity in the ventral premotor cortex depended on the feeling of ownership and was reduced during stimulation of the alienated compared to the owned leg. In contrast, no significant differences between groups were observed during the performance of motor actions. These results suggest that altered somatosensory processing in the premotor cortex is associated with the feeling of disownership in BIID, which may be related to altered integration of somatosensory and proprioceptive information.

  14. Effects of intranasal oxytocin on the neural basis of face processing in autism spectrum disorder.

    Science.gov (United States)

    Domes, Gregor; Heinrichs, Markus; Kumbier, Ekkehardt; Grossmann, Annette; Hauenstein, Karlheinz; Herpertz, Sabine C

    2013-08-01

    Autism spectrum disorder (ASD) is associated with altered face processing and decreased activity in brain regions involved in face processing. The neuropeptide oxytocin has been shown to promote face processing and modulate brain activity in healthy adults. The present study examined the effects of oxytocin on the neural basis of face processing in adults with Asperger syndrome (AS). A group of 14 individuals with AS and a group of 14 neurotypical control participants performed a face-matching and a house-matching task during functional magnetic resonance imaging. The effects of a single dose of 24 IU intranasally administered oxytocin were tested in a randomized, placebo-controlled, within-subject, cross-over design. Under placebo, the AS group showed decreased activity in the right amygdala, fusiform gyrus, and inferior occipital gyrus compared with the control group during face processing. After oxytocin treatment, right amygdala activity to facial stimuli increased in the AS group. These findings indicate that oxytocin increases the saliency of social stimuli and in ASD and suggest that oxytocin might promote face processing and eye contact in individuals with ASD as prerequisites for neurotypical social interaction. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  15. The neural basis of intuitive and counterintuitive moral judgment

    Science.gov (United States)

    Wiech, Katja; Shackel, Nicholas; Farias, Miguel; Savulescu, Julian; Tracey, Irene

    2012-01-01

    Neuroimaging studies on moral decision-making have thus far largely focused on differences between moral judgments with opposing utilitarian (well-being maximizing) and deontological (duty-based) content. However, these studies have investigated moral dilemmas involving extreme situations, and did not control for two distinct dimensions of moral judgment: whether or not it is intuitive (immediately compelling to most people) and whether it is utilitarian or deontological in content. By contrasting dilemmas where utilitarian judgments are counterintuitive with dilemmas in which they are intuitive, we were able to use functional magnetic resonance imaging to identify the neural correlates of intuitive and counterintuitive judgments across a range of moral situations. Irrespective of content (utilitarian/deontological), counterintuitive moral judgments were associated with greater difficulty and with activation in the rostral anterior cingulate cortex, suggesting that such judgments may involve emotional conflict; intuitive judgments were linked to activation in the visual and premotor cortex. In addition, we obtained evidence that neural differences in moral judgment in such dilemmas are largely due to whether they are intuitive and not, as previously assumed, to differences between utilitarian and deontological judgments. Our findings therefore do not support theories that have generally associated utilitarian and deontological judgments with distinct neural systems. PMID:21421730

  16. Cultural effects on the neural basis of theory of mind.

    Science.gov (United States)

    Kobayashi Frank, Chiyoko; Temple, Elise

    2009-01-01

    "Theory of mind" has been described as the ability to attribute and understand other people's desires and intentions as distinct from one's own. It has been found to develop as early as between 3 and 4 years old, with precursor abilities possibly developing much earlier. There has been debate about the extent to which the developmental trajectory of theory of mind may differ across cultures or language systems. Although very few neuroimaging studies have directly compared different groups from different culture and language systems, across studies of a number of cultural/language groups have been used to explore the neural correlates of theory of mind. A summary of these findings suggests that there may be both universal and culture or language-specific neural correlates related to theory of mind. These studies, while still preliminary in many ways, illustrate the importance of taking into account the cultural background of participants. Furthermore these results suggest that there may be important cultural influence on theory of mind and the neural correlates associated with this ability.

  17. The neural basis of the psychomotor vigilance task.

    Science.gov (United States)

    Drummond, Sean P A; Bischoff-Grethe, Amanda; Dinges, David F; Ayalon, Liat; Mednick, Sara C; Meloy, M J

    2005-09-01

    To identify brain regions underlying the fastest and slowest reaction times on the Psychomotor Vigilance task (PVT) under well-rested conditions, as well as brain regions related to particularly poor performance after sleep deprivation. Subjects took the PVT twice while undergoing functional magnetic resonance imaging: once 12 hours after waking from a normal night of sleep and once after 36 hours of total sleep deprivation (TSD). Session order was counterbalanced. UCSD J. Christian Gillin Laboratory for Sleep and Chronobiology (the sleep core of the General Clinical Research Center) and UCSD Magnetic Resonance Institute. Twenty right-handed healthy adults (8 women; age = 27.4 +/- 6.7 years; education = 15.6 +/- 1.5 years). After a normal night of sleep, optimal performance was related to greater cerebral responses within a cortical sustained attention network and the cortical and subcortical motor systems. Slow reaction times, particularly after TSD, were associated with greater activity in the "default mode network" consisting of frontal and posterior midline regions. Optimal performance on the PVT appears to rely on activation both within the sustained attention system and within the motor system. Poor performance following TSD may result from a disengagement from the task and related inattention, and brain regions responsible for this localize within midline structures shown to be involved in the brain's "default mode." Finally, particularly poor performance after TSD may elicit a subsequent attentional recovery that manifests as greater activation within the same regions normally responsible for fast reaction times.

  18. Behavioural and neural basis of anomalous motor learning in children with autism.

    Science.gov (United States)

    Marko, Mollie K; Crocetti, Deana; Hulst, Thomas; Donchin, Opher; Shadmehr, Reza; Mostofsky, Stewart H

    2015-03-01

    Autism spectrum disorder is a developmental disorder characterized by deficits in social and communication skills and repetitive and stereotyped interests and behaviours. Although not part of the diagnostic criteria, individuals with autism experience a host of motor impairments, potentially due to abnormalities in how they learn motor control throughout development. Here, we used behavioural techniques to quantify motor learning in autism spectrum disorder, and structural brain imaging to investigate the neural basis of that learning in the cerebellum. Twenty children with autism spectrum disorder and 20 typically developing control subjects, aged 8-12, made reaching movements while holding the handle of a robotic manipulandum. In random trials the reach was perturbed, resulting in errors that were sensed through vision and proprioception. The brain learned from these errors and altered the motor commands on the subsequent reach. We measured learning from error as a function of the sensory modality of that error, and found that children with autism spectrum disorder outperformed typically developing children when learning from errors that were sensed through proprioception, but underperformed typically developing children when learning from errors that were sensed through vision. Previous work had shown that this learning depends on the integrity of a region in the anterior cerebellum. Here we found that the anterior cerebellum, extending into lobule VI, and parts of lobule VIII were smaller than normal in children with autism spectrum disorder, with a volume that was predicted by the pattern of learning from visual and proprioceptive errors. We suggest that the abnormal patterns of motor learning in children with autism spectrum disorder, showing an increased sensitivity to proprioceptive error and a decreased sensitivity to visual error, may be associated with abnormalities in the cerebellum. © The Author (2015). Published by Oxford University Press on behalf

  19. The brain basis of musicophilia: evidence from frontotemporal lobar degeneration

    Directory of Open Access Journals (Sweden)

    Phillip David Fletcher

    2013-06-01

    Full Text Available Musicophilia, or abnormal craving for music, is a poorly understood phenomenon that has been associated in particular with focal degeneration of the temporal lobes. Here we addressed the brain basis of musicophilia using voxel-based morphometry (VBM on MR volumetric brain images in a retrospectively ascertained cohort of patients meeting clinical consensus criteria for frontotemporal lobar degeneration: of 37 cases ascertained, 12 had musicophilia and 25 did not exhibit the phenomenon. The syndrome of semantic dementia was relatively over-represented among the musicophilic subgroup. A VBM analysis revealed significantly increased regional grey matter volume in left posterior hippocampus in the musicophilic subgroup relative to the non-musicophilic group (p<0.05 corrected for regional comparisons; at a relaxed significance threshold (P<0.001 uncorrected across the brain volume musicophilia was associated with additional relative sparing of regional grey matter in other temporal lobe and prefrontal areas and atrophy of grey matter in posterior parietal and orbitofrontal areas. The present findings suggest a candidate brain substrate for musicophilia as a signature of distributed network damage that may reflect a shift of hedonic processing toward more abstract (non-social stimuli, with some specificity for particular neurodegenerative pathologies.

  20. The neural basis of risky choice with affective outcomes.

    Directory of Open Access Journals (Sweden)

    Renata S Suter

    Full Text Available Both normative and many descriptive theories of decision making under risk are based on the notion that outcomes are weighted by their probability, with subsequent maximization of the (subjective expected outcome. Numerous investigations from psychology, economics, and neuroscience have produced evidence consistent with this notion. However, this research has typically investigated choices involving relatively affect-poor, monetary outcomes. We compared choice in relatively affect-poor, monetary lottery problems with choice in relatively affect-rich medical decision problems. Computational modeling of behavioral data and model-based neuroimaging analyses provide converging evidence for substantial differences in the respective decision mechanisms. Relative to affect-poor choices, affect-rich choices yielded a more strongly curved probability weighting function of cumulative prospect theory, thus signaling that the psychological impact of probabilities is strongly diminished for affect-rich outcomes. Examining task-dependent brain activation, we identified a region-by-condition interaction indicating qualitative differences of activation between affect-rich and affect-poor choices. Moreover, brain activation in regions that were more active during affect-poor choices (e.g., the supramarginal gyrus correlated with individual trial-by-trial decision weights, indicating that these regions reflect processing of probabilities. Formal reverse inference Neurosynth meta-analyses suggested that whereas affect-poor choices seem to be based on brain mechanisms for calculative processes, affect-rich choices are driven by the representation of outcomes' emotional value and autobiographical memories associated with them. These results provide evidence that the traditional notion of expectation maximization may not apply in the context of outcomes laden with affective responses, and that understanding the brain mechanisms of decision making requires the domain

  1. The neural basis of social influence and attitude change.

    Science.gov (United States)

    Izuma, Keise

    2013-06-01

    Human attitudes and preferences are susceptible to social influence. Recent social neuroscience studies, using theories and experimental paradigms from social psychology, have begun to elucidate the neural mechanisms underlying how others influence our attitudes through processes such as social conformity, cognitive inconsistency and persuasion. The currently available evidence highlights the role of the posterior medial frontal cortex (pMFC) in social conformity and cognitive inconsistency, which represents the discrepancy between one's own and another person's opinion, or, more broadly, between currently inconsistent and ideally consistent states. Research on persuasion has revealed that people's susceptibility to persuasive messages is related to activation in a nearby but more anterior part of the medial frontal cortex. Future progress in this field will depend upon the ability of researchers to dissociate underlying motivations for attitude change in different paradigms, and to utilize neuroimaging methods to advance social psychological theories of social influence. Copyright © 2013 Elsevier Ltd. All rights reserved.

  2. Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

    Directory of Open Access Journals (Sweden)

    Mohammad S. Islam

    2017-01-01

    Full Text Available Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs for robust movement decoding of Parkinson’s disease (PD and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.

  3. Similarity on neural stem cells and brain tumor stem cells in transgenic brain tumor mouse models

    OpenAIRE

    Qiao, Guanqun; Li, Qingquan; Peng, Gang; Ma, Jun; Fan, Hongwei; Li, Yingbin

    2013-01-01

    Although it is believed that glioma is derived from brain tumor stem cells, the source and molecular signal pathways of these cells are still unclear. In this study, we used stable doxycycline-inducible transgenic mouse brain tumor models (c-myc+/SV40Tag+/Tet-on+) to explore the malignant trans-formation potential of neural stem cells by observing the differences of neural stem cells and brain tumor stem cells in the tumor models. Results showed that chromosome instability occurred in brain t...

  4. Formation and remodeling of the brain extracellular matrix in neural plasticity: Roles of chondroitin sulfate and hyaluronan.

    Science.gov (United States)

    Miyata, Shinji; Kitagawa, Hiroshi

    2017-10-01

    The extracellular matrix (ECM) of the brain is rich in glycosaminoglycans such as chondroitin sulfate (CS) and hyaluronan. These glycosaminoglycans are organized into either diffuse or condensed ECM. Diffuse ECM is distributed throughout the brain and fills perisynaptic spaces, whereas condensed ECM selectively surrounds parvalbumin-expressing inhibitory neurons (PV cells) in mesh-like structures called perineuronal nets (PNNs). The brain ECM acts as a non-specific physical barrier that modulates neural plasticity and axon regeneration. Here, we review recent progress in understanding of the molecular basis of organization and remodeling of the brain ECM, and the involvement of several types of experience-dependent neural plasticity, with a particular focus on the mechanism that regulates PV cell function through specific interactions between CS chains and their binding partners. We also discuss how the barrier function of the brain ECM restricts dendritic spine dynamics and limits axon regeneration after injury. The brain ECM not only forms physical barriers that modulate neural plasticity and axon regeneration, but also forms molecular brakes that actively controls maturation of PV cells and synapse plasticity in which sulfation patterns of CS chains play a key role. Structural remodeling of the brain ECM modulates neural function during development and pathogenesis. Genetic or enzymatic manipulation of the brain ECM may restore neural plasticity and enhance recovery from nerve injury. This article is part of a Special Issue entitled Neuro-glycoscience, edited by Kenji Kadomatsu and Hiroshi Kitagawa. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. The neural basis of individual face and object representation

    Directory of Open Access Journals (Sweden)

    Rebecca eWatson

    2016-03-01

    Full Text Available We routinely need to process the identity of many faces around us, and how the brain achieves this is still the subject of much research in cognitive neuroscience. To date, insights on face identity processing have come from both healthy and clinical populations. However, in order to directly compare results across and within participant groups, and across different studies, it is crucial that a standard task is utilised which includes different exemplars (for example, non-face stimuli along with faces, is memory-neutral, and taps into identity recognition across orientation and across viewpoint change. The goal of this study was to test a previously behaviourally tested, optimised face and object identity matching design in a healthy control sample whilst being scanned using fMRI. Specifically, we investigated categorical, orientation, and category-specific orientation effects while participants were focused on identity processing of simultaneously presented exemplar stimuli. Alongside observing category and orientation specific effects in a distributed set of brain regions, we also saw an interaction between stimulus category and orientation in the bilateral fusiform gyrus and bilateral middle occipital gyrus. Generally these clusters showed the pattern of a heightened response to inverted, as opposed to upright faces; and to upright, as opposed to inverted shoes. These results are discussed in relation to previous studies and to potential future research within prosopagnosic individuals.

  6. Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

    Science.gov (United States)

    Kim, Junsuk; Yeon, Jiwon; Ryu, Jaekyun; Park, Jang-Yeon; Chung, Soon-Cheol; Kim, Sung-Phil

    2017-01-01

    Our previous human fMRI study found brain activations correlated with tactile stickiness perception using the uni-variate general linear model (GLM) (Yeon et al., 2017). Here, we conducted an in-depth investigation on neural correlates of sticky sensations by employing a multivoxel pattern analysis (MVPA) on the same dataset. In particular, we statistically compared multi-variate neural activities in response to the three groups of sticky stimuli: A supra-threshold group including a set of sticky stimuli that evoked vivid sticky perception; an infra-threshold group including another set of sticky stimuli that barely evoked sticky perception; and a sham group including acrylic stimuli with no physically sticky property. Searchlight MVPAs were performed to search for local activity patterns carrying neural information of stickiness perception. Similar to the uni-variate GLM results, significant multi-variate neural activity patterns were identified in postcentral gyrus, subcortical (basal ganglia and thalamus), and insula areas (insula and adjacent areas). Moreover, MVPAs revealed that activity patterns in posterior parietal cortex discriminated the perceptual intensities of stickiness, which was not present in the uni-variate analysis. Next, we applied a principal component analysis (PCA) to the voxel response patterns within identified clusters so as to find low-dimensional neural representations of stickiness intensities. Follow-up clustering analyses clearly showed separate neural grouping configurations between the Supra- and Infra-threshold groups. Interestingly, this neural categorization was in line with the perceptual grouping pattern obtained from the psychophysical data. Our findings thus suggest that different stickiness intensities would elicit distinct neural activity patterns in the human brain and may provide a neural basis for the perception and categorization of tactile stickiness. PMID:28936171

  7. Feeling form: the neural basis of haptic shape perception

    Science.gov (United States)

    Kim, Sung Soo; Thakur, Pramodsingh H.; Bensmaia, Sliman J.

    2015-01-01

    The tactile perception of the shape of objects critically guides our ability to interact with them. In this review, we describe how shape information is processed as it ascends the somatosensory neuraxis of primates. At the somatosensory periphery, spatial form is represented in the spatial patterns of activation evoked across populations of mechanoreceptive afferents. In the cerebral cortex, neurons respond selectively to particular spatial features, like orientation and curvature. While feature selectivity of neurons in the earlier processing stages can be understood in terms of linear receptive field models, higher order somatosensory neurons exhibit nonlinear response properties that result in tuning for more complex geometrical features. In fact, tactile shape processing bears remarkable analogies to its visual counterpart and the two may rely on shared neural circuitry. Furthermore, one of the unique aspects of primate somatosensation is that it contains a deformable sensory sheet. Because the relative positions of cutaneous mechanoreceptors depend on the conformation of the hand, the haptic perception of three-dimensional objects requires the integration of cutaneous and proprioceptive signals, an integration that is observed throughout somatosensory cortex. PMID:26581869

  8. Neural basis of moral verdict and moral deliberation

    Science.gov (United States)

    Borg, Jana Schaich; Sinnott-Armstrong, Walter; Calhoun, Vince D.; Kiehl, Kent A.

    2011-01-01

    How people judge something to be morally right or wrong is a fundamental question of both the sciences and the humanities. Here we aim to identify the neural processes that underlie the specific conclusion that something is morally wrong. To do this, we introduce a novel distinction between “moral deliberation,” or the weighing of moral considerations, and the formation of a “moral verdict,” or the commitment to one moral conclusion. We predict and identify hemodynamic activity in the bilateral anterior insula and basal ganglia that correlates with committing to the moral verdict “this is morally wrong” as opposed to “this is morally not wrong,” a finding that is consistent with research from economic decision-making. Using comparisons of deliberation-locked vs. verdict-locked analyses, we also demonstrate that hemodynamic activity in high-level cortical regions previously implicated in morality—including the ventromedial prefrontal cortex, posterior cingulate, and temporoparietal junction—correlates primarily with moral deliberation as opposed to moral verdicts. These findings provide new insights into what types of processes comprise the enterprise of moral judgment, and in doing so point to a framework for resolving why some clinical patients, including psychopaths, may have intact moral judgment but impaired moral behavior. PMID:21590588

  9. Tinnitus and neural plasticity of the brain

    NARCIS (Netherlands)

    Bartels, Hilke; Staal, Michiel J.; Albers, Frans W. J.

    Objective: To describe the current ideas about the manifestations of neural plasticity in generating tinnitus. Data Sources: Recently published source articles were identified using MEDLINE, PubMed, and Cochrane Library according to the key words mentioned below. Study Selection: Review articles and

  10. Diagnosis of Cervical Cancer Using the Median M-Type Radial Basis Function (MMRBF) Neural Network

    Science.gov (United States)

    Gómez-Mayorga, Margarita E.; Gallegos-Funes, Francisco J.; de-La-Rosa-Vázquez, José M.; Cruz-Santiago, Rene; Ponomaryov, Volodymyr

    The automatic analysis of Pap smear microscopic images is one of the most interesting fields in biomedical image processing. In this paper we present the capability of the Median M-Type Radial Basis Function (MMRBF) neural network in the classification of cervical cancer cells. From simulation results we observe that the MMRBF neural network has better classification capabilities in comparison with the Median RBF algorithm used as comparative.

  11. Upset Prediction in Friction Welding Using Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Wei Liu

    2013-01-01

    Full Text Available This paper addresses the upset prediction problem of friction welded joints. Based on finite element simulations of inertia friction welding (IFW, a radial basis function (RBF neural network was developed initially to predict the final upset for a number of welding parameters. The predicted joint upset by the RBF neural network was compared to validated finite element simulations, producing an error of less than 8.16% which is reasonable. Furthermore, the effects of initial rotational speed and axial pressure on the upset were investigated in relation to energy conversion with the RBF neural network. The developed RBF neural network was also applied to linear friction welding (LFW and continuous drive friction welding (CDFW. The correlation coefficients of RBF prediction for LFW and CDFW were 0.963 and 0.998, respectively, which further suggest that an RBF neural network is an effective method for upset prediction of friction welded joints.

  12. Neural basis of altered earlier attention and higher order biological motion processing in schizophrenia.

    Science.gov (United States)

    Matsumoto, Yukiko; Takahashi, Hideyuki; Miyata, Jun; Sugihara, Genichi; Murai, Toshiya; Takahashi, Hidehiko

    2017-08-25

    Schizophrenia patients have impairments of biological motion (BM) perception, which provides critical information about social cognition. Because social cognition is underpinned by attention, the impairments of BM perception in schizophrenia could be partially attributable to altered attention. To elucidate the impairments in attention and social perception in schizophrenia, we investigated the neural basis of impaired BM processing using MRI in respect to attention deficits by eye tracker. Voxel-based morphometry was performed to evaluate the relationship between BM perception and gray matter (GM) volume. The temporo-parietal junction (TPJ) and anterior superior temporal sulcus (aSTS) were related to task accuracy. However, when the effect of attention (i.e., eye movement) was controlled, the relationship in TPJ became non-significant, while aSTS showed a significant relationship with BM perception. Alteration in TPJ might be associated with inefficient attentional strategy, whereas dysfunctional aSTS might be correlated with deficit in higher order BM processing per se. Several cognitive levels as well as corresponding brain areas are possibly involved in the manifestation of social cognitive deficits in schizophrenia.

  13. Neural basis of music imagery and the effect of musical expertise.

    Science.gov (United States)

    Herholz, Sibylle C; Lappe, Claudia; Knief, Arne; Pantev, Christo

    2008-12-01

    Although the influence of long-term musical training on the processing of heard music has been the subject of many studies, the neural basis of music imagery and the effect of musical expertise remain insufficiently understood. By means of magnetoencephalography (MEG) we compared musicians and nonmusicians in a musical imagery task with familiar melodies. Subjects listened to the beginnings of the melodies, continued them in their imagination and then heard a tone which was either a correct or an incorrect further continuation of the melody. Only in musicians was the imagery of these melodies strong enough to elicit an early preattentive brain response to unexpected incorrect continuations of the imagined melodies; this response, the imagery mismatch negativity (iMMN), peaked approximately 175 ms after tone onset and was right-lateralized. In contrast to previous studies the iMMN was not based on a heard but on a purely imagined memory trace. Our results suggest that in trained musicians imagery and perception rely on similar neuronal correlates, and that the musicians' intense musical training has modified this network to achieve a superior ability for imagery and preattentive processing of music.

  14. The Application of Radial Basis Function (RBF) Neural Network for Mechanical Fault Diagnosis of Gearbox

    Science.gov (United States)

    Wang, Pengbo

    2017-11-01

    In this paper, the radial basis function (RBF) neural network is used for the mechanical fault diagnosis of a gearbox. We introduce the basic principles of the RBF neural network which is used for pattern classification and features a fast learning pace and strong nonlinear mapping capability; thus, it can be employed for fault diagnosis. The gearbox is a widely-used piece of equipment in engineering, and diagnosing mechanical faults is of great significance for engineers. A numerical example is presented to demonstrate the capability of the proposed method. The results indicate that the mechanical faults of a gearbox can be correctly diagnosed with a trained RBF neural network.

  15. Neural basis of moral elevation demonstrated through inter-subject synchronization of cortical activity during free-viewing.

    Directory of Open Access Journals (Sweden)

    Zoë A Englander

    Full Text Available Most research investigating the neural basis of social emotions has examined emotions that give rise to negative evaluations of others (e.g. anger, disgust. Emotions triggered by the virtues and excellences of others have been largely ignored. Using fMRI, we investigated the neural basis of two "other-praising" emotions--Moral Elevation (a response to witnessing acts of moral beauty, and Admiration (which we restricted to admiration for physical skill.Ten participants viewed the same nine video clips. Three clips elicited moral elevation, three elicited admiration, and three were emotionally neutral. We then performed pair-wise voxel-by-voxel correlations of the BOLD signal between individuals for each video clip and a separate resting-state run. We observed a high degree of inter-subject synchronization, regardless of stimulus type, across several brain regions during free-viewing of videos. Videos in the elevation condition evoked significant inter-subject synchronization in brain regions previously implicated in self-referential and interoceptive processes, including the medial prefrontal cortex, precuneus, and insula. The degree of synchronization was highly variable over the course of the videos, with the strongest synchrony occurring during portions of the videos that were independently rated as most emotionally arousing. Synchrony in these same brain regions was not consistently observed during the admiration videos, and was absent for the neutral videos.Results suggest that the neural systems supporting moral elevation are remarkably consistent across subjects viewing the same emotional content. We demonstrate that model-free techniques such as inter-subject synchronization may be a useful tool for studying complex, context dependent emotions such as self-transcendent emotion.

  16. Neural basis of moral elevation demonstrated through inter-subject synchronization of cortical activity during free-viewing.

    Science.gov (United States)

    Englander, Zoë A; Haidt, Jonathan; Morris, James P

    2012-01-01

    Most research investigating the neural basis of social emotions has examined emotions that give rise to negative evaluations of others (e.g. anger, disgust). Emotions triggered by the virtues and excellences of others have been largely ignored. Using fMRI, we investigated the neural basis of two "other-praising" emotions--Moral Elevation (a response to witnessing acts of moral beauty), and Admiration (which we restricted to admiration for physical skill). Ten participants viewed the same nine video clips. Three clips elicited moral elevation, three elicited admiration, and three were emotionally neutral. We then performed pair-wise voxel-by-voxel correlations of the BOLD signal between individuals for each video clip and a separate resting-state run. We observed a high degree of inter-subject synchronization, regardless of stimulus type, across several brain regions during free-viewing of videos. Videos in the elevation condition evoked significant inter-subject synchronization in brain regions previously implicated in self-referential and interoceptive processes, including the medial prefrontal cortex, precuneus, and insula. The degree of synchronization was highly variable over the course of the videos, with the strongest synchrony occurring during portions of the videos that were independently rated as most emotionally arousing. Synchrony in these same brain regions was not consistently observed during the admiration videos, and was absent for the neutral videos. Results suggest that the neural systems supporting moral elevation are remarkably consistent across subjects viewing the same emotional content. We demonstrate that model-free techniques such as inter-subject synchronization may be a useful tool for studying complex, context dependent emotions such as self-transcendent emotion.

  17. Statistical Physics, Neural Networks, Brain Studies

    OpenAIRE

    TOULOUSE, Gérard

    2014-01-01

    An overview of some aspects of a vast domain, located at the crossroads of physics, biology and computer science is presented: 1) During the last fifteen years, physicists advancing along various pathways have come into contact with biology (computational neurosciences) and engineering (formal neural nets). 2) This move may actually be viewed as one component in a larger picture. A prominent trend of recent years, observable over many countries, has been the establishment of interdis...

  18. Natural and artificial intelligence misconceptions about brains and neural networks

    CERN Document Server

    de Callataÿ, A

    1992-01-01

    How does the mind work? How is data stored in the brain? How does the mental world connect with the physical world? The hybrid system developed in this book shows a radically new view on the brain. Briefly, in this model memory remains permanent by changing the homeostasis rebuilding the neuronal organelles. These transformations are approximately abstracted as all-or-none operations. Thus the computer-like neural systems become plausible biological models. This illustrated book shows how artificial animals with such brains learn invariant methods of behavior control from their repeated action

  19. Neural basis of impaired safety signaling in Obsessive Compulsive Disorder.

    Science.gov (United States)

    Apergis-Schoute, Annemieke M; Gillan, Claire M; Fineberg, Naomi A; Fernandez-Egea, Emilio; Sahakian, Barbara J; Robbins, Trevor W

    2017-03-21

    The ability to assign safety to stimuli in the environment is integral to everyday functioning. A key brain region for this evaluation is the ventromedial prefrontal cortex (vmPFC). To investigate the importance of vmPFC safety signaling, we used neuroimaging of Pavlovian fear reversal, a paradigm that involves flexible updating when the contingencies for a threatening (CS+) and safe (CS-) stimulus reverse, in a prototypical disorder of inflexible behavior influenced by anxiety, Obsessive Compulsive Disorder (OCD). Skin conductance responses in OCD patients (n = 43) failed to differentiate during reversal compared with healthy controls (n = 35), although significant differentiation did occur during early conditioning and amygdala BOLD signaling was unaffected in these patients. Increased vmPFC activation (for CS+ > CS-) during early conditioning predicted the degree of generalization in OCD patients during reversal, whereas vmPFC safety signals were absent throughout learning in these patients. Regions of the salience network (dorsal anterior cingulate, insula, and thalamus) showed early learning task-related hyperconnectivity with the vmPFC in OCD, consistent with biased processing of the CS+. Our findings reveal an absence of vmPFC safety signaling in OCD, undermining flexible threat updating and explicit contingency knowledge. Although differential threat learning can occur to some extent in the absence of vmPFC safety signals, effective CS- signaling becomes crucial during conflicting threat and safety cues. These results promote further investigation of vmPFC safety signaling in other anxiety disorders, with potential implications for the development of exposure-based therapies, in which safety signaling is likely to play a key role.

  20. Both of us disgusted in My Insula : The common neural basis of seeing and feeling disgust

    NARCIS (Netherlands)

    Wicker, B; Keysers, C; Plailly, J; Royet, JP; Gallese, [No Value; Rizzolatti, G

    2003-01-01

    What neural mechanism underlies the capacity to understand the emotions of others? Does this mechanism involve brain areas normally involved in experiencing the same emotion? We performed an fMRI study in which participants inhaled odorants producing a strong feeling of disgust. The same

  1. The neural basis of economic decision-making in the ultimatum game

    NARCIS (Netherlands)

    Sanfey, A.G.; Rilling, J.K.; Aronson, J.A.; Nystrom, L.E.; Cohen, J.D.

    2003-01-01

    The nascent field of neuroeconomics seeks to ground economic decision-making in the biological substrate of the brain. We used functional magnetic resonance imaging of Ultimatum Game players to investigate neural substrates of cognitive and emotional processes involved in economic decision-making.

  2. Copine1 regulates neural stem cell functions during brain development.

    Science.gov (United States)

    Kim, Tae Hwan; Sung, Soo-Eun; Cheal Yoo, Jae; Park, Jae-Yong; Yi, Gwan-Su; Heo, Jun Young; Lee, Jae-Ran; Kim, Nam-Soon; Lee, Da Yong

    2018-01-01

    Copine 1 (CPNE1) is a well-known phospholipid binding protein in plasma membrane of various cell types. In brain cells, CPNE1 is closely associated with AKT signaling pathway, which is important for neural stem cell (NSC) functions during brain development. Here, we investigated the role of CPNE1 in the regulation of brain NSC functions during brain development and determined its underlying mechanism. In this study, abundant expression of CPNE1 was observed in neural lineage cells including NSCs and immature neurons in human. With mouse brain tissues in various developmental stages, we found that CPNE1 expression was higher at early embryonic stages compared to postnatal and adult stages. To model developing brain in vitro, we used primary NSCs derived from mouse embryonic hippocampus. Our in vitro study shows decreased proliferation and multi-lineage differentiation potential in CPNE1 deficient NSCs. Finally, we found that the deficiency of CPNE1 downregulated mTOR signaling in embryonic NSCs. These data demonstrate that CPNE1 plays a key role in the regulation of NSC functions through the activation of AKT-mTOR signaling pathway during brain development. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Todd, Faraday and the electrical basis of brain activity.

    Science.gov (United States)

    Reynolds, Edward

    2007-10-01

    The origins of our understanding of brain electricity and electrical discharges in epilepsy can be traced to Robert Bentley Todd (1809-60). Todd was influenced by his contemporary in London, Michael Faraday (1791-1867), who in the 1830 s and 1840 s was laying the foundations of our modern understanding of electromagnetism. Todd's concept of nervous polarity, generated in nerve vesicles and transmitted in nerve fibres (neurons in later terminology), was confirmed a century later by the Nobel Prize-winning work of Hodgkin and Huxley, who demonstrated the ionic basis of neuro-transmission, involving the same ions which had had been discovered by Faraday's mentor, Sir Humphry Davy (1778-1829).

  4. A growing and pruning sequential learning algorithm of hyper basis function neural network for function approximation.

    Science.gov (United States)

    Vuković, Najdan; Miljković, Zoran

    2013-10-01

    Radial basis function (RBF) neural network is constructed of certain number of RBF neurons, and these networks are among the most used neural networks for modeling of various nonlinear problems in engineering. Conventional RBF neuron is usually based on Gaussian type of activation function with single width for each activation function. This feature restricts neuron performance for modeling the complex nonlinear problems. To accommodate limitation of a single scale, this paper presents neural network with similar but yet different activation function-hyper basis function (HBF). The HBF allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The HBF is based on generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. Compared to the RBF, the HBF neuron has more parameters to optimize, but HBF neural network needs less number of HBF neurons to memorize relationship between input and output sets in order to achieve good generalization property. However, recent research results of HBF neural network performance have shown that optimal way of constructing this type of neural network is needed; this paper addresses this issue and modifies sequential learning algorithm for HBF neural network that exploits the concept of neuron's significance and allows growing and pruning of HBF neuron during learning process. Extensive experimental study shows that HBF neural network, trained with developed learning algorithm, achieves lower prediction error and more compact neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. A prediction method for the wax deposition rate based on a radial basis function neural network

    Directory of Open Access Journals (Sweden)

    Ying Xie

    2017-06-01

    Full Text Available The radial basis function neural network is a popular supervised learning tool based on machinery learning technology. Its high precision having been proven, the radial basis function neural network has been applied in many areas. The accumulation of deposited materials in the pipeline may lead to the need for increased pumping power, a decreased flow rate or even to the total blockage of the line, with losses of production and capital investment, so research on predicting the wax deposition rate is significant for the safe and economical operation of an oil pipeline. This paper adopts the radial basis function neural network to predict the wax deposition rate by considering four main influencing factors, the pipe wall temperature gradient, pipe wall wax crystal solubility coefficient, pipe wall shear stress and crude oil viscosity, by the gray correlational analysis method. MATLAB software is employed to establish the RBF neural network. Compared with the previous literature, favorable consistency exists between the predicted outcomes and the experimental results, with a relative error of 1.5%. It can be concluded that the prediction method of wax deposition rate based on the RBF neural network is feasible.

  6. A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

    Science.gov (United States)

    Hong, Xia

    2006-07-01

    In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

  7. Radial Basis Function Neural Network-based PID model for functional electrical stimulation system control.

    Science.gov (United States)

    Cheng, Longlong; Zhang, Guangju; Wan, Baikun; Hao, Linlin; Qi, Hongzhi; Ming, Dong

    2009-01-01

    Functional electrical stimulation (FES) has been widely used in the area of neural engineering. It utilizes electrical current to activate nerves innervating extremities affected by paralysis. An effective combination of a traditional PID controller and a neural network, being capable of nonlinear expression and adaptive learning property, supply a more reliable approach to construct FES controller that help the paraplegia complete the action they want. A FES system tuned by Radial Basis Function (RBF) Neural Network-based Proportional-Integral-Derivative (PID) model was designed to control the knee joint according to the desired trajectory through stimulation of lower limbs muscles in this paper. Experiment result shows that the FES system with RBF Neural Network-based PID model get a better performance when tracking the preset trajectory of knee angle comparing with the system adjusted by Ziegler- Nichols tuning PID model.

  8. METHODS OF TEXT INFORMATION CLASSIFICATION ON THE BASIS OF ARTIFICIAL NEURAL AND SEMANTIC NETWORKS

    OpenAIRE

    L. V. Serebryanaya; V. V. Potaraev

    2016-01-01

    The article covers the use of perseptron, Hopfild artificial neural network and semantic network for classification of text information. Network training algorithms are studied. An algorithm of inverse mistake spreading for perceptron network and convergence algorithm for Hopfild network are implemented. On the basis of the offered models and algorithms automatic text classification software is developed and its operation results are evaluated.

  9. Mechanisms and Neural Basis of Object and Pattern Recognition: A Study with Chess Experts

    Science.gov (United States)

    Bilalic, Merim; Langner, Robert; Erb, Michael; Grodd, Wolfgang

    2010-01-01

    Comparing experts with novices offers unique insights into the functioning of cognition, based on the maximization of individual differences. Here we used this expertise approach to disentangle the mechanisms and neural basis behind two processes that contribute to everyday expertise: object and pattern recognition. We compared chess experts and…

  10. The Molecular Basis of Neural Memory. Part 7: Neural Intelligence (NI versus Artificial Intelligence (AI

    Directory of Open Access Journals (Sweden)

    Gerard Marx

    2017-07-01

    Full Text Available The link of memory to intelligence is incontestable, though the development of electronic artifacts with memory has confounded cognitive and computer scientists’ conception of memory and its relevance to “intelligence”. We propose two categories of “Intelligence”: (1 Logical (objective — mathematics, numbers, pattern recognition, games, programmable in binary format. (2 Emotive (subjective — sensations, feelings, perceptions, goals desires, sociability, sex, food, love. The 1st has been reduced to computational algorithms of which we are well versed, witness global technology and the internet. The 2nd relates to the mysterious process whereby (psychic emotive states are achieved by neural beings sensing, comprehending, remembering and dealing with their surroundings. Many theories and philosophies have been forwarded to rationalize this process, but as neuroscientists, we remain dissatisfied. Our own musings on universal neural memory, suggest a tripartite mechanism involving neurons interacting with their surroundings, notably the neural extracellular matrix (nECM with dopants [trace metals and neurotransmitters (NTs]. In particular, the NTs are the molecular encoders of emotive states. We have developed a chemographic representation of such a molecular code.To quote Longuet-Higgins, “Perhaps it is time for the term ‘artificial intelligence’ to be replaced by something more modest and less provisional”. We suggest “artifact intelligence” (ARTI or “machine intelligence” (MI, neither of which imply emulation of emotive neural processes, but simply refer to the ‘demotive’ (lacking emotive quality capability of electronic artifacts that employ a recall function, to calculate algorithms.

  11. The Differential Role of Verbal and Spatial Working Memory in the Neural Basis of Arithmetic

    Science.gov (United States)

    Demir, Özlem Ece; Prado, Jérôme; Booth, James R.

    2014-01-01

    We examine the relations of verbal and spatial WM ability to the neural bases of arithmetic in school-age children. We independently localize brain regions subserving verbal versus spatial representations. For multiplication, higher verbal WM ability is associated with greater recruitment of the left temporal cortex, identified by the verbal localizer. For multiplication and subtraction, higher spatial WM ability is associated with greater recruitment of right parietal cortex, identified by the spatial localizer. Depending on their WM ability, children engage different neural systems that manipulate different representations to solve arithmetic problems. PMID:25144257

  12. Development of modularity in the neural activity of children's brains

    OpenAIRE

    Chen, Man; Deem, Michael W.

    2015-01-01

    We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. Head moti...

  13. Todd, Faraday, and the electrical basis of brain activity.

    Science.gov (United States)

    Reynolds, Edward H

    2004-09-01

    Robert Bentley Todd (1809-60) was the UK's first eminent neurologist and neuroscientist. An anatomist, physiologist, and clinical scientist with an interest in the nervous system, he was the first to confirm the electrical basis of brain activity in the 1840s. He was influenced by his contemporary, Michael Faraday at the Royal Institution, and by two colleagues at King's College, John Daniell and Charles Wheatstone, who were also working at the cutting edge of electrical science. Todd conceived of nervous polarity (force) generated in nervous centres and compared this with the polar force of voltaic electricity developed in the galvanic battery. He brilliantly foresaw each nerve vesicle (cell) and its related fibres (ie, neuron) as a distinct apparatus for the development and transmission of nervous polarity. Epilepsy was the result of periodic unnatural development of nervous force leading to the "disruptive discharge" described by Faraday. Faraday, who studied animal electricity in the Gymnotus (electric eel), and Todd saw nervous polarity as a higher form of interchangeable energy.

  14. BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

    Science.gov (United States)

    Kawahara, Jeremy; Brown, Colin J; Miller, Steven P; Booth, Brian G; Chau, Vann; Grunau, Ruth E; Zwicker, Jill G; Hamarneh, Ghassan

    2017-02-01

    We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is composed of novel edge-to-edge, edge-to-node and node-to-graph convolutional filters that leverage the topological locality of structural brain networks. We apply the BrainNetCNN framework to predict cognitive and motor developmental outcome scores from structural brain networks of infants born preterm. Diffusion tensor images (DTI) of preterm infants, acquired between 27 and 46 weeks gestational age, were used to construct a dataset of structural brain connectivity networks. We first demonstrate the predictive capabilities of BrainNetCNN on synthetic phantom networks with simulated injury patterns and added noise. BrainNetCNN outperforms a fully connected neural-network with the same number of model parameters on both phantoms with focal and diffuse injury patterns. We then apply our method to the task of joint prediction of Bayley-III cognitive and motor scores, assessed at 18 months of age, adjusted for prematurity. We show that our BrainNetCNN framework outperforms a variety of other methods on the same data. Furthermore, BrainNetCNN is able to identify an infant's postmenstrual age to within about 2 weeks. Finally, we explore the high-level features learned by BrainNetCNN by visualizing the importance of each connection in the brain with respect to predicting the outcome scores. These findings are then discussed in the context of the anatomy and function of the developing preterm infant brain. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Volumetric multimodality neural network for brain tumor segmentation

    Science.gov (United States)

    Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

    2017-11-01

    Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

  16. Computing single step operators of logic programming in radial basis function neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia)

    2014-07-10

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

  17. METHODS OF TEXT INFORMATION CLASSIFICATION ON THE BASIS OF ARTIFICIAL NEURAL AND SEMANTIC NETWORKS

    Directory of Open Access Journals (Sweden)

    L. V. Serebryanaya

    2016-01-01

    Full Text Available The article covers the use of perseptron, Hopfild artificial neural network and semantic network for classification of text information. Network training algorithms are studied. An algorithm of inverse mistake spreading for perceptron network and convergence algorithm for Hopfild network are implemented. On the basis of the offered models and algorithms automatic text classification software is developed and its operation results are evaluated.

  18. Neural Plastic Effects of Cognitive Training on Aging Brain.

    Science.gov (United States)

    Leung, Natalie T Y; Tam, Helena M K; Chu, Leung W; Kwok, Timothy C Y; Chan, Felix; Lam, Linda C W; Woo, Jean; Lee, Tatia M C

    2015-01-01

    Increasing research has evidenced that our brain retains a capacity to change in response to experience until late adulthood. This implies that cognitive training can possibly ameliorate age-associated cognitive decline by inducing training-specific neural plastic changes at both neural and behavioral levels. This longitudinal study examined the behavioral effects of a systematic thirteen-week cognitive training program on attention and working memory of older adults who were at risk of cognitive decline. These older adults were randomly assigned to the Cognitive Training Group (n = 109) and the Active Control Group (n = 100). Findings clearly indicated that training induced improvement in auditory and visual-spatial attention and working memory. The training effect was specific to the experience provided because no significant difference in verbal and visual-spatial memory between the two groups was observed. This pattern of findings is consistent with the prediction and the principle of experience-dependent neuroplasticity. Findings of our study provided further support to the notion that the neural plastic potential continues until older age. The baseline cognitive status did not correlate with pre- versus posttraining changes to any cognitive variables studied, suggesting that the initial cognitive status may not limit the neuroplastic potential of the brain at an old age.

  19. Assessing the Neural Basis of Uncertainty in Perceptual Category Learning through Varying Levels of Distortion

    Science.gov (United States)

    Daniel, Reka; Wagner, Gerd; Koch, Kathrin; Reichenbach, Jurgen R.; Sauer, Heinrich; Schlosser, Ralf G. M.

    2011-01-01

    The formation of new perceptual categories involves learning to extract that information from a wide range of often noisy sensory inputs, which is critical for selecting between a limited number of responses. To identify brain regions involved in visual classification learning under noisy conditions, we developed a task on the basis of the…

  20. Improved Radio Frequency Identification Indoor Localization Method via Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Dongliang Guo

    2014-01-01

    Full Text Available Indoor localization technique has received much attention in recent years. Many techniques have been developed to solve the problem. Among the recent proposed methods, radio frequency identification (RFID indoor localization technology has the advantages of low-cost, noncontact, non-line-of-sight, and high precision. This paper proposed two radial basis function (RBF neural network based indoor localization methods. The RBF neural networks are trained to learn the mapping relationship between received signal strength indication values and position of objects. Traditional method used the received signal strength directly as the input of neural network; we added another input channel by taking the difference of the received signal strength, thus improving the reliability and precision of positioning. Fuzzy clustering is used to determine the center of radial basis function. In order to reduce the impact of signal fading due to non-line-of-sight and multipath transmission in indoor environment, we improved the Gaussian filter to process received signal strength values. The experimental results show that the proposed method outperforms the existing methods as well as improves the reliability and precision of the RFID indoor positioning system.

  1. Neural Basis of Intrinsic Motivation: Evidence from Event-Related Potentials.

    Science.gov (United States)

    Jin, Jia; Yu, Liping; Ma, Qingguo

    2015-01-01

    Human intrinsic motivation is of great importance in human behavior. However, although researchers have focused on this topic for decades, its neural basis was still unclear. The current study employed event-related potentials to investigate the neural disparity between an interesting stop-watch (SW) task and a boring watch-stop task (WS) to understand the neural mechanisms of intrinsic motivation. Our data showed that, in the cue priming stage, the cue of the SW task elicited smaller N2 amplitude than that of the WS task. Furthermore, in the outcome feedback stage, the outcome of the SW task induced smaller FRN amplitude and larger P300 amplitude than that of the WS task. These results suggested that human intrinsic motivation did exist and that it can be detected at the neural level. Furthermore, intrinsic motivation could be quantitatively indexed by the amplitude of ERP components, such as N2, FRN, and P300, in the cue priming stage or feedback stage. Quantitative measurements would also be convenient for intrinsic motivation to be added as a candidate social factor in the construction of a machine learning model.

  2. Application of radial basis function neural network to predict soil sorption partition coefficient using topological descriptors.

    Science.gov (United States)

    Sabour, Mohammad Reza; Moftakhari Anasori Movahed, Saman

    2017-02-01

    The soil sorption partition coefficient logKoc is an indispensable parameter that can be used in assessing the environmental risk of organic chemicals. In order to predict soil sorption partition coefficient for different and even unknown compounds in a fast and accurate manner, a radial basis function neural network (RBFNN) model was developed. Eight topological descriptors of 800 organic compounds were used as inputs of the model. These 800 organic compounds were chosen from a large and very diverse data set. Generalized Regression Neural Network (GRNN) was utilized as the function in this neural network model due to its capability to adapt very quickly. Hence, it can be used to predict logKoc for new chemicals, as well. Out of total data set, 560 organic compounds were used for training and 240 to test efficiency of the model. The obtained results indicate that the model performance is very well. The correlation coefficients (R2) for training and test sets were 0.995 and 0.933, respectively. The root-mean square errors (RMSE) were 0.2321 for training set and 0.413 for test set. As the results for both training and test set are extremely satisfactory, the proposed neural network model can be employed not only to predict logKoc of known compounds, but also to be adaptive for prediction of this value precisely for new products that enter the market each year. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Neural Basis of Intrinsic Motivation: Evidence from Event-Related Potentials

    Directory of Open Access Journals (Sweden)

    Jia Jin

    2015-01-01

    Full Text Available Human intrinsic motivation is of great importance in human behavior. However, although researchers have focused on this topic for decades, its neural basis was still unclear. The current study employed event-related potentials to investigate the neural disparity between an interesting stop-watch (SW task and a boring watch-stop task (WS to understand the neural mechanisms of intrinsic motivation. Our data showed that, in the cue priming stage, the cue of the SW task elicited smaller N2 amplitude than that of the WS task. Furthermore, in the outcome feedback stage, the outcome of the SW task induced smaller FRN amplitude and larger P300 amplitude than that of the WS task. These results suggested that human intrinsic motivation did exist and that it can be detected at the neural level. Furthermore, intrinsic motivation could be quantitatively indexed by the amplitude of ERP components, such as N2, FRN, and P300, in the cue priming stage or feedback stage. Quantitative measurements would also be convenient for intrinsic motivation to be added as a candidate social factor in the construction of a machine learning model.

  4. A neural basis for password-based species recognition in an avian brood parasite.

    Science.gov (United States)

    Lynch, Kathleen S; Gaglio, Annmarie; Tyler, Elizabeth; Coculo, Joseph; Louder, Matthew I M; Hauber, Mark E

    2017-07-01

    Obligate avian brood parasites are raised by heterospecific hosts and, therefore, lack crucial early exposure to relatives and other conspecifics. Yet, young brood parasites readily recognize and affiliate with others of their own species upon independence. One solution to this social recognition paradox is the ontogenetic 'password' mechanism used by obligate parasitic brown-headed cowbirds (Molothrus ater), whereby conspecific identification is initially mediated through the cowbird chatter: a non-learned vocal cue. We explored the neural basis of such password-based species recognition in juvenile and adult male cowbirds. We found that cowbird auditory forebrain regions express greater densities of the protein product of the immediate-early gene ZENK in response to the password chatter call relative to control sounds of mourning dove (Zenaida macroura) coos. The chatter-selective induction of ZENK expression occurs in both the caudal medial nidopallium (NCM) and the caudal medial mesopallium (CMM) in adults, but only within the NCM in juveniles. In contrast, we discovered that juvenile cowbirds exhibit neural selectivity to presentations of either conspecific or heterospecific songs, but only in CMM and only after recent experience. Juvenile cowbirds that did not have previous experience with the song type they were exposed to during the test period exhibited significantly lower activity-dependent gene expression. Thus, in juvenile male cowbirds, there is early onset of species-specific selective neural representation of non-learned calls in NCM and recently experienced song in CMM. These results suggest that NCM is evolutionarily co-opted in parasitic cowbirds to selectively recognize the password chatter, allowing juvenile cowbirds to identify adult conspecifics and avoid mis-imprinting upon unrelated host species. These ontogenetic comparisons reveal novel insights into the neural basis of species recognition in brood parasitic species. © 2017. Published by

  5. Neural correlates of training-induced improvements of calculation skills in patients with brain lesions.

    Science.gov (United States)

    Claros-Salinas, Dolores; Greitemann, Georg; Hassa, Thomas; Nedelko, Violetta; Steppacher, Inga; Harris, Joseph Allen; Schoenfeld, Mircea Ariel

    2014-01-01

    The loss of calculation skills due to brain lesions leads to a major reduction in the quality of life and is often associated with difficulties of returning to work and a normal life. Very little is known about the neural mechanisms underlying performance improvement due to calculation training during rehabilitation. The current study investigates the neural basis of training-induced changes in patients with acalculia following ischemic stroke or traumatic brain lesions. Functional hemodynamic responses (fMRI) were recorded in seven patients during calculation and perceptual tasks both before and after acalculia training. Despite the heterogeneity of brain lesions associated with acalculia in our patient sample, a common pattern of training-induced changes emerged. Performance improvements were associated with widespread deactivations in the prefrontal cortex. These deactivations were calculation-specific and only observed in patients exhibiting a considerable improvement after training. These findings suggest that the training-induced changes in our patients rely on an increase of frontal processing efficiency.

  6. Long-range correlations in rabbit brain neural activity.

    Science.gov (United States)

    de la Fuente, I M; Perez-Samartin, A L; Martínez, L; Garcia, M A; Vera-Lopez, A

    2006-02-01

    We have analyzed the presence of persistence properties in rabbit brain electrical signals by means of non-equilibrium statistical physics tools. To measure long-memory properties of these experimental signals, we have first determined whether the data are fractional Gaussian noise (fGn) or fractional Brownian motion (fBm) by calculating the slope of the power spectral density plot of the series. The results show that the series correspond to fBm. Then, the data were studied by means of the bridge detrended scaled windowed variance analysis, detecting long-term correlation. Three different types of experimental signals have been studied: neural basal activity without stimulation, the response induced by a single flash light stimulus and the average of the activity evoked by 200 flash light stimulations. Analysis of the series revealed the existence of persistent behavior in all cases. Moreover, the results also exhibited an increasing correlation in the level of long-term memory from recordings without stimulation, to one sweep recording or 200 sweeps averaged recordings. Thus, brain neural electrical activity is affected not only by its most recent states, but also by previous states much more distant in the past.

  7. Noise Reduction Technique for Images using Radial Basis Function Neural Networks

    Directory of Open Access Journals (Sweden)

    Sander Ali Khowaja

    2014-07-01

    Full Text Available This paper presents a NN (Neural Network based model for reducing the noise from images. This is a RBF (Radial Basis Function network which is used to reduce the effect of noise and blurring from the captured images. The proposed network calculates the mean MSE (Mean Square Error and PSNR (Peak Signal to Noise Ratio of the noisy images. The proposed network has also been successfully applied to medical images. The performance of the trained RBF network has been compared with the MLP (Multilayer Perceptron Network and it has been demonstrated that the performance of the RBF network is better than the MLP network.

  8. Radial basis function neural networks with sequential learning MRAN and its applications

    CERN Document Server

    Sundararajan, N; Wei Lu Ying

    1999-01-01

    This book presents in detail the newly developed sequential learning algorithm for radial basis function neural networks, which realizes a minimal network. This algorithm, created by the authors, is referred to as Minimal Resource Allocation Networks (MRAN). The book describes the application of MRAN in different areas, including pattern recognition, time series prediction, system identification, control, communication and signal processing. Benchmark problems from these areas have been studied, and MRAN is compared with other algorithms. In order to make the book self-contained, a review of t

  9. Selective brain cooling and its vascular basis in diving seals.

    Science.gov (United States)

    Blix, Arnoldus Schytte; Walløe, Lars; Messelt, Edward B; Folkow, Lars P

    2010-08-01

    Brain (T(brain)), intra-aorta (T(aorta)), latissimus dorsi muscle (T(m)) and rectal temperature (T(r)) were measured in harp (Pagophilus groenlandicus) and hooded (Cystophora cristata) seals during experimental dives in 4 degrees C water. The median brain cooling was about 1 degrees C during 15 min diving, but in some cases it was as much as 2.5 degrees C. Cooling rates were slow for the first couple of minutes, but increased significantly after about 5 min of diving. The onset of cooling sometimes occurred before the start of the dive, confirming that the cooling is under cortical control, like the rest of the diving responses. T(aorta) also fell significantly, and was always lower than T(brain), while T(m) was fairly stable during dives. Detailed studies of the vascular anatomy of front flippers revealed that brachial arterial blood can be routed either through flipper skin capillaries for nutritive purposes and return through sophisticated vascular heat exchangers to avoid heat loss to the environment, or, alternatively, through numerous arterio-venous shunts in the skin and return by way of large superficial veins, which then carry cold blood to the heart. In the latter situation the extent to which the brain is cooled is determined by the ratio of carotid to brachial arterial blood flow, and water temperature, and the cooling is selective in that only those organs that are circulated will be cooled. It is concluded that T(brain) is actively down-regulated during diving, sometimes by as much as 2.5 degrees C, whereby cerebral oxygen requirements may be reduced by as much as 25% during extended dives.

  10. Model of brain activation predicts the neural collective influence map of the brain.

    Science.gov (United States)

    Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Stanley, H Eugene; Makse, Hernán A

    2017-04-11

    Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory.

  11. Sex, Lies and fMRI—Gender Differences in Neural Basis of Deception

    Science.gov (United States)

    Falkiewicz, Marcel; Szeszkowski, Wojciech; Grabowska, Anna; Szatkowska, Iwona

    2012-01-01

    Deception has always been a part of human communication as it helps to promote self-presentation. Although both men and women are equally prone to try to manage their appearance, their strategies, motivation and eagerness may be different. Here, we asked if lying could be influenced by gender on both the behavioral and neural levels. To test whether the hypothesized gender differences in brain activity related to deceptive responses were caused by differential socialization in men and women, we administered the Gender Identity Inventory probing the participants’ subjective social sex role. In an fMRI session, participants were instructed either to lie or to tell the truth while answering a questionnaire focusing on general and personal information. Only for personal information, we found differences in neural responses during instructed deception in men and women. The women vs. men direct contrast revealed no significant differences in areas of activation, but men showed higher BOLD signal compared to women in the left middle frontal gyrus (MFG). Moreover, this effect remained unchanged when self-reported psychological gender was controlled for. Thus, our study showed that gender differences in the neural processes engaged during falsifying personal information might be independent from socialization. PMID:22952631

  12. Sex, lies and fMRI--gender differences in neural basis of deception.

    Directory of Open Access Journals (Sweden)

    Artur Marchewka

    Full Text Available Deception has always been a part of human communication as it helps to promote self-presentation. Although both men and women are equally prone to try to manage their appearance, their strategies, motivation and eagerness may be different. Here, we asked if lying could be influenced by gender on both the behavioral and neural levels. To test whether the hypothesized gender differences in brain activity related to deceptive responses were caused by differential socialization in men and women, we administered the Gender Identity Inventory probing the participants' subjective social sex role. In an fMRI session, participants were instructed either to lie or to tell the truth while answering a questionnaire focusing on general and personal information. Only for personal information, we found differences in neural responses during instructed deception in men and women. The women vs. men direct contrast revealed no significant differences in areas of activation, but men showed higher BOLD signal compared to women in the left middle frontal gyrus (MFG. Moreover, this effect remained unchanged when self-reported psychological gender was controlled for. Thus, our study showed that gender differences in the neural processes engaged during falsifying personal information might be independent from socialization.

  13. Sex, lies and fMRI--gender differences in neural basis of deception.

    Science.gov (United States)

    Marchewka, Artur; Jednorog, Katarzyna; Falkiewicz, Marcel; Szeszkowski, Wojciech; Grabowska, Anna; Szatkowska, Iwona

    2012-01-01

    Deception has always been a part of human communication as it helps to promote self-presentation. Although both men and women are equally prone to try to manage their appearance, their strategies, motivation and eagerness may be different. Here, we asked if lying could be influenced by gender on both the behavioral and neural levels. To test whether the hypothesized gender differences in brain activity related to deceptive responses were caused by differential socialization in men and women, we administered the Gender Identity Inventory probing the participants' subjective social sex role. In an fMRI session, participants were instructed either to lie or to tell the truth while answering a questionnaire focusing on general and personal information. Only for personal information, we found differences in neural responses during instructed deception in men and women. The women vs. men direct contrast revealed no significant differences in areas of activation, but men showed higher BOLD signal compared to women in the left middle frontal gyrus (MFG). Moreover, this effect remained unchanged when self-reported psychological gender was controlled for. Thus, our study showed that gender differences in the neural processes engaged during falsifying personal information might be independent from socialization.

  14. Neural basis of stereotype-induced shifts in women's mental rotation performance.

    Science.gov (United States)

    Wraga, Maryjane; Helt, Molly; Jacobs, Emily; Sullivan, Kerry

    2007-03-01

    Recent negative focus on women's academic abilities has fueled disputes over gender disparities in the sciences. The controversy derives, in part, from women's relatively poorer performance in aptitude tests, many of which require skills of spatial reasoning. We used functional magnetic imaging to examine the neural structure underlying shifts in women's performance of a spatial reasoning task induced by positive and negative stereotypes. Three groups of participants performed a task involving imagined rotations of the self. Prior to scanning, the positive stereotype group was exposed to a false but plausible stereotype of women's superior perspective-taking abilities; the negative stereotype group was exposed to the pervasive stereotype that men outperform women on spatial tasks; and the control group received neutral information. The significantly poorer performance we found in the negative stereotype group corresponded to increased activation in brain regions associated with increased emotional load. In contrast, the significantly improved performance we found in the positive stereotype group was associated with increased activation in visual processing areas and, to a lesser degree, complex working memory processes. These findings suggest that stereotype messages affect the brain selectively, with positive messages producing relatively more efficient neural strategies than negative messages.

  15. Brain Basis of Phonological Awareness for Spoken Language in Children and Its Disruption in Dyslexia

    Science.gov (United States)

    Norton, Elizabeth S.; Christodoulou, Joanna A.; Gaab, Nadine; Lieberman, Daniel A.; Triantafyllou, Christina; Wolf, Maryanne; Whitfield-Gabrieli, Susan; Gabrieli, John D. E.

    2012-01-01

    Phonological awareness, knowledge that speech is composed of syllables and phonemes, is critical for learning to read. Phonological awareness precedes and predicts successful transition from language to literacy, and weakness in phonological awareness is a leading cause of dyslexia, but the brain basis of phonological awareness for spoken language in children is unknown. We used functional magnetic resonance imaging to identify the neural correlates of phonological awareness using an auditory word-rhyming task in children who were typical readers or who had dyslexia (ages 7–13) and a younger group of kindergarteners (ages 5–6). Typically developing children, but not children with dyslexia, recruited left dorsolateral prefrontal cortex (DLPFC) when making explicit phonological judgments. Kindergarteners, who were matched to the older children with dyslexia on standardized tests of phonological awareness, also recruited left DLPFC. Left DLPFC may play a critical role in the development of phonological awareness for spoken language critical for reading and in the etiology of dyslexia. PMID:21693783

  16. Neural basis of first and second language processing of sentence-level linguistic prosody.

    Science.gov (United States)

    Gandour, Jackson; Tong, Yunxia; Talavage, Thomas; Wong, Donald; Dzemidzic, Mario; Xu, Yisheng; Li, Xiaojian; Lowe, Mark

    2007-02-01

    A fundamental question in multilingualism is whether the neural substrates are shared or segregated for the two or more languages spoken by polyglots. This study employs functional MRI to investigate the neural substrates underlying the perception of two sentence-level prosodic phenomena that occur in both Mandarin Chinese (L1) and English (L2): sentence focus (sentence-initial vs. -final position of contrastive stress) and sentence type (declarative vs. interrogative modality). Late-onset, medium proficiency Chinese-English bilinguals were asked to selectively attend to either sentence focus or sentence type in paired three-word sentences in both L1 and L2 and make speeded-response discrimination judgments. L1 and L2 elicited highly overlapping activations in frontal, temporal, and parietal lobes. Furthermore, region of interest analyses revealed that for both languages the sentence focus task elicited a leftward asymmetry in the supramarginal gyrus; both tasks elicited a rightward asymmetry in the mid-portion of the middle frontal gyrus. A direct comparison between L1 and L2 did not show any difference in brain activation in the sentence type task. In the sentence focus task, however, greater activation for L2 than L1 occurred in the bilateral anterior insula and superior frontal sulcus. The sentence focus task also elicited a leftward asymmetry in the posterior middle temporal gyrus for L1 only. Differential activation patterns are attributed primarily to disparities between L1 and L2 in the phonetic manifestation of sentence focus. Such phonetic divergences lead to increased computational demands for processing L2. These findings support the view that L1 and L2 are mediated by a unitary neural system despite late age of acquisition, although additional neural resources may be required in task-specific circumstances for unequal bilinguals.

  17. The role of visual experience for the neural basis of spatial cognition.

    Science.gov (United States)

    Pasqualotto, Achille; Proulx, Michael J

    2012-04-01

    Blindness often results in the adaptive neural reorganization of the remaining modalities, producing sharper auditory and haptic behavioral performance. Yet, non-visual modalities might not be able to fully compensate for the lack of visual experience as in the case of congenital blindness. For example, developmental visual experience seems to be necessary for the maturation of multisensory neurons for spatial tasks. Additionally, the ability of vision to convey information in parallel might be taken into account as the main attribute that cannot be fully compensated by the spared modalities. Therefore, the lack of visual experience might impair all spatial tasks that require the integration of inputs from different modalities, such as having to represent a set of objects on the basis of the spatial relationships among the objects, rather than the spatial relationship that each object has with oneself. Here we integrate behavioral and neural evidence to conclude that visual experience is necessary for the neural development of normal spatial cognition. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Circular antenna array pattern analysis using radial basis function neural network

    Science.gov (United States)

    Rama Sanjeeva Reddy, B.; Vakula, D.; Sarma, N. V. S. N.

    2013-04-01

    A method is proposed to design circular antenna array for the given gain and beam width using Artificial Neural Networks. In optimizing circular arrays, the parameters to be controlled are excitation of the elements, their separation, lengths and the circle radius. This paper deals about finding the parameters of radiation pattern of given uniform circular antenna array. Initially, the network is trained with a set of input-output data pairs. The trained network is used for testing. The training data set is generated from MATLAB simulation with number of elements N=5, 10, 15 and 20 elements of uniform circular array, respectively, distributed over a given circle, assuming 20 training cases. The number of input nodes, hidden nodes and output nodes are 20, 20 and 1, respectively. Predicted values of the neural network are compared with those of MATLAB simulation results and are found to be in agreement. This work establishes the application of Radial Basis Function Neural Network (RBFNN) for circular array pattern optimization. RBFNN is able to predict the output values with 97% of accuracy. This work proves that RBFNN can be used for circular antenna array design.

  19. Commonality of neural representations of sentences across languages: Predicting brain activation during Portuguese sentence comprehension using an English-based model of brain function.

    Science.gov (United States)

    Yang, Ying; Wang, Jing; Bailer, Cyntia; Cherkassky, Vladimir; Just, Marcel Adam

    2017-02-01

    The aim of the study was to test the cross-language generative capability of a model that predicts neural activation patterns evoked by sentence reading, based on a semantic characterization of the sentence. In a previous study on English monolingual speakers (Wang et al., submitted), a computational model performed a mapping from a set of 42 concept-level semantic features (Neurally Plausible Semantic Features, NPSFs) as well as 6 thematic role markers to neural activation patterns (assessed with fMRI), to predict activation levels in a network of brain locations. The model used two types of information gained from the English-based fMRI data to predict the activation for individual sentences in Portuguese. First, it used the mapping weights from NPSFs to voxel activation levels derived from the model for English reading. Second, the brain locations for which the activation levels were predicted were derived from a factor analysis of the brain activation patterns during English reading. These meta-language locations were defined by the clusters of voxels with high loadings on each of the four main dimensions (factors), namely people, places, actions and feelings, underlying the neural representations of the stimulus sentences. This cross-language model succeeded in predicting the brain activation patterns associated with the reading of 60 individual Portuguese sentences that were entirely new to the model, attaining accuracies reliably above chance level. The prediction accuracy was not affected by whether the Portuguese speaker was monolingual or Portuguese-English bilingual. The model's confusion errors indicated an accurate capture of the events or states described in the sentence at a conceptual level. Overall, the cross-language predictive capability of the model demonstrates the neural commonality between speakers of different languages in the representations of everyday events and states, and provides an initial characterization of the common meta

  20. The neural basis for establishing a focal point in pure coordination games.

    Science.gov (United States)

    McMillan, Corey T; Rascovsky, Katya; Khella, M Catherine; Clark, Robin; Grossman, Murray

    2012-11-01

    When making a decision, humans often have to 'coordinate'-reach the same conclusion-as another individual without explicitly communicating. Relatively, little is known about the neural basis for coordination. Moreover, previous fMRI investigations have supported conflicting hypotheses. One account proposes that individuals coordinate using a 'gut feeling' and that this is supported by insula recruitment. Another account proposes that individuals recruit strategic decision-making mechanisms in prefrontal cortex in order to coordinate. We investigate the neural basis for coordination in individuals with behavioral-variant frontotemporal dementia (bvFTD) who have limitations in social decision-making associated with disease in prefrontal cortex. We demonstrate that bvFTD are impaired at establishing a focal point in a semantic task (e.g. 'Tell me any boy's name') that requires coordination relative to a similar, control semantic task that does not. Additionally, coordination limitations in bvFTD are related to cortical thinning in prefrontal cortex. These findings are consistent with behavioral economic models proposing that, beyond a 'gut feeling', strategic decision-making contributes to the coordination process, including a probabilistic mechanism that evaluates the salience of a response (e.g. is 'John' a frequent boy's name), a hierarchical mechanism that iteratively models an opponent's likely response and a mechanism involved in social perspective taking.

  1. Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

    Science.gov (United States)

    Świetlicka, Izabela; Muszyński, Siemowit; Marzec, Agata

    2015-04-01

    The presented work covers the problem of developing a method of extruded bread classification with the application of artificial neural networks. Extruded flat graham, corn, and rye breads differening in water activity were used. The breads were subjected to the compression test with simultaneous registration of acoustic signal. The amplitude-time records were analyzed both in time and frequency domains. Acoustic emission signal parameters: single energy, counts, amplitude, and duration acoustic emission were determined for the breads in four water activities: initial (0.362 for rye, 0.377 for corn, and 0.371 for graham bread), 0.432, 0.529, and 0.648. For classification and the clustering process, radial basis function, and self-organizing maps (Kohonen network) were used. Artificial neural networks were examined with respect to their ability to classify or to cluster samples according to the bread type, water activity value, and both of them. The best examination results were achieved by the radial basis function network in classification according to water activity (88%), while the self-organizing maps network yielded 81% during bread type clustering.

  2. Modeling brain resonance phenomena using a neural mass model.

    Directory of Open Access Journals (Sweden)

    Andreas Spiegler

    2011-12-01

    Full Text Available Stimulation with rhythmic light flicker (photic driving plays an important role in the diagnosis of schizophrenia, mood disorder, migraine, and epilepsy. In particular, the adjustment of spontaneous brain rhythms to the stimulus frequency (entrainment is used to assess the functional flexibility of the brain. We aim to gain deeper understanding of the mechanisms underlying this technique and to predict the effects of stimulus frequency and intensity. For this purpose, a modified Jansen and Rit neural mass model (NMM of a cortical circuit is used. This mean field model has been designed to strike a balance between mathematical simplicity and biological plausibility. We reproduced the entrainment phenomenon observed in EEG during a photic driving experiment. More generally, we demonstrate that such a single area model can already yield very complex dynamics, including chaos, for biologically plausible parameter ranges. We chart the entire parameter space by means of characteristic Lyapunov spectra and Kaplan-Yorke dimension as well as time series and power spectra. Rhythmic and chaotic brain states were found virtually next to each other, such that small parameter changes can give rise to switching from one to another. Strikingly, this characteristic pattern of unpredictability generated by the model was matched to the experimental data with reasonable accuracy. These findings confirm that the NMM is a useful model of brain dynamics during photic driving. In this context, it can be used to study the mechanisms of, for example, perception and epileptic seizure generation. In particular, it enabled us to make predictions regarding the stimulus amplitude in further experiments for improving the entrainment effect.

  3. Detection of neural activity in the brains of Japanese honeybee workers during the formation of a "hot defensive bee ball".

    Directory of Open Access Journals (Sweden)

    Atsushi Ugajin

    Full Text Available Anti-predator behaviors are essential to survival for most animals. The neural bases of such behaviors, however, remain largely unknown. Although honeybees commonly use their stingers to counterattack predators, the Japanese honeybee (Apis cerana japonica uses a different strategy to fight against the giant hornet (Vespa mandarinia japonica. Instead of stinging the hornet, Japanese honeybees form a "hot defensive bee ball" by surrounding the hornet en masse, killing it with heat. The European honeybee (A. mellifera ligustica, on the other hand, does not exhibit this behavior, and their colonies are often destroyed by a hornet attack. In the present study, we attempted to analyze the neural basis of this behavior by mapping the active brain regions of Japanese honeybee workers during the formation of a hot defensive bee ball. First, we identified an A. cerana homolog (Acks = Apis cerana kakusei of kakusei, an immediate early gene that we previously identified from A. mellifera, and showed that Acks has characteristics similar to kakusei and can be used to visualize active brain regions in A. cerana. Using Acks as a neural activity marker, we demonstrated that neural activity in the mushroom bodies, especially in Class II Kenyon cells, one subtype of mushroom body intrinsic neurons, and a restricted area between the dorsal lobes and the optic lobes was increased in the brains of Japanese honeybee workers involved in the formation of a hot defensive bee ball. In addition, workers exposed to 46°C heat also exhibited Acks expression patterns similar to those observed in the brains of workers involved in the formation of a hot defensive bee ball, suggesting that the neural activity observed in the brains of workers involved in the hot defensive bee ball mainly reflects thermal stimuli processing.

  4. Detection of neural activity in the brains of Japanese honeybee workers during the formation of a "hot defensive bee ball".

    Science.gov (United States)

    Ugajin, Atsushi; Kiya, Taketoshi; Kunieda, Takekazu; Ono, Masato; Yoshida, Tadaharu; Kubo, Takeo

    2012-01-01

    Anti-predator behaviors are essential to survival for most animals. The neural bases of such behaviors, however, remain largely unknown. Although honeybees commonly use their stingers to counterattack predators, the Japanese honeybee (Apis cerana japonica) uses a different strategy to fight against the giant hornet (Vespa mandarinia japonica). Instead of stinging the hornet, Japanese honeybees form a "hot defensive bee ball" by surrounding the hornet en masse, killing it with heat. The European honeybee (A. mellifera ligustica), on the other hand, does not exhibit this behavior, and their colonies are often destroyed by a hornet attack. In the present study, we attempted to analyze the neural basis of this behavior by mapping the active brain regions of Japanese honeybee workers during the formation of a hot defensive bee ball. First, we identified an A. cerana homolog (Acks = Apis cerana kakusei) of kakusei, an immediate early gene that we previously identified from A. mellifera, and showed that Acks has characteristics similar to kakusei and can be used to visualize active brain regions in A. cerana. Using Acks as a neural activity marker, we demonstrated that neural activity in the mushroom bodies, especially in Class II Kenyon cells, one subtype of mushroom body intrinsic neurons, and a restricted area between the dorsal lobes and the optic lobes was increased in the brains of Japanese honeybee workers involved in the formation of a hot defensive bee ball. In addition, workers exposed to 46°C heat also exhibited Acks expression patterns similar to those observed in the brains of workers involved in the formation of a hot defensive bee ball, suggesting that the neural activity observed in the brains of workers involved in the hot defensive bee ball mainly reflects thermal stimuli processing.

  5. Neural correlates of apathy in patients with neurodegenerative disorders, acquired brain injury, and psychiatric disorders.

    Science.gov (United States)

    Kos, Claire; van Tol, Marie-José; Marsman, Jan-Bernard C; Knegtering, Henderikus; Aleman, André

    2016-10-01

    Apathy can be described as a loss of goal-directed purposeful behavior and is common in a variety of neurological and psychiatric disorders. Although previous studies investigated associations between abnormal brain functioning and apathy, it is unclear whether the neural basis of apathy is similar across different pathological conditions. The purpose of this systematic review was to provide an extensive overview of the neuroimaging literature on apathy including studies of various patient populations, and evaluate whether the current state of affairs suggest disorder specific or shared neural correlates of apathy. Results suggest that abnormalities within fronto-striatal circuits are most consistently associated with apathy across the different pathological conditions. Of note, abnormalities within the inferior parietal cortex were also linked to apathy, a region previously not included in neuroanatomical models of apathy. The variance in brain regions implicated in apathy may suggest that different routes towards apathy are possible. Future research should investigate possible alterations in different processes underlying goal-directed behavior, ranging from intention and goal-selection to action planning and execution. Copyright © 2016. Published by Elsevier Ltd.

  6. Neural correlates of envy: Regional homogeneity of resting-state brain activity predicts dispositional envy.

    Science.gov (United States)

    Xiang, Yanhui; Kong, Feng; Wen, Xue; Wu, Qihan; Mo, Lei

    2016-11-15

    Envy differs from common negative emotions across cultures. Although previous studies have explored the neural basis of episodic envy via functional magnetic resonance imaging (fMRI), little is known about the neural processes associated with dispositional envy. In the present study, we used regional homogeneity (ReHo) as an index in resting-state fMRI (rs-fMRI) to identify brain regions involved in individual differences in dispositional envy, as measured by the Dispositional Envy Scale (DES). Results showed that ReHo in the inferior/middle frontal gyrus (IFG/MFG) and dorsomedial prefrontal cortex (DMPFC) positively predicted dispositional envy. Moreover, of all the personality traits measured by the Revised NEO Personality Inventory (NEO-PI-R), only neuroticism was significantly associated with dispositional envy. Furthermore, neuroticism mediated the underlying association between the ReHo of the IFG/MFG and dispositional envy. Hence, to the best of our knowledge, this study provides the first evidence that spontaneous brain activity in multiple regions related to self-evaluation, social perception, and social emotion contributes to dispositional envy. In addition, our findings reveal that neuroticism may play an important role in the cognitive processing of dispositional envy. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Computational Assessment of Neural Probe and Brain Tissue Interface under Transient Motion

    Directory of Open Access Journals (Sweden)

    Michael Polanco

    2016-06-01

    Full Text Available The functional longevity of a neural probe is dependent upon its ability to minimize injury risk during the insertion and recording period in vivo, which could be related to motion-related strain between the probe and surrounding tissue. A series of finite element analyses was conducted to study the extent of the strain induced within the brain in an area around a neural probe. This study focuses on the transient behavior of neural probe and brain tissue interface with a viscoelastic model. Different stages of the interface from initial insertion of neural probe to full bonding of the probe by astro-glial sheath formation are simulated utilizing analytical tools to investigate the effects of relative motion between the neural probe and the brain while friction coefficients and kinematic frequencies are varied. The analyses can provide an in-depth look at the quantitative benefits behind using soft materials for neural probes.

  8. Movement decoding using neural synchronization and inter-hemispheric connectivity from deep brain local field potentials.

    Science.gov (United States)

    Mamun, K A; Mace, M; Lutman, M E; Stein, J; Liu, X; Aziz, T; Vaidyanathan, R; Wang, S

    2015-10-01

    Correlating electrical activity within the human brain to movement is essential for developing and refining interventions (e.g. deep brain stimulation (DBS)) to treat central nervous system disorders. It also serves as a basis for next generation brain-machine interfaces (BMIs). This study highlights a new decoding strategy for capturing movement and its corresponding laterality from deep brain local field potentials (LFPs). LFPs were recorded with surgically implanted electrodes from the subthalamic nucleus or globus pallidus interna in twelve patients with Parkinson's disease or dystonia during a visually cued finger-clicking task. We introduce a method to extract frequency dependent neural synchronization and inter-hemispheric connectivity features based upon wavelet packet transform (WPT) and Granger causality approaches. A novel weighted sequential feature selection algorithm has been developed to select optimal feature subsets through a feature contribution measure. This is particularly useful when faced with limited trials of high dimensionality data as it enables estimation of feature importance during the decoding process. This novel approach was able to accurately and informatively decode movement related behaviours from the recorded LFP activity. An average accuracy of 99.8% was achieved for movement identification, whilst subsequent laterality classification was 81.5%. Feature contribution analysis highlighted stronger contralateral causal driving between the basal ganglia hemispheres compared to ipsilateral driving, with causality measures considerably improving laterality discrimination. These findings demonstrate optimally selected neural synchronization alongside causality measures related to inter-hemispheric connectivity can provide an effective control signal for augmenting adaptive BMIs. In the case of DBS patients, acquiring such signals requires no additional surgery whilst providing a relatively stable and computationally inexpensive control

  9. Toward a Neural Basis of Music Perception – A Review and Updated Model

    Science.gov (United States)

    Koelsch, Stefan

    2011-01-01

    Music perception involves acoustic analysis, auditory memory, auditory scene analysis, processing of interval relations, of musical syntax and semantics, and activation of (pre)motor representations of actions. Moreover, music perception potentially elicits emotions, thus giving rise to the modulation of emotional effector systems such as the subjective feeling system, the autonomic nervous system, the hormonal, and the immune system. Building on a previous article (Koelsch and Siebel, 2005), this review presents an updated model of music perception and its neural correlates. The article describes processes involved in music perception, and reports EEG and fMRI studies that inform about the time course of these processes, as well as about where in the brain these processes might be located. PMID:21713060

  10. Towards a neural basis of music perception -- A review and updated model

    Directory of Open Access Journals (Sweden)

    Stefan eKoelsch

    2011-06-01

    Full Text Available Music perception involves acoustic analysis, auditory memory, auditoryscene analysis, processing of interval relations, of musical syntax and semantics,and activation of (premotor representations of actions. Moreover, music percep-tion potentially elicits emotions, thus giving rise to the modulation of emotionaleffector systems such as the subjective feeling system, the autonomic nervoussystem, the hormonal, and the immune system. Building on a previous article(Koelsch & Siebel, 2005, this review presents an updated model of music percep-tion and its neural correlates. The article describes processes involved in musicperception, and reports EEG and fMRI studies that inform about the time courseof these processes, as well as about where in the brain these processes might belocated.

  11. Neural basis of self-initiative in relation to apathy in a student sample.

    Science.gov (United States)

    Kos, Claire; Klaasen, Nicky G; Marsman, Jan-Bernard C; Opmeer, Esther M; Knegtering, Henderikus; Aleman, André; van Tol, Marie-José

    2017-06-12

    Human behaviour can be externally driven, e.g. catching a falling glass, or self-initiated and goal-directed, e.g. drinking a cup of coffee when one deems it is time for a break. Apathy refers to a reduction of self-initiated goal-directed or motivated behaviour, frequently present in neurological and psychiatric disorders. The amount of undertaken goal-directed behaviour varies considerably in clinical as well as healthy populations. In the present study, we investigated behavioural and neural correlates of self-initiated action in a student sample (N = 39) with minimal to high levels of apathy. We replicated activation of fronto-parieto-striatal regions during self-initiation. The neural correlates of self-initiated action did not explain varying levels of apathy in our sample, neither when mass-univariate analysis was used, nor when multivariate patterns of brain activation were considered. Other hypotheses, e.g. regarding a putative role of deficits in reward anticipation, effort expenditure or executive difficulties, deserve investigation in future studies.

  12. Reducing the neural search space for hominid cognition: what distinguishes human and great ape brains from those of small apes?

    Science.gov (United States)

    Butler, David; Suddendorf, Thomas

    2014-06-01

    Differences in the psychological capacities of closely related species are likely due to differences in their brains. Here, we review neuroanatomical comparisons between hominids (i.e., great apes and humans) and their closest living relatives, the hylobatids (i.e., small apes). We report the differences in quantitative, as well as qualitative, neural characteristics on the basis of 19 comparative studies that each included representatives of all hominid genera and at least one genus of hylobatid. The current data are patchy, based on a small number of hylobatids and few neuroanatomical features. Yet a systematic interspecies comparison could help reduce the neuroanatomical search space for the neural correlates underlying psychological abilities restricted to hominids. We illustrate the potential power of this approach by discussing the neural features of visual self-recognition.

  13. Neural basis of stimulus-angle-dependent motor control of wind-elicited walking behavior in the cricket Gryllus bimaculatus.

    Directory of Open Access Journals (Sweden)

    Momoko Oe

    Full Text Available Crickets exhibit oriented walking behavior in response to air-current stimuli. Because crickets move in the opposite direction from the stimulus source, this behavior is considered to represent 'escape behavior' from an approaching predator. However, details of the stimulus-angle-dependent control of locomotion during the immediate phase, and the neural basis underlying the directional motor control of this behavior remain unclear. In this study, we used a spherical-treadmill system to measure locomotory parameters including trajectory, turn angle and velocity during the immediate phase of responses to air-puff stimuli applied from various angles. Both walking direction and turn angle were correlated with stimulus angle, but their relationships followed different rules. A shorter stimulus also induced directionally-controlled walking, but reduced the yaw rotation in stimulus-angle-dependent turning. These results suggest that neural control of the turn angle requires different sensory information than that required for oriented walking. Hemi-severance of the ventral nerve cords containing descending axons from the cephalic to the prothoracic ganglion abolished stimulus-angle-dependent control, indicating that this control required descending signals from the brain. Furthermore, we selectively ablated identified ascending giant interneurons (GIs in vivo to examine their functional roles in wind-elicited walking. Ablation of GI8-1 diminished control of the turn angle and decreased walking distance in the initial response. Meanwhile, GI9-1b ablation had no discernible effect on stimulus-angle-dependent control or walking distance, but delayed the reaction time. These results suggest that the ascending signals conveyed by GI8-1 are required for turn-angle control and maintenance of walking behavior, and that GI9-1b is responsible for rapid initiation of walking. It is possible that individual types of GIs separately supply the sensory signals

  14. The neural and psychological basis of herding in purchasing books online: an event-related potential study.

    Science.gov (United States)

    Chen, Mingliang; Ma, Qingguo; Li, Minle; Dai, Shenyi; Wang, Xiaoyi; Shu, Liangchao

    2010-06-01

    In this study, event-related brain potentials (ERPs) were used to investigate the neural and psychological bases of consumer herding decision in purchasing books online. Sixteen participants were asked to decide as quickly as possible whether to buy a book on the basis of its title keywords and the numbers of positive and negative reviews in stimulus. The given title keywords were very similar, and participants did not have special preference for any particular one. Hence, they were forced to adopt the strategy of herding decision: choosing to buy the book when there were consistent positive reviews, choosing not to buy when there were consistent negative reviews, randomly choosing to buy or not to buy when there were no consistent reviews. The herding decision triggers a categorical processing of the consistency level of customer reviews. Remarkable late positive potential (LPP), a component of ERP sensitive to categorization processes, was elicited. The LPP amplitudes varied as a function of review consistency. The LPP amplitudes for three categories of review consistency were significantly different, and their order is such that absolute consistent review was greater than relative consistent review, which was greater than inconsistent review. In addition, behavioral data revealed that the higher the consistency of the customer reviews, the higher the herd rate. It is possible that customer reviews with higher consistency let participants make herding decisions more resolutely. The present results suggest that the LPP may be regarded as an endogenous neural signal of the herding mechanism in a sense and that the LPP amplitude is potentially a measure of consumers' herd tendency in purchase decisions.

  15. Beyond laterality: a critical assessment of research on the neural basis of metaphor.

    Science.gov (United States)

    Schmidt, Gwenda L; Kranjec, Alexander; Cardillo, Eileen R; Chatterjee, Anjan

    2010-01-01

    Metaphors are a fundamental aspect of human cognition. The major neuropsychological hypothesis that metaphoric processing relies primarily on the right hemisphere is not confirmed consistently. We propose ways to advance our understanding of the neuropsychology of metaphor that go beyond simple laterality. Neuropsychological studies need to more carefully control confounding lexical and sentential factors, and consider the role of different parts of speech as they are extended metaphorically. They need to incorporate recent theoretical frameworks such as the career of metaphor theory, and address factors such as novelty. We also advocate the use of new methods such as voxel-based lesion-symptom mapping, which permits precise and formal tests of hypotheses correlating behavior with lesions sites. Finally, we outline a plausible model for the neural basis of metaphor. (JINS, 2009, 16, 1-5.).

  16. Forecasting of PT. PLN (Persero) revenue using radial basis function neural network

    Science.gov (United States)

    Junior, Cindy Fajarianti; Suprijadi, Jadi; Franty, Yeny Krista

    2017-03-01

    PT. PLN (Persero) Distribusi Jakarta Raya (Disjaya) is a government-owned company that job is to maintain electricity distribution in Jakarta and Tangerang. The company's revenue can be seen from the pattern of the existing data, constantly increasing every year. This research aims to forecast company's revenue. The forecasting method using Artificial Neural Network method with Radial Basis Function (RBF) model based on historic data from January 2010 to December 2015. Based on the result of this research, the best model obtained (1-6-1) with composition 1 Neuron from input layer, 6 Neuron from hidden layer, and 1 Neuron output layer. The MAPE obtained with this model is 1.32 %.

  17. Beyond Laterality: A Critical Assessment of Research on the Neural Basis of Metaphor

    Science.gov (United States)

    Schmidt, Gwenda L.; Kranjec, Alexander; Cardillo, Eileen R.; Chatterjee, Anjan

    2010-01-01

    Metaphors are a fundamental aspect of human cognition. The major neuropsychological hypothesis that metaphoric processing relies primarily on the right hemisphere is not confirmed consistently. We propose ways to advance our understanding of the neuropsychology of metaphor that go beyond simple laterality. Neuropsychological studies need to more carefully control confounding lexical and sentential factors, and consider the role of different parts of speech as they are extended metaphorically. They need to incorporate recent theoretical frameworks such as the career of metaphor theory, and address factors such as novelty. We also advocate the use of new methods such as voxel-based lesion-symptom mapping, which permits precise and formal tests of hypotheses correlating behavior with lesions sites. Finally, we outline a plausible model for the neural basis of metaphor. PMID:19765354

  18. Hybrid model decomposition of speech and noise in a radial basis function neural model framework

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe

    1994-01-01

    The aim of the paper is to focus on a new approach to automatic speech recognition in noisy environments where the noise has either stationary or non-stationary statistical characteristics. The aim is to perform automatic recognition of speech in the presence of additive car noise. The technique...... applied is based on a combination of the hidden Markov model (HMM) decomposition method, for speech recognition in noise, developed by Varga and Moore (1990) from DRA and the hybrid (HMM/RBF) recognizer containing hidden Markov models and radial basis function (RBF) neural networks, developed by Singer...... and Lippmann (1992) from MIT Lincoln Lab. The present authors modified the hybrid recognizer to fit into the decomposition method to achieve high performance speech recognition in noisy environments. The approach has been denoted the hybrid model decomposition method and it provides an optimal method...

  19. Tracting the neural basis of music: Deficient structural connectivity underlying acquired amusia.

    Science.gov (United States)

    Sihvonen, Aleksi J; Ripollés, Pablo; Särkämö, Teppo; Leo, Vera; Rodríguez-Fornells, Antoni; Saunavaara, Jani; Parkkola, Riitta; Soinila, Seppo

    2017-12-01

    Acquired amusia provides a unique opportunity to investigate the fundamental neural architectures of musical processing due to the transition from a functioning to defective music processing system. Yet, the white matter (WM) deficits in amusia remain systematically unexplored. To evaluate which WM structures form the neural basis for acquired amusia and its recovery, we studied 42 stroke patients longitudinally at acute, 3-month, and 6-month post-stroke stages using DTI [tract-based spatial statistics (TBSS) and deterministic tractography (DT)] and the Scale and Rhythm subtests of the Montreal Battery of Evaluation of Amusia (MBEA). Non-recovered amusia was associated with structural damage and subsequent degeneration in multiple WM tracts including the right inferior fronto-occipital fasciculus (IFOF), arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), uncinate fasciculus (UF), and frontal aslant tract (FAT), as well as in the corpus callosum (CC) and its posterior part (tapetum). In a linear regression analysis, the volume of the right IFOF was the main predictor of MBEA performance across time. Overall, our results provide a comprehensive picture of the large-scale deficits in intra- and interhemispheric structural connectivity underlying amusia, and conversely highlight which pathways are crucial for normal music perception. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. The neural basis of nonvisual object recognition memory in the rat.

    Science.gov (United States)

    Albasser, Mathieu M; Olarte-Sánchez, Cristian M; Amin, Eman; Horne, Murray R; Newton, Michael J; Warburton, E Clea; Aggleton, John P

    2013-02-01

    Research into the neural basis of recognition memory has traditionally focused on the remembrance of visual stimuli. The present study examined the neural basis of object recognition memory in the dark, with a view to determining the extent to which it shares common pathways with visual-based object recognition. Experiment 1 assessed the expression of the immediate-early gene c-fos in rats that discriminated novel from familiar objects in the dark (Group Novel). Comparisons made with a control group that explored only familiar objects (Group Familiar) showed that Group Novel had higher c-fos activity in the rostral perirhinal cortex and the lateral entorhinal cortex. Outside the temporal region, Group Novel showed relatively increased c-fos activity in the anterior medial thalamic nucleus and the anterior cingulate cortex. Both the hippocampal CA fields and the granular retrosplenial cortex showed borderline increases in c-fos activity with object novelty. The hippocampal findings prompted Experiment 2. Here, rats with hippocampal lesions were tested in the dark for object recognition memory at different retention delays. Across two replications, no evidence was found that hippocampal lesions impair nonvisual object recognition. The results indicate that in the dark, as in the light, interrelated parahippocampal sites are activated when rats explore novel stimuli. These findings reveal a network of linked c-fos activations that share superficial features with those associated with visual recognition but differ in the fine details; for example, in the locus of the perirhinal cortex activation. While there may also be a relative increase in c-fos activation in the extended-hippocampal system to object recognition in the dark, there was no evidence that this recognition memory problem required an intact hippocampus. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  1. Vibration control of uncertain multiple launch rocket system using radial basis function neural network

    Science.gov (United States)

    Li, Bo; Rui, Xiaoting

    2018-01-01

    Poor dispersion characteristics of rockets due to the vibration of Multiple Launch Rocket System (MLRS) have always restricted the MLRS development for several decades. Vibration control is a key technique to improve the dispersion characteristics of rockets. For a mechanical system such as MLRS, the major difficulty in designing an appropriate control strategy that can achieve the desired vibration control performance is to guarantee the robustness and stability of the control system under the occurrence of uncertainties and nonlinearities. To approach this problem, a computed torque controller integrated with a radial basis function neural network is proposed to achieve the high-precision vibration control for MLRS. In this paper, the vibration response of a computed torque controlled MLRS is described. The azimuth and elevation mechanisms of the MLRS are driven by permanent magnet synchronous motors and supposed to be rigid. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, in order to deal with the nonlinearities, a computed torque controller is designed to control the vibration of the MLRS when it is firing a salvo of rockets. Furthermore, to compensate for the lumped uncertainty due to parametric variations and un-modeled dynamics in the design of the computed torque controller, a radial basis function neural network estimator is developed to adapt the uncertainty based on Lyapunov stability theory. Finally, the simulated results demonstrate the effectiveness of the proposed control system and show that the proposed controller is robust with regard to the uncertainty.

  2. Age and experience shape developmental changes in the neural basis of language-related learning.

    Science.gov (United States)

    McNealy, Kristin; Mazziotta, John C; Dapretto, Mirella

    2011-11-01

    Very little is known about the neural underpinnings of language learning across the lifespan and how these might be modified by maturational and experiential factors. Building on behavioral research highlighting the importance of early word segmentation (i.e. the detection of word boundaries in continuous speech) for subsequent language learning, here we characterize developmental changes in brain activity as this process occurs online, using data collected in a mixed cross-sectional and longitudinal design. One hundred and fifty-six participants, ranging from age 5 to adulthood, underwent functional magnetic resonance imaging (fMRI) while listening to three novel streams of continuous speech, which contained either strong statistical regularities, strong statistical regularities and speech cues, or weak statistical regularities providing minimal cues to word boundaries. All age groups displayed significant signal increases over time in temporal cortices for the streams with high statistical regularities; however, we observed a significant right-to-left shift in the laterality of these learning-related increases with age. Interestingly, only the 5- to 10-year-old children displayed significant signal increases for the stream with low statistical regularities, suggesting an age-related decrease in sensitivity to more subtle statistical cues. Further, in a sample of 78 10-year-olds, we examined the impact of proficiency in a second language and level of pubertal development on learning-related signal increases, showing that the brain regions involved in language learning are influenced by both experiential and maturational factors. 2011 Blackwell Publishing Ltd.

  3. Neural Basis of Psychological Growth following Adverse Experiences: A Resting-State Functional MRI Study.

    Directory of Open Access Journals (Sweden)

    Takashi X Fujisawa

    Full Text Available Over the past decade, research on the aftereffects of stressful or traumatic events has emphasized the negative outcomes from these experiences. However, the positive outcomes deriving from adversity are increasingly being examined, and such positive changes are described as posttraumatic growth (PTG. To investigate the relationship between basal whole-brain functional connectivity and PTG, we employed resting-state functional magnetic resonance imaging and analyzed the neural networks using independent component analysis in a sample of 33 healthy controls. Correlations were calculated between the network connectivity strength and the Posttraumatic Growth Inventory (PTGI score. There were positive associations between the PTGI scores and brain activation in the rostral prefrontal cortex and superior parietal lobule (SPL within the left central executive network (CEN (respectively, r = 0.41, p < 0.001; r = 0.49, p < 0.001. Individuals with higher psychological growth following adverse experiences had stronger activation in prospective or working memory areas within the executive function network than did individuals with lower psychological growth (r = 0.40, p < 0.001. Moreover, we found that individuals with higher PTG demonstrated stronger connectivity between the SPL and supramarginal gyrus (SMG. The SMG is one of the brain regions associated with the ability to reason about the mental states of others, otherwise known as mentalizing. These findings suggest that individuals with higher psychological growth may have stronger functional connectivity between memory functions within the CEN and social functioning in the SMG, and that their better sociality may result from using more memory for mentalizing during their daily social interactions.

  4. Rescue of Brain Function Using Tunneling Nanotubes Between Neural Stem Cells and Brain Microvascular Endothelial Cells.

    Science.gov (United States)

    Wang, Xiaoqing; Yu, Xiaowen; Xie, Chong; Tan, Zijian; Tian, Qi; Zhu, Desheng; Liu, Mingyuan; Guan, Yangtai

    2016-05-01

    Evidence indicates that neural stem cells (NSCs) can ameliorate cerebral ischemia in animal models. In this study, we investigated the mechanism underlying one of the neuroprotective effects of NSCs: tunneling nanotube (TNT) formation. We addressed whether the control of cell-to-cell communication processes between NSCs and brain microvascular endothelial cells (BMECs) and, particularly, the control of TNT formation could influence the rescue function of stem cells. In an attempt to mimic the cellular microenvironment in vitro, a co-culture system consisting of terminally differentiated BMECs from mice in a distressed state and NSCs was constructed. Additionally, engraftment experiments with infarcted mouse brains revealed that control of TNT formation influenced the effects of stem cell transplantation in vivo. In conclusion, our findings provide the first evidence that TNTs exist between NSCs and BMECs and that regulation of TNT formation alters cell function.

  5. Using a Novel Motion Index to Study the Neural Basis of Event Segmentation

    Directory of Open Access Journals (Sweden)

    Frank Pollick

    2012-05-01

    Full Text Available Our understanding of the perceived actions of those around us includes an ability to segment this continuous stream of activity into discrete events. We studied naïve observers' abilities to segment a video of an unfamiliar dance style into events using a combination of behavioural, computational vision and brain imaging methods. A 386 s video of a solo Bharatanatyam dancer was used as the basis for the study. A computational analysis provided us with, for every video frame, a Motion Index (MI quantifying the movement of the entire dancer. A behavioural analysis using 30 naïve observers provided us with the time points where observers were most likely to place an event boundary. These behavioural and computational data were used to interpret the brain activity of another 11 participants who viewed the dance video while in an MRI scanner. Results showed that the Motion Index predicted brain activity in a single cluster in the right hemisphere that was located close to the Extrastriate Body Area (EBA. Event boundaries in the video were related to extensive clusters of bilateral activity in the Inferior Occipital Gyrus which extended towards the posterior Superior Temporal Sulcus (pSTS. Event boundaries also activated a region in the right Inferior Frontal Gyrus. These results extend our understanding of how movement kinaesthetics modulate action interpretation.

  6. Neural Basis of Cognitive Assessment in Alzheimer Disease, Amnestic Mild Cognitive Impairment, and Subjective Memory Complaints.

    Science.gov (United States)

    Matías-Guiu, Jordi A; Cabrera-Martín, María Nieves; Valles-Salgado, María; Pérez-Pérez, Alicia; Rognoni, Teresa; Moreno-Ramos, Teresa; Carreras, José Luis; Matías-Guiu, Jorge

    2017-07-01

    Interpreting cognitive tests is often challenging. The same test frequently examines multiple cognitive functions, and the functional and anatomical basis underlying test performance is unknown in many cases. This study analyses the correlation of different neuropsychological test results with brain metabolism in a series of patients evaluated for suspected Alzheimer disease. 20 healthy controls and 80 patients consulting for memory loss were included, in which cognitive study and (18)F-fluorodeoxyglucose PET were performed. Patients were categorized according to Reisberg's Global Deterioration Scale. Voxel-based analysis was used to determine correlations between brain metabolism and performance on the following tests: Free and Cued Selective Reminding Test (FCSRT), Boston Naming Test (BNT), Trail Making Test, Rey-Osterrieth Complex Figure test, Visual Object and Space Perception Battery (VOSP), and Tower of London (ToL) test. Mean age in the patient group was 73.9 ± 10.6 years, and 47 patients were women (58.7%). FCSRT findings were positively correlated with metabolism in the medial and anterior temporal region bilaterally, the left precuneus, and posterior cingulate. BNT results were correlated with metabolism in the middle temporal, superior, fusiform, and frontal medial gyri bilaterally. VOSP results were related to the occipital and parietotemporal regions bilaterally. ToL scores were correlated to metabolism in the right temporoparietal and frontal regions. These results suggest that different areas of the brain are involved in the processes required to complete different cognitive tests. Ascertaining the functional basis underlying these tests may prove helpful for understanding and interpreting them. Copyright © 2017 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

  7. Assessment of Global Voltage Stability Margin through Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Akash Saxena

    2016-01-01

    Full Text Available Dynamic operating conditions along with contingencies often present formidable challenges to the power engineers. Decisions pertaining to the control strategies taken by the system operators at energy management centre are based on the information about the system’s behavior. The application of ANN as a tool for voltage stability assessment is empirical because of its ability to do parallel data processing with high accuracy, fast response, and capability to model dynamic, nonlinear, and noisy data. This paper presents an effective methodology based on Radial Basis Function Neural Network (RBFN to predict Global Voltage Stability Margin (GVSM, for any unseen loading condition of the system. GVSM is used to assess the overall voltage stability status of the power system. A comparative analysis of different topologies of ANN, namely, Feedforward Backprop (FFBP, Cascade Forward Backprop (CFB, Generalized Regression (GR, Layer Recurrent (LR, Nonlinear Autoregressive Exogenous (NARX, ELMAN Backprop, and Feedforward Distributed Time Delay Network (FFDTDN, is carried out on the basis of capability of the prediction of GVSM. The efficacy of RBFN is better than other networks, which is validated by taking the predictions of GVSM at different levels of Additive White Gaussian Noise (AWGN in input features. The results obtained from ANNs are validated through the offline Newton Raphson (N-R method. The proposed methodology is tested over IEEE 14-bus, IEEE 30-bus, and IEEE 118-bus test systems.

  8. Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm. (On-Line Harmonics Estimation Application

    Directory of Open Access Journals (Sweden)

    Eyad K Almaita

    2017-03-01

    Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application.  International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17

  9. Engineering the Brain: Ethical Issues and the Introduction of Neural Devices.

    Science.gov (United States)

    Klein, Eran; Brown, Tim; Sample, Matthew; Truitt, Anjali R; Goering, Sara

    2015-01-01

    Neural devices now under development stand to interact with and alter the human brain in ways that may challenge standard notions of identity, normality, authority, responsibility, privacy and justice.

  10. Localization of neural efficiency of the mathematically gifted brain through a feature subset selection method

    OpenAIRE

    Zhang, Li; Gan, John Q.; Wang, Haixian

    2015-01-01

    Based on the neural efficiency hypothesis and task-induced EEG gamma-band response (GBR), this study investigated the brain regions where neural resource could be most efficiently recruited by the math-gifted adolescents in response to varying cognitive demands. In this experiment, various GBR-based mental states were generated with three factors (level of mathematical ability, task complexity, and short-term learning) modulating the level of neural activation. A feature subset selection meth...

  11. Embryonic cerebrospinal fluid activates neurogenesis of neural precursors within the subventricular zone of the adult mouse brain.

    Science.gov (United States)

    Carnicero, E; Alonso, M I; Carretero, R; Lamus, F; Moro, J A; de la Mano, A; Fernández, J M F; Gato, A

    2013-01-01

    There is a nondeveloped neurogenic potential in the adult mammalian brain, which could be the basis for neuroregenerative strategies. Many research efforts have been made to understand the control mechanisms which regulate the transition from a neural precursor to a neuron in the adult brain. Embryonic cerebrospinal fluid (CSF) is a complex fluid which has been shown to play a key role in neural precursor behavior during development, working as a powerful neurogenic inductor. We tested if the neurogenic properties of embryonic CSF are able to increase the neurogenic activity of neuronal precursors from the subventricular zone (SVZ) in the brains of adult mice. Our results show that mouse embryonic CSF significantly increases the neurogenic activity in precursor cells from adult brain SVZ. This intense neurogenic effect was specific for embryonic CSF and was not induced by adult CSF. Embryonic CSF is a powerful neurogenesis inductor in homologous neuronal precursors in the adult brain. This property of embryonic CSF could be a useful tool in neuroregeneration strategies.

  12. Embryonic cerebrospinal fluid in brain development: neural progenitor control.

    Science.gov (United States)

    Gato, Angel; Alonso, M Isabel; Martín, Cristina; Carnicero, Estela; Moro, José Antonio; De la Mano, Aníbal; Fernández, José M F; Lamus, Francisco; Desmond, Mary E

    2014-08-28

    Due to the effort of several research teams across the world, today we have a solid base of knowledge on the liquid contained in the brain cavities, its composition, and biological roles. Although the cerebrospinal fluid (CSF) is among the most relevant parts of the central nervous system from the physiological point of view, it seems that it is not a permanent and stable entity because its composition and biological properties evolve across life. So, we can talk about different CSFs during the vertebrate life span. In this review, we focus on the CSF in an interesting period, early in vertebrate development before the formation of the choroid plexus. This specific entity is called "embryonic CSF." Based on the structure of the compartment, CSF composition, origin and circulation, and its interaction with neuroepithelial precursor cells (the target cells) we can conclude that embryonic CSF is different from the CSF in later developmental stages and from the adult CSF. This article presents arguments that support the singularity of the embryonic CSF, mainly focusing on its influence on neural precursor behavior during development and in adult life.

  13. Development of modularity in the neural activity of children's brains.

    Science.gov (United States)

    Chen, Man; Deem, Michael W

    2015-01-26

    We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from functional magnetic resonance imaging (fMRI) data is observed to increase during childhood development and peak in young adulthood. Head motion is deconvolved from the fMRI data, and it is shown that the dependence of modularity on age is independent of the magnitude of head motion. A model is presented to illustrate how modularity can provide greater cognitive performance at short times, i.e. task switching. A fitness function is extracted from the model. Quasispecies theory is used to predict how the average modularity evolves with age, illustrating the increase of modularity during development from children to adults that arises from selection for rapid cognitive function in young adults. Experiments exploring the effect of modularity on cognitive performance are suggested. Modularity may be a potential biomarker for injury, rehabilitation, or disease.

  14. Games in the Brain: Neural Substrates of Gambling Addiction.

    Science.gov (United States)

    Murch, W Spencer; Clark, Luke

    2016-10-01

    As a popular form of recreational risk taking, gambling games offer a paradigm for decision neuroscience research. As an individual behavior, gambling becomes dysfunctional in a subset of the population, with debilitating consequences. Gambling disorder has been recently reconceptualized as a "behavioral addiction" in the DSM-5, based on emerging parallels with substance use disorders. Why do some individuals undergo this transition from recreational to disordered gambling? The biomedical model of problem gambling is a "brain disorder" account that posits an underlying neurobiological abnormality. This article first delineates the neural circuitry that underpins gambling-related decision making, comprising ventral striatum, ventromedial prefrontal cortex, dopaminergic midbrain, and insula, and presents evidence for pathophysiology in this circuitry in gambling disorder. These biological dispositions become translated into clinical disorder through the effects of gambling games. This influence is better articulated in a public health approach that describes the interplay between the player and the (gambling) product. Certain forms of gambling, including electronic gambling machines, appear to be overrepresented in problem gamblers. These games harness psychological features, including variable ratio schedules, near-misses, "losses disguised as wins," and the illusion of control, which modulate the core decision-making circuitry that is perturbed in gambling disorder. © The Author(s) 2015.

  15. Neural basis of feature-based contextual effects on visual search behavior

    Directory of Open Access Journals (Sweden)

    Kelly eShen

    2012-01-01

    Full Text Available Searching for a visual object is known to be adaptable to context, and it is thought to result from the selection of neural representations distributed on a visual salience map, wherein stimulus-driven and goal-directed signals are combined. Here we investigated the neural basis of this adaptability by recording superior colliculus (SC neurons while three female rhesus monkeys (Macaca mulatta searched with saccadic eye movements for a target presented in an array of visual stimuli whose feature composition varied from trial to trial. We found that sensory-motor activity associated with distracters was enhanced or suppressed depending on the search array composition and that it corresponded to the monkey's search strategy, as assessed by the distribution of the occasional errant saccades. This feature-related modulation occurred independently from the saccade goal and facilitated the process of saccade target selection. We also observed feature-related enhancement in the activity associated with distracters that had been the search target during the previous session. Consistent with recurrent processing, both feature-related neuronal modulations occurred more than 60 ms after the onset of the visually evoked responses, and their near coincidence with the time of saccade target selection suggests that they are integral to this process. These results suggest that SC neuronal activity is shaped by the visual context as dictated by both stimulus-driven and goal-directed signals. Given the close proximity of the SC to the motor circuit, our findings suggest a direct link between perception and action and no need for distinct salience and motor maps.

  16. Music perception and cognition: development, neural basis, and rehabilitative use of music.

    Science.gov (United States)

    Särkämö, Teppo; Tervaniemi, Mari; Huotilainen, Minna

    2013-07-01

    Music is a highly versatile form of art and communication that has been an essential part of human society since its early days. Neuroimaging studies indicate that music is a powerful stimulus also for the human brain, engaging not just the auditory cortex but also a vast, bilateral network of temporal, frontal, parietal, cerebellar, and limbic brain areas that govern auditory perception, syntactic and semantic processing, attention and memory, emotion and mood control, and motor skills. Studies of amusia, a severe form of musical impairment, highlight the right temporal and frontal cortices as the core neural substrates for adequate perception and production of music. Many of the basic auditory and musical skills, such as pitch and timbre perception, start developing already in utero, and babies are born with a natural preference for music and singing. Music has many important roles and functions throughout life, ranging from emotional self-regulation, mood enhancement, and identity formation to promoting the development of verbal, motor, cognitive, and social skills and maintaining their healthy functioning in old age. Music is also used clinically as a part of treatment in many illnesses, which involve affective, attention, memory, communication, or motor deficits. Although more research is still needed, current evidence suggests that music-based rehabilitation can be effective in many developmental, psychiatric, and neurological disorders, such as autism, depression, schizophrenia, and stroke, as well as in many chronic somatic illnesses that cause pain and anxiety. WIREs Cogn Sci 2013, 4:441-451. doi: 10.1002/wcs.1237 The authors have declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. Copyright © 2013 John Wiley & Sons, Ltd.

  17. fMRI of the auditory system: understanding the neural basis of auditory gestalt.

    Science.gov (United States)

    Di Salle, Francesco; Esposito, Fabrizio; Scarabino, Tommaso; Formisano, Elia; Marciano, Elio; Saulino, Claudio; Cirillo, Sossio; Elefante, Raffaele; Scheffler, Klaus; Seifritz, Erich

    2003-12-01

    Functional magnetic resonance imaging (fMRI) has rapidly become the most widely used imaging method for studying brain functions in humans. This is a result of its extreme flexibility of use and of the astonishingly detailed spatial and temporal information it provides. Nevertheless, until very recently, the study of the auditory system has progressed at a considerably slower pace compared to other functional systems. Several factors have limited fMRI research in the auditory field, including some intrinsic features of auditory functional anatomy and some peculiar interactions between fMRI technique and audition. A well known difficulty arises from the high intensity acoustic noise produced by gradient switching in echo-planar imaging (EPI), as well as in other fMRI sequences more similar to conventional MR sequences. The acoustic noise interacts in an unpredictable way with the experimental stimuli both from a perceptual point of view and in the evoked hemodynamics. To overcome this problem, different approaches have been proposed recently that generally require careful tailoring of the experimental design and the fMRI methodology to the specific requirements posed by the auditory research. The novel methodological approaches can make the fMRI exploration of auditory processing much easier and more reliable, and thus may permit filling the gap with other fields of neuroscience research. As a result, some fundamental neural underpinnings of audition are being clarified, and the way sound stimuli are integrated in the auditory gestalt are beginning to be understood.

  18. Neural Basis for the Ability of Atypical Antipsychotic Drugs to Improve Cognition in Schizophrenia

    Science.gov (United States)

    Sumiyoshi, Tomiki; Higuchi, Yuko; Uehara, Takashi

    2013-01-01

    Cognitive impairments are considered to largely affect functional outcome in patients with schizophrenia, other psychotic illnesses, or mood disorders. Specifically, there is much attention to the role of psychotropic compounds acting on serotonin (5-HT) receptors in ameliorating cognitive deficits of schizophrenia. It is noteworthy that atypical antipsychotic drugs (AAPDs), e.g., clozapine, melperone, risperidone, olanzapine, quetiapine, aripiprazole, perospirone, blonanserin, and lurasidone, have variable affinities for these receptors. Among the 5-HT receptor subtypes, the 5-HT1A receptor is attracting particular interests as a potential target for enhancing cognition, based on preclinical and clinical evidence. The neural network underlying the ability of 5-HT1A agonists to treat cognitive impairments of schizophrenia likely includes dopamine, glutamate, and gamma-aminobutyric acid neurons. A novel strategy for cognitive enhancement in psychosis may be benefited by focusing on energy metabolism in the brain. In this context, lactate plays a major role, and has been shown to protect neurons against oxidative and other stressors. In particular, our data indicate chronic treatment with tandospirone, a partial 5-HT1A agonist, recover stress-induced lactate production in the prefrontal cortex of a rat model of schizophrenia. Recent advances of electrophysiological measures, e.g., event-related potentials, and their imaging have provided insights into facilitative effects on cognition of some AAPDs acting directly or indirectly on 5-HT1A receptors. These findings are expected to promote the development of novel therapeutics for the improvement of functional outcome in people with schizophrenia. PMID:24137114

  19. Neural basis for the ability of atypical antipsychotic drugs to improve cognition in schizophrenia.

    Science.gov (United States)

    Sumiyoshi, Tomiki; Higuchi, Yuko; Uehara, Takashi

    2013-10-16

    Cognitive impairments are considered to largely affect functional outcome in patients with schizophrenia, other psychotic illnesses, or mood disorders. Specifically, there is much attention to the role of psychotropic compounds acting on serotonin (5-HT) receptors in ameliorating cognitive deficits of schizophrenia. It is noteworthy that atypical antipsychotic drugs (AAPDs), e.g., clozapine, melperone, risperidone, olanzapine, quetiapine, aripiprazole, perospirone, blonanserin, and lurasidone, have variable affinities for these receptors. Among the 5-HT receptor subtypes, the 5-HT1A receptor is attracting particular interests as a potential target for enhancing cognition, based on preclinical and clinical evidence. The neural network underlying the ability of 5-HT1A agonists to treat cognitive impairments of schizophrenia likely includes dopamine, glutamate, and gamma-aminobutyric acid neurons. A novel strategy for cognitive enhancement in psychosis may be benefited by focusing on energy metabolism in the brain. In this context, lactate plays a major role, and has been shown to protect neurons against oxidative and other stressors. In particular, our data indicate chronic treatment with tandospirone, a partial 5-HT1A agonist, recover stress-induced lactate production in the prefrontal cortex of a rat model of schizophrenia. Recent advances of electrophysiological measures, e.g., event-related potentials, and their imaging have provided insights into facilitative effects on cognition of some AAPDs acting directly or indirectly on 5-HT1A receptors. These findings are expected to promote the development of novel therapeutics for the improvement of functional outcome in people with schizophrenia.

  20. The neural basis of temporal order processing in past and future thought.

    Science.gov (United States)

    D'Argembeau, Arnaud; Jeunehomme, Olivier; Majerus, Steve; Bastin, Christine; Salmon, Eric

    2015-01-01

    Although growing evidence has shown that remembering the past and imagining the future recruit a common core network of frontal-parietal-temporal regions, the extent to which these regions contribute to the temporal dimension of autobiographical thought remains unclear. In this fMRI study, we focused on the event-sequencing aspect of time and examined whether ordering past and future events involve common neural substrates. Participants had to determine which of two past (or future) events occurred (or would occur) before the other, and these order judgments were compared with a task requiring to think about the content of the same past or future events. For both past and future events, we found that the left posterior hippocampus was more activated when establishing the order of events, whereas the anterior hippocampus was more activated when representing their content. Aside from the hippocampus, most of the brain regions that were activated when thinking about temporal order (notably the intraparietal sulcus, dorsolateral pFC, dorsal anterior cingulate, and visual cortex) lied outside the core network and may reflect the involvement of controlled processes and visuospatial imagery to locate events in time. Collectively, these findings suggest (a) that the same processing operations are engaged for ordering past events and planned future events in time, (b) that anterior and posterior portions of the hippocampus are involved in processing different aspects of autobiographical thought, and (c) that temporal order is not necessarily an intrinsic property of memory or future thought but instead requires additional, controlled processes.

  1. Optogenetics in the Teaching Laboratory: Using Channelrhodopsin-2 to Study the Neural Basis of Behavior and Synaptic Physiology in "Drosophila"

    Science.gov (United States)

    Pulver, Stefan R.; Hornstein, Nicholas J.; Land, Bruce L.; Johnson, Bruce R.

    2011-01-01

    Here we incorporate recent advances in "Drosophila" neurogenetics and "optogenetics" into neuroscience laboratory exercises. We used the light-activated ion channel channelrhodopsin-2 (ChR2) and tissue-specific genetic expression techniques to study the neural basis of behavior in "Drosophila" larvae. We designed and implemented exercises using…

  2. An Intelligent Approach to Educational Data: Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks

    Science.gov (United States)

    Kayri, Murat

    2015-01-01

    The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…

  3. The Neural Basis of Reversible Sentence Comprehension: Evidence from Voxel-Based Lesion Symptom Mapping in Aphasia

    Science.gov (United States)

    Thothathiri, Malathi; Kimberg, Daniel Y.; Schwartz, Myrna F.

    2012-01-01

    We explored the neural basis of reversible sentence comprehension in a large group of aphasic patients (n = 79). Voxel-based lesion symptom mapping revealed a significant association between damage in temporo-parietal cortex and impaired sentence comprehension. This association remained after we controlled for phonological working memory. We…

  4. Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction

    Directory of Open Access Journals (Sweden)

    P. Kumudha

    2016-01-01

    Full Text Available Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN and the novel adaptive dimensional biogeography based optimization (ADBBO model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

  5. Absence of visual experience modifies the neural basis of numerical thinking.

    Science.gov (United States)

    Kanjlia, Shipra; Lane, Connor; Feigenson, Lisa; Bedny, Marina

    2016-10-04

    In humans, the ability to reason about mathematical quantities depends on a frontoparietal network that includes the intraparietal sulcus (IPS). How do nature and nurture give rise to the neurobiology of numerical cognition? We asked how visual experience shapes the neural basis of numerical thinking by studying numerical cognition in congenitally blind individuals. Blind (n = 17) and blindfolded sighted (n = 19) participants solved math equations that varied in difficulty (e.g., 27 - 12 = x vs. 7 - 2 = x), and performed a control sentence comprehension task while undergoing fMRI. Whole-cortex analyses revealed that in both blind and sighted participants, the IPS and dorsolateral prefrontal cortices were more active during the math task than the language task, and activity in the IPS increased parametrically with equation difficulty. Thus, the classic frontoparietal number network is preserved in the total absence of visual experience. However, surprisingly, blind but not sighted individuals additionally recruited a subset of early visual areas during symbolic math calculation. The functional profile of these "visual" regions was identical to that of the IPS in blind but not sighted individuals. Furthermore, in blindness, number-responsive visual cortices exhibited increased functional connectivity with prefrontal and IPS regions that process numbers. We conclude that the frontoparietal number network develops independently of visual experience. In blindness, this number network colonizes parts of deafferented visual cortex. These results suggest that human cortex is highly functionally flexible early in life, and point to frontoparietal input as a mechanism of cross-modal plasticity in blindness.

  6. DATA CLASSIFICATION WITH NEURAL CLASSIFIER USING RADIAL BASIS FUNCTION WITH DATA REDUCTION USING HIERARCHICAL CLUSTERING

    Directory of Open Access Journals (Sweden)

    M. Safish Mary

    2012-04-01

    Full Text Available Classification of large amount of data is a time consuming process but crucial for analysis and decision making. Radial Basis Function networks are widely used for classification and regression analysis. In this paper, we have studied the performance of RBF neural networks to classify the sales of cars based on the demand, using kernel density estimation algorithm which produces classification accuracy comparable to data classification accuracy provided by support vector machines. In this paper, we have proposed a new instance based data selection method where redundant instances are removed with help of a threshold thus improving the time complexity with improved classification accuracy. The instance based selection of the data set will help reduce the number of clusters formed thereby reduces the number of centers considered for building the RBF network. Further the efficiency of the training is improved by applying a hierarchical clustering technique to reduce the number of clusters formed at every step. The paper explains the algorithm used for classification and for conditioning the data. It also explains the complexities involved in classification of sales data for analysis and decision-making.

  7. Motion planning for autonomous vehicle based on radial basis function neural network in unstructured environment.

    Science.gov (United States)

    Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

    2014-09-18

    The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.

  8. Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction.

    Science.gov (United States)

    Kumudha, P; Venkatesan, R

    Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

  9. "Shall I compare thee": The neural basis of literary awareness, and its benefits to cognition.

    Science.gov (United States)

    O'Sullivan, Noreen; Davis, Philip; Billington, Josie; Gonzalez-Diaz, Victorina; Corcoran, Rhiannon

    2015-12-01

    Functional magnetic resonance imaging (fMRI) was used to explore the neural and cognitive basis of literary awareness in 24 participants. The 2×2 design explored the capacity to process and derive meanings in complex poetic and prosaic texts that either did or did not require significant reappraisal during reading. Following this, participants rated each piece on its 'poeticness' and the extent to which it prompted a reappraisal of meaning during reading, providing subjective measures of poetic recognition and the need to reappraise meaning. The substantial shared variance between these 2 subjective measures provided a proxy measure of literary awareness, which was found to modulate activity in regions comprising the central executive and saliency networks. We suggest that enhanced literary awareness is related to increased flexibility of internal models of meaning, enhanced interoceptive awareness of change, and an enhanced capacity to reason about events. In addition, we found that the residual variance in the measure of poetic recognition modulated right dorsal caudate activity, which may be related to tolerance of uncertainty. These findings are consistent with evidence that relates reading to improved mental wellbeing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Feature extraction for EEG-based brain-computer interfaces by wavelet packet best basis decomposition.

    Science.gov (United States)

    Yang, Bang-hua; Yan, Guo-zheng; Yan, Rong-guo; Wu, Ting

    2006-12-01

    A method based on wavelet packet best basis decomposition (WPBBD) is investigated for the purpose of extracting features of electroencephalogram signals produced during motor imagery tasks in brain-computer interfaces. The method includes the following three steps. (1) Original signals are decomposed by wavelet packet transform (WPT) and a wavelet packet library can be formed. (2) The best basis for classification is selected from the library. (3) Subband energies included in the best basis are used as effective features. Three different motor imagery tasks are discriminated using the features. The WPBBD produces a 70.3% classification accuracy, which is 4.2% higher than that of the existing wavelet packet method.

  11. Feature extraction for EEG-based brain computer interfaces by wavelet packet best basis decomposition

    Science.gov (United States)

    Yang, Bang-hua; Yan, Guo-zheng; Yan, Rong-guo; Wu, Ting

    2006-12-01

    A method based on wavelet packet best basis decomposition (WPBBD) is investigated for the purpose of extracting features of electroencephalogram signals produced during motor imagery tasks in brain-computer interfaces. The method includes the following three steps. (1) Original signals are decomposed by wavelet packet transform (WPT) and a wavelet packet library can be formed. (2) The best basis for classification is selected from the library. (3) Subband energies included in the best basis are used as effective features. Three different motor imagery tasks are discriminated using the features. The WPBBD produces a 70.3% classification accuracy, which is 4.2% higher than that of the existing wavelet packet method.

  12. Neural mechanisms of auditory categorization: from across brain areas to within local microcircuits

    Directory of Open Access Journals (Sweden)

    Joji eTsunada

    2014-06-01

    Full Text Available Categorization enables listeners to efficiently encode and respond to auditory stimuli. Behavioral evidence for auditory categorization has been well documented across a broad range of human and non-human animal species. Moreover, neural correlates of auditory categorization have been documented in a variety of different brain regions in the ventral auditory pathway, which is thought to underlie auditory-object processing and auditory perception. Here, we review and discuss how neural representations of auditory categories are transformed across different scales of neural organization in the ventral auditory pathway: from across different brain areas to within local microcircuits. We propose different neural transformations across different scales of neural organization in auditory categorization. Along the ascending auditory system in the ventral pathway, there is a progression in the encoding of categories from simple acoustic categories to categories for abstract information. On the other hand, in local microcircuits, different classes of neurons differentially compute categorical information.

  13. Neural Operant Conditioning as a Core Mechanism of Brain-Machine Interface Control

    Directory of Open Access Journals (Sweden)

    Yoshio Sakurai

    2016-08-01

    Full Text Available The process of changing the neuronal activity of the brain to acquire rewards in a broad sense is essential for utilizing brain-machine interfaces (BMIs, which is essentially operant conditioning of neuronal activity. Currently, this is also known as neural biofeedback, and it is often referred to as neurofeedback when human brain activity is targeted. In this review, we first illustrate biofeedback and operant conditioning, which are methodological background elements in neural operant conditioning. Then, we introduce research models of neural operant conditioning in animal experiments and demonstrate that it is possible to change the firing frequency and synchronous firing of local neuronal populations in a short time period. We also debate the possibility of the application of neural operant conditioning and its contribution to BMIs.

  14. A radial basis function neural network based on artificial immune systems for remote sensing image classification

    Science.gov (United States)

    Yan, Qin; Zhong, Yanfei

    2008-12-01

    The radial basis function (RBF) neural network is a powerful method for remote sensing image classification. It has a simple architecture and the learning algorithm corresponds to the solution of a linear regression problem, resulting in a fast training process. The main drawback of this strategy is the requirement of an efficient algorithm to determine the number, position, and dispersion of the RBF. Traditional methods to determine the centers are: randomly choose input vectors from the training data set; vectors obtained from unsupervised clustering algorithms, such as k-means, applied to the input data. These conduce that traditional RBF neural network is sensitive to the center initialization. In this paper, the artificial immune network (aiNet) model, a new computational intelligence based on artificial immune networks (AIN), is applied to obtain appropriate centers for remote sensing image classification. In the aiNet-RBF algorihtm, each input pattern corresonds to an antigenic stimulus, while each RBF candidate center is considered to be an element, or cell, of the immune network model. The steps are as follows: A set of candidate centers is initialized at random, where the initial number of candidates and their positions is not crucial to the performance. Then, the clonal selection principle will control which candidates will be selected and how they will be upadated. Note that the clonal selection principle will be responsible for how the centers will represent the training data set. Finally, the immune network will identify and eliminate or suppress self-recognizing individuals to control the number of candidate centers. After the above learning phase, the aiNet network centers represent internal images of the inuput patterns presented to it. The algorithm output is taken to be the matrix of memory cells' coordinates that represent the final centers to be adopted by the RBF network. The stopping criterion of the proposed algorithm is given by a pre

  15. The neural basis for writing from dictation in the temporoparietal cortex.

    Science.gov (United States)

    Roux, Franck-Emmanuel; Durand, Jean-Baptiste; Réhault, Emilie; Planton, Samuel; Draper, Louisa; Démonet, Jean-François

    2014-01-01

    Cortical electrical stimulation mapping was used to study neural substrates of the function of writing in the temporoparietal cortex. We identified the sites involved in oral language (sentence reading and naming) and writing from dictation, in order to spare these areas during removal of brain tumours in 30 patients (23 in the left, and 7 in the right hemisphere). Electrostimulation of the cortex impaired writing ability in 62 restricted cortical areas (.25 cm2). These were found in left temporoparietal lobes and were mostly located along the superior temporal gyrus (Brodmann's areas 22 and 42). Stimulation of right temporoparietal lobes in right-handed patients produced no writing impairments. However there was a high variability of location between individuals. Stimulation resulted in combined symptoms (affecting oral language and writing) in fourteen patients, whereas in eight other patients, stimulation-induced pure agraphia symptoms with no oral language disturbance in twelve of the identified areas. Each detected area affected writing in a different way. We detected the various different stages of the auditory-to-motor pathway of writing from dictation: either through comprehension of the dictated sentences (word deafness areas), lexico-semantic retrieval, or phonologic processing. In group analysis, barycentres of all different types of writing interferences reveal a hierarchical functional organization along the superior temporal gyrus from initial word recognition to lexico-semantic and phonologic processes along the ventral and the dorsal comprehension pathways, supporting the previously described auditory-to-motor process. The left posterior Sylvian region supports different aspects of writing function that are extremely specialized and localized, sometimes being segregated in a way that could account for the occurrence of pure agraphia that has long-been described in cases of damage to this region. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Neural basis for the ability of atypical antipsychotic drugs to improve cognition in schizophrenia

    Directory of Open Access Journals (Sweden)

    Tomiki eSumiyoshi

    2013-10-01

    Full Text Available Cognitive impairments are considered to largely affect functional outcome in patients with schizophrenia, other psychotic illnesses, or mood disorders. Specifically, there is much attention to the role of psychotropic compounds acting on serotonin (5-HT receptors in ameliorating cognitive deficits of schizophrenia.It is noteworthy that atypical antipsychotic drugs, e.g. clozapine, melperone, risperidone, olanzapine, quetiapine, aripiprazole, perospirone, blonanserin, and lurasidone, have variable affinities for these receptors. Among the 5-HT receptor subtypes, the 5-HT1A receptor is attracting particular interests as a potential target for enhancing cognition, based on preclinical and clinical evidence.The neural network underlying the ability of 5-HT1A agonists to treat cognitive impairments of schizophrenia likely includes dopamine, glutamate, and GABA neurons. A novel strategy for cognitive enhancement in psychosis may be benefitted by focusing on energy metabolism in the brain. In this context, lactate plays a major role, and has been shown to protect neurons against oxidative and other stressors. In particular, our data indicate chronic treatment with tandospirone, a partial 5-HT1A agonist, recover stress-induced lactate production in the prefrontal cortex of a rat model of schizophrenia. Recent advances of electrophysiological measures, e.g. event-related potentials, and their imaging have provided insights into facilitative effects on cognition of some atypical antipsychotic drugs acting directly or indirectly on 5-HT1A receptors.These findings are expected to promote the development of novel therapeutics for the improvement of functional outcome in people with schizophrenia.

  17. Brain plasticity, cognitive functions and neural stem cells: a pivotal role for the brain-specific neural master gene |-SRGAP2-FAM72-|.

    Science.gov (United States)

    Ho, Nguyen Thi Thanh; Kutzner, Arne; Heese, Klaus

    2017-12-20

    Due to an aging society with an increased dementia-induced threat to higher cognitive functions, it has become imperative to understand the molecular and cellular events controlling the memory and learning processes in the brain. Here, we suggest that the novel master gene pair |-SRGAP2-FAM72-| (SLIT-ROBO Rho GTPase activating the protein 2, family with sequence similarity to 72) reveals a new dogma for the regulation of neural stem cell (NSC) gene expression and is a distinctive player in the control of human brain plasticity. Insight into the specific regulation of the brain-specific neural master gene |-SRGAP2-FAM72-| may essentially contribute to novel therapeutic approaches to restore or improve higher cognitive functions.

  18. Expression of Nestin by Neural Cells in the Adult Rat and Human Brain

    OpenAIRE

    Hendrickson, Michael L.; Rao, Abigail J.; Demerdash, Omar N. A.; Kalil, Ronald E.

    2011-01-01

    Neurons and glial cells in the developing brain arise from neural progenitor cells (NPCs). Nestin, an intermediate filament protein, is thought to be expressed exclusively by NPCs in the normal brain, and is replaced by the expression of proteins specific for neurons or glia in differentiated cells. Nestin expressing NPCs are found in the adult brain in the subventricular zone (SVZ) of the lateral ventricle and the subgranular zone (SGZ) of the dentate gyrus. While significant attention has b...

  19. Brains--Computers--Machines: Neural Engineering in Science Classrooms

    Science.gov (United States)

    Chudler, Eric H.; Bergsman, Kristen Clapper

    2016-01-01

    Neural engineering is an emerging field of high relevance to students, teachers, and the general public. This feature presents online resources that educators and scientists can use to introduce students to neural engineering and to integrate core ideas from the life sciences, physical sciences, social sciences, computer science, and engineering…

  20. The neural basis of learning to spell again: An fMRI study of spelling training in acquired dysgraphia.

    Directory of Open Access Journals (Sweden)

    Jeremy Purcell

    2015-05-01

    1 For all participants we identified brain areas associated with a normalized response for the TRAINING words at the post-training time point. 2 For all participants we identified an up-regulation of the TRAINING response (i.e., the TRAINING neural response was initially low and then increased post-training; whereas in only one participant did we also observe a down-regulation of the training response (i.e., the TRAINING neural response was initially high, but then decreased post-training. 3 Although the areas associated with the normalized TRAINING response were different in each individual, they all include areas typically associated with the spelling system (Purcell et al. 2011, including the right homologues of typically left hemisphere spelling regions. Across the participants, the following areas of normalization were observed: bilateral superior temporal gyrus, inferior frontal gyrus, and the bilateral inferior temporal/fusiform gyrus. Discussion: We found that the predominant BOLD response to training involved an up-regulation of the neural response to spelling the TRAINING items. In addition, we found individual differences in the neurotopography of the normalization response patterns although all were with within brain areas that form a part of the spelling network(Purcell et al. 2011. This work provides evidence regarding one aspect of the multiplicity of neural responses associated with recovery of spelling in individuals with acquired dysgraphia.

  1. Revisiting the Neural Basis of Acquired Amusia: Lesion Patterns and Structural Changes Underlying Amusia Recovery

    Directory of Open Access Journals (Sweden)

    Aleksi J. Sihvonen

    2017-07-01

    Full Text Available Although, acquired amusia is a common deficit following stroke, relatively little is still known about its precise neural basis, let alone to its recovery. Recently, we performed a voxel-based lesion-symptom mapping (VLSM and morphometry (VBM study which revealed a right lateralized lesion pattern, and longitudinal gray matter volume (GMV and white matter volume (WMV changes that were specifically associated with acquired amusia after stroke. In the present study, using a larger sample of stroke patients (N = 90, we aimed to replicate and extend the previous structural findings as well as to determine the lesion patterns and volumetric changes associated with amusia recovery. Structural MRIs were acquired at acute and 6-month post-stroke stages. Music perception was behaviorally assessed at acute and 3-month post-stroke stages using the Scale and Rhythm subtests of the Montreal Battery of Evaluation of Amusia (MBEA. Using these scores, the patients were classified as non-amusic, recovered amusic, and non-recovered amusic. The results of the acute stage VLSM analyses and the longitudinal VBM analyses converged to show that more severe and persistent (non-recovered amusia was associated with an extensive pattern of lesions and GMV/WMV decrease in right temporal, frontal, parietal, striatal, and limbic areas. In contrast, less severe and transient (recovered amusia was linked to lesions specifically in left inferior frontal gyrus as well as to a GMV decrease in right parietal areas. Separate continuous analyses of MBEA Scale and Rhythm scores showed extensively overlapping lesion pattern in right temporal, frontal, and subcortical structures as well as in the right insula. Interestingly, the recovered pitch amusia was related to smaller GMV decreases in the temporoparietal junction whereas the recovered rhythm amusia was associated to smaller GMV decreases in the inferior temporal pole. Overall, the results provide a more comprehensive picture of

  2. Optimized face recognition algorithm using radial basis function neural networks and its practical applications.

    Science.gov (United States)

    Yoo, Sung-Hoon; Oh, Sung-Kwun; Pedrycz, Witold

    2015-09-01

    In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Experience-Dependent Neural Plasticity in the Adult Damaged Brain

    Science.gov (United States)

    Kerr, Abigail L.; Cheng, Shao-Ying; Jones, Theresa A.

    2011-01-01

    Behavioral experience is at work modifying the structure and function of the brain throughout the lifespan, but it has a particularly dramatic influence after brain injury. This review summarizes recent findings on the role of experience in reorganizing the adult damaged brain, with a focus on findings from rodent stroke models of chronic upper…

  4. Delineating Neural Structures of Developmental Human Brains with Diffusion Tensor Imaging

    Directory of Open Access Journals (Sweden)

    Hao Huang

    2010-01-01

    Full Text Available The human brain anatomy is characterized by dramatic structural changes during fetal development. It is extraordinarily complex and yet its origin is a simple tubular structure. Revealing detailed anatomy at different stages of brain development not only aids in understanding this highly ordered process, but also provides clues to detect abnormalities caused by genetic or environmental factors. However, anatomical studies of human brain development during the fetal period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor imaging (DTI measures water diffusion to delineate the underlying neural structures. The high contrasts derived from DTI can be used to establish the brain atlas. With DTI tractography, coherent neural structures, such as white matter tracts, can be three-dimensionally reconstructed. The primary eigenvector of the diffusion tensor can be further explored to characterize microstructures in the cerebral wall of the developmental brains. In this mini-review, the application of DTI in order to reveal the structures of developmental fetal brains has been reviewed in the above-mentioned aspects. The fetal brain DTI provides a unique insight for delineating the neural structures in both macroscopic and microscopic levels. The resultant DTI database will provide structural guidance for the developmental study of human fetal brains in basic neuroscience, and reference standards for diagnostic radiology of premature newborns.

  5. The human infant brain: A neural architecture able to learn language.

    Science.gov (United States)

    Dehaene-Lambertz, Ghislaine

    2017-02-01

    To understand the type of neural computations that may explain how human infants acquire their native language in only a few months, the study of their neural architecture is necessary. The development of brain imaging techniques has opened the possibilities of studying human infants without discomfort, and although these studies are still sparse, several characteristics are noticeable in the human infant's brain: first, parallel and hierarchical processing pathways are observed before intense exposure to speech with an efficient temporal coding in the left hemisphere and, second, frontal regions are involved from the start in infants' cognition. These observations are certainly not sufficient to explain language acquisition but illustrate a new approach that relies on a better description of infants' brain activity during linguistic tasks, which is compared to results in animals and human adults to clarify the neural bases of language in humans.

  6. Brain Basis of Self: Self-Organization and Lessons from Dreaming

    Directory of Open Access Journals (Sweden)

    David eKahn

    2013-07-01

    Full Text Available Through dreaming a different facet of the self is created as a result of a self-organizing process in the brain. Self-organization in biological systems often happens as an answer to an environmental change for which the existing system cannot cope; self-organization creates a system that can cope in the newly changed environment. In dreaming, self-organization serves the function of organizing disparate memories into a dream since the dreamer herself is not able to control how individual memories become weaved into a dream. The self-organized dream provides, thereby, a wide repertoire of experiences; this expanded repertoire of experience results in an expansion of the self beyond that obtainable when awake. Since expression of the self is associated with activity in specific areas of the brain, the article also discusses the brain basis of the self by reviewing studies of brain injured patients, discussing brain imaging studies in normal brain functioning when focused, when daydreaming and when asleep and dreaming.

  7. Emotional moments across time: a possible neural basis for time perception in the anterior insula

    National Research Council Canada - National Science Library

    A.D. (Bud) Craig

    2009-01-01

    ... in the range of seconds to subseconds. The model posits that the neural substrate for awareness across time is located in the anterior insular cortex, which fits with recent functional imaging evidence relevant to awareness and time perception...

  8. The construction of digital terain model by using neural networks with optimised radial basis functions

    Science.gov (United States)

    Stateczny, A.; Lubczonek, J.

    2003-04-01

    The basic problem in the construction of a numerical spatial sea chart is such transformation of the sounding data that it should be possible to determine the depth at any point of the bottom area. In recent years, much attention has been devoted to the problem of modelling the seabed shape in a numerical three-dimensional sea chart. Various methods for modelling the seabed shape are applied. These methods can be divided into analytical and neural. In the case of applying the model for navigational tasks, the selection of a suitable method should ensure high accuracy of surface projection. The model should be conformed to the surface shape, spatial distribution of the measurement points and their number. The application of universal methods like 'multiquadric' or 'kriging' does not ensure an optimal result either, as each of these methods can have a certain number of options and parameters, which frequently play a significant role during surface modelling. It is often difficult to optimise these factors and even experience does not guarantee a satisfactory result. This applies especially to modelling irregular surfaces, when it is difficult to select the method suitable for the surface shape that is sometimes unpredictable. It has been suggested that the method of selecting the shape parameter of the radial basis functions should be applied which makes it possible to minimise the mean square error of the approximated surface. The paper presents a new method of optimising the parameters of radial functions used for modelling the bottom surface. The accuracy of the surface projection obtained was the criterion for optimisation. The properties of self-organizing networks created the possibility of selecting testing points out of any set of measurement points and the determination of the minimum value of RMS error by means of the GRNN network. Optimisation of the shape parameter required building the proper polygon of the test points. For building such kind of polygon

  9. Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory

    OpenAIRE

    Davis, Tyler; Xue, Gui; Love, Bradley C.; Preston, Alison. R.; Poldrack, Russell A

    2014-01-01

    Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categoriza...

  10. Global neural pattern similarity as a common basis for categorization and recognition memory.

    Science.gov (United States)

    Davis, Tyler; Xue, Gui; Love, Bradley C; Preston, Alison R; Poldrack, Russell A

    2014-05-28

    Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. Copyright © 2014 the authors 0270-6474/14/347472-13$15.00/0.

  11. Global Neural Pattern Similarity as a Common Basis for Categorization and Recognition Memory

    Science.gov (United States)

    Xue, Gui; Love, Bradley C.; Preston, Alison R.; Poldrack, Russell A.

    2014-01-01

    Familiarity, or memory strength, is a central construct in models of cognition. In previous categorization and long-term memory research, correlations have been found between psychological measures of memory strength and activation in the medial temporal lobes (MTLs), which suggests a common neural locus for memory strength. However, activation alone is insufficient for determining whether the same mechanisms underlie neural function across domains. Guided by mathematical models of categorization and long-term memory, we develop a theory and a method to test whether memory strength arises from the global similarity among neural representations. In human subjects, we find significant correlations between global similarity among activation patterns in the MTLs and both subsequent memory confidence in a recognition memory task and model-based measures of memory strength in a category learning task. Our work bridges formal cognitive theories and neuroscientific models by illustrating that the same global similarity computations underlie processing in multiple cognitive domains. Moreover, by establishing a link between neural similarity and psychological memory strength, our findings suggest that there may be an isomorphism between psychological and neural representational spaces that can be exploited to test cognitive theories at both the neural and behavioral levels. PMID:24872552

  12. Information-geometric measures estimate neural interactions during oscillatory brain states.

    Science.gov (United States)

    Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami

    2014-01-01

    The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

  13. Information-geometric measures estimate neural interactions during oscillatory brain states

    Directory of Open Access Journals (Sweden)

    Yimin eNie

    2014-02-01

    Full Text Available The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG, a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.

  14. Brain without mind: Computer simulation of neural networks with modifiable neuronal interactions

    Science.gov (United States)

    Clark, John W.; Rafelski, Johann; Winston, Jeffrey V.

    1985-07-01

    Aspects of brain function are examined in terms of a nonlinear dynamical system of highly interconnected neuron-like binary decision elements. The model neurons operate synchronously in discrete time, according to deterministic or probabilistic equations of motion. Plasticity of the nervous system, which underlies such cognitive collective phenomena as adaptive development, learning, and memory, is represented by temporal modification of interneuronal connection strengths depending on momentary or recent neural activity. A formal basis is presented for the construction of local plasticity algorithms, or connection-modification routines, spanning a large class. To build an intuitive understanding of the behavior of discrete-time network models, extensive computer simulations have been carried out (a) for nets with fixed, quasirandom connectivity and (b) for nets with connections that evolve under one or another choice of plasticity algorithm. From the former experiments, insights are gained concerning the spontaneous emergence of order in the form of cyclic modes of neuronal activity. In the course of the latter experiments, a simple plasticity routine (“brainwashing,” or “anti-learning”) was identified which, applied to nets with initially quasirandom connectivity, creates model networks which provide more felicitous starting points for computer experiments on the engramming of content-addressable memories and on learning more generally. The potential relevance of this algorithm to developmental neurobiology and to sleep states is discussed. The model considered is at the same time a synthesis of earlier synchronous neural-network models and an elaboration upon them; accordingly, the present article offers both a focused review of the dynamical properties of such systems and a selection of new findings derived from computer simulation.

  15. Expression of nestin by neural cells in the adult rat and human brain.

    Science.gov (United States)

    Hendrickson, Michael L; Rao, Abigail J; Demerdash, Omar N A; Kalil, Ronald E

    2011-04-07

    Neurons and glial cells in the developing brain arise from neural progenitor cells (NPCs). Nestin, an intermediate filament protein, is thought to be expressed exclusively by NPCs in the normal brain, and is replaced by the expression of proteins specific for neurons or glia in differentiated cells. Nestin expressing NPCs are found in the adult brain in the subventricular zone (SVZ) of the lateral ventricle and the subgranular zone (SGZ) of the dentate gyrus. While significant attention has been paid to studying NPCs in the SVZ and SGZ in the adult brain, relatively little attention has been paid to determining whether nestin-expressing neural cells (NECs) exist outside of the SVZ and SGZ. We therefore stained sections immunocytochemically from the adult rat and human brain for NECs, observed four distinct classes of these cells, and present here the first comprehensive report on these cells. Class I cells are among the smallest neural cells in the brain and are widely distributed. Class II cells are located in the walls of the aqueduct and third ventricle. Class IV cells are found throughout the forebrain and typically reside immediately adjacent to a neuron. Class III cells are observed only in the basal forebrain and closely related areas such as the hippocampus and corpus striatum. Class III cells resemble neurons structurally and co-express markers associated exclusively with neurons. Cell proliferation experiments demonstrate that Class III cells are not recently born. Instead, these cells appear to be mature neurons in the adult brain that express nestin. Neurons that express nestin are not supposed to exist in the brain at any stage of development. That these unique neurons are found only in brain regions involved in higher order cognitive function suggests that they may be remodeling their cytoskeleton in supporting the neural plasticity required for these functions.

  16. Neural representation of expected value in the adolescent brain

    OpenAIRE

    Barkley-Levenson, Emily; Galván, Adriana

    2014-01-01

    The brain undergoes significant maturation during adolescence that influences reward sensitivity and risk-taking behavior. However, it is unknown if the adolescent brain truly values rewards in a way that is unique from the mature brain or if confounding factors contribute to this developmental difference. Here we show that adolescents place greater value on rewards than do adults through exaggerated activation of the ventral striatum and that this valuation increases gambling behavior. This ...

  17. Reorganization of the injured brain: Implications for studies of the neural substrate of cognition

    Directory of Open Access Journals (Sweden)

    Jesper eMogensen

    2011-01-01

    Full Text Available In the search for a neural substrate of cognitive processes, a frequently utilized method is the scrutiny of posttraumatic symptoms exhibited by individuals suffering focal injury to the brain. For instance, the presence or absence of conscious awareness within a particular domain may, combined with knowledge of which regions of the brain have been injured, provide important data in the search for neural correlates of consciousness. Like all studies addressing the consequences of brain injury, however, such research has to face the fact that in most cases, posttraumatic impairments are accompanied by a functional recovery during which symptoms are reduced or eliminated. The apparent contradiction between localization and recovery, respectively, of functions constitutes a problem to almost all aspects of cognitive neuroscience. Several lines of investigation indicate that although the brain remains highly plastic throughout life, the posttraumatic plasticity does not recreate a copy of the neural mechanisms lost to injury. Instead, the uninjured parts of the brain are functionally reorganized in a manner which – in spite of not recreating the basic information processing lost to injury – is able to allow a more or less complete return of the surface phenomena (including manifestations of consciousness originally impaired by the trauma. A novel model (the REF-model of these processes is presented – and some of its implications discussed relative to studies of the neural substrates of cognition and consciousness.

  18. Localization of neural efficiency of the mathematically gifted brain through a feature subset selection method.

    Science.gov (United States)

    Zhang, Li; Gan, John Q; Wang, Haixian

    2015-10-01

    Based on the neural efficiency hypothesis and task-induced EEG gamma-band response (GBR), this study investigated the brain regions where neural resource could be most efficiently recruited by the math-gifted adolescents in response to varying cognitive demands. In this experiment, various GBR-based mental states were generated with three factors (level of mathematical ability, task complexity, and short-term learning) modulating the level of neural activation. A feature subset selection method based on the sequential forward floating search algorithm was used to identify an "optimal" combination of EEG channel locations, where the corresponding GBR feature subset could obtain the highest accuracy in discriminating pairwise mental states influenced by each experiment factor. The integrative results from multi-factor selections suggest that the right-lateral fronto-parietal system is highly involved in neural efficiency of the math-gifted brain, primarily including the bilateral superior frontal, right inferior frontal, right-lateral central and right temporal regions. By means of the localization method based on single-trial classification of mental states, new GBR features and EEG channel-based brain regions related to mathematical giftedness were identified, which could be useful for the brain function improvement of children/adolescents in mathematical learning through brain-computer interface systems.

  19. Neural computing architectures: The design of brain-like machines

    Energy Technology Data Exchange (ETDEWEB)

    Aleksander, I.

    1989-01-01

    Theoretical and applications aspects of neural-network (NN) computers are discussed in chapters contributed by European experts. Topics addressed include speech recognition based on topology-preserving neural maps, neural-map applications, backpropagation in nonfeedforward NNs, a parallel-distributed-processing learning approach to natural language, the learning capabilities of Boolean NNs, the logic of connectionist systems, and a probabilistic-logic NN for associative learning. Consideration is given to N-tuple sampling and genetic algorithms for speech recognition; the dynamic behavior of Boolean NNs; statistical mechanics and NNs; digital NNs, matched filters, and optical implementations; heteroassociative NNs using cabling vs link-disabling local modification rules; and the generation of movement trajectories in primates and robots. Also provided is an overview of parallel distributed processing.

  20. BrainSegNet: a convolutional neural network architecture for automated segmentation of human brain structures.

    Science.gov (United States)

    Mehta, Raghav; Majumdar, Aabhas; Sivaswamy, Jayanthi

    2017-04-01

    Automated segmentation of cortical and noncortical human brain structures has been hitherto approached using nonrigid registration followed by label fusion. We propose an alternative approach for this using a convolutional neural network (CNN) which classifies a voxel into one of many structures. Four different kinds of two-dimensional and three-dimensional intensity patches are extracted for each voxel, providing local and global (context) information to the CNN. The proposed approach is evaluated on five different publicly available datasets which differ in the number of labels per volume. The obtained mean Dice coefficient varied according to the number of labels, for example, it is [Formula: see text] and [Formula: see text] for datasets with the least (32) and the most (134) number of labels, respectively. These figures are marginally better or on par with those obtained with the current state-of-the-art methods on nearly all datasets, at a reduced computational time. The consistently good performance of the proposed method across datasets and no requirement for registration make it attractive for many applications where reduced computational time is necessary.

  1. Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

    Science.gov (United States)

    Kriegeskorte, Nikolaus

    2015-11-24

    Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.

  2. Neural correlates of delayed visual-motor performance in children treated for brain tumours.

    Science.gov (United States)

    Dockstader, Colleen; Gaetz, William; Bouffet, Eric; Tabori, Uri; Wang, Frank; Bostan, Stefan R; Laughlin, Suzanne; Mabbott, Donald J

    2013-09-01

    Both structural and functional neural integrity is critical for healthy cognitive function and performance. Across studies, it is evident that children who are affected by neurological insult commonly demonstrate impaired cognitive abilities. Children treated with cranial radiation for brain tumours suffer substantial structural damage and exhibit a particularly high correlation between the degree of neural injury and cognitive deficits. However the pathophysiology underlying impaired cognitive performance in this population, and many other paediatric populations affected by neurological injury or disease, is unknown. We wished to investigate the characteristics of neuronal function during visual-motor task performance in a group of children who were treated with cranial radiation for brain tumours. We used Magnetoencephalography to investigate neural function during visual-motor reaction time (RT) task performance in 15 children treated with cranial radiation for Posterior Fossa malignant brain tumours and 17 healthy controls. We found that, relative to controls, the patient group showed: 1) delayed latencies for neural activation in both visual and motor cortices; 2) muted motor responses in the alpha (8-12Hz) and beta (13-29Hz) bandwidths, and 3) potentiated visual and motor responses in the gamma (30-100Hz) bandwidth. Collectively these observations indicate impaired neural processing during visual-motor RT performance in this population and that delays in the speed of visual and motor neuronal processing both contribute to the delays in the behavioural response. As increases in gamma activity are often observed with increases in attention and effort, increased gamma activities in the patient group may reflect compensatory neural activity during task performance. This is the first study to investigate neural function in real-time during cognitive performance in paediatric brain tumour patients. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  4. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  5. Using chaotic artificial neural networks to model memory in the brain

    Science.gov (United States)

    Aram, Zainab; Jafari, Sajad; Ma, Jun; Sprott, Julien C.; Zendehrouh, Sareh; Pham, Viet-Thanh

    2017-03-01

    In the current study, a novel model for human memory is proposed based on the chaotic dynamics of artificial neural networks. This new model explains a biological fact about memory which is not yet explained by any other model: There are theories that the brain normally works in a chaotic mode, while during attention it shows ordered behavior. This model uses the periodic windows observed in a previously proposed model for the brain to store and then recollect the information.

  6. Language and the Newborn Brain: Does Prenatal Language Experience Shape the Neonate Neural Response to Speech?

    OpenAIRE

    Lillian eMay; Krista eByers-Heinlein; Judit eGervain; Werker, Janet F.

    2011-01-01

    Previous research has shown that by the time of birth, the neonate brain responds specially to the native language when compared to acoustically similar non-language stimuli. In the current study, we use Near Infrared Spectroscopy to ask how prenatal language experience might shape the brain response to language in newborn infants. To do so, we examine the neural response of neonates when listening to familiar versus unfamiliar language, as well as to non-linguistic backwards language. Twenty...

  7. The neural basis of humour comprehension and humour appreciation: The roles of the temporoparietal junction and superior frontal gyrus.

    Science.gov (United States)

    Campbell, Darren W; Wallace, Marc G; Modirrousta, Mandana; Polimeni, Joseph O; McKeen, Nancy A; Reiss, Jeffrey P

    2015-12-01

    Psychological well-being and social acumen benefit from the recognition of humourous intent and its enjoyment. The enjoyment of humour requires recognition, but humour recognition is not necessarily accompanied by humour enjoyment. Humour recognition is crucial during social interactions, while the associated enjoyment is less critical. Few neuroimaging studies have explicitly differentiated between the neural foundations of humour comprehension and humour appreciation. Among such studies, design limitations have obscured the specification of neural correlates to humour comprehension or appreciation. We implemented a trichotomous response option to address these design limitations. Twenty-four participants rated 120 comics (90 unaltered with humourous intent and 30 caption-altered without humourous intent) as either funny jokes (FJ), not funny jokes but intended to be funny (NFJ), or not intended to be funny or non-jokes (NJ). We defined humour comprehension by NFJ minus NJ and humour appreciation by FJ minus NFJ. We measured localized blood oxygen level dependent (BOLD) neural responses with a 3T MRI scanner. We tested for BOLD responses in humour comprehension brain regions of interest (ROIs), humour appreciation ROIs, and across the whole-brain. We found significant NFJ-NJ BOLD responses in our humour comprehension ROIs and significant FJ-NFJ BOLD responses in select humour appreciation ROIs. One key finding is that comprehension accuracy levels correlated with humour-comprehension responses in the left temporo-parietal junction (TPJ). This finding represents a novel and precise neural linkage to humour comprehension. A second key finding is that the superior frontal gyrus (SFG) was uniquely associated with humour-appreciation. The SFG response suggests that complex cognitive processing underlies humour appreciation and that current models of humour appreciation be revised. Finally, our research design provides an operational distinction between humour

  8. Neural Imaginaries and Clinical Epistemology: Rhetorically Mapping the Adolescent Brain in the Clinical Encounter

    Science.gov (United States)

    Buchbinder, Mara

    2014-01-01

    The social work of brain images has taken center stage in recent theorizing of the intersections between neuroscience and society. However, neuroimaging is only one of the discursive modes through which public representations of neurobiology travel. This article adopts an expanded view toward the social implications of neuroscientific thinking to examine how neural imaginaries are constructed in the absence of visual evidence. Drawing on ethnographic fieldwork conducted over 18 months (2008–2009) in a United States multidisciplinary pediatric pain clinic, I examine the pragmatic clinical work undertaken to represent ambiguous symptoms in neurobiological form. Focusing on one physician, I illustrate how, by rhetorically mapping the brain as a therapeutic tool, she engaged in a distinctive form of representation that I call neural imagining. In shifting my focus away from the purely material dimensions of brain images, I juxtapose the cultural work of brain scanning technologies with clinical neural imaginaries in which the teenage brain becomes a space of possibility, not to map things as they are, but rather, things as we hope they might be. These neural imaginaries rely upon a distinctive clinical epistemology that privileges the creative work of the imagination over visualization technologies in revealing the truths of the body. By creating a therapeutic space for adolescents to exercise their imaginative faculties and a discursive template for doing so, neural imagining relocates adolescents’ agency with respect to epistemologies of bodily knowledge and the role of visualization practices therein. In doing so, it provides a more hopeful alternative to the dominant popular and scientific representations of the teenage brain that view it primarily through the lens of pathology. PMID:24780561

  9. Differentiation and Cell-Cell Interactions of Neural Progenitor Cells Transplanted into Intact Adult Brain.

    Science.gov (United States)

    Sukhinich, K K; Kosykh, A V; Aleksandrova, M A

    2015-11-01

    We studied the behavior and cell-cell interactions of embryonic brain cell from GFP-reporter mice after their transplantation into the intact adult brain. Fragments or cell suspensions of fetal neocortical cells at different stages of development were transplanted into the neocortex and striatum of adult recipients. Even in intact brain, the processes of transplanted neurons formed extensive networks in the striatum and neocortical layers I and V-VI. Processes of transplanted cells at different stages of development attained the rostral areas of the frontal cortex and some of them reached the internal capsule. However, the cells transplanted in suspension had lower process growth potency than cells from tissue fragments. Tyrosine hydroxylase fibers penetrated from the recipient brain into grafts at both early and late stages of development. Our experiments demonstrated the formation of extensive reciprocal networks between the transplanted fetal neural cells and recipient brain neurons even in intact brain.

  10. High Frequency Deep Brain Stimulation and Neural Rhythms in Parkinson's Disease.

    Science.gov (United States)

    Blumenfeld, Zack; Brontë-Stewart, Helen

    2015-12-01

    High frequency (HF) deep brain stimulation (DBS) is an established therapy for the treatment of Parkinson's disease (PD). It effectively treats the cardinal motor signs of PD, including tremor, bradykinesia, and rigidity. The most common neural target is the subthalamic nucleus, located within the basal ganglia, the region most acutely affected by PD pathology. Using chronically-implanted DBS electrodes, researchers have been able to record underlying neural rhythms from several nodes in the PD network as well as perturb it using DBS to measure the ensuing neural and behavioral effects, both acutely and over time. In this review, we provide an overview of the PD neural network, focusing on the pathophysiological signals that have been recorded from PD patients as well as the mechanisms underlying the therapeutic benefits of HF DBS. We then discuss evidence for the relationship between specific neural oscillations and symptoms of PD, including the aberrant relationships potentially underlying functional connectivity in PD as well as the use of different frequencies of stimulation to more specifically target certain symptoms. Finally, we briefly describe several current areas of investigation and how the ability to record neural data in ecologically-valid settings may allow researchers to explore the relationship between brain and behavior in an unprecedented manner, culminating in the future automation of neurostimulation therapy for the treatment of a variety of neuropsychiatric diseases.

  11. The neural basis of theory of mind and its relationship to social functioning and social anhedonia in individuals with schizophrenia

    Directory of Open Access Journals (Sweden)

    David Dodell-Feder

    2014-01-01

    Full Text Available Theory of mind (ToM, the ability to attribute and reason about the mental states of others, is a strong determinant of social functioning among individuals with schizophrenia. Identifying the neural bases of ToM and their relationship to social functioning may elucidate functionally relevant neurobiological targets for intervention. ToM ability may additionally account for other social phenomena that affect social functioning, such as social anhedonia (SocAnh. Given recent research in schizophrenia demonstrating improved neural functioning in response to increased use of cognitive skills, it is possible that SocAnh, which decreases one's opportunity to engage in ToM, could compromise social functioning through its deleterious effect on ToM-related neural circuitry. Here, twenty individuals with schizophrenia and 18 healthy controls underwent fMRI while performing the False-Belief Task. Aspects of social functioning were assessed using multiple methods including self-report (Interpersonal Reactivity Index, Social Adjustment Scale, clinician-ratings (Global Functioning Social Scale, and performance-based tasks (MSCEIT—Managing Emotions. SocAnh was measured with the Revised Social Anhedonia Scale. Region-of-interest and whole-brain analyses revealed reduced recruitment of medial prefrontal cortex (MPFC for ToM in individuals with schizophrenia. Across all participants, activity in this region correlated with most social variables. Mediation analysis revealed that neural activity for ToM in MPFC accounted for the relationship between SocAnh and social functioning. These findings demonstrate that reduced recruitment of MPFC for ToM is an important neurobiological determinant of social functioning. Furthermore, SocAhn may affect social functioning through its impact on ToM-related neural circuitry. Together, these findings suggest ToM ability as an important locus for intervention.

  12. Principles of Experience-Dependent Neural Plasticity: Implications for Rehabilitation after Brain Damage

    Science.gov (United States)

    Kleim, Jeffrey A.; Jones, Theresa A.

    2008-01-01

    Purpose: This paper reviews 10 principles of experience-dependent neural plasticity and considerations in applying them to the damaged brain. Method: Neuroscience research using a variety of models of learning, neurological disease, and trauma are reviewed from the perspective of basic neuroscientists but in a manner intended to be useful for the…

  13. MRI visualization of endogenous neural progenitor cell migration along the RMS in the adult mouse brain

    DEFF Research Database (Denmark)

    Vreys, Ruth; Vande Velde, Greetje; Krylychkina, Olga

    2010-01-01

    The adult rodent brain contains neural progenitor cells (NPCs), generated in the subventricular zone (SVZ), which migrate along the rostral migratory stream (RMS) towards the olfactory bulb (OB) where they differentiate into neurons. The aim of this study was to visualize endogenous NPC migration...

  14. Feed-forward control for magnetic shape memory alloy actuators based on the radial basis function neural network model.

    Science.gov (United States)

    Zhou, Miaolei; Wang, Yifan; Xu, Rui; Zhang, Qi; Zhu, Dong

    2017-06-16

    Hysteresis exists in magnetic shape memory alloy (MSMA) actuators, which restricts MSMA actuators' application. To describe hysteresis of the MSMA actuators, a hysteresis model based on the radial basis function neural network (RBFNN) is put forward. Then, an inverse RBFNN model is set up, and it is compared with the inverse model based on the traditional cut-and-try method. Finally, to solve hysteresis of the actuators, an inverse model for MSMA actuators is used to build feed-forward controller. Simulation results show the maximum modeling error for inverse hysteresis model designed by neural network is 0.79% and compared with traditional cut-and-try method, the maximum modeling error decreases by 1.85%. The maximum tracking error rate of feed-forward control is 0.38%. The hysteresis of MSMA actuators is reduced. By using the feed-forward controller, high precision control is achieved.

  15. The Neural Basis of Sustained and Transient Attentional Control in Young Adults with ADHD

    Science.gov (United States)

    Banich, Marie T.; Burgess, Gregory C.; Depue, Brendan E.; Ruzic, Luka; Bidwell, L. Cinnamon; Hitt-Laustsen, Sena; Du, Yiping P.; Willcutt, Erik G.

    2009-01-01

    Differences in neural activation during performance on an attentionally demanding Stroop task were examined between 23 young adults with ADHD carefully selected to not be co-morbid for other psychiatric disorders and 23 matched controls. A hybrid blocked/single-trial design allowed for examination of more sustained vs. more transient aspects of…

  16. Dynamic neural networking as a basis for plasticity in the control of heart rate.

    Science.gov (United States)

    Kember, G; Armour, J A; Zamir, M

    2013-01-21

    A model is proposed in which the relationship between individual neurons within a neural network is dynamically changing to the effect of providing a measure of "plasticity" in the control of heart rate. The neural network on which the model is based consists of three populations of neurons residing in the central nervous system, the intrathoracic extracardiac nervous system, and the intrinsic cardiac nervous system. This hierarchy of neural centers is used to challenge the classical view that the control of heart rate, a key clinical index, resides entirely in central neuronal command (spinal cord, medulla oblongata, and higher centers). Our results indicate that dynamic networking allows for the possibility of an interplay among the three populations of neurons to the effect of altering the order of control of heart rate among them. This interplay among the three levels of control allows for different neural pathways for the control of heart rate to emerge under different blood flow demands or disease conditions and, as such, it has significant clinical implications because current understanding and treatment of heart rate anomalies are based largely on a single level of control and on neurons acting in unison as a single entity rather than individually within a (plastically) interconnected network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  17. [Molecular mechanism of brain regeneration and reconstruction of dopaminergic neural network in planarians].

    Science.gov (United States)

    Nishimura, Kaneyasu; Kitamura, Yoshihisa; Agata, Kiyokazu

    2008-04-01

    Recently, planarians have received much attention because of their contributions to research on the basic science of stem cell systems, neural regeneration, and regenerative medicine. Planarians can regenerate complete organs, including a well-organized central nervous system (CNS), within about 7 days. This high regenerative capacity is supported by pluripotent stem cells present in the mesenchymal space throughout the body. Interestingly, planarians can regenerate their brain via a molecular mechanism similar to that of mammalian brain development. The regeneration process of the planarian brain can be divided into five steps: (1) anterior blastema formation, (2) brain rudiment formation, (3) brain pattern formation, (4) neural network formation, and (5) functional recovery, with several kinds of genes and molecular cascades acting at each step. Recently, we have identified a planarian tyrosine hydroxylase (TH) gene, a rate-limiting enzyme for dopamine (DA) biosynthesis, and produced TH-knockdown planarians by the RNA interference technique. Studies of TH-knockdown planarians showed that DA has an important role of the modification in behavioral movement in planarians. Using monoclonal anti-planarian TH antibody, we also found that dopaminergic neurons are mainly localized in the planarian brain. When the planarian body was amputated, newly generated TH-immunopositive neurons were detected in the anterior region at day 3 of regeneration (i.e., the period of neural network formation), and the TH-immunopositive axonal and dendritic neural network in the CNS was reconstructed during day 5-7 of regeneration. In this article, recent advances in elucidating the molecular mechanism of planarian brain regeneration and dopaminergic neurons are reviewed, and its future prospects for contribution of this system to basic science and medical science research are described.

  18. Design of hybrid radial basis function neural networks (HRBFNNs) realized with the aid of hybridization of fuzzy clustering method (FCM) and polynomial neural networks (PNNs).

    Science.gov (United States)

    Huang, Wei; Oh, Sung-Kwun; Pedrycz, Witold

    2014-12-01

    In this study, we propose Hybrid Radial Basis Function Neural Networks (HRBFNNs) realized with the aid of fuzzy clustering method (Fuzzy C-Means, FCM) and polynomial neural networks. Fuzzy clustering used to form information granulation is employed to overcome a possible curse of dimensionality, while the polynomial neural network is utilized to build local models. Furthermore, genetic algorithm (GA) is exploited here to optimize the essential design parameters of the model (including fuzzification coefficient, the number of input polynomial fuzzy neurons (PFNs), and a collection of the specific subset of input PFNs) of the network. To reduce dimensionality of the input space, principal component analysis (PCA) is considered as a sound preprocessing vehicle. The performance of the HRBFNNs is quantified through a series of experiments, in which we use several modeling benchmarks of different levels of complexity (different number of input variables and the number of available data). A comparative analysis reveals that the proposed HRBFNNs exhibit higher accuracy in comparison to the accuracy produced by some models reported previously in the literature. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. Evolution of the neural basis of consciousness: a bird-mammal comparison.

    Science.gov (United States)

    Butler, Ann B; Manger, Paul R; Lindahl, B I B; Arhem, Peter

    2005-09-01

    The main objective of this essay is to validate some of the principal, currently competing, mammalian consciousness-brain theories by comparing these theories with data on both cognitive abilities and brain organization in birds. Our argument is that, given that multiple complex cognitive functions are correlated with presumed consciousness in mammals, this correlation holds for birds as well. Thus, the neuroanatomical features of the forebrain common to both birds and mammals may be those that are crucial to the generation of both complex cognition and consciousness. The general conclusion is that most of the consciousness-brain theories appear to be valid for the avian brain. Even though some specific homologies are unresolved, most of the critical structures presumed necessary for consciousness in mammalian brains have clear homologues in avian brains. Furthermore, considering the fact that the reptile-bird brain transition shows more structural continuity than the stem amniote-mammalian transition, the line drawn at the origin of mammals for consciousness by several of the theorists seems questionable. An equally important point is that consciousness cannot be ruled out in the absence of complex cognition; it may in fact be the case that consciousness is a necessary prerequisite for complex cognition.

  20. Iterative Radial Basis Functions Neural Networks as Metamodels of Stochastic Simulations of the Quality of Search Engines in the World Wide Web.

    Science.gov (United States)

    Meghabghab, George

    2001-01-01

    Discusses the evaluation of search engines and uses neural networks in stochastic simulation of the number of rejected Web pages per search query. Topics include the iterative radial basis functions (RBF) neural network; precision; response time; coverage; Boolean logic; regression models; crawling algorithms; and implications for search engine…

  1. Bitter taste stimuli induce differential neural codes in mouse brain.

    Directory of Open Access Journals (Sweden)

    David M Wilson

    Full Text Available A growing literature suggests taste stimuli commonly classified as "bitter" induce heterogeneous neural and perceptual responses. Here, the central processing of bitter stimuli was studied in mice with genetically controlled bitter taste profiles. Using these mice removed genetic heterogeneity as a factor influencing gustatory neural codes for bitter stimuli. Electrophysiological activity (spikes was recorded from single neurons in the nucleus tractus solitarius during oral delivery of taste solutions (26 total, including concentration series of the bitter tastants quinine, denatonium benzoate, cycloheximide, and sucrose octaacetate (SOA, presented to the whole mouth for 5 s. Seventy-nine neurons were sampled; in many cases multiple cells (2 to 5 were recorded from a mouse. Results showed bitter stimuli induced variable gustatory activity. For example, although some neurons responded robustly to quinine and cycloheximide, others displayed concentration-dependent activity (p<0.05 to quinine but not cycloheximide. Differential activity to bitter stimuli was observed across multiple neurons recorded from one animal in several mice. Across all cells, quinine and denatonium induced correlated spatial responses that differed (p<0.05 from those to cycloheximide and SOA. Modeling spatiotemporal neural ensemble activity revealed responses to quinine/denatonium and cycloheximide/SOA diverged during only an early, at least 1 s wide period of the taste response. Our findings highlight how temporal features of sensory processing contribute differences among bitter taste codes and build on data suggesting heterogeneity among "bitter" stimuli, data that challenge a strict monoguesia model for the bitter quality.

  2. Detection of Neural Activity in the Brains of Japanese Honeybee Workers during the Formation of a “Hot Defensive Bee Ball”

    Science.gov (United States)

    Ugajin, Atsushi; Kiya, Taketoshi; Kunieda, Takekazu; Ono, Masato; Yoshida, Tadaharu; Kubo, Takeo

    2012-01-01

    Anti-predator behaviors are essential to survival for most animals. The neural bases of such behaviors, however, remain largely unknown. Although honeybees commonly use their stingers to counterattack predators, the Japanese honeybee (Apis cerana japonica) uses a different strategy to fight against the giant hornet (Vespa mandarinia japonica). Instead of stinging the hornet, Japanese honeybees form a “hot defensive bee ball” by surrounding the hornet en masse, killing it with heat. The European honeybee (A. mellifera ligustica), on the other hand, does not exhibit this behavior, and their colonies are often destroyed by a hornet attack. In the present study, we attempted to analyze the neural basis of this behavior by mapping the active brain regions of Japanese honeybee workers during the formation of a hot defensive bee ball. First, we identified an A. cerana homolog (Acks = Apis cerana kakusei) of kakusei, an immediate early gene that we previously identified from A. mellifera, and showed that Acks has characteristics similar to kakusei and can be used to visualize active brain regions in A. cerana. Using Acks as a neural activity marker, we demonstrated that neural activity in the mushroom bodies, especially in Class II Kenyon cells, one subtype of mushroom body intrinsic neurons, and a restricted area between the dorsal lobes and the optic lobes was increased in the brains of Japanese honeybee workers involved in the formation of a hot defensive bee ball. In addition, workers exposed to 46°C heat also exhibited Acks expression patterns similar to those observed in the brains of workers involved in the formation of a hot defensive bee ball, suggesting that the neural activity observed in the brains of workers involved in the hot defensive bee ball mainly reflects thermal stimuli processing. PMID:22431987

  3. Unsupervised Neural Techniques Applied to MR Brain Image Segmentation

    Directory of Open Access Journals (Sweden)

    A. Ortiz

    2012-01-01

    Full Text Available The primary goal of brain image segmentation is to partition a given brain image into different regions representing anatomical structures. Magnetic resonance image (MRI segmentation is especially interesting, since accurate segmentation in white matter, grey matter and cerebrospinal fluid provides a way to identify many brain disorders such as dementia, schizophrenia or Alzheimer’s disease (AD. Then, image segmentation results in a very interesting tool for neuroanatomical analyses. In this paper we show three alternatives to MR brain image segmentation algorithms, with the Self-Organizing Map (SOM as the core of the algorithms. The procedures devised do not use any a priori knowledge about voxel class assignment, and results in fully-unsupervised methods for MRI segmentation, making it possible to automatically discover different tissue classes. Our algorithm has been tested using the images from the Internet Brain Image Repository (IBSR outperforming existing methods, providing values for the average overlap metric of 0.7 for the white and grey matter and 0.45 for the cerebrospinal fluid. Furthermore, it also provides good results for high-resolution MR images provided by the Nuclear Medicine Service of the “Virgen de las Nieves” Hospital (Granada, Spain.

  4. Radial glial neural progenitors regulate nascent brain vascular network stabilization via inhibition of Wnt signaling.

    Directory of Open Access Journals (Sweden)

    Shang Ma

    Full Text Available The cerebral cortex performs complex cognitive functions at the expense of tremendous energy consumption. Blood vessels in the brain are known to form stereotypic patterns that facilitate efficient oxygen and nutrient delivery. Yet little is known about how vessel development in the brain is normally regulated. Radial glial neural progenitors are well known for their central role in orchestrating brain neurogenesis. Here we show that, in the late embryonic cortex, radial glial neural progenitors also play a key role in brain angiogenesis, by interacting with nascent blood vessels and regulating vessel stabilization via modulation of canonical Wnt signaling. We find that ablation of radial glia results in vessel regression, concomitant with ectopic activation of Wnt signaling in endothelial cells. Direct activation of Wnt signaling also results in similar vessel regression, while attenuation of Wnt signaling substantially suppresses regression. Radial glial ablation and ectopic Wnt pathway activation leads to elevated endothelial expression of matrix metalloproteinases, while inhibition of metalloproteinase activity significantly suppresses vessel regression. These results thus reveal a previously unrecognized role of radial glial progenitors in stabilizing nascent brain vascular network and provide novel insights into the molecular cascades through which target neural tissues regulate vessel stabilization and patterning during development and throughout life.

  5. Taurine enhances the growth of neural precursors derived from fetal human brain and promotes neuronal specification.

    Science.gov (United States)

    Hernández-Benítez, Reyna; Vangipuram, Sharada D; Ramos-Mandujano, Gerardo; Lyman, William D; Pasantes-Morales, Herminia

    2013-01-01

    Taurine is present at high concentrations in the fetal brain and is required for optimal brain development. Recent studies have reported that taurine causes increased proliferation of neural stem/progenitor neural cells (neural precursor cells, NPCs) obtained from embryonic and adult rodent brain. The present study is the first to show that taurine markedly increases cell numbers in cultures and neuronal generation from human NPCs (hNPCs). hNPCs obtained from 3 fetal brains (14-15 weeks of gestation) were cultured and expanded as neurospheres, which contained 76.3% nestin-positive cells. Taurine (5-20 mM) increased the number of hNPCs in culture, with maximal effect found at 10 mM and 4 days of culture. The taurine-induced increase ranged from 57 to 188% in the 3 brains examined. Taurine significantly enhanced the percentage of neurons formed from hNPCs under differentiating conditions, with increases ranging from 172 to 480% over controls without taurine. Taurine also increased the cell number and neuronal generation in cultures of the immortalized human cell line ReNcell VM. These results suggest that taurine has a positive influence on hNPC growth and neuronal formation. Copyright © 2013 S. Karger AG, Basel.

  6. Simultaneous in vivo recording of local brain temperature and electrophysiological signals with a novel neural probe

    Science.gov (United States)

    Fekete, Z.; Csernai, M.; Kocsis, K.; Horváth, Á. C.; Pongrácz, A.; Barthó, P.

    2017-06-01

    Objective. Temperature is an important factor for neural function both in normal and pathological states, nevertheless, simultaneous monitoring of local brain temperature and neuronal activity has not yet been undertaken. Approach. In our work, we propose an implantable, calibrated multimodal biosensor that facilitates the complex investigation of thermal changes in both cortical and deep brain regions, which records multiunit activity of neuronal populations in mice. The fabricated neural probe contains four electrical recording sites and a platinum temperature sensor filament integrated on the same probe shaft within a distance of 30 µm from the closest recording site. The feasibility of the simultaneous functionality is presented in in vivo studies. The probe was tested in the thalamus of anesthetized mice while manipulating the core temperature of the animals. Main results. We obtained multiunit and local field recordings along with measurement of local brain temperature with accuracy of 0.14 °C. Brain temperature generally followed core body temperature, but also showed superimposed fluctuations corresponding to epochs of increased local neural activity. With the application of higher currents, we increased the local temperature by several degrees without observable tissue damage between 34-39 °C. Significance. The proposed multifunctional tool is envisioned to broaden our knowledge on the role of the thermal modulation of neuronal activity in both cortical and deeper brain regions.

  7. The exon junction complex component Magoh controls brain size by regulating neural stem cell division

    Science.gov (United States)

    Silver, Debra L.; Watkins-Chow, Dawn E.; Schreck, Karisa C.; Pierfelice, Tarran J.; Larson, Denise M.; Burnetti, Anthony J.; Liaw, Hung-Jiun; Myung, Kyungjae; Walsh, Christopher A.; Gaiano, Nicholas; Pavan, William J.

    2010-01-01

    Summary Brain structure and size requires precise division of neural stem cells (NSCs), which self-renew and generate intermediate neural progenitors (INPs) and neurons. The factors that regulate NSCs remain poorly understood, as do mechanistic explanations of how aberrant NSC division causes reduced brain size as seen in microcephaly. Here we demonstrate that Magoh, a component of the exon junction complex (EJC) that binds RNA, controls mouse cerebral cortical size by regulating NSC division. Magoh haploinsufficiency causes microcephaly due to INP depletion and neuronal apoptosis. Defective mitosis underlies these phenotypes as depletion of EJC components disrupts mitotic spindle orientation and integrity, chromosome number, and genomic stability. In utero rescue experiments revealed that a key function of Magoh is to control levels of the microcephaly-associated protein, LIS1, during neurogenesis. This study uncovers new requirements for the EJC in brain development, NSC maintenance, and mitosis, thus implicating this complex in the pathogenesis of microcephaly. PMID:20364144

  8. Dosha brain-types: A neural model of individual differences

    Directory of Open Access Journals (Sweden)

    Frederick T Travis

    2015-01-01

    Full Text Available This paper explores brain patterns associated with the three categories of regulatory principles of the body, mind, and behavior in Ayurveda, called Vata, Pitta, and Kapha dosha. A growing body of research has reported patterns of blood chemistry, genetic expression, physiological states, and chronic diseases associated with each dosha type. Since metabolic and growth factors are controlled by the nervous system, each dosha type should be associated with patterns of functioning of six major areas of the nervous system: The prefrontal cortex, the reticular activating system, the autonomic nervous system, the enteric nervous system, the limbic system, and the hypothalamus. For instance, the prefrontal cortex, which includes the anterior cingulate, ventral medial, and the dorsal lateral cortices, would exhibit a high range of functioning in the Vata brain-type leading to the possibility of being easily overstimulated. The Vata brain-type performs activity quickly. Learns quickly and forgets quickly. Their fast mind gives them an edge in creative problem solving. The Pitta brain-type reacts strongly to all challenges leading to purposeful and resolute actions. They never give up and are very dynamic and goal oriented. The Kapha brain-type is slow and steady leading to methodical thinking and action. They prefer routine and needs stimulation to get going. A model of dosha brain-types could provide a physiological foundation to understand individual differences. This model could help individualize treatment modalities to address different mental and physical dysfunctions. It also could explain differences in behavior seen in clinical as well as in normal populations.

  9. Dosha brain-types: A neural model of individual differences.

    Science.gov (United States)

    Travis, Frederick T; Wallace, Robert Keith

    2015-01-01

    This paper explores brain patterns associated with the three categories of regulatory principles of the body, mind, and behavior in Ayurveda, called Vata, Pitta, and Kapha dosha. A growing body of research has reported patterns of blood chemistry, genetic expression, physiological states, and chronic diseases associated with each dosha type. Since metabolic and growth factors are controlled by the nervous system, each dosha type should be associated with patterns of functioning of six major areas of the nervous system: The prefrontal cortex, the reticular activating system, the autonomic nervous system, the enteric nervous system, the limbic system, and the hypothalamus. For instance, the prefrontal cortex, which includes the anterior cingulate, ventral medial, and the dorsal lateral cortices, would exhibit a high range of functioning in the Vata brain-type leading to the possibility of being easily overstimulated. The Vata brain-type performs activity quickly. Learns quickly and forgets quickly. Their fast mind gives them an edge in creative problem solving. The Pitta brain-type reacts strongly to all challenges leading to purposeful and resolute actions. They never give up and are very dynamic and goal oriented. The Kapha brain-type is slow and steady leading to methodical thinking and action. They prefer routine and needs stimulation to get going. A model of dosha brain-types could provide a physiological foundation to understand individual differences. This model could help individualize treatment modalities to address different mental and physical dysfunctions. It also could explain differences in behavior seen in clinical as well as in normal populations.

  10. Systematic review of the neural basis of social cognition in patients with mood disorders

    Science.gov (United States)

    Cusi, Andrée M.; Nazarov, Anthony; Holshausen, Katherine; MacQueen, Glenda M.; McKinnon, Margaret C.

    2012-01-01

    Background This review integrates neuroimaging studies of 2 domains of social cognition — emotion comprehension and theory of mind (ToM) — in patients with major depressive disorder and bipolar disorder. The influence of key clinical and method variables on patterns of neural activation during social cognitive processing is also examined. Methods Studies were identified using PsycINFO and PubMed (January 1967 to May 2011). The search terms were “fMRI,” “emotion comprehension,” “emotion perception,” “affect comprehension,” “affect perception,” “facial expression,” “prosody,” “theory of mind,” “mentalizing” and “empathy” in combination with “major depressive disorder,” “bipolar disorder,” “major depression,” “unipolar depression,” “clinical depression” and “mania.” Results Taken together, neuroimaging studies of social cognition in patients with mood disorders reveal enhanced activation in limbic and emotion-related structures and attenuated activity within frontal regions associated with emotion regulation and higher cognitive functions. These results reveal an overall lack of inhibition by higher-order cognitive structures on limbic and emotion-related structures during social cognitive processing in patients with mood disorders. Critically, key variables, including illness burden, symptom severity, comorbidity, medication status and cognitive load may moderate this pattern of neural activation. Limitations Studies that did not include control tasks or a comparator group were included in this review. Conclusion Further work is needed to examine the contribution of key moderator variables and to further elucidate the neural networks underlying altered social cognition in patients with mood disorders. The neural networks underlying higher-order social cognitive processes, including empathy, remain unexplored in patients with mood disorders. PMID:22297065

  11. Neural Basis of Two Kinds of Social Influence: Obedience and Conformity

    OpenAIRE

    Ying eXie; Mingliang eChen; Hongxia eLai; Wuke eZhang; Zhen eZhao; Ch. Mahmood eAnwar

    2016-01-01

    Event-related potentials (ERPs) were used in this study to explore the neural mechanism of obedience and conformity on the model of online book purchasing. Participants were asked to decide as quickly as possible whether to buy a book based on limited information including its title, keywords and number of positive and negative reviews. Obedience was induced by forcing participants to buy books which received mostly negative reviews. In contrast, conformity was aroused by majority influence (...

  12. Neural basis of stereotype-induced shifts in women's mental rotation performance

    OpenAIRE

    Wraga, Maryjane; Helt, Molly; Jacobs, Emily; Sullivan, Kerry

    2007-01-01

    Recent negative focus on women's academic abilities has fueled disputes over gender disparities in the sciences. The controversy derives, in part, from women's relatively poorer performance in aptitude tests, many of which require skills of spatial reasoning. We used functional magnetic imaging to examine the neural structure underlying shifts in women's performance of a spatial reasoning task induced by positive and negative stereotypes. Three groups of participants performed a task involvin...

  13. Systematic review of the neural basis of social cognition in patients with mood disorders.

    Science.gov (United States)

    Cusi, Andrée M; Nazarov, Anthony; Holshausen, Katherine; Macqueen, Glenda M; McKinnon, Margaret C

    2012-05-01

    This review integrates neuroimaging studies of 2 domains of social cognition--emotion comprehension and theory of mind (ToM)--in patients with major depressive disorder and bipolar disorder. The influence of key clinical and method variables on patterns of neural activation during social cognitive processing is also examined. Studies were identified using PsycINFO and PubMed (January 1967 to May 2011). The search terms were "fMRI," "emotion comprehension," "emotion perception," "affect comprehension," "affect perception," "facial expression," "prosody," "theory of mind," "mentalizing" and "empathy" in combination with "major depressive disorder," "bipolar disorder," "major depression," "unipolar depression," "clinical depression" and "mania." Taken together, neuroimaging studies of social cognition in patients with mood disorders reveal enhanced activation in limbic and emotion-related structures and attenuated activity within frontal regions associated with emotion regulation and higher cognitive functions. These results reveal an overall lack of inhibition by higher-order cognitive structures on limbic and emotion-related structures during social cognitive processing in patients with mood disorders. Critically, key variables, including illness burden, symptom severity, comorbidity, medication status and cognitive load may moderate this pattern of neural activation. Studies that did not include control tasks or a comparator group were included in this review. Further work is needed to examine the contribution of key moderator variables and to further elucidate the neural networks underlying altered social cognition in patients with mood disorders. The neural networks under lying higher-order social cognitive processes, including empathy, remain unexplored in patients with mood disorders.

  14. Neural plasticity in hypocretin neurons: the basis of hypocretinergic regulation of physiological and behavioral functions in animals

    Directory of Open Access Journals (Sweden)

    Xiao-Bing eGao

    2015-10-01

    Full Text Available The neuronal system that resides in the perifornical and lateral hypothalamus (Pf/LH and synthesizes the neuropeptide hypocretin/orexin participates in critical brain functions across species from fish to human. The hypocretin system regulates neural activity responsible for daily functions (such as sleep/wake homeostasis, energy balance, appetite, etc and long-term behavioral changes (such as reward seeking and addiction, stress response, etc in animals. The most recent evidence suggests that the hypocretin system undergoes substantial plastic changes in response to both daily fluctuations (such as food intake and sleep-wake regulation and long-term changes (such as cocaine seeking in neuronal activity in the brain. The understanding of these changes in the hypocretin system is essential in addressing the role of the hypocretin system in normal physiological functions and pathological conditions in animals and humans. In this review, the evidence demonstrating that neural plasticity occurs in hypocretin-containing neurons in the Pf/LH will be presented and possible physiological behavioral, and mental health implications of these findings will be discussed.

  15. Neural plasticity in hypocretin neurons: the basis of hypocretinergic regulation of physiological and behavioral functions in animals

    Science.gov (United States)

    Gao, Xiao-Bing; Hermes, Gretchen

    2015-01-01

    The neuronal system that resides in the perifornical and lateral hypothalamus (Pf/LH) and synthesizes the neuropeptide hypocretin/orexin participates in critical brain functions across species from fish to human. The hypocretin system regulates neural activity responsible for daily functions (such as sleep/wake homeostasis, energy balance, appetite, etc.) and long-term behavioral changes (such as reward seeking and addiction, stress response, etc.) in animals. The most recent evidence suggests that the hypocretin system undergoes substantial plastic changes in response to both daily fluctuations (such as food intake and sleep-wake regulation) and long-term changes (such as cocaine seeking) in neuronal activity in the brain. The understanding of these changes in the hypocretin system is essential in addressing the role of the hypocretin system in normal physiological functions and pathological conditions in animals and humans. In this review, the evidence demonstrating that neural plasticity occurs in hypocretin-containing neurons in the Pf/LH will be presented and possible physiological, behavioral, and mental health implications of these findings will be discussed. PMID:26539086

  16. Native language experience shapes neural basis of addressed and assembled phonologies.

    Science.gov (United States)

    Mei, Leilei; Xue, Gui; Lu, Zhong-Lin; He, Qinghua; Wei, Miao; Zhang, Mingxia; Dong, Qi; Chen, Chuansheng

    2015-07-01

    Previous studies have suggested differential engagement of addressed and assembled phonologies in reading Chinese and alphabetic languages (e.g., English) and the modulatory role of native language in learning to read a second language. However, it is not clear whether native language experience shapes the neural mechanisms of addressed and assembled phonologies. To address this question, we trained native Chinese and native English speakers to read the same artificial language (based on Korean Hangul) either through addressed (i.e., whole-word mapping) or assembled (i.e., grapheme-to-phoneme mapping) phonology. We found that, for both native Chinese and native English speakers, addressed phonology relied on the regions in the ventral pathway, whereas assembled phonology depended on the regions in the dorsal pathway. More importantly, we found that the neural mechanisms of addressed and assembled phonologies were shaped by native language experience. Specifically, one key region for addressed phonology (i.e., the left middle temporal gyrus) showed greater activation for addressed phonology in native Chinese speakers, while one key region for assembled phonology (i.e., the left supramarginal gyrus) showed more activation for assembled phonology in native English speakers. These results provide direct neuroimaging evidence for the effect of native language experience on the neural mechanisms of phonological access in a new language and support the assimilation-accommodation hypothesis. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. The neural basis of non-native speech perception in bilingual children.

    Science.gov (United States)

    Archila-Suerte, Pilar; Zevin, Jason; Ramos, Aurora Isabel; Hernandez, Arturo E

    2013-02-15

    The goal of the present study is to reveal how the neural mechanisms underlying non-native speech perception change throughout childhood. In a pre-attentive listening fMRI task, English monolingual and Spanish-English bilingual children - divided into groups of younger (6-8yrs) and older children (9-10yrs) - were asked to watch a silent movie while several English syllable combinations played through a pair of headphones. Two additional groups of monolingual and bilingual adults were included in the analyses. Our results show that the neural mechanisms supporting speech perception throughout development differ in monolinguals and bilinguals. While monolinguals recruit perceptual areas (i.e., superior temporal gyrus) in early and late childhood to process native speech, bilinguals recruit perceptual areas (i.e., superior temporal gyrus) in early childhood and higher-order executive areas in late childhood (i.e., bilateral middle frontal gyrus and bilateral inferior parietal lobule, among others) to process non-native speech. The findings support the Perceptual Assimilation Model and the Speech Learning Model and suggest that the neural system processes phonological information differently depending on the stage of L2 speech learning. Published by Elsevier Inc.

  18. Native Language Experience Shapes Neural Basis of Addressed and Assembled Phonologies

    Science.gov (United States)

    Mei, Leilei; Xue, Gui; Lu, Zhong-Lin; He, Qinghua; Wei, Miao; Zhang, Mingxia; Dong, Qi; Chen, Chuansheng

    2015-01-01

    Previous studies have suggested differential engagement of addressed and assembled phonologies in reading Chinese and alphabetic languages (e.g., English) and the modulatory role of native language in learning to read a second language. However, it is not clear whether native language experience shapes the neural mechanisms of addressed and assembled phonologies. To address this question, we trained native Chinese and native English speakers to read the same artificial language (based on Korean Hangul) either through addressed (i.e., whole-word mapping) or assembled (i.e., grapheme-to-phoneme mapping) phonology. We found that, for both native Chinese and native English speakers, addressed phonology relied on the regions in the ventral pathway, whereas assembled phonology depended on the regions in the dorsal pathway. More importantly, we found that the neural mechanisms of addressed and assembled phonologies were shaped by native language experience. Specifically, two key regions for addressed phonology (i.e., the left middle temporal gyrus and right inferior temporal gyrus) showed greater activation for addressed phonology in native Chinese speakers, while one key region for assembled phonology (i.e., the left supramarginal gyrus) showed more activation for assembled phonology in native English speakers. These results provide direct neuroimaging evidence for the effect of native language experience on the neural mechanisms of phonological access in a new language and support the assimilation-accommodation hypothesis. PMID:25858447

  19. Brain basis of childhood speech and language disorders: are we closer to clinically meaningful MRI markers?

    Science.gov (United States)

    Morgan, Angela; Bonthrone, Alexandra; Liégeois, Frédérique J

    2016-12-01

    Developmental speech and language disorders are common, seen in one in 20 preschool children, in the absence of frank neurological deficits or intellectual impairment. They are a key reason parents seek help from paediatricians. Complex neurogenetic and environmental contributions underpin the disorders, yet few specific causes are known. With the advent of quantitative brain imaging, a growing number of studies have investigated neural contributions. Here, we discuss current MRI approaches and recent findings (January 2014-June 2016) in the field. Five relevant studies were identified (n = 3 - speech disorder and n = 2 - language disorder). Significant variability in MRI approaches and heterogeneity of participant phenotypes was seen. Children with speech disorder had structural and functional anomalies in the left supramarginal gyrus and functional anomalies in the posterior cerebellum bilaterally - regions critical for sensory-motor integration or feedback. Children with language disorder showed increased mean and radial diffusivity of the left arcuate fasciculus, although a widespread cortical and subcortical network of regions was implicated. Limited evidence exists for specific regional brain anomalies in this population. MRI prognostic markers of speech and language ability are not currently available at an individual level. Further work is required to disentangle neurobiological contributions to speech and language disorders for affected children.

  20. The Neural Bases of Reading: The Accommodation of the Brain's Reading Network to Writing Systems

    NARCIS (Netherlands)

    Perfetti, C.A.; Liu, Y.; Fiez, J.; Tan, L.H.; Cornelissen, P.; Hansen, P.; Kringelbach, M.; Pugh, K.

    2010-01-01

    This chapter explores the highly contrastive cases of English and Chinese to examine how the neural basis of reading accommodates variability in the structure of languages. The notion of accommodation, in fact, is central to the analysis. It argues that the reading network must accommodate variation

  1. Brain Tumor Tropism of Transplanted Human Neural Stem Cells Is Induced by Vascular Endothelial Growth Factor

    Directory of Open Access Journals (Sweden)

    Nils Ole Schmidt

    2005-06-01

    Full Text Available The transplantation of neural stem cells (NSCs offers a new potential therapeutic approach as a cell-based delivery system for gene therapy in brain tumors. This is based on the unique capacity of NSCs to migrate throughout the brain and to target invading tumor cells. However, the signals controlling the targeted migration of transplanted NSCs are poorly defined. We analyzed the in vitro and in vivo effects of angiogenic growth factors and protein extracts from surgical specimens of brain tumor patients on NSC migration. Here, we demonstrate that vascular endothelial growth factor (VEGF is able to induce a long-range attraction of transplanted human NSCs from distant sites in the adult brain. Our results indicate that tumorupregulated VEGF and angiogenic-activated microvasculature are relevant guidance signals for NSC tropism toward brain tumors.

  2. Brain basis of early parent-infant interactions: psychology, physiology, and in vivo functional neuroimaging studies.

    Science.gov (United States)

    Swain, James E; Lorberbaum, Jeffrey P; Kose, Samet; Strathearn, Lane

    2007-01-01

    Parenting behavior critically shapes human infants' current and future behavior. The parent-infant relationship provides infants with their first social experiences, forming templates of what they can expect from others and how to best meet others' expectations. In this review, we focus on the neurobiology of parenting behavior, including our own functional magnetic resonance imaging (fMRI) brain imaging experiments of parents. We begin with a discussion of background, perspectives and caveats for considering the neurobiology of parent-infant relationships. Then, we discuss aspects of the psychology of parenting that are significantly motivating some of the more basic neuroscience research. Following that, we discuss some of the neurohormones that are important for the regulation of social bonding, and the dysregulation of parenting with cocaine abuse. Then, we review the brain circuitry underlying parenting, proceeding from relevant rodent and nonhuman primate research to human work. Finally, we focus on a study-by-study review of functional neuroimaging studies in humans. Taken together, this research suggests that networks of highly conserved hypothalamic-midbrain-limbic-paralimbic-cortical circuits act in concert to support aspects of parent response to infants, including the emotion, attention, motivation, empathy, decision-making and other thinking that are required to navigate the complexities of parenting. Specifically, infant stimuli activate basal forebrain regions, which regulate brain circuits that handle specific nurturing and caregiving responses and activate the brain's more general circuitry for handling emotions, motivation, attention, and empathy--all of which are crucial for effective parenting. We argue that an integrated understanding of the brain basis of parenting has profound implications for mental health.

  3. Neural Correlates of Socioeconomic Status in the Developing Human Brain

    Science.gov (United States)

    Noble, Kimberly G.; Houston, Suzanne M.; Kan, Eric; Sowell, Elizabeth R.

    2012-01-01

    Socioeconomic disparities in childhood are associated with remarkable differences in cognitive and socio-emotional development during a time when dramatic changes are occurring in the brain. Yet, the neurobiological pathways through which socioeconomic status (SES) shapes development remain poorly understood. Behavioral evidence suggests that…

  4. Donor-derived brain tumor following neural stem cell transplantation in an ataxia telangiectasia patient.

    Directory of Open Access Journals (Sweden)

    Ninette Amariglio

    2009-02-01

    Full Text Available BACKGROUND: Neural stem cells are currently being investigated as potential therapies for neurodegenerative diseases, stroke, and trauma. However, concerns have been raised over the safety of this experimental therapeutic approach, including, for example, whether there is the potential for tumors to develop from transplanted stem cells. METHODS AND FINDINGS: A boy with ataxia telangiectasia (AT was treated with intracerebellar and intrathecal injection of human fetal neural stem cells. Four years after the first treatment he was diagnosed with a multifocal brain tumor. The biopsied tumor was diagnosed as a glioneuronal neoplasm. We compared the tumor cells and the patient's peripheral blood cells by fluorescent in situ hybridization using X and Y chromosome probes, by PCR for the amelogenin gene X- and Y-specific alleles, by MassArray for the ATM patient specific mutation and for several SNPs, by PCR for polymorphic microsatellites, and by human leukocyte antigen (HLA typing. Molecular and cytogenetic studies showed that the tumor was of nonhost origin suggesting it was derived from the transplanted neural stem cells. Microsatellite and HLA analysis demonstrated that the tumor is derived from at least two donors. CONCLUSIONS: This is the first report of a human brain tumor complicating neural stem cell therapy. The findings here suggest that neuronal stem/progenitor cells may be involved in gliomagenesis and provide the first example of a donor-derived brain tumor. Further work is urgently needed to assess the safety of these therapies.

  5. Neural Probes with Integrated Temperature Sensors for Monitoring Retina and Brain Implantation and Stimulation.

    Science.gov (United States)

    Wang, Jiaqi; Xie, Hui; Chung, Tsing; Chan, Leanne Lai Hang; Pang, Stella W

    2017-09-01

    Gold (Au) resistive temperature sensors were integrated on flexible polyimide-based neural probes to monitor temperature changes during neural probe implantation and stimulation. Temperature changes were measured as neural probes were implanted to infer the positions of the neural probes, and as the retina or the deep brain region was stimulated electrically. The temperature sensor consisted of a serpentine Au resistor and surrounded by four Au electrodes with 200 and [Formula: see text] diameter (dia.). The Au temperature sensors had temperature coefficient of 0.32%, and they were biocompatible and small in size. In vivo measurements of temperature changes during implantation and stimulation were carried out in the retina and deep brain region in rats. The desired implantation position was reached when temperature measured by the sensor increased to the calibrated level and became stable. There was no temperature increase when low level stimulation current of 8 and [Formula: see text] each for the two 200- and 400- [Formula: see text]-dia. electrodes, respectively, were applied. When higher level stimulation current of 100 and [Formula: see text] each were applied to the two 200- and 400- [Formula: see text]-dia. electrodes, respectively, maximum temperature increases of 1.2 °C in retina and 1 °C in deep brain region were found.

  6. Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease.

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    Voytek, Bradley; Knight, Robert T

    2015-06-15

    Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this article, we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low-frequency (communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders-including Parkinson's disease, autism, depression, schizophrenia, and anxiety-are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural gray or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states or their treatment are a product of how these physical processes affect dynamic network communication. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  7. When a loved one feels unfamiliar: a case study on the neural basis of Capgras delusion.

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    Thiel, Christiane M; Studte, Sara; Hildebrandt, Helmut; Huster, Rene; Weerda, Riklef

    2014-03-01

    Perception of familiar faces depends on a core system analysing visual appearance and an extended system dealing with inference of mental states and emotional responses. Damage to the core system impairs face perception as seen in prosopagnosia. In contrast, patients with Capgras delusion show intact face perception but believe that closely related persons are impostors. It has been suggested that two deficits are necessary for the delusion, an aberrant perceptual or affective experience that leads to a bizarre belief as well as an impaired ability to evaluate beliefs. Using functional magnetic resonance imaging, we compared neural activity to familiar and unfamiliar faces in a patient with Capgras delusion and an age matched control group. We provide evidence that Capgras delusion is related to dysfunctional activity in the extended face processing system. The patient, who developed the delusion for the partner after a large right prefrontal lesion sparing the ventromedial and medial orbitofrontal cortex, lacked neural activity to the partner's face in left posterior cingulate cortex and left posterior superior temporal sulcus. Further, we found impaired functional connectivity of the latter region with the left superior frontal gyrus and to a lesser extent with the right superior frontal sulcus/middle frontal gyrus. The findings of this case study suggest that the first factor in Capgras delusion may be reduced neural activity in the extended face processing system that deals with inference of mental states while the second factor may be due to a lesion in the right middle frontal gyrus. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Presenilins are required for maintenance of neural stem cells in the developing brain

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    Kim Woo-Young

    2008-01-01

    Full Text Available Abstract The early embryonic lethality of mutant mice bearing germ-line deletions of both presenilin genes precluded the study of their functions in neural development. We therefore employed the Cre-loxP technology to generate presenilin conditional double knockout (PS cDKO mice, in which expression of both presenilins is inactivated in neural progenitor cells (NPC or neural stem cells and their derivative neurons and glia beginning at embryonic day 11 (E11. In PS cDKO mice, dividing NPCs labeled by BrdU are decreased in number beginning at E13.5. By E15.5, fewer than 20% of NPCs remain in PS cDKO mice. The depletion of NPCs is accompanied by severe morphological defects and hemorrhages in the PS cDKO embryonic brain. Interkinetic nuclear migration of NPCs is also disrupted in PS cDKO embryos, as evidenced by displacement of S-phase and M-phase nuclei in the ventricular zone of the telencephalon. Furthermore, the depletion of neural progenitor cells in PS cDKO embryos is due to NPCs exiting cell cycle and differentiating into neurons rather than reentering cell cycle between E13.5 and E14.5 following PS inactivation in most NPCs. The length of cell cycle, however, is unchanged in PS cDKO embryos. Expression of Notch target genes, Hes1 and Hes5, is significantly decreased in PS cDKO brains, whereas Dll1 expression is up-regulated, indicating that Notch signaling is effectively blocked by PS inactivation. These findings demonstrate that presenilins are essential for neural progenitor cells to re-enter cell cycle and thus ensure proper expansion of neural progenitor pool during embryonic neural development.

  9. Optimal feedback control successfully explains changes in neural modulations during experiments with brain-machine interfaces

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    Miriam eZacksenhouse

    2015-05-01

    Full Text Available Recent experiments with brain-machine-interfaces (BMIs indicate that the extent of neural modulations increased abruptly upon starting to operate the interface, and especially after the monkey stopped moving its hand. In contrast, neural modulations that are correlated with the kinematics of the movement remained relatively unchanged. Here we demonstrate that similar changes are produced by simulated neurons that encode the relevant signals generated by an optimal feedback controller during simulated BMI experiments. The optimal feedback controller relies on state estimation that integrates both visual and proprioceptive feedback with prior estimations from an internal model. The processing required for optimal state estimation and control were conducted in the state-space, and neural recording was simulated by modeling two populations of neurons that encode either only the estimated state or also the control signal. Spike counts were generated as realizations of doubly stochastic Poisson processes with linear tuning curves. The model successfully reconstructs the main features of the kinematics and neural activity during regular reaching movements. Most importantly, the activity of the simulated neurons successfully reproduces the observed changes in neural modulations upon switching to brain control. Further theoretical analysis and simulations indicate that increasing the process noise during normal reaching movement results in similar changes in neural modulations. Thus we conclude that the observed changes in neural modulations during BMI experiments can be attributed to increasing process noise associated with the imperfect BMI filter, and, more directly, to the resulting increase in the variance of the encoded signals associated with state estimation and the required control signal.

  10. Combining decoder design and neural adaptation in brain-machine interfaces.

    Science.gov (United States)

    Shenoy, Krishna V; Carmena, Jose M

    2014-11-19

    Brain-machine interfaces (BMIs) aim to help people with paralysis by decoding movement-related neural signals into control signals for guiding computer cursors, prosthetic arms, and other assistive devices. Despite compelling laboratory experiments and ongoing FDA pilot clinical trials, system performance, robustness, and generalization remain challenges. We provide a perspective on how two complementary lines of investigation, that have focused on decoder design and neural adaptation largely separately, could be brought together to advance BMIs. This BMI paradigm should also yield new scientific insights into the function and dysfunction of the nervous system. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. The Future Vocation of Neural Stem Cells: Lineage Commitment in Brain Development and Evolution.

    Science.gov (United States)

    Nomura, Tadashi; Gotoh, Hitoshi; Ono, Katsuhiko

    2017-08-24

    Understanding the fate commitment of neural stem cells is critical to identify the regulatory mechanisms in developing brains. Genetic lineage-tracing has provided a powerful strategy to unveil the heterogeneous nature of stem cells and their descendants. However, recent studies have reported controversial data regarding the heterogeneity of neural stem cells in the developing mouse neocortex, which prevents a decisive conclusion on this issue. Here, we review the progress that has been made using lineage-tracing analyses of the developing neocortex and discuss stem cell heterogeneity from the viewpoint of comparative and evolutionary biology.

  12. Evolvable neuronal paths: a novel basis for information and search in the brain.

    Science.gov (United States)

    Fernando, Chrisantha; Vasas, Vera; Szathmáry, Eörs; Husbands, Phil

    2011-01-01

    We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques) which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard 'genetic' informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA) is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain.

  13. Evolvable neuronal paths: a novel basis for information and search in the brain.

    Directory of Open Access Journals (Sweden)

    Chrisantha Fernando

    Full Text Available We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard 'genetic' informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain.

  14. Exploring the Neural Basis of Fairness: A Model of Neuro-Organizational Justice

    Science.gov (United States)

    Beugre, Constant D.

    2009-01-01

    Drawing from the literature in neuroeconomics, organizational justice, and social cognitive neuroscience, I propose a model of neuro-organizational justice that explores the role of the brain in how people form fairness judgments and react to situations of fairness and/or unfairness in organizations. The model integrates three levels of analysis:…

  15. Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders.

    Directory of Open Access Journals (Sweden)

    Michelle Hampson

    2010-08-01

    Full Text Available There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

  16. Could LC-NE-Dependent Adjustment of Neural Gain Drive Functional Brain Network Reorganization?

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    Carole Guedj

    2017-01-01

    Full Text Available The locus coeruleus-norepinephrine (LC-NE system is thought to act at synaptic, cellular, microcircuit, and network levels to facilitate cognitive functions through at least two different processes, not mutually exclusive. Accordingly, as a reset signal, the LC-NE system could trigger brain network reorganizations in response to salient information in the environment and/or adjust the neural gain within its target regions to optimize behavioral responses. Here, we provide evidence of the co-occurrence of these two mechanisms at the whole-brain level, in resting-state conditions following a pharmacological stimulation of the LC-NE system. We propose that these two mechanisms are interdependent such that the LC-NE-dependent adjustment of the neural gain inferred from the clustering coefficient could drive functional brain network reorganizations through coherence in the gamma rhythm. Via the temporal dynamic of gamma-range band-limited power, the release of NE could adjust the neural gain, promoting interactions only within the neuronal populations whose amplitude envelopes are correlated, thus making it possible to reorganize neuronal ensembles, functional networks, and ultimately, behavioral responses. Thus, our proposal offers a unified framework integrating the putative influence of the LC-NE system on both local- and long-range adjustments of brain dynamics underlying behavioral flexibility.

  17. Uniform and Non-uniform Perturbations in Brain-Machine Interface Task Elicit Similar Neural Strategies.

    Science.gov (United States)

    Armenta Salas, Michelle; Helms Tillery, Stephen I

    2016-01-01

    The neural mechanisms that take place during learning and adaptation can be directly probed with brain-machine interfaces (BMIs). We developed a BMI controlled paradigm that enabled us to enforce learning by introducing perturbations which changed the relationship between neural activity and the BMI's output. We introduced a uniform perturbation to the system, through a visuomotor rotation (VMR), and a non-uniform perturbation, through a decorrelation task. The controller in the VMR was essentially unchanged, but produced an output rotated at 30° from the neurally specified output. The controller in the decorrelation trials decoupled the activity of neurons that were highly correlated in the BMI task by selectively forcing the preferred directions of these cell pairs to be orthogonal. We report that movement errors were larger in the decorrelation task, and subjects needed more trials to restore performance back to baseline. During learning, we measured decreasing trends in preferred direction changes and cross-correlation coefficients regardless of task type. Conversely, final adaptations in neural tunings were dependent on the type controller used (VMR or decorrelation). These results hint to the similar process the neural population might engage while adapting to new tasks, and how, through a global process, the neural system can arrive to individual solutions.

  18. The neural basis of understanding the expression of the emotions in man and animals.

    Science.gov (United States)

    Spunt, Robert P; Ellsworth, Emily; Adolphs, Ralph

    2017-01-01

    Humans cannot help but attribute human emotions to non-human animals. Although such attributions are often regarded as gratuitous anthropomorphisms and held apart from the attributions humans make about each other's internal states, they may be the product of a general mechanism for flexibly interpreting adaptive behavior. To examine this, we used functional magnetic resonance imaging (fMRI) in humans to compare the neural mechanisms associated with attributing emotions to humans and non-human animal behavior. Although undergoing fMRI, participants first passively observed the facial displays of human, non-human primate and domestic dogs, and subsequently judged the acceptability of emotional (e.g. 'annoyed') and facial descriptions (e.g. 'baring teeth') for the same images. For all targets, emotion attributions selectively activated regions in prefrontal and anterior temporal cortices associated with causal explanation in prior studies. These regions were similarly activated by both human and non-human targets even during the passive observation task; moreover, the degree of neural similarity was dependent on participants' self-reported beliefs in the mental capacities of non-human animals. These results encourage a non-anthropocentric view of emotion understanding, one that treats the idea that animals have emotions as no more gratuitous than the idea that humans other than ourselves do. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  19. Neural Stem Cell Transplantation Promotes Functional Recovery from Traumatic Brain Injury via Brain Derived Neurotrophic Factor-Mediated Neuroplasticity.

    Science.gov (United States)

    Xiong, Liu-Lin; Hu, Yue; Zhang, Piao; Zhang, Zhuo; Li, Li-Hong; Gao, Guo-Dong; Zhou, Xin-Fu; Wang, Ting-Hua

    2017-04-18

    Traumatic brain injury (TBI) induces cognitive impairments, motor and behavioral deficits. Previous evidences have suggested that neural stem cell (NSC) transplantation could facilitate functional recovery from brain insults, but their underlying mechanisms remains to be elucidated. Here, we established TBI model by an electromagnetic-controlled cortical impact device in the rats. Then, 5 μl NSCs (5.0 × 10 5 /μl), derived from green fluorescent protein (GFP) transgenic mouse, was transplanted into the traumatic brain regions of rats at 24 h after injury. After differentiation of the NSCs was determined using immunohistochemistry, neurological severity scores (NSS) and rotarod test were conducted to detect the neurological behavior. Western blot and RT-PCR as well as ELASA were used to evaluate the expression of synaptophysin and brain-derived neurotrophic factor (BDNF). In order to elucidate the role of BDNF on the neural recovery after NSC transplantation, BDNF knockdown in NSC was performed and transplanted into the rats with TBI, and potential mechanism for BDNF knockdown in the NSC was analyzed using microassay analysis. Meanwhile, BDNF antibody blockade was conducted to further confirm the effect of BDNF on neural activity. As a result, an increasing neurological function improvement was seen in NSC transplanted rats, which was associated with the upregulation of synaptophysin and BDNF expression. Moreover, transplantation of BDNF knockdown NSCs and BDNF antibody block reduced not only the level of synaptophysin but also exacerbated neurological function deficits. Microassay analysis showed that 14 genes such as Wnt and Gsk3-β were downregulated after BDNF knockdown. The present data therefore showed that BDNF-mediated neuroplasticity underlie the mechanism of NSC transplantation for the treatment of TBI in adult rats.

  20. The neural basis of hand gesture comprehension: A meta-analysis of functional magnetic resonance imaging studies.

    Science.gov (United States)

    Yang, Jie; Andric, Michael; Mathew, Mili M

    2015-10-01

    Gestures play an important role in face-to-face communication and have been increasingly studied via functional magnetic resonance imaging. Although a large amount of data has been provided to describe the neural substrates of gesture comprehension, these findings have never been quantitatively summarized and the conclusion is still unclear. This activation likelihood estimation meta-analysis investigated the brain networks underpinning gesture comprehension while considering the impact of gesture type (co-speech gestures vs. speech-independent gestures) and task demand (implicit vs. explicit) on the brain activation of gesture comprehension. The meta-analysis of 31 papers showed that as hand actions, gestures involve a perceptual-motor network important for action recognition. As meaningful symbols, gestures involve a semantic network for conceptual processing. Finally, during face-to-face interactions, gestures involve a network for social emotive processes. Our finding also indicated that gesture type and task demand influence the involvement of the brain networks during gesture comprehension. The results highlight the complexity of gesture comprehension, and suggest that future research is necessary to clarify the dynamic interactions among these networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. Brain-machine interface control of a manipulator using small-world neural network and shared control strategy.

    Science.gov (United States)

    Li, Ting; Hong, Jun; Zhang, Jinhua; Guo, Feng

    2014-03-15

    The improvement of the resolution of brain signal and the ability to control external device has been the most important goal in BMI research field. This paper describes a non-invasive brain-actuated manipulator experiment, which defined a paradigm for the motion control of a serial manipulator based on motor imagery and shared control. The techniques of component selection, spatial filtering and classification of motor imagery were involved. Small-world neural network (SWNN) was used to classify five brain states. To verify the effectiveness of the proposed classifier, we replace the SWNN classifier by a radial basis function (RBF) networks neural network, a standard multi-layered feed-forward backpropagation network (SMN) and a multi-SVM classifier, with the same features for the classification. The results also indicate that the proposed classifier achieves a 3.83% improvement over the best results of other classifiers. We proposed a shared control method consisting of two control patterns to expand the control of BMI from the software angle. The job of path building for reaching the 'end' point was designated as an assessment task. We recorded all paths contributed by subjects and picked up relevant parameters as evaluation coefficients. With the assistance of two control patterns and series of machine learning algorithms, the proposed BMI originally achieved the motion control of a manipulator in the whole workspace. According to experimental results, we confirmed the feasibility of the proposed BMI method for 3D motion control of a manipulator using EEG during motor imagery. Copyright © 2013 Elsevier B.V. All rights reserved.

  2. Neural basis of attachment-caregiving systems interaction: insights from neuroimaging studies

    Science.gov (United States)

    Lenzi, Delia; Trentini, Cristina; Tambelli, Renata; Pantano, Patrizia

    2015-01-01

    The attachment and the caregiving system are complementary systems which are active simultaneously in infant and mother interactions. This ensures the infant survival and optimal social, emotional, and cognitive development. In this brief review we first define the characteristics of these two behavioral systems and the theory that links them, according to what Bowlby called the “attachment-caregiving social bond” (Bowlby, 1969). We then follow with those neuroimaging studies that have focused on this particular issue, i.e., those which have studied the activation of the careging system in women (using infant stimuli) and have explored how the individual attachment model (through the Adult Attachment Interview) modulates its activity. Studies report altered activation in limbic and prefrontal areas and in basal ganglia and hypothalamus/pituitary regions. These altered activations are thought to be the neural substrate of the attachment-caregiving systems interaction. PMID:26379578

  3. Neural basis of attachment-caregiving systems interaction:insights from neuroimaging

    Directory of Open Access Journals (Sweden)

    Delia eLenzi

    2015-08-01

    Full Text Available The attachment and the caregiving system are complementary systems which are active simultaneously in infant and mother interactions. This ensures the infant survival and optimal social, emotional and cognitive development. In this brief review we first define the characteristics of these two behavioral systems and the theory that links them, according to what Bowlby called the attachment-caregiving social bond (Bowlby, 1969. We then follow with those neuroimaging studies that have focused on this particular issue, i.e. those which have studied the activation of the careging system in women (using infant stimuli and have explored how the individual attachment model (through the Adult Attachment Interview modulates its activity. Studies report altered activation in limbic and prefrontal areas and in basal ganglia and hypothalamus/pituitary regions. These altered activations are thought to be the neural substrate of the attachment-caregiving systems interaction.

  4. Modulating neural plasticity with non-invasive brain stimulation in schizophrenia.

    Science.gov (United States)

    Hasan, Alkomiet; Wobrock, Thomas; Rajji, Tarek; Malchow, Berend; Daskalakis, Zafiris J

    2013-12-01

    Schizophrenia is a severe mental disorder characterised by a complex phenotype including positive, negative, affective and cognitive symptoms. Various theories have been developed to integrate the clinical phenotype into a strong neurobiological framework. One theory describes schizophrenia as a disorder of impaired neural plasticity. Recently, non-invasive brain stimulation techniques have garnered much attention to their ability to modulate plasticity and treat schizophrenia. The aim of this review is to introduce the basic physiological principles of conventional non-invasive brain stimulation techniques and to review the available evidence for schizophrenia. Despite promising evidence for efficacy in a large number of clinical trials, we continue to have a rudimentary understanding of the underlying neurobiology. Additional investigation is required to improve the response rates to non-invasive brain stimulation, to reduce the interindividual variability and to improve the understanding of non-invasive brain stimulation in schizophrenia.

  5. Structural basis for cholinergic regulation of neural circuits in the mouse olfactory bulb.

    Science.gov (United States)

    Hamamoto, Masakazu; Kiyokage, Emi; Sohn, Jaerin; Hioki, Hiroyuki; Harada, Tamotsu; Toida, Kazunori

    2017-02-15

    Odor information is regulated by olfactory inputs, bulbar interneurons, and centrifugal inputs in the olfactory bulb (OB). Cholinergic neurons projecting from the nucleus of the horizontal limb of the diagonal band of Broca and the magnocellular preoptic nucleus are one of the primary centrifugal inputs to the OB. In this study, we focused on cholinergic regulation of the OB and analyzed neural morphology with a particular emphasis on the projection pathways of cholinergic neurons. Single-cell imaging of a specific neuron within dense fibers is critical to evaluate the structure and function of the neural circuits. We labeled cholinergic neurons by infection with virus vector and then reconstructed them three-dimensionally. We also examined the ultramicrostructure of synapses by electron microscopy tomography. To further clarify the function of cholinergic neurons, we performed confocal laser scanning microscopy to investigate whether other neurotransmitters are present within cholinergic axons in the OB. Our results showed the first visualization of complete cholinergic neurons, including axons projecting to the OB, and also revealed frequent axonal branching within the OB where it innervated multiple glomeruli in different areas. Furthermore, electron tomography demonstrated that cholinergic axons formed asymmetrical synapses with a morphological variety of thicknesses of the postsynaptic density. Although we have not yet detected the presence of other neurotransmitters, the range of synaptic morphology suggests multiple modes of transmission. The present study elucidates the ways that cholinergic neurons could contribute to the elaborate mechanisms involved in olfactory processing in the OB. J. Comp. Neurol. 525:574-591, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  6. Neural basis of the time window for subjective motor-auditory integration

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    Koichi eToida

    2016-01-01

    Full Text Available Temporal contiguity between an action and corresponding auditory feedback is crucial to the perception of self-generated sound. However, the neural mechanisms underlying motor–auditory temporal integration are unclear. Here, we conducted four experiments with an oddball paradigm to examine the specific event-related potentials (ERPs elicited by delayed auditory feedback for a self-generated action. The first experiment confirmed that a pitch-deviant auditory stimulus elicits mismatch negativity (MMN and P300, both when it is generated passively and by the participant’s action. In our second and third experiments, we investigated the ERP components elicited by delayed auditory feedback of for a self-generated action. We found that delayed auditory feedback elicited an enhancement of P2 (enhanced-P2 and a N300 component, which were apparently different from the MMN and P300 components observed in the first experiment. We further investigated the sensitivity of the enhanced-P2 and N300 to delay length in our fourth experiment. Strikingly, the amplitude of the N300 increased as a function of the delay length. Additionally, the N300 amplitude was significantly correlated with the conscious detection of the delay (the 50% detection point was around 200 ms, and hence reduction in the feeling of authorship of the sound (the sense of agency. In contrast, the enhanced-P2 was most prominent in short-delay (≤ 200 ms conditions and diminished in long-delay conditions. Our results suggest that different neural mechanisms are employed for the processing of temporally-deviant and pitch-deviant auditory feedback. Additionally, the temporal window for subjective motor–auditory integration is likely about 200 ms, as indicated by these auditory ERP components.

  7. Dopaminergic differentiation of human neural stem cells mediated by co-cultured rat striatal brain slices

    DEFF Research Database (Denmark)

    Anwar, Mohammad Raffaqat; Andreasen, Christian Maaløv; Lippert, Solvej Kølvraa

    2008-01-01

    differentiation, we co-cultured cells from a human neural forebrain-derived stem cell line (hNS1) with rat striatal brain slices. In brief, coronal slices of neonatal rat striatum were cultured on semiporous membrane inserts placed in six-well trays overlying monolayers of hNS1 cells. After 12 days of co......Properly committed neural stem cells constitute a promising source of cells for transplantation in Parkinson's disease, but a protocol for controlled dopaminergic differentiation is not yet available. To establish a setting for identification of secreted neural compounds promoting dopaminergic......-culture, large numbers of tyrosine hydroxylase (TH)-immunoreactive, catecholaminergic cells could be found underneath individual striatal slices. Cell counting revealed that up to 25.3% (average 16.1%) of the total number of cells in these areas were TH-positive, contrasting a few TH-positive cells (

  8. Complement peptide C3a stimulates neural plasticity after experimental brain ischaemia.

    Science.gov (United States)

    Stokowska, Anna; Atkins, Alison L; Morán, Javier; Pekny, Tulen; Bulmer, Linda; Pascoe, Michaela C; Barnum, Scott R; Wetsel, Rick A; Nilsson, Jonas A; Dragunow, Mike; Pekna, Marcela

    2017-02-01

    Ischaemic stroke induces endogenous repair processes that include proliferation and differentiation of neural stem cells and extensive rewiring of the remaining neural connections, yet about 50% of stroke survivors live with severe long-term disability. There is an unmet need for drug therapies to improve recovery by promoting brain plasticity in the subacute to chronic phase after ischaemic stroke. We previously showed that complement-derived peptide C3a regulates neural progenitor cell migration and differentiation in vitro and that C3a receptor signalling stimulates neurogenesis in unchallenged adult mice. To determine the role of C3a-C3a receptor signalling in ischaemia-induced neural plasticity, we subjected C3a receptor-deficient mice, GFAP-C3a transgenic mice expressing biologically active C3a in the central nervous system, and their respective wild-type controls to photothrombotic stroke. We found that C3a overexpression increased, whereas C3a receptor deficiency decreased post-stroke expression of GAP43 (P plasticity, in the peri-infarct cortex. To verify the translational potential of these findings, we used a pharmacological approach. Daily intranasal treatment of wild-type mice with C3a beginning 7 days after stroke induction robustly increased synaptic density (P neural plasticity and intranasal treatment with C3a receptor agonists is an attractive approach to improve functional recovery after ischaemic brain injury. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  9. Microinjection of membrane-impermeable molecules into single neural stem cells in brain tissue.

    Science.gov (United States)

    Wong, Fong Kuan; Haffner, Christiane; Huttner, Wieland B; Taverna, Elena

    2014-05-01

    This microinjection protocol allows the manipulation and tracking of neural stem and progenitor cells in tissue at single-cell resolution. We demonstrate how to apply microinjection to organotypic brain slices obtained from mice and ferrets; however, our technique is not limited to mouse and ferret embryos, but provides a means of introducing a wide variety of membrane-impermeable molecules (e.g., nucleic acids, proteins, hydrophilic compounds) into neural stem and progenitor cells of any developing mammalian brain. Microinjection experiments are conducted by using a phase-contrast microscope equipped with epifluorescence, a transjector and a micromanipulator. The procedure normally takes ∼2 h for an experienced researcher, and the entire protocol, including tissue processing, can be performed within 1 week. Thus, microinjection is a unique and versatile method for changing and tracking the fate of a cell in organotypic slice culture.

  10. Role of astrocytes as neural stem cells in the adult brain

    Science.gov (United States)

    Gonzalez-Perez, Oscar; Quiñones-Hinojosa, Alfredo

    2012-01-01

    In the adult mammalian brain, bona fide neural stem cells were discovered in the subventricular zone (SVZ), the largest neurogenic niche lining the striatal wall of the lateral ventricles of the brain. In this region resides a subpopulation of astrocytes that express the glial fibrillary acidic protein (GFAP), nestin and LeX. Astonishingly, these GFAP-expressing progenitors display stem-cell-like features both in vivo and in vitro. Throughout life SVZ astrocytes give rise to interneurons and oligodendrocyte precursors, which populate the olfactory bulb and the white matter, respectively. The role of the progenies of SVZ astrocytes has not been fully elucidated, but some evidence indicates that the new neurons play a role in olfactory discrimination, whereas oligodendrocytes contribute to myelinate white matter tracts. In this chapter, we describe the astrocytic nature of adult neural stem cells, their organization into the SVZ and some of their molecular and genetic characteristics. PMID:23619383

  11. Classification of brain compartments and head injury lesions by neural networks applied to MRI

    Energy Technology Data Exchange (ETDEWEB)

    Kischell, E.R. [Dept. of Electrical Engineering, Texas A and M Univ., College Station, TX (United States); Kehtarnavaz, N. [Dept. of Electrical Engineering, Texas A and M Univ., College Station, TX (United States); Hillman, G.R. [Dept. of Pharmacology, Univ. of Texas Medical Branch, Galveston, TX (United States); Levin, H. [Dept. of Neurosurgery, Univ. of Texas Medical Branch, Galveston, TX (United States); Lilly, M. [Dept. of Neurosurgery, Univ. of Texas Medical Branch, Galveston, TX (United States); Kent, T.A. [Dept. of Neurology and Psychiatry, Univ. of Texas Medical Branch, Galveston, TX (United States)

    1995-10-01

    An automatic, neural network-based approach was applied to segment normal brain compartments and lesions on MR images. Two supervised networks, backpropagation (BPN) and counterpropagation, and two unsupervised networks, Kohonen learning vector quantizer and analog adaptive resonance theory, were trained on registered T2-weighted and proton density images. The classes of interest were background, gray matter, white matter, cerebrospinal fluid, macrocystic encephalomalacia, gliosis, and `unknown`. A comprehensive feature vector was chosen to discriminate these classes. The BPN combined with feature conditioning, multiple discriminant analysis followed by Hotelling transform, produced the most accurate and consistent classification results. Classifications of normal brain compartments were generally in agreement with expert interpretation of the images. Macrocystic encephalomalacia and gliosis were recognized and, except around the periphery, classified in agreement with the clinician`s report used to train the neural network. (orig.)

  12. Classification of brain compartments and head injury lesions by neural networks applied to MRI.

    Science.gov (United States)

    Kischell, E R; Kehtarnavaz, N; Hillman, G R; Levin, H; Lilly, M; Kent, T A

    1995-10-01

    An automatic, neural network-based approach was applied to segment normal brain compartments and lesions on MR images. Two supervised networks, backpropagation (BPN) and counterpropagation, and two unsupervised networks, Kohonen learning vector quantizer and analog adaptive resonance theory, were trained on registered T2-weighted and proton density images. The classes of interest were background, gray matter, white matter, cerebrospinal fluid, macrocystic encephalomalacia, gliosis, and "unknown." A comprehensive feature vector was chosen to discriminate these classes. The BPN combined with feature conditioning, multiple discriminant analysis followed by Hotelling transform, produced the most accurate and consistent classification results. Classification of normal brain compartments were generally in agreement with expert interpretation of the images. Macrocystic encephalomalacia and gliosis were recognized and, except around the periphery, classified in agreement with the clinician's report used to train the neural network.

  13. Astrocytic Calcium Waves Signal Brain Injury to Neural Stem and Progenitor Cells

    Directory of Open Access Journals (Sweden)

    Anna Kraft

    2017-03-01

    Full Text Available Brain injuries, such as stroke or trauma, induce neural stem cells in the subventricular zone (SVZ to a neurogenic response. Very little is known about the molecular cues that signal tissue damage, even over large distances, to the SVZ. Based on our analysis of gene expression patterns in the SVZ, 48 hr after an ischemic lesion caused by middle cerebral artery occlusion, we hypothesized that the presence of an injury might be transmitted by an astrocytic traveling calcium wave rather than by diffusible factors or hypoxia. Using a newly established in vitro system we show that calcium waves induced in an astrocytic monolayer spread to neural stem and progenitor cells and increase their self-renewal as well as migratory behavior. These changes are due to an upregulation of the Notch signaling pathway. This introduces the concept of propagating astrocytic calcium waves transmitting brain injury signals over long distances.

  14. Evaluation of Raman spectra of human brain tumor tissue using the learning vector quantization neural network

    Science.gov (United States)

    Liu, Tuo; Chen, Changshui; Shi, Xingzhe; Liu, Chengyong

    2016-05-01

    The Raman spectra of tissue of 20 brain tumor patients was recorded using a confocal microlaser Raman spectroscope with 785 nm excitation in vitro. A total of 133 spectra were investigated. Spectra peaks from normal white matter tissue and tumor tissue were analyzed. Algorithms, such as principal component analysis, linear discriminant analysis, and the support vector machine, are commonly used to analyze spectral data. However, in this study, we employed the learning vector quantization (LVQ) neural network, which is typically used for pattern recognition. By applying the proposed method, a normal diagnosis accuracy of 85.7% and a glioma diagnosis accuracy of 89.5% were achieved. The LVQ neural network is a recent approach to excavating Raman spectra information. Moreover, it is fast and convenient, does not require the spectra peak counterpart, and achieves a relatively high accuracy. It can be used in brain tumor prognostics and in helping to optimize the cutting margins of gliomas.

  15. BrainCrafter: An investigation into human-based neural network engineering

    DEFF Research Database (Denmark)

    Piskur, J.; Greve, P.; Togelius, J.

    2015-01-01

    This paper presents the online application Brain-Crafter, in which users can manually build artificial neural networks (ANNs) to control a robot in a maze environment. Users can either start to construct networks from scratch or elaborate on networks created by other users. In particular, Brain......Crafter was designed to study how good we as humans are at building ANNs for control problems and if collaborating with other users can facilitate this process. The results in this paper show that (1) some users were in fact able to successfully construct ANNs that solve the navigation tasks, (2) collaboration between...

  16. Asynchronous BCI and local neural classifiers: an overview of the Adaptive Brain Interface project.

    Science.gov (United States)

    Millán, José del R; Mouriño, Josep

    2003-06-01

    In this communication, we give an overview of our work on an asynchronous brain-computer interface (where the subject makes self-paced decisions on when to switch from one mental task to the next) that responds every 0.5 s. A local neural classifier tries to recognize three different mental tasks; it may also respond "unknown" for uncertain samples as the classifier has incorporated statistical rejection criteria. We report our experience with 15 subjects. We also briefly describe two brain-actuated applications we have developed: a virtual keyboard and a mobile robot (emulating a motorized wheelchair).

  17. Neural coding of movement direction in the healthy human brain.

    Directory of Open Access Journals (Sweden)

    Christopher D Cowper-Smith

    2010-10-01

    Full Text Available Neurophysiological studies in monkeys show that activity of neurons in primary cortex (M1, pre-motor cortex (PMC, and cerebellum varies systematically with the direction of reaching movements. These neurons exhibit preferred direction tuning, where the level of neural activity is highest when movements are made in the preferred direction (PD, and gets progressively lower as movements are made at increasing degrees of offset from the PD. Using a functional magnetic resonance imaging adaptation (fMRI-A paradigm, we show that PD coding does exist in regions of the human motor system that are homologous to those observed in non-human primates. Consistent with predictions of the PD model, we show adaptation (i.e., a lower level of the blood oxygen level dependent (BOLD time-course signal in M1, PMC, SMA, and cerebellum when consecutive wrist movements were made in the same direction (0° offset relative to movements offset by 90° or 180°. The BOLD signal in dorsolateral prefrontal cortex adapted equally in all movement offset conditions, mitigating against the possibility that the present results are the consequence of differential task complexity or attention to action in each movement offset condition.

  18. Three-dimensional reconstruction and neural map of the serotonergic brain of Asplanchna brightwellii (Rotifera, Monogononta).

    Science.gov (United States)

    Hochberg, Rick

    2009-04-01

    The basic organization of the rotifer brain has been known for nearly a century; yet, fine details on its structure and organization remain limited despite the importance of rotifers in studies of evolution and population biology. To gain insight into the structure of the rotifer brain, and provide a foundation for future neurophysiologic and neurophylogenetic research, the brain of Asplanchna brightwellii was studied with immunohistochemistry, confocal laser scanning microscopy, and computer modeling. A three-dimensional map of serotonergic connections reveals a complex network of approximately 28 mostly unipolar, cerebral perikarya and associated neurites. Cells and their projections display symmetry in quantity, size, connections, and pathways between cerebral hemispheres within and among individuals. Most immunopositive cells are distributed close to the brain midline. Three pairs of neurites form decussations at the brain midline and may innervate sensory receptors in the corona. A single neuronal pathway appears to connect both the lateral horns and dorsolateral apical receptors, suggesting that convergence of synaptic connections may be common in the afferent sensory systems of rotifers. Results show that the neural map of A. brightwellii is much more intricate than that of other monogonont rotifers; nevertheless, the consistency in neural circuits provides opportunities to identify homologous neurons, distinguish functional regions based on neurotransmitter phenotype, and explore new avenues of neurophylogeny in Rotifera.

  19. Neural mechanisms of brain plasticity with complex cognitive training in healthy seniors.

    Science.gov (United States)

    Chapman, Sandra B; Aslan, Sina; Spence, Jeffrey S; Hart, John J; Bartz, Elizabeth K; Didehbani, Nyaz; Keebler, Molly W; Gardner, Claire M; Strain, Jeremy F; DeFina, Laura F; Lu, Hanzhang

    2015-02-01

    Complex mental activity induces improvements in cognition, brain function, and structure in animals and young adults. It is not clear to what extent the aging brain is capable of such plasticity. This study expands previous evidence of generalized cognitive gains after mental training in healthy seniors. Using 3 MRI-based measurements, that is, arterial spin labeling MRI, functional connectivity, and diffusion tensor imaging, we examined brain changes across 3 time points pre, mid, and post training (12 weeks) in a randomized sample (n = 37) who received cognitive training versus a control group. We found significant training-related brain state changes at rest; specifically, 1) increases in global and regional cerebral blood flow (CBF), particularly in the default mode network and the central executive network, 2) greater connectivity in these same networks, and 3) increased white matter integrity in the left uncinate demonstrated by an increase in fractional anisotropy. Improvements in cognition were identified along with significant CBF correlates of the cognitive gains. We propose that cognitive training enhances resting-state neural activity and connectivity, increasing the blood supply to these regions via neurovascular coupling. These convergent results provide preliminary evidence that neural plasticity can be harnessed to mitigate brain losses with cognitive training in seniors. © The Author 2013. Published by Oxford University Press.

  20. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.

    Directory of Open Access Journals (Sweden)

    Eric A Pohlmeyer

    Full Text Available Brain-machine interface (BMI systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings. These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.

  1. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.

    Science.gov (United States)

    Pohlmeyer, Eric A; Mahmoudi, Babak; Geng, Shijia; Prins, Noeline W; Sanchez, Justin C

    2014-01-01

    Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled.

  2. Radial Basis Neural Networks Based Fault Detection and Isolation Scheme for Pneumatic Actuator

    OpenAIRE

    Prabakaran, K.; S, Kaushik; R, Mouleeshuwarapprabu

    2014-01-01

    Fault diagnosis is an ongoing significant research field due to the constantly increasing need for maintainability, reliability and safety of industrial plants. The pneumatic actuators are installed in harsh environment: high temperature, pressure, aggressive media and vibration, etc. This influenced the pneumatic actuator predicted life time. The failures in pneumatic actuator cause forces the installation shut down and may also determine the final quality of the product. A Radial Basis Neur...

  3. VEGF-mediated angiogenesis stimulates neural stem cell proliferation and differentiation in the premature brain

    Energy Technology Data Exchange (ETDEWEB)

    Sun, Jinqiao, E-mail: jinqiao1977@163.com [Institute of Pediatrics, Children' s Hospital of Fudan University (China); Sha, Bin [Department of Neonatology, Children' s Hospital of Fudan University, 399 Wanyuan Road, Shanghai 201102 (China); Zhou, Wenhao, E-mail: zhou_wenhao@yahoo.com.cn [Department of Neonatology, Children' s Hospital of Fudan University, 399 Wanyuan Road, Shanghai 201102 (China); Yang, Yi [Institute of Pediatrics, Children' s Hospital of Fudan University (China)

    2010-03-26

    This study investigated the effects of angiogenesis on the proliferation and differentiation of neural stem cells in the premature brain. We observed the changes in neurogenesis that followed the stimulation and inhibition of angiogenesis by altering vascular endothelial growth factor (VEGF) expression in a 3-day-old rat model. VEGF expression was overexpressed by adenovirus transfection and down-regulated by siRNA interference. Using immunofluorescence assays, Western blot analysis, and real-time PCR methods, we observed angiogenesis and the proliferation and differentiation of neural stem cells. Immunofluorescence assays showed that the number of vWF-positive areas peaked at day 7, and they were highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at every time point. The number of neural stem cells, neurons, astrocytes, and oligodendrocytes in the subventricular zone gradually increased over time in the VEGF up-regulation group. Among the three groups, the number of these cells was highest in the VEGF up-regulation group and lowest in the VEGF down-regulation group at the same time point. Western blot analysis and real-time PCR confirmed these results. These data suggest that angiogenesis may stimulate the proliferation of neural stem cells and differentiation into neurons, astrocytes, and oligodendrocytes in the premature brain.

  4. Induced Pluripotent Stem Cell-Derived Neural Cells Survive and Mature in the Nonhuman Primate Brain

    Directory of Open Access Journals (Sweden)

    Marina E. Emborg

    2013-03-01

    Full Text Available The generation of induced pluripotent stem cells (iPSCs opens up the possibility for personalized cell therapy. Here, we show that transplanted autologous rhesus monkey iPSC-derived neural progenitors survive for up to 6 months and differentiate into neurons, astrocytes, and myelinating oligodendrocytes in the brains of MPTP-induced hemiparkinsonian rhesus monkeys with a minimal presence of inflammatory cells and reactive glia. This finding represents a significant step toward personalized regenerative therapies.

  5. All-diamond functional surface micro-electrode arrays for brain-slice neural analysis

    OpenAIRE

    Vahidpour, Farnoosh; Curley, Lowry; Biró, István; McDonald, Matthew; Croux, Dieter; POBEDINSKAS, Paulius; Haenen, Ken; Giugliano, Michele; Zivcova, Zuzana Vlckova; Kavan, Ladislav; Nesladek, Milos

    2017-01-01

    Abstract: Diamond-based microelectrode arrays were fabricated by using nanocrystalline diamond as an insulating layer and conductive boron-doped in order to used them for analysis of brain cortical slices. MEA surface is solely composed of diamond, exposed to the cells. The impedance measurements showed negligible cross-talk between neighbouring diamond microelectrodes. Local field potentials related to neural signals were then successfully recorded from pharmacologically disinhibited rat cor...

  6. Implications of the Dependence of Neuronal Activity on Neural Network States for the Design of Brain-Machine Interfaces.

    Science.gov (United States)

    Panzeri, Stefano; Safaai, Houman; De Feo, Vito; Vato, Alessandro

    2016-01-01

    Brain-machine interfaces (BMIs) can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state) that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brain. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  7. Implications of the dependence of neuronal activity on neural network states for the design of brain-machine interfaces

    Directory of Open Access Journals (Sweden)

    Stefano ePanzeri

    2016-04-01

    Full Text Available Brain-machine interfaces (BMIs can improve the quality of life of patients with sensory and motor disabilities by both decoding motor intentions expressed by neural activity, and by encoding artificially sensed information into patterns of neural activity elicited by causal interventions on the neural tissue. Yet, current BMIs can exchange relatively small amounts of information with the brain. This problem has proved difficult to overcome by simply increasing the number of recording or stimulating electrodes, because trial-to-trial variability of neural activity partly arises from intrinsic factors (collectively known as the network state that include ongoing spontaneous activity and neuromodulation, and so is shared among neurons. Here we review recent progress in characterizing the state dependence of neural responses, and in particular of how neural responses depend on endogenous slow fluctuations of network excitability. We then elaborate on how this knowledge may be used to increase the amount of information that BMIs exchange with brains. Knowledge of network state can be used to fine-tune the stimulation pattern that should reliably elicit a target neural response used to encode information in the brain, and to discount part of the trial-by-trial variability of neural responses, so that they can be decoded more accurately.

  8. Flexible deep brain neural probes based on a parylene tube structure

    Science.gov (United States)

    Zhao, Zhiguo; Kim, Eric; Luo, Hao; Zhang, Jinsheng; Xu, Yong

    2018-01-01

    Most microfabricated neural probes have limited shank length, which prevents them from reaching many deep brain structures. This paper reports deep brain neural probes with ultra-long penetrating shanks based on a simple but novel parylene tube structure. The mechanical strength of the parylene tube shank is temporarily enhanced during implantation by inserting a metal wire. The metal wire can be removed after implantation, making the implanted probe very flexible and thus minimizing the stress caused by micromotions of brain tissues. Optogenetic stimulation and chemical delivery capabilities can be potentially integrated by taking advantage of the tube structure. Single-shank prototypes with a shank length of 18.2 mm have been developed. The microfabrication process comprises of deep reactive ion etching (DRIE) of silicon, parylene conformal coating/refilling, and XeF2 isotropic silicon etching. In addition to bench-top insertion characterization, the functionality of developed probes has been preliminarily demonstrated by implanting into the amygdala of a rat and recording neural signals.

  9. Whole-brain 3D mapping of human neural transplant innervation.

    Science.gov (United States)

    Doerr, Jonas; Schwarz, Martin Karl; Wiedermann, Dirk; Leinhaas, Anke; Jakobs, Alina; Schloen, Florian; Schwarz, Inna; Diedenhofen, Michael; Braun, Nils Christian; Koch, Philipp; Peterson, Daniel A; Kubitscheck, Ulrich; Hoehn, Mathias; Brüstle, Oliver

    2017-01-19

    While transplantation represents a key tool for assessing in vivo functionality of neural stem cells and their suitability for neural repair, little is known about the integration of grafted neurons into the host brain circuitry. Rabies virus-based retrograde tracing has developed into a powerful approach for visualizing synaptically connected neurons. Here, we combine this technique with light sheet fluorescence microscopy (LSFM) to visualize transplanted cells and connected host neurons in whole-mouse brain preparations. Combined with co-registration of high-precision three-dimensional magnetic resonance imaging (3D MRI) reference data sets, this approach enables precise anatomical allocation of the host input neurons. Our data show that the same neural donor cell population grafted into different brain regions receives highly orthotopic input. These findings indicate that transplant connectivity is largely dictated by the circuitry of the target region and depict rabies-based transsynaptic tracing and LSFM as efficient tools for comprehensive assessment of host-donor cell innervation.

  10. A neural basis for interindividual differences in the McGurk effect, a multisensory speech illusion.

    Science.gov (United States)

    Nath, Audrey R; Beauchamp, Michael S

    2012-01-02

    The McGurk effect is a compelling illusion in which humans perceive mismatched audiovisual speech as a completely different syllable. However, some normal individuals do not experience the illusion, reporting that the stimulus sounds the same with or without visual input. Converging evidence suggests that the left superior temporal sulcus (STS) is critical for audiovisual integration during speech perception. We used blood-oxygen level dependent functional magnetic resonance imaging (BOLD fMRI) to measure brain activity as McGurk perceivers and non-perceivers were presented with congruent audiovisual syllables, McGurk audiovisual syllables, and non-McGurk incongruent syllables. The inferior frontal gyrus showed an effect of stimulus condition (greater responses for incongruent stimuli) but not susceptibility group, while the left auditory cortex showed an effect of susceptibility group (greater response in susceptible individuals) but not stimulus condition. Only one brain region, the left STS, showed a significant effect of both susceptibility and stimulus condition. The amplitude of the response in the left STS was significantly correlated with the likelihood of perceiving the McGurk effect: a weak STS response meant that a subject was less likely to perceive the McGurk effect, while a strong response meant that a subject was more likely to perceive it. These results suggest that the left STS is a key locus for interindividual differences in speech perception. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. A specific brain structural basis for individual differences in reality monitoring.

    Science.gov (United States)

    Buda, Marie; Fornito, Alex; Bergström, Zara M; Simons, Jon S

    2011-10-05

    Much recent interest has centered on understanding the relationship between brain structure variability and individual differences in cognition, but there has been little progress in identifying specific neuroanatomical bases of such individual differences. One cognitive ability that exhibits considerable variability in the healthy population is reality monitoring; the cognitive processes used to introspectively judge whether a memory came from an internal or external source (e.g., whether an event was imagined or actually occurred). Neuroimaging research has implicated the medial anterior prefrontal cortex (PFC) in reality monitoring, and here we sought to determine whether morphological variability in a specific anteromedial PFC brain structure, the paracingulate sulcus (PCS), might underlie performance. Fifty-three healthy volunteers were selected on the basis of MRI scans and classified into four groups according to presence or absence of the PCS in their left or right hemisphere. The group with absence of the PCS in both hemispheres showed significantly reduced reality monitoring performance and ability to introspect metacognitively about their performance when compared with other participants. Consistent with the prediction that sulcal absence might mean greater volume in the surrounding frontal gyri, voxel-based morphometry revealed a significant negative correlation between anterior PFC gray matter and reality monitoring performance. The findings provide evidence that individual differences in introspective abilities like reality monitoring may be associated with specific structural variability in the PFC.

  12. A stranger in my brain: Neural representation for unfamiliar persons using fMRI repetition suppression.

    Science.gov (United States)

    Heleven, Elien; Boukhlal, Siham; Van Overwalle, Frank

    2017-08-02

    Prior neuroimaging research demonstrated that the ventromedial prefrontal cortex (vmPFC) houses neural representations for traits and familiar persons that possess these traits. But do such neural representations also exist for people we do not know? We hypothesized that knowledge about unknown persons is encoded in "generic" mentalizing representations as opposed to "specific" representations for well-known individuals. Neural representations for unfamiliar persons were investigated by fMRI repetition suppression, which is a rapid suppression of fMRI responses upon repeated presentation of the same stimulus signaling the neural representation of this stimulus. Participants had to infer an unfamiliar person's traits from brief behavioral descriptions. In each trial, a critical sentence was preceded by another sentence in which we manipulated whether or not the person or trait was repeated. The results revealed suppression for unfamiliar others in the vmPFC extending earlier research, as well as in novel areas including the inferior parietal lobule and dorsal posterior cingulate. We also found trait suppression in the vmPFC. This indicates that the vmPFC houses neural populations of "generic" representations of unknown persons and their traits. We speculate that the other brain areas showing suppression might reflect embodied representations at a somatomotor level.

  13. The Neural Basis of Speech Perception through Lipreading and Manual Cues: Evidence from Deaf Native Users of Cued Speech

    Science.gov (United States)

    Aparicio, Mario; Peigneux, Philippe; Charlier, Brigitte; Balériaux, Danielle; Kavec, Martin; Leybaert, Jacqueline

    2017-01-01

    We present here the first neuroimaging data for perception of Cued Speech (CS) by deaf adults who are native users of CS. CS is a visual mode of communicating a spoken language through a set of manual cues which accompany lipreading and disambiguate it. With CS, sublexical units of the oral language are conveyed clearly and completely through the visual modality without requiring hearing. The comparison of neural processing of CS in deaf individuals with processing of audiovisual (AV) speech in normally hearing individuals represents a unique opportunity to explore the similarities and differences in neural processing of an oral language delivered in a visuo-manual vs. an AV modality. The study included deaf adult participants who were early CS users and native hearing users of French who process speech audiovisually. Words were presented in an event-related fMRI design. Three conditions were presented to each group of participants. The deaf participants saw CS words (manual + lipread), words presented as manual cues alone, and words presented to be lipread without manual cues. The hearing group saw AV spoken words, audio-alone and lipread-alone. Three findings are highlighted. First, the middle and superior temporal gyrus (excluding Heschl’s gyrus) and left inferior frontal gyrus pars triangularis constituted a common, amodal neural basis for AV and CS perception. Second, integration was inferred in posterior parts of superior temporal sulcus for audio and lipread information in AV speech, but in the occipito-temporal junction, including MT/V5, for the manual cues and lipreading in CS. Third, the perception of manual cues showed a much greater overlap with the regions activated by CS (manual + lipreading) than lipreading alone did. This supports the notion that manual cues play a larger role than lipreading for CS processing. The present study contributes to a better understanding of the role of manual cues as support of visual speech perception in the framework

  14. Neural Basis of Two Kinds of Social Influence: Obedience and Conformity

    Directory of Open Access Journals (Sweden)

    Ying eXie

    2016-02-01

    Full Text Available Event-related potentials (ERPs were used in this study to explore the neural mechanism of obedience and conformity on the model of online book purchasing. Participants were asked to decide as quickly as possible whether to buy a book based on limited information including its title, keywords and number of positive and negative reviews. Obedience was induced by forcing participants to buy books which received mostly negative reviews. In contrast, conformity was aroused by majority influence (caused by positive and negative comments. P3 and N2, two kinds of ERP components related to social cognitive process, were measured and recorded with electroencephalogram (EEG test. The results show that compared with conformity decisions, obedience decisions induced greater cognitive conflicts. In ERP measurements, greater amplitudes of N2 component were observed in the context of obedience. However, consistency level did not make a difference on P3 peak latency for both conformity and obedience. This shows that classification process is implicit in both conformity and obedience decision-making. In addition, for both conformity and obedience decisions, augmented P3 was observed when the reviews consistency (either negative or positive was higher.

  15. The cognitive and neural basis of option generation and subsequent choice.

    Science.gov (United States)

    Kaiser, Stefan; Simon, Joe J; Kalis, Annemarie; Schweizer, Sophie; Tobler, Philippe N; Mojzisch, Andreas

    2013-12-01

    Decision-making research has thoroughly investigated how people choose from a set of externally provided options. However, in ill-structured real-world environments, possible options for action are not defined by the situation but have to be generated by the agent. Here, we apply behavioral analysis (Study 1) and functional magnetic resonance imaging (Study 2) to investigate option generation and subsequent choice. For this purpose, we employ a new experimental task that requires participants to generate options for simple real-world scenarios and to subsequently decide among the generated options. Correlational analysis with a cognitive test battery suggests that retrieval of options from long-term memory is a relevant process during option generation. The results of the fMRI study demonstrate that option generation in simple real-world scenarios recruits the anterior prefrontal cortex. Furthermore, we show that choice behavior and its neural correlates differ between self-generated and externally provided options. Specifically, choice between self-generated options is associated with stronger recruitment of the dorsal anterior cingulate cortex. This impact of option generation on subsequent choice underlines the need for an expanded model of decision making to accommodate choice between self-generated options.

  16. Neural Basis of Two Kinds of Social Influence: Obedience and Conformity.

    Science.gov (United States)

    Xie, Ying; Chen, Mingliang; Lai, Hongxia; Zhang, Wuke; Zhao, Zhen; Anwar, Ch Mahmood

    2016-01-01

    Event-related potentials (ERPs) were used in this study to explore the neural mechanism of obedience and conformity on the model of online book purchasing. Participants were asked to decide as quickly as possible whether to buy a book based on limited information including its title, keywords and number of positive and negative reviews. Obedience was induced by forcing participants to buy books which received mostly negative reviews. In contrast, conformity was aroused by majority influence (caused by positive and negative comments). P3 and N2, two kinds of ERP components related to social cognitive process, were measured and recorded with electroencephalogram (EEG) test. The results show that compared with conformity decisions, obedience decisions induced greater cognitive conflicts. In ERP measurements, greater amplitudes of N2 component were observed in the context of obedience. However, consistency level did not make a difference on P3 peak latency for both conformity and obedience. This shows that classification process is implicit in both conformity and obedience decision-making. In addition, for both conformity and obedience decisions, augmented P3 was observed when the reviews consistency (either negative or positive) was higher.

  17. Targeted activation of primitive neural stem cells in the mouse brain.

    Science.gov (United States)

    Reeve, Rachel L; Yammine, Samantha Z; DeVeale, Brian; van der Kooy, Derek

    2016-06-01

    Primitive neural stem cells (pNSCs) are the earliest NSCs to appear in the developing forebrain. They persist into the adult forebrain where they can generate all cells in the neural lineage and therefore hold great potential for brain regeneration. Thus, pNSCs are an ideal population to target to promote endogenous NSC activation. pNSCs can be isolated from the periventricular region as leukaemia inhibitory factor-responsive cells, and comprise a rare population in the adult mouse brain. We hypothesized that the pup periventricular region gives rise to more clonal pNSC-derived neurospheres but that pup-derived pNSCs are otherwise comparable to adult-derived pNSCs, and can be used to identify selective markers and activators of endogenous pNSCs. We tested the self-renewal ability, differentiation capacity and gene expression profile of pup-derived pNSCs and found them each to be comparable to adult-derived pNSCs, including being GFAP(-) , nestin(mid) , Oct4(+) . Next, we used pup pNSCs to test pharmacological compounds to activate pNSCs to promote endogenous brain repair. We hypothesized that pNSCs could be activated by targeting the cell surface proteins C-Kit and ErbB2, which were enriched in pNSCs relative to definitive NSCs (dNSCs) in an in vitro screen. C-Kit and ErbB2 signalling inhibition had distinct effects on pNSCs and dNSCs in vitro, and when infused directly into the adult brain in vivo. Targeted activation of pNSCs with C-Kit and ErbB2 modulation is a valuable strategy to activate the earliest cell in the neural lineage to contribute to endogenous brain regeneration. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  18. A Computationally Inexpensive Optimal Guidance via Radial-Basis-Function Neural Network for Autonomous Soft Landing on Asteroids.

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    Full Text Available Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP. Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm.

  19. A Computationally Inexpensive Optimal Guidance via Radial-Basis-Function Neural Network for Autonomous Soft Landing on Asteroids.

    Science.gov (United States)

    Zhang, Peng; Liu, Keping; Zhao, Bo; Li, Yuanchun

    2015-01-01

    Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN) is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP). Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm.

  20. A repair algorithm for radial basis function neural network and its application to chemical oxygen demand modeling.

    Science.gov (United States)

    Qiao, Jun-Fei; Han, Hong-Gui

    2010-02-01

    This paper presents a repair algorithm for the design of a Radial Basis Function (RBF) neural network. The proposed repair RBF (RRBF) algorithm starts from a single prototype randomly initialized in the feature space. The algorithm has two main phases: an architecture learning phase and a parameter adjustment phase. The architecture learning phase uses a repair strategy based on a sensitivity analysis (SA) of the network's output to judge when and where hidden nodes should be added to the network. New nodes are added to repair the architecture when the prototype does not meet the requirements. The parameter adjustment phase uses an adjustment strategy where the capabilities of the network are improved by modifying all the weights. The algorithm is applied to two application areas: approximating a non-linear function, and modeling the key parameter, chemical oxygen demand (COD) used in the waste water treatment process. The results of simulation show that the algorithm provides an efficient solution to both problems.

  1. Simulation and prediction of the thuringiensin abiotic degradation processes in aqueous solution by a radius basis function neural network model.

    Science.gov (United States)

    Zhou, Jingwen; Xu, Zhenghong; Chen, Shouwen

    2013-04-01

    The thuringiensin abiotic degradation processes in aqueous solution under different conditions, with a pH range of 5.0-9.0 and a temperature range of 10-40°C, were systematically investigated by an exponential decay model and a radius basis function (RBF) neural network model, respectively. The half-lives of thuringiensin calculated by the exponential decay model ranged from 2.72 d to 16.19 d under the different conditions mentioned above. Furthermore, an RBF model with accuracy of 0.1 and SPREAD value 5 was employed to model the degradation processes. The results showed that the model could simulate and predict the degradation processes well. Both the half-lives and the prediction data showed that thuringiensin was an easily degradable antibiotic, which could be an important factor in the evaluation of its safety. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. R-Peak Detection using Daubechies Wavelet and ECG Signal Classification using Radial Basis Function Neural Network

    Science.gov (United States)

    Rai, H. M.; Trivedi, A.; Chatterjee, K.; Shukla, S.

    2014-01-01

    This paper employed the Daubechies wavelet transform (WT) for R-peak detection and radial basis function neural network (RBFNN) to classify the electrocardiogram (ECG) signals. Five types of ECG beats: normal beat, paced beat, left bundle branch block (LBBB) beat, right bundle branch block (RBBB) beat and premature ventricular contraction (PVC) were classified. 500 QRS complexes were arbitrarily extracted from 26 records in Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, which are available on Physionet website. Each and every QRS complex was represented by 21 points from p1 to p21 and these QRS complexes of each record were categorized according to types of beats. The system performance was computed using four types of parameter evaluation metrics: sensitivity, positive predictivity, specificity and classification error rate. The experimental result shows that the average values of sensitivity, positive predictivity, specificity and classification error rate are 99.8%, 99.60%, 99.90% and 0.12%, respectively with RBFNN classifier. The overall accuracy achieved for back propagation neural network (BPNN), multilayered perceptron (MLP), support vector machine (SVM) and RBFNN classifiers are 97.2%, 98.8%, 99% and 99.6%, respectively. The accuracy levels and processing time of RBFNN is higher than or comparable with BPNN, MLP and SVM classifiers.

  3. A Fault Diagnosis Method for Oil Well Pump Using Radial Basis Function Neural Network Combined with Modified Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Deliang Yu

    2017-01-01

    Full Text Available This paper presents a new method to diagnose oil well pump faults using a modified radial basis function neural network. With the development of submersible linear motor technology, rodless pumping units have been widely used in oil exploration. However, the ground indicator diagram method cannot be used to diagnose the working conditions of rodless pumping units because it is based on the load change of the polished rod suspension point and its displacement. To solve this problem, this paper presents a new method that is applicable to rodless oil pumps. The advantage of this new method is its use of a simple feature extraction method and advanced genetic algorithm to optimize the threshold and weight of the RBF neural network. In this paper, we extract the characteristic value from the operation parameters of the submersible linear motor and oil wellhead as the input vector of the fault diagnosis model. Through experimental analysis, the proposed method is proven to have good convergence performance, high accuracy, and high reliability.

  4. Optogenetics in the teaching laboratory: using channelrhodopsin-2 to study the neural basis of behavior and synaptic physiology in Drosophila.

    Science.gov (United States)

    Pulver, Stefan R; Hornstein, Nicholas J; Land, Bruce L; Johnson, Bruce R

    2011-03-01

    Here we incorporate recent advances in Drosophila neurogenetics and "optogenetics" into neuroscience laboratory exercises. We used the light-activated ion channel channelrhodopsin-2 (ChR2) and tissue-specific genetic expression techniques to study the neural basis of behavior in Drosophila larvae. We designed and implemented exercises using inexpensive, easy-to-use systems for delivering blue light pulses with fine temporal control. Students first examined the behavioral effects of activating glutamatergic neurons in Drosophila larvae and then recorded excitatory junctional potentials (EJPs) mediated by ChR2 activation at the larval neuromuscular junction (NMJ). Comparison of electrically and light-evoked EJPs demonstrates that the amplitudes and time courses of light-evoked EJPs are not significantly different from those generated by electrical nerve stimulation. These exercises introduce students to new genetic technology for remotely manipulating neural activity, and they simplify the process of recording EJPs at the Drosophila larval NMJ. Relatively little research work has been done using ChR2 in Drosophila, so students have opportunities to test novel hypotheses and make tangible contributions to the scientific record. Qualitative and quantitative assessment of student experiences suggest that these exercises help convey principles of synaptic transmission while also promoting integrative and inquiry-based studies of genetics, cellular physiology, and animal behavior.

  5. The neural basis of novelty and appropriateness in processing of creative chunk decomposition.

    Science.gov (United States)

    Huang, Furong; Fan, Jin; Luo, Jing

    2015-06-01

    Novelty and appropriateness have been recognized as the fundamental features of creative thinking. However, the brain mechanisms underlying these features remain largely unknown. In this study, we used event-related functional magnetic resonance imaging (fMRI) to dissociate these mechanisms in a revised creative chunk decomposition task in which participants were required to perform different types of chunk decomposition that systematically varied in novelty and appropriateness. We found that novelty processing involved functional areas for procedural memory (caudate), mental rewarding (substantia nigra, SN), and visual-spatial processing, whereas appropriateness processing was mediated by areas for declarative memory (hippocampus), emotional arousal (amygdala), and orthography recognition. These results indicate that non-declarative and declarative memory systems may jointly contribute to the two fundamental features of creative thinking. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. The neural basis of social risky decision making in females with major depressive disorder.

    Science.gov (United States)

    Shao, Robin; Zhang, Hui-jun; Lee, Tatia M C

    2015-01-01

    Recent evidence indicates that Major Depressive Disorder (MDD) may be associated with reduced tendency of committing noncompliant actions during social decision-making even when the risk of being punished is low. The neural underpinnings of this behavioral pattern are unknown, although it likely relates to compromised functioning of the lateral prefrontal-striatal/limbic networks implicated in executive control, emotion regulation and risk/value-based instrumental behaviors. We employed a modified trust game (TG) that provided explicit information on the risk levels of cheating behaviors being detected and punished. Behavioral and neuro-image data were acquired and analyzed from 14 first-episode female MDD patients and 15 age- and gender-matched controls performing the role of trustee in the TG. Relative to controls, MDD patients exhibited less behavioral switching to making cheating choices under low risk, and reduced activity in the dorsal putamen, anterior insula and dorsolateral prefrontal cortex (DLPFC) during making low-risk cheating versus benevolent choices, with limited evidence indicating abnormal bilateral inferior frontal gyrus activities of patients when making high-risk cheating versus benevolent choices. Patients' left dorsal putamen/anterior insular signals correlated positively with their frequency of low-risk cheating. MDD patients' symptom severity correlated positively with their signals in the lateral prefrontal networks during decision-making. A psycho-physiological interaction analysis provided tentative evidence for the recruitment of IFG-striatal/limbic circuitry among the control participants, but greater frontopolar-striatal/limbic connectivity among the MDD patients, during low-risk decision-making. We propose that making risky social decisions based on the balancing of self-gain and other's welfare relies on the functioning of the integrated lateral prefrontal-striatal/limbic networks, which are less efficient and dysregulated among MDD

  7. Advantages of comparative studies in songbirds to understand the neural basis of sensorimotor integration.

    Science.gov (United States)

    Murphy, Karagh; James, Logan S; Sakata, Jon T; Prather, Jonathan F

    2017-08-01

    Sensorimotor integration is the process through which the nervous system creates a link between motor commands and associated sensory feedback. This process allows for the acquisition and refinement of many behaviors, including learned communication behaviors such as speech and birdsong. Consequently, it is important to understand fundamental mechanisms of sensorimotor integration, and comparative analyses of this process can provide vital insight. Songbirds offer a powerful comparative model system to study how the nervous system links motor and sensory information for learning and control. This is because the acquisition, maintenance, and control of birdsong critically depend on sensory feedback. Furthermore, there is an incredible diversity of song organizations across songbird species, ranging from songs with simple, stereotyped sequences to songs with complex sequencing of vocal gestures, as well as a wide diversity of song repertoire sizes. Despite this diversity, the neural circuitry for song learning, control, and maintenance remains highly similar across species. Here, we highlight the utility of songbirds for the analysis of sensorimotor integration and the insights about mechanisms of sensorimotor integration gained by comparing different songbird species. Key conclusions from this comparative analysis are that variation in song sequence complexity seems to covary with the strength of feedback signals in sensorimotor circuits and that sensorimotor circuits contain distinct representations of elements in the vocal repertoire, possibly enabling evolutionary variation in repertoire sizes. We conclude our review by highlighting important areas of research that could benefit from increased comparative focus, with particular emphasis on the integration of new technologies. Copyright © 2017 the American Physiological Society.

  8. Characterizing Deep Brain Stimulation effects in computationally efficient neural network models.

    Science.gov (United States)

    Latteri, Alberta; Arena, Paolo; Mazzone, Paolo

    2011-04-15

    Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation (DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures, responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces the surgical interventions implemented to contrast the activity of specific brain nuclei, called Basal Ganglia (BG). This clinical protocol gave the possibility to analyse and inspect signals measured from the electrodes implanted into the deep brain regions. The analysis of these signals led to the possibility to study the PD as a specific case of dynamical synchronization in biological neural networks, with the advantage to apply the theoretical analysis developed in such scientific field to find efficient treatments to face with this important disease. Experimental results in fact show that the PD neurological diseases are characterized by a pathological signal synchronization in BG. Parkinsonian tremor, for example, is ascribed to be caused by neuron populations of the Thalamic and Striatal structures that undergo an abnormal synchronization. On the contrary, in normal conditions, the activity of the same neuron populations do not appear to be correlated and synchronized. To study in details the effect of the stimulation signal on a pathological neural medium, efficient models of these neural structures were built, which are able to show, without any external input, the intrinsic properties of a pathological neural tissue, mimicking the BG synchronized dynamics.We start considering a model already introduced in the literature to investigate the effects of electrical stimulation on pathologically synchronized clusters of neurons. This model used Morris Lecar type neurons. This neuron model, although having a high level of biological plausibility, requires a large computational effort

  9. Auto-context Convolutional Neural Network (Auto-Net) for Brain Extraction in Magnetic Resonance Imaging.

    Science.gov (United States)

    Salehi, Seyed Sadegh Mohseni; Erdogmus, Deniz; Gholipour, Ali

    2017-06-28

    Brain extraction or whole brain segmentation is an important first step in many of the neuroimage analysis pipelines. The accuracy and robustness of brain extraction, therefore, is crucial for the accuracy of the entire brain analysis process. State-of-the-art brain extraction techniques rely heavily on the accuracy of alignment or registration between brain atlases and query brain anatomy, and/or make assumptions about the image geometry; therefore have limited success when these assumptions do not hold or image registration fails. With the aim of designing an accurate, learning-based, geometry-independent and registration-free brain extraction tool in this study, we present a technique based on an auto-context convolutional neural network (CNN), in which intrinsic local and global image features are learned through 2D patches of different window sizes. We consider two different architectures: 1) a voxelwise approach based on three parallel 2D convolutional pathways for three different directions (axial, coronal, and sagittal) that implicitly learn 3D image information without the need for computationally expensive 3D convolutions, and 2) a fully convolutional network based on the U-net architecture. Posterior probability maps generated by the networks are used iteratively as context information along with the original image patches to learn the local shape and connectedness of the brain to extract it from non-brain tissue. The brain extraction results we have obtained from our CNNs are superior to the recently reported results in the literature on two publicly available benchmark datasets, namely LPBA40 and OASIS, in which we obtained Dice overlap coefficients of 97.73% and 97.62%, respectively. Significant improvement was achieved via our auto-context algorithm. Furthermore, we evaluated the performance of our algorithm in the challenging problem of extracting arbitrarily-oriented fetal brains in reconstructed fetal brain magnetic resonance imaging (MRI

  10. The impoverished brain: disparities in maternal education affect the neural response to sound.

    Science.gov (United States)

    Skoe, Erika; Krizman, Jennifer; Kraus, Nina

    2013-10-30

    Despite the prevalence of poverty worldwide, little is known about how early socioeconomic adversity affects auditory brain function. Socioeconomically disadvantaged children are underexposed to linguistically and cognitively stimulating environments and overexposed to environmental toxins, including noise pollution. This kind of sensory impoverishment, we theorize, has extensive repercussions on how the brain processes sound. To characterize how this impoverishment affects auditory brain function, we compared two groups of normal-hearing human adolescents who attended the same schools and who were matched in age, sex, and ethnicity, but differed in their maternal education level, a correlate of socioeconomic status (SES). In addition to lower literacy levels and cognitive abilities, adolescents from lower maternal education backgrounds were found to have noisier neural activity than their classmates, as reflected by greater activity in the absence of auditory stimulation. Additionally, in the lower maternal education group, the neural response to speech was more erratic over repeated stimulation, with lower fidelity to the input signal. These weaker, more variable, and noisier responses are suggestive of an inefficient auditory system. By studying SES within a neuroscientific framework, we have the potential to expand our understanding of how experience molds the brain, in addition to informing intervention research aimed at closing the achievement gap between high-SES and low-SES children.

  11. Engraftment of enteric neural progenitor cells into the injured adult brain.

    Science.gov (United States)

    Belkind-Gerson, Jaime; Hotta, Ryo; Whalen, Michael; Nayyar, Naema; Nagy, Nandor; Cheng, Lily; Zuckerman, Aaron; Goldstein, Allan M; Dietrich, Jorg

    2016-01-25

    A major area of unmet need is the development of strategies to restore neuronal network systems and to recover brain function in patients with neurological disease. The use of cell-based therapies remains an attractive approach, but its application has been challenging due to the lack of suitable cell sources, ethical concerns, and immune-mediated tissue rejection. We propose an innovative approach that utilizes gut-derived neural tissue for cell-based therapies following focal or diffuse central nervous system injury. Enteric neuronal stem and progenitor cells, able to differentiate into neuronal and glial lineages, were isolated from the postnatal enteric nervous system and propagated in vitro. Gut-derived neural progenitors, genetically engineered to express fluorescent proteins, were transplanted into the injured brain of adult mice. Using different models of brain injury in combination with either local or systemic cell delivery, we show that transplanted enteric neuronal progenitor cells survive, proliferate, and differentiate into neuronal and glial lineages in vivo. Moreover, transplanted cells migrate extensively along neuronal pathways and appear to modulate the local microenvironment to stimulate endogenous neurogenesis. Our findings suggest that enteric nervous system derived cells represent a potential source for tissue regeneration in the central nervous system. Further studies are needed to validate these findings and to explore whether autologous gut-derived cell transplantation into the injured brain can result in functional neurologic recovery.

  12. Neural progenitor cell engraftment corrects lysosomal storage throughout the MPS VII mouse brain.

    Science.gov (United States)

    Snyder, E Y; Taylor, R M; Wolfe, J H

    1995-03-23

    Many metabolic diseases affecting the central nervous system are refractory to treatment because the blood-brain barrier restricts entry of therapeutic molecules. It may be possible to deliver therapeutic gene products directly to the brain by transplantation of neural progenitor cells, which can integrate into the murine central nervous system in a cytoarchitecturally appropriate manner. We tested this approach in mucopolysaccharidosis VII (Sly disease), a lysosomal storage disorder of humans, dogs and mice caused by an inherited deficiency of beta-glucuronidase. Lysosomal accumulation of glycosaminoglycans occurs in the brain and other tissues, causing a fatal progressive degenerative disorder, including mental retardation. Treatments are designed to provide a source of normal enzyme for uptake by diseased cells. We report here that by transplanting beta-glucuronidase-expressing neural progenitors into the cerebral ventricles of newborn mice, donor cells engrafted throughout the neuraxis. At maturity, donor-derived cells were present as normal constituents of diverse brain regions. beta-Glucuronidase activity was expressed along the entire neuraxis, resulting in widespread correction of lysosomal storage in neurons and glia in affected mice.

  13. Neural, cognitive, and neuroimaging markers of the suicidal brain

    Directory of Open Access Journals (Sweden)

    Sobanski T

    2015-05-01

    Full Text Available Thomas Sobanski,1 Karl-Jürgen Bär,2 Gerd Wagner2 1Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, Thüringen-Kliniken "Georgius Agricola" GmbH, Saalfeld, Germany; 2Department of Psychiatry and Psychotherapy, Psychiatric Brain and Body Research Group Jena, Jena University Hospital, Jena, GermanyAbstract: Suicidal behavior (SB is characterized by the occurrence of suicide attempts with substantial intent to die. SB is a major health problem worldwide. In the great majority of cases, SB occurs in patients suffering from psychiatric disorders, mainly from affective disorders or schizophrenia. Despite this high association, there is growing evidence from genetic studies that SB might represent a psychiatric condition on its own. This review provides an overview of the most significant neurobiological and neurocognitive findings in SB. We provide evidence for specific dysfunctions within the serotonergic system, for distinct morphological abnormalities in the gray and white matter composition as well as for neurofunctional alterations in the fronto-striatal network. Additionally, the putative role of impulsivity and hopelessness as trait-like risk factors for SB is outlined. Both the personality traits are associated with altered prefrontal cortex function and deficits in cognitive and affective control similar to the findings in SB. Given the difficulties of clinical risk assessment, there is a need to identify specific markers that can predict SB more reliably. Some recent neurocognitive and functional/structural neuroimaging findings might be appropriate to use as SB indicators in the close future.Keywords: suicidal behavior, biological markers, serotonin, hopelessness, impulsivity, major depressive disorder, fMRI, PET, SPECT

  14. Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

    Science.gov (United States)

    D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  15. The Racer's Brain - How Domain Expertise is Reflected in the Neural Substrates of Driving.

    Science.gov (United States)

    Lappi, Otto

    2015-01-01

    A fundamental question in human brain plasticity is how sensory, motor, and cognitive functions adapt in the process of skill acquisition extended over a period of many years. Recently, there has emerged a growing interest in cognitive neuroscience on studying the functional and structural differences in the brains of elite athletes. Elite performance in sports, music, or the arts, allows us to observe sensorimotor and cognitive performance at the limits of human capability. In this mini-review, we look at driving expertise. The emerging brain imaging literature on the neural substrates of real and simulated driving is reviewed (for the first time), and used as the context for interpreting recent findings on the differences between racing drivers and non-athlete controls. Also the cognitive psychology and cognitive neuroscience of expertise are discussed.

  16. The neural basis of audiomotor entrainment: An ALE meta-analysis

    Directory of Open Access Journals (Sweden)

    Léa A. S. Chauvigné

    2014-09-01

    Full Text Available Synchronization of body movement to an acoustic rhythm is a major form of entrainment, such as occurs in dance. This is exemplified in experimental studies of finger tapping. Entrainment to a beat is contrasted with movement that is internally driven and is therefore self-paced. In order to examine brain areas important for entrainment to an acoustic beat, we meta-analyzed the functional neuroimaging literature on finger tapping (43 studies using activation likelihood estimation (ALE meta-analysis with a focus on the contrast between externally-paced and self-paced tapping. The results demonstrated a dissociation between two subcortical systems involved in timing, namely the cerebellum and the basal ganglia. Externally-paced tapping highlighted the importance of the spinocerebellum, most especially the vermis, which was not activated at all by self-paced tapping. In contrast, the basal ganglia, including the putamen and globus pallidus, were active during both types of tapping, but preferentially during self-paced tapping. These results suggest a central role for the spinocerebellum in audiomotor entrainment. We conclude with a theoretical discussion about the various forms of entrainment in humans and other animals.

  17. Adaptive prognosis of lithium-ion batteries based on the combination of particle filters and radial basis function neural networks

    Science.gov (United States)

    Sbarufatti, Claudio; Corbetta, Matteo; Giglio, Marco; Cadini, Francesco

    2017-03-01

    Lithium-Ion rechargeable batteries are widespread power sources with applications to consumer electronics, electrical vehicles, unmanned aerial and spatial vehicles, etc. The failure to supply the required power levels may lead to severe safety and economical consequences. Thus, in view of the implementation of adequate maintenance strategies, the development of diagnostic and prognostic tools for monitoring the state of health of the batteries and predicting their remaining useful life is becoming a crucial task. Here, we propose a method for predicting the end of discharge of Li-Ion batteries, which stems from the combination of particle filters with radial basis function neural networks. The major innovation lies in the fact that the radial basis function model is adaptively trained on-line, i.e., its parameters are identified in real time by the particle filter as new observations of the battery terminal voltage become available. By doing so, the prognostic algorithm achieves the flexibility needed to provide sound end-of-discharge time predictions as the charge-discharge cycles progress, even in presence of anomalous behaviors due to failures or unforeseen operating conditions. The method is demonstrated with reference to actual Li-Ion battery discharge data contained in the prognostics data repository of the NASA Ames Research Center database.

  18. 3D culture of murine neural stem cells on decellularized mouse brain sections.

    Science.gov (United States)

    De Waele, Jorrit; Reekmans, Kristien; Daans, Jasmijn; Goossens, Herman; Berneman, Zwi; Ponsaerts, Peter

    2015-02-01

    Transplantation of neural stem cells (NSC) in diseased or injured brain tissue is widely studied as a potential treatment for various neurological pathologies. However, effective cell replacement therapy relies on the intrinsic capacity of cellular grafts to overcome hypoxic and/or immunological barriers after transplantation. In this context, it is hypothesized that structural support for grafted NSC will be of utmost importance. With this study, we present a novel decellularization protocol for 1.5 mm thick mouse brain sections, resulting in the generation of acellular three-dimensional (3D) brain sections. Next, the obtained 3D brain sections were seeded with murine NSC expressing both the eGFP and luciferase reporter proteins (NSC-eGFP/Luc). Using real-time bioluminescence imaging, the survival and growth of seeded NSC-eGFP/Luc cells was longitudinally monitored for 1-7 weeks in culture, indicating the ability of the acellular brain sections to support sustained ex vivo growth of NSC. Next, the organization of a 3D maze-like cellular structure was examined using confocal microscopy. Moreover, under mitogenic stimuli (EGF and hFGF-2), most cells in this 3D culture retained their NSC phenotype. Concluding, we here present a novel protocol for decellularization of mouse brain sections, which subsequently support long-term 3D culture of undifferentiated NSC. Copyright © 2014 Elsevier Ltd. All rights reserved.

  19. The relation of ongoing brain activity, evoked neural responses, and cognition

    Directory of Open Access Journals (Sweden)

    Sepideh Sadaghiani

    2010-06-01

    Full Text Available Ongoing brain activity has been observed since the earliest neurophysiological recordings and is found over a wide range of temporal and spatial scales. It is characterized by remarkably large spontaneous modulations. Here, we review evidence for the functional role of these ongoing activity fluctuations and argue that they constitute an essential property of the neural architecture underlying cognition. The role of spontaneous activity fluctuations is probably best understood when considering both their spatiotemporal structure and their functional impact on cognition. We first briefly argue against a ‘segregationist’ view on ongoing activity, both in time and space, countering this view with an emphasis on integration within a hierarchical spatiotemporal organization of intrinsic activity. We then highlight the flexibility and context-sensitivity of intrinsic functional connectivity that suggest its involvement in functionally relevant information processing. This role in information processing is pursued by reviewing how ongoing brain activity interacts with afferent and efferent information exchange of the brain with its environment. We focus on the relationship between the variability of ongoing and evoked brain activity, and review recent reports that tie ongoing brain activity fluctuations to variability in human perception and behavior. Finally, these observations are discussed within the framework of the free-energy principle which – applied to human brain function - provides a theoretical account for a non-random, coordinated interaction of ongoing and evoked activity in perception and behaviour.

  20. Neural control of finger movement via intracortical brain-machine interface.

    Science.gov (United States)

    Irwin, Z T; Schroeder, K E; Vu, P P; Bullard, A J; Tat, D M; Nu, C S; Vaskov, A; Nason, S R; Thompson, D E; Bentley, J N; Patil, P G; Chestek, C A

    2017-12-01

    Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques. In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex. Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ  =  0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys' ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits s -1 throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter. This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We believe that these results represent an important step

  1. Thalamic Multisensory integration: Creating a neural network map of involved brain areas in music perception, processing and execution

    NARCIS (Netherlands)

    Jaschke, A.C.; Scherder, E.J.A.

    2013-01-01

    Music activates a wide array of neural areas involved in different functions besides the perception, processing and execution of music itself. Understanding musical processes in the brain has had multiple implications in the neuro- and health sciences. Engaging the brain with a multisensory stimulus

  2. Neural murmurations. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

    Science.gov (United States)

    Laurienti, Paul J.

    2014-09-01

    If not the last frontier, understanding the human brain is certainly one of the last. Over the past decade there has been a shift in the focus of neuroscience. The concept of the brain as a network is gaining traction and is rapidly becoming a dominant perspective [1]. In the target article [2], Luiz Pessoa discusses major conceptual shifts that must accompany the methodological changes associated with network science applications to the brain. The software, algorithms, and computational power needed to perform network analyses are now at the fingertips of all neuroscientists. But, this places us at a fork in the road. Will these tools be used to substantiate what has already been discovered, or will we seek a totally new and improved understanding of the brain?

  3. Dynamics of modularity of neural activity in the brain during development

    Science.gov (United States)

    Deem, Michael; Chen, Man

    2014-03-01

    Theory suggests that more modular systems can have better response functions at short times. This theory suggests that greater cognitive performance may be achieved for more modular neural activity, and that modularity of neural activity may, therefore, likely increase with development in children. We study the relationship between age and modularity of brain neural activity in developing children. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. We interpret these results as evidence of selection for plasticity in the cognitive function of the human brain. We present a model to illustrate how modularity can provide greater cognitive performance at short times and enhance fast, low-level, automatic cognitive processes. Conversely, high-level, effortful, conscious cognitive processes may not benefit from modularity. We use quasispecies theory to predict how the average modularity evolves with age, given a fitness function extracted from the model. We suggest further experiments exploring the effect of modularity on cognitive performance and suggest that modularity may be a potential biomarker for injury, rehabilitation, or disease.

  4. Neural Plasticity in Human Brain Connectivity: The Effects of Long Term Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson’s Disease

    Science.gov (United States)

    van Hartevelt, Tim J.; Cabral, Joana; Deco, Gustavo; Møller, Arne; Green, Alexander L.; Aziz, Tipu Z.; Kringelbach, Morten L.

    2014-01-01

    Background Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson’s Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. Results We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson’s Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson’s Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. Conclusions The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation. PMID

  5. Neural plasticity in human brain connectivity: the effects of long term deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

    Science.gov (United States)

    van Hartevelt, Tim J; Cabral, Joana; Deco, Gustavo; Møller, Arne; Green, Alexander L; Aziz, Tipu Z; Kringelbach, Morten L

    2014-01-01

    Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson's Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson's Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson's Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation.

  6. Genetic ablation of caveolin-1 increases neural stem cell proliferation in the subventricular zone (SVZ) of the adult mouse brain.

    Science.gov (United States)

    Jasmin, Jean-François; Yang, Ming; Iacovitti, Lorraine; Lisanti, Michael P

    2009-12-01

    Adult neural stem cells are self-renewing multipotent cells that have the potential to replace dysfunctional and/or dying neuronal cells at the site of brain injury or degeneration. Caveolins are well-known tumor-suppressor genes that were recently found to be involved in the regulation of stem cell proliferation. For instance, ablation of the caveolin-1 (Cav-1) gene in mice markedly increases the proliferation of intestinal and mammary stem cells. However, the roles of caveolins in the proliferation of adult neural stem cells still remain unknown. In this study, dual-label immunofluorescence analysis of the proliferation marker, Ki67, and the stem cell markers, nestin and Sox2, was performed on brains of 8 week-old wild-type (WT) and Cav-1 knockout (KO) mice. Our results demonstrate an increased number of Ki67-positive nuclei in the subventricular zone (SVZ) of Cav-1 KO brains. Importantly, our dual-label immunofluorescence analyses demonstrate increased co-localization of Ki67 with both nestin and Sox2 in the SVZ of Cav-1 KO brains. Remarkably similar results were also obtained with Cav-2 and Cav-3 KO mouse brains as well, with increased proliferation of adult neural stem cells. Thus, the SVZ of caveolin KO mouse brains displays an increased proliferation of adult neural stem cells. Caveolin proteins might represent new crucial regulators of adult neural stem cell proliferation.

  7. Auto-deleting brain machine interface: Error detection using spiking neural activity in the motor cortex.

    Science.gov (United States)

    Even-Chen, Nir; Stavisky, Sergey D; Kao, Jonathan C; Ryu, Stephen I; Shenoy, Krishna V

    2015-01-01

    Brain machine interfaces (BMIs) aim to assist people with paralysis by increasing their independence and ability to communicate, e.g., by using a cursor-based virtual keyboard. Current BMI clinical trials are hampered by modest performance that causes selection of wrong characters (errors) and thus reduces achieved typing rate. If it were possible to detect these errors without explicit knowledge of the task goal, this could be used to automatically "undo" wrong selections or even prevent upcoming wrong selections. We decoded imminent or recent errors during closed-loop BMI control from intracortical spiking neural activity. In our experiment, a non-human primate controlled a neurally-driven BMI cursor to acquire targets on a grid, which simulates a virtual keyboard. In offline analyses of this closed-loop BMI control data, we identified motor cortical neural signals indicative of task error occurrence. We were able to detect task outcomes (97% accuracy) and even predict upcoming task outcomes (86% accuracy) using neural activity alone. This novel strategy may help increase the performance and clinical viability of BMIs.

  8. Anger in brain and body: the neural and physiological perturbation of decision-making by emotion.

    Science.gov (United States)

    Garfinkel, Sarah N; Zorab, Emma; Navaratnam, Nakulan; Engels, Miriam; Mallorquí-Bagué, Núria; Minati, Ludovico; Dowell, Nicholas G; Brosschot, Jos F; Thayer, Julian F; Critchley, Hugo D

    2016-01-01

    Emotion and cognition are dynamically coupled to bodily arousal: the induction of anger, even unconsciously, can reprioritise neural and physiological resources toward action states that bias cognitive processes. Here we examine behavioural, neural and bodily effects of covert anger processing and its influence on cognition, indexed by lexical decision-making. While recording beat-to-beat blood pressure, the words ANGER or RELAX were presented subliminally just prior to rapid word/non-word reaction-time judgements of letter-strings. Subliminal ANGER primes delayed the time taken to reach rapid lexical decisions, relative to RELAX primes. However, individuals with high trait anger were speeded up by subliminal anger primes. ANGER primes increased systolic blood pressure and the magnitude of this increase predicted reaction time prolongation. Within the brain, ANGER trials evoked an enhancement of activity within dorsal pons and an attenuation of activity within visual occipitotemporal and attentional parietal cortices. Activity within periaqueductal grey matter, occipital and parietal regions increased linearly with evoked blood pressure changes, indicating neural substrates through which covert anger impairs semantic decisions, putatively through its expression as visceral arousal. The behavioural and physiological impact of anger states compromises the efficiency of cognitive processing through action-ready changes in autonomic response that skew regional neural activity. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  9. Comparative transcriptome analysis in induced neural stem cells reveals defined neural cell identities in vitro and after transplantation into the adult rodent brain

    Directory of Open Access Journals (Sweden)

    Anna-Lena Hallmann

    2016-05-01

    Full Text Available Reprogramming technology enables the production of neural progenitor cells (NPCs from somatic cells by direct transdifferentiation. However, little is known on how neural programs in these induced neural stem cells (iNSCs differ from those of alternative stem cell populations in vitro and in vivo. Here, we performed transcriptome analyses on murine iNSCs in comparison to brain-derived neural stem cells (NSCs and pluripotent stem cell-derived NPCs, which revealed distinct global, neural, metabolic and cell cycle-associated marks in these populations. iNSCs carried a hindbrain/posterior cell identity, which could be shifted towards caudal, partially to rostral but not towards ventral fates in vitro. iNSCs survived after transplantation into the rodent brain and exhibited in vivo-characteristics, neural and metabolic programs similar to transplanted NSCs. However, iNSCs vastly retained caudal identities demonstrating cell-autonomy of regional programs in vivo. These data could have significant implications for a variety of in vitro- and in vivo-applications using iNSCs.

  10. Neurogenin-2-transduced human neural progenitor cells attenuate neonatal hypoxic-ischemic brain injury.

    Science.gov (United States)

    Lee, Il-Shin; Koo, Kyo Yeon; Jung, Kwangsoo; Kim, Miri; Kim, Il-Sun; Hwang, Kyujin; Yun, Seokhwan; Lee, Haejin; Shin, Jeong Eun; Park, Kook In

    2017-05-01

    Neonatal hypoxic-ischemic (HI) brain injury leads to high mortality and neurodevelopmental disabilities. Multipotent neural progenitor cells (NPCs) with self-renewing capacity have the potential to reduce neuronal loss and improve the compromised environment in the HI brain injury. However, the therapeutic efficacy of neuronal-committed progenitor cells and the underlying mechanisms of recovery are not yet fully understood. Therefore, this study investigated the regenerative ability and action mechanisms of neuronally committed human NPCs (hNPCs) transduced with neurogenin-2 (NEUROG2) in neonatal HI brain injury. NEUROG2- or green fluorescent protein (GFP)-encoding adenoviral vector-transduced hNPCs (NEUROG2- or GFP-NPCs) were transplanted into neonatal mouse brains with HI injury. Grafted NEUROG2-NPCs showed robust dispersion and engraftment, prolonged survival, and neuronal differentiation in HI brain injury. NEUROG2-NPCs significantly improved neurological behaviors, decreased cellular apoptosis, and increased the neurite outgrowth and axonal sprouting in HI brain injury. In contrast, GFP-NPC grafts moderately enhanced axonal extension with limited behavioral recovery. Notably, NEUROG2-NPCs showed increased secretion of multiple factors, such as nerve growth factor, brain-derived neurotrophic factor, neurotrophin-3 (NTF3), fibroblast growth factor 9 (FGF9), ciliary neurotrophic factor (CNTF), and thrombospondins 1 and 2 (THBS 1/2), which promoted SH-SY5Y neuroblastoma cell survival and neurite outgrowth. Thus, we postulate that NEUROG2-expressing human NPCs facilitate functional recovery after neonatal HI brain injury via their ability to secrete multiple factors that enhance neuronal survival and neuroplasticity. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Brain Dynamics in Predicting Driving Fatigue Using a Recurrent Self-Evolving Fuzzy Neural Network.

    Science.gov (United States)

    Liu, Yu-Ting; Lin, Yang-Yin; Wu, Shang-Lin; Chuang, Chun-Hsiang; Lin, Chin-Teng

    2016-02-01

    This paper proposes a generalized prediction system called a recurrent self-evolving fuzzy neural network (RSEFNN) that employs an on-line gradient descent learning rule to address the electroencephalography (EEG) regression problem in brain dynamics for driving fatigue. The cognitive states of drivers significantly affect driving safety; in particular, fatigue driving, or drowsy driving, endangers both the individual and the public. For this reason, the development of brain-computer interfaces (BCIs) that can identify drowsy driving states is a crucial and urgent topic of study. Many EEG-based BCIs have been developed as artificial auxiliary systems for use in various practical applications because of the benefits of measuring EEG signals. In the literature, the efficacy of EEG-based BCIs in recognition tasks has been limited by low resolutions. The system proposed in this paper represents the first attempt to use the recurrent fuzzy neural network (RFNN) architecture to increase adaptability in realistic EEG applications to overcome this bottleneck. This paper further analyzes brain dynamics in a simulated car driving task in a virtual-reality environment. The proposed RSEFNN model is evaluated using the generalized cross-subject approach, and the results indicate that the RSEFNN is superior to competing models regardless of the use of recurrent or nonrecurrent structures.

  12. Branding and a child's brain: an fMRI study of neural responses to logos.

    Science.gov (United States)

    Bruce, Amanda S; Bruce, Jared M; Black, William R; Lepping, Rebecca J; Henry, Janice M; Cherry, Joseph Bradley C; Martin, Laura E; Papa, Vlad B; Davis, Ann M; Brooks, William M; Savage, Cary R

    2014-01-01

    Branding and advertising have a powerful effect on both familiarity and preference for products, yet no neuroimaging studies have examined neural response to logos in children. Food advertising is particularly pervasive and effective in manipulating choices in children. The purpose of this study was to examine how healthy children's brains respond to common food and other logos. A pilot validation study was first conducted with 32 children to select the most culturally familiar logos, and to match food and non-food logos on valence and intensity. A new sample of 17 healthy weight children were then scanned using functional magnetic resonance imaging. Food logos compared to baseline were associated with increased activation in orbitofrontal cortex and inferior prefrontal cortex. Compared to non-food logos, food logos elicited increased activation in posterior cingulate cortex. Results confirmed that food logos activate some brain regions in children known to be associated with motivation. This marks the first study in children to examine brain responses to culturally familiar logos. Considering the pervasiveness of advertising, research should further investigate how children respond at the neural level to marketing.

  13. Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging

    Directory of Open Access Journals (Sweden)

    Dipanjan Ray

    2017-09-01

    Full Text Available Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research.

  14. Brain-controlled neuromuscular stimulation to drive neural plasticity and functional recovery.

    Science.gov (United States)

    Ethier, C; Gallego, J A; Miller, L E

    2015-08-01

    There is mounting evidence that appropriately timed neuromuscular stimulation can induce neural plasticity and generate functional recovery from motor disorders. This review addresses the idea that coordinating stimulation with a patient's voluntary effort might further enhance neurorehabilitation. Studies in cell cultures and behaving animals have delineated the rules underlying neural plasticity when single neurons are used as triggers. However, the rules governing more complex stimuli and larger networks are less well understood. We argue that functional recovery might be optimized if stimulation were modulated by a brain machine interface, to match the details of the patient's voluntary intent. The potential of this novel approach highlights the need for a better understanding of the complex rules underlying this form of plasticity. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. A novel fluorescent reporter CDy1 enriches for neural stem cells derived from the murine brain.

    Science.gov (United States)

    Vukovic, Jana; Bedin, Anne-Sophie; Bartlett, Perry F; Osborne, Geoffrey W

    2013-08-15

    Neurogenesis occurs continuously in two brain regions of adult mammals, underpinned by a pool of resident neural stem cells (NSCs) that can differentiate into all neural cell types. To advance our understanding of NSC function and to develop therapeutic and diagnostic approaches, it is important to accurately identify and enrich for NSCs. There are no definitive markers for the identification and enrichment of NSCs present in the mouse brain. Recently, a fluorescent rosamine dye, CDy1, has been identified as a label for pluripotency in cultured human embryonic and induced pluripotent stem cells. As similar cellular characteristics may enable the uptake and retention of CDy1 by other stem cell populations, we hypothesized that this dye may also enrich for primary NSCs from the mouse brain. Because the subventricular zone (SVZ) and the hippocampus represent brain regions that are highly enriched for NSCs in adult mammals, we sampled cells from these areas to test this hypothesis. These experiments revealed that CDy1 staining indeed allows for enrichment and selection of all neurosphere-forming cells from both the SVZ and the hippocampus. We next examined the effectiveness of CDy1 to select for NSCs derived from the SVZ of aged animals, where the total pool of NSCs present is significantly lower than in young animals. We found that CDy1 effectively labels the NSCs in adult and aged animals as assessed by the neurosphere assay and reflects the numbers of NSCs present in aged animals. CDy1, therefore, appears to be a novel marker for enrichment of NSCs in primary brain tissue preparations.

  16. Image analysis of neural stem cell division patterns in the zebrafish brain.

    Science.gov (United States)

    Lupperger, Valerio; Buggenthin, Felix; Chapouton, Prisca; Marr, Carsten

    2017-11-10

    Proliferating stem cells in the adult body are the source of constant regeneration. In the brain, neural stem cells (NSCs) divide to maintain the stem cell population and generate neural progenitor cells that eventually replenish mature neurons and glial cells. How much spatial coordination of NSC division and differentiation is present in a functional brain is an open question. To quantify the patterns of stem cell divisions, one has to (i) identify the pool of NSCs that have the ability to divide, (ii) determine NSCs that divide within a given time window, and (iii) analyze the degree of spatial coordination. Here, we present a bioimage informatics pipeline that automatically identifies GFP expressing NSCs in three-dimensional image stacks of zebrafish brain from whole-mount preparations. We exploit the fact that NSCs in the zebrafish hemispheres are located on a two-dimensional surface and identify between 1,500 and 2,500 NSCs in six brain hemispheres. We then determine the position of dividing NSCs in the hemisphere by EdU incorporation into cells undergoing S-phase and calculate all pairwise NSC distances with three alternative metrics. Finally, we fit a probabilistic model to the observed spatial patterns that accounts for the non-homogeneous distribution of NSCs. We find a weak positive coordination between dividing NSCs irrespective of the metric and conclude that neither strong inhibitory nor strong attractive signals drive NSC divisions in the adult zebrafish brain. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

  17. Application of viral vectors to the study of neural connectivities and neural circuits in the marmoset brain.

    Science.gov (United States)

    Watakabe, Akiya; Sadakane, Osamu; Hata, Katsusuke; Ohtsuka, Masanari; Takaji, Masafumi; Yamamori, Tetsuo

    2017-03-01

    It is important to study the neural connectivities and functions in primates. For this purpose, it is critical to be able to transfer genes to certain neurons in the primate brain so that we can image the neuronal signals and analyze the function of the transferred gene. Toward this end, our team has been developing gene transfer systems using viral vectors. In this review, we summarize our current achievements as follows. 1) We compared the features of gene transfer using five different AAV serotypes in combination with three different promoters, namely, CMV, mouse CaMKII (CaMKII), and human synapsin 1 (hSyn1), in the marmoset cortex with those in the mouse and macaque cortices. 2) We used target-specific double-infection techniques in combination with TET-ON and TET-OFF using lentiviral retrograde vectors for enhanced visualization of neural connections. 3) We used an AAV-mediated gene transfer method to study the transcriptional control for amplifying fluorescent signals using the TET/TRE system in the primate neocortex. We also established systems for shRNA mediated gene targeting in a neocortical region where a gene is significantly expressed and for expressing the gene using the CMV promoter for an unexpressed neocortical area in the primate cortex using AAV vectors to understand the regulation of downstream genes. Our findings have demonstrated the feasibility of using viral vector mediated gene transfer systems for the study of primate cortical circuits using the marmoset as an animal model. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 354-372, 2017. © 2016 The Authors. Developmental Neurobiology Published by Wiley Periodicals, Inc.

  18. Neural networks improve brain cancer detection with Raman spectroscopy in the presence of light artifacts

    Science.gov (United States)

    Jermyn, Michael; Desroches, Joannie; Mercier, Jeanne; St-Arnaud, Karl; Guiot, Marie-Christine; Petrecca, Kevin; Leblond, Frederic

    2016-03-01

    It is often difficult to identify cancer tissue during brain cancer (glioma) surgery. Gliomas invade into areas of normal brain, and this cancer invasion is frequently not detected using standard preoperative magnetic resonance imaging (MRI). This results in enduring invasive cancer following surgery and leads to recurrence. A hand-held Raman spectroscopy is able to rapidly detect cancer invasion in patients with grade 2-4 gliomas. However, ambient light sources can produce spectral artifacts which inhibit the ability to distinguish between cancer and normal tissue using the spectral information available. To address this issue, we have demonstrated that artificial neural networks (ANN) can accurately classify invasive cancer versus normal brain tissue, even when including measurements with significant spectral artifacts from external light sources. The non-parametric and adaptive model used by ANN makes it suitable for detecting complex non-linear spectral characteristics associated with different tissues and the confounding presence of light artifacts. The use of ANN for brain cancer detection with Raman spectroscopy, in the presence of light artifacts, improves the robustness and clinical translation potential for intraoperative use. Integration with the neurosurgical workflow is facilitated by accounting for the effect of light artifacts which may occur, due to operating room lights, neuronavigation systems, windows, or other light sources. The ability to rapidly detect invasive brain cancer under these conditions may reduce residual cancer remaining after surgery, and thereby improve patient survival.

  19. Topographic factor analysis: a Bayesian model for inferring brain networks from neural data.

    Science.gov (United States)

    Manning, Jeremy R; Ranganath, Rajesh; Norman, Kenneth A; Blei, David M

    2014-01-01

    The neural patterns recorded during a neuroscientific experiment reflect complex interactions between many brain regions, each comprising millions of neurons. However, the measurements themselves are typically abstracted from that underlying structure. For example, functional magnetic resonance imaging (fMRI) datasets comprise a time series of three-dimensional images, where each voxel in an image (roughly) reflects the activity of the brain structure(s)-located at the corresponding point in space-at the time the image was collected. FMRI data often exhibit strong spatial correlations, whereby nearby voxels behave similarly over time as the underlying brain structure modulates its activity. Here we develop topographic factor analysis (TFA), a technique that exploits spatial correlations in fMRI data to recover the underlying structure that the images reflect. Specifically, TFA casts each brain image as a weighted sum of spatial functions. The parameters of those spatial functions, which may be learned by applying TFA to an fMRI dataset, reveal the locations and sizes of the brain structures activated while the data were collected, as well as the interactions between those structures.

  20. Topographic factor analysis: a Bayesian model for inferring brain networks from neural data.

    Directory of Open Access Journals (Sweden)

    Jeremy R Manning

    Full Text Available The neural patterns recorded during a neuroscientific experiment reflect complex interactions between many brain regions, each comprising millions of neurons. However, the measurements themselves are typically abstracted from that underlying structure. For example, functional magnetic resonance imaging (fMRI datasets comprise a time series of three-dimensional images, where each voxel in an image (roughly reflects the activity of the brain structure(s-located at the corresponding point in space-at the time the image was collected. FMRI data often exhibit strong spatial correlations, whereby nearby voxels behave similarly over time as the underlying brain structure modulates its activity. Here we develop topographic factor analysis (TFA, a technique that exploits spatial correlations in fMRI data to recover the underlying structure that the images reflect. Specifically, TFA casts each brain image as a weighted sum of spatial functions. The parameters of those spatial functions, which may be learned by applying TFA to an fMRI dataset, reveal the locations and sizes of the brain structures activated while the data were collected, as well as the interactions between those structures.

  1. Neural Underpinnings of Working Memory in Adult Survivors of Childhood Brain Tumors.

    Science.gov (United States)

    King, Tricia Z; Na, Sabrina; Mao, Hui

    2015-08-01

    Adult survivors of childhood brain tumors are at risk for cognitive performance deficits that require the core cognitive skill of working memory. Our goal was to examine the neural mechanisms underlying working memory performance in survivors. We studied the working memory of adult survivors of pediatric posterior fossa brain tumors using a letter n-back paradigm with varying cognitive workload (0-, 1-, 2-, and 3-back) and functional magnetic resonance imaging as well as neuropsychological measures. Survivors of childhood brain tumors evidenced lower working memory performance than demographically matched healthy controls. Whole-brain analyses revealed significantly greater blood-oxygen level dependent (BOLD) activation in the left superior / middle frontal gyri and left parietal lobe during working memory (2-back versus 0-back contrast) in survivors. Left frontal BOLD response negatively correlated with 2- and 3-back working memory performance, Auditory Consonant Trigrams (ACT), and Digit Span Backwards. In contrast, parietal lobe BOLD response negatively correlated with 0-back (vigilance task) and ACT. The results revealed that adult survivors of childhood posterior fossa brain tumors recruited additional cognitive control resources in the prefrontal lobe during increased working memory demands. This increased prefrontal activation is associated with lower working memory performance and is consistent with the allocation of latent resources theory.

  2. Pharmacological approach for targeting dysfunctional brain plasticity: Focus on neural cell adhesion molecule (NCAM).

    Science.gov (United States)

    Aonurm-Helm, Anu; Jaako, Külli; Jürgenson, Monika; Zharkovsky, Alexander

    2016-11-01

    Brain plasticity refers to the ability of the brain to undergo functionally relevant adaptations in response to external and internal stimuli. Alterations in brain plasticity have been associated with several neuropsychiatric disorders, and current theories suggest that dysfunctions in neuronal circuits and synaptogenesis have a major impact in the development of these diseases. Among the molecules that regulate brain plasticity, neural cell adhesion molecule (NCAM) and its polysialylated form PSA-NCAM have been of particular interest for years because alterations in NCAM and PSA-NCAM levels have been associated with memory impairment, depression, autistic spectrum disorders and schizophrenia. In this review, we discuss the roles of NCAM and PSA-NCAM in the regulation of brain plasticity and, in particular, their roles in the mechanisms of depression. We also demonstrate that the NCAM-mimetic peptides FGL and Enreptin are able to restore disrupted neuronal plasticity. FGL peptide has also been demonstrated to ameliorate the symptoms of depressive-like behavior in NCAM-deficient mice and therefore, may be considered a new drug candidate for the treatment of depression as well as other neuropsychiatric disorders with disrupted neuroplasticity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

    Science.gov (United States)

    Liu, Yan; Stojadinovic, Strahinja; Hrycushko, Brian; Wardak, Zabi; Lau, Steven; Lu, Weiguo; Yan, Yulong; Jiang, Steve B; Zhen, Xin; Timmerman, Robert; Nedzi, Lucien; Gu, Xuejun

    2017-01-01

    Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS) treatment planning. In this work, we developed a deep learning convolutional neural network (CNN) algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI) datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS) data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs) of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

  4. A deep convolutional neural network-based automatic delineation strategy for multiple brain metastases stereotactic radiosurgery.

    Directory of Open Access Journals (Sweden)

    Yan Liu

    Full Text Available Accurate and automatic brain metastases target delineation is a key step for efficient and effective stereotactic radiosurgery (SRS treatment planning. In this work, we developed a deep learning convolutional neural network (CNN algorithm for segmenting brain metastases on contrast-enhanced T1-weighted magnetic resonance imaging (MRI datasets. We integrated the CNN-based algorithm into an automatic brain metastases segmentation workflow and validated on both Multimodal Brain Tumor Image Segmentation challenge (BRATS data and clinical patients' data. Validation on BRATS data yielded average DICE coefficients (DCs of 0.75±0.07 in the tumor core and 0.81±0.04 in the enhancing tumor, which outperformed most techniques in the 2015 BRATS challenge. Segmentation results of patient cases showed an average of DCs 0.67±0.03 and achieved an area under the receiver operating characteristic curve of 0.98±0.01. The developed automatic segmentation strategy surpasses current benchmark levels and offers a promising tool for SRS treatment planning for multiple brain metastases.

  5. The Effects of Low-Dose Bisphenol A and Bisphenol F on Neural Differentiation of a Fetal Brain-Derived Neural Progenitor Cell Line

    Directory of Open Access Journals (Sweden)

    Yuki Fujiwara

    2018-02-01

    Full Text Available Environmental chemicals are known to disrupt the endocrine system in humans and to have adverse effects on several organs including the developing brain. Recent studies indicate that exposure to environmental chemicals during gestation can interfere with neuronal differentiation, subsequently affecting normal brain development in newborns. Xenoestrogen, bisphenol A (BPA, which is widely used in plastic products, is one such chemical. Adverse effects of exposure to BPA during pre- and postnatal periods include the disruption of brain function. However, the effect of BPA on neural differentiation remains unclear. In this study, we explored the effects of BPA or bisphenol F (BPF, an alternative compound for BPA, on neural differentiation using ReNcell, a human fetus-derived neural progenitor cell line. Maintenance in growth factor-free medium initiated the differentiation of ReNcell to neuronal cells including neurons, astrocytes, and oligodendrocytes. We exposed the cells to BPA or BPF for 3 days from the period of initiation and performed real-time PCR for neural markers such as β III-tubulin and glial fibrillary acidic protein (GFAP, and Olig2. The β III-tubulin mRNA level decreased in response to BPA, but not BPF, exposure. We also observed that the number of β III-tubulin-positive cells in the BPA-exposed group was less than that of the control group. On the other hand, there were no changes in the MAP2 mRNA level. These results indicate that BPA disrupts neural differentiation in human-derived neural progenitor cells, potentially disrupting brain development.

  6. The dynamic brain: from spiking neurons to neural masses and cortical fields.

    Directory of Open Access Journals (Sweden)

    Gustavo Deco

    2008-08-01

    Full Text Available The cortex is a complex system, characterized by its dynamics and architecture, which underlie many functions such as action, perception, learning, language, and cognition. Its structural architecture has been studied for more than a hundred years; however, its dynamics have been addressed much less thoroughly. In this paper, we review and integrate, in a unifying framework, a variety of computational approaches that have been used to characterize the dynamics of the cortex, as evidenced at different levels of measurement. Computational models at different space-time scales help us understand the fundamental mechanisms that underpin neural processes and relate these processes to neuroscience data. Modeling at the single neuron level is necessary because this is the level at which information is exchanged between the computing elements of the brain; the neurons. Mesoscopic models tell us how neural elements interact to yield emergent behavior at the level of microcolumns and cortical columns. Macroscopic models can inform us about whole brain dynamics and interactions between large-scale neural systems such as cortical regions, the thalamus, and brain stem. Each level of description relates uniquely to neuroscience data, from single-unit recordings, through local field potentials to functional magnetic resonance imaging (fMRI, electroencephalogram (EEG, and magnetoencephalogram (MEG. Models of the cortex can establish which types of large-scale neuronal networks can perform computations and characterize their emergent properties. Mean-field and related formulations of dynamics also play an essential and complementary role as forward models that can be inverted given empirical data. This makes dynamic models critical in integrating theory and experiments. We argue that elaborating principled and informed models is a prerequisite for grounding empirical neuroscience in a cogent theoretical framework, commensurate with the achievements in the

  7. The flexible brain - On mind and brain, neural darwinism and psychiatry

    NARCIS (Netherlands)

    DenBoer, JA

    A theoretical introduction is given in which several theoretical viewpoints concerning the mind-brain problem are discussed. During the last decade philosophers like Searle, Dennett and the Churchlands have taken a more or less pure materialistic position in explaining mental phenomena.

  8. Brain tumor segmentation using holistically nested neural networks in MRI images.

    Science.gov (United States)

    Zhuge, Ying; Krauze, Andra V; Ning, Holly; Cheng, Jason Y; Arora, Barbara C; Camphausen, Kevin; Miller, Robert W

    2017-10-01

    Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Magnetic resonance imaging (MRI) is a widely used technique employed in the diagnosis and management of gliomas in clinical practice. MRI is also the standard imaging modality used to delineate the brain tumor target as part of treatment planning for the administration of radiation therapy. Despite more than 20 yr of research and development, computational brain tumor segmentation in MRI images remains a challenging task. We are presenting a novel method of automatic image segmentation based on holistically nested neural networks that could be employed for brain tumor segmentation of MRI images. Two preprocessing techniques were applied to MRI images. The N4ITK method was employed for correction of bias field distortion. A novel landmark-based intensity normalization method was developed so that tissue types have a similar intensity scale in images of different subjects for the same MRI protocol. The holistically nested neural networks (HNN), which extend from the convolutional neural networks (CNN) with a deep supervision through an additional weighted-fusion output layer, was trained to learn the multiscale and multilevel hierarchical appearance representation of the brain tumor in MRI images and was subsequently applied to produce a prediction map of the brain tumor on test images. Finally, the brain tumor was obtained through an optimum thresholding on the prediction map. The proposed method was evaluated on both the Multimodal Brain Tumor Image Segmentation (BRATS) Benchmark 2013 training datasets, and clinical data from our institute. A dice similarity coefficient (DSC) and sensitivity of 0.78 and 0.81 were achieved on 20 BRATS 2013 training datasets with high-grade gliomas (HGG), based on a two-fold cross-validation. The HNN model built on the BRATS 2013 training data was applied to ten clinical datasets with HGG from a locally developed database. DSC and sensitivity of

  9. Dusp16 Deficiency Causes Congenital Obstructive Hydrocephalus and Brain Overgrowth by Expansion of the Neural Progenitor Pool

    Directory of Open Access Journals (Sweden)

    Ksenija Zega

    2017-11-01

    Full Text Available Hydrocephalus can occur in children alone or in combination with other neurodevelopmental disorders that are often associated with brain overgrowth. Despite the severity of these disorders, the molecular and cellular mechanisms underlying these pathologies and their comorbidity are poorly understood. Here, we studied the consequences of genetically inactivating in mice dual-specificity phosphatase 16 (Dusp16, which is known to negatively regulate mitogen-activated protein kinases (MAPKs and which has never previously been implicated in brain development and disorders. Mouse mutants lacking a functional Dusp16 gene (Dusp16−/− developed fully-penetrant congenital obstructive hydrocephalus together with brain overgrowth. The midbrain aqueduct in Dusp16−/− mutants was obstructed during mid-gestation by an expansion of neural progenitors, and during later gestational stages by neurons resulting in a blockage of cerebrospinal fluid (CSF outflow. In contrast, the roof plate and ependymal cells developed normally. We identified a delayed cell cycle exit of neural progenitors in Dusp16−/− mutants as a cause of progenitor overproliferation during mid-gestation. At later gestational stages, this expanded neural progenitor pool generated an increased number of neurons associated with enlarged brain volume. Taken together, we found that Dusp16 plays a critical role in neurogenesis by balancing neural progenitor cell proliferation and neural differentiation. Moreover our results suggest that a lack of functional Dusp16 could play a central role in the molecular mechanisms linking brain overgrowth and hydrocephalus.

  10. Neural stem cells sustain natural killer cells that dictate recovery from brain inflammation

    Science.gov (United States)

    Liu, Qiang; Sanai, Nader; Jin, Wei-Na; La Cava, Antonio; Van Kaer, Luc; Shi, Fu-Dong

    2017-01-01

    Recovery from organ-specific autoimmune diseases largely relies on the mobilization of endogenous repair mechanisms and local factors that control them. Natural killer (NK) cells are swiftly mobilized to organs targeted by autoimmunity and typically undergo numerical contraction when inflammation wanes. We report the unexpected finding that NK cells are retained in the brain subventricular zone (SVZ) during the chronic phase of multiple sclerosis in humans and its animal model in mice. These NK cells were found preferentially in close proximity to SVZ neural stem cells (NSCs) that produce interleukin-15 and sustain functionally competent NK cells. Moreover, NK cells limited the reparative capacity of NSCs following brain inflammation. These findings reveal that reciprocal interactions between NSCs and NK cells regulate neurorepair. PMID:26752157

  11. Cantorian Fractal Spacetime and Quantum-like Chaos in Neural Networks of the Human Brain

    CERN Document Server

    Selvam, A M

    1998-01-01

    The neural networks of the human brain act as very efficient parallel processing computers co-ordinating memory related responses to a multitude of input signals from sensory organs. Information storage, update and appropriate retrieval are controlled at the molecular level by the neuronal cytoskeleton which serves as the internal communication network within neurons. Information flow in the highly ordered parallel networks of the filamentous protein polymers which make up the cytoskeleton may be compared to atmospheric flows which exhibit long-range spatiotemporal correlations, i.e. long-term memory. Such long-range spatiotemporal correlations are ubiquitous to real world dynamical systems and is recently identified as signature of self-organized criticality or chaos. The signatures of self-organized criticality i.e. long-range temporal correlations have recently been identified in the electrical activity of the brain. A recently developed non-deterministic cell dynamical system model for atmospheric flows p...

  12. Cascaded evolutionary algorithm for nonlinear system identification based on correlation functions and radial basis functions neural networks

    Science.gov (United States)

    Ayala, Helon Vicente Hultmann; Coelho, Leandro dos Santos

    2016-02-01

    The present work introduces a procedure for input selection and parameter estimation for system identification based on Radial Basis Functions Neural Networks (RBFNNs) models with an improved objective function based on the residuals and its correlation function coefficients. We show the results when the proposed methodology is applied to model a magnetorheological damper, with real acquired data, and other two well-known benchmarks. The canonical genetic and differential evolution algorithms are used in cascade to decompose the problem of defining the lags taken as the inputs of the model and its related parameters based on the simultaneous minimization of the residuals and higher orders correlation functions. The inner layer of the cascaded approach is composed of a population which represents the lags on the inputs and outputs of the system and an outer layer represents the corresponding parameters of the RBFNN. The approach is able to define both the inputs of the model and its parameters. This is interesting as it frees the designer of manual procedures, which are time consuming and prone to error, usually done to define the model inputs. We compare the proposed methodology with other works found in the literature, showing overall better results for the cascaded approach.

  13. Neural basis of phonological processing in second language reading: an fMRI study of Chinese regularity effect.

    Science.gov (United States)

    Zhao, Jing; Li, Qing-Lin; Wang, Jiu-Ju; Yang, Yang; Deng, Yuan; Bi, Hong-Yan

    2012-03-01

    The present study examined the neural basis of phonological processing in Chinese later acquired as a second language (L2). The regularity effect of Chinese was selected to elucidate the addressed phonological processing. We recruited a group of alphabetic language speakers who had been learning Chinese as L2 for at least one year, and a control group of native Chinese speakers. Participants from both groups exhibited a regularity effect in a pilot behavioral test. Neuroimaging results revealed that L2 learners exhibited stronger activation than native Chinese speakers in the right occipitotemporal region (i.e. right lingual gyrus and right fusiform gyrus). Moreover, L2 learners exhibited greater activations in the ventral aspects of the left inferior parietal lobule (LIPL) and the left inferior frontal gyrus (LIFG) for irregular character reading minus regular character reading. In contrast, native Chinese speakers exhibited more dorsal activations in the LIPL and LIFG. According to the "accommodation/assimilation" hypothesis of second language reading, the current findings suggest that native speakers of alphabetic languages utilized an accommodation pattern for the specific requirements of the visual form of Chinese characters, and an assimilation pattern for orthography-to-phonology transformation in Chinese reading. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

  14. Interevent times estimation of major and continuous earthquakes in Hormozgan region based on radial basis function neural network

    Directory of Open Access Journals (Sweden)

    M.R. Mosavi

    2016-01-01

    Full Text Available This paper presents a new method to estimate the time of important earthquakes in Hormozgan region with magnitude greater than 5.5 based on the Radial Basis Function (RBF Neural Network (NN models. Input vector to the network is composed of different seismicity rates between main events that are calculated in convenient and reliable way to create optimized training methods. It helps network with a limited number of training data to estimation. It is common for earthquakes modeling by data-driven methods in this case. In addition, the proposed method is combined with Rosenberg cluster method to remove aftershocks events from the history of catalog for NN to better process the data. The results show that created RBF model successfully estimates the interevent times between large and sequence earthquakes that can be used as a tool to predict earthquake, so that comparison with other NN structure, for example Multi-Layer Perceptron (MLP NN, reveals the superiority of the proposed method. Because of superiority proposed method has higher accuracy, lower costs and simpler network structure.

  15. Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

    Science.gov (United States)

    Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

    2013-03-01

    Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

  16. Computation of the Speed of Four In-Wheel Motors of an Electric Vehicle Using a Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    M. Yildirim

    2016-12-01

    Full Text Available This paper presents design and speed estimation for an Electric Vehicle (EV with four in-wheel motors using Radial Basis Neural Network (RBNN. According to the steering angle and the speed of EV, the speeds of all wheels are calculated by equations derived from the Ackermann-Jeantand model using CoDeSys Software Package. The Electronic Differential System (EDS is also simulated by Matlab/Simulink using the mathematical equations. RBNN is used for the estimation of the wheel speeds based on the steering angle and EV speed. Further, different levels of noise are added to the steering angle and the EV speed. The speeds of front wheels calculated by CoDeSys are sent to two Induction Motor (IM drives via a Controller Area Network-Bus (CAN-Bus. These speed values are measured experimentally by a tachometer changing the steering angle and EV speed. RBNN results are verified by CoDeSys, Simulink, and experimental results. As a result, it is observed that RBNN is a good estimator for EDS of an EV with in-wheel motor due to its robustness to different levels of sensor noise.

  17. Isolating dividing neural and brain tumour cells for gene expression profiling.

    Science.gov (United States)

    Endaya, Berwini; Cavanagh, Brenton; Alowaidi, Faisal; Walker, Tom; de Pennington, Nicholas; Ng, Jin-Ming A; Lam, Paula Y P; Mackay-Sim, Alan; Neuzil, Jiri; Meedeniya, Adrian C B

    2016-01-15

    The characterisation of dividing brain cells is fundamental for studies ranging from developmental and stem cell biology, to brain cancers. Whilst there is extensive anatomical data on these dividing cells, limited gene transcription data is available due to technical constraints. We focally isolated dividing cells whilst conserving RNA, from culture, primary neural tissue and xenografted glioma tumours, using a thymidine analogue that enables gene transcription analysis. 5-ethynyl-2-deoxyuridine labels the replicating DNA of dividing cells. Once labelled, cultured cells and tissues were dissociated, fluorescently tagged with a revised click chemistry technique and the dividing cells isolated using fluorescence-assisted cell sorting. RNA was extracted and analysed using real time PCR. Proliferation and maturation related gene expression in neurogenic tissues was demonstrated in acutely and 3 day old labelled cells, respectively. An elevated expression of marker and pathway genes was demonstrated in the dividing cells of xenografted brain tumours, with the non-dividing cells showing relatively low levels of expression. BrdU "immune-labelling", the most frequently used protocol for detecting cell proliferation, causes complete denaturation of RNA, precluding gene transcription analysis. This EdU labelling technique, maintained cell integrity during dissociation, minimized copper exposure during labelling and used a cell isolation protocol that avoided cell lysis, thus conserving RNA. The technique conserves RNA, enabling the definition of cell proliferation-related changes in gene transcription of neural and pathological brain cells in cells harvested immediately after division, or following a period of maturation. Copyright © 2015 Elsevier B.V. All rights reserved.

  18. Physics strategies for sparing neural stem cells during whole-brain radiation treatments.

    Science.gov (United States)

    Kirby, Neil; Chuang, Cynthia; Pouliot, Jean; Hwang, Andrew; Barani, Igor J

    2011-10-01

    Currently, there are no successful long-term treatments or preventive strategies for radiation-induced cognitive impairments, and only a few possibilities have been suggested. One such approach involves reducing the dose to neural stem cell compartments (within and outside of the hippocampus) during whole-brain radiation treatments for brain metastases. This study investigates the fundamental physics issues associated with the sparing of neural stem cells during photon radiotherapy for brain metastases. Several factors influence the stem cell dose: intracranial scattering, collimator leakage, beam energy, and total number of beams. The relative importance of these factors is investigated through a set of radiation therapy plans, which are all variations of an initial 6 MV intensity-modulated radiation therapy (IMRT) plan designed to simultaneously deliver a whole-brain dose of 30 Gy and maximally reduce stem cell compartment dose. Additionally, an in-house leaf segmentation algorithm was developed that utilizes jaw motion to minimize the collimator leakage. The plans are all normalized such that 50% of the PTV receives 30 Gy. For the initial 6 MV IMRT plan, 50% of the stem cells receive a dose greater than 6.3 Gy. Calculations indicate that 3.6 Gy of this dose originates from intracranial scattering. The jaw-tracking segmentation algorithm, used in conjunction with direct machine parameter optimization, reduces the 50% stem cell dose to 4.3 and 3.7 Gy for 6 and 10 MV treatment beams, respectively. Intracranial scattering alone is responsible for a large dose contribution to the stem cell compartment. It is, therefore, important to minimize other contributing factors, particularly the collimator leakage, to maximally reduce dose to these critical structures. The use of collimator jaw tracking in conjunction with modern collimators can minimize this leakage.

  19. Physics strategies for sparing neural stem cells during whole-brain radiation treatments

    Energy Technology Data Exchange (ETDEWEB)

    Kirby, Neil; Chuang, Cynthia; Pouliot, Jean; Hwang, Andrew; Barani, Igor J. [Department of Radiation Oncology, University of California San Francisco, San Francisco, California 94143-1708 (United States)

    2011-10-15

    Purpose: Currently, there are no successful long-term treatments or preventive strategies for radiation-induced cognitive impairments, and only a few possibilities have been suggested. One such approach involves reducing the dose to neural stem cell compartments (within and outside of the hippocampus) during whole-brain radiation treatments for brain metastases. This study investigates the fundamental physics issues associated with the sparing of neural stem cells during photon radiotherapy for brain metastases. Methods: Several factors influence the stem cell dose: intracranial scattering, collimator leakage, beam energy, and total number of beams. The relative importance of these factors is investigated through a set of radiation therapy plans, which are all variations of an initial 6 MV intensity-modulated radiation therapy (IMRT) plan designed to simultaneously deliver a whole-brain dose of 30 Gy and maximally reduce stem cell compartment dose. Additionally, an in-house leaf segmentation algorithm was developed that utilizes jaw motion to minimize the collimator leakage. Results: The plans are all normalized such that 50% of the PTV receives 30 Gy. For the initial 6 MV IMRT plan, 50% of the stem cells receive a dose greater than 6.3 Gy. Calculations indicate that 3.6 Gy of this dose originates from intracranial scattering. The jaw-tracking segmentation algorithm, used in conjunction with direct machine parameter optimization, reduces the 50% stem cell dose to 4.3 and 3.7 Gy for 6 and 10 MV treatment beams, respectively. Conclusions: Intracranial scattering alone is responsible for a large dose contribution to the stem cell compartment. It is, therefore, important to minimize other contributing factors, particularly the collimator leakage, to maximally reduce dose to these critical structures. The use of collimator jaw tracking in conjunction with modern collimators can minimize this leakage.

  20. Neural signatures of third-party punishment: evidence from penetrating traumatic brain injury.

    Science.gov (United States)

    Glass, Leila; Moody, Lara; Grafman, Jordan; Krueger, Frank

    2016-02-01

    The ability to survive within a cooperative society depends on impartial third-party punishment (TPP) of social norm violations. Two cognitive mechanisms have been postulated as necessary for the successful completion of TPP: evaluation of legal responsibility and selection of a suitable punishment given the magnitude of the crime. Converging neuroimaging research suggests two supporting domain-general networks; a mentalizing network for evaluation of legal responsibility and a central-executive network for determination of punishment. A whole-brain voxel-based lesion-symptom mapping approach was used in conjunction with a rank-order TPP task to identify brain regions necessary for TPP in a large sample of patients with penetrating traumatic brain injury. Patients who demonstrated atypical TPP had specific lesions in core regions of the mentalizing (dorsomedial prefrontal cortex [PFC], ventromedial PFC) and central-executive (bilateral dorsolateral PFC, right intraparietal sulcus) networks. Altruism and executive functioning (concept formation skills) were significant predictors of TPP: altruism was uniquely associated with TPP in patients with lesions in right dorsolateral PFC and executive functioning was uniquely associated with TPP in individuals with lesions in left PFC. Our findings contribute to the extant literature to support underlying neural networks associated with TPP, with specific brain-behavior causal relationships confirming recent functional neuroimaging research. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  1. Targeted delivery of neural stem cells to the brain using MRI-guided focused ultrasound to disrupt the blood-brain barrier.

    Directory of Open Access Journals (Sweden)

    Alison Burgess

    Full Text Available Stem cell therapy is a promising strategy to treat neurodegenerative diseases, traumatic brain injury, and stroke. For stem cells to progress towards clinical use, the risks associated with invasive intracranial surgery used to deliver the cells to the brain, needs to be reduced. Here, we show that MRI-guided focused ultrasound (MRIgFUS is a novel method for non-invasive delivery of stem cells from the blood to the brain by opening the blood brain barrier (BBB in specific brain regions. We used MRI guidance to target the ultrasound beam thereby delivering the iron-labeled, green fluorescent protein (GFP-expressing neural stem cells specifically to the striatum and the hippocampus of the rat brain. Detection of cellular iron using MRI established that the cells crossed the BBB to enter the brain. After sacrifice, 24 hours later, immunohistochemical analysis confirmed the presence of GFP-positive cells in the targeted brain regions. We determined that the neural stem cells expressed common stem cell markers (nestin and polysialic acid suggesting they survived after transplantation with MRIgFUS. Furthermore, delivered stem cells expressed doublecortin in vivo indicating the stem cells were capable of differentiating into neurons. Together, we demonstrate that transient opening of the BBB with MRIgFUS is sufficient for transplantation of stem cells from the blood to targeted brain structures. These results suggest that MRIgFUS may be an effective alternative to invasive intracranial surgery for stem cell transplantation.

  2. [Neural basis of pain].

    Science.gov (United States)

    Calvino, Bernard

    2006-03-01

    Main elements concerning the physiology of pain are described, as well as the structures of the nervous system at the origin of the central control of pain: peripheral fibres (small diameter myelinated A delta and unmyelinated C fibres); spinal ascending pathways; cerebral structures relaying nociceptive information (medial and ventro-postero-lateral thalamic relays); SI and SII cortical areas; spinal segmentary and supraspinal excitatory and inhibitory controls; diffuse noxious inhibitory controls (DNIC). Chronic pain is a result of two processes: peripheral and central sensitization, in relation with inflammation and nerve injury at peripheral level and with neuroplasticity at central level. Neurotrophins, mainly NGF and BDNF and their receptors (LNTR, TrkA and TrkB) are involved in these processes. Pain is a result of an unpleasant emotional experience: its various components, mainly the emotional one, may be increased or decreased considering the different characteristics of the stimulus and of the affective state of the patient, as well as the context in which this stimulus is applied. The role of physiological systems, unconnected with those classically involved in the physiology of nociception and pain, such as the motor cortex in phantom limb pain, are described in conclusion, to focus on the extreme complexity of the control systems of pain in humans.

  3. Identifying endogenous neural stem cells in the adult brain in vitro and in vivo: novel approaches.

    Science.gov (United States)

    Rueger, Maria Adele; Androutsellis-Theotokis, Andreas

    2013-01-01

    In the 1960s, Joseph Altman reported that the adult mammalian brain is capable of generating new neurons. Today it is understood that some of these neurons are derived from uncommitted cells in the subventricular zone lining the lateral ventricles, and the dentate gyrus of the hippocampus. The first area generates new neuroblasts which migrate to the olfactory bulb, whereas hippocampal neurogenesis seems to play roles in particular types of learning and memory. A part of these uncommitted (immature) cells is able to divide and their progeny can generate all three major cell types of the nervous system: neurons, astrocytes, and oligodendrocytes; these properties define such cells as neural stem cells. Although the roles of these cells are not yet clear, it is accepted that they affect functions including olfaction and learning/memory. Experiments with insults to the central nervous system also show that neural stem cells are quickly mobilized due to injury and in various disorders by proliferating, and migrating to injury sites. This suggests a role of endogenous neural stem cells in disease. New pools of stem cells are being discovered, suggesting an even more important role for these cells. To understand these cells and to coax them to contribute to tissue repair it would be very useful to be able to image them in the living organism. Here we discuss advances in imaging approaches as well as new concepts that emerge from stem cell biology with emphasis on the interface between imaging and stem cells.

  4. Differential neural activation when voluntarily regulating emotions in service members with chronic mild traumatic brain injury.

    Science.gov (United States)

    Dretsch, Michael N; Daniel, Thomas A; Goodman, Adam M; Katz, Jeffrey S; Denney, Thomas; Deshpande, Gopikrishna; Robinson, Jennifer L

    2017-09-19

    The objective of this study was to characterize the functional activation of the neural correlates of voluntary regulation of emotion in soldiers both with and without chronic mild traumatic brain injury (mTBI). Using functional magnetic resonance imaging (fMRI) and a battery of cognitive and psychological health measures, we assessed differences between active-duty U.S. soldiers with chronic mTBI (n = 37) and without (Controls, n = 35). Participants were instructed to maintain (passively view), enhance, and suppress emotions associated with negative and neutral visual stimuli. The mTBI group showed significantly greater clinical symptoms, but only a mild decrement in attention. Group contrasts, while controlling for posttraumatic stress disorder (PTSD) symptoms, revealed a differential neural activation pattern compared to controls, but only during the enhance condition. Specifically, the mTBI group showed greater activation in the precentral gyrus, postcentral gyrus, inferior parietal lobe, insula, and superior temporal gyrus. Finally, the effect of PTSD symptoms during the enhance condition was associated with accentuated activation of the frontal and limbic regions implicated in both emotion regulation and PTSD. Hyperactivation of neural regions in the mTBI group during the enhance condition may reflect vigilance towards negative contextual stimuli and/or poor strategy that might result in suboptimal allocation of resources to regulate emotions.

  5. Expression of Tau Pathology-Related Proteins in Different Brain Regions: A Molecular Basis of Tau Pathogenesis

    Directory of Open Access Journals (Sweden)

    Wen Hu

    2017-09-01

    Full Text Available Microtubule-associated protein tau is hyperphosphorylated and aggregated in affected neurons in Alzheimer disease (AD brains. The tau pathology starts from the entorhinal cortex (EC, spreads to the hippocampus and frontal and temporal cortices, and finally to all isocortex areas, but the cerebellum is spared from tau lesions. The molecular basis of differential vulnerability of different brain regions to tau pathology is not understood. In the present study, we analyzed brain regional expressions of tau and tau pathology-related proteins. We found that tau was hyperphosphorylated at multiple sites in the frontal cortex (FC, but not in the cerebellum, from AD brain. The level of tau expression in the cerebellum was about 1/4 of that seen in the frontal and temporal cortices in human brain. In the rat brain, the expression level of tau with three microtubule-binding repeats (3R-tau was comparable in the hippocampus, EC, FC, parietal-temporal cortex (PTC, occipital-temporal cortex (OTC, striatum, thalamus, olfactory bulb (OB and cerebellum. However, the expression level of 4R-tau was the highest in the EC and the lowest in the cerebellum. Tau phosphatases, kinases, microtubule-related proteins and other tau pathology-related proteins were also expressed in a region-specific manner in the rat brain. These results suggest that higher levels of tau and tau kinases in the EC and low levels of these proteins in the cerebellum may accounts for the vulnerability and resistance of these representative brain regions to the development of tau pathology, respectively. The present study provides the regional expression profiles of tau and tau pathology-related proteins in the brain, which may help understand the brain regional vulnerability to tau pathology in neurodegenerative tauopathies.

  6. Quantum neural network-based EEG filtering for a brain-computer interface.

    Science.gov (United States)

    Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

    2014-02-01

    A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

  7. Astrocytic Calcium Waves Signal Brain Injury to Neural Stem and Progenitor Cells.

    Science.gov (United States)

    Kraft, Anna; Jubal, Eduardo Rosales; von Laer, Ruth; Döring, Claudia; Rocha, Adriana; Grebbin, Moyo; Zenke, Martin; Kettenmann, Helmut; Stroh, Albrecht; Momma, Stefan

    2017-03-14

    Brain injuries, such as stroke or trauma, induce neural stem cells in the subventricular zone (SVZ) to a neurogenic response. Very little is known about the molecular cues that signal tissue damage, even over large distances, to the SVZ. Based on our analysis of gene expression patterns in the SVZ, 48 hr after an ischemic lesion caused by middle cerebral artery occlusion, we hypothesized that the presence of an injury might be transmitted by an astrocytic traveling calcium wave rather than by diffusible factors or hypoxia. Using a newly established in vitro system we show that calcium waves induced in an astrocytic monolayer spread to neural stem and progenitor cells and increase their self-renewal as well as migratory behavior. These changes are due to an upregulation of the Notch signaling pathway. This introduces the concept of propagating astrocytic calcium waves transmitting brain injury signals over long distances. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  8. Targeting Neural Endophenotypes of Eating Disorders with Non-invasive Brain Stimulation.

    Science.gov (United States)

    Dunlop, Katharine A; Woodside, Blake; Downar, Jonathan

    2016-01-01

    The term "eating disorders" (ED) encompasses a wide variety of disordered eating and compensatory behaviors, and so the term is associated with considerable clinical and phenotypic heterogeneity. This heterogeneity makes optimizing treatment techniques difficult. One class of treatments is non-invasive brain stimulation (NIBS). NIBS, including repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS), are accessible forms of neuromodulation that alter the cortical excitability of a target brain region. It is crucial for NIBS to be successful that the target is well selected for the patient population in question. Targets may best be selected by stepping back from conventional DSM-5 diagnostic criteria to identify neural substrates of more basic phenotypes, including behavior related to rewards and punishment, cognitive control, and social processes. These phenotypic dimensions have been recently laid out by the Research Domain Criteria (RDoC) initiative. Consequently, this review is intended to identify potential dimensions as outlined by the RDoC and the underlying behavioral and neurobiological targets associated with ED. This review will also identify candidate targets for NIBS based on these dimensions and review the available literature on rTMS and tDCS in ED. This review systematically reviews abnormal neural circuitry in ED within the RDoC framework, and also systematically reviews the available literature investigating NIBS as a treatment for ED.

  9. Targeting neural endophenotypes of eating disorders with non-invasive brain stimulation

    Directory of Open Access Journals (Sweden)

    Katharine A Dunlop

    2016-02-01

    Full Text Available The term eating disorders (ED encompasses a wide variety of disordered eating and compensatory behaviors, and so the term is associated with considerable clinical and phenotypic heterogeneity. This heterogeneity makes optimizing treatment techniques difficult. One class of treatments is non-invasive brain stimulation (NIBS. NIBS, including repetitive transcranial magnetic stimulation (rTMS and transcranial direct current stimulation (tDCS are accessible forms of neuromodulation that alter the cortical excitability of a target brain region. It is crucial for NIBS to be successful that the target is well selected for the patient population in question. Targets may best be selected by stepping back from conventional DSM-5 diagnostic criteria to identify neural substrates of more basic phenotypes, including behavior related rewards and punishment cognitive control, and social processes. These phenotypic dimensions have been recently laid out by the Research Domain Criteria (RDoC initiative. Consequently, this review is intended to identify potential dimensions as outlined by the RDoC and their underlying behavioral and neurobiological targets associated with ED as potential candidates for NIBS and review the available literature on rTMS and tDCS in ED. This review systematically reviews abnormal neural circuitry in ED within the RDoC framework, and also systematically reviews the available literature investigating NIBS as a treatment for ED.

  10. A 128-Channel Extreme Learning Machine-Based Neural Decoder for Brain Machine Interfaces.

    Science.gov (United States)

    Chen, Yi; Yao, Enyi; Basu, Arindam

    2016-06-01

    Currently, state-of-the-art motor intention decoding algorithms in brain-machine interfaces are mostly implemented on a PC and consume significant amount of power. A machine learning coprocessor in 0.35- μm CMOS for the motor intention decoding in the brain-machine interfaces is presented in this paper. Using Extreme Learning Machine algorithm and low-power analog processing, it achieves an energy efficiency of 3.45 pJ/MAC at a classification rate of 50 Hz. The learning in second stage and corresponding digitally stored coefficients are used to increase robustness of the core analog processor. The chip is verified with neural data recorded in monkey finger movements experiment, achieving a decoding accuracy of 99.3% for movement type. The same coprocessor is also used to decode time of movement from asynchronous neural spikes. With time-delayed feature dimension enhancement, the classification accuracy can be increased by 5% with limited number of input channels. Further, a sparsity promoting training scheme enables reduction of number of programmable weights by ≈ 2X.

  11. Effects of transient unilateral functional brain disruption on global neural network status in rats

    Directory of Open Access Journals (Sweden)

    Willem M Otte

    2014-03-01

    Full Text Available Permanent focal brain damage can have critical effects on the function of nearby as well as remote brain regions. However, the effects of transient disturbances on global brain function are largely unknown. Our goal was to develop an experimental in vivo model to map the impact of transient functional brain impairment on large-scale neural networks in the absence of structural damage.We describe a new rat model of transient functional hemispheric disruption using unilateral focal anesthesia by intracarotid pentobarbital injection. The brain’s functional status was assessed with resting-state fMRI (rs-fMRI and EEG. We performed network analysis to identify and quantify highly connected network hubs, i.e. ‘rich-club organization’, in pre- and postbarbital functional networks.Perfusion MRI data demonstrated that the catheterized carotid artery predominantly supplied the ipsilateral hemisphere, allowing for selective hemispheric brain silencing. The prebarbital baseline network displayed strong functional connectivity within and between hemispheres. Following pentobarbital injection, the disrupted hemisphere revealed increased intrahemispheric functional connectivity with concomitant decrease of interhemispheric connectivity. The bilateral functional network was characterized by a strong positive rich-club effect, which was not affected by ipsilateral disruption. Nevertheless, the rich-club value was significantly decreased in the ipsilateral hemisphere and to a lesser extent contralaterally. Loss of interhemispheric EEG synchronization supported the rs-fMRI findings.Our data support the concept that densely connected rich-club regions play a central role in global brain communication, and show that network hub configurations can be significantly affected by focal temporary functional hemispheric disruption without structural neuronal damage. Further studies with this rat model will provide essential additional insights into network

  12. Involvement of Atm and Trp53 in neural cell loss due to Terf2 inactivation during mouse brain development.

    Science.gov (United States)

    Kim, Jusik; Choi, Inseo; Lee, Youngsoo

    2017-11-01

    Maintenance of genomic integrity is one of the critical features for proper neurodevelopment and inhibition of neurological diseases. The signals from both ATM and ATR to TP53 are well-known mechanisms to remove neural cells with DNA damage during neurogenesis. Here we examined the involvement of Atm and Atr in genomic instability due to Terf2 inactivation during mouse brain development. Selective inactivation of Terf2 in neural progenitors induced apoptosis, resulting in a complete loss of the brain structure. This neural loss was rescued partially in both Atm and Trp53 deficiency, but not in an Atr-deficient background in the mouse. Atm inactivation resulted in incomplete brain structures, whereas p53 deficiency led to the formation of multinucleated giant neural cells and the disruption of the brain structure. These giant neural cells disappeared in Lig4 deficiency. These data demonstrate ATM and TP53 are important for the maintenance of telomere homeostasis and the surveillance of telomere dysfunction during neurogenesis.

  13. A survey of American neurologists about brain death: understanding the conceptual basis and diagnostic tests for brain death.

    Science.gov (United States)

    Joffe, Ari R; Anton, Natalie R; Duff, Jonathan P; Decaen, Allan

    2012-02-17

    Neurologists often diagnose brain death (BD) and explain BD to families in the intensive care unit. This study was designed to determine whether neurologists agree with the standard concept of death (irreversible loss of integrative unity of the organism) and understand the state of the brain when BD is diagnosed. A previously validated survey was mailed to a random sample of 500 board-certified neurologists in the United States. Main outcomes were: responses indicating the concept of death that BD fulfills and the empirical state of the brain that would rule out BD. After the second mailing, 218 (44%) surveys were returned. Few (n = 52, 27%; 95% confidence interval (CI), 21%, 34%) responded that BD is death because the organism has lost integrative unity. The most common justification was a higher brain concept (n = 93, 48%; 95% CI, 41%, 55%), suggesting that irreversible loss of consciousness is death. Contrary to the recent President's Council on Bioethics, few (n = 22, 12%; 95% CI, 8%, 17%) responded that the irreversible lack of vital work of an organism is a concept of death that the BD criterion may satisfy. Many responded that certain brain functions remaining are not compatible with a diagnosis of BD, including EEG activity, evoked potential activity, and hypothalamic neuroendocrine function. Many also responded that brain blood flow and lack of brainstem destruction are not compatible with a diagnosis of BD. American neurologists do not have a consistent rationale for accepting BD as death, nor a clear understanding of diagnostic tests for BD.

  14. Performance Enhancement at the Cost of Potential Brain Plasticity: Neural Ramifications of Nootropic Drugs in the Healthy Developing Brain

    Directory of Open Access Journals (Sweden)

    Kimberly R. Urban

    2014-05-01

    Full Text Available Cognitive enhancement is perhaps one of the most intriguing and controversial topics in neuroscience today. Currently, the main classes of drugs used as potential cognitive enhancers include psychostimulants (methylphenidate, amphetamine, but wakefulness-promoting agents (modafinil and glutamate activators (ampakine are also frequently used. Pharmacologically, substances that enhance the components of the memory/learning circuits - dopamine, glutamate (neuronal excitation, and/or norepinephrine - stand to improve brain function in healthy individuals beyond their baseline functioning. In particular, non-medical use of prescription stimulants such as methylphenidate and illicit use of psychostimulants for cognitive enhancement have seen a recent rise among teens and young adults in schools and college campuses. However, this enhancement likely comes with a neuronal, as well as ethical, cost. Altering glutamate function via the use of psychostimulants may impair behavioral flexibility, leading to the development and/or potentiation of addictive behaviors. Furthermore, dopamine and norepinephrine do not display linear effects; instead, their modulation of cognitive and neuronal function maps on an inverted-U curve. Healthy individuals run the risk of pushing themselves beyond optimal levels into hyperdopaminergic and hypernoradrenergic states, thus vitiating the very behaviors they are striving to improve. Finally, recent studies have begun to highlight potential damaging effects of stimulant exposure in healthy juveniles. This review explains how the main classes of cognitive enhancing drugs affect the learning and memory circuits, and highlights the potential risks and concerns in healthy individuals, particularly juveniles and adolescents. We emphasize the performance enhancement at the potential cost of brain plasticity that is associated with the neural ramifications of nootropic drugs in the healthy developing brain.

  15. Performance enhancement at the cost of potential brain plasticity: neural ramifications of nootropic drugs in the healthy developing brain.

    Science.gov (United States)

    Urban, Kimberly R; Gao, Wen-Jun

    2014-01-01

    Cognitive enhancement is perhaps one of the most intriguing and controversial topics in neuroscience today. Currently, the main classes of drugs used as potential cognitive enhancers include psychostimulants (methylphenidate (MPH), amphetamine), but wakefulness-promoting agents (modafinil) and glutamate activators (ampakine) are also frequently used. Pharmacologically, substances that enhance the components of the memory/learning circuits-dopamine, glutamate (neuronal excitation), and/or norepinephrine-stand to improve brain function in healthy individuals beyond their baseline functioning. In particular, non-medical use of prescription stimulants such as MPH and illicit use of psychostimulants for cognitive enhancement have seen a recent rise among teens and young adults in schools and college campuses. However, this enhancement likely comes with a neuronal, as well as ethical, cost. Altering glutamate function via the use of psychostimulants may impair behavioral flexibility, leading to the development and/or potentiation of addictive behaviors. Furthermore, dopamine and norepinephrine do not display linear effects; instead, their modulation of cognitive and neuronal function maps on an inverted-U curve. Healthy individuals run the risk of pushing themselves beyond optimal levels into hyperdopaminergic and hypernoradrenergic states, thus vitiating the very behaviors they are striving to improve. Finally, recent studies have begun to highlight potential damaging effects of stimulant exposure in healthy juveniles. This review explains how the main classes of cognitive enhancing drugs affect the learning and memory circuits, and highlights the potential risks and concerns in healthy individuals, particularly juveniles and adolescents. We emphasize the performance enhancement at the potential cost of brain plasticity that is associated with the neural ramifications of nootropic drugs in the healthy developing brain.

  16. Novel theory of the human brain: information-commutation basis of architecture and principles of operation

    Directory of Open Access Journals (Sweden)

    Bryukhovetskiy AS

    2015-02-01

    Full Text Available Andrey S Bryukhovetskiy Center for Biomedical Technologies, Federal Research and Clinical Center for Specialized Types of Medical Assistance and Medical Technologies of the Federal Medical Biological Agency, NeuroVita Clinic of Interventional and Restorative Neurology and Therapy, Moscow, Russia Abstract: Based on the methodology of the informational approach and research of the genome, proteome, and complete transcriptome profiles of different cells in the nervous tissue of the human brain, the author proposes a new theory of information-commutation organization and architecture of the human brain which is an alternative to the conventional systemic connective morphofunctional paradigm of the brain framework. Informational principles of brain operation are defined: the modular principle, holographic principle, principle of systematicity of vertical commutative connection and complexity of horizontal commutative connection, regulatory principle, relay principle, modulation principle, “illumination” principle, principle of personalized memory and intellect, and principle of low energy consumption. The author demonstrates that the cortex functions only as a switchboard and router of information, while information is processed outside the nervous tissue of the brain in the intermeningeal space. The main structural element of information-commutation in the brain is not the neuron, but information-commutation modules that are subdivided into receiver modules, transmitter modules, and subscriber modules, forming a vertical architecture of nervous tissue in the brain as information lines and information channels, and a horizontal architecture as central, intermediate, and peripheral information-commutation platforms. Information in information-commutation modules is transferred by means of the carriers that are characteristic to the specific information level from inductome to genome, transcriptome, proteome, metabolome, secretome, and magnetome

  17. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  18. Brain Immune Interactions as the Basis of Gulf War Illness: Gulf War Illness Consortium (GWIC)

    Science.gov (United States)

    2016-10-01

    indication that prior stress hormone exposure (CORT) changes the permeability of PB to the brain (see AChE activity). Furthermore, using the brain...response requiring naming of ink color and inhibiting discordant color-names; measures fronto-executive, selective response and inhibition. Total

  19. Deep convolutional neural networks for multi-modality isointense infant brain image segmentation.

    Science.gov (United States)

    Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

    2015-03-01

    The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6-8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multi-modality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. Copyright © 2014 Elsevier Inc. All rights reserved.

  20. Convolutional neural networks for P300 detection with application to brain-computer interfaces.

    Science.gov (United States)

    Cecotti, Hubert; Gräser, Axel

    2011-03-01

    A Brain-Computer Interface (BCI) is a specific type of human-computer interface that enables the direct communication between human and computers by analyzing brain measurements. Oddball paradigms are used in BCI to generate event-related potentials (ERPs), like the P300 wave, on targets selected by the user. A P300 speller is based on this principle, where the detection of P300 waves allows the user to write characters. The P300 speller is composed of two classification problems. The first classification is to detect the presence of a P300 in the electroencephalogram (EEG). The second one corresponds to the combination of different P300 responses for determining the right character to spell. A new method for the detection of P300 waves is presented. This model is based on a convolutional neural network (CNN). The topology of the network is adapted to the detection of P300 waves in the time domain. Seven classifiers based on the CNN are proposed: four single classifiers with different features set and three multiclassifiers. These models are tested and compared on the Data set II of the third BCI competition. The best result is obtained with a multiclassifier solution with a recognition rate of 95.5 percent, without channel selection before the classification. The proposed approach provides also a new way for analyzing brain activities due to the receptive field of the CNN models.

  1. Neural correlates of apathy revealed by lesion mapping in participants with traumatic brain injuries.

    Science.gov (United States)

    Knutson, Kristine M; Monte, Olga Dal; Raymont, Vanessa; Wassermann, Eric M; Krueger, Frank; Grafman, Jordan

    2014-03-01

    Apathy, common in neurological disorders, is defined as disinterest and loss of motivation, with a reduction in self-initiated activity. Research in diseased populations has shown that apathy is associated with variations in the volume of brain regions such as the anterior cingulate and the frontal lobes. The goal of this study was to determine the neural signatures of apathy in people with penetrating traumatic brain injuries (pTBIs), as to our knowledge, these have not been studied in this sample. We studied 176 male Vietnam War veterans with pTBIs using voxel-based lesion-symptom mapping (VLSM) and apathy scores from the UCLA Neuropsychiatric Inventory (NPI), a structured inventory of symptoms completed by a caregiver. Our results revealed that increased apathy symptoms were associated with brain damage in limbic and cortical areas of the left hemisphere including the anterior cingulate, inferior, middle, and superior frontal regions, insula, and supplementary motor area. Our results are consistent with the literature, and extend them to people with focal pTBI. Apathy is a significant symptom since it can reduce participation of the patient in family and other social interactions, and diminish affective decision-making. Copyright © 2013 Wiley Periodicals, Inc.

  2. Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Rahib H. Abiyev

    2016-01-01

    Full Text Available The design of brain-computer interface for the wheelchair for physically disabled people is presented. The design of the proposed system is based on receiving, processing, and classification of the electroencephalographic (EEG signals and then performing the control of the wheelchair. The number of experimental measurements of brain activity has been done using human control commands of the wheelchair. Based on the mental activity of the user and the control commands of the wheelchair, the design of classification system based on fuzzy neural networks (FNN is considered. The design of FNN based algorithm is used for brain-actuated control. The training data is used to design the system and then test data is applied to measure the performance of the control system. The control of the wheelchair is performed under real conditions using direction and speed control commands of the wheelchair. The approach used in the paper allows reducing the probability of misclassification and improving the control accuracy of the wheelchair.

  3. Vascular Basis for Brain Degeneration: Faltering Controls and Risk Factors for Dementia

    Science.gov (United States)

    Kalaria, Raj N.

    2010-01-01

    The integrity of the vascular system is essential for the efficient functioning of the brain. Ageing related structural and functional disturbances in the macro- or microcirculation of the brain make it vulnerable to cognitive dysfunction leading to brain degeneration and dementing illness. Several faltering controls including impairment in autoregulation, neurovascular coupling, blood-brain barrier leakage, decreased cerebrospinal fluid and reduced vascular tone appear responsible for variable degrees of neurodegeneration in old age. There is ample evidence that vascular risk factors are also linked to neurodegenerative processes preceding cognitive decline and dementia. Age is the strongest risk factor for brain degeneration whether it results from vascular or neurodegenerative mechanisms or both. However, several modifiable risks such as cardiovascular disease, hypertension, dyslipidaemia, diabetes and obesity enhance the rate of cognitive decline and increase the risk of Alzheimer’s disease in particular. The ultimate accumulation of brain pathological lesions may be modified by genetic influences such as apoliopoprotein E ε4 allele and the environment. Lifestyle measures that maintain or improve cardiovascular health including consumption of healthy diets, moderate use of alcohol and implementing regular physical exercise are important factors for brain protection. PMID:21091952

  4. Fat1 interacts with Fat4 to regulate neural tube closure, neural progenitor proliferation and apical constriction during mouse brain development.

    Science.gov (United States)

    Badouel, Caroline; Zander, Mark A; Liscio, Nicole; Bagherie-Lachidan, Mazdak; Sopko, Richelle; Coyaud, Etienne; Raught, Brian; Miller, Freda D; McNeill, Helen

    2015-08-15

    Mammalian brain development requires coordination between neural precursor proliferation, differentiation and cellular organization to create the intricate neuronal networks of the adult brain. Here, we examined the role of the atypical cadherins Fat1 and Fat4 in this process. We show that mutation of Fat1 in mouse embryos causes defects in cranial neural tube closure, accompanied by an increase in the proliferation of cortical precursors and altered apical junctions, with perturbations in apical constriction and actin accumulation. Similarly, knockdown of Fat1 in cortical precursors by in utero electroporation leads to overproliferation of radial glial precursors. Fat1 interacts genetically with the related cadherin Fat4 to regulate these processes. Proteomic analysis reveals that Fat1 and Fat4 bind different sets of actin-regulating and junctional proteins. In vitro data suggest that Fat1 and Fat4 form cis-heterodimers, providing a mechanism for bringing together their diverse interactors. We propose a model in which Fat1 and Fat4 binding coordinates distinct pathways at apical junctions to regulate neural progenitor proliferation, neural tube closure and apical constriction. © 2015. Published by The Company of Biologists Ltd.

  5. Acute stress evokes sexually dimorphic, stressor-specific patterns of neural activation across multiple limbic brain regions in adult rats.

    Science.gov (United States)

    Sood, Ankit; Chaudhari, Karina; Vaidya, Vidita A

    2018-03-01

    Stress enhances the risk for psychiatric disorders such as anxiety and depression. Stress responses vary across sex and may underlie the heightened vulnerability to psychopathology in females. Here, we examined the influence of acute immobilization stress (AIS) and a two-day short-term forced swim stress (FS) on neural activation in multiple cortical and subcortical brain regions, implicated as targets of stress and in the regulation of neuroendocrine stress responses, in male and female rats using Fos as a neural activity marker. AIS evoked a sex-dependent pattern of neural activation within the cingulate and infralimbic subdivisions of the medial prefrontal cortex (mPFC), lateral septum (LS), habenula, and hippocampal subfields. The degree of neural activation in the mPFC, LS, and habenula was higher in males. Female rats exhibited reduced Fos positive cell numbers in the dentate gyrus hippocampal subfield, an effect not observed in males. We addressed whether the sexually dimorphic neural activation pattern noted following AIS was also observed with the short-term stress of FS. In the paraventricular nucleus of the hypothalamus and the amygdala, FS similar to AIS resulted in robust increases in neural activation in both sexes. The pattern of neural activation evoked by FS was distinct across sexes, with a heightened neural activation noted in the prelimbic mPFC subdivision and hippocampal subfields in females and differed from the pattern noted with AIS. This indicates that the sex differences in neural activation patterns observed within stress-responsive brain regions are dependent on the nature of stressor experience.

  6. The neural basis of emotions varies over time: different regions go with onset- and offset-bound processes underlying emotion intensity.

    Science.gov (United States)

    Résibois, Maxime; Verduyn, Philippe; Delaveau, Pauline; Rotgé, Jean-Yves; Kuppens, Peter; Van Mechelen, Iven; Fossati, Philippe

    2017-08-01

    According to theories of emotion dynamics, emotions unfold across two phases in which different types of processes come to the fore: emotion onset and emotion offset. Differences in onset-bound processes are reflected by the degree of explosiveness or steepness of the response at onset, and differences in offset-bound processes by the degree of accumulation or intensification of the subsequent response. Whether onset- and offset-bound processes have distinctive neural correlates and, hence, whether the neural basis of emotions varies over time, still remains unknown. In the present fMRI study, we address this question using a recently developed paradigm that allows to disentangle explosiveness and accumulation. Thirty-one participants were exposed to neutral and negative social feedback, and asked to reflect on its contents. Emotional intensity while reading and thinking about the feedback was measured with an intensity profile tracking approach. Using non-negative matrix factorization, the resulting profile data were decomposed in explosiveness and accumulation components, which were subsequently entered as continuous regressors of the BOLD response. It was found that the neural basis of emotion intensity shifts as emotions unfold over time with emotion explosiveness and accumulation having distinctive neural correlates. © The Author (2017). Published by Oxford University Press.

  7. Advanced biomaterial strategies to transplant preformed micro-tissue engineered neural networks into the brain

    Science.gov (United States)

    Harris, J. P.; Struzyna, L. A.; Murphy, P. L.; Adewole, D. O.; Kuo, E.; Cullen, D. K.

    2016-02-01

    Objective. Connectome disruption is a hallmark of many neurological diseases and trauma with no current strategies to restore lost long-distance axonal pathways in the brain. We are creating transplantable micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of embedded neurons and long axonal tracts to integrate with the nervous system to physically reconstitute lost axonal pathways. Approach. We advanced micro-tissue engineering techniques to generate micro-TENNs consisting of discrete populations of mature primary cerebral cortical neurons spanned by long axonal fascicles encased in miniature hydrogel micro-columns. Further, we improved the biomaterial encasement scheme by adding a thin layer of low viscosity carboxymethylcellulose (CMC) to enable needle-less insertion and rapid softening for mechanical similarity with brain tissue. Main results. The engineered architecture of cortical micro-TENNs facilitated robust neuronal viability and axonal cytoarchitecture to at least 22 days in vitro. Micro-TENNs displayed discrete neuronal populations spanned by long axonal fasciculation throughout the core, thus mimicking the general systems-level anatomy of gray matter—white matter in the brain. Additionally, micro-columns with thin CMC-coating upon mild dehydration were able to withstand a force of 893 ± 457 mN before buckling, whereas a solid agarose cylinder of similar dimensions was predicted to withstand less than 150 μN of force. This thin CMC coating increased the stiffness by three orders of magnitude, enabling needle-less insertion into brain while significantly reducing the footprint of previous needle-based delivery methods to minimize insertion trauma. Significance. Our novel micro-TENNs are the first strategy designed for minimally invasive implantation to facilitate nervous system repair by simultaneously providing neuronal replacement and physical reconstruction of long-distance axon pathways in the brain

  8. Neural tension technique is no different from random passive movements in reducing spasticity in patients with traumatic brain injury

    DEFF Research Database (Denmark)

    Lorentzen, Jakob; Nielsen, Dorthe; Holm, Karl

    2012-01-01

    Purpose: Neural tension technique (NTT) is a therapy believed to reduce spasticity and to increase range of motion (ROM). This study compared the ability of NTT and random passive movements (RPMs) to reduce spasticity in the knee flexors in 10 spastic patients with brain injury. Methods: An RCT...

  9. A Smarter Brain Is Associated with Stronger Neural Interaction in Healthy Young Females: A Resting EEG Coherence Study

    Science.gov (United States)

    Lee, Tien-Wen; Wu, Yu-Te; Yu, Younger W.-Y.; Wu, Hung-Chi; Chen, Tai-Jui

    2012-01-01

    General intelligence, the "g" factor, is a major issue in psychology and neuroscience. However, the neural mechanism of the "g" factor is still not clear. It is suggested that the "g" factor should be non-modular (a property across the brain) and show good colinearity with various cognitive tests. This study examines…

  10. Prediction of Welded Joint Strength in Plasma Arc Welding: A Comparative Study Using Back-Propagation and Radial Basis Neural Networks

    Science.gov (United States)

    Srinivas, Kadivendi; Vundavilli, Pandu R.; Manzoor Hussain, M.; Saiteja, M.

    2016-09-01

    Welding input parameters such as current, gas flow rate and torch angle play a significant role in determination of qualitative mechanical properties of weld joint. Traditionally, it is necessary to determine the weld input parameters for every new welded product to obtain a quality weld joint which is time consuming. In the present work, the effect of plasma arc welding parameters on mild steel was studied using a neural network approach. To obtain a response equation that governs the input-output relationships, conventional regression analysis was also performed. The experimental data was constructed based on Taguchi design and the training data required for neural networks were randomly generated, by varying the input variables within their respective ranges. The responses were calculated for each combination of input variables by using the response equations obtained through the conventional regression analysis. The performances in Levenberg-Marquardt back propagation neural network and radial basis neural network (RBNN) were compared on various randomly generated test cases, which are different from the training cases. From the results, it is interesting to note that for the above said test cases RBNN analysis gave improved training results compared to that of feed forward back propagation neural network analysis. Also, RBNN analysis proved a pattern of increasing performance as the data points moved away from the initial input values.

  11. MHC class I protein is expressed by neurons and neural progenitors in mid-gestation mouse brain.

    Science.gov (United States)

    Chacon, Marcelo A; Boulanger, Lisa M

    2013-01-01

    Proteins of the major histocompatibility complex class I (MHCI) are known for their role in the vertebrate adaptive immune response, and are required for normal postnatal brain development and plasticity. However, it remains unknown if MHCI proteins are present in the mammalian brain before birth. Here, we show that MHCI proteins are widely expressed in the developing mouse central nervous system at mid-gestation (E9.5-10.5). MHCI is strongly expressed in several regions of the prenatal brain, including the neuroepithelium and olfactory placode. MHCI is expressed by neural progenitors at these ages, as identified by co-expression in cells positive for neuron-specific class III β-tubulin (Tuj1) or for Pax6, a marker of neural progenitors in the dorsal neuroepithelium. MHCI is also co-expressed with nestin, a marker of neural stem/progenitor cells, in olfactory placode, but the co-localization is less extensive in other regions. MHCI is detected in the small population of post-mitotic neurons that are present at this early stage of brain development, as identified by co-expression in cells positive for neuronal microtubule-associated protein-2 (MAP2). Thus MHCI protein is expressed during the earliest stages of neuronal differentiation in the mammalian brain. MHCI expression in neurons and neural progenitors at mid-gestation, prior to the maturation of the adaptive immune system, is consistent with MHCI performing non-immune functions in prenatal brain development. These results raise the possibility that disruption of the levels and/or patterns of MHCI expression in the prenatal brain could contribute to the pathogenesis of neurodevelopmental disorders. Copyright © 2012 Elsevier Inc. All rights reserved.

  12. Circumventricular organs: a novel site of neural stem cells in the adult brain.

    Science.gov (United States)

    Bennett, Lori; Yang, Ming; Enikolopov, Grigori; Iacovitti, Lorraine

    2009-07-01

    Neurogenesis in the adult mammalian nervous system is now well established in the subventricular zone of the anterolateral ventricle and subgranular zone of the hippocampus. In these regions, neurons are thought to arise from neural stem cells, identified by their expression of specific intermediate filament proteins (nestin, vimentin, GFAP) and transcription factors (Sox2). In the present study, we show that in adult rat and mouse, the circumventricular organs (CVOs) are rich in nestin+, GFAP+, vimentin+ cells which express Sox2 and the cell cycle-regulating protein Ki67. In culture, these cells proliferate as neurospheres and express neuronal (doublecortin+, beta-tubulin III+) and glial (S100beta+, GFAP+, RIP+) phenotypic traits. Further, our in vivo studies using bromodeoxyuridine show that CVO cells proliferate and undergo constitutive neurogenesis and gliogenesis. These findings suggest that CVOs may constitute a heretofore unknown source of stem/progenitor cells, capable of giving rise to new neurons and/or glia in the adult brain.

  13. In silico log P prediction for a large data set with support vector machines, radial basis neural networks and multiple linear regression.

    Science.gov (United States)

    Chen, Hai-Feng

    2009-08-01

    Oil/water partition coefficient (log P) is one of the key points for lead compound to be drug. In silico log P models based solely on chemical structures have become an important part of modern drug discovery. Here, we report support vector machines, radial basis function neural networks, and multiple linear regression methods to investigate the correlation between partition coefficient and physico-chemical descriptors for a large data set of compounds. The correlation coefficient r(2) between experimental and predicted log P for training and test sets by support vector machines, radial basis function neural networks, and multiple linear regression is 0.92, 0.90, and 0.88, respectively. The results show that non-linear support vector machines derives statistical models that have better prediction ability than those of radial basis function neural networks and multiple linear regression methods. This indicates that support vector machines can be used as an alternative modeling tool for quantitative structure-property/activity relationships studies.

  14. Long-term neural recordings using MEMS based moveable microelectrodes in the brain

    Directory of Open Access Journals (Sweden)

    Nathan Jackson

    2010-06-01

    Full Text Available One of the critical requirements of the emerging class of neural prosthetic devices is to maintain good quality neural recordings over long time periods. We report here a novel (Micro-ElectroMechanical Systems based technology that can move microelectrodes in the event of deterioration in neural signal to sample a new set of neurons. Microscale electro-thermal actuators are used to controllably move microelectrodes post-implantation in steps of approximately 9 µm. In this study, a total of 12 moveable microelectrode chips were individually implanted in adult rats. Two of the 12 moveable microelectrode chips were not moved over a period of 3 weeks and were treated as control experiments. During the first three weeks of implantation, moving the microelectrodes led to an improvement in the average SNR from 14.61 ± 5.21 dB before movement to 18.13 ± 4.99 dB after movement across all microelectrodes and all days. However, the average RMS values of noise amplitudes were similar at 2.98 ± 1.22 µV and 3.01 ± 1.16 µV before and after microelectrode movement. Beyond three weeks, the primary observed failure mode was biological rejection of the PMMA (dental cement based skull mount resulting in the device loosening and eventually falling from the skull. Additionally, the average SNR for functioning devices beyond three weeks was 11.88 ± 2.02 dB before microelectrode movement and was significantly different (p<0.01 from the average SNR of 13.34 ± 0.919 dB after movement. The results of this study demonstrate that MEMS based technologies can move microelectrodes in rodent brains in long-term experiments resulting in improvements in signal quality. Further improvements in packaging and surgical techniques will potentially enable movable microelectrodes to record cortical neuronal activity in chronic experiments.

  15. Brain-Immune Interactions as the Basis of Gulf War Illness: Gulf War Illness Consortium (GWIC)

    Science.gov (United States)

    2014-10-01

    related to proinflammatory cytokine signaling in the CNS in fibromyalgia and CFS and is often referred to as central sensitization (Arnett et al...formation of spatial memory (hippocampal dependent) using the Morris water maze and for contextual fear memory after fear conditioning. Anxiety was...neural activity with symptom severity; i.e., fatigue, pain, disability, depression, and anxiety . In addition, Drs. Sullivan, Baas, Klimas, Fields

  16. Multipotent neural stem cells generate glial cells of the central complex through transit amplifying intermediate progenitors in Drosophila brain development.

    Science.gov (United States)

    Viktorin, Gudrun; Riebli, Nadia; Popkova, Anna; Giangrande, Angela; Reichert, Heinrich

    2011-08-15

    The neural stem cells that give rise to the neural lineages of the brain can generate their progeny directly or through transit amplifying intermediate neural progenitor cells (INPs). The INP-producing neural stem cells in Drosophila are called type II neuroblasts, and their neural progeny innervate the central complex, a prominent integrative brain center. Here we use genetic lineage tracing and clonal analysis to show that the INPs of these type II neuroblast lineages give rise to glial cells as well as neurons during postembryonic brain development. Our data indicate that two main types of INP lineages are generated, namely mixed neuronal/glial lineages and neuronal lineages. Genetic loss-of-function and gain-of-function experiments show that the gcm gene is necessary and sufficient for gliogenesis in these lineages. The INP-derived glial cells, like the INP-derived neuronal cells, make major contributions to the central complex. In postembryonic development, these INP-derived glial cells surround the entire developing central complex neuropile, and once the major compartments of the central complex are formed, they also delimit each of these compartments. During this process, the number of these glial cells in the central complex is increased markedly through local proliferation based on glial cell mitosis. Taken together, these findings uncover a novel and complex form of neurogliogenesis in Drosophila involving transit amplifying intermediate progenitors. Moreover, they indicate that type II neuroblasts are remarkably multipotent neural stem cells that can generate both the neuronal and the glial progeny that make major contributions to one and the same complex brain structure. Copyright © 2011 Elsevier Inc. All rights reserved.

  17. Co-speech gestures influence neural activity in brain regions associated with processing semantic information.

    Science.gov (United States)

    Dick, Anthony Steven; Goldin-Meadow, Susan; Hasson, Uri; Skipper, Jeremy I; Small, Steven L

    2009-11-01

    Everyday communication is accompanied by visual information from several sources, including co-speech gestures, which provide semantic information listeners use to help disambiguate the speaker's message. Using fMRI, we examined how gestures influence neural activity in brain regions associated with processing semantic information. The BOLD response was recorded while participants listened to stories under three audiovisual conditions and one auditory-only (speech alone) condition. In the first audiovisual condition, the storyteller produced gestures that naturally accompany speech. In the second, the storyteller made semantically unrelated hand movements. In the third, the storyteller kept her hands still. In addition to inferior parietal and posterior superior and middle temporal regions, bilateral posterior superior temporal sulcus and left anterior inferior frontal gyrus responded more strongly to speech when it was further accompanied by gesture, regardless of the semantic relation to speech. However, the right inferior frontal gyrus was sensitive to the semantic import of the hand movements, demonstrating more activity when hand movements were semantically unrelated to the accompanying speech. These findings show that perceiving hand movements during speech modulates the distributed pattern of neural activation involved in both biological motion perception and discourse comprehension, suggesting listeners attempt to find meaning, not only in the words speakers produce, but also in the hand movements that accompany speech.

  18. Ensemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Hossein Bashashati

    2017-07-01

    Full Text Available Classification of EEG signals in self-paced Brain Computer Interfaces (BCI is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing the mental task, the user’s brain goes through several well-defined internal state changes. Applying appropriate classifiers that can capture these state changes and exploit the temporal correlation in EEG data can enhance the performance of the BCI. In this paper, we propose an ensemble learning approach for self-paced BCIs. We use Bayesian optimization to train several different classifiers on different parts of the BCI hyper- parameter space. We call each of these classifiers Neural Network Conditional Random Field (NNCRF. NNCRF is a combination of a neural network and conditional random field (CRF. As in the standard CRF, NNCRF is able to model the correlation between adjacent EEG samples. However, NNCRF can also model the nonlinear dependencies between the input and the output, which makes it more powerful than the standard CRF. We compare the performance of our algorithm to those of three popular sequence labeling algorithms (Hidden Markov Models, Hidden Markov Support Vector Machines and CRF, and to two classical classifiers (Logistic Regression and Support Vector Machines. The classifiers are compared for the two cases: when the ensemble learning approach is not used and when it is. The data used in our studies are those from the BCI competition IV and the SM2 dataset. We show that our algorithm is considerably superior to the other approaches in terms of the Area Under the Curve (AUC of the BCI system.

  19. Cortical geometry as a determinant of brain activity eigenmodes: Neural field analysis

    Science.gov (United States)

    Gabay, Natasha C.; Robinson, P. A.

    2017-09-01

    Perturbation analysis of neural field theory is used to derive eigenmodes of neural activity on a cortical hemisphere, which have previously been calculated numerically and found to be close analogs of spherical harmonics, despite heavy cortical folding. The present perturbation method treats cortical folding as a first-order perturbation from a spherical geometry. The first nine spatial eigenmodes on a population-averaged cortical hemisphere are derived and compared with previous numerical solutions. These eigenmodes contribute most to brain activity patterns such as those seen in electroencephalography and functional magnetic resonance imaging. The eigenvalues of these eigenmodes are found to agree with the previous numerical solutions to within their uncertainties. Also in agreement with the previous numerics, all eigenmodes are found to closely resemble spherical harmonics. The first seven eigenmodes exhibit a one-to-one correspondence with their numerical counterparts, with overlaps that are close to unity. The next two eigenmodes overlap the corresponding pair of numerical eigenmodes, having been rotated within the subspace spanned by that pair, likely due to second-order effects. The spatial orientations of the eigenmodes are found to be fixed by gross cortical shape rather than finer-scale cortical properties, which is consistent with the observed intersubject consistency of functional connectivity patterns. However, the eigenvalues depend more sensitively on finer-scale cortical structure, implying that the eigenfrequencies and consequent dynamical properties of functional connectivity depend more strongly on details of individual cortical folding. Overall, these results imply that well-established tools from perturbation theory and spherical harmonic analysis can be used to calculate the main properties and dynamics of low-order brain eigenmodes.

  20. Harmonic Training and the formation of pitch representation in a neural network model of the auditory brain

    Directory of Open Access Journals (Sweden)

    Nasir eAhmad

    2016-03-01

    Full Text Available Attempting to explain the perceptual qualities of pitch has proven to be, and remains, a difficult problem. The wide range of sounds which illicit pitch and a lack of agreement across neurophysiological studies on how pitch is encoded by the brain have made this attempt more difficult. In describing the potential neural mechanisms by which pitch may be processed, a number of neural networks have been proposed and implemented. However, no unsupervised neural networks with biologically accurate cochlear inputs have yet been demonstrated. This paper proposes a simplified system in which pitch representing neurons are easily produced under a highly biological setting. Purely unsupervised regimes of neural network learning are implemented and these prove to be sufficient in identifying the pitch of sounds with a variety of spectral profiles, including missing fundamental sounds.

  1. Biologically Inspired Modular Neural Networks

    OpenAIRE

    Azam, Farooq

    2000-01-01

    This dissertation explores the modular learning in artificial neural networks that mainly driven by the inspiration from the neurobiological basis of the human learning. The presented modularization approaches to the neural network design and learning are inspired by the engineering, complexity, psychological and neurobiological aspects. The main theme of this dissertation is to explore the organization and functioning of the brain to discover new structural and learning ...

  2. A radial basis function neural network approach to determine the survival of Listeria monocytogenes in Katiki, a traditional Greek soft cheese.

    Science.gov (United States)

    Panagou, Efstathios Z

    2008-04-01

    A radial basis function neural network was developed to determine the kinetic behavior of Listeria monocytogenes in Katiki, a traditional white acid-curd soft spreadable cheese. The applicability of the neural network approach was compared with the reparameterized Gompertz, the modified Weibull, and the Geeraerd primary models. Model performance was assessed with the root mean square error of the residuals of the model (RMSE), the regression coefficient (R2), and the F test. Commercially prepared cheese samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 10(6) CFU g(-1) and stored at 5, 10, 15, and 20 degrees C for 40 days. At each storage temperature, a pathogen viability loss profile was evident and included a shoulder, a log-linear phase, and a tailing phase. The developed neural network described the survival of L. monocytogenes equally well or slightly better than did the three primary models. The performance indices for the training subset of the network were R2 = 0.993 and RMSE = 0.214. The relevant mean values for all storage temperatures were R2 = 0.981, 0.986, and 0.985 and RMSE = 0.344, 0.256, and 0.262 for the reparameterized Gompertz, modified Weibull, and Geeraerd models, respectively. The results of the F test indicated that none of the primary models were able to describe accurately the survival of the pathogen at 5 degrees C, whereas with the neural network all fvalues were significant. The neural network and primary models all were validated under constant temperature storage conditions (12 and 17 degrees C). First or second order polynomial models were used to relate the inactivation parameters to temperature, whereas the neural network was used a one-step modeling approach. Comparison of the prediction capability was based on bias and accuracy factors and on the goodness-of-fit index. The prediction performance of the neural network approach was equal to that of the primary

  3. Fatigue in multiple sclerosis: neural correlates and the role of non-invasive brain stimulation

    Directory of Open Access Journals (Sweden)

    Moussa A. Chalah

    2015-11-01

    Full Text Available Multiple sclerosis (MS is a chronic progressive inflammatory disease of the central nervous system and the major cause of non-traumatic disability in young adults. Fatigue is a frequent symptom reported by the majority of MS patients during their disease course and drastically af-fects their quality of life. Despite its significant prevalence and impact, the underlying patho-physiological mechanisms are not well elucidated. MS fatigue is still considered the result of multifactorial and complex constellations, and is commonly classified into primary fatigue related to the pathological changes of the disease itself, and secondary fatigue attributed to mimicking symptoms, comorbid sleep and mood disorders, and medications side effects. Data from neuroimaging, neurophysiology, neuroendocrine and neuroimmune studies have raised hypotheses regarding the origin of this symptom, some of which have succeeded in identifying an association between MS fatigue and structural or functional abnormalities within various brain networks. Hence, the aim of this work is to reappraise the neural correlates of MS fatigue and to discuss the rationale for the emergent use of noninvasive brain stimulation (NIBS techniques as potential treatments. This will include a presentation of the various NIBS modalities and a proposition of their potential mechanisms of action in this context. Specific issues related to the value of transcranial direct current stimulation will be addressed.

  4. Two neural streams, one voice: pathways for theme and variation in the songbird brain.

    Science.gov (United States)

    Bertram, R; Daou, A; Hyson, R L; Johnson, F; Wu, W

    2014-09-26

    Birdsong offers a unique model system to understand how a developing brain - once given a set of purely acoustic targets - teaches itself the vocal-tract gestures necessary to imitate those sounds. Like human infants, to juvenile male zebra finches (Taeniopygia guttata) falls the burden of initiating the vocal-motor learning of adult sounds. In both species, adult caregivers provide only a set of sounds to be imitated, with little or no information about the vocal-tract gestures used to produce the sounds. Here, we focus on the central control of birdsong and review the recent discovery that zebra finch song is under dual premotor control. Distinct forebrain pathways for structured (theme) and unstructured (variation) singing not only raise new questions about mechanisms of sensory-motor integration, but also provide a fascinating new research opportunity. A cortical locus for a motor memory of the learned song is now firmly established, meaning that anatomical, physiological, and computational approaches are poised to reveal the neural mechanisms used by the brain to compose the songs of birds. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

  5. Emotion Regulatory Brain Function and SSRI Treatment in PTSD: Neural Correlates and Predictors of Change.

    Science.gov (United States)

    MacNamara, Annmarie; Rabinak, Christine A; Kennedy, Amy E; Fitzgerald, Daniel A; Liberzon, Israel; Stein, Murray B; Phan, K Luan

    2016-01-01

    Posttraumatic stress disorder (PTSD)-a chronic, debilitating condition, broadly characterized by emotion dysregulation-is prevalent among US military personnel who have returned from Operations Enduring Freedom (OEF) and Iraqi Freedom (OIF). Selective serotonin reuptake inhibitors (SSRIs) are a first-line treatment for PTSD, but treatment mechanisms are unknown and patient response varies. SSRIs may exert their effects by remediating emotion regulatory brain activity and individual differences in patient response might be explained, in part, by pre-treatment differences in neural systems supporting the downregulation of negative affect. Thirty-four OEF/OIF veterans, 17 with PTSD and 17 without PTSD underwent 2 functional magnetic resonance imaging scans 12 weeks apart. At each scan, they performed an emotion regulation task; in the interim, veterans with PTSD were treated with the SSRI, paroxetine. SSRI treatment increased activation in both the left dorsolateral prefrontal cortex (PFC) and supplementary motor area (SMA) during emotion regulation, although only change in the SMA over time occurred in veterans with PTSD and not those without PTSD. Less activation of the right ventrolateral PFC/inferior frontal gyrus during pre-treatment emotion regulation was associated with greater reduction in PTSD symptoms with SSRI treatment, irrespective of pre-treatment severity. Patients with the least recruitment of prefrontal emotion regulatory brain regions may benefit most from treatment with SSRIs, which appear to augment activity in these regions.

  6. Neural Contributions to Muscle Fatigue: From the Brain to the Muscle and Back Again.

    Science.gov (United States)

    Taylor, Janet L; Amann, Markus; Duchateau, Jacques; Meeusen, Romain; Rice, Charles L

    2016-11-01

    : During exercise, there is a progressive reduction in the ability to produce muscle force. Processes within the nervous system as well as within the muscles contribute to this fatigue. In addition to impaired function of the motor system, sensations associated with fatigue and impairment of homeostasis can contribute to the impairment of performance during exercise. This review discusses some of the neural changes that accompany exercise and the development of fatigue. The role of brain monoaminergic neurotransmitter systems in whole-body endurance performance is discussed, particularly with regard to exercise in hot environments. Next, fatigue-related alterations in the neuromuscular pathway are discussed in terms of changes in motor unit firing, motoneuron excitability, and motor cortical excitability. These changes have mostly been investigated during single-limb isometric contractions. Finally, the small-diameter muscle afferents that increase firing with exercise and fatigue are discussed. These afferents have roles in cardiovascular and respiratory responses to exercise, and in the impairment of exercise performance through interaction with the motor pathway, as well as in providing sensations of muscle discomfort. Thus, changes at all levels of the nervous system, including the brain, spinal cord, motor output, sensory input, and autonomic function, occur during exercise and fatigue. The mix of influences and the importance of their contribution vary with the type of exercise being performed.

  7. Automatic Segmentation of MR Brain Images With a Convolutional Neural Network.

    Science.gov (United States)

    Moeskops, Pim; Viergever, Max A; Mendrik, Adrienne M; de Vries, Linda S; Benders, Manon J N L; Isgum, Ivana

    2016-05-01

    Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue classes using a convolutional neural network. To ensure that the method obtains accurate segmentation details as well as spatial consistency, the network uses multiple patch sizes and multiple convolution kernel sizes to acquire multi-scale information about each voxel. The method is not dependent on explicit features, but learns to recognise the information that is important for the classification based on training data. The method requires a single anatomical MR image only. The segmentation method is applied to five different data sets: coronal T2-weighted images of preterm infants acquired at 30 weeks postmenstrual age (PMA) and 40 weeks PMA, axial T2-weighted images of preterm infants acquired at 40 weeks PMA, axial T1-weighted images of ageing adults acquired at an average age of 70 years, and T1-weighted images of young adults acquired at an average age of 23 years. The method obtained the following average Dice coefficients over all segmented tissue classes for each data set, respectively: 0.87, 0.82, 0.84, 0.86, and 0.91. The results demonstrate that the method obtains accurate segmentations in all five sets, and hence demonstrates its robustness to differences in age and acquisition protocol.

  8. Brain Basics

    Science.gov (United States)

    ... Events About Us Home > Health & Education > Educational Resources Brain Basics Introduction The Growing Brain The Working Brain ... to mental disorders, such as depression. The Growing Brain Inside the Brain: Neurons & Neural Circuits Neurons are ...

  9. Brain Basics

    Medline Plus

    Full Text Available ... Events About Us Home > Health & Education > Educational Resources Brain Basics Introduction The Growing Brain The Working Brain ... to mental disorders, such as depression. The Growing Brain Inside the Brain: Neurons & Neural Circuits Neurons are ...

  10. Brain-Immune Interactions as the Basis of Gulf War Illness: Consortium Development

    Science.gov (United States)

    2012-12-01

    fibromyalgia and CFS and is often referred to as central sensitization (Arnett, 2012). Recent studies of GW veterans with chronic pain have also...Barth DS (2012). Acute neuroimmune modulation attenuates the development of anxiety - like freezing behavior in an animal model of traumatic brain

  11. The Cognitive Basis for Sentence Planning Difficulties in Discourse after Traumatic Brain Injury

    Science.gov (United States)

    Peach, Richard K.

    2013-01-01

    Purpose: Analyses of language production of individuals with traumatic brain injury (TBI) place increasing emphasis on microlinguistic (i.e., within-sentence) patterns. It is unknown whether the observed problems involve implementation of well-formed sentence frames or represent a fundamental linguistic disturbance in computing sentence structure.…

  12. Genetic basis of brain size evolution in cetaceans: insights from adaptive evolution of seven primary microcephaly (MCPH) genes.

    Science.gov (United States)

    Xu, Shixia; Sun, Xiaohui; Niu, Xu; Zhang, Zepeng; Tian, Ran; Ren, Wenhua; Zhou, Kaiya; Yang, Guang

    2017-08-29

    Cetacean brain size expansion is an enigmatic event in mammalian evolution, yet its genetic basis remains poorly explored. Here, all exons of the seven primary microcephaly (MCPH) genes that play key roles in size regulation during brain development were investigated in representative cetacean lineages. Sequences of MCPH2-7 genes were intact in cetaceans but frameshift mutations and stop codons was identified in MCPH1. Extensive positive selection was identified in four of six intact MCPH genes: WDR62, CDK5RAP2, CEP152, and ASPM. Specially, positive selection at CDK5RAP2 and ASPM were examined along lineages of odontocetes with increased encephalization quotients (EQ) and mysticetes with reduced EQ but at WDR62 only found along odontocete lineages. Interestingly, a positive association between evolutionary rate (ω) and EQ was identified for CDK5RAP2 and ASPM. Furthermore, we tested the binding affinities between Calmodulin (CaM) and ASPM IQ motif in cetaceans because only CaM combined with IQ, can ASPM perform the function in determining brain size. Preliminary function assay showed binding affinities between CaM and IQ motif of the odontocetes with increased EQ was stronger than for the mysticetes with decreased EQ. In addition, evolution rate of ASPM and CDK5RAP2 were significantly related to mean group size (as one measure of social complexity). Our study investigated the genetic basis of cetacean brain size evolution. Significant positive selection was examined along lineages with both increased and decreased EQ at CDK5RAP2 and ASPM, which is well matched with cetacean complex brain size evolution. Evolutionary rate of CDK5RAP2 and ASPM were significantly related to EQ, suggesting that these two genes may have contributed to EQ expansion in cetaceans. This suggestion was further indicated by our preliminary function test that ASPM might be mainly linked to evolutionary increases in EQ. Most strikingly, our results suggested that cetaceans evolved large brains

  13. Brain Immune Interactions as the Basis of Gulf War Illness: Gulf War Illness Consortium (GWIC)

    Science.gov (United States)

    2015-10-01

    cohesive understanding of the pathobiological mechanisms responsible for the symptoms of GWI in order to provide a rational and efficient basis for...an anti-inflammatory antibiotic has also been started by Dr. O’Callaghan’s lab at CDC. Initial results are presented in the figure below. 26

  14. Prediction of brain target site concentrations on the basis of CSF PK : impact of mechanisms of blood-to-brain transport and within brain distribution

    NARCIS (Netherlands)

    Westerhout, J.

    2014-01-01

    In the development of drugs for the treatment of central nervous system (CNS) disorders, the prediction of human CNS drug action is a big challenge. Direct measurement of brain extracellular fluid (brainECF) concentrations is highly restricted in human. Therefore, unbound drug concentrations in

  15. Study of brain-derived neurotrophic factor gene transgenic neural stem cells in the rat retina.

    Science.gov (United States)

    Zhou, Xue-mei; Yuan, Hui-ping; Wu, Dong-lai; Zhou, Xin-rong; Sun, Da-wei; Li, Hong-yi; Shao, Zheng-bo

    2009-07-20

    Neural stem cells (NSCs) transplantation and gene therapy have been widely investigated for treating the cerebullar and myelonic injuries, however, studies on the ophthalmology are rare. The aim of this study was to investigate the migration and differentiation of brain-derived neurotrophic factor (BDNF) gene transgenic NSCs transplanted into the normal rat retinas. NSCs were cultured and purified in vitro and infected with recombinant retrovirus pLXSN-BDNF and pLXSN respectively, to obtain the BDNF overexpressed NSCs (BDNF-NSCs) and control cells (p-NSCs). The expression of BDNF genes in two transgenic NSCs and untreated NSCs were measured by fluorescent quantitative polymerase chain reaction (FQ-PCR) and enzyme-linked immunosorbent assay (ELISA). BDNF-NSCs and NSCs were infected with adeno-associated viruses-enhanced green fluorescent protein (AAV-EGFP) to track them in vivo and served as donor cells for transplantation into the subretinal space of normal rat retinas, phosphated buffer solution (PBS) served as pseudo transplantation for a negative control. Survival, migration, and differentiation of donor cells in host retinas were observed and analyzed with Heidelberg retina angiograph (HRA) and immunohistochemistry, respectively. NSCs were purified successfully by limiting dilution assay. The expression of BDNF gene in BDNF-NSCs was the highest among three groups both at mRNA level tested by FQ-PCR (P neuron more efficiently compared with the control NSCs 2 months after transplantation. The seed cells of NSCs highly secreting BDNF were established. BDNF can promote NSCs to migrate and differentiate into neural cells in the normal host retinas.

  16. The malleable brain: plasticity of neural circuits and behavior - a review from students to students.

    Science.gov (United States)

    Schaefer, Natascha; Rotermund, Carola; Blumrich, Eva-Maria; Lourenco, Mychael V; Joshi, Pooja; Hegemann, Regina U; Jamwal, Sumit; Ali, Nilufar; García Romero, Ezra Michelet; Sharma, Sorabh; Ghosh, Shampa; Sinha, Jitendra K; Loke, Hannah; Jain, Vishal; Lepeta, Katarzyna; Salamian, Ahmad; Sharma, Mahima; Golpich, Mojtaba; Nawrotek, Katarzyna; Paidi, Ramesh K; Shahidzadeh, Sheila M; Piermartiri, Tetsade; Amini, Elham; Pastor, Veronica; Wilson, Yvette; Adeniyi, Philip A; Datusalia, Ashok K; Vafadari, Benham; Saini, Vedangana; Suárez-Pozos, Edna; Kushwah, Neetu; Fontanet, Paula; Turner, Anthony J

    2017-06-20

    One of the most intriguing features of the brain is its ability to be malleable, allowing it to adapt continually to changes in the environment. Specific neuronal activity patterns drive long-lasting increases or decreases in the strength of synaptic connections, referred to as long-term potentiation and long-term depression, respectively. Such phenomena have been described in a variety of model organisms, which are used to study molecular, structural, and functional aspects of synaptic plasticity. This review originated from the first International Society for Neurochemistry (ISN) and Journal of Neurochemistry (JNC) Flagship School held in Alpbach, Austria (Sep 2016), and will use its curriculum and discussions as a framework to review some of the current knowledge in the field of synaptic plasticity. First, we describe the role of plasticity during development and the persistent changes of neural circuitry occurring when sensory input is altered during critical developmental stages. We then outline the signaling cascades resulting in the synthesis of new plasticity-related proteins, which ultimately enable sustained changes in synaptic strength. Going beyond the traditional understanding of synaptic plasticity conceptualized by long-term potentiation and long-term depression, we discuss system-wide modifications and recently unveiled homeostatic mechanisms, such as synaptic scaling. Finally, we describe the neural circuits and synaptic plasticity mechanisms driving associative memory and motor learning. Evidence summarized in this review provides a current view of synaptic plasticity in its various forms, offers new insights into the underlying mechanisms and behavioral relevance, and provides directions for future research in the field of synaptic plasticity. Read the Editorial Highlight for this article on doi: 10.1111/jnc.14102. © 2017 International Society for Neurochemistry.

  17. Is Neural Activity Detected by ERP-Based Brain-Computer Interfaces Task Specific?

    Directory of Open Access Journals (Sweden)

    Markus A Wenzel

    Full Text Available Brain-computer interfaces (BCIs that are based on event-related potentials (ERPs can estimate to which stimulus a user pays particular attention. In typical BCIs, the user silently counts the selected stimulus (which is repeatedly presented among other stimuli in order to focus the attention. The stimulus of interest is then inferred from the electroencephalogram (EEG. Detecting attention allocation implicitly could be also beneficial for human-computer interaction (HCI, because it would allow software to adapt to the user's interest. However, a counting task would be inappropriate for the envisaged implicit application in HCI. Therefore, the question was addressed if the detectable neural activity is specific for silent counting, or if it can be evoked also by other tasks that direct the attention to certain stimuli.Thirteen people performed a silent counting, an arithmetic and a memory task. The tasks required the subjects to pay particular attention to target stimuli of a random color. The stimulus presentation was the same in all three tasks, which allowed a direct comparison of the experimental conditions.Classifiers that were trained to detect the targets in one task, according to patterns present in the EEG signal, could detect targets in all other tasks (irrespective of some task-related differences in the EEG.The neural activity detected by the classifiers is not strictly task specific but can be generalized over tasks and is presumably a result of the attention allocation or of the augmented workload. The results may hold promise for the transfer of classification algorithms from BCI research to implicit relevance detection in HCI.

  18. Neural Processing of Calories in Brain Reward Areas Can be Modulated by Reward Sensitivity.

    Science.gov (United States)

    van Rijn, Inge; Griffioen-Roose, Sanne; de Graaf, Cees; Smeets, Paul A M

    2015-01-01

    A food's reward value is dependent on its caloric content. Furthermore, a food's acute reward value also depends on hunger state. The drive to obtain rewards (reward sensitivity), however, differs between individuals. Here, we assessed the association between brain responses to calories in the mouth and trait reward sensitivity in different hunger states. Firstly, we assessed this in data from a functional neuroimaging study (van Rijn et al., 2015), in which participants (n = 30) tasted simple solutions of a non-caloric sweetener with or without a non-sweet carbohydrate (maltodextrin) during hunger and satiety. Secondly, we expanded these analyses to regular drinks by assessing the same relationship in data from a study in which soft drinks sweetened with either sucrose or a non-caloric sweetener were administered during hunger (n = 18) (Griffioen-Roose et al., 2013). First, taste activation by the non-caloric solution/soft drink was subtracted from that by the caloric solution/soft drink to eliminate sweetness effects and retain activation induced by calories. Subsequently, this difference in taste activation was correlated with reward sensitivity as measured with the BAS drive subscale of the Behavioral Activation System (BAS) questionnaire. When participants were hungry and tasted calories from the simple solution, brain activation in the right ventral striatum (caudate), right amygdala and anterior cingulate cortex (bilaterally) correlated negatively with BAS drive scores. In contrast, when participants were satiated, taste responses correlated positively with BAS drive scores in the left caudate. These results were not replicated for soft drinks. Thus, neural responses to oral calories from maltodextrin were modulated by reward sensitivity in reward-related brain areas. This was not the case for sucrose. This may be due to the direct detection of maltodextrin, but not sucrose in the oral cavity. Also, in a familiar beverage, detection of calories per se may be

  19. The alexithymic brain: the neural pathways linking alexithymia to physical disorders

    Directory of Open Access Journals (Sweden)

    Kano Michiko

    2013-01-01

    Full Text Available Abstract Alexithymia is a personality trait characterized by difficulties in identifying and describing feelings and is associated with psychiatric and psychosomatic disorders. The mechanisms underlying the link between emotional dysregulation and psychosomatic disorders are unclear. Recent progress in neuroimaging has provided important information regarding emotional experience in alexithymia. We have conducted three brain imaging studies on alexithymia, which we describe herein. This article considers the role of emotion in the development of physical symptoms and discusses a possible pathway that we have identified in our neuroimaging studies linking alexithymia with psychosomatic disorders. In terms of socio-affective processing, alexithymics demonstrate lower reactivity in brain regions associated with emotion. Many studies have reported reduced activation in limbic areas (e.g., cingulate cortex, anterior insula, amygdala and the prefrontal cortex when alexithymics attempt to feel other people’s feelings or retrieve their own emotional episodes, compared to nonalexithymics. With respect to primitive emotional reactions such as the response to pain, alexithymics show amplified activity in areas considered to be involved in physical sensation. In addition to greater hormonal arousal responses in alexithymics during visceral pain, increased activity has been reported in the insula, anterior cingulate cortex, and midbrain. Moreover, in complex social situations, alexithymics may not be able to use feelings to guide their behavior appropriately. The Iowa gambling task (IGT was developed to assess decision-making processes based on emotion-guided evaluation. When alexithymics perform the IGT, they fail to learn an advantageous decision-making strategy and show reduced activity in the medial prefrontal cortex, a key area