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Sample records for brain neural basis

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

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    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. 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

    2014-02-01

    Individuation refers to individuals' use of spatial and temporal properties to register an object as a distinct perceptual event relative to other stimuli. Although behavioral studies have examined both spatial and temporal individuation, neuroimaging investigations of individuation have been restricted to the spatial domain and at relatively late stages of information processing. In this study we used univariate and multivoxel pattern analyses of functional magnetic resonance imaging 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 in a large group of brain regions involved in "lower-level" perceptual and "higher-level" attentional/executive processing 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, stimulus or response factors, task difficulty, regional activation differences, other capacity-limited processes, or artifacts in the data or analyses. Consistent with the global workplace model of consciousness, 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) modulated the amplitude, rather than spatial pattern, of activity in the left hemisphere premotor cortex. This finding could not be attributed to response conflict/ambiguity and likely reflects a candidate brain region underlying the capacity-limited process that gives rise to RB.

  3. Analysis of CT Brain Images using Radial Basis Function Neural Network

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    T. Joshva Devadas

    2012-07-01

    Full Text Available Medical image processing and analysis is the tool to assist radiologists in the diagnosis process to obtain a moreaccurate and faster diagnosis. In this work, we have developed a neural network to classify the computer tomography(CT brain tumor image for automatic diagnosis. This system is divided into four steps namely enhancement, segmentation, feature extraction and classification. In the first phase, an edge-based selective median filter is usedto improve the visibility of the loss of the gray-white matter interface in CT brain tumor images. Second phaseuses a modified version of shift genetic algorithm for the segmentation. Next phase extracts the textural featuresusing statistical texture analysis method. These features are fed into classifiers like BPN, Fuzzy k-NN, and radialbasis function network. The performances of these classifiers are analyzed in the final phase with receiver operating characteristic and precision-recall curve. The result shows that the CAD system is only to develop the tool for braintumor and proposed method is very accurate and computationally more efficient and less time consuming.Defence Science Journal, 2012, 62(4, pp.212-218, DOI:http://dx.doi.org/10.14429/dsj.62.1830

  4. 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

  5. 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.

  6. Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders.

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    Zhang, Jie; Cheng, Wei; Liu, Zhaowen; Zhang, Kai; Lei, Xu; Yao, Ye; Becker, Benjamin; Liu, Yicen; Kendrick, Keith M; Lu, Guangming; Feng, Jianfeng

    2016-08-01

    SEE MATTAR ET AL DOI101093/AWW151 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Functional brain networks demonstrate significant temporal variability and dynamic reconfiguration even in the resting state. Currently, most studies investigate temporal variability of brain networks at the scale of single (micro) or whole-brain (macro) connectivity. However, the mechanism underlying time-varying properties remains unclear, as the coupling between brain network variability and neural activity is not readily apparent when analysed at either micro or macroscales. We propose an intermediate (meso) scale analysis and characterize temporal variability of the functional architecture associated with a particular region. This yields a topography of variability that reflects the whole-brain and, most importantly, creates an analytical framework to establish the fundamental relationship between variability of regional functional architecture and its neural activity or structural connectivity. We find that temporal variability reflects the dynamical reconfiguration of a brain region into distinct functional modules at different times and may be indicative of brain flexibility and adaptability. Primary and unimodal sensory-motor cortices demonstrate low temporal variability, while transmodal areas, including heteromodal association areas and limbic system, demonstrate the high variability. In particular, regions with highest variability such as hippocampus/parahippocampus, inferior and middle temporal gyrus, olfactory gyrus and caudate are all related to learning, suggesting that the temporal variability may indicate the level of brain adaptability. With simultaneously recorded electroencephalography/functional magnetic resonance imaging and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variability of regional functional architecture is modulated by local blood oxygen level-dependent activity and α-band oscillation, and is governed by the

  7. [Neural basis of maternal behavior].

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    Noriuchi, Madoka; Kikuchi, Yoshiaki

    2013-01-01

    Maternal love, which may be the core of maternal behavior, is essential for the mother-infant attachment relationship and is important for the infant's development and mental health. However, little has been known about these neural mechanisms in human mothers. We examined patterns of maternal brain activation in response to infant cues using video clips. We performed functional magnetic resonance imaging (fMRI) measurements while 13 mothers viewed video clips, with no sound, of their own infant and other infants of approximately 16 months of age who demonstrated two different attachment behaviors (smiling at the infant's mother and crying for her). We found that a limited number of the mother's brain areas were specifically involved in recognition of the mother's own infant, namely orbitofrontal cortex (OFC). and periaqueductal gray, anterior insula, and dorsal and ventrolateral parts of putamen. Additionally, we found the strong and specific mother's brain response for the mother's own infant's distress. The differential neural activation pattern was found in the dorsal region of OFC, caudate nucleus, right inferior frontal gyrus, dorsomedial prefrontal cortex (PFC), anterior cingulate, posterior cingulate, posterior superior temporal sulcus, and dorsolateral PFC. Our results showed the highly elaborate neural mechanism mediating maternal love and diverse and complex maternal behaviors for vigilant protectiveness.

  8. 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.

  9. 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.

  10. Framing effects: behavioral dynamics and neural basis.

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    Zheng, Hongming; Wang, X T; Zhu, Liqi

    2010-09-01

    This study examined the neural basis of framing effects using life-death decision problems framed either positively in terms of lives saved or negatively in terms of lives lost in large group and small group contexts. Using functional MRI we found differential brain activations to the verbal and social cues embedded in the choice problems. In large group contexts, framing effects were significant where participants were more risk seeking under the negative (loss) framing than under the positive (gain) framing. This behavioral difference in risk preference was mainly regulated by the activation in the right inferior frontal gyrus, including the homologue of the Broca's area. In contrast, framing effects diminished in small group contexts while the insula and parietal lobe in the right hemisphere were distinctively activated, suggesting an important role of emotion in switching choice preference from an indecisive mode to a more consistent risk-taking inclination, governed by a kith-and-kin decision rationality.

  11. 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.

  12. 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

  13. 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.

  14. A re-examination of neural basis of language processing: proposal of a dynamic hodotopical model from data provided by brain stimulation mapping during picture naming.

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    Duffau, Hugues; Moritz-Gasser, Sylvie; Mandonnet, Emmanuel

    2014-04-01

    From recent findings provided by brain stimulation mapping during picture naming, we re-examine the neural basis of language. We studied structural-functional relationships by correlating the types of language disturbances generated by stimulation in awake patients, mimicking a transient virtual lesion both at cortical and subcortical levels (white matter and deep grey nuclei), with the anatomical location of the stimulation probe. We propose a hodotopical (delocalized) and dynamic model of language processing, which challenges the traditional modular and serial view. According to this model, following the visual input, the language network is organized in parallel, segregated (even if interconnected) large-scale cortico-subcortical sub-networks underlying semantic, phonological and syntactic processing. Our model offers several advantages (i) it explains double dissociations during stimulation (comprehension versus naming disorders, semantic versus phonemic paraphasias, syntactic versus naming disturbances, plurimodal judgment versus naming disorders); (ii) it takes into account the cortical and subcortical anatomic constraints; (iii) it explains the possible recovery of aphasia following a lesion within the "classical" language areas; (iv) it establishes links with a model executive functions.

  15. Neural Basis of Visual Distraction

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    Kim, So-Yeon; Hopfinger, Joseph B.

    2010-01-01

    The ability to maintain focus and avoid distraction by goal-irrelevant stimuli is critical for performing many tasks and may be a key deficit in attention-related problems. Recent studies have demonstrated that irrelevant stimuli that are consciously perceived may be filtered out on a neural level and not cause the distraction triggered by…

  16. The neural basis of altruistic punishment.

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    de Quervain, Dominique J-F; Fischbacher, Urs; Treyer, Valerie; Schellhammer, Melanie; Schnyder, Ulrich; Buck, Alfred; Fehr, Ernst

    2004-08-27

    Many people voluntarily incur costs to punish violations of social norms. Evolutionary models and empirical evidence indicate that such altruistic punishment has been a decisive force in the evolution of human cooperation. We used H2 15O positron emission tomography to examine the neural basis for altruistic punishment of defectors in an economic exchange. Subjects could punish defection either symbolically or effectively. Symbolic punishment did not reduce the defector's economic payoff, whereas effective punishment did reduce the payoff. We scanned the subjects' brains while they learned about the defector's abuse of trust and determined the punishment. Effective punishment, as compared with symbolic punishment, activated the dorsal striatum, which has been implicated in the processing of rewards that accrue as a result of goal-directed actions. Moreover, subjects with stronger activations in the dorsal striatum were willing to incur greater costs in order to punish. Our findings support the hypothesis that people derive satisfaction from punishing norm violations and that the activation in the dorsal striatum reflects the anticipated satisfaction from punishing defectors.

  17. The neural basis of bounded rational behavior

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    Coricelli, Giorgio; Nagel, Rosemarie

    2010-01-01

    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. ...

  18. Neural basis of interpersonal traits in neurodegenerative diseases.

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    Sollberger, Marc; Stanley, Christine M; Wilson, Stephen M; Gyurak, Anett; Beckman, Victoria; Growdon, Matthew; Jang, Jung; Weiner, Michael W; Miller, Bruce L; Rankin, Katherine P

    2009-11-01

    Several functional and structural imaging studies have investigated the neural basis of personality in healthy adults, but human lesions studies are scarce. Personality changes are a common symptom in patients with neurodegenerative diseases like frontotemporal dementia (FTD) and semantic dementia (SD), allowing a unique window into the neural basis of personality. In this study, we used the Interpersonal Adjective Scales to investigate the structural basis of eight interpersonal traits (dominance, arrogance, coldness, introversion, submissiveness, ingenuousness, warmth, and extraversion) in 257 subjects: 214 patients with neurodegenerative diseases such as FTD, SD, progressive nonfluent aphasia, Alzheimer's disease, amnestic mild cognitive impairment, corticobasal degeneration, and progressive supranuclear palsy and 43 healthy elderly people. Measures of interpersonal traits were correlated with regional atrophy pattern using voxel-based morphometry (VBM) analysis of structural MR images. Interpersonal traits mapped onto distinct brain regions depending on the degree to which they involved agency and affiliation. Interpersonal traits high in agency related to left dorsolateral prefrontal and left lateral frontopolar regions, whereas interpersonal traits high in affiliation related to right ventromedial prefrontal and right anteromedial temporal regions. Consistent with the existing literature on neural networks underlying social cognition, these results indicate that brain regions related to externally focused, executive control-related processes underlie agentic interpersonal traits such as dominance, whereas brain regions related to internally focused, emotion- and reward-related processes underlie affiliative interpersonal traits such as warmth. In addition, these findings indicate that interpersonal traits are subserved by complex neural networks rather than discrete anatomic areas.

  19. 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.

  20. 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

  1. Towards a neural basis of music perception.

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    Koelsch, Stefan; Siebel, Walter A

    2005-12-01

    Music perception involves complex brain functions underlying acoustic analysis, auditory memory, auditory scene analysis, and processing of musical syntax and semantics. Moreover, music perception potentially affects emotion, influences the autonomic nervous system, the hormonal and immune systems, and activates (pre)motor representations. During the past few years, research activities on different aspects of music processing and their neural correlates have rapidly progressed. This article provides an overview of recent developments and a framework for the perceptual side of music processing. This framework lays out a model of the cognitive modules involved in music perception, and incorporates information about the time course of activity of some of these modules, as well as research findings about where in the brain these modules might be located.

  2. Exploring the neural basis of cognitive reserve.

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    Stern, Yaakov; Zarahn, Eric; Hilton, H John; Flynn, Joseph; DeLaPaz, Robert; Rakitin, Brian

    2003-08-01

    There is epidemiologic and imaging evidence for the presence of cognitive reserve, but the neurophysiologic substrate of CR has not been established. In order to test the hypothesis that CR is related to aspects of neural processing, we used fMRI to image 19 healthy young adults while they performed a nonverbal recognition test. There were two task conditions. A low demand condition required encoding and recognition of single items and a titrated demand condition required the subject to encode and then recognize a larger list of items, with the study list size for each subject adjusted prior to scanning such that recognition accuracy was 75%. We hypothesized that individual differences in cognitive reserve are related to changes in neural activity as subjects moved from the low to the titrated demand task. To test this, we examined the correlation between subjects' fMRI activation and NART scores. This analysis was implemented voxel-wise in a whole brain fMRI dataset. During both the study and test phases of the recognition memory task we noted areas where, across subjects, there were significant positive and negative correlations between change in activation from low to titrated demand and the NART score. These correlations support our hypothesis that neural processing differs across individuals as a function of CR. This differential processing may help explain individual differences in capacity, and may underlie reserve against age-related or other pathologic changes.

  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. Afferent Fiber Remodeling in the Somatosensory Thalamus of Mice as a Neural Basis of Somatotopic Reorganization in the Brain and Ectopic Mechanical Hypersensitivity after Peripheral Sensory Nerve Injury

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    Yagasaki, Yuki; Katayama, Yoko

    2017-01-01

    Abstract Plastic changes in the CNS in response to peripheral sensory nerve injury are a series of complex processes, ranging from local circuit remodeling to somatotopic reorganization. However, the link between circuit remodeling and somatotopic reorganization remains unclear. We have previously reported that transection of the primary whisker sensory nerve causes the abnormal rewiring of lemniscal fibers (sensory afferents) on a neuron in the mouse whisker sensory thalamus (V2 VPM). In the present study, using transgenic mice whose lemniscal fibers originate from the whisker sensory principle trigeminal nucleus (PrV2) are specifically labeled, we identified that the transection induced retraction of PrV2-originating lemniscal fibers and invasion of those not originating from PrV2 in the V2 VPM. This anatomical remodeling with somatotopic reorganization was highly correlated with the rewiring of lemniscal fibers. Origins of the non-PrV2-origin lemniscal fibers in the V2 VPM included the mandibular subregion of trigeminal nuclei and the dorsal column nuclei (DCNs), which normally represent body parts other than whiskers. The transection also resulted in ectopic receptive fields of V2 VPM neurons and extraterritorial pain behavior on the uninjured mandibular region of the face. The anatomical remodeling, emergence of ectopic receptive fields, and extraterritorial pain behavior all concomitantly developed within a week and lasted more than three months after the transection. Our findings, thus, indicate a strong linkage between these plastic changes after peripheral sensory nerve injury, which may provide a neural circuit basis underlying large-scale reorganization of somatotopic representation and abnormal ectopic sensations.

  5. The neural basis of event simulation: an FMRI study.

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    Yukihito Yomogida

    Full Text Available Event simulation (ES is the situational inference process in which perceived event features such as objects, agents, and actions are associated in the brain to represent the whole situation. ES provides a common basis for various cognitive processes, such as perceptual prediction, situational understanding/prediction, and social cognition (such as mentalizing/trait inference. Here, functional magnetic resonance imaging was used to elucidate the neural substrates underlying important subdivisions within ES. First, the study investigated whether ES depends on different neural substrates when it is conducted explicitly and implicitly. Second, the existence of neural substrates specific to the future-prediction component of ES was assessed. Subjects were shown contextually related object pictures implying a situation and performed several picture-word-matching tasks. By varying task goals, subjects were made to infer the implied situation implicitly/explicitly or predict the future consequence of that situation. The results indicate that, whereas implicit ES activated the lateral prefrontal cortex and medial/lateral parietal cortex, explicit ES activated the medial prefrontal cortex, posterior cingulate cortex, and medial/lateral temporal cortex. Additionally, the left temporoparietal junction plays an important role in the future-prediction component of ES. These findings enrich our understanding of the neural substrates of the implicit/explicit/predictive aspects of ES-related cognitive processes.

  6. Genetic basis of human brain evolution.

    Science.gov (United States)

    Vallender, Eric J; Mekel-Bobrov, Nitzan; Lahn, Bruce T

    2008-12-01

    Human evolution is characterized by a rapid increase in brain size and complexity. Decades of research have made important strides in identifying anatomical and physiological substrates underlying the unique features of the human brain. By contrast, it has become possible only very recently to examine the genetic basis of human brain evolution. Through comparative genomics, tantalizing insights regarding human brain evolution have emerged. The genetic changes that potentially underlie human brain evolution span a wide range from single-nucleotide substitutions to large-scale structural alterations of the genome. Similarly, the functional consequences of these genetic changes vary greatly, including protein-sequence alterations, cis-regulatory changes and even the emergence of new genes and the extinction of existing ones. Here, we provide a general review of recent findings into the genetic basis of human brain evolution, highlight the most notable trends that have emerged and caution against over-interpretation of current data.

  7. 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.

  8. The neural basis of human tool use

    Directory of Open Access Journals (Sweden)

    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.

  9. The neural basis of tactile motion perception.

    Science.gov (United States)

    Pei, Yu-Cheng; Bensmaia, Sliman J

    2014-12-15

    The manipulation of objects commonly involves motion between object and skin. In this review, we discuss the neural basis of tactile motion perception and its similarities with its visual counterpart. First, much like in vision, the perception of tactile motion relies on the processing of spatiotemporal patterns of activation across populations of sensory receptors. Second, many neurons in primary somatosensory cortex are highly sensitive to motion direction, and the response properties of these neurons draw strong analogies to those of direction-selective neurons in visual cortex. Third, tactile speed may be encoded in the strength of the response of cutaneous mechanoreceptive afferents and of a subpopulation of speed-sensitive neurons in cortex. However, both afferent and cortical responses are strongly dependent on texture as well, so it is unclear how texture and speed signals are disambiguated. Fourth, motion signals from multiple fingers must often be integrated during the exploration of objects, but the way these signals are combined is complex and remains to be elucidated. Finally, visual and tactile motion perception interact powerfully, an integration process that is likely mediated by visual association cortex.

  10. 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

  11. Neural Basis of Interpersonal Traits in Neurodegenerative Diseases

    OpenAIRE

    Sollberger, Marc; Stanley, Christine M.; Wilson, Stephen M.; Gyurak, Anett; Beckman, Victoria; Growdon, Matthew; Jang, Jung; Weiner, Michael W.; Miller, Bruce L.; Katherine P. Rankin

    2009-01-01

    Several functional and structural imaging studies have investigated the neural basis of personality in healthy adults, but human lesions studies are scarce. Personality changes are a common symptom in patients with neurodegenerative diseases like frontotemporal dementia (FTD) and semantic dementia (SD), allowing a unique window into the neural basis of personality. In this study, we used the Interpersonal Adjective Scales to investigate the structural basis of eight interpersonal traits (domi...

  12. 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.

  13. 双语加工的脑神经基础差异研究%The differences of brain neural basis on bilingual processing

    Institute of Scientific and Technical Information of China (English)

    党彩萍

    2012-01-01

      Is the language centre of bilingual who grasps two kinds of languages (L1: first language; L2: second language) same as that of the monolingual? This paper analyze this problem and summarized that different brain regions were activicted by different language processing in bilingual which were revealed by some research. Hence, this paper also confirms the famous theory that different bilingual language is represented by the different brain cortex. And the paper also point out that some features of the second language, such as its fluency, pronunciation nature, grammar nature, are important factors affecting the brain regions activation.%  掌握两种语言(L1: first language; L2: second language)的双语者,其语言中枢是否和单语者相同?文章围绕该问题探讨了许多研究证实的双语者加工不同语言时会激活不同脑区的研究结论,并支持了不同的双语语言是由不同脑皮层来表征这一理论,也分析了第二语言的流利性、语音、语法等特点,都是影响双语脑区激活的重要因素

  14. 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.

  15. 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.

  16. 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.

  17. A Meta-analysis on the neural basis of planning: Activation likelihood estimation of functional brain imaging results in the Tower of London task.

    Science.gov (United States)

    Nitschke, Kai; Köstering, Lena; Finkel, Lisa; Weiller, Cornelius; Kaller, Christoph P

    2017-01-01

    The ability to mentally design and evaluate series of future actions has often been studied in terms of planning abilities, commonly using well-structured laboratory tasks like the Tower of London (ToL). Despite a wealth of studies, findings on the specific localization of planning processes within prefrontal cortex (PFC) and on the hemispheric lateralization are equivocal. Here, we address this issue by integrating evidence from two different sources of data: First, we provide a systematic overview of the existing lesion data on planning in the ToL (10 studies, 211 patients) which does not indicate any evidence for a general lateralization of planning processes in (pre)frontal cortex. Second, we report a quantitative meta-analysis with activation likelihood estimation based on 31 functional neuroimaging datasets on the ToL. Separate meta-analyses of the activation patterns reported for Overall Planning (537 participants) and for Planning Complexity (182 participants) congruently show bilateral contributions of mid-dorsolateral PFC, frontal eye fields, supplementary motor area, precuneus, caudate, anterior insula, and inferior parietal cortex in addition to a left-lateralized involvement of rostrolateral PFC. In contrast to previous attributions of planning-related brain activity to the entire dorsolateral prefrontal cortex (dlPFC) and either its left or right homolog derived from single studies on the ToL, the present meta-analyses stress the pivotal role specifically of the mid-dorsolateral part of PFC (mid-dlPFC), presumably corresponding to Brodmann Areas 46 and 9/46, and strongly argue for a bilateral rather than lateralized involvement of the dlPFC in planning in the ToL. Hum Brain Mapp 38:396-413, 2017. © 2016 Wiley Periodicals, Inc.

  18. Identification and integration of sensory modalities: Neural basis and relation to consciousness

    NARCIS (Netherlands)

    Pennartz, C.M.A.

    2009-01-01

    A key question in studying consciousness is how neural operations in the brain can identify streams of sensory input as belonging to distinct modalities, which contributes to the representation of qualitatively different experiences. The basis for identification of modalities is proposed to be const

  19. The neural basis of involuntary episodic memories.

    Science.gov (United States)

    Hall, Shana A; Rubin, David C; Miles, Amanda; Davis, Simon W; Wing, Erik A; Cabeza, Roberto; Berntsen, Dorthe

    2014-10-01

    Voluntary episodic memories require an intentional memory search, whereas involuntary episodic memories come to mind spontaneously without conscious effort. Cognitive neuroscience has largely focused on voluntary memory, leaving the neural mechanisms of involuntary memory largely unknown. We hypothesized that, because the main difference between voluntary and involuntary memory is the controlled retrieval processes required by the former, there would be greater frontal activity for voluntary than involuntary memories. Conversely, we predicted that other components of the episodic retrieval network would be similarly engaged in the two types of memory. During encoding, all participants heard sounds, half paired with pictures of complex scenes and half presented alone. During retrieval, paired and unpaired sounds were presented, panned to the left or to the right. Participants in the involuntary group were instructed to indicate the spatial location of the sound, whereas participants in the voluntary group were asked to additionally recall the pictures that had been paired with the sounds. All participants reported the incidence of their memories in a postscan session. Consistent with our predictions, voluntary memories elicited greater activity in dorsal frontal regions than involuntary memories, whereas other components of the retrieval network, including medial-temporal, ventral occipitotemporal, and ventral parietal regions were similarly engaged by both types of memories. These results clarify the distinct role of dorsal frontal and ventral occipitotemporal regions in predicting strategic retrieval and recalled information, respectively, and suggest that, although there are neural differences in retrieval, involuntary memories share neural components with established voluntary memory systems.

  20. 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.

  1. 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.

  2. Biological effect of velvet antler polypeptides on neural stem cells from embryonic rat brain

    Institute of Scientific and Technical Information of China (English)

    LU Lai-jin; CHEN Lei; MENG Xiao-ting; YANG Fan; ZHANG Zhi-xin; CHEN Dong

    2005-01-01

    Background Velvet antler polypeptides (VAPs), which are derived from the antler velvets, have been reported to maintain survival and promote growth and differentiation of neural cells and, especially the development of neural tissues. This study was designed to explore the influence of VAPs on neural stem cells in vitro derived from embryonic rat brain. Methods Neural stem cells derived from E12-14 rat brain were isolated, cultured, and expanded for 7 days until neural stem cell aggregations and neurospheres were generated. The neurospheres were cultured under the condition of different concentration of VAPs followed by immunocytochemistry to detect the differentiation of neural stem cells. Results VAPs could remarkablely promote differentiation of neural stem cells and most neural stem cells were induced to differentiate towards the direction of neurons under certain concentration of VAPs.Conclusion Neural stem cells can be successfully induced into neurons by VAPs in vitro, which could provide a basis for regeneration of the nervous system.

  3. Understanding the brain by controlling neural activity

    OpenAIRE

    Krug, Kristine; Salzman, C. Daniel; Waddell, Scott

    2015-01-01

    Causal methods to interrogate brain function have been employed since the advent of modern neuroscience in the nineteenth century. Initially, randomly placed electrodes and stimulation of parts of the living brain were used to localize specific functions to these areas. Recent technical developments have rejuvenated this approach by providing more precise tools to dissect the neural circuits underlying behaviour, perception and cognition. Carefully controlled behavioural experiments have been...

  4. A brain basis for musical hallucinations.

    Science.gov (United States)

    Kumar, Sukhbinder; Sedley, William; Barnes, Gareth R; Teki, Sundeep; Friston, Karl J; Griffiths, Timothy D

    2014-03-01

    The physiological basis for musical hallucinations (MH) is not understood. One obstacle to understanding has been the lack of a method to manipulate the intensity of hallucination during the course of experiment. Residual inhibition, transient suppression of a phantom percept after the offset of a masking stimulus, has been used in the study of tinnitus. We report here a human subject whose MH were residually inhibited by short periods of music. Magnetoencephalography (MEG) allowed us to examine variation in the underlying oscillatory brain activity in different states. Source-space analysis capable of single-subject inference defined left-lateralised power increases, associated with stronger hallucinations, in the gamma band in left anterior superior temporal gyrus, and in the beta band in motor cortex and posteromedial cortex. The data indicate that these areas form a crucial network in the generation of MH, and are consistent with a model in which MH are generated by persistent reciprocal communication in a predictive coding hierarchy.

  5. The Neural Basis for Learning of Simple Motor Skills.

    Science.gov (United States)

    Lisberger, Stephen G.

    1988-01-01

    Discusses the vestibulo-ocular reflex (VOR) which is used to investigate the neural basis for motor learning in monkeys. Suggests organizing principles that may apply in forms of motor learning as a result of similarities among VOR and other motor systems. (Author/RT)

  6. 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.

  7. 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.

  8. Regulation of the nascent brain vascular network by neural progenitors.

    Science.gov (United States)

    Santhosh, Devi; Huang, Zhen

    2015-11-01

    Neural progenitors are central players in the development of the brain neural circuitry. They not only produce the diverse neuronal and glial cell types in the brain, but also guide their migration in this process. Recent evidence indicates that neural progenitors also play a critical role in the development of the brain vascular network. At an early stage, neural progenitors have been found to facilitate the ingression of blood vessels from outside the neural tube, through VEGF and canonical Wnt signaling. Subsequently, neural progenitors directly communicate with endothelial cells to stabilize nascent brain vessels, in part through down-regulating Wnt pathway activity. Furthermore, neural progenitors promote nascent brain vessel integrity, through integrin αvβ8-dependent TGFβ signaling. In this review, we will discuss the evidence for, as well as questions that remain, regarding these novel roles of neural progenitors and the underlying mechanisms in their regulation of the nascent brain vascular network.

  9. The neural basis of implicit perceptual sequence learning

    Directory of Open Access Journals (Sweden)

    Freja eGheysen

    2011-11-01

    Full Text Available The present fMRI study investigated the neural areas involved in implicit perceptual sequence learning. To obtain more insight in the functional contributions of the brain areas, we tracked both the behavioral and neural time course of the learning process, using a perceptual serial color matching task. Next, to investigate whether the neural time course was specific for perceptual information, imaging results were compared to the results of implicit motor sequence learning, previously investigated using an identical serial color matching task. Results indicated that implicit sequences can be acquired by at least two neural systems: the caudate nucleus and the hippocampus, having different operating principles. The caudate nucleus contributed to the implicit sequence learning process for perceptual as well as motor information in a similar and gradual way. The hippocampus, on the other hand, was engaged in a much faster learning process which was more pronounced for the motor compared to the perceptual task. Interestingly, the perceptual and motor learning process occurred on a comparable implicit level, suggesting that consciousness is not the main determinant factor dissociating the hippocampal from the caudate learning system. This study is not only the first to successfully and unambiguously compare brain activation between perceptual and motor levels of implicit sequence learning, it also provides new insights into the specific hippocampal and caudate learning function.

  10. 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.

  11. 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…

  12. Neural mass model-based tracking of anesthetic brain states

    NARCIS (Netherlands)

    Kuhlmann, Levin; Freestone, Dean R.; Manton, Jonathan H.; Heyse, Bjorn; Vereecke, Hugo E. M.; Lipping, Tarmo; Struys, Michel M. R. F.; Liley, David T. J.

    2016-01-01

    Neural mass model-based tracking of brain states from electroencephalographic signals holds the promise of simultaneously tracking brain states while inferring underlying physiological changes in various neuroscientific and clinical applications. Here, neural mass model-based tracking of brain state

  13. 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.

  14. 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.

  15. Nonlinear Time Series Forecast Using Radial Basis Function Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHENGXin; CHENTian-Lun

    2003-01-01

    In the research of using Radial Basis Function Neural Network (RBF NN) forecasting nonlinear time series, we investigate how the different clusterings affect the process of learning and forecasting. We find that k-means clustering is very suitable. In order to increase the precision we introduce a nonlinear feedback term to escape from the local minima of energy, then we use the model to forecast the nonlinear time series which are produced by Mackey-Glass equation and stocks. By selecting the k-means clustering and the suitable feedback term, much better forecasting results are obtained.

  16. Nonlinear Time Series Forecast Using Radial Basis Function Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHENG Xin; CHEN Tian-Lun

    2003-01-01

    In the research of using Radial Basis Function Neural Network (RBF NN) forecasting nonlinear timeseries, we investigate how the different clusterings affect the process of learning and forecasting. We find that k-meansclustering is very suitable. In order to increase the precision we introduce a nonlinear feedback term to escape from thelocal minima of energy, then we use the model to forecast the nonlinear time series which are produced by Mackey-Glassequation and stocks. By selecting the k-means clustering and the suitable feedback term, much better forecasting resultsare obtained.

  17. Synchronization of chaos using radial basis functions neural networks

    Institute of Scientific and Technical Information of China (English)

    Ren Haipeng; Liu Ding

    2007-01-01

    The Radial Basis Functions Neural Network (RBFNN) is used to establish the model of a response system through the input and output data of the system. The synchronization between a drive system and the response system can be implemented by employing the RBFNN model and state feedback control. In this case, the exact mathematical model, which is the precondition for the conventional method, is unnecessary for implementing synchronization. The effect of the model error is investigated and a corresponding theorem is developed. The effect of the parameter perturbations and the measurement noise is investigated through simulations. The simulation results under different conditions show the effectiveness of the method.

  18. 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.

  19. 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.

  20. 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.

  1. Neural basis of quasi-rational decision making.

    Science.gov (United States)

    Lee, Daeyeol

    2006-04-01

    Standard economic theories conceive homo economicus as a rational decision maker capable of maximizing utility. In reality, however, people tend to approximate optimal decision-making strategies through a collection of heuristic routines. Some of these routines are driven by emotional processes, and others are adjusted iteratively through experience. In addition, routines specialized for social decision making, such as inference about the mental states of other decision makers, might share their origins and neural mechanisms with the ability to simulate or imagine outcomes expected from alternative actions that an individual can take. A recent surge of collaborations across economics, psychology and neuroscience has provided new insights into how such multiple elements of decision making interact in the brain.

  2. A brain basis for musical hallucinations ☆

    OpenAIRE

    2014-01-01

    The physiological basis for musical hallucinations (MH) is not understood. One obstacle to understanding has been the lack of a method to manipulate the intensity of hallucination during the course of experiment. Residual inhibition, transient suppression of a phantom percept after the offset of a masking stimulus, has been used in the study of tinnitus. We report here a human subject whose MH were residually inhibited by short periods of music. Magnetoencephalography (MEG) allowed us to exam...

  3. 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.

  4. 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

  5. Estimation of spatiotemporal neural activity using radial basis function networks.

    Science.gov (United States)

    Anderson, R W; Das, S; Keller, E L

    1998-12-01

    We report a method using radial basis function (RBF) networks to estimate the time evolution of population activity in topologically organized neural structures from single-neuron recordings. This is an important problem in neuroscience research, as such estimates may provide insights into systems-level function of these structures. Since single-unit neural data tends to be unevenly sampled and highly variable under similar behavioral conditions, obtaining such estimates is a difficult task. In particular, a class of cells in the superior colliculus called buildup neurons can have very narrow regions of saccade vectors for which they discharge at high rates but very large surround regions over which they discharge at low, but not zero, levels. Estimating the dynamic movement fields for these cells for two spatial dimensions at closely spaced timed intervals is a difficult problem, and no general method has been described that can be applied to all buildup cells. Estimation of individual collicular cells' spatiotemporal movement fields is a prerequisite for obtaining reliable two-dimensional estimates of the population activity on the collicular motor map during saccades. Therefore, we have developed several computational-geometry-based algorithms that regularize the data before computing a surface estimation using RBF networks. The method is then expanded to the problem of estimating simultaneous spatiotemporal activity occurring across the superior colliculus during a single movement (the inverse problem). In principle, this methodology could be applied to any neural structure with a regular, two-dimensional organization, provided a sufficient spatial distribution of sampled neurons is available.

  6. Neural basis of disgust perception in racial prejudice.

    Science.gov (United States)

    Liu, Yunzhe; Lin, Wanjun; Xu, Pengfei; Zhang, Dandan; Luo, Yuejia

    2015-12-01

    Worldwide racial prejudice is originated from in-group/out-group discrimination. This prejudice can bias face perception at the very beginning of social interaction. However, little is known about the neurocognitive mechanism underlying the influence of racial prejudice on facial emotion perception. Here, we examined the neural basis of disgust perception in racial prejudice using a passive viewing task and functional magnetic resonance imaging. We found that compared with the disgusted faces of in-groups, the disgusted faces of out-groups result in increased amygdala and insular engagement, positive coupling of the insula with amygdala-based emotional system, and negative coupling of the insula with anterior cingulate cortex (ACC)-based regulatory system. Furthermore, machine-learning algorithms revealed that the level of implicit racial prejudice could be predicted by functional couplings of the insula with both the amygdala and the ACC, which suggests that the insula is largely involved in racially biased disgust perception through two distinct neural circuits. In addition, individual difference in disgust sensitivity was found to be predictive of implicit racial prejudice. Taken together, our results suggest a crucial role of insula-centered circuits for disgust perception in racial prejudice.

  7. Neural reuse in the organization and development of the brain.

    Science.gov (United States)

    Anderson, Michael L

    2016-03-01

    Neural reuse is the process by which neural elements originally developed for one purpose are put to many different subsequent uses. In this brief review I will outline the role of neural reuse in the development of the brain. Special attention will be paid to elucidating and differentiating between two different mechanisms of neurocognitive development: Hebbian plasticity, the importance of which is already well known, and a neural search mechanism that supports the establishment of new functional partnerships in the brain. I describe how these two mechanisms work in concert throughout development to produce the functional architecture we observe in the adult brain; outline the evidence for the importance of neural reuse; offer suggestions for some clinical implications of neural reuse; and point to future research directions.

  8. fMRI of Simultaneous Interpretation Reveals the Neural Basis of Extreme Language Control.

    Science.gov (United States)

    Hervais-Adelman, Alexis; Moser-Mercer, Barbara; Michel, Christoph M; Golestani, Narly

    2015-12-01

    We used functional magnetic resonance imaging (fMRI) to examine the neural basis of extreme multilingual language control in a group of 50 multilingual participants. Comparing brain responses arising during simultaneous interpretation (SI) with those arising during simultaneous repetition revealed activation of regions known to be involved in speech perception and production, alongside a network incorporating the caudate nucleus that is known to be implicated in domain-general cognitive control. The similarity between the networks underlying bilingual language control and general executive control supports the notion that the frequently reported bilingual advantage on executive tasks stems from the day-to-day demands of language control in the multilingual brain. We examined neural correlates of the management of simultaneity by correlating brain activity during interpretation with the duration of simultaneous speaking and hearing. This analysis showed significant modulation of the putamen by the duration of simultaneity. Our findings suggest that, during SI, the caudate nucleus is implicated in the overarching selection and control of the lexico-semantic system, while the putamen is implicated in ongoing control of language output. These findings provide the first clear dissociation of specific dorsal striatum structures in polyglot language control, roles that are consistent with previously described involvement of these regions in nonlinguistic executive control.

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

    NARCIS (Netherlands)

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

    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. Sensory, hormonal, and neural basis of maternal aggression in rodents.

    Science.gov (United States)

    de Almeida, Rosa Maria Martins; Ferreira, Annabel; Agrati, Daniella

    2014-01-01

    We review existing knowledge of the neural, hormonal, and sensory basis of maternal aggression in the female rat. Although females may express different kinds of aggression, such as defense or dominance, the most frequent and conspicuous form of aggressive behavior among females is the one associated with motherhood. Maternal aggression occurs in various vertebrate and invertebrate species; however, our emphasis will be on maternal aggression in rats because most of the physiological investigations have been performed in this species. Firstly, we address those factors that predispose the female to attack, such as the endocrine profile, the maternal state, and the stimulation provided by the pups, as well as those that trigger the aggressive response, as the intruder's characteristics and the context. As the postpartum aggression is a fundamental component of the maternal repertoire, we emphasize its association with maternal motivation and the reduction of fear and anxiety in dams. Finally, we outline the neurocircuitry involved in the control of maternal aggression, stressing the role of the ventro-orbital region of prefrontal cortex and the serotoninergic system.

  11. 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.

  12. 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...

  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.

  14. 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.

  15. The potential of neural transplantation for brain repair and regeneration following traumatic brain injury

    Institute of Scientific and Technical Information of China (English)

    Dong Sun

    2016-01-01

    Traumatic brain injury is a major health problem worldwide. Currently, there is no effective treatment to improve neural structural repair and functional recovery of patients in the clinic. Cell transplantation is a potential strategy to repair and regenerate the injured brain. This review article summarized recent de-velopment in cell transplantation studies for post-traumatic brain injury brain repair with varying types of cell sources. It also discussed the potential of neural transplantation to repair/promote recovery of the injured brain following traumatic brain injury.

  16. 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.

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

    Institute of Scientific and Technical Information of China (English)

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

    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 stil 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 cel s and brain tumor stem cells in the tumor models. Results showed that chromosome instability occurred in brain tumor stem cells. The numbers of cytolysosomes and autophagosomes in brain tumor stem cells and induced neural stem cel s were lower and the proliferative activity was obviously stronger than that in normal neural stem cells. Normal neural stem cells could differentiate into glial fibril ary acidic protein-positive and microtubule associated protein-2-positive cells, which were also negative for nestin. However, glial fibril ary acidic protein/nestin, microtubule associated protein-2/nestin, and glial fibril ary acidic protein/microtubule associated protein-2 double-positive cells were found in induced neural stem cells and brain tumor stem cel s. Results indicate that induced neural stem cells are similar to brain tumor stem cells, and are possibly the source of brain tumor stem cells.

  18. 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.

  19. Neural basis of individualistic and collectivistic views of self.

    Science.gov (United States)

    Chiao, Joan Y; Harada, Tokiko; Komeda, Hidetsugu; Li, Zhang; Mano, Yoko; Saito, Daisuke; Parrish, Todd B; Sadato, Norihiro; Iidaka, Tetsuya

    2009-09-01

    Individualism and collectivism refer to cultural values that influence how people construe themselves and their relation to the world. Individualists perceive themselves as stable entities, autonomous from other people and their environment, while collectivists view themselves as dynamic entities, continually defined by their social context and relationships. Despite rich understanding of how individualism and collectivism influence social cognition at a behavioral level, little is known about how these cultural values modulate neural representations underlying social cognition. Using cross-cultural functional magnetic resonance imaging (fMRI), we examined whether the cultural values of individualism and collectivism modulate neural activity within medial prefrontal cortex (MPFC) during processing of general and contextual self judgments. Here, we show that neural activity within the anterior rostral portion of the MPFC during processing of general and contextual self judgments positively predicts how individualistic or collectivistic a person is across cultures. These results reveal two kinds of neural representations of self (eg, a general self and a contextual self) within MPFC and demonstrate how cultural values of individualism and collectivism shape these neural representations.

  20. Neural activity control of neural stem cells and SVZ niche response to brain injury

    OpenAIRE

    Páez González, Patricia

    2014-01-01

    Patricia Paez-Gonzalez Kuo Lab, Dept. of Cell Biology, Duke University Medical Center, NC,USA. Date: 11/16/2014 Utilizing stem cells in the adult brain hold great promise for regenerative medicine. Harnessing ability of adult neural stem cells (NSCs) to generate new neurons or other types of brain cells may provide much needed therapies for patients suffering from brain injuries or neuro-degenerative diseases such as Parkinson’s, Scizophrenia, or Alzheimer’s disease. However...

  1. Drosophila neural stem cells in brain development and tumor formation.

    Science.gov (United States)

    Jiang, Yanrui; Reichert, Heinrich

    2014-01-01

    Neuroblasts, the neural stem cells in Drosophila, generate the complex neural structure of the central nervous system. Significant progress has been made in understanding the mechanisms regulating the self-renewal, proliferation, and differentiation in Drosophila neuroblast lineages. Deregulation of these mechanisms can lead to severe developmental defects and the formation of malignant brain tumors. Here, the authors review the molecular genetics of Drosophila neuroblasts and discuss some recent advances in stem cell and cancer biology using this model system.

  2. Neural Basis of Working Memory Enhancement after Acute Aerobic Exercise: fMRI Study of Preadolescent Children.

    Science.gov (United States)

    Chen, Ai-Guo; Zhu, Li-Na; Yan, Jun; Yin, Heng-Chan

    2016-01-01

    Working memory lies at the core of cognitive function and plays a crucial role in children's learning, reasoning, problem solving, and intellectual activity. Behavioral findings have suggested that acute aerobic exercise improves children's working memory; however, there is still very little knowledge about whether a single session of aerobic exercise can alter working memory's brain activation patterns, as assessed by functional magnetic resonance imaging (fMRI). Therefore, we investigated the effect of acute moderate-intensity aerobic exercise on working memory and its brain activation patterns in preadolescent children, and further explored the neural basis of acute aerobic exercise on working memory in these children. We used a within-subjects design with a counterbalanced order. Nine healthy, right-handed children were scanned with a Siemens MAGNETOM Trio 3.0 Tesla magnetic resonance imaging scanner while they performed a working memory task (N-back task), following a baseline session and a 30-min, moderate-intensity exercise session. Compared with the baseline session, acute moderate-intensity aerobic exercise benefitted performance in the N-back task, increasing brain activities of bilateral parietal cortices, left hippocampus, and the bilateral cerebellum. These data extend the current knowledge by indicating that acute aerobic exercise enhances children's working memory, and the neural basis may be related to changes in the working memory's brain activation patterns elicited by acute aerobic exercise.

  3. Neural Basis of Working Memory Enhancement after Acute Aerobic Exercise: fMRI Study of Preadolescent Children

    Directory of Open Access Journals (Sweden)

    Ai-Guo Chen

    2016-11-01

    Full Text Available Working memory lies at the core of cognitive function and plays a crucial role in children’s learning, reasoning, problem solving, and intellectual activity. Behavioral findings have suggested that acute aerobic exercise improves children’s working memory; however, there is still very little knowledge about whether a single session of aerobic exercise can alter working memory’s brain activation patterns, as assessed by functional magnetic resonance imaging (fMRI. Therefore, we investigated the effect of acute moderate-intensity aerobic exercise on working memory and its brain activation patterns in preadolescent children, and further explored the neural basis of acute aerobic exercise on working memory in these children. We used a within-subjects design with a counterbalanced order. Nine healthy, right-handed children were scanned with a Siemens MAGNETOM Trio 3.0 Tesla magnetic resonance imaging scanner while they performed a working memory task (N-back task, following a baseline session and a 30-min, moderate-intensity exercise session. Compared with the baseline session, acute moderate-intensity aerobic exercise benefitted performance in the N-back task, increasing brain activities of bilateral parietal cortices, left hippocampus, and the bilateral cerebellum. These data extend the current knowledge by indicating that acute aerobic exercise enhances children’s working memory, and the neural basis may be related to changes in the working memory’s brain activation patterns elicited by acute aerobic exercise.

  4. Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

    Science.gov (United States)

    Burken, John J.

    2005-01-01

    This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

  5. 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...

  6. Incidental regulation of attraction: The neural basis of the derogation of attractive alternatives in romantic relationships

    NARCIS (Netherlands)

    Meyer, M.L.; Berkman, E.T.; Karremans, J.C.T.M.; Lieberman, M.D.

    2011-01-01

    Although a great deal of research addresses the neural basis of deliberate and intentional emotion-regulation strategies, less attention has been paid to the neural mechanisms involved in implicit forms of emotion regulation. Behavioural research suggests that romantically involved participants impl

  7. 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.

  8. 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.

  9. Tinnitus and neural plasticity of the brain

    NARCIS (Netherlands)

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

    2007-01-01

    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. Institute for Brain and Neural Systems

    Science.gov (United States)

    2009-10-06

    data. In Proceedings of the International Conference on Artificial Neural Networks (ICANN), pages 308–313. Agarwal, S., Awan, A., and Roth , D. (2004...University of Edinburgh, Scotland . Guyon, I., Weston, J., Barnhill, S., and Vapnik, V. (2002). Gene selection for cancer classification using support

  11. The Neural Basis of Long-Distance Navigation in Birds.

    Science.gov (United States)

    Mouritsen, Henrik; Heyers, Dominik; Güntürkün, Onur

    2016-01-01

    Migratory birds can navigate over tens of thousands of kilometers with an accuracy unobtainable for human navigators. To do so, they use their brains. In this review, we address how birds sense navigation- and orientation-relevant cues and where in their brains each individual cue is processed. When little is currently known, we make educated predictions as to which brain regions could be involved. We ask where and how multisensory navigational information is integrated and suggest that the hippocampus could interact with structures that represent maps and compass information to compute and constantly control navigational goals and directions. We also suggest that the caudolateral nidopallium could be involved in weighing conflicting pieces of information against each other, making decisions, and helping the animal respond to unexpected situations. Considering the gaps in current knowledge, some of our suggestions may be wrong. However, our main aim is to stimulate further research in this fascinating field.

  12. Supervised learning for neural manifold using spatiotemporal brain activity

    Science.gov (United States)

    Kuo, Po-Chih; Chen, Yong-Sheng; Chen, Li-Fen

    2015-12-01

    Objective. Determining the means by which perceived stimuli are compactly represented in the human brain is a difficult task. This study aimed to develop techniques for the construction of the neural manifold as a representation of visual stimuli. Approach. We propose a supervised locally linear embedding method to construct the embedded manifold from brain activity, taking into account similarities between corresponding stimuli. In our experiments, photographic portraits were used as visual stimuli and brain activity was calculated from magnetoencephalographic data using a source localization method. Main results. The results of 10 × 10-fold cross-validation revealed a strong correlation between manifolds of brain activity and the orientation of faces in the presented images, suggesting that high-level information related to image content can be revealed in the brain responses represented in the manifold. Significance. Our experiments demonstrate that the proposed method is applicable to investigation into the inherent patterns of brain activity.

  13. Neural correlates of establishing, maintaining, and switching brain states.

    Science.gov (United States)

    Tang, Yi-Yuan; Rothbart, Mary K; Posner, Michael I

    2012-06-01

    Although the study of brain states is an old one in neuroscience, there has been growing interest in brain state specification owing to MRI studies tracing brain connectivity at rest. In this review, we summarize recent research on three relatively well-described brain states: the resting, alert, and meditation states. We explore the neural correlates of maintaining a state or switching between states, and argue that the anterior cingulate cortex and striatum play a critical role in state maintenance, whereas the insula has a major role in switching between states. Brain state may serve as a predictor of performance in a variety of perceptual, memory, and problem solving tasks. Thus, understanding brain states is critical for understanding human performance.

  14. The brain basis of a "consciousness monitor": scientific and medical significance.

    Science.gov (United States)

    Baars, B J

    2001-06-01

    Surgical patients under anesthesia can wake up unpredictably and be exposed to intense, traumatic pain. Current medical techniques cannot maintain depth of anesthesia at a perfectly stable and safe level; the depth of unconsciousness may change from moment to moment. Without an effective consciousness monitor anesthesiologists may not be able to adjust dosages in time to protect patients from pain. An estimated 40,000 to 200,000 midoperative awakenings may occur in the United States annually. E. R. John and coauthors present the scientific basis of a practical "consciousness monitor" in two articles. One article is empirical and shows widespread and consistent electrical field changes across subjects and anesthetic agents as soon as consciousness is lost; these changes reverse when consciousness is regained afterward. These findings form the basis of a surgical consciousness monitor that recently received approval from the U.S. Food and Drug Administration. This may be the first practical application of research on the brain basis of consciousness. The other John article suggests theoretical explanations at three levels, a neurophysiological account of anesthesia, a neural dynamic account of conscious and unconscious states, and an integrative field theory. Of these, the neurophysiology is the best understood. Neural dynamics is evolving rapidly, with several alternative points of view. The field theory sketched here is the most novel and controversial.

  15. 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.

  16. The neural basis of visual behaviors in the larval zebrafish.

    Science.gov (United States)

    Portugues, Ruben; Engert, Florian

    2009-12-01

    We review visually guided behaviors in larval zebrafish and summarise what is known about the neural processing that results in these behaviors, paying particular attention to the progress made in the last 2 years. Using the examples of the optokinetic reflex, the optomotor response, prey tracking and the visual startle response, we illustrate how the larval zebrafish presents us with a very promising model vertebrate system that allows neurocientists to integrate functional and behavioral studies and from which we can expect illuminating insights in the near future.

  17. Satisfiability of logic programming based on radial basis function neural networks

    Science.gov (United States)

    Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged; Choon, Ong Hong

    2014-07-01

    In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.

  18. Satisfiability of logic programming based on radial basis function neural networks

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-07-10

    In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.

  19. 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

  20. Neural basis of reward anticipation and its genetic determinants.

    Science.gov (United States)

    Jia, Tianye; Macare, Christine; Desrivières, Sylvane; Gonzalez, Dante A; Tao, Chenyang; Ji, Xiaoxi; Ruggeri, Barbara; Nees, Frauke; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia J; Dove, Rachel; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny A; Heinz, Andreas; Ittermann, Bernd; Lathrop, Mark; Lemaitre, Hervé; Martinot, Jean-Luc; Paus, Tomáš; Pausova, Zdenka; Poline, Jean-Baptiste; Rietschel, Marcella; Robbins, Trevor; Smolka, Michael N; Müller, Christian P; Feng, Jianfeng; Rothenfluh, Adrian; Flor, Herta; Schumann, Gunter

    2016-04-05

    Dysfunctional reward processing is implicated in various mental disorders, including attention deficit hyperactivity disorder (ADHD) and addictions. Such impairments might involve different components of the reward process, including brain activity during reward anticipation. We examined brain nodes engaged by reward anticipation in 1,544 adolescents and identified a network containing a core striatal node and cortical nodes facilitating outcome prediction and response preparation. Distinct nodes and functional connections were preferentially associated with either adolescent hyperactivity or alcohol consumption, thus conveying specificity of reward processing to clinically relevant behavior. We observed associations between the striatal node, hyperactivity, and the vacuolar protein sorting-associated protein 4A (VPS4A) gene in humans, and the causal role of Vps4 for hyperactivity was validated in Drosophila Our data provide a neurobehavioral model explaining the heterogeneity of reward-related behaviors and generate a hypothesis accounting for their enduring nature.

  1. The neural basis of belief updating and rational decision making.

    Science.gov (United States)

    Achtziger, Anja; Alós-Ferrer, Carlos; Hügelschäfer, Sabine; Steinhauser, Marco

    2014-01-01

    Rational decision making under uncertainty requires forming beliefs that integrate prior and new information through Bayes' rule. Human decision makers typically deviate from Bayesian updating by either overweighting the prior (conservatism) or overweighting new information (e.g. the representativeness heuristic). We investigated these deviations through measurements of electrocortical activity in the human brain during incentivized probability-updating tasks and found evidence of extremely early commitment to boundedly rational heuristics. Participants who overweight new information display a lower sensibility to conflict detection, captured by an event-related potential (the N2) observed around 260 ms after the presentation of new information. Conservative decision makers (who overweight prior probabilities) make up their mind before new information is presented, as indicated by the lateralized readiness potential in the brain. That is, they do not inhibit the processing of new information but rather immediately rely on the prior for making a decision.

  2. 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.

  3. 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.

  4. The Neural Basis of Individual Face and Object Perception

    Science.gov (United States)

    Watson, Rebecca; Huis in ’t Veld, Elisabeth M. J.; de Gelder, Beatrice

    2016-01-01

    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 utilized which includes different exemplars (for example, non-face stimuli along with faces), is memory-neutral, and taps into identity matching across orientation and across viewpoint change. The goal of this study was to test a previously behaviourally tested 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 matching 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 versus upright faces, and to upright, as compared to inverted shoes. These results are discussed in relation to previous studies and to potential future research within prosopagnosic individuals. PMID:26973490

  5. Neural localization of addicsin in mouse brain.

    Science.gov (United States)

    Akiduki, Saori; Ochiishi, Tomoyo; Ikemoto, Mitsushi J

    2007-10-22

    Addicsin is a member of the prenylated Rab acceptor (PRA) 1 domain family and a murine homolog of the rat glutamate-transporter-associated protein 3-18 (GTRAP3-18). This protein is considered to function as a modulator of the neural glutamate transporter excitatory amino acid carrier 1 (EAAC1). However, its molecular functions remain largely unknown. Here, we examined the regional and cellular localization of addicsin in the central nervous system (CNS) by using a newly generated antibody specific for the protein. Distribution analysis by Western blot and immunohistochemistry demonstrated that the protein was widely distributed in various regions of the mature CNS, including the olfactory bulbs, cerebral cortex, amygdala, hippocampus CA1-3 fields, dentate gyrus, and cerebellum. Double immunofluorescence analysis revealed that addicsin was expressed in the somata of principal neurons in the CNS such as the pyramidal cells and gamma-aminobutyric acid (GABA)-ergic interneurons scattered in the hippocampal formation. Furthermore, the protein showed pre-synaptic localization in the stratum lucidum of the CA3 field of the hippocampal formation. Subcellular localization analysis of highly purified synaptic fractions prepared from mouse forebrain supported the cytoplasmic and pre-synaptic distribution of addicsin. These results suggest that addicsin has neural expression and may play crucial roles in the basic physiological functions of the mature CNS.

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

    Science.gov (United States)

    Yau, Jeffrey M; Kim, Sung Soo; Thakur, Pramodsingh H; Bensmaia, Sliman J

    2016-02-01

    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.

  7. 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 BACKGROUND: 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. METHODOLOGY/PRINCIPAL FINDINGS: 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. CONCLUSIONS/SIGNIFICANCE: 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.

  8. 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

    Background 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). Methodology/Principal Findings 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. Conclusions/Significance 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. PMID:22745745

  9. 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.

  10. Radial basis function neural network for power system load-flow

    Energy Technology Data Exchange (ETDEWEB)

    Karami, A.; Mohammadi, M.S. [Faculty of Engineering, The University of Guilan, P.O. Box 41635-3756, Rasht (Iran)

    2008-01-15

    This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)

  11. Brain tumor grading based on Neural Networks and Convolutional Neural Networks.

    Science.gov (United States)

    Yuehao Pan; Weimin Huang; Zhiping Lin; Wanzheng Zhu; Jiayin Zhou; Wong, Jocelyn; Zhongxiang Ding

    2015-08-01

    This paper studies brain tumor grading using multiphase MRI images and compares the results with various configurations of deep learning structure and baseline Neural Networks. The MRI images are used directly into the learning machine, with some combination operations between multiphase MRIs. Compared to other researches, which involve additional effort to design and choose feature sets, the approach used in this paper leverages the learning capability of deep learning machine. We present the grading performance on the testing data measured by the sensitivity and specificity. The results show a maximum improvement of 18% on grading performance of Convolutional Neural Networks based on sensitivity and specificity compared to Neural Networks. We also visualize the kernels trained in different layers and display some self-learned features obtained from Convolutional Neural Networks.

  12. [Neural basis of self-face recognition: social aspects].

    Science.gov (United States)

    Sugiura, Motoaki

    2012-07-01

    Considering the importance of the face in social survival and evidence from evolutionary psychology of visual self-recognition, it is reasonable that we expect neural mechanisms for higher social-cognitive processes to underlie self-face recognition. A decade of neuroimaging studies so far has, however, not provided an encouraging finding in this respect. Self-face specific activation has typically been reported in the areas for sensory-motor integration in the right lateral cortices. This observation appears to reflect the physical nature of the self-face which representation is developed via the detection of contingency between one's own action and sensory feedback. We have recently revealed that the medial prefrontal cortex, implicated in socially nuanced self-referential process, is activated during self-face recognition under a rich social context where multiple other faces are available for reference. The posterior cingulate cortex has also exhibited this activation modulation, and in the separate experiment showed a response to attractively manipulated self-face suggesting its relevance to positive self-value. Furthermore, the regions in the right lateral cortices typically showing self-face-specific activation have responded also to the face of one's close friend under the rich social context. This observation is potentially explained by the fact that the contingency detection for physical self-recognition also plays a role in physical social interaction, which characterizes the representation of personally familiar people. These findings demonstrate that neuroscientific exploration reveals multiple facets of the relationship between self-face recognition and social-cognitive process, and that technically the manipulation of social context is key to its success.

  13. The neural basis of deictic shifting in linguistic perspective-taking in high-functioning autism.

    Science.gov (United States)

    Mizuno, Akiko; Liu, Yanni; Williams, Diane L; Keller, Timothy A; Minshew, Nancy J; Just, Marcel Adam

    2011-08-01

    Personal pronouns, such as 'I' and 'you', require a speaker/listener to continuously re-map their reciprocal relation to their referent, depending on who is saying the pronoun. This process, called 'deictic shifting', may underlie the incorrect production of these pronouns, or 'pronoun reversals', such as referring to oneself with the pronoun 'you', which has been reported in children with autism. The underlying neural basis of deictic shifting, however, is not understood, nor has the processing of pronouns been studied in adults with autism. The present study compared the brain activation pattern and functional connectivity (synchronization of activation across brain areas) of adults with high-functioning autism and control participants using functional magnetic resonance imaging in a linguistic perspective-taking task that required deictic shifting. The results revealed significantly diminished frontal (right anterior insula) to posterior (precuneus) functional connectivity during deictic shifting in the autism group, as well as reliably slower and less accurate behavioural responses. A comparison of two types of deictic shifting revealed that the functional connectivity between the right anterior insula and precuneus was lower in autism while answering a question that contained the pronoun 'you', querying something about the participant's view, but not when answering a query about someone else's view. In addition to the functional connectivity between the right anterior insula and precuneus being lower in autism, activation in each region was atypical, suggesting over reliance on individual regions as a potential compensation for the lower level of collaborative interregional processing. These findings indicate that deictic shifting constitutes a challenge for adults with high-functioning autism, particularly when reference to one's self is involved, and that the functional collaboration of two critical nodes, right anterior insula and precuneus, may play a

  14. 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.

  15. Psychophysical investigations into the neural basis of synaesthesia.

    Science.gov (United States)

    Ramachandran, V S; Hubbard, E M

    2001-05-07

    We studied two otherwise normal, synaesthetic subjects who 'saw' a specific colour every time they saw a specific number or letter. We conducted four experiments in order to show that this was a genuine perceptual experience rather than merely a memory association. (i) The synaesthetically induced colours could lead to perceptual grouping, even though the inducing numerals or letters did not. (ii) Synaesthetically induced colours were not experienced if the graphemes were presented peripherally. (iii) Roman numerals were ineffective: the actual number grapheme was required. (iv) If two graphemes were alternated the induced colours were also seen in alternation. However, colours were no longer experienced if the graphemes were alternated at more than 4 Hz. We propose that grapheme colour synaesthesia arises from 'cross-wiring' between the 'colour centre' (area V4 or V8) and the 'number area', both of which lie in the fusiform gyrus. We also suggest a similar explanation for the representation of metaphors in the brain: hence, the higher incidence of synaesthesia among artists and poets.

  16. Brain tumour classification using Gaussian decomposition and neural networks.

    Science.gov (United States)

    Arizmendi, Carlos; Sierra, Daniel A; Vellido, Alfredo; Romero, Enrique

    2011-01-01

    The development, implementation and use of computer-based medical decision support systems (MDSS) based on pattern recognition techniques holds the promise of substantially improving the quality of medical practice in diagnostic and prognostic tasks. In this study, the core of a decision support system for brain tumour classification from magnetic resonance spectroscopy (MRS) data is presented. It combines data pre-processing using Gaussian decomposition, dimensionality reduction using moving window with variance analysis, and classification using artificial neural networks (ANN). This combination of techniques is shown to yield high diagnostic classification accuracy in problems concerning diverse brain tumour pathologies, some of which have received little attention in the literature.

  17. Cellular basis of neuroepithelial bending during mouse spinal neural tube closure.

    Science.gov (United States)

    McShane, Suzanne G; Molè, Matteo A; Savery, Dawn; Greene, Nicholas D E; Tam, Patrick P L; Copp, Andrew J

    2015-08-15

    Bending of the neural plate at paired dorsolateral hinge points (DLHPs) is required for neural tube closure in the spinal region of the mouse embryo. As a step towards understanding the morphogenetic mechanism of DLHP development, we examined variations in neural plate cellular architecture and proliferation during closure. Neuroepithelial cells within the median hinge point (MHP) contain nuclei that are mainly basally located and undergo relatively slow proliferation, with a 7 h cell cycle length. In contrast, cells in the dorsolateral neuroepithelium, including the DLHP, exhibit nuclei distributed throughout the apico-basal axis and undergo rapid proliferation, with a 4 h cell cycle length. As the neural folds elevate, cell numbers increase to a greater extent in the dorsolateral neural plate that contacts the surface ectoderm, compared with the more ventromedial neural plate where cells contact paraxial mesoderm and notochord. This marked increase in dorsolateral cell number cannot be accounted for solely on the basis of enhanced cell proliferation in this region. We hypothesised that neuroepithelial cells may translocate in a ventral-to-dorsal direction as DLHP formation occurs, and this was confirmed by vital cell labelling in cultured embryos. The translocation of cells into the neural fold, together with its more rapid cell proliferation, leads to an increase in cell density dorsolaterally compared with the more ventromedial neural plate. These findings suggest a model in which DLHP formation may proceed through 'buckling' of the neuroepithelium at a dorso-ventral boundary marked by a change in cell-packing density.

  18. Balanced Neural Architecture and the Idling Brain

    Directory of Open Access Journals (Sweden)

    Brent eDoiron

    2014-05-01

    Full Text Available A signature feature of cortical spike trains is their trial-to-trial variability. This variability is large in spontaneous conditions and is reduced when cortex is driven by a stimulus or task. Models of recurrent cortical networks with unstructured, yet balanced, excitation and inhibition generate variability consistent with evoked conditions. However, these models lack the long timescale fluctuations and large variability present in spontaneous conditions. We propose that global network architectures which support a large number of stable states (attractor networks allow balanced networks to capture key features of neural variability in both spontaneous and evoked conditions. We illustrate this using balanced spiking networks with clustered assembly, feedforward chain, and ring structures. By assuming that global network structure is related to stimulus preference, we show that signal correlations are related to the magnitude of correlations in the spontaneous state. In our models, the dynamics of spontaneous activity encompasses much of the possible evoked states, consistent with many experimental reports. Finally, we contrast the impact of stimulation on the trial-to-trial variability in attractor networks with that of strongly coupled spiking networks with chaotic firing rate instabilities, recently investigated by Ostojic (2014. We find that only attractor networks replicate an experimentally observed stimulus-induced quenching of trial-to-trial variability. In total, the comparison of the trial-variable dynamics of single neurons or neuron pairs during spontaneous and evoked activity can be a window into the global structure of balanced cortical networks.

  19. Balanced neural architecture and the idling brain.

    Science.gov (United States)

    Doiron, Brent; Litwin-Kumar, Ashok

    2014-01-01

    A signature feature of cortical spike trains is their trial-to-trial variability. This variability is large in the spontaneous state and is reduced when cortex is driven by a stimulus or task. Models of recurrent cortical networks with unstructured, yet balanced, excitation and inhibition generate variability consistent with evoked conditions. However, these models produce spike trains which lack the long timescale fluctuations and large variability exhibited during spontaneous cortical dynamics. We propose that global network architectures which support a large number of stable states (attractor networks) allow balanced networks to capture key features of neural variability in both spontaneous and evoked conditions. We illustrate this using balanced spiking networks with clustered assembly, feedforward chain, and ring structures. By assuming that global network structure is related to stimulus preference, we show that signal correlations are related to the magnitude of correlations in the spontaneous state. Finally, we contrast the impact of stimulation on the trial-to-trial variability in attractor networks with that of strongly coupled spiking networks with chaotic firing rate instabilities, recently investigated by Ostojic (2014). We find that only attractor networks replicate an experimentally observed stimulus-induced quenching of trial-to-trial variability. In total, the comparison of the trial-variable dynamics of single neurons or neuron pairs during spontaneous and evoked activity can be a window into the global structure of balanced cortical networks.

  20. 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.

  1. The role of BDNF in depression on the basis of its location in the neural circuitry

    Institute of Scientific and Technical Information of China (English)

    Hui YU; Zhe-yu CHEN

    2011-01-01

    Depression is one of the most prevalent and life-threatening forms of mental illnesses and the neural circuitry underlying depression remains incompletely understood. Most attention in the field has focused on hippocampal and frontal cortical regions for their roles in depression and antidepressant action. While these regions no doubt play important roles in the mental illness, there is compelling evi-dence that other brain regions are also involved. Brain-derived neurotrophic factor (BDNF) is broadly expressed in the developing and adult mammalian brain and has been implicated in development, neural regeneration, synaptic transmission, synaptic plasticity and neurogenesis. Recently BDNF has been shown to play an important role in the pathophysiology of depression, however there are con-troversial reports about the effects of BDNF on depression. Here, we present an overview of the current knowledge concerning BDNF actions and associated intracellular signaling in hippocampus, prefrontal cortex, nucleus accumbens (NAc) and amygdala as their rela-tion to depression.

  2. 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.

  3. Nonlinear Time-Varying Systems Identification Using Basis Sequence Expansions Combined with Neural Networks

    Institute of Scientific and Technical Information of China (English)

    顾成奎; 王正欧; 孙雅明

    2003-01-01

    A new method for identifying nonlinear time-varying systems with unknown structure is presented. The method extends the application area of basis sequence identification. The essential idea is to utilize the learning and nonlinear approximating ability of neural networks to model the non-linearity of the system, characterize time-varying dynamics of the system by the time-varying parametric vector of the network, then the parametric vector of the network is approximated by a weighted sum of known basis sequences. Because of black-box modeling ability of neural networks, the presented method can identify nonlinear time-varying systems with unknown structure. In order to improve the real-time capability of the algorithm, the neural network is trained by a simple fast learning algorithm based on local least squares presented by the authors. The effectiveness and the performance of the method are demonstrated by some simulation results.

  4. Filtered-X Radial Basis Function Neural Networks for Active Noise Control

    Directory of Open Access Journals (Sweden)

    Bambang Riyanto

    2004-05-01

    Full Text Available This paper presents active control of acoustic noise using radial basis function (RBF networks and its digital signal processor (DSP real-time implementation. The neural control system consists of two stages: first, identification (modeling of secondary path of the active noise control using RBF networks and its learning algorithm, and secondly neural control of primary path based on neural model obtained in the first stage. A tapped delay line is introduced in front of controller neural, and another tapped delay line is inserted between controller neural networks and model neural networks. A new algorithm referred to as Filtered X-RBF is proposed to account for secondary path effects of the control system arising in active noise control. The resulting algorithm turns out to be the filtered-X version of the standard RBF learning algorithm. We address centralized and decentralized controller configurations and their DSP implementation is carried out. Effectiveness of the neural controller is demonstrated by applying the algorithm to active noise control within a 3 dimension enclosure to generate quiet zones around error microphones. Results of the real-time experiments show that 10-23 dB noise attenuation is produced with moderate transient response.

  5. 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.

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

    NARCIS (Netherlands)

    van Dijk, M.T.; van Wingen, G.A.; van Lammeren, A.; Blom, R.M.; de Kwaasteniet, B.P.; Scholte, H.S.; Denys, D.

    2013-01-01

    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 underlyin

  7. 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…

  8. Growth hormone (GH), brain development and neural stem cells.

    Science.gov (United States)

    Waters, M J; Blackmore, D G

    2011-12-01

    A range of observations support a role for GH in development and function of the brain. These include altered brain structure in GH receptor null mice, and impaired cognition in GH deficient rodents and in a subgroup of GH receptor defective patients (Laron dwarfs). GH has been shown to alter neurogenesis, myelin synthesis and dendritic branching, and both the GH receptor and GH itself are expressed widely in the brain. We have found a population of neural stem cells which are activated by GH infusion, and which give rise to neurons in mice. These stem cells are activated by voluntary exercise in a GH-dependent manner. Given the findings that local synthesis of GH occurs in the hippocampus in response to a memory task, and that GH replacement improves memory and cognition in rodents and humans, these new observations warrant a reappraisal of the clinical importance of GH replacement in GH deficient states.

  9. [Hyperspectral remote sensing image classification based on radical basis function neural network].

    Science.gov (United States)

    Tan, Kun; Du, Pei-jun

    2008-09-01

    Based on the radial basis function neural network (RBFNN) theory and the specialty of hyperspectral remote sensing data, the effective feature extraction model was designed, and those extracted features were connected to the input layer of RBFNN, finally the classifier based on radial basis function neural network was constructed. The hyperspectral image with 64 bands of OMIS II made by Chinese was experimented, and the case study area was zhongguancun in Beijing. Minimum noise fraction (MNF) was conducted, and the former 20 components were extracted for further processing. The original data (20 dimension) of extraction by MNF, the texture transformation data (20 dimension) extracted from the former 20 components after MNF, and the principal component analysis data (20 dimension) of extraction were combined to 60 dimension. For classification by RBFNN, the sizes of training samples were less than 6.13% of the whole image. That classifier has a simple structure and fast convergence capacity, and can be easily trained. The classification precision of radial basis function neural network classifier is up to 69.27% in contrast with the 51.20% of back propagation neural network (BPNN) and 40. 88% of traditional minimum distance classification (MDC), so RBFNN classifier performs better than the other three classifiers. It proves that RBFNN is of validity in hyperspectral remote sensing classification.

  10. On the use of back propagation and radial basis function neural networks in surface roughness prediction

    Science.gov (United States)

    Markopoulos, Angelos P.; Georgiopoulos, Sotirios; Manolakos, Dimitrios E.

    2016-03-01

    Various artificial neural networks types are examined and compared for the prediction of surface roughness in manufacturing technology. The aim of the study is to evaluate different kinds of neural networks and observe their performance and applicability on the same problem. More specifically, feed-forward artificial neural networks are trained with three different back propagation algorithms, namely the adaptive back propagation algorithm of the steepest descent with the use of momentum term, the back propagation Levenberg-Marquardt algorithm and the back propagation Bayesian algorithm. Moreover, radial basis function neural networks are examined. All the aforementioned algorithms are used for the prediction of surface roughness in milling, trained with the same input parameters and output data so that they can be compared. The advantages and disadvantages, in terms of the quality of the results, computational cost and time are identified. An algorithm for the selection of the spread constant is applied and tests are performed for the determination of the neural network with the best performance. The finally selected neural networks can satisfactorily predict the quality of the manufacturing process performed, through simulation and input-output surfaces for combinations of the input data, which correspond to milling cutting conditions.

  11. Vector control of wind turbine on the basis of the fuzzy selective neural net*

    Science.gov (United States)

    Engel, E. A.; Kovalev, I. V.; Engel, N. E.

    2016-04-01

    An article describes vector control of wind turbine based on fuzzy selective neural net. Based on the wind turbine system’s state, the fuzzy selective neural net tracks an maximum power point under random perturbations. Numerical simulations are accomplished to clarify the applicability and advantages of the proposed vector wind turbine’s control on the basis of the fuzzy selective neuronet. The simulation results show that the proposed intelligent control of wind turbine achieves real-time control speed and competitive performance, as compared to a classical control model with PID controllers based on traditional maximum torque control strategy.

  12. Investigating the neural basis of empathy by EEG hyperscanning during a Third Party Punishment.

    Science.gov (United States)

    Astolfi, Laura; Toppi, Jlenia; Casper, Chantal; Freitag, Christine; Mattia, Donatella; Babiloni, Fabio; Ciaramidaro, Angela; Siniatchkin, Michael

    2015-01-01

    The recently developed technique of hyperscanning consists of the simultaneous recording of brain activity from multiple subjects involved in social interaction. The multivariate analysis of data coming from different subjects allows to model a system made of multiple brains interacting, and to characterize it in relation with different processes at the basis of social cognition. In this study, we investigate the empathy established between two subjects during a Third Party Punishment paradigm, in terms of the properties of the multiple-brain network obtained from EEG hyperscanning. Preliminary results show that significantly different multiple-brain network structures characterize a social situation operated by a human agent with respect to a computer based condition, and that the different levels of empathy induced by a fair or unfair treatment received by one of the subjects are characterized by denser inter-subjects connectivity and lower divisibility in the two single brain networks.

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

    Science.gov (United States)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

    2014-07-01

    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 (Tp: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.

  14. 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.

  15. Perceptual awareness and its neural basis: bridging experimental and theoretical paradigms.

    Science.gov (United States)

    Raffone, Antonino; Srinivasan, Narayanan; van Leeuwen, Cees

    2014-05-05

    Understanding consciousness is a major scientific challenge of our times, and perceptual awareness is an integral part of that challenge. This Theme Issue aims to provide a timely focus on crucial insights from leading scientists on perceptual awareness and its neural basis. The issue refers to key research questions and findings in perceptual awareness research and aims to be a catalyst for further research, by bringing together the state-of-the-art. It shows how bridges are being built between empirical and theoretical research and proposes new directions for the study of multisensory awareness and the role of the states of the body therein. In this introduction, we highlight crucial problems that have characterized the development of the study of perceptual awareness. We then provide an overview of major experimental and theoretical paradigms related to perceptual awareness and its neural basis. Finally, we present an overview of the Theme Issue, with reference to the contributed articles and their relationships.

  16. The flexible brain. On mind and brain, neural darwinism and psychiatry.

    Science.gov (United States)

    den Boer, J A

    1997-09-01

    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. Investigators in biological psychiatry have hardly ever taken a clear position in this discussion, whereas we believe it is important that the conclusions drawn from biological research are embedded in a theoretical framework related to the mind-brain problem. In this article the thesis is defended that the theory of neural darwinism represents a major step forward and may bridge previous distinctions between biological, clinical and social psychiatry.

  17. Automated Brain Image classification using Neural Network Approach and Abnormality Analysis

    Directory of Open Access Journals (Sweden)

    P.Muthu Krishnammal

    2015-06-01

    Full Text Available Image segmentation of surgical images plays an important role in diagnosis and analysis the anatomical structure of human body. Magnetic Resonance Imaging (MRI helps in obtaining a structural image of internal parts of the body. This paper aims at developing an automatic support system for stage classification using learning machine and to detect brain Tumor by fuzzy clustering methods to detect the brain Tumor in its early stages and to analyze anatomical structures. The three stages involved are: feature extraction using GLCM and the tumor classification using PNN-RBF network and segmentation using SFCM. Here fast discrete curvelet transformation is used to analyze texture of an image which be used as a base for a Computer Aided Diagnosis (CAD system .The Probabilistic Neural Network with radial basis function is employed to implement an automated Brain Tumor classification. It classifies the stage of Brain Tumor that is benign, malignant or normal automatically. Then the segmentation of the brain abnormality using Spatial FCM and the severity of the tumor is analysed using the number of tumor cells in the detected abnormal region.The proposed method reports promising results in terms of training performance and classification accuracies.

  18. The neural sociometer: brain mechanisms underlying state self-esteem.

    Science.gov (United States)

    Eisenberger, Naomi I; Inagaki, Tristen K; Muscatell, Keely A; Byrne Haltom, Kate E; Leary, Mark R

    2011-11-01

    On the basis of the importance of social connection for survival, humans may have evolved a "sociometer"-a mechanism that translates perceptions of rejection or acceptance into state self-esteem. Here, we explored the neural underpinnings of the sociometer by examining whether neural regions responsive to rejection or acceptance were associated with state self-esteem. Participants underwent fMRI while viewing feedback words ("interesting," "boring") ostensibly chosen by another individual (confederate) to describe the participant's previously recorded interview. Participants rated their state self-esteem in response to each feedback word. Results demonstrated that greater activity in rejection-related neural regions (dorsal ACC, anterior insula) and mentalizing regions was associated with lower-state self-esteem. Additionally, participants whose self-esteem decreased from prescan to postscan versus those whose self-esteem did not showed greater medial prefrontal cortical activity, previously associated with self-referential processing, in response to negative feedback. Together, the results inform our understanding of the origin and nature of our feelings about ourselves.

  19. 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.

  20. 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.

  1. Spectral basis neural networks for real-time travel time forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Park, D.; Rilett, L.R.; Han, G.

    1999-12-01

    This paper examines how real-time information gathered as part of intelligent transportation systems can be used to predict link travel times for one through five time periods ahead (of 5-min duration). The study employed a spectral basis artificial neural network (SNN) that utilizes a sinusoidal transformation technique to increase the linear separability of the input features. Link travel times from Houston that had been collected as part of the automatic vehicle identification system of the TranStar system were used as a test bed. It was found that the SNN outperformed a conventional artificial neural network and gave similar results to that of modular neural networks. However, the SNN requires significantly less effort on the part of the modeler than modular neural networks. The results, of the best SNN were compared with conventional link travel time prediction techniques including a Kalman filtering model, exponential smoothing model, historical profile, and real-time profile. It was found that the SNN gave the best overall results.

  2. 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.

  3. Neural repair in the adult brain [version 1; referees: 3 approved

    OpenAIRE

    Sebastian Jessberger

    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 rep...

  4. 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.

  5. Neural consequences of competing stimuli in both visual hemifields: a physiological basis for visual extinction.

    Science.gov (United States)

    Fink, G R; Driver, J; Rorden, C; Baldeweg, T; Dolan, R J

    2000-04-01

    We used positron emission tomography in healthy volunteers to test hemispheric rivalry theories for normal and pathological spatial attention, which provide an influential account of contralesional extinction on bilateral stimulation after unilateral brain injury. Subjects reported visual characters presented either unilaterally or bilaterally. An extinction-like pattern was found behaviorally, with characters in one hemifield reported less accurately when competing characters appeared in the other hemifield. Differences in neural activity for unilateral minus bilateral conditions revealed greater activation of striate and extrastriate areas for stimuli presented without competing stimuli in the other hemifield. Thus, simultaneous bilateral stimulation led to a significant reduction in response by spatiotopic visual cortex contralateral to a particular stimulus. These data provide physiological support for interhemispheric rivalry in the intact human brain, and demonstrate that such competition impacts at early levels of perceptual processing.

  6. 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.

  7. Reconstruction of virtual neural circuits in an insect brain

    Directory of Open Access Journals (Sweden)

    Shigehiro Namiki

    2009-09-01

    Full Text Available The reconstruction of large-scale nervous systems represents a major scientific and engineering challenge in current neuroscience research that needs to be resolved in order to understand the emergent properties of such systems. We focus on insect nervous systems because they represent a good compromise between architectural simplicity and the ability to generate a rich behavioral repertoire. In insects, several sensory maps have been reconstructed so far. We provide an overview over this work including our reconstruction of population activity in the primary olfactory network, the antennal lobe. Our reconstruction approach, that also provides functional connectivity data, will be refined and extended to allow the building of larger scale neural circuits up to entire insect brains, from sensory input to motor output.

  8. On-line Cutting Quality Recognition in Milling Using a Radical Basis Function Neural Network

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Tool wear, chatter vibration, chip breaking and built-up edge are main phenomena to be monitored in modern manufacturing processes, which are considered as important factors to the quality of products.They are closely related to the cutting parameters, which are to be selected in manufacturing process.However, it is very difficult to measure directly the cutting quality based on on-line monitoring.In this study, the relationship between the cutting parameters and cutting quality is analyzed.A Radical Basis Function (RBF) neural network based on-line quality recognition scheme is also presented, which monitors the level of surface roughness.The experimental results reveal that the RBF neural network has a high prediction success rate.

  9. An efficient learning algorithm for improving generalization performance of radial basis function neural networks.

    Science.gov (United States)

    Wang, Z O; Zhu, T

    2000-01-01

    This paper presents an efficient recursive learning algorithm for improving generalization performance of radial basis function (RBF) neural networks. The approach combines the rival penalized competitive learning (PRCL) [Xu, L., Kizyzak, A. & Oja, E. (1993). Rival penalized competitive learning for clustering analysis, RBF net and curve detection, IEEE Transactions on Neural Networks, 4, 636-649] and the regularized least squares (RLS) to provide an efficient and powerful procedure for constructing a minimal RBF network that generalizes very well. The RPCL selects the number of hidden units of network and adjusts centers, while the RLS constructs the parsimonious network and estimates the connection weights. In the RLS we derived a simple recursive algorithm, which needs no matrix calculation, and so largely reduces the computational cost. This combined algorithm significantly enhances the generalization performance and the real-time capability of the RBF networks. Simulation results of three different problems demonstrate much better generalization performance of the present algorithm over other existing similar algorithms.

  10. Prediction Study on PCI Failure of Reactor Fuel Based on a Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Xinyu Wei

    2016-01-01

    Full Text Available Pellet-clad interaction (PCI is one of the major issues in fuel rod design and reactor core operation in water cooled reactors. The prediction of fuel rod failure by PCI is studied in this paper by the method of radial basis function neural network (RBFNN. The neural network is built through the analysis of the existing experimental data. It is concluded that it is a suitable way to reduce the calculation complexity. A self-organized RBFNN is used in our study, which can vary its structure dynamically in order to maintain the prediction accuracy. For the purpose of the appropriate network complexity and overall computational efficiency, the hidden neurons in the RBFNN can be changed online based on the neuron activity and mutual information. The presented method is tested by the experimental data from the reference, and the results demonstrate its effectiveness.

  11. Identification of tartrazine and sunset yellow by fluorescence spectroscopy combined with radial basis function neural network

    Institute of Scientific and Technical Information of China (English)

    Jun Wang; Guoqing Chen; Tuo Zhu; Shumei Gao; Bailin Wei; Linna Bi

    2009-01-01

    @@ The fluorescence spectra of synthetic food dyes of sunset yellow and tartrazine are analyzed.The fluorescence peak wavelengths of sunset yellow and tartrazine are 576 and 569 nm, respectively, while the fluorescence spectra widths are 480-750 and 500-750 nm induced by ultraviolet light between 310-400 nm.The fluorescence spectra of sunset yellow overlap heavily with those of tartrazine, so it is diffic ult to distinguish them.Based on the principle of radial basis function neural network, a neural network is obtained from the training of the 14 groups of experimental data.The results show that the species of sunset yellow and tartrazine could be recognized accurately.This method has potential applications in other synthetic food dyes detection and food safety inspection.

  12. DENSENESS OF RADIAL-BASIS FUNCTIONS IN L2(Rn) AND ITS APPLICATIONS IN NEURAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    CHENTIANPING; CHENHONG

    1996-01-01

    The authors discuss problems of approximation to functions in L2 (Rn)and operators from L2(Rn1)to L2(Rn2)by Radial-Basis Functions. The results obtained solve the parblem of capability of RBF neural networks,a basic problem in neural networks.

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

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    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.

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

    Science.gov (United States)

    Polanco, Michael; Bawab, Sebastian; Yoon, Hargsoon

    2016-06-16

    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.

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

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    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.

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

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    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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. Neural repair in the adult brain [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Sebastian Jessberger

    2016-02-01

    Full Text Available 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.

  3. Design of Radial Basis Function Neural Networks for Software Effort Estimation

    Directory of Open Access Journals (Sweden)

    Ali Idri

    2010-07-01

    Full Text Available In spite of the several software effort estimation models developed over the last 30 years, providing accurate estimates of the software project under development is still unachievable goal. Therefore, many researchers are working on the development of new models and the improvement of the existing ones using artificial intelligence techniques such as: case-based reasoning, decision trees, genetic algorithms and neural networks. This paper is devoted to the design of Radial Basis Function Networks for software cost estimation. It shows the impact of the RBFN network structure, especially the number of neurons in the hidden layer and the widths of the basis function, on the accuracy of the produced estimates measured by means of MMRE and Pred indicators. The empirical study uses two different software project datasets namely, artificial COCOMO'81 and Tukutuku datasets.

  4. NFL-lipid nanocapsules for brain neural stem cell targeting in vitro and in vivo.

    Science.gov (United States)

    Carradori, Dario; Saulnier, Patrick; Préat, Véronique; des Rieux, Anne; Eyer, Joel

    2016-09-28

    The replacement of injured neurons by the selective stimulation of neural stem cells in situ represents a potential therapeutic strategy for the treatment of neurodegenerative diseases. The peptide NFL-TBS.40-63 showed specific interactions towards neural stem cells of the subventricular zone. The aim of our work was to produce a NFL-based drug delivery system able to target neural stem cells through the selective affinity between the peptide and these cells. NFL-TBS.40-63 (NFL) was adsorbed on lipid nanocapsules (LNC) whom targeting efficiency was evaluated on neural stem cells from the subventricular zone (brain) and from the central canal (spinal cord). NFL-LNC were incubated with primary neural stem cells in vitro or injected in vivo in adult rat brain (right lateral ventricle) or spinal cord (T10). NFL-LNC interactions with neural stem cells were different depending on the origin of the cells. NFL-LNC showed a preferential uptake by neural stem cells from the brain, while they did not interact with neural stem cells from the spinal cord. The results obtained in vivo correlate with the results observed in vitro, demonstrating that NFL-LNC represent a promising therapeutic strategy to selectively deliver bioactive molecules to brain neural stem cells.

  5. 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.

  6. 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.

  7. A constructive hybrid structure optimization methodology for radial basis probabilistic neural networks.

    Science.gov (United States)

    Huang, De-Shuang; Du, Ji-Xiang

    2008-12-01

    In this paper, a novel heuristic structure optimization methodology for radial basis probabilistic neural networks (RBPNNs) is proposed. First, a minimum volume covering hyperspheres (MVCH) algorithm is proposed to select the initial hidden-layer centers of the RBPNN, and then the recursive orthogonal least square algorithm (ROLSA) combined with the particle swarm optimization (PSO) algorithm is adopted to further optimize the initial structure of the RBPNN. The proposed algorithms are evaluated through eight benchmark classification problems and two real-world application problems, a plant species identification task involving 50 plant species and a palmprint recognition task. Experimental results show that our proposed algorithm is feasible and efficient for the structure optimization of the RBPNN. The RBPNN achieves higher recognition rates and better classification efficiency than multilayer perceptron networks (MLPNs) and radial basis function neural networks (RBFNNs) in both tasks. Moreover, the experimental results illustrated that the generalization performance of the optimized RBPNN in the plant species identification task was markedly better than that of the optimized RBFNN.

  8. Prediction of fMRI time series of a single voxel using radial basis function neural network

    Science.gov (United States)

    Song, Sutao; Zhang, Jiacai; Yao, Li

    2011-03-01

    A great deal of current literature regarding functional neuroimaging has elucidated the relationships of neurons distributed all over the brain. Modern neuroimaging techniques, such as the functional MRI (fMRI), provide a convenient tool for people to study the correlation among different voxels as well as the spatio-temporal patterns of brain activity. In this study, we present a computational model using radial basis function neural network (RBF-NN) to predict the fMRI voxel activation with the activation of other voxels acquired at the same time. The fMRI data from a visual images stimuli presentation experiment was separated into two sets; one was used to train the model, and the other to validate the accuracy or generalizability of the model. In the visual stimuli presentation experiment, the subject did simple one-back-repetition tasks when four categories of stimuli (houses, faces, cars, and cats) were presented. Voxel sets A and B were selected from fMRI data by two different voxel selection criterion: (1) Voxel set A are those activated for any kind of object stronger than the other three objects in regions of interest (ROIs) without correction (P=0.001); (2) Voxel set B are those activated for at least one of the categories of stimuli within the ROIs (FWE correction, P=0.05). RBF-NN regression models construct the nonlinear relationship between the activation of voxels in A and B. Our test results showed that RBF-NN can capture the nonlinear relationship existing in neurons and reveal the relationship between voxel's activation from different brain regions.

  9. 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.

  10. Amplification of neural stem cell proliferation by intermediate progenitor cells in Drosophila brain development

    Directory of Open Access Journals (Sweden)

    Bello Bruno C

    2008-02-01

    Full Text Available Abstract Background In the mammalian brain, neural stem cells divide asymmetrically and often amplify the number of progeny they generate via symmetrically dividing intermediate progenitors. Here we investigate whether specific neural stem cell-like neuroblasts in the brain of Drosophila might also amplify neuronal proliferation by generating symmetrically dividing intermediate progenitors. Results Cell lineage-tracing and genetic marker analysis show that remarkably large neuroblast lineages exist in the dorsomedial larval brain of Drosophila. These lineages are generated by brain neuroblasts that divide asymmetrically to self renew but, unlike other brain neuroblasts, do not segregate the differentiating cell fate determinant Prospero to their smaller daughter cells. These daughter cells continue to express neuroblast-specific molecular markers and divide repeatedly to produce neural progeny, demonstrating that they are proliferating intermediate progenitors. The proliferative divisions of these intermediate progenitors have novel cellular and molecular features; they are morphologically symmetrical, but molecularly asymmetrical in that key differentiating cell fate determinants are segregated into only one of the two daughter cells. Conclusion Our findings provide cellular and molecular evidence for a new mode of neurogenesis in the larval brain of Drosophila that involves the amplification of neuroblast proliferation through intermediate progenitors. This type of neurogenesis bears remarkable similarities to neurogenesis in the mammalian brain, where neural stem cells as primary progenitors amplify the number of progeny they generate through generation of secondary progenitors. This suggests that key aspects of neural stem cell biology might be conserved in brain development of insects and mammals.

  11. The neural basis of semantic and episodic forms of self-knowledge: insights from functional neuroimaging.

    Science.gov (United States)

    D'Argembeau, Arnaud; Salmon, Eric

    2012-01-01

    Throughout evolution, hominids have developed greater capacity to think about themselves in abstract and symbolic ways. This process has reached its apex in humans with the construction of a concept of self as a distinct entity with a personal history. This chapter provides a review of recent functional neuroimaging studies that have investigated the neural correlates of such "higher-level" aspects of the human self, focusing in particular on processes that allow individuals to consciously represent and reflect on their own personal attributes (semantic forms of self-knowledge) and experiences (episodic forms of self-knowledge). These studies point to the medial prefrontal cortex (MPFC) as a key neural structure for processing various kinds of self-referential information. We speculate that the MPFC may mediate dynamic processes that appraise and code the self-relatedness or self-relevance of information. This brain region may thus play a key role in creating the mental model of the self that is displayed in our mind at a given moment.

  12. 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.

  13. 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.

  14. Estimation of vegetation biophysical parameters by remote sensing using radial basis function neural network

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-hua; HUANG Jing-feng; WANG Jian-wen; WANG Xiu-zhen; LIU Zhan-yu

    2007-01-01

    Hyperspectral reflectance (350-2500 nm) data were recorded at two different sites of rice in two experiment fields including two cultivars, and three levels of nitrogen (N) application. Twenty-five Vegetation Indices (VIs) were used to predict the rice agronomic parameters including Leaf Area Index (LAI, m2 green leaf/m2 soil) and Green Leaf Chlorophyll Density (GLCD,mg chlorophyll/m2 soil) by the traditional regression models and Radial Basis Function Neural Network (RBF). RBF emerged as a variant of Artificial Neural Networks (ANNs) in the late 1980's. A large variety of training algorithms has been tested for training RBF networks. In this study, Original RBF (ORBF), Gradient Descent RBF (GDRBF), and Generalized Regression Neural Network (GRNN) were employed. Results showed that green waveband Normalized Difference Vegetation Index (NDVIgreen) and TCARI/OSAVI have the best prediction power for LAI by exponent model and ORBF respectively, and that TCARI/OSAVI has the best prediction power for GLCD by exponent model and GDRBF. The best performances of RBF are compared with the traditional models, showing that the relationship between VIs and agronomic variables are further improved when RBF is used.Compared with the best traditional models, ORBF using TCARI/OSAVI improves the prediction power for LAI by lowering the Root Mean Square Error (RMSE) for 0.1119, and GDRBF using TCARI/OSAVI improves the prediction power for GLCD by lowering the RMSE for 26.7853. It is concluded that RBF provides a useful exploratory and predictive tool when applied to the sensitive VIs.

  15. Neural basis of the undermining effect of monetary reward on intrinsic motivation.

    Science.gov (United States)

    Murayama, Kou; Matsumoto, Madoka; Izuma, Keise; Matsumoto, Kenji

    2010-12-07

    Contrary to the widespread belief that people are positively motivated by reward incentives, some studies have shown that performance-based extrinsic reward can actually undermine a person's intrinsic motivation to engage in a task. This "undermining effect" has timely practical implications, given the burgeoning of performance-based incentive systems in contemporary society. It also presents a theoretical challenge for economic and reinforcement learning theories, which tend to assume that monetary incentives monotonically increase motivation. Despite the practical and theoretical importance of this provocative phenomenon, however, little is known about its neural basis. Herein we induced the behavioral undermining effect using a newly developed task, and we tracked its neural correlates using functional MRI. Our results show that performance-based monetary reward indeed undermines intrinsic motivation, as assessed by the number of voluntary engagements in the task. We found that activity in the anterior striatum and the prefrontal areas decreased along with this behavioral undermining effect. These findings suggest that the corticobasal ganglia valuation system underlies the undermining effect through the integration of extrinsic reward value and intrinsic task value.

  16. An improved method using radial basis function neural networks to speed up optimization algorithms

    CERN Document Server

    Bazan, M; Russenschuck, Stephan

    2002-01-01

    The paper presents a method using radial basis function (RBF) neural networks to speed up deterministic search algorithms used for the optimization of superconducting magnets for the LHC accelerator project at CERN. The optimization of the iron yoke of the main LHC dipoles requires a number of numerical field computations per trial solution as the field quality depends on the excitation and local iron saturation in the yoke. This results in computation times of about 30 min for each objective function evaluation (on DEC-Alpha 600 /333). In this paper, we present a method for constructing an RBF neural network for a local approximation of the objective function. The computational time required for such a construction is negligible compared to the deterministic function evaluation, and, thus, yields a speed-up of the overall search process. The effectiveness of this method is demonstrated by means of two- and three-parametric optimization examples. The achieved speed-up of the search routine is up to 30%. (12 r...

  17. Radial Basis Function Neural Network Based Super-Resolution Restoration for an Underspled Image

    Institute of Scientific and Technical Information of China (English)

    苏秉华; 金伟其; 牛丽红

    2004-01-01

    To achieve restoration of high frequency information for an underspled and degraded low-resolution image, a nonlinear and real-time processing method-the radial basis function (RBF) neural network based super-resolution method of restoration is proposed. The RBF network configuration and processing method is suitable for a high resolution restoration from an underspled low-resolution image. The soft-competition learning scheme based on the k-means algorithm is used, and can achieve higher mapping approximation accuracy without increase in the network size. Experiments showed that the proposed algorithm can achieve a super-resolution restored image from an underspled and degraded low-resolution image, and requires a shorter training time when compared with the multiplayer perception (MLP) network.

  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

    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...... for decomposition of speech and noise by using a set of speech pattern models and a noise model(s), each realized as an HMM/RBF pattern model...

  19. Shape identification of electrocardiographic ST segment based on radial basis function neural network

    Institute of Scientific and Technical Information of China (English)

    LIU Hailong; TANG Jiling

    2007-01-01

    The types of myocardial ischemia can be revealed by electrocardiographic (ECG) ST segment.Effective measurement and electrocardiographic analysis of ST as well as calculation of displacement and shape change of ST segment can help doctors diagnose coronary heart disease and myocardial ischemia,especially for asymptomatic myocardial ischemia.Therefore,it is a very important subject in clinical practice to measure and classify the ECG ST segment.In this paper,we introduce a computerized automatic identification method of the electrocardiographic ST segment shape with radial basis function neural network based on adaptive fuzzy system,which has a better effect than other methods.It helps to analyze the reason of the ST segment change and confirm the position of myocardial ischemia,and is useful for doctor diagnosis.

  20. 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.).

  1. Radial Basis Function Neural Networks Based QSPR for the Prediction of log P

    Institute of Scientific and Technical Information of China (English)

    姚小军; 范波涛; 等

    2002-01-01

    Quantitative structure-property relationship(QSPR) method is used to study the correlation models between the structures of a set of diverse organic compounds and their log P.Molecular descriptors calculated from strucure alone are used to describe the molecular structures.A subset of the calcualted descriptors,selected using forward stepwise regression,is used in the QSPR models development.Multiple linear regression (MLR) and radial basis function neural networks (RBFNNs) are utilied to construct the linear and non-linear correlation model,respectively,The optimal QSPR model developed is based on a 7-17-1 RBFNNs architecture using sever calculated molecular descriptors .The root mean square errors in predictions for the training,predicting and overall data sets are 0.284,0.327 and 0.291 log P units respectively.

  2. The effect of apolipoprotein E4 on synchronous neural interactions in brain cultures.

    Science.gov (United States)

    Christopoulos, Vassilios; Georgopoulos, Angeliki; Georgopoulos, Apostolos P

    2015-06-01

    In a previous study, we assessed the synchronous neural interactions (SNI) in a developing neural network in brain cultures on multielectrode arrays (Christopoulos et al. in J Neural Eng 9:046008, 2012). Here, we report on the effects of apolipoprotein E4 (apoE4) on these neural interactions. We carried out six experiments (five using rodent brain cultures and one using neuroblastoma cultures) in which we recorded local field potentials (LFP) from 59 sites for several days in vitro under the following conditions. In one experiment, we added to the culture media triglyceride (TG)-rich lipoproteins from a human subject with the apoE4/4 genotype, whereas in the other experiments, we added recombinant human apoE4. We found that SNI in the apoE4-treated cultures had higher coefficient of SNI variation, as compared to control cultures. These findings further document the role of SNI as a fundamental aspect of the dynamic organization of neural networks (Langheim et al. in Proc Natl Acad Sci USA 103:455-459, 2006. doi: 10.1073/pnas.0509623102 ; Georgopoulos et al. in J Neural Eng 4:349-355, 2007) and extend the effect of apoE4 on SNI (Leuthold et al. in Exp Brain Res 226:525-536, 2013) across different brain species (human, rodents), apoE source (TG-rich lipoproteins, recombinant), neural signals (MEG, LFP), and brain network (intact brain, developing brain in vitro). To our knowledge, this is the first study of the effects of apoE4 on neural network function in vitro.

  3. 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.

  4. Review: Human Intracortical recording and neural decoding for brain-computer interfaces.

    Science.gov (United States)

    Brandman, David M; Cash, Sydney S; Hochberg, Leigh R

    2017-03-02

    Brain Computer Interfaces (BCIs) use neural information recorded from the brain for voluntary control of external devices. The development of BCI systems has largely focused on improving functional independence for individuals with severe motor impairments, including providing tools for communication and mobility. In this review, we describe recent advances in intracortical BCI technology and provide potential directions for further research.

  5. Analysis of Neural Stem Cells from Human Cortical Brain Structures In Vitro.

    Science.gov (United States)

    Aleksandrova, M A; Poltavtseva, R A; Marei, M V; Sukhikh, G T

    2016-05-01

    Comparative immunohistochemical analysis of the neocortex from human fetuses showed that neural stem and progenitor cells are present in the brain throughout the gestation period, at least from week 8 through 26. At the same time, neural stem cells from the first and second trimester fetuses differed by the distribution, morphology, growth, and quantity. Immunocytochemical analysis of neural stem cells derived from fetuses at different gestation terms and cultured under different conditions showed their differentiation capacity. Detailed analysis of neural stem cell populations derived from fetuses on gestation weeks 8-9, 18-20, and 26 expressing Lex/SSEA1 was performed.

  6. Neural correlates of induced motion perception in the human brain.

    Science.gov (United States)

    Takemura, Hiromasa; Ashida, Hiroshi; Amano, Kaoru; Kitaoka, Akiyoshi; Murakami, Ikuya

    2012-10-10

    A physically stationary stimulus surrounded by a moving stimulus appears to move in the opposite direction. There are similarities between the characteristics of this phenomenon of induced motion and surround suppression of directionally selective neurons in the brain. Here, functional magnetic resonance imaging was used to investigate the link between the subjective perception of induced motion and cortical activity. The visual stimuli consisted of a central drifting sinusoid surrounded by a moving random-dot pattern. The change in cortical activity in response to changes in speed and direction of the central stimulus was measured. The human cortical area hMT+ showed the greatest activation when the central stimulus moved at a fast speed in the direction opposite to that of the surround. More importantly, the activity in this area was the lowest when the central stimulus moved in the same direction as the surround and at a speed such that the central stimulus appeared to be stationary. The results indicate that the activity in hMT+ is related to perceived speed modulated by induced motion rather than to physical speed or a kinetic boundary. Early visual areas (V1, V2, V3, and V3A) showed a similar pattern; however, the relationship to perceived speed was not as clear as that in hMT+. These results suggest that hMT+ may be a neural correlate of induced motion perception and play an important role in contrasting motion signals in relation to their surrounding context and adaptively modulating our motion perception depending on the spatial context.

  7. Foraging under competition: the neural basis of input-matching in humans.

    Science.gov (United States)

    Mobbs, Dean; Hassabis, Demis; Yu, Rongjun; Chu, Carlton; Rushworth, Matthew; Boorman, Erie; Dalgleish, Tim

    2013-06-01

    Input-matching is a key mechanism by which animals optimally distribute themselves across habitats to maximize net gains based on the changing input values of food supply rate and competition. To examine the neural systems that underlie this rule in humans, we created a continuous-input foraging task where subjects had to decide to stay or switch between two habitats presented on the left and right of the screen. The subject's decision to stay or switch was based on changing input values of reward-token supply rate and competition density. High density of competition or low-reward token rate was associated with decreased chance of winning. Therefore, subjects attempted to maximize their gains by switching to habitats that possessed low competition density and higher token rate. When it was increasingly disadvantageous to be in a habitat, we observed increased activity in brain regions that underlie preparatory motor actions, including the dorsal anterior cingulate cortex and the supplementary motor area, as well as the insula, which we speculate may be involved in the conscious urge to switch habitats. Conversely, being in an advantageous habitat is associated with activity in the reward systems, namely the striatum and medial prefrontal cortex. Moreover, amygdala and dorsal putamen activity steered interindividual preferences in competition avoidance and pursuing reward. Our results suggest that input-matching decisions are made as a net function of activity in a distributed set of neural systems. Furthermore, we speculate that switching behaviors are related to individual differences in competition avoidance and reward drive.

  8. Combined eye tracking and fMRI reveals neural basis of linguistic predictions during sentence comprehension.

    Science.gov (United States)

    Bonhage, Corinna E; Mueller, Jutta L; Friederici, Angela D; Fiebach, Christian J

    2015-07-01

    It is widely agreed upon that linguistic predictions are an integral part of language comprehension. Yet, experimental proof of their existence remains challenging. Here, we introduce a new predictive eye gaze reading task combining eye tracking and functional magnetic resonance imaging (fMRI) that allows us to infer the existence and timing of linguistic predictions via anticipatory eye-movements. Participants read different types of word sequences (i.e., regular sentences, meaningless jabberwocky sentences, non-word lists) up to the pre-final word. The final target word was displayed with a temporal delay and its screen position was dependent on the syntactic word category (nouns vs verbs). During the delay, anticipatory eye-movements into the correct target word area were indicative of linguistic predictions. For fMRI analysis, the predictive sentence conditions were contrasted to the non-word condition, with the anticipatory eye-movements specifying differences in timing across conditions. A conjunction analysis of both sentence conditions revealed the neural substrate of word category prediction, namely a distributed network of cortical and subcortical brain regions including language systems, basal ganglia, thalamus, and hippocampus. Direct contrasts between the regular sentence condition and the jabberwocky condition indicate that prediction of word category in meaningless jabberwocky sentences relies on classical left-hemispheric language systems involving Brodman's area 44/45 in the left inferior frontal gyrus, left superior temporal areas, and the dorsal caudate nucleus. Regular sentences, in contrast, allowed for the prediction of specific words. Word-specific predictions were specifically associated with more widely distributed temporal and parietal cortical systems, most prominently in the right hemisphere. Our results support the presence of linguistic predictions during sentence processing and demonstrate the validity of the predictive eye gaze

  9. 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.

  10. Interval model updating using perturbation method and Radial Basis Function neural networks

    Science.gov (United States)

    Deng, Zhongmin; Guo, Zhaopu; Zhang, Xinjie

    2017-02-01

    In recent years, stochastic model updating techniques have been applied to the quantification of uncertainties inherently existing in real-world engineering structures. However in engineering practice, probability density functions of structural parameters are often unavailable due to insufficient information of a structural system. In this circumstance, interval analysis shows a significant advantage of handling uncertain problems since only the upper and lower bounds of inputs and outputs are defined. To this end, a new method for interval identification of structural parameters is proposed using the first-order perturbation method and Radial Basis Function (RBF) neural networks. By the perturbation method, each random variable is denoted as a perturbation around the mean value of the interval of each parameter and that those terms can be used in a two-step deterministic updating sense. Interval model updating equations are then developed on the basis of the perturbation technique. The two-step method is used for updating the mean values of the structural parameters and subsequently estimating the interval radii. The experimental and numerical case studies are given to illustrate and verify the proposed method in the interval identification of structural parameters.

  11. OPTIMASI LEARNING RADIAL BASIS FUNCTION NEURAL NETWORK DENGAN EXTENDED KALMAN FILTER

    Directory of Open Access Journals (Sweden)

    Oni Soesanto

    2015-09-01

    Full Text Available Dalam paper ini dibahas mengenai optimasi Radial Basis Function Neural Network (RBFNN dengan Extended Kalman Filter. Proses learning RBF dengan Extended Kalman Filter menggunakan parameter bobot pada hidden center RBF yaitu noise proses pada perhitungan bobot hidden center dan noise pengukuran pada data output. Extended Kalman Filter pada jaringan syaraf RBF berfungsi mengoptimalkan bobot pada hidden center dengan meminimalkan error pada output RBF dengan parameter proses pada unit center RBF dan parameter bobot output pada output layer. Bobot output optimal diperoleh pada saat error output pada training RBF telah konvergen, selanjutnya digunakan untuk proses testing. Algoritma Extended Kalman Filter dan Radial Basis Fuction (EKF-RBF memungkinkan proses learning memungkinkan center dan variansi pada hidden layer tidak perlu dihitung sebelum bobot output optimum ditemukan. Hasil simulasi menunjukkan bahwa pada training, performansi klasifikasi algoritma EKF-RBF mampu mengenali rata-rata 92.42% dan untuk prediksi didapatkan MAE sebesar 5,3846 dan RMSE sebesar 16,2398 dengan CPU time 24,4146 detik dengan iterasi rata-rata 68,8 iterasi, testing in sample rata-rata MAE sebesar 4,3388, rata-rata RMSE sebesar 13,2230 dan rata-rata CPU time sebesar 0,1123 detik sedangkan pada testing out sample didapatkan rata-rata MAE sebesar 4,1065, RMSE sebesar 11,0126 dan CPU time sebesar 0,0265 detik. Kata kunci : Extended Kalman Filter, Extended Kalman Filter – Radial Basis Function (EKF-RBF, Optimasi Jaringan Syaraf RBF

  12. The roots of empathy: the shared manifold hypothesis and the neural basis of intersubjectivity.

    Science.gov (United States)

    Gallese, Vittorio

    2003-01-01

    Starting from a neurobiological standpoint, I will propose that our capacity to understand others as intentional agents, far from being exclusively dependent upon mentalistic/linguistic abilities, be deeply grounded in the relational nature of our interactions with the world. According to this hypothesis, an implicit, prereflexive form of understanding of other individuals is based on the strong sense of identity binding us to them. We share with our conspecifics a multiplicity of states that include actions, sensations and emotions. A new conceptual tool able to capture the richness of the experiences we share with others will be introduced: the shared manifold of intersubjectivity. I will posit that it is through this shared manifold that it is possible for us to recognize other human beings as similar to us. It is just because of this shared manifold that intersubjective communication and ascription of intentionality become possible. It will be argued that the same neural structures that are involved in processing and controlling executed actions, felt sensations and emotions are also active when the same actions, sensations and emotions are to be detected in others. It therefore appears that a whole range of different "mirror matching mechanisms" may be present in our brain. This matching mechanism, constituted by mirror neurons originally discovered and described in the domain of action, could well be a basic organizational feature of our brain, enabling our rich and diversified intersubjective experiences. This perspective is in a position to offer a global approach to the understanding of the vulnerability to major psychoses such as schizophrenia.

  13. 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.

  14. 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…

  15. The Neural Basis of the Right Visual Field Advantage in Reading: An MEG Analysis Using Virtual Electrodes

    Science.gov (United States)

    Barca, Laura; Cornelissen, Piers; Simpson, Michael; Urooj, Uzma; Woods, Will; Ellis, Andrew W.

    2011-01-01

    Right-handed participants respond more quickly and more accurately to written words presented in the right visual field (RVF) than in the left visual field (LVF). Previous attempts to identify the neural basis of the RVF advantage have had limited success. Experiment 1 was a behavioral study of lateralized word naming which established that the…

  16. Using Complement Coercion to Understand the Neural Basis of Semantic Composition: Evidence from an fMRI Study

    Science.gov (United States)

    Husband, E. Matthew; Kelly, Lisa A.; Zhu, David C.

    2011-01-01

    Previous research regarding the neural basis of semantic composition has relied heavily on violation paradigms, which often compare implausible sentences that violate world knowledge to plausible sentences that do not violate world knowledge. This comparison is problematic as it may involve extralinguistic operations such as contextual repair and…

  17. 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…

  18. 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…

  19. 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…

  20. 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…

  1. 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.

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

    Science.gov (United States)

    Venkatesan, R.

    2016-01-01

    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.

  3. "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.

  4. 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.

  5. 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.

  6. Prospects and Limitations of Using Endogenous Neural Stem Cells for Brain Regeneration

    OpenAIRE

    Kazunobu Sawamoto; Eisuke Kako; Naoko Kaneko

    2011-01-01

    Neural stem cells (NSCs) are capable of producing a variety of neural cell types, and are indispensable for the development of the mammalian brain. NSCs can be induced in vitro from pluripotent stem cells, including embryonic stem cells and induced-pluripotent stem cells. Although the transplantation of these exogenous NSCs is a potential strategy for improving presently untreatable neurological conditions, there are several obstacles to its implementation, including tumorigenic, immunologica...

  7. 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.

  8. The neural basis of semantic cognition: converging evidence from neuropsychology, neuroimaging and TMS.

    Science.gov (United States)

    Jefferies, Elizabeth

    2013-03-01

    Recent studies suggest that a complex, distributed neural network underpins semantic cognition. This article reviews our contribution to this emerging picture and traces the putative roles of each region within this network. Neuropsychological studies indicate that semantic cognition draws on at least two interacting components: semantic representations [degraded in semantic dementia (SD)] and control processes [deficient in patients with multimodal semantic impairment following stroke aphasia (SA)]. To explore the first component, we employed distortion-corrected functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) in healthy volunteers: these studies convergently indicated that the anterior temporal lobes (ATLs; atrophied in SD) combine information from different modalities within an amodal semantic "hub". Regions of cortex that code specific semantic features ("spokes") also make a critical contribution to knowledge within particular categories. This network of brain regions interacts with semantic control processes reliant on left inferior frontal gyrus (LIFG), posterior middle temporal gyrus (pMTG) and inferior parietal cortices. SA patients with damage to these regions have difficulty focussing on aspects of knowledge that are relevant to the current goal or context, in both verbal and non-verbal tasks. SA patients with LIFG and temporoparietal lesions show similar deficits of semantic control, suggesting that a large-scale distributed cortical network underpins semantic control. Convergent evidence is again provided by fMRI and TMS. We separately manipulated the representational and control demands of a semantic task in fMRI, and found a dissociation within the temporal lobe: ATL was sensitive to the number of meanings retrieved, while pMTG and LIFG showed effects of semantic selection. Moreover, TMS to LIFG and pMTG produced equal disruption of tasks tapping semantic control. The next challenges are to delineate the

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Neural stem cell transplantation with Nogo-66 receptor gene silencing to treat severe traumatic brain injury

    Institute of Scientific and Technical Information of China (English)

    Dong Wang; Jianjun Zhang; Jingjian Ma; Yuan Mu; Yinghui Zhuang

    2011-01-01

    Inhibition of neurite growth, which is mediated by the Nogo-66 receptor (NgR), affects nerve regeneration following neural stem cell (NSC) transplantation. The present study utilized RNA interference to silence NgR gene expression in NSCs, which were subsequently transplanted into rats with traumatic brain injury. Following transplantation of NSCs transfected with small interfering RNA,typical neural cell-like morphology was detected in injured brain tissues, and was accompanied by absence of brain tissue cavity, increased growth-associated protein 43 mRNA and protein expression,and improved neurological function compared with NSC transplantation alone. Results demonstrated that NSC transplantation with silenced NgR gene promoted functional recovery following brain injury.

  15. Objects and their icons in the brain: the neural correlates of visual concept formation.

    Science.gov (United States)

    Shin, Yong-Wook; Kwon, Jun Soo; Kwon, Ki Won; Gu, Bon Mi; Song, In Chan; Na, Dong Gyu; Park, Sohee

    2008-05-16

    We are constantly exposed to symbols such as traffic signs, emoticons in internet communication, or other abstract representations of objects as well as, of course, the written words. However, aside from the word reading, little is known about the way our brain responds when we read non-lexical iconic symbols. By using functional MRI, we found that the watching of icons recruited manifold brain areas including frontal and parietal cortices in addition to the temporo-occipital junction in the ventral pathway. Remarkably, the brain response for icons was contrasted with the response for corresponding concrete objects with the pattern of 'hyper-cortical and hypo-subcortical' brain activation. This neural underpinning might be called the neural correlates for visual concept formation.

  16. The neural basis of parallel saccade programming: an fMRI study.

    Science.gov (United States)

    Hu, Yanbo; Walker, Robin

    2011-11-01

    The neural basis of parallel saccade programming was examined in an event-related fMRI study using a variation of the double-step saccade paradigm. Two double-step conditions were used: one enabled the second saccade to be partially programmed in parallel with the first saccade while in a second condition both saccades had to be prepared serially. The intersaccadic interval, observed in the parallel programming (PP) condition, was significantly reduced compared with latency in the serial programming (SP) condition and also to the latency of single saccades in control conditions. The fMRI analysis revealed greater activity (BOLD response) in the frontal and parietal eye fields for the PP condition compared with the SP double-step condition and when compared with the single-saccade control conditions. By contrast, activity in the supplementary eye fields was greater for the double-step condition than the single-step condition but did not distinguish between the PP and SP requirements. The role of the frontal eye fields in PP may be related to the advanced temporal preparation and increased salience of the second saccade goal that may mediate activity in other downstream structures, such as the superior colliculus. The parietal lobes may be involved in the preparation for spatial remapping, which is required in double-step conditions. The supplementary eye fields appear to have a more general role in planning saccade sequences that may be related to error monitoring and the control over the execution of the correct sequence of responses.

  17. 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...

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

    OpenAIRE

    May, Lillian; Byers-Heinlein, Krista; Gervain, Judit; 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 language stimuli. Twenty monolingual ...

  19. 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.

  20. Implications of the Dependence of Neuronal Activity on Neural Network States for the Design of Brain-Machine Interfaces

    OpenAIRE

    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 stim...

  1. 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

  2. Neural imaginaries and clinical epistemology: Rhetorically mapping the adolescent brain in the clinical encounter.

    Science.gov (United States)

    Buchbinder, Mara

    2015-10-01

    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.

  3. Reconstruction of brain circuitry by neural transplants generated from pluripotent stem cells.

    Science.gov (United States)

    Thompson, Lachlan H; Björklund, Anders

    2015-07-01

    Pluripotent stem cells (embryonic stem cells, ESCs, and induced pluripotent stem cells, iPSCs) have the capacity to generate neural progenitors that are intrinsically patterned to undergo differentiation into specific neuronal subtypes and express in vivo properties that match the ones formed during normal embryonic development. Remarkable progress has been made in this field during recent years thanks to the development of more refined protocols for the generation of transplantable neuronal progenitors from pluripotent stem cells, and the access to new tools for tracing of neuronal connectivity and assessment of integration and function of grafted neurons. Recent studies in brains of neonatal mice or rats, as well as in rodent models of brain or spinal cord damage, have shown that ESC- or iPSC-derived neural progenitors can be made to survive and differentiate after transplantation, and that they possess a remarkable capacity to extend axons over long distances and become functionally integrated into host neural circuitry. Here, we summarize these recent developments in the perspective of earlier studies using intracerebral and intraspinal transplants of primary neurons derived from fetal brain, with special focus on the ability of human ESC- and iPSC-derived progenitors to reconstruct damaged neural circuitry in cortex, hippocampus, the nigrostriatal system and the spinal cord, and we discuss the intrinsic and extrinsic factors that determine the growth properties of the grafted neurons and their capacity to establish target-specific long-distance axonal connections in the damaged host brain.

  4. Regulation of neural development and adult brain homeostasis in the zebrafish

    NARCIS (Netherlands)

    Paridaen, J.T.M.L.

    2009-01-01

    During vertebrate neural development, many genes and pathways are involved in order to properly pattern and maintain regional brain identities. This thesis documents the roles and pathways they are involved in of several genes that were identified from forward and reverse genetic screens in the zebr

  5. Transcriptional profiling of adult neural stem-like cells from the human brain.

    Science.gov (United States)

    Sandberg, Cecilie Jonsgar; Vik-Mo, Einar O; Behnan, Jinan; Helseth, Eirik; Langmoen, Iver A

    2014-01-01

    There is a great potential for the development of new cell replacement strategies based on adult human neural stem-like cells. However, little is known about the hierarchy of cells and the unique molecular properties of stem- and progenitor cells of the nervous system. Stem cells from the adult human brain can be propagated and expanded in vitro as free floating neurospheres that are capable of self-renewal and differentiation into all three cell types of the central nervous system. Here we report the first global gene expression study of adult human neural stem-like cells originating from five human subventricular zone biopsies (mean age 42, range 33-60). Compared to adult human brain tissue, we identified 1,189 genes that were significantly up- and down-regulated in adult human neural stem-like cells (1% false discovery rate). We found that adult human neural stem-like cells express stem cell markers and have reduced levels of markers that are typical of the mature cells in the nervous system. We report that the genes being highly expressed in adult human neural stem-like cells are associated with developmental processes and the extracellular region of the cell. The calcium signaling pathway and neuroactive ligand-receptor interactions are enriched among the most differentially regulated genes between adult human neural stem-like cells and adult human brain tissue. We confirmed the expression of 10 of the most up-regulated genes in adult human neural stem-like cells in an additional sample set that included adult human neural stem-like cells (n = 6), foetal human neural stem cells (n = 1) and human brain tissues (n = 12). The NGFR, SLITRK6 and KCNS3 receptors were further investigated by immunofluorescence and shown to be heterogeneously expressed in spheres. These receptors could potentially serve as new markers for the identification and characterisation of neural stem- and progenitor cells or as targets for manipulation of cellular fate.

  6. Regulation of endogenous neural stem/progenitor cells for neural repair - factors that promote neurogenesis and gliogenesis in the normal and damaged brain

    Directory of Open Access Journals (Sweden)

    Kimberly eChristie

    2013-01-01

    Full Text Available Neural stem/precursor cells in the adult brain reside in the subventricular zone (SVZ of the lateral ventricles and the subgranular zone (SGZ of the dentate gyrus in the hippocampus. These cells primarily generate neuroblasts that normally migrate to the olfactory bulb and the dentate granule cell layer respectively. Following brain damage, such as traumatic brain injury, ischemic stroke or in degenerative disease models, neural precursor cells from the SVZ in particular, can migrate from their normal route along the rostral migratory stream to the site of neural damage. This neural precursor cell response to neural damage is mediated by release of endogenous factors, including cytokines and chemokines produced by the inflammatory response at the injury site, and by the production of growth and neurotrophic factors. Endogenous hippocampal neurogenesis is frequently also directly or indirectly affected by neural damage. Administration of a variety of factors that regulate different aspects of neural stem/precursor biology often leads to improved functional motor and/or behavioural outcomes. Such factors can target neural stem/precursor proliferation, survival, migration and differentiation into appropriate neuronal or glial lineages. Newborn cells also need to subsequently survive and functionally integrate into extant neural circuitry, which may be the major bottleneck to the current therapeutic potential of neural stem/precursor cells. This review will cover the effects of a range of intrinsic and extrinsic factors that regulate neural stem /precursor cell functions. In particular it focuses on factors that may be harnessed to enhance the endogenous neural stem/precursor cell response to neural damage, highlighting those that have already shown evidence of preclinical effectiveness and discussing others that warrant further preclinical investigation.

  7. Optimal and robust design of brain-state-in-a-box neural associative memories.

    Science.gov (United States)

    Park, Yonmook

    2010-03-01

    This paper presents a new optimization approach to the design of associative memories via the brain-state-in-a-box (BSB) neural network. The optimization approach proposed in this paper provides the large and uniform domains of attraction of the prototype patterns, the large robustness margin for the weight matrix of the perturbed BSB neural network, the asymptotic stability of the prototype patterns, and the global stability of the BSB neural network. Based on some known qualitative properties of the BSB neural network and theoretical results presented in this paper, a synthesis method of the BSB-based associative memory is established. The synthesis method presented in this paper is given in the form of a linear matrix inequality-based optimization problem, which can be efficiently solved by a readily available software. Design examples are given to demonstrate the applicability of the proposed method and to compare with the existing synthesis methods.

  8. 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.

  9. 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.

  10. Prospects and Limitations of Using Endogenous Neural Stem Cells for Brain Regeneration

    Directory of Open Access Journals (Sweden)

    Kazunobu Sawamoto

    2011-01-01

    Full Text Available Neural stem cells (NSCs are capable of producing a variety of neural cell types, and are indispensable for the development of the mammalian brain. NSCs can be induced in vitro from pluripotent stem cells, including embryonic stem cells and induced-pluripotent stem cells. Although the transplantation of these exogenous NSCs is a potential strategy for improving presently untreatable neurological conditions, there are several obstacles to its implementation, including tumorigenic, immunological, and ethical problems. Recent studies have revealed that NSCs also reside in the adult brain. The endogenous NSCs are activated in response to disease or trauma, and produce new neurons and glia, suggesting they have the potential to regenerate damaged brain tissue while avoiding the above-mentioned problems. Here we present an overview of the possibility and limitations of using endogenous NSCs in regenerative medicine.

  11. Prospects and limitations of using endogenous neural stem cells for brain regeneration.

    Science.gov (United States)

    Kaneko, Naoko; Kako, Eisuke; Sawamoto, Kazunobu

    2011-01-14

    Neural stem cells (NSCs) are capable of producing a variety of neural cell types, and are indispensable for the development of the mammalian brain. NSCs can be induced in vitro from pluripotent stem cells, including embryonic stem cells and induced-pluripotent stem cells. Although the transplantation of these exogenous NSCs is a potential strategy for improving presently untreatable neurological conditions, there are several obstacles to its implementation, including tumorigenic, immunological, and ethical problems. Recent studies have revealed that NSCs also reside in the adult brain. The endogenous NSCs are activated in response to disease or trauma, and produce new neurons and glia, suggesting they have the potential to regenerate damaged brain tissue while avoiding the above-mentioned problems. Here we present an overview of the possibility and limitations of using endogenous NSCs in regenerative medicine.

  12. Predicting healthy older adult's brain age based on structural connectivity networks using artificial neural networks.

    Science.gov (United States)

    Lin, Lan; Jin, Cong; Fu, Zhenrong; Zhang, Baiwen; Bin, Guangyu; Wu, Shuicai

    2016-03-01

    Brain ageing is followed by changes of the connectivity of white matter (WM) and changes of the grey matter (GM) concentration. Neurodegenerative disease is more vulnerable to an accelerated brain ageing, which is associated with prospective cognitive decline and disease severity. Accurate detection of accelerated ageing based on brain network analysis has a great potential for early interventions designed to hinder atypical brain changes. To capture the brain ageing, we proposed a novel computational approach for modeling the 112 normal older subjects (aged 50-79 years) brain age by connectivity analyses of networks of the brain. Our proposed method applied principal component analysis (PCA) to reduce the redundancy in network topological parameters. Back propagation artificial neural network (BPANN) improved by hybrid genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithm is established to model the relation among principal components (PCs) and brain age. The predicted brain age is strongly correlated with chronological age (r=0.8). The model has mean absolute error (MAE) of 4.29 years. Therefore, we believe the method can provide a possible way to quantitatively describe the typical and atypical network organization of human brain and serve as a biomarker for presymptomatic detection of neurodegenerative diseases in the future.

  13. 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.

  14. A novel hypothesis of blood-brain barrier (BBB development and in vitro BBB model: neural stem cell is the driver of BBB formation and maintenance

    Directory of Open Access Journals (Sweden)

    Jian Lu

    2012-02-01

    Full Text Available There is an ongoing effort to develop in vitro models for the blood-brain barrier (BBB research and the central nervous system (CNS drug screening. But the phenotypes of the existing in vitro models are still very remote from those found in vivo. The trouble in establishing in vitro BBB models comes from the unclear mechanism of the BBB formation and maintenance. The astrocytes have been found to be responsible for the maintenance of the BBB, but the studies of the CNS development have shown that the BBB formation starts largely before the gliogenesis. We hypothesize here that the neural stem cell is the real driver of the BBB formation, development and maintenance. The formation of the BBB is initiated by the neural stem cells during the earliest stage of CNS angiogenesis. The maintenance of the BBB is driven by the soluble signals produced by the neural stem cells which exist in the dentate gyrus of the hippocampus and the subventricular zone throughout the life. The brain microvascular endothelial cells (BMEC-pericyte complex is the anatomical basis of the BBB. Based on our hypothesis we suggest using the neural stem cells to induce the BMEC-pericyte complex to establish in vitro BBB models. The further research on the role of the neural stem cells in the BBB formation and maintenance may elucidate the mechanism of the BBB development. [J Exp Integr Med 2012; 2(1.000: 39-43

  15. 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…

  16. 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.

  17. 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.

  18. 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.

  19. Studies of the neural mechanisms of deep brain stimulation in rodent models of Parkinson's disease.

    Science.gov (United States)

    Chang, Jing-Yu; Shi, Li-Hong; Luo, Fei; Zhang, Wang-Ming; Woodward, Donald J

    2008-01-01

    Several rodent models of deep brain stimulation (DBS) have been developed in recent years. Electrophysiological and neurochemical studies have been performed to examine the mechanisms underlying the effects of DBS. In vitro studies have provided deep insights into the role of ion channels in response to brain stimulation. In vivo studies reveal neural responses in the context of intact neural circuits. Most importantly, recording of neural responses to behaviorally effective DBS in freely moving animals provides a direct means for examining how DBS modulates the basal ganglia thalamocortical circuits and thereby improves motor function. DBS can modulate firing rate, normalize irregular burst firing patterns and reduce low frequency oscillations associated with the Parkinsonian state. Our current efforts are focused on elucidating the mechanisms by which DBS effects on neural circuitry improve motor performance. New behavioral models and improved recording techniques will aide researchers conducting future DBS studies in a variety of behavioral modalities and enable new treatment strategies to be explored, such as closed-loop stimulations based on real time computation of ensemble neural activity.

  20. Neural correlates of executive control in the avian brain.

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    Jonas Rose

    2005-06-01

    Full Text Available Executive control, the ability to plan one's behaviour to achieve a goal, is a hallmark of frontal lobe function in humans and other primates. In the current study we report neural correlates of executive control in the avian nidopallium caudolaterale, a region analogous to the mammalian prefrontal cortex. Homing pigeons (Columba livia performed a working memory task in which cues instructed them whether stimuli should be remembered or forgotten. When instructed to remember, many neurons showed sustained activation throughout the memory period. When instructed to forget, the sustained activation was abolished. Consistent with the neural data, the behavioural data showed that memory performance was high after instructions to remember, and dropped to chance after instructions to forget. Our findings indicate that neurons in the avian nidopallium caudolaterale participate in one of the core forms of executive control, the control of what should be remembered and what should be forgotten. This form of executive control is fundamental not only to working memory, but also to all cognition.

  1. Investigating the brain basis of facial expression perception using multi-voxel pattern analysis.

    Science.gov (United States)

    Wegrzyn, Martin; Riehle, Marcel; Labudda, Kirsten; Woermann, Friedrich; Baumgartner, Florian; Pollmann, Stefan; Bien, Christian G; Kissler, Johanna

    2015-08-01

    Humans can readily decode emotion expressions from faces and perceive them in a categorical manner. The model by Haxby and colleagues proposes a number of different brain regions with each taking over specific roles in face processing. One key question is how these regions directly compare to one another in successfully discriminating between various emotional facial expressions. To address this issue, we compared the predictive accuracy of all key regions from the Haxby model using multi-voxel pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data. Regions of interest were extracted using independent meta-analytical data. Participants viewed four classes of facial expressions (happy, angry, fearful and neutral) in an event-related fMRI design, while performing an orthogonal gender recognition task. Activity in all regions allowed for robust above-chance predictions. When directly comparing the regions to one another, fusiform gyrus and superior temporal sulcus (STS) showed highest accuracies. These results underscore the role of the fusiform gyrus as a key region in perception of facial expressions, alongside STS. The study suggests the need for further specification of the relative role of the various brain areas involved in the perception of facial expression. Face processing appears to rely on more interactive and functionally overlapping neural mechanisms than previously conceptualised.

  2. Language and the newborn brain: does prenatal language experience shape the neonate neural response to speech?

    Science.gov (United States)

    May, Lillian; Byers-Heinlein, Krista; Gervain, Judit; 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 language stimuli. Twenty monolingual English-exposed neonates aged 0-3 days were tested. Each infant heard low-pass filtered sentences of forward English (familiar language), forward Tagalog (unfamiliar language), and backward English and Tagalog (non-language). During exposure, neural activation was measured across 12 channels on each hemisphere. Our results indicate a bilateral effect of language familiarity on neonates' brain response to language. Differential brain activation was seen when neonates listened to forward Tagalog (unfamiliar language) as compared to other types of language stimuli. We interpret these results as evidence that the prenatal experience with the native language gained in utero influences how the newborn brain responds to language across brain regions sensitive to speech processing.

  3. A positron emission tomography study of the neural basis of informational and energetic masking effects in speech perception

    Science.gov (United States)

    Scott, Sophie K.; Rosen, Stuart; Wickham, Lindsay; Wise, Richard J. S.

    2004-02-01

    Positron emission tomography (PET) was used to investigate the neural basis of the comprehension of speech in unmodulated noise (``energetic'' masking, dominated by effects at the auditory periphery), and when presented with another speaker (``informational'' masking, dominated by more central effects). Each type of signal was presented at four different signal-to-noise ratios (SNRs) (+3, 0, -3, -6 dB for the speech-in-speech, +6, +3, 0, -3 dB for the speech-in-noise), with listeners instructed to listen for meaning to the target speaker. Consistent with behavioral studies, there was SNR-dependent activation associated with the comprehension of speech in noise, with no SNR-dependent activity for the comprehension of speech-in-speech (at low or negative SNRs). There was, in addition, activation in bilateral superior temporal gyri which was associated with the informational masking condition. The extent to which this activation of classical ``speech'' areas of the temporal lobes might delineate the neural basis of the informational masking is considered, as is the relationship of these findings to the interfering effects of unattended speech and sound on more explicit working memory tasks. This study is a novel demonstration of candidate neural systems involved in the perception of speech in noisy environments, and of the processing of multiple speakers in the dorso-lateral temporal lobes.

  4. 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.

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

    Science.gov (United States)

    Dodell-Feder, David; Tully, Laura M; Lincoln, Sarah Hope; Hooker, Christine I

    2014-01-01

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Benyamini, Miri; Zacksenhouse, Miriam

    2015-01-01

    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.

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

    Directory of Open Access Journals (Sweden)

    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. MicroRNAs in neural cell development and brain diseases.

    Science.gov (United States)

    Feng, Wei; Feng, Yue

    2011-12-01

    MicroRNAs play important roles in post-transcriptional regulation of gene expression by inhibiting protein translation and/or promoting mRNA degradation. Importantly, biogenesis of microRNAs displays specific temporal and spatial profiles in distinct cell and tissue types and hence affects a broad spectrum of biological functions in normal cell growth and tumor development. Recent discoveries have revealed sophisticated mechanisms that control microRNA production and homeostasis in response to developmental and extracellular signals. Moreover, a link between dysregulation of microRNAs and human brain disorders has become increasingly evident. In this review, we focus on recent advances in understanding the regulation of microRNA biogenesis and function in neuronal and glial development in the mammalian brain, and dysregulation of the microRNA pathway in neurodevelopmental and neurodegenerative diseases.

  10. 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…

  11. 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.

  12. Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging.

    Science.gov (United States)

    Glahn, David C; Kent, Jack W; Sprooten, Emma; Diego, Vincent P; Winkler, Anderson M; Curran, Joanne E; McKay, D Reese; Knowles, Emma E; Carless, Melanie A; Göring, Harald H H; Dyer, Thomas D; Olvera, Rene L; Fox, Peter T; Almasy, Laura; Charlesworth, Jac; Kochunov, Peter; Duggirala, Ravi; Blangero, John

    2013-11-19

    Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18-83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging.

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. The Neural and Behavioral Basis of Empathy for Positive and Negative Emotions

    OpenAIRE

    Morelli, Sylvia Annette

    2012-01-01

    Empathy provides a window into another person's mind, creating a shared experience between two individuals. This intimate view of another person's emotional world often makes the empathizer feel more connected to the other person and may motivate the empathizer to respond to the other's emotional needs. While past studies have investigated the underlying psychological and neural mechanisms for this fundamental human experience, researchers have predominantly focused on examining empathy for...

  19. Growth hormone responsive neural precursor cells reside within the adult mammalian brain

    OpenAIRE

    Blackmore, Daniel G.; Brent A. Reynolds; Golmohammadi, Mohammad G.; Large, Beatrice; Aguilar, Roberto M.; Haro, Luis; Waters, Michael J.; Rietze, Rodney L.

    2012-01-01

    The detection of growth hormone (GH) and its receptor in germinal regions of the mammalian brain prompted our investigation of GH and its role in the regulation of endogenous neural precursor cell activity. Here we report that the addition of exogenous GH significantly increased the expansion rate in long-term neurosphere cultures derived from wild-type mice, while neurospheres derived from GH null mice exhibited a reduced expansion rate. We also detected a doubling in the frequency of large ...

  20. The Regenerative Response of Endogenous Neural Stem/Progenitor Cells to Traumatic Brain Injury

    Science.gov (United States)

    2014-06-09

    neural stem cells in the adjacent SVZ, the largest germinal zone in the mammalian CNS. Ex vivo and in vivo DTI were combined with post-imaging...faults accrued over 50 steps was counted for each hind limb. Controlled Cortical Impact (CCI), which involves craniotomy and impact onto the dura...the subventricular zone (SVZ), a major germinal zone in the adult brain, have potential repair capacity that is not well understood relative to the

  1. 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.

  2. Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches

    Science.gov (United States)

    Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Thibodeaux, David N.; Zhao, Hanzhi T.; Yu, Hang

    2016-01-01

    Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574312

  3. Murine cytomegalovirus infection of neural stem cells alters neurogenesis in the developing brain.

    Directory of Open Access Journals (Sweden)

    Manohar B Mutnal

    Full Text Available BACKGROUND: Congenital cytomegalovirus (CMV brain infection causes serious neuro-developmental sequelae including: mental retardation, cerebral palsy, and sensorineural hearing loss. But, the mechanisms of injury and pathogenesis to the fetal brain are not completely understood. The present study addresses potential pathogenic mechanisms by which this virus injures the CNS using a neonatal mouse model that mirrors congenital brain infection. This investigation focused on, analysis of cell types infected with mouse cytomegalovirus (MCMV and the pattern of injury to the developing brain. METHODOLOGY/PRINCIPAL FINDINGS: We used our MCMV infection model and a multi-color flow cytometry approach to quantify the effect of viral infection on the developing brain, identifying specific target cells and the consequent effect on neurogenesis. In this study, we show that neural stem cells (NSCs and neuronal precursor cells are the principal target cells for MCMV in the developing brain. In addition, viral infection was demonstrated to cause a loss of NSCs expressing CD133 and nestin. We also showed that infection of neonates leads to subsequent abnormal brain development as indicated by loss of CD24(hi cells that incorporated BrdU. This neonatal brain infection was also associated with altered expression of Oct4, a multipotency marker; as well as down regulation of the neurotrophins BDNF and NT3, which are essential to regulate the birth and differentiation of neurons during normal brain development. Finally, we report decreased expression of doublecortin, a marker to identify young neurons, following viral brain infection. CONCLUSIONS: MCMV brain infection of newborn mice causes significant loss of NSCs, decreased proliferation of neuronal precursor cells, and marked loss of young neurons.

  4. 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.

  5. 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.

  6. Learning and Forgetting in Generalized Brain-state-in-a-box (BSB) Neural Associative Memories.

    Science.gov (United States)

    Hui, Stefen; Lillo, Walter E.; Zak, Stanislaw H.

    1996-07-01

    We propose learning and forgetting techniques for the generalized brain-state-in-a-box (BSB) based associative memories. A generalization of the BSB model allows each neuron to have its own bias and the synaptic weight matrix does not have to be symmetric. A pattern is learned by a memory if its noisy or an incomplete version presented to the memory is mapped back to this pattern. A pattern, previously stored, is forgotten or deleted from the memory if a stimulus that is a perturbed version of the pattern, when presented to the memory, is not mapped back to this pattern. In this paper we propose "on-line" memory storage and deletion methods using an iterative method of computing the pseudo-inverse of a given matrix. The proposed methods allow one to "add" or "delete" a memory pattern by updating, rather than recomputing from scratch, the current synaptic weight matrix in a single step. We first analyze the desired characteristics of neural network associative memories. After that, we review the existing methods for design of neural associative memories. Then we discuss the generalized BSB neural model and its possible function as an associative memory and proffer arguments in support of using such models for neural associative memories. In particular, the generalized BSB type models are easier to analyze, synthesize, and implement than other neural networks. The results obtained are illustrated by numerical examples. Copyright 1996 Elsevier Science Ltd

  7. Moderate alcohol exposure compromises neural tube midline development in prenatal brain.

    Science.gov (United States)

    Zhou, Feng C; Sari, Youssef; Powrozek, Teresa; Goodlett, Charles R; Li, Ting-Kai

    2003-08-12

    We previously reported that fetal alcohol treatment compromised the development of the midline raphe and the serotonin neurons contained in it. In this study, we report that the timely development of midline neural tissue during neural tube formation is sensitive to alcohol exposure. Pregnant dams were treated from embryonic day 7 (E7, prior to neurulation) or E8.5 (at neurulation) with the following diets: (a) alcohol (ALC), given as either a 20% or 25% ethanol-derived calorie (EDC) liquid diet, or (b) isocaloric liquid diet pair-fed (PF), or (c) standard rat chow (Chow). Fetal brains from each group were examined on E13, E15, or E18. Neural tube development was compromised as a result of alcohol exposure in the following ways: (1) approximately 60% of embryos at E13 and 20% at E15 showed perforation of the floor plate in the diencephalic vesicle, (2) although completely closed at E13, 70-80% of embryos failed to complete the formation of neural tissue at the roof as the alcohol exposure continued to E15, and (3) 60-80% of embryos show delayed 'occlusion' of the ventral canal by newly formed nestin-positive neuroepithelial cells and S100beta-positive glia in the brainstem of E15. The compromised (incomplete) neural tube midline (cNTM) occurred near the ventricles at E13 and E15, but was later completed at E18. In all cases, the cNTM was accompanied by an enlarged ventricle, and dose-dependent brain weight reduction. The midline of the neural tube at the roof and floor plates is known to mediate timely trophic induction for neural differentiation. Prenatal midline deficits also have the potential to affect the development of midline neurons such as raphe, septal nuclei, and the timely crossing of commissural fibers. The results of the liquid diet alcohol exposure paradigm suggest it is more a model for Alcohol-Related Neurodevelopmental Disorder (ARND) featuring neuropsychiatric disorders than for full-blown fetal alcohol syndrome (FAS) with noticeable facial

  8. 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:…

  9. The neurocognitive basis of feature integration

    NARCIS (Netherlands)

    Keizer, André Willem

    2010-01-01

    One of the most striking features of the brain is that it is modular; it consists of often highly specialized areas. This modular organization requires efficient communication in order to integrate the information that is represented in distinct brain areas. In my thesis, I studied the neural basis

  10. Neural basis of three dimensions of agitated behaviors in patients with Alzheimer disease

    Directory of Open Access Journals (Sweden)

    Banno K

    2014-02-01

    Full Text Available Koichi Banno,1 Shutaro Nakaaki,2 Junko Sato,1 Katsuyoshi Torii,1 Jin Narumoto,3 Jun Miyata,4 Nobutsugu Hirono,5 Toshi A Furukawa,6 Masaru Mimura,2 Tatsuo Akechi1 1Department of Psychiatry and Cognitive-Behavioral Medicine, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan; 2Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; 3Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, 4Department of Neuropsychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan; 5Department of Psychology, Kobe Gakuin University; Hyogo, Japan; 6Departments of Health Promotion and Human Behavior and of Clinical Epidemiology, Graduate School of Medicine/School of Public Health, Kyoto University, Kyoto, Japan Background: Agitated behaviors are frequently observed in patients with Alzheimer disease (AD. The neural substrate underlying the agitated behaviors in dementia is unclear. We hypothesized that different dimensions of agitated behaviors are mediated by distinct neural systems. Methods: All the patients (n=32 underwent single photon emission computed tomography (SPECT. Using the Agitated Behavior in Dementia scale, we identified the relationships between regional cerebral blood flow (rCBF patterns and the presence of each of three dimensions of agitated behavior (physically agitated behavior, verbally agitated behavior, and psychosis symptoms in AD patients. Statistical parametric mapping (SPM software was used to explore these neural correlations. Results: Physically agitated behavior was significantly correlated with lower rCBF values in the right superior temporal gyrus (Brodmann 22 and the right inferior frontal gyrus (Brodmann 47. Verbally agitated behavior was significantly associated with lower rCBF values in the left inferior frontal gyrus (Brodmann 46, 44 and the left insula (Brodmann 13. The psychosis symptoms were significantly correlated

  11. 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.

  12. Neural basis of implicit memory for socio-emotional information in schizophrenia.

    Science.gov (United States)

    Schwartz, Barbara L; Vaidya, Chandan J; Shook, Devon; Deutsch, Stephen I

    2013-04-30

    Individuals with schizophrenia are impaired in processing social signals such as facial expressions of emotion. Perceiving facial expressions is a complex process that depends on a distributed neural network of regions involved in affective, cognitive, and visual processing. We examined repetition priming, a non-conscious form of perceptual learning, to explore the visual-perceptual processes associated with perceiving facial expression in people with schizophrenia. Functional magnetic resonance imaging (fMRI) was also employed to probe the sensitivity of face-responsive regions in the ventral pathway to the repetition of stimuli. Subjects viewed blocks of novel and repeated faces displaying fear expressions and neutral expressions and identified each face as male or female. Gender decisions were faster for repeated encoding relative to initial encoding of faces, indicating significant priming for facial expressions. Priming was normal in schizophrenia patients, but, as expected, recognition memory for the expressions was impaired. Neuroimaging findings showed that priming-related activation for patients was reduced in the left fusiform gyrus, relative to controls, regardless of facial expression. The findings suggest that schizophrenia patients have altered neural sensitivity in regions of the ventral visual processing stream that underlie early perceptual learning of objects and faces.

  13. Strategies for Regenerating Striatal Neurons in the Adult Brain by Using Endogenous Neural Stem Cells

    Directory of Open Access Journals (Sweden)

    Kanako Nakaguchi

    2011-01-01

    Full Text Available Currently, there is no effective treatment for the marked neuronal loss caused by neurodegenerative diseases, such as Huntington's disease (HD or ischemic stroke. However, recent studies have shown that new neurons are continuously generated by endogenous neural stem cells in the subventricular zone (SVZ of the adult mammalian brain, including the human brain. Because some of these new neurons migrate to the injured striatum and differentiate into mature neurons, such new neurons may be able to replace degenerated neurons and improve or repair neurological deficits. To establish a neuroregenerative therapy using this endogenous system, endogenous regulatory mechanisms that can be co-opted for efficient regenerative interventions must be understood, along with any potential drawbacks. Here, we review current knowledge on the generation of new neurons in the adult brain and discuss their potential for use in replacing striatal neurons lost to neurodegenerative diseases, including HD, and to ischemic stroke.

  14. Adaptive, optical, radial basis function neural network for handwritten digit recognition

    Science.gov (United States)

    Foor, Wesley E.; Neifeld, Mark A.

    1995-11-01

    An adaptive, optical, radial basis function classifier for handwritten digit recognition is experimentally demonstrated. We describe a spatially multiplexed system that incorporates an on-line adaptation of weights and basis function widths to provide robustness to optical system imperfections and system noise. The optical system computes the Euclidean distances between a 100-dimensional input vector and 198 stored reference patterns in parallel by using dual vector-matrix multipliers and a contrast-reversing spatial light modulator. Software is used to emulate an electronic chip that performs the on-line learning of the weights and basis function widths. An experimental recognition rate of 92.7% correct out of 300 testing samples is achieved with the adaptive training, versus 31.0% correct for nonadaptive training. We compare the experimental results with a detailed computer model of the system in order to analyze the influence of various noise sources on the system performance.

  15. Artificial Brain Based on Credible Neural Circuits in a Human Brain

    CERN Document Server

    Burger, John Robert

    2010-01-01

    Neurons are individually translated into simple gates to plan a brain with human psychology and intelligence. State machines, assumed previously learned in subconscious associative memory are shown to enable equation solving and rudimentary thinking using nanoprocessing within short term memory.

  16. Neural Basis of Empathy and Its Dysfunction in Autism Spectrum Disorders (ASD)

    Science.gov (United States)

    2012-08-01

    Use Committee. Two donor monkeys (MY and MO) and a recipient monkey (MD) participated in the study. All animals underwent standard surgical procedures...2006; Tsao et al., 2008; Azzi et al., 2012; Chang et al., 2012) and in animals that have very different brains as well, like scrub jays and rooks...social context on prospective caching strategies by scrub jays. Nature 414:443-446. Fujii, N., Hihara, S. & Iriki, A. (2007) Dynamic social adaptation

  17. 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.

  18. 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.

  19. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  1. 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.

  2. Gap junction proteins in the blood-brain barrier control nutrient-dependent reactivation of Drosophila neural stem cells.

    Science.gov (United States)

    Spéder, Pauline; Brand, Andrea H

    2014-08-11

    Neural stem cells in the adult brain exist primarily in a quiescent state but are reactivated in response to changing physiological conditions. How do stem cells sense and respond to metabolic changes? In the Drosophila CNS, quiescent neural stem cells are reactivated synchronously in response to a nutritional stimulus. Feeding triggers insulin production by blood-brain barrier glial cells, activating the insulin/insulin-like growth factor pathway in underlying neural stem cells and stimulating their growth and proliferation. Here we show that gap junctions in the blood-brain barrier glia mediate the influence of metabolic changes on stem cell behavior, enabling glia to respond to nutritional signals and reactivate quiescent stem cells. We propose that gap junctions in the blood-brain barrier are required to translate metabolic signals into synchronized calcium pulses and insulin secretion.

  3. Neural basis of Chinese phonological processing under picture stimulus A functional magnetic resonance imaging study

    Institute of Scientific and Technical Information of China (English)

    Junfei Liu; Shiwen Feng; Wei Song; Liang Yu; Haijiang Cui; Yiming Yang

    2011-01-01

    Studies concerning phonological processing mainly use written stimuli. Functional magnetic resonance imaging was used to investigate the brain regions related to the phonological processing under the picture stimulus in the rhyme task of Chinese language. Results of the test in 13 healthy college students whose native language is Chinese showed the extensive activation in the frontal lobe, parietal lobe and the occipitotemporal cortex, including the inferior frontal gyrus, middle frontal gyrus, supramarginal gyrus and medial occipitotemporal gyrus under the picture stimuli. Moreover, phonological processing induced activation in the superior temporal gyrus (BA 22) under the picture stimuli, but activation was not found in the middle temporal gyrus.

  4. 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.

  5. Cognitive disorder and changes in cholinergic receptors, N-methyl-D aspartate receptors, neural cell adhesion molecule, and brain-derived neurotrophic factor following brain injury

    Institute of Scientific and Technical Information of China (English)

    Weiliang Zhao; Dezhi Kang; Yuanxiang Lin

    2008-01-01

    BACKGROUND: Learning and memory damage is one of the most permanent and the severest symptoms of traumatic brain injury; it can seriously influence the normal life and work of patients. Some research has demonstrated that cognitive disorder is closely related to nicotine cholinergic receptors, N-methyl-D aspartate receptors, neural cell adhesion molecule, and brain-derived neurotrophic factor. OBJECTIVE: To summarize the cognitive disorder and changes in nicotine cholinergic receptors, N-methyl-D aspartate receptors, neural cell adhesion molecule, and brain-derived neurotrophic factor following brain injury. RETRIEVAL STRATEGY: A computer-based online search was conducted in PUBMED for English language publications containing the key words "brain injured, cognitive handicap, acetylcholine, N-methyl-D aspartate receptors, neural cell adhesion molecule, brain-derived neurotrophic factor" from January 2000 to December 2007. There were 44 papers in total. Inclusion criteria: ① articles about changes in nicotine cholinergic receptors, N-methyl-D aspartate receptors, neural cell adhesion molecule, and brain-derived neurotrophic factor following brain injury; ② articles in the same researching circle published in authoritative journals or recently published. Exclusion criteria: duplicated articles.LITERATURE EVALUATION: References were mainly derived from research on changes in these four factors following brain injury. The 20 included papers were clinical or basic experimental studies. DATA SYNTHESIS: After craniocerebral injury, changes in these four factors in brain were similar to those during recovery from cognitive disorder, to a certain degree. Some data have indicated that activation of nicotine cholinergic receptors, N-methyl-D aspartate receptors, neural cell adhesion molecule, and brain-derived neurotrophic factor could greatly improve cognitive disorder following brain injury. However, there are still a lot of questions remaining; for example, how do these

  6. 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.

  7. 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.

  8. An Improved Brain Tumour Classification System using Wavelet Transform and Neural Network.

    Science.gov (United States)

    Dhas, DAS; Madheswaran, M

    2015-06-09

    An improved brain tumour classification system using wavelet transform and neural network is developed and presented in this paper. The anisotropic diffusion filter is used for image denoising and the performance of oriented rician noise reducing anisotropic diffusion (ORNRAD) filter is validated. The segmentation of the denoised image is carried out by Fuzzy C-means clustering. The features are extracted using Symlet and Coiflet Wavelet transform and Levenberg Marquardt algorithm based neural network is used to classify the magnetic resonance imaging (MRI) images. This MRI classification technique is tested and analysed with the existing methodologies and its performance is found to be satisfactory with a classification accuracy of 93.02%. The developed system can assist the physicians for classifying the MRI images for better decision-making.

  9. The neural control of bimanual movements in the elderly: Brain regions exhibiting age-related increases in activity, frequency-induced neural modulation, and task-specific compensatory recruitment.

    Science.gov (United States)

    Goble, Daniel J; Coxon, James P; Van Impe, Annouchka; De Vos, Jeroen; Wenderoth, Nicole; Swinnen, Stephan P

    2010-08-01

    Coordinated hand use is an essential component of many activities of daily living. Although previous studies have demonstrated age-related behavioral deficits in bimanual tasks, studies that assessed the neural basis underlying such declines in function do not exist. In this fMRI study, 16 old and 16 young healthy adults performed bimanual movements varying in coordination complexity (i.e., in-phase, antiphase) and movement frequency (i.e., 45, 60, 75, 90% of critical antiphase speed) demands. Difficulty was normalized on an individual subject basis leading to group performances (measured by phase accuracy/stability) that were matched for young and old subjects. Despite lower overall movement frequency, the old group "overactivated" brain areas compared with the young adults. These regions included the supplementary motor area, higher order feedback processing areas, and regions typically ascribed to cognitive functions (e.g., inferior parietal cortex/dorsolateral prefrontal cortex). Further, age-related increases in activity in the supplementary motor area and left secondary somatosensory cortex showed positive correlations with coordinative ability in the more complex antiphase task, suggesting a compensation mechanism. Lastly, for both old and young subjects, similar modulation of neural activity was seen with increased movement frequency. Overall, these findings demonstrate for the first time that bimanual movements require greater neural resources for old adults in order to match the level of performance seen in younger subjects. Nevertheless, this increase in neural activity does not preclude frequency-induced neural modulations as a function of increased task demand in the elderly.

  10. Comparative transcriptome analysis in induced neural stem cells reveals defined neural cell identities in vitro and after transplantation into the adult rodent brain.

    Science.gov (United States)

    Hallmann, Anna-Lena; Araúzo-Bravo, Marcos J; Zerfass, Christina; Senner, Volker; Ehrlich, Marc; Psathaki, Olympia E; Han, Dong Wook; Tapia, Natalia; Zaehres, Holm; Schöler, Hans R; Kuhlmann, Tanja; Hargus, Gunnar

    2016-05-01

    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.

  11. 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

    2017-03-22

    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 like 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.

  12. 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.

  13. 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. PMID:26941632

  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. Neural basis of decision-making and assessment: Issues on testability and philosophical relevance

    Directory of Open Access Journals (Sweden)

    Mograbi Gabriel José

    2011-01-01

    Full Text Available Decision-making is an intricate subject in neuroscience. It is often argued that laboratorial research is not capable of dealing with the necessary complexity to study the issue. Whereas philosophers in general neglect the physiological features that constitute the main aspects of thought and behaviour, I advocate that cutting-edge neuroscientific experiments can offer us a framework to explain human behaviour in its relationship with will, self-control, inhibition, emotion and reasoning. It is my contention that self-control mechanisms can modulate more basic stimuli. Assuming the aforementioned standpoints, I show the physiological mechanisms underlying social assessment and decision-making. I also establish a difference between veridical and adaptive decision-making, useful to create experimental designs that can better mimic the complexity of our day-by-day decisions in more ecologically relevant laboratorial research. Moreover, I analyse some experiments in order to develop an epistemological reflection about the necessary neural mechanisms to social assessment and decision-making.

  16. Neural basis of decision-making and assessment: Issues on testability and philosophical relevance

    Directory of Open Access Journals (Sweden)

    Gabriel José Corrêa Mograbi

    2011-03-01

    Full Text Available Decision-making is an intricate subject in neuroscience. It is often argued that laboratorial research is not capable of dealing with the necessary complexity to study the issue. Whereas philosophers in general neglect the physiological features that constitute the main aspects of thought and behaviour, I advocate that cutting-edge neuroscientific experiments can offer us a framework to explain human behaviour in its relationship with will, self-control, inhibition, emotion and reasoning. It is my contention that self-control mechanisms can modulate more basic stimuli. Assuming the aforementioned standpoints, I show the physiological mechanisms underlying social assessment and decision-making. I also establish a difference between veridical and adaptive decision-making, useful to create experimental designs that can better mimic the complexity of our day-by-day decisions in more ecologically relevant laboratorial research. Moreover, I analyse some experiments in order to develop an epistemological reflection about the necessary neural mechanisms to social assessment and decision-making.

  17. Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning.

    Science.gov (United States)

    Daniel, Reka; Pollmann, Stefan

    2010-01-06

    The dopaminergic system is known to play a central role in reward-based learning (Schultz, 2006), yet it was also observed to be involved when only cognitive feedback is given (Aron et al., 2004). Within the domain of information-integration category learning, in which information from several stimulus dimensions has to be integrated predecisionally (Ashby and Maddox, 2005), the importance of contingent feedback is well established (Maddox et al., 2003). We examined the common neural correlates of reward anticipation and prediction error in this task. Sixteen subjects performed two parallel information-integration tasks within a single event-related functional magnetic resonance imaging session but received a monetary reward only for one of them. Similar functional areas including basal ganglia structures were activated in both task versions. In contrast, a single structure, the nucleus accumbens, showed higher activation during monetary reward anticipation compared with the anticipation of cognitive feedback in information-integration learning. Additionally, this activation was predicted by measures of intrinsic motivation in the cognitive feedback task and by measures of extrinsic motivation in the rewarded task. Our results indicate that, although all other structures implicated in category learning are not significantly affected by altering the type of reward, the nucleus accumbens responds to the positive incentive properties of an expected reward depending on the specific type of the reward.

  18. A Novel Carbon Steel Pipe Protection Based on Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Sami A. Ajeel

    2010-01-01

    Full Text Available Problem statement: The cost due to corrosion Damage have estimated to be 3-4% of their gross national product which significantly Countries problem around the world. Approach: In this study, a novel carbon steel pipe protection based on RBFNN was proposed. The RBFNN used to predict the minimum current density required in impressed current cathodic protection to protect low carbon steel pipe. Learning data was performed by using a 30 samples test with different concentration C%, temperature T, distance D and pH. The RBFNN model has four input nodes representing the (concentration C%, temperature T, distance D and pH, eight nodes at hidden layer and one output node representing the min. current density. Results: Generalization test used 5 data samples taken from the experimental results other than those data samples used in the learning process to check the performance of the neural network on these data. Conclusion: In addition, the experimental results indicate that proposed system can be used successfully to obtain minimum cathodic protection current density to protect low carbon steel pipes.

  19. 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.

  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. Image segmentation by EM-based adaptive pulse coupled neural networks in brain magnetic resonance imaging.

    Science.gov (United States)

    Fu, J C; Chen, C C; Chai, J W; Wong, S T C; Li, I C

    2010-06-01

    We propose an automatic hybrid image segmentation model that integrates the statistical expectation maximization (EM) model and the spatial pulse coupled neural network (PCNN) for brain magnetic resonance imaging (MRI) segmentation. In addition, an adaptive mechanism is developed to fine tune the PCNN parameters. The EM model serves two functions: evaluation of the PCNN image segmentation and adaptive adjustment of the PCNN parameters for optimal segmentation. To evaluate the performance of the adaptive EM-PCNN, we use it to segment MR brain image into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The performance of the adaptive EM-PCNN is compared with that of the non-adaptive EM-PCNN, EM, and Bias Corrected Fuzzy C-Means (BCFCM) algorithms. The result is four sets of boundaries for the GM and the brain parenchyma (GM+WM), the two regions of most interest in medical research and clinical applications. Each set of boundaries is compared with the golden standard to evaluate the segmentation performance. The adaptive EM-PCNN significantly outperforms the non-adaptive EM-PCNN, EM, and BCFCM algorithms in gray mater segmentation. In brain parenchyma segmentation, the adaptive EM-PCNN significantly outperforms the BCFCM only. However, the adaptive EM-PCNN is better than the non-adaptive EM-PCNN and EM on average. We conclude that of the three approaches, the adaptive EM-PCNN yields the best results for gray matter and brain parenchyma segmentation.

  2. Activation of endogenous neural stem cells in experimental intracerebral hemorrhagic rat brains

    Institute of Scientific and Technical Information of China (English)

    唐涛; 黎杏群; 武衡; 罗杰坤; 张花先; 罗团连

    2004-01-01

    Background Many researchers suggest that adult mammalian central nervous system (CNS) is incapable of completing self-repair or regeneration. And there are accumulating lines of evidence which suggest that endogenous neural stem cells (NSCs) are activated in many pathological conditions, including stroke in the past decades, which might partly account for rehabilitation afterwards. In this study, we investigated whether there was endogenous neural stem cell activation in intracerebral hemorrhagic (ICH) rat brains.Methods After ICH induction by stereotactical injection of collagenase type Ⅶ into globus pallidus, 5-Bromo-2 Deoxyuridine (BrdU) was administered intraperitoneally to label newborn cells. Immunohistochemical method was used to detect Nestin, a marker for neural stem cells, and BrdU.Results Nestin-positive or BrdU-Labeled cells were predominantly located at 2 sites: basal ganglion around hemotoma, ependyma and nearby subventricular zone (SVZ). No positive cells for the 2 markers were found in the 2 sites of normal control group and sham group, as well as in non-leisoned parenchyma, both hippocampi and olfactory bulbs in the 4 groups. Nestin+ cells presented 4 types of morphology, and BrdU+ nucleus were polymorphologic. Postive cell counting around hemotoma showed that at day 2, Nestin+ cells were seen around hemotoma in model group , the number of which increased at day 4, day 7(P<0.01), peaked at day 14(P<0.05), and reduced significantly by day 28(P<0.01).Conclusion Endogenous neural stem cells were activated in experimental intracerebral hemorrhagic rat brains.

  3. 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.

  4. Multi-sensor integration for on-line tool wear estimation through radial basis function networks and fuzzy neural network.

    Science.gov (United States)

    Kuo, R J.; Cohen, P H.

    1999-03-01

    On-line tool wear estimation plays a very critical role in industry automation for higher productivity and product quality. In addition, appropriate and timely decision for tool change is significantly required in the machining systems. Thus, this paper is dedicated to develop an estimation system through integration of two promising technologies, artificial neural networks (ANN) and fuzzy logic. An on-line estimation system consisting of five components: (1) data collection; (2) feature extraction; (3) pattern recognition; (4) multi-sensor integration; and (5) tool/work distance compensation for tool flank wear, is proposed herein. For each sensor, a radial basis function (RBF) network is employed to recognize the extracted features. Thereafter, the decisions from multiple sensors are integrated through a proposed fuzzy neural network (FNN) model. Such a model is self-organizing and self-adjusting, and is able to learn from the experience. Physical experiments for the metal cutting process are implemented to evaluate the proposed system. The results show that the proposed system can significantly increase the accuracy of the product profile.

  5. Comparison Between Radial Basis Function Neural Network and Regression Model for Estimation of Rice Biophysical Parameters Using Remote Sensing

    Institute of Scientific and Technical Information of China (English)

    YANG Xiao-Hua; WANG Fu-Min; HUANG Jing-Feng; WANG Jian-Wen; WANG Ren-Chao; SHEN Zhang-Quan; WANG Xiu-Zhen

    2009-01-01

    The radial basis function (RBF) emerged as a variant of artificial neural network.Generalized regression neural network (GRNN) is one type of RBF,and its principal advantages are that it can quickly learn and rapidly converge to the optimal regression surface with large number of data sets.Hyperspectral reflectance (350 to 2 500 nm) data were recorded at two different rice sites in two experiment fields with two cultivars,three nitrogen treatments and one plant density (45 plants m-2).Stepwise multivariable regression model (SMR) and RBF were used to compare their predictability for the leaf area index (LAI) and green leaf chlorophyll density (GLCD) of rice based on reflectance (R) and its three different transformations,the first derivative reflectance (D1),the second derivative reflectance (D2) and the log-transformed reflectance (LOG).GRNN based on D1 was the best model for the prediction of rice LAI and GLCD.The relationships between different transformations of reflectance and rice parameters could be further improved when RBF was employed.Owing to its strong capacity for nonlinear mapping and good robustness,GRNN could maximize the sensitivity to chlorophyll content using D1.It is concluded that RBF may provide a useful exploratory and predictive tool for the estimation of rice biophysical parameters.

  6. Modeling research on wheat protein content measurement using near-infrared reflectance spectroscopy and optimized radial basis function neural network

    Directory of Open Access Journals (Sweden)

    Xiaodong Mao

    2014-06-01

    Full Text Available In this study, near-infrared reflectance spectroscopy and radial basis function (RBF neural network algorithm were used to measure the protein content of wheat owing to their nondestructiveness and quick speed as well as better performance compared to the traditional measuring method (semimicro-Kjeldahl in actual practice. To simplify the complex structure of the RBF network caused by the excessive wave points of samples obtained by near-infrared reflectance spectroscopy, we proposed the particle swarm optimization (PSO algorithm to optimize the cluster center in the hidden layers of the RBF neural network. In addition, a series of improvements for the PSO algorithm was also made to deal with its drawbacks in premature convergence and mechanical inertia weight setting. The experimental analysis demonstrated that the improved PSO algorithm greatly reduced the complexity of the network structure and improved the training speed of the RBF network. Meanwhile, the research result also proved the high performance of the model with its root-mean-square error of prediction (RMSEP and prediction correlation coefficient (R at 0.26576 and 0.975, respectively, thereby fulfilling the modern agricultural testing requirements featuring nondestructiveness, real-timing, and abundance in the number of samples.

  7. The flexible brain - On mind and brain, neural darwinism and psychiatry

    NARCIS (Netherlands)

    DenBoer, JA

    1997-01-01

    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. Investigator

  8. Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network.

    Science.gov (United States)

    Li, Meina; Kwak, Keun-Chang; Kim, Youn Tae

    2016-09-22

    Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model.

  9. Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Meina Li

    2016-09-01

    Full Text Available Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR and movement index (MI monitoring. The embedded incremental network includes linear regression (LR and RBFNN based on context-based fuzzy c-means (CFCM clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model.

  10. Radial Basis Function Neural Networks-Based Modeling of the Membrane Separation Process: Hydrogen Recovery from Refinery Gases

    Institute of Scientific and Technical Information of China (English)

    Lei Wang; Cheng Shao; Hai Wang; Hong Wu

    2006-01-01

    Membrane technology has found wide applications in the petrochemical industry, mainly in the purification and recovery of the hydrogen resources. Accurate prediction of the membrane separation performance plays an important role in carrying out advanced process control (APC). For the first time, a soft-sensor model for the membrane separation process has been established based on the radial basis function (RBF) neural networks. The main performance parameters, i.e, permeate hydrogen concentration, permeate gas flux, and residue hydrogen concentration, are estimated quantitatively by measuring the operating temperature, feed-side pressure, permeate-side pressure, residue-side pressure, feed-gas flux, and feed-hydrogen concentration excluding flow structure, membrane parameters, and other compositions. The predicted results can gain the desired effects. The effectiveness of this novel approach lays a foundation for integrating control technology and optimizing the operation of the gas membrane separation process.

  11. 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.

  12. The neural basis of analogical reasoning: an event-related potential study.

    Science.gov (United States)

    Qiu, Jiang; Li, Hong; Chen, Antao; Zhang, Qinglin

    2008-10-01

    The spatiotemporal analysis of brain activation during the execution of easy analogy (EA) and difficult analogy (DA) tasks was investigated using high-density event-related brain potentials (ERPs). Results showed that reasoning tasks (schema induction) elicited a more negative ERP deflection (N500-1000) than did the baseline task (BS) between 500 and 1000 ms. Dipole source analysis of difference waves (EA-BS and DA-BS) indicated that the negative components were both localized near the left thalamus, possibly associated with the retrieval of alphabetical information. Furthermore, DA elicited a more positive ERP component (P600-1000) than did EA in the same time window. Two generators of P600-1000 were located in the medial prefrontal cortex (BA10) and the left frontal cortex (BA6) which was possibly involved in integrating information in schema abstraction. In the stage of analogy mapping, a greater negativity (N400-600) in the reasoning tasks as compared to BS was found over fronto-central scalp regions. A generator of this effect was located in the left fusiform gyrus and was possibly related to associative memory and activation of schema. Then, a greater negativity in the reasoning tasks, in comparison to BS task, developed between 900-1200 ms (LNC1) and 2000-2500 ms (LNC2). Dipole source analysis (EA-BS) localized the generator of LNC1 in the left prefrontal cortex (BA 10) which was possibly related to mapping the schema to the target problem, and the generator of LNC2 in the left prefrontal cortex (BA 9) which was possibly related to deciding whether a conclusion correctly follows from the schema.

  13. The dynamic brain: from spiking neurons to neural masses and cortical fields.

    Directory of Open Access Journals (Sweden)

    Gustavo Deco

    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

  14. Electrode Wear Prediction in Milling Electrical Discharge Machining Based on Radial Basis Function Neural Network

    Institute of Scientific and Technical Information of China (English)

    HUANG He; BAI Ji-cheng; LU Ze-sheng; GUO Yong-feng

    2009-01-01

    Milling electrical discharge machining (EDM) enables the machining of complex cavities using cylindrical or tubular electrodes. To ensure acceptable machining accuracy the process requires some methods of compensating for electrode wear. Due to the complexity and random nature of the process, existing methods of compensating for such wear usually involve off-line prediction. This paper discusses an innovative model of electrode wear prediction for milling EDM based upon a radial basis function (RBF) network. Data gained from an orthogonal experiment were used to provide training samples for the RBF network. The model established was used to forecast the electrode wear, making it possible to calculate the real-time tool wear in the milling EDM process and, to lay the foundations for dynamic compensation of the electrode wear on-line. This paper demonstrates that by using this model prediction errors can be controlled within 8%.

  15. Brain MR Image Segmentation for Tumor Detection using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Monica Subashini.M

    2013-04-01

    Full Text Available Detection, diagnosis and evaluation of Brain tumour is an important task in recent days. MRI is the current technology which enables the detection, diagnosis and evaluation. The medical problems are severe if tumour is detected at the later stage. Hence diagnosis is necessary at the earliest. In this work, pulse coupled neural network is applied for enhancing the MR Images. The enhanced images aresegmented and classified using back propagation networks. The Classification involves labelling the images into normal and abnormal (tumor detected. If the input MRI brain images are more in number,the physician could seek the help of this model and the network would help the physician to save time for further analysis. PCNN and BPN are less complex in nature and hence the processing of MRI brainimages is very simple. The term ‘abnormal’ indicates the presence of tumour. The tumour may be benign or malignant and it needs medical support for further classification.

  16. Microcephaly disease gene Wdr62 regulates mitotic progression of embryonic neural stem cells and brain size.

    Science.gov (United States)

    Chen, Jian-Fu; Zhang, Ying; Wilde, Jonathan; Hansen, Kirk C; Lai, Fan; Niswander, Lee

    2014-05-30

    Human genetic studies have established a link between a class of centrosome proteins and microcephaly. Current studies of microcephaly focus on defective centrosome/spindle orientation. Mutations in WDR62 are associated with microcephaly and other cortical abnormalities in humans. Here we create a mouse model of Wdr62 deficiency and find that the mice exhibit reduced brain size due to decreased neural progenitor cells (NPCs). Wdr62 depleted cells show spindle instability, spindle assembly checkpoint (SAC) activation, mitotic arrest and cell death. Mechanistically, Wdr62 associates and genetically interacts with Aurora A to regulate spindle formation, mitotic progression and brain size. Our results suggest that Wdr62 interacts with Aurora A to control mitotic progression, and loss of these interactions leads to mitotic delay and cell death of NPCs, which could be a potential cause of human microcephaly.

  17. Neurodevelopment. Live imaging of adult neural stem cell behavior in the intact and injured zebrafish brain.

    Science.gov (United States)

    Barbosa, Joana S; Sanchez-Gonzalez, Rosario; Di Giaimo, Rossella; Baumgart, Emily Violette; Theis, Fabian J; Götz, Magdalena; Ninkovic, Jovica

    2015-05-15

    Adult neural stem cells are the source for restoring injured brain tissue. We used repetitive imaging to follow single stem cells in the intact and injured adult zebrafish telencephalon in vivo and found that neurons are generated by both direct conversions of stem cells into postmitotic neurons and via intermediate progenitors amplifying the neuronal output. We observed an imbalance of direct conversion consuming the stem cells and asymmetric and symmetric self-renewing divisions, leading to depletion of stem cells over time. After brain injury, neuronal progenitors are recruited to the injury site. These progenitors are generated by symmetric divisions that deplete the pool of stem cells, a mode of neurogenesis absent in the intact telencephalon. Our analysis revealed changes in the behavior of stem cells underlying generation of additional neurons during regeneration.

  18. Mechanisms of brain evolution: regulation of neural progenitor cell diversity and cell cycle length.

    Science.gov (United States)

    Borrell, Victor; Calegari, Federico

    2014-09-01

    In the last few years, several studies have revisited long-held assumptions in the field of brain development and evolution providing us with a fundamentally new vision on the mechanisms controlling its size and shape, hence function. Among these studies, some described hitherto unforeseeable subtypes of neural progenitors while others reinterpreted long-known observations about their cell cycle in alternative new ways. Most remarkably, this knowledge combined has allowed the generation of mammalian model organisms in which brain size and folding has been selectively increased giving us the means to understand the mechanisms underlying the evolution of the most complex and sophisticated organ. Here we review the key findings made in this area and make a few conjectures about their evolutionary meaning including the likelihood of Martians conquering our planet.

  19. 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...

  20. Rules from words: a dynamic neural basis for a lawful linguistic process.

    Directory of Open Access Journals (Sweden)

    David W Gow

    Full Text Available Listeners show a reliable bias towards interpreting speech sounds in a way that conforms to linguistic restrictions (phonotactic constraints on the permissible patterning of speech sounds in a language. This perceptual bias may enforce and strengthen the systematicity that is the hallmark of phonological representation. Using Granger causality analysis of magnetic resonance imaging (MRI-constrained magnetoencephalography (MEG and electroencephalography (EEG data, we tested the differential predictions of rule-based, frequency-based, and top-down lexical influence-driven explanations of processes that produce phonotactic biases in phoneme categorization. Consistent with the top-down lexical influence account, brain regions associated with the representation of words had a stronger influence on acoustic-phonetic regions in trials that led to the identification of phonotactically legal (versus illegal word-initial consonant clusters. Regions associated with the application of linguistic rules had no such effect. Similarly, high frequency phoneme clusters failed to produce stronger feedforward influences by acoustic-phonetic regions on areas associated with higher linguistic representation. These results suggest that top-down lexical influences contribute to the systematicity of phonological representation.

  1. The Neural Basis of Smooth Pursuit Eye Movements in the Rhesus Monkey Brain

    Science.gov (United States)

    Ilg, Uwe J.; Thier, Peter

    2008-01-01

    Smooth pursuit eye movements are performed in order to prevent retinal image blur of a moving object. Rhesus monkeys are able to perform smooth pursuit eye movements quite similar as humans, even if the pursuit target does not consist in a simple moving dot. Therefore, the study of the neuronal responses as well as the consequences of…

  2. Three-dimensional brain reconstruction of in vivo electrode tracks for neuroscience and neural prosthetic applications

    Directory of Open Access Journals (Sweden)

    Craig D. Markovitz

    2012-06-01

    Full Text Available The brain is a densely interconnected network that relies on populations of neurons within and across multiple nuclei to code for features leading to perception and action. However, the neurophysiology field is still dominated by the characterization of individual neurons, rather than simultaneous recordings across multiple regions, without consistent spatial reconstruction of their locations for comparisons across studies. There are sophisticated histological and imaging techniques for performing brain reconstructions. However, what is needed is a method that is relatively easy and inexpensive to implement in a typical neurophysiology lab and provides consistent identification of electrode locations to make it widely used for pooling data across studies and research groups. This paper presents our initial development of such an approach for reconstructing electrode tracks and site locations within the guinea pig inferior colliculus (IC to identify its functional organization for frequency coding relevant for a new auditory midbrain implant. Encouragingly, the spatial error associated with different individuals reconstructing electrode tracks for the same midbrain was less than 65 µm, corresponding to an error of ~1.5% relative to the entire IC structure (~4-5 mm diameter sphere. Furthermore, the reconstructed frequency laminae of the IC were consistently aligned across three sampled midbrains, demonstrating the ability to use our method to combine location data across animals. Hopefully, through further improvements in our reconstruction method, it can be used as a standard protocol across neurophysiology labs to characterize neural data not only within the IC but also within other brain regions to help bridge the gap between cellular activity and network function. Clinically, correlating function with location within and across multiple brain regions can guide optimal placement of electrodes for the growing field of neural prosthetics.

  3. 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.

  4. 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.

  5. Analysis of Abnormal Intra-QRS Potentials in Signal-Averaged Electrocardiograms Using a Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Chun-Cheng Lin

    2016-09-01

    Full Text Available Abnormal intra-QRS potentials (AIQPs are commonly observed in patients at high risk for ventricular tachycardia. We present a method for approximating a measured QRS complex using a non-linear neural network with all radial basis functions having the same smoothness. We extracted the high frequency, but low amplitude intra-QRS potentials using the approximation error to identify possible ventricular tachycardia. With a specified number of neurons, we performed an orthogonal least squares algorithm to determine the center of each Gaussian radial basis function. We found that the AIQP estimation error arising from part of the normal QRS complex could cause clinicians to misjudge patients with ventricular tachycardia. Our results also show that it is possible to correct this misjudgment by combining multiple AIQP parameters estimated using various spread parameters and numbers of neurons. Clinical trials demonstrate that higher AIQP-to-QRS ratios in the X, Y and Z leads are visible in patients with ventricular tachycardia than in normal subjects. A linear combination of 60 AIQP-to-QRS ratios can achieve 100% specificity, 90% sensitivity, and 95.8% total prediction accuracy for diagnosing ventricular tachycardia.

  6. Rough set and radial basis function neural network based insulation data mining fault diagnosis for power transformer

    Institute of Scientific and Technical Information of China (English)

    DONG Li-xin; XIAO Deng-ming Xiao; LIU Yi-lu

    2007-01-01

    Rough set (RS) and radial basis function neural network (RBFNN) based insulation data mining fault diagnosis for power transformer is proposed. On the one hand rough set is used as front of RBFNN to simplify the input of RBFNN and mine the rules. The mined rules whose "confidence" and "support" is higher than requirement are used to offer fault diagnosis service for power transformer directly. On the other hand the mining samples corresponding to the mined rule, whose "confidence and support" is lower than requirement,are used to be training samples set of RBFNN and these samples are clustered by rough set. The center of each clustering set is used to be center of radial basis function, i.e. , as the hidden layer neuron. The RBFNN is structured with above base, which is used to diagnose the case that can not be diagnosed by mined simplified valuable rules based on rough set. The advantages and effectiveness of this method are verified by testing.

  7. The Application of Direction Basis Function Neural Networks to the Prediction of Chaotic Time Series

    Institute of Scientific and Technical Information of China (English)

    CAOWenming

    2004-01-01

    In this paper we have examined the ability of Direction basis function networks (DBFN) to predict the output of a chaotic time series generated from a model of a physical system. DBFNs are known to be universal approximators, and chaotic systems are known to exhibit “random” behavior. Therefore the challenge is to apply the DBFN to the prediction of the output of a chaotic system, which we have chosen here to be the Mackey-Glass delay differential equation. The DBFN has been trained with off-line supervised learning using a Recursive Least Squares optimization for obtaining weights. Key issues which are addressed are the estimation of the order of the system and dependence of prediction error on various factors such as placement of DBF centers, selection of perceptive widths, and number of training samples. Included in this study is an implementation of Moody and Darken's K Means Clustering approach to optimally place DBF centers and a heuristic nearest neighbor method for determining perceptive widths.

  8. 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.

  9. Neural stem cell-based dual suicide gene delivery for metastatic brain tumors.

    Science.gov (United States)

    Wang, C; Natsume, A; Lee, H J; Motomura, K; Nishimira, Y; Ohno, M; Ito, M; Kinjo, S; Momota, H; Iwami, K; Ohka, F; Wakabayashi, T; Kim, S U

    2012-11-01

    In our previous works, we demonstrated that human neural stem cells (NSCs) transduced with the cytosine deaminase (CD) gene showed remarkable 'bystander killer effect' on glioma and medulloblastoma cells after administration of the prodrug 5-fluorocytosine (5-FC). In addition, herpes simplex virus thymidine kinase (TK) is a widely studied enzyme used for suicide gene strategies, for which the prodrug is ganciclovir (GCV). To apply this strategy to brain metastasis treatment, we established here a human NSC line (F3.CD-TK) expressing the dual suicide genes CD and TK. We examined whether F3.CD-TK cells intensified the antitumor effect on lung cancer brain metastases. In vitro studies showed that F3.CD-TK cells exerted a marked bystander effect on human lung cancer cells after treatment with 5-FC and GCV. In a novel experimental brain metastases model, intravenously administered F3 cells migrated near lung cancer metastatic lesions, which were induced by the injection of lung cancer cells via the intracarotid artery. More importantly, F3.CD-TK cells in the presence of prodrugs 5-FC and GCV decreased tumor size and considerably prolonged animal survival. The results of the present study indicate that the dual suicide gene-engineered, NSC-based treatment strategy might offer a new promising therapeutic modality for brain metastases.

  10. Injection of SDF-1 loaded nanoparticles following traumatic brain injury stimulates neural stem cell recruitment.

    Science.gov (United States)

    Zamproni, Laura N; Mundim, Mayara V; Porcionatto, Marimelia A; des Rieux, Anne

    2017-03-15

    Recruiting neural stem cell (NSC) at the lesion site is essential for central nervous system repair. This process could be triggered by the local delivery of the chemokine SDF-1. We compared two PLGA formulations for local brain SDF-1 delivery: SDF-1 loaded microspheres (MS) and SDF-1 loaded nanoparticles (NP). Both formulations were able to encapsulate more than 80% of SDF-1 but presented different release profiles, with 100% of SDF-1 released after 6days for the MS and with 25% of SDF-1 released after 2 weeks for NP. SDF-1 bioactivity was demonstrated by a chemotactic assay. When injected in mouse brain after traumatic brain injury, only SDF-1 nanoparticles induced NSC migration to the damage area. More neuroblasts (DCX+ cells) could be visualized around the lesions treated with NP SDF-1 compared to the other conditions. Rostral migratory stream destabilization with massive migration of DCX+ cell toward the perilesional area was observed 2 weeks after NP SDF-1 injection. Local injection of SDF-1-loaded nanoparticles induces recruitment of NSC and could be promising for brain injury lesion.

  11. A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm.

    Science.gov (United States)

    Dethier, Julie; Nuyujukian, Paul; Eliasmith, Chris; Stewart, Terry; Elassaad, Shauki A; Shenoy, Krishna V; Boahen, Kwabena

    2011-01-01

    Motor prostheses aim to restore function to disabled patients. Despite compelling proof of concept systems, barriers to clinical translation remain. One challenge is to develop a low-power, fully-implantable system that dissipates only minimal power so as not to damage tissue. To this end, we implemented a Kalman-filter based decoder via a spiking neural network (SNN) and tested it in brain-machine interface (BMI) experiments with a rhesus monkey. The Kalman filter was trained to predict the arm's velocity and mapped on to the SNN using the Neural Engineering Framework (NEF). A 2,000-neuron embedded Matlab SNN implementation runs in real-time and its closed-loop performance is quite comparable to that of the standard Kalman filter. The success of this closed-loop decoder holds promise for hardware SNN implementations of statistical signal processing algorithms on neuromorphic chips, which may offer power savings necessary to overcome a major obstacle to the successful clinical translation of neural motor prostheses.

  12. The Athlete's Brain: Cross-Sectional Evidence for Neural Efficiency during Cycling Exercise.

    Science.gov (United States)

    Ludyga, Sebastian; Gronwald, Thomas; Hottenrott, Kuno

    2016-01-01

    The "neural efficiency" hypothesis suggests that experts are characterized by a more efficient cortical function in cognitive tests. Although this hypothesis has been extended to a variety of movement-related tasks within the last years, it is unclear whether or not neural efficiency is present in cyclists performing endurance exercise. Therefore, this study examined brain cortical activity at rest and during exercise between cyclists of higher (HIGH; n = 14; 55.6 ± 2.8 mL/min/kg) and lower (LOW; n = 15; 46.4 ± 4.1 mL/min/kg) maximal oxygen consumption (VO2MAX). Male and female participants performed a graded exercise test with spirometry to assess VO2MAX. After 3 to 5 days, EEG was recorded at rest with eyes closed and during cycling at the individual anaerobic threshold over a 30 min period. Possible differences in alpha/beta ratio as well as alpha and beta power were investigated at frontal, central, and parietal sites. The statistical analysis revealed significant differences between groups (F = 12.04; p = 0.002), as the alpha/beta ratio was increased in HIGH compared to LOW in both the resting state (p ≤ 0.018) and the exercise condition (p ≤ 0.025). The present results indicate enhanced neural efficiency in subjects with high VO2MAX, possibly due to the inhibition of task-irrelevant cognitive processes.

  13. The Athlete’s Brain: Cross-Sectional Evidence for Neural Efficiency during Cycling Exercise

    Directory of Open Access Journals (Sweden)

    Sebastian Ludyga

    2016-01-01

    Full Text Available The “neural efficiency” hypothesis suggests that experts are characterized by a more efficient cortical function in cognitive tests. Although this hypothesis has been extended to a variety of movement-related tasks within the last years, it is unclear whether or not neural efficiency is present in cyclists performing endurance exercise. Therefore, this study examined brain cortical activity at rest and during exercise between cyclists of higher (HIGH; n=14; 55.6 ± 2.8 mL/min/kg and lower (LOW; n=15; 46.4 ± 4.1 mL/min/kg maximal oxygen consumption (VO2MAX. Male and female participants performed a graded exercise test with spirometry to assess VO2MAX. After 3 to 5 days, EEG was recorded at rest with eyes closed and during cycling at the individual anaerobic threshold over a 30 min period. Possible differences in alpha/beta ratio as well as alpha and beta power were investigated at frontal, central, and parietal sites. The statistical analysis revealed significant differences between groups (F=12.04; p=0.002, as the alpha/beta ratio was increased in HIGH compared to LOW in both the resting state (p≤0.018 and the exercise condition (p≤0.025. The present results indicate enhanced neural efficiency in subjects with high VO2MAX, possibly due to the inhibition of task-irrelevant cognitive processes.

  14. 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.

  15. 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.

  16. 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.

  17. The strength of a remorseful heart: Psychological and neural basis of how apology emolliates reactive aggression and promotes forgiveness

    Directory of Open Access Journals (Sweden)

    Urielle eBeyens

    2015-10-01

    Full Text Available Apology from the offender facilitates forgiveness and thus has the power to restore a broken relationship. Here we showed that apology from the offender not only reduces the victim’s propensity to react aggressively but also alters the victim’s implicit attitude and neural responses towards the offender. We adopted an interpersonal competitive game which consisted of two phases. In the first, passive phase, participants were punished by high or low pain stimulation chosen by the opponents when losing a trial. During the break, participants received a note from each of the opponents, one apologizing and the other not. The second, active phase involved a change of roles where participants could punish the two opponents when winning. Experiment 1 included an Implicit Association Test (IAT in between the reception of notes and the second phase. Experiment 2 recorded participants’ brain potentials in the second phase. We found that participants reacted less aggressively towards the apologizing opponent than the non-apologizing opponent in the active phase. Moreover, female, but not male, participants responded faster in the IAT when positive and negative words were associated to the apologizing and the non-apologizing opponents, respectively, suggesting that female participants had enhanced implicit attitude towards the apologizing opponent. Furthermore, the late positive component (LPP in brain potentials, a component associated with affective/motivational reactions, was larger for viewing the portrait of the apologizing than the non-apologizing opponent when participants subsequently selected low punishment. Additionally, the LPP elicited by the apologizing opponents’ portrait was larger in the female than in the male participants. These findings confirm the apology’s role in reducing reactive aggression and further reveal that this forgiveness process engages, at least in female, an enhancement of the victim’s implicit attitude and a

  18. The strength of a remorseful heart: psychological and neural basis of how apology emolliates reactive aggression and promotes forgiveness.

    Science.gov (United States)

    Beyens, Urielle; Yu, Hongbo; Han, Ting; Zhang, Li; Zhou, Xiaolin

    2015-01-01

    Apology from the offender facilitates forgiveness and thus has the power to restore a broken relationship. Here we showed that apology from the offender not only reduces the victim's propensity to react aggressively but also alters the victim's implicit attitude and neural responses toward the offender. We adopted an interpersonal competitive game which consisted of two phases. In the first, "passive" phase, participants were punished by high or low pain stimulation chosen by the opponents when losing a trial. During the break, participants received a note from each of the opponents, one apologizing and the other not. The second, "active" phase, involved a change of roles where participants could punish the two opponents after winning. Experiment 1 included an Implicit Association Test (IAT) in between the reception of notes and the second phase. Experiment 2 recorded participants' brain potentials in the second phase. We found that participants reacted less aggressively toward the apologizing opponent than the non-apologizing opponent in the active phase. Moreover, female, but not male, participants responded faster in the IAT when positive and negative words were associated with the apologizing and the non-apologizing opponents, respectively, suggesting that female participants had enhanced implicit attitude toward the apologizing opponent. Furthermore, the late positive potential (LPP), a component in brain potentials associated with affective/motivational reactions, was larger when viewing the portrait of the apologizing than the non-apologizing opponent when participants subsequently selected low punishment. Additionally, the LPP elicited by the apologizing opponents' portrait was larger in the female than in the male participants. These findings confirm the apology's role in reducing reactive aggression and further reveal that this forgiveness process engages, at least in female, an enhancement of the victim's implicit attitude and a prosocial motivational

  19. Brain vascular pericytes following ischemia have multipotential stem cell activity to differentiate into neural and vascular lineage cells.

    Science.gov (United States)

    Nakagomi, Takayuki; Kubo, Shuji; Nakano-Doi, Akiko; Sakuma, Rika; Lu, Shan; Narita, Aya; Kawahara, Maiko; Taguchi, Akihiko; Matsuyama, Tomohiro

    2015-06-01

    Brain vascular pericytes (PCs) are a key component of the blood-brain barrier (BBB)/neurovascular unit, along with neural and endothelial cells. Besides their crucial role in maintaining the BBB, increasing evidence shows that PCs have multipotential stem cell activity. However, their multipotency has not been considered in the pathological brain, such as after an ischemic stroke. Here, we examined whether brain vascular PCs following ischemia (iPCs) have multipotential stem cell activity and differentiate into neural and vascular lineage cells to reconstruct the BBB/neurovascular unit. Using PCs extracted from ischemic regions (iPCs) from mouse brains and human brain PCs cultured under oxygen/glucose deprivation, we show that PCs developed stemness presumably through reprogramming. The iPCs revealed a complex phenotype of angioblasts, in addition to their original mesenchymal properties, and multidifferentiated into cells from both a neural and vascular lineage. These data indicate that under ischemic/hypoxic conditions, PCs can acquire multipotential stem cell activity and can differentiate into major components of the BBB/neurovascular unit. Thus, these findings support the novel concept that iPCs can contribute to both neurogenesis and vasculogenesis at the site of brain injuries.

  20. Modular organization as a basis for the functional integration/segregation in large-scale brain networks

    CERN Document Server

    Valencia, M; Fernandez-Seara, MA; Artieda, J; Martinerie, J; Chavez, M

    2009-01-01

    Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large-scale (voxel level) extracted from functional magnetic resonance imaging (fMRI) signals. By using a random walk-based method, we unveil the modularity of brain-webs, and show that modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intra-modular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

  1. 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.

  2. Is this a brain which I see before me? Modeling human neural development with pluripotent stem cells.

    Science.gov (United States)

    Suzuki, Ikuo K; Vanderhaeghen, Pierre

    2015-09-15

    The human brain is arguably the most complex structure among living organisms. However, the specific mechanisms leading to this complexity remain incompletely understood, primarily because of the poor experimental accessibility of the human embryonic brain. Over recent years, technologies based on pluripotent stem cells (PSCs) have been developed to generate neural cells of various types. While the translational potential of PSC technologies for disease modeling and/or cell replacement therapies is usually put forward as a rationale for their utility, they are also opening novel windows for direct observation and experimentation of the basic mechanisms of human brain development. PSC-based studies have revealed that a number of cardinal features of neural ontogenesis are remarkably conserved in human models, which can be studied in a reductionist fashion. They have also revealed species-specific features, which constitute attractive lines of investigation to elucidate the mechanisms underlying the development of the human brain, and its link with evolution.

  3. 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.

  4. Neural Resilience to Traumatic Brain Injury: Identification of Bioactive Metabolites of Docosahexaenoic Acids Involved in Neuroprotection and Recovery

    Science.gov (United States)

    2015-05-01

    rates of traumatic brain injury (TBI) causing lifelong neurological and cognitive impairments, especially in learning and memory . Numerous studies...Hamilton, R.S. Greiner, T. Moriguchi, N. Salem, Jr., and H.Y. Kim, Differential effects of n-3 fatty acid deficiency on phospholipid molecular species...project are to develop strategies to improve neural resilience to traumatic brain injury and facilitate recovery through mechanism- based optimization of

  5. Brain-Computer Interface for Control of Wheelchair Using Fuzzy Neural Networks

    Science.gov (United States)

    Akkaya, Nurullah; Aytac, Ersin; Günsel, Irfan; Çağman, Ahmet

    2016-01-01

    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. PMID:27777953

  6. Binary Color Classification For Brain Computer Interface Using Neural Networks And Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Charmi Sunil Mehta

    2014-04-01

    Full Text Available As the power of modern computers grows alongside our understanding of the human brain, we move a step closer in transforming some pretty spectacular science fiction into reality. The advent of Brain Computer Interface (BCI is indeed leading us to a burgeoning era of complete automation empowering our interaction with computer not only with robustness but with also a gift of intelligence. For the fraction of our society suffering from severe motor disabilities BCI has offered a novel solution of overcoming the problems faced in communicating and environment control. Thus the purpose of our current research is to harness the brain‟s ability to generate Visually Evoked Potentials (VEPs by capturing the response of the brain to the transitions of color from grey to green and grey to red. Our prime focus is to explore EEG-based signal processing techniques in order to classify two colors; which can be further deployed in future by coupling the actuators so as to perform few basic tasks. The extracted EEG features are classified using Support Vector Machines (SVM and Artificial Neural Networks (ANN. We recorded 100% accuracy on testing the model after training and validation process. Moreover, we obtained 90% accuracy on re-testing the model with all samples acquired for the task using Quadratic SVM classifier.

  7. 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.

  8. 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.

  9. Design of radial basis function neural network classifier realized with the aid of data preprocessing techniques: design and analysis

    Science.gov (United States)

    Oh, Sung-Kwun; Kim, Wook-Dong; Pedrycz, Witold

    2016-05-01

    In this paper, we introduce a new architecture of optimized Radial Basis Function neural network classifier developed with the aid of fuzzy clustering and data preprocessing techniques and discuss its comprehensive design methodology. In the preprocessing part, the Linear Discriminant Analysis (LDA) or Principal Component Analysis (PCA) algorithm forms a front end of the network. The transformed data produced here are used as the inputs of the network. In the premise part, the Fuzzy C-Means (FCM) algorithm determines the receptive field associated with the condition part of the rules. The connection weights of the classifier are of functional nature and come as polynomial functions forming the consequent part. The Particle Swarm Optimization algorithm optimizes a number of essential parameters needed to improve the accuracy of the classifier. Those optimized parameters include the type of data preprocessing, the dimensionality of the feature vectors produced by the LDA (or PCA), the number of clusters (rules), the fuzzification coefficient used in the FCM algorithm and the orders of the polynomials of networks. The performance of the proposed classifier is reported for several benchmarking data-sets and is compared with the performance of other classifiers reported in the previous studies.

  10. 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.

  11. Brain Basics

    Medline Plus

    Full Text Available ... News 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 ...

  12. Brain Basics

    Science.gov (United States)

    ... News 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 ...

  13. 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…

  14. Genetic basis of human brain evolution: accelerating along the primate speedway.

    Science.gov (United States)

    Hayakawa, Toshiyuki; Altheide, Tasha K; Varki, Ajit

    2005-01-01

    Using novel variations of traditional methods, report in the December 29(th) issue of Cell that diverse genes involved in neural biology (particularly those critical in development) show higher rates of protein evolution in primates than in rodents-particularly in the lineage leading to humans.

  15. Activin and TGF-β effects on brain development and neural stem cells.

    Science.gov (United States)

    Rodríguez-Martínez, Griselda; Velasco, Iván

    2012-11-01

    Transforming Growth Factor-β (TGF-β) family members are ubiquitously expressed, participating in the regulation of many processes in different cell types both in embryonic and adult stages. Several members of this family, including Activins, TGF-β1-3 and Nodal, have been implicated in the development and maintenance of various organs, in which stem cells play important roles. Although TGF-β was initially considered an injury-related cytokine, it became clear that not only TGF-β, but other members of this family, play critical roles in morphogenesis and cell lineage specification. During brain development, Activin and TGF-βs as well as their cognate receptors, are expressed in different patterns. The roles of Activin and TGF-β during CNS development are sometimes contradictory, because these proteins present different actions depending on the cell type and the context. The aim of this review is to summarize current information on the actions of TGF-β members during developing brain, and also on Neural Stem/Progenitor Cells (NSPC). We focus on the TGF-β subgroup, specifically on the effects of TGF-β1 and Activin A. In the first section we describe the main characteristics of the ligands, its receptors as well as the proteins and mechanisms involved in signaling. Next, we discuss the main advances concerning TGF-β1 and Activin actions during brain development and their roles in NSPC fate decision and neuroprotection both in vitro and in vivo. The emerging picture from these studies suggests that these growth factors can be used to manipulate neurogenesis and might help to achieve restoration after brain deterioration.

  16. Histone deacetylases 1 and 2 control the progression of neural precursors to neurons during brain development

    Science.gov (United States)

    Montgomery, Rusty L.; Hsieh, Jenny; Barbosa, Ana C.; Richardson, James A.; Olson, Eric N.

    2009-01-01

    The molecular mechanism by which neural progenitor cells commit to a specified lineage of the central nervous system remains unknown. We show that HDAC1 and HDAC2 redundantly control neuronal development and are required for neuronal specification. Mice lacking HDAC1 or HDAC2 in neuronal precursors show no overt histoarchitectural phenotypes, whereas deletion of both HDAC1 and HDAC2 in developing neurons results in severe hippocampal abnormalities, absence of cerebellar foliation, disorganization of cortical neurons, and lethality by postnatal day 7. These abnormalities in brain formation can be attributed to a failure of neuronal precursors to differentiate into mature neurons and to excessive cell death. These results reveal redundant and essential roles for HDAC1 and HDAC2 in the progression of neuronal precursors to mature neurons in vivo. PMID:19380719

  17. Microbiota-generated metabolites promote metabolic benefits via gut-brain neural circuits.

    Science.gov (United States)

    De Vadder, Filipe; Kovatcheva-Datchary, Petia; Goncalves, Daisy; Vinera, Jennifer; Zitoun, Carine; Duchampt, Adeline; Bäckhed, Fredrik; Mithieux, Gilles

    2014-01-16

    Soluble dietary fibers promote metabolic benefits on body weight and glucose control, but underlying mechanisms are poorly understood. Recent evidence indicates that intestinal gluconeogenesis (IGN) has beneficial effects on glucose and energy homeostasis. Here, we show that the short-chain fatty acids (SCFAs) propionate and butyrate, which are generated by fermentation of soluble fiber by the gut microbiota, activate IGN via complementary mechanisms. Butyrate activates IGN gene expression through a cAMP-dependent mechanism, while propionate, itself a substrate of IGN, activates IGN gene expression via a gut-brain neural circuit involving the fatty acid receptor FFAR3. The metabolic benefits on body weight and glucose control induced by SCFAs or dietary fiber in normal mice are absent in mice deficient for IGN, despite similar modifications in gut microbiota composition. Thus, the regulation of IGN is necessary for the metabolic benefits associated with SCFAs and soluble fiber.

  18. 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.

  19. 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.

  20. Interpreting the effects of altered brain anatomical connectivity on fMRI functional connectivity: a role for computational neural modeling.

    Science.gov (United States)

    Horwitz, Barry; Hwang, Chuhern; Alstott, Jeff

    2013-01-01

    Recently, there have been a large number of studies using resting state fMRI to characterize abnormal brain connectivity in patients with a variety of neurological, psychiatric, and developmental disorders. However, interpreting what the differences in resting state fMRI functional connectivity (rsfMRI-FC) actually reflect in terms of the underlying neural pathology has proved to be elusive because of the complexity of brain anatomical connectivity. The same is the case for task-based fMRI studies. In the last few years, several groups have used large-scale neural modeling to help provide some insight into the relationship between brain anatomical connectivity and the corresponding patterns of fMRI-FC. In this paper we review several efforts at using large-scale neural modeling to investigate the relationship between structural connectivity and functional/effective connectivity to determine how alterations in structural connectivity are manifested in altered patterns of functional/effective connectivity. Because the alterations made in the anatomical connectivity between specific brain regions in the model are known in detail, one can use the results of these simulations to determine the corresponding alterations in rsfMRI-FC. Many of these simulation studies found that structural connectivity changes do not necessarily result in matching changes in functional/effective connectivity in the areas of structural modification. Often, it was observed that increases in functional/effective connectivity in the altered brain did not necessarily correspond to increases in the strength of the anatomical connection weights. Note that increases in rsfMRI-FC in patients have been interpreted in some cases as resulting from neural plasticity. These results suggest that this interpretation can be mistaken. The relevance of these simulation findings to the use of functional/effective fMRI connectivity as biomarkers for brain disorders is also discussed.

  1. The neural underpinnings of associative learning in health and psychosis: how can performance be preserved when brain responses are abnormal?

    Science.gov (United States)

    Murray, Graham K; Corlett, Philip R; Fletcher, Paul C

    2010-05-01

    Associative learning experiments in schizophrenia and other psychoses reveal subtle abnormalities in patients' brain responses. These are sometimes accompanied by intact task performance. An important question arises: How can learning occur if the brain system is not functioning normally? Here, we examine a series of possible explanations for this apparent discrepancy: (1) standard brain activation patterns may be present in psychosis but partially obscured by greater noise, (2) brain signals may be more sensitive to real group differences than behavioral measures, and (3) patients may achieve comparable levels of performance to control subjects by employing alternative or compensatory neural strategies. We consider these explanations in relation to data from causal- and reward-learning imaging experiments in first-episode psychosis patients. The findings suggest that a combination of these factors may resolve the question of why performance is sometimes preserved when brain patterns are disrupted.

  2. In vivo imaging of endogenous neural stem cells in theadult brain

    Institute of Scientific and Technical Information of China (English)

    Maria Adele Rueger; Michael Schroeter

    2015-01-01

    The discovery of endogenous neural stem cells (eNSCs) inthe adult mammalian brain with their ability to self-renewand differentiate into functional neurons, astrocytes andoligodendrocytes has raised the hope for novel therapiesof neurological diseases. Experimentally, those eNSCscan be mobilized in vivo , enhancing regeneration andaccelerating functional recovery after, e.g., focal cerebralischemia, thus constituting a most promising approachin stem cell research. In order to translate those currentexperimental approaches into a clinical setting in thefuture, non-invasive imaging methods are required tomonitor eNSC activation in a longitudinal and intraindividualmanner. As yet, imaging protocols to assesseNSC mobilization non-invasively in the live brain remainscarce, but considerable progress has been made inthis field in recent years. This review summarizes anddiscusses the current imaging modalities suitable tomonitor eNSCs in individual experimental animals overtime, including optical imaging, magnetic resonancetomography and-spectroscopy, as well as positronemission tomography (PET). Special emphasis is puton the potential of each imaging method for a possibleclinical translation, and on the specificity of the signalobtained. PET-imaging with the radiotracer 3'-deoxy-3'-[18F]fluoro-L-thymidine in particular constitutes amodality with excellent potential for clinical translationbut low specificity; however, concomitant imaging ofneuroinflammation is feasible and increases its specificity.The non-invasive imaging strategies presented here allowfor the exploitation of novel treatment strategies basedupon the regenerative potential of eNSCs, and will helpto facilitate a translation into the clinical setting.

  3. Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders

    Science.gov (United States)

    Georgopoulos, Apostolos P.; Karageorgiou, Elissaios; Leuthold, Arthur C.; Lewis, Scott M.; Lynch, Joshua K.; Alonso, Aurelio A.; Aslam, Zaheer; Carpenter, Adam F.; Georgopoulos, Angeliki; Hemmy, Laura S.; Koutlas, Ioannis G.; Langheim, Frederick J. P.; Riley McCarten, J.; McPherson, Susan E.; Pardo, José V.; Pardo, Patricia J.; Parry, Gareth J.; Rottunda, Susan J.; Segal, Barbara M.; Sponheim, Scott R.; Stanwyck, John J.; Stephane, Massoud; Westermeyer, Joseph J.

    2007-12-01

    We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45-60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCCij0) and their z-transforms (zij0) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of zij0 successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjögren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results. Contribution by the authors: Designed research (APG); acquired data (AAA, IGK, FJPL, ACL, SML, JJS); analyzed data (APG, EK, ACL, JKL); wrote the paper (APG, EK, ACL, SML); contributed subjects (AAA, ZA, AFC, AG, LSH, IGK, FJPL, SML, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW); discussed results (All); contributed equally (ZA, AFC, AG, LSH, FJPL, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW).

  4. 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.

  5. 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.

  6. Analysis of neural activity in human motor cortex -- Towards brain machine interface system

    Science.gov (United States)

    Secundo, Lavi

    , the correlation of ECoG activity to kinematic parameters of arm movement is context-dependent, an important constraint to consider in future development of BMI systems. The third chapter delves into a fundamental organizational principle of the primate motor system---cortical control of contralateral limb movements. However, ipsilateral motor areas also appear to play a role in the control of ipsilateral limb movements. Several studies in monkeys have shown that individual neurons in ipsilateral primary motor cortex (M1) may represent, on average, the direction of movements of the ipsilateral arm. Given the increasing body of evidence demonstrating that neural ensembles can reliably represent information with a high temporal resolution, here we characterize the distributed neural representation of ipsilateral upper limb kinematics in both monkey and man. In two macaque monkeys trained to perform center-out reaching movements, we found that the ensemble spiking activity in M1 could continuously represent ipsilateral limb position. We also recorded cortical field potentials from three human subjects and also consistently found evidence of a neural representation for ipsilateral movement parameters. Together, our results demonstrate the presence of a high-fidelity neural representation for ipsilateral movement and illustrates that it can be successfully incorporated into a brain-machine interface.

  7. Subpixel mapping on remote sensing imagery using a prediction model combining wavelet transform and radial basis function neural network

    Science.gov (United States)

    Dai, Xiaoyan; Guo, Zhongyang; Zhang, Liquan; Xu, Wencheng

    2009-12-01

    Soft classification methods can be used for mixed-pixel classification on remote sensing imagery by estimating different land cover class fractions of every pixel. However, the spatial distribution and location of these class components within the pixel remain unknown. To map land cover at subpixel scale and increase the spatial resolution of land cover classification maps, in this paper, a prediction model combining wavelet transform and Radial Basis Functions (RBF) neural network, abbreviated as Wavelet-RBFNN, is constructed by predicting high-frequency wavelet coefficients from low-frequency coefficients at the same resolution with RBF network and taking wavelet coefficients at coarser resolution as training samples. According to different land cover class fraction images obtained from mixed-pixel classification, based on the assumption of neighborhood dependence of wavelet coefficients, subpixel mapping on remote sensing imagery can be accomplished through two steps, i.e., prediction of land cover class compositions within subpixels and hard classification. The experimental results obtained with artificial images, QuickBird image and Landsat 7 ETM+ image indicate that the subpixel mapping method proposed in this paper can successfully produce super-resolution land cover classification maps from remote sensing imagery, outperforming cubic B-spline and Kriging interpolation method in visual effect and prediction accuracy. The Wavelet-RBFNN model can also be applied to simulate higher spatial resolution image, and automatically identify and locate land cover targets at the subpixel scales, when the cost and availability of high resolution imagery prohibit its use in many areas of work.

  8. Evaluation of region selective bilirubin-induced brain damage as a basis for a pharmacological treatment

    Science.gov (United States)

    Dal Ben, Matteo; Bottin, Cristina; Zanconati, Fabrizio; Tiribelli, Claudio; Gazzin, Silvia

    2017-01-01

    The neurologic manifestations of neonatal hyperbilirubinemia in the central nervous system (CNS) exhibit high variations in the severity and appearance of motor, auditory and cognitive symptoms, which is suggestive of a still unexplained selective topography of bilirubin-induced damage. By applying the organotypic brain culture (OBC: preserving in vitro the cellular complexity, connection and architecture of the in vivo brain) technique to study hyperbilirubinemia, we mapped the regional target of bilirubin-induced damage, demonstrated a multifactorial toxic action of bilirubin, and used this information to evaluate the efficacy of drugs applicable to newborns to protect the brain. OBCs from 8-day-old rat pups showed a 2–13 fold higher sensitivity to bilirubin damage than 2-day-old preparations. The hippocampus, inferior colliculus and cerebral cortex were the only brain regions affected, presenting a mixed inflammatory-oxidative mechanism. Glutamate excitotoxicity was appreciable in only the hippocampus and inferior colliculus. Single drug treatment (indomethacin, curcumin, MgCl2) significantly improved cell viability in all regions, while the combined (cocktail) administration of the three drugs almost completely prevented damage in the most affected area (hippocampus). Our data may supports an innovative (complementary to phototherapy) approach for directly protecting the newborn brain from bilirubin neurotoxicity. PMID:28102362

  9. Alloimmunisation to donor antigens and immune rejection following foetal neural grafts to the brain in patients with Huntington's disease.

    Directory of Open Access Journals (Sweden)

    Pierre Krystkowiak

    Full Text Available BACKGROUND: The brain is deemed "immunologically privileged" due to sparse professional antigen-presenting cells and lymphatic drainage, and to the blood-brain barrier. Although the actual extent of this privilege is controversial, there is general consensus about the limited need in intracerebral neural grafts for immunosuppressive regimens comparable to those used in other cases of allotransplantation. This has led over the past fifteen years to the use of either short-term or even no immunosuppression in most clinical trials with foetal neural transplant in patients with Parkinson's and Huntington's disease. METHODOLOGY/PRINCIPAL FINDINGS: We report biological demonstration of alloimmunisation without signs of rejection in four grafted patients out of 13 studied during the course of a clinical trial involving fetal neural transplantation in patients with Huntington's Disease. Biological, radiological and clinical demonstration of an ongoing rejection process was observed in a fifth transplanted patient. The rejection process was, however, fully reversible under immunosuppressive treatment and graft activity recovered within six months. CONCLUSIONS/SIGNIFICANCE: There had been, up to date, no report of documented cases that could have cast a doubt on those procedures. Our results underline the need for a reconsideration of the extent of the so-called immune privilege of the brain and of the follow-up protocols of patients with intracerebral grafts. It also suggests that some of the results obtained in past studies with foetal neural transplants may have been biased by an unrecognized immune response to donor cells.

  10. Functional electrical stimulation-facilitated proliferation and regeneration of neural precursor cells in the brains of rats with cerebral infarction

    Institute of Scientific and Technical Information of China (English)

    Yun Xiang; Huihua Liu; Tiebin Yan; Zhiqiang Zhuang; Dongmei Jin; Yuan Peng

    2014-01-01

    Previous studies have shown that proliferation of endogenous neural precursor cells cannot alone compensate for the damage to neurons and axons. From the perspective of neural plastici-ty, we observed the effects of functional electrical stimulation treatment on endogenous neural precursor cell proliferation and expression of basic fibroblast growth factor and epidermal growth factor in the rat brain on the infarct side. Functional electrical stimulation was performed in rat models of acute middle cerebral artery occlusion. Simultaneously, we set up a placebo stimulation group and a sham-operated group. Immunohistochemical staining showed that, at 7 and 14 days, compared with the placebo group, the numbers of nestin (a neural precursor cell marker)-positive cells in the subgranular zone and subventricular zone were increased in the functional electrical stimulation treatment group. Western blot assays and reverse-transcription PCR showed that total protein levels and gene expression of epidermal growth factor and basic ifbroblast growth factor were also upregulated on the infarct side. Prehensile traction test results showed that, at 14 days, prehension function of rats in the functional electrical stimulation group was signiifcantly better than in the placebo group. These results suggest that functional electrical stimulation can promote endogenous neural precursor cell proliferation in the brains of acute cerebral infarction rats, enhance expression of basic fibroblast growth factor and epidermal growth factor, and improve the motor function of rats.

  11. Recent advances in the involvement of long non-coding RNAs in neural stem cell biology and brain pathophysiology

    Directory of Open Access Journals (Sweden)

    Daphne eAntoniou

    2014-04-01

    Full Text Available Exploration of non-coding genome has recently uncovered a growing list of formerly unknown regulatory long non-coding RNAs (lncRNAs with important functions in stem cell pluripotency, development and homeostasis of several tissues. Although thousands of lncRNAs are expressed in mammalian brain in a highly patterned manner, their roles in brain development have just begun to emerge. Recent data suggest key roles for these molecules in gene regulatory networks controlling neuronal and glial cell differentiation. Analysis of the genomic distribution of genes encoding for lncRNAs indicates a physical association of these regulatory RNAs with transcription factors (TFs with well-established roles in neural differentiation, suggesting that lncRNAs and TFs may form coherent regulatory networks with important functions in neural stem cells (NSCs. Additionally, many studies show that lncRNAs are involved in the pathophysiology of brain-related diseases/disorders. Here we discuss these observations and investigate the links between lncRNAs, brain development and brain-related diseases. Understanding the functions of lncRNAs in NSCs and brain organogenesis could revolutionize the basic principles of developmental biology and neuroscience.

  12. 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 huma

  13. 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.

  14. Are human dental papilla-derived stem cell and human brain-derived neural stem cell transplantations suitable for treatment of Parkinson's disease?

    Institute of Scientific and Technical Information of China (English)

    Hyung Ho Yoon; Joongkee Min; Nari Shin; Yong Hwan Kim; Jin-Mo Kim; Yu-Shik Hwang; Jun-Kyo Francis Suh; Onyou Hwang; Sang Ryong Jeon

    2013-01-01

    Transplantation of neural stem cells has been reported as a possible approach for replacing impaired dopaminergic neurons. In this study, we tested the efficacy of early-stage human dental papilla-derived stem cells and human brain-derived neural stem cells in rat models of 6-hydroxydopamine-induced Parkinson's disease. Rats received a unilateral injection of 6-hydroxydopamine into right medial forebrain bundle, followed 3 weeks later by injections of PBS, early-stage human dental papilla-derived stem cells, or human brain-derived neural stem cells into the ipsilateral striatum. All of the rats in the human dental papilla-derived stem cell group died from tumor formation at around 2 weeks following cell transplantation. Postmortem examinations revealed homogeneous malignant tumors in the striatum of the human dental papilla-derived stem cell group. Stepping tests revealed that human brain-derived neural stem cell transplantation did not improve motor dysfunction. In apomorphine-induced rotation tests, neither the human brain-derived neural stem cell group nor the control groups (PBS injection) demonstrated significant changes. Glucose metabolism in the lesioned side of striatum was reduced by human brain-derived neural stem cell transplantation. [18 F]-FP-CIT PET scans in the striatum did not demonstrate a significant increase in the human brain-derived neural stem cell group. Tyrosine hydroxylase (dopaminergic neuronal marker) staining and G protein-activated inward rectifier potassium channel 2 (A9 dopaminergic neuronal marker) were positive in the lesioned side of striatum in the human brain-derived neural stem cell group. The use of early-stage human dental papilla-derived stem cells confirmed its tendency to form tumors. Human brain-derived neural stem cells could be partially differentiated into dopaminergic neurons, but they did not secrete dopamine.

  15. Study of brain-derived neurotrophic factor gene transgenic neural stem cells in the rat retina

    Institute of Scientific and Technical Information of China (English)

    ZHOU Xue-mei; YUAN Hui-ping; WU Dong-lai; ZHOU Xin-rong; SUN Da-wei; LI Hong-yi; SHAO Zheng-bo

    2009-01-01

    Background 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. Methods 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. Results 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<0.05) and at protein level measured by ELISA (P<0.05), which showed that BDNF was overexpressed in BDNF-NSCs. The results of HRA demonstrated that graft cells could survive well and migrate into the host retinas, while the immunohistochemical analysis revealed that transplanted BDNF-NSCs differentiated into neuron more efficiently compared with the control NSCs 2 months after transplantation. Conclusions The seed cells of NSCs highly secreting BDNF were established. BDNF can promote NSCs to migrate and differentiate into neural cells in

  16. 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 for successful performance of the IGT, and increased activity in the caudate, a region associated with impulsive choice. The

  17. Identification and culture of neural stem cells isolated from adult rat subventricular zone following fluid percussion brain injury

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Objective To analyze proliferation and differentiation of glial fibrillary acid protein(GFAP)-and nestin-positive(GFAP+/nestin+)cells isolated from the subventricular zone following fluid percussion brain injury to determine whether GFAP+/nestin+ cells exhibit characteristics of neural stem cells.Methods Male Sprague-Dawley rats,aged 12 weeks and weighing 200-250 g,were randomly and evenly assigned to normal control group and model group.In the model group,a rat model of fluid percussion brain injury was es...

  18. The use of brain imaging to elucidate neural circuit changes in cocaine addiction

    Directory of Open Access Journals (Sweden)

    Hanlon CA

    2012-09-01

    Full Text Available Colleen A Hanlon,1,2 Melanie Canterberry11Department of Psychiatry and Behavioral Sciences, 2Department of Neurosciences Medical University of South Carolina, Charleston, SC, USAAbstract: Within substance abuse, neuroimaging has experienced tremendous growth as both a research method and a clinical tool in the last decade. The application of functional imaging methods to cocaine dependent patients and individuals in treatment programs, has revealed that the effects of cocaine are not limited to dopamine-rich subcortical structures, but that the cortical projection areas are also disrupted in cocaine dependent patients. In this review, we will first describe several of the imaging methods that are actively being used to address functional and structural abnormalities in addiction. This will be followed by an overview of the cortical and subcortical brain regions that are most often cited as dysfunctional in cocaine users. We will also introduce functional connectivity analyses currently being used to investigate interactions between these cortical and subcortical areas in cocaine users and abstainers. Finally, this review will address recent research which demonstrates that alterations in the functional connectivity in cocaine users may be associated with structural pathology in these circuits, as demonstrated through diffusion tensor imaging. Through the use of these tools in both a basic science setting and as applied to treatment seeking individuals, we now have a greater understanding of the complex cortical and subcortical networks which contribute to the stages of initial craving, dependence, abstinence, and relapse. Although the ability to use neuroimaging to predict treatment response or identify vulnerable populations is still in its infancy, the next decade holds tremendous promise for using neuroimaging to tailor either behavioral or pharmacologic treatment interventions to the individual.Keywords: addiction, neural circuit, functional

  19. Dual Channel Pulse Coupled Neural Network Algorithm for Fusion of Multimodality Brain Images with Quality Analysis

    Directory of Open Access Journals (Sweden)

    Kavitha SRINIVASAN

    2014-09-01

    Full Text Available Background: In the review of medical imaging techniques, an important fact that emerged is that radiologists and physicians still are in a need of high-resolution medical images with complementary information from different modalities to ensure efficient analysis. This requirement should have been sorted out using fusion techniques with the fused image being used in image-guided surgery, image-guided radiotherapy and non-invasive diagnosis. Aim: This paper focuses on Dual Channel Pulse Coupled Neural Network (PCNN Algorithm for fusion of multimodality brain images and the fused image is further analyzed using subjective (human perception and objective (statistical measures for the quality analysis. Material and Methods: The modalities used in fusion are CT, MRI with subtypes T1/T2/PD/GAD, PET and SPECT, since the information from each modality is complementary to one another. The objective measures selected for evaluation of fused image were: Information Entropy (IE - image quality, Mutual Information (MI – deviation in fused to the source images and Signal to Noise Ratio (SNR – noise level, for analysis. Eight sets of brain images with different modalities (T2 with T1, T2 with CT, PD with T2, PD with GAD, T2 with GAD, T2 with SPECT-Tc, T2 with SPECT-Ti, T2 with PET are chosen for experimental purpose and the proposed technique is compared with existing fusion methods such as the Average method, the Contrast pyramid, the Shift Invariant Discrete Wavelet Transform (SIDWT with Harr and the Morphological pyramid, using the selected measures to ascertain relative performance. Results: The IE value and SNR value of the fused image derived from dual channel PCNN is higher than other fusion methods, shows that the quality is better with less noise. Conclusion: The fused image resulting from the proposed method retains the contrast, shape and texture as in source images without false information or information loss.

  20. Candy and the brain: neural response to candy gains and losses.

    Science.gov (United States)

    Luking, Katherine R; Barch, Deanna M

    2013-09-01

    Incentive processing is a critical component of a host of cognitive processes, including attention, motivation, and learning. Neuroimaging studies have clarified the neural systems underlying processing of primary and secondary rewards in adults. However, current reward paradigms have hindered comparisons across these reward types as well as between age groups. To address methodological issues regarding the timing of incentive delivery (during scan vs. postscan) and the age-appropriateness of the incentive type, we utilized fMRI and a modified version of a card-guessing game (CGG), in which candy pieces delivered postscan served as the reinforcer, to investigate neural responses to incentives. Healthy young adults 22-26 years of age won and lost large and small amounts of candy on the basis of their ability to guess the number on a mystery card. BOLD activity was compared following candy gain (large/small), loss (large/small), and neutral feedback. During candy gains, adults recruited regions typically involved in response to monetary and other rewards, such as the caudate, putamen, and orbitofrontal cortex. During losses, they displayed greater deactivation in the hippocampus than in response to neutral and gain feedback. Additionally, individual-difference analyses suggested a negative relationship between reward sensitivity (assessed by the Behavioral Inhibition/Behavioral Activation Scales) and the difference between high- and low-magnitude losses in the caudate and lateral orbitofrontal cortex. Also within the striatum, greater punishment sensitivity was positively related to the difference in activity following high as compared to low gains. Overall, these results show strong overlap with those from previous monetary versions of the CGG and provide a baseline for future work with developmental populations.

  1. Neural Decoding and “Inner” Psychophysics: A Distance-to-Bound Approach for Linking Mind, Brain, and Behavior

    Science.gov (United States)

    Ritchie, J. Brendan; Carlson, Thomas A.

    2016-01-01

    A fundamental challenge for cognitive neuroscience is characterizing how the primitives of psychological theory are neurally implemented. Attempts to meet this challenge are a manifestation of what Fechner called “inner” psychophysics: the theory of the precise mapping between mental quantities and the brain. In his own time, inner psychophysics remained an unrealized ambition for Fechner. We suggest that, today, multivariate pattern analysis (MVPA), or neural “decoding,” methods provide a promising starting point for developing an inner psychophysics. A cornerstone of these methods are simple linear classifiers applied to neural activity in high-dimensional activation spaces. We describe an approach to inner psychophysics based on the shared architecture of linear classifiers and observers under decision boundary models such as signal detection theory. Under this approach, distance from a decision boundary through activation space, as estimated by linear classifiers, can be used to predict reaction time in accordance with signal detection theory, and distance-to-bound models of reaction time. Our “neural distance-to-bound” approach is potentially quite general, and simple to implement. Furthermore, our recent work on visual object recognition suggests it is empirically viable. We believe the approach constitutes an important step along the path to an inner psychophysics that links mind, brain, and behavior. PMID:27199652

  2. Separating neural and vascular effects of caffeine using simultaneous EEG–FMRI: Differential effects of caffeine on cognitive and sensorimotor brain responses

    OpenAIRE

    Diukova, Ana; Ware, Jennifer; Smith, Jessica E.; Evans, C. John; Murphy, Kevin; Rogers, Peter J.; Wise, Richard G.

    2012-01-01

    The effects of caffeine are mediated through its non-selective antagonistic effects on adenosine A1 and A2A adenosine receptors resulting in increased neuronal activity but also vasoconstriction in the brain. Caffeine, therefore, can modify BOLD FMRI signal responses through both its neural and its vascular effects depending on receptor distributions in different brain regions. In this study we aim to distinguish neural and vascular influences of a single dose of caffeine in measurements of t...

  3. 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

    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...

  4. 孤独症谱系障碍的遗传基础与神经机制%Genetic Basis and Neural Mechanism of Autism Spectrum Disorder

    Institute of Scientific and Technical Information of China (English)

    李晶; 林珠梅; 朱莉琪

    2012-01-01

    Autism spectrum disorder (ASD) is a defective mental disease and its core impairments are social function defect, communication defect, restrictive and stereotyped behavior pattern. The paper introduces the genetic basis and neural mechanism of ASD. ASD has high genetic rate, and 5-HT and testosterone of ASD individual are both higher. Neuroimaging studies find that there are some differences between ASD and normal individuals in the structure and function of amygdala, cingulate gyrus, the fusiform gyrus, mirror neurons, prefrontal lobe and other brain areas, but it is inconsistent in the discrepancy direction of some areas' activation patterns. In addition, the results of functional connectivity studies also confirm the hypothesis that the ASD individuals are under-connection. Future research should focus more on how to use the basic research outcomes to put forward effective treatment and training for clinical research.%孤独症谱系障碍(autism spectrum disorder,ASD)是一种神经精神障碍,主要表现为社会交往障碍、交流障碍以及局限性的兴趣和重复刻板的行为模式三个主要核心症状.本文介绍了ASD的遗传基础和神经机制的最新研究进展.ASD具有较高的遗传率,且ASD个体的5-羟色胺和睾丸激素都较高.神经影像学研究发现,ASD个体的杏仁核、扣带回、梭状回、镜像神经元和前额叶等大脑区域在结构和功能上都与正常发育个体存在差异,但在个别区域激活模式的差异方向上仍存在不一致的地方.此外,功能连接的研究结果也证实了ASD个体连接不良的假设.未来的研究应该更多地着眼于如何利用这些基础研究成果为临床上提出有效的治疗和训练方式.

  5. Altered behavior and neural activity in conspecific cagemates co-housed with mouse models of brain disorders.

    Science.gov (United States)

    Yang, Hyunwoo; Jung, Seungmoon; Seo, Jinsoo; Khalid, Arshi; Yoo, Jung-Seok; Park, Jihyun; Kim, Soyun; Moon, Jangsup; Lee, Soon-Tae; Jung, Keun-Hwa; Chu, Kon; Lee, Sang Kun; Jeon, Daejong

    2016-09-01

    The psychosocial environment is one of the major contributors of social stress. Family members or caregivers who consistently communicate with individuals with brain disorders are considered at risk for physical and mental health deterioration, possibly leading to mental disorders. However, the underlying neural mechanisms of this phenomenon remain poorly understood. To address this, we developed a social stress paradigm in which a mouse model of epilepsy or depression was housed long-term (>4weeks) with normal conspecifics. We characterized the behavioral phenotypes and electrophysiologically investigated the neural activity of conspecific cagemate mice. The cagemates exhibited deficits in behavioral tasks assessing anxiety, locomotion, learning/memory, and depression-like behavior. Furthermore, they showed severe social impairment in social behavioral tasks involving social interaction or aggression. Strikingly, behavioral dysfunction remained in the cagemates 4weeks following co-housing cessation with the mouse models. In an electrophysiological study, the cagemates showed an increased number of spikes in medial prefrontal cortex (mPFC) neurons. Our results demonstrate that conspecifics co-housed with mouse models of brain disorders develop chronic behavioral dysfunctions, and suggest a possible association between abnormal mPFC neural activity and their behavioral pathogenesis. These findings contribute to the understanding of the psychosocial and psychiatric symptoms frequently present in families or caregivers of patients with brain disorders.

  6. Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach

    Science.gov (United States)

    Teng, Santani

    2017-01-01

    In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) and models, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research. This article is part of the themed issue ‘Auditory and visual scene analysis’. PMID:28044019

  7. Carbon Nanofiber Nanoelectrodes for Neural Stimulation and Chemical Detection: The Era of Smart Deep Brain Stimulation

    Science.gov (United States)

    Koehne, Jessica E.

    2016-01-01

    A sensor platform based on vertically aligned carbon nanofibers (CNFs) has been developed. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report two studies using vertically aligned CNF nanoelectrodes for biomedical applications. CNF arrays are investigated as neural stimulation and neurotransmitter recording electrodes for application in deep brain stimulation (DBS). Polypyrrole coated CNF nanoelectrodes have shown great promise as stimulating electrodes due to their large surface area, low impedance, biocompatibility and capacity for highly localized stimulation. CNFs embedded in SiO2 have been used as sensing electrodes for neurotransmitter detection. Our approach combines a multiplexed CNF electrode chip, developed at NASA Ames Research Center, with the Wireless Instantaneous Neurotransmitter Concentration Sensor (WINCS) system, developed at the Mayo Clinic. Preliminary results indicate that the CNF nanoelectrode arrays are easily integrated with WINCS for neurotransmitter detection in a multiplexed array format. In the future, combining CNF based stimulating and recording electrodes with WINCS may lay the foundation for an implantable "smart" therapeutic system that utilizes neurochemical feedback control while likely resulting in increased DBS application in various neuropsychiatric disorders. In total, our goal is to take advantage of the nanostructure of CNF arrays for biosensing studies requiring ultrahigh sensitivity, high-degree of miniaturization, and selective biofunctionalization.

  8. Carbon Nanofiber Nanoelectrodes for Neural Stimulation and Chemical Detection: The Era of "Smart" Deep Brain Stimulation

    Science.gov (United States)

    Koehne, Jessica E.

    2016-01-01

    A sensor platform based on vertically aligned carbon nanofibers (CNFs) has been developed. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report two studies using vertically aligned CNF nanoelectrodes for biomedical applications. CNF arrays are investigated as neural stimulation and neurotransmitter recording electrodes for application in deep brain stimulation (DBS). Polypyrrole coated CNF nanoelectrodes have shown great promise as stimulating electrodes due to their large surface area, low impedance, biocompatibility and capacity for highly localized stimulation. CNFs embedded in SiO2 have been used as sensing electrodes for neurotransmitter detection. Our approach combines a multiplexed CNF electrode chip, developed at NASA Ames Research Center, with the Wireless Instantaneous Neurotransmitter Concentration Sensor (WINCS) system, developed at the Mayo Clinic. Preliminary results indicate that the CNF nanoelectrode arrays are easily integrated with WINCS for neurotransmitter detection in a multiplexed array format. In the future, combining CNF based stimulating and recording electrodes with WINCS may lay the foundation for an implantable smart therapeutic system that utilizes neurochemical feedback control while likely resulting in increased DBS application in various neuropsychiatric disorders. In total, our goal is to take advantage of the nanostructure of CNF arrays for biosensing studies requiring ultrahigh sensitivity, high-degree of miniaturization, and selective biofunctionalization.

  9. When problem size matters: differential effects of brain stimulation on arithmetic problem solving and neural oscillations.

    Directory of Open Access Journals (Sweden)

    Bruno Rütsche

    Full Text Available The problem size effect is a well-established finding in arithmetic problem solving and is characterized by worse performance in problems with larger compared to smaller operand size. Solving small and large arithmetic problems has also been shown to involve different cognitive processes and distinct electroencephalography (EEG oscillations over the left posterior parietal cortex (LPPC. In this study, we aimed to provide further evidence for these dissociations by using transcranial direct current stimulation (tDCS. Participants underwent anodal (30min, 1.5 mA, LPPC and sham tDCS. After the stimulation, we recorded their neural activity using EEG while the participants solved small and large arithmetic problems. We found that the tDCS effects on performance and oscillatory activity critically depended on the problem size. While anodal tDCS improved response latencies in large arithmetic problems, it decreased solution rates in small arithmetic problems. Likewise, the lower-alpha desynchronization in large problems increased, whereas the theta synchronization in small problems decreased. These findings reveal that the LPPC is differentially involved in solving small and large arithmetic problems and demonstrate that the effects of brain stimulation strikingly differ depending on the involved neuro-cognitive processes.

  10. Differential Responses of Human Fetal Brain Neural Stem Cells to Zika Virus Infection

    Directory of Open Access Journals (Sweden)

    Erica L. McGrath

    2017-03-01

    Full Text Available Zika virus (ZIKV infection causes microcephaly in a subset of infants born to infected pregnant mothers. It is unknown whether human individual differences contribute to differential susceptibility of ZIKV-related neuropathology. Here, we use an Asian-lineage ZIKV strain, isolated from the 2015 Mexican outbreak (Mex1-7, to infect primary human neural stem cells (hNSCs originally derived from three individual fetal brains. All three strains of hNSCs exhibited similar rates of Mex1-7 infection and reduced proliferation. However, Mex1-7 decreased neuronal differentiation in only two of the three stem cell strains. Correspondingly, ZIKA-mediated transcriptome alterations were similar in these two strains but significantly different from that of the third strain with no ZIKV-induced neuronal reduction. This study thus confirms that an Asian-lineage ZIKV strain infects primary hNSCs and demonstrates a cell-strain-dependent response of hNSCs to ZIKV infection.

  11. Neural correlates of radial frequency trajectory perception in the human brain.

    Science.gov (United States)

    Gorbet, Diana J; Wilkinson, Frances; Wilson, Hugh R

    2014-01-10

    Radial frequency (RF) motion trajectories are visual stimuli that consist of a difference of Gaussians moving along a closed trajectory defined by a sinusoidal variation of the radius relative to a circular path. In the current study, multivoxel fMRI analyses demonstrated that spatial patterns of activity in visual regions V2, V3, and MT can predict RF motion trajectory shape regardless of whether an observer can behaviorally identify the shape or not. This result suggests that processing in these regions is concerned with local properties of the trajectories and not directly linked with a conscious percept of global trajectory shape. Whole-brain analyses show that RF motion trajectories also evoke premotor and posterior parietal cortical activity that may be a neural correlate of shape recognizability. Further, comparisons with activity evoked by static versions of the RF shapes reveal cue-invariant processing in regions of the posterior parietal and occipitotemporal cortices. Interestingly, the RF motion trajectories evoke patterns of dorsal visual stream cortical activity typical of visually guided movement preparation or action observation, suggesting that these stimuli may be processed as potential motor actions rather than as purely visual experiences.

  12. Development of modularity in the neural activity of childrenʼs brains

    Science.gov (United States)

    Chen, Man; Deem, Michael W.

    2015-02-01

    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 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.

  13. Cholinergic enhancement of visual attention and neural oscillations in the human brain.

    Science.gov (United States)

    Bauer, Markus; Kluge, Christian; Bach, Dominik; Bradbury, David; Heinze, Hans Jochen; Dolan, Raymond J; Driver, Jon

    2012-03-06

    Cognitive processes such as visual perception and selective attention induce specific patterns of brain oscillations. The neurochemical bases of these spectral changes in neural activity are largely unknown, but neuromodulators are thought to regulate processing. The cholinergic system is linked to attentional function in vivo, whereas separate in vitro studies show that cholinergic agonists induce high-frequency oscillations in slice preparations. This has led to theoretical proposals that cholinergic enhancement of visual attention might operate via gamma oscillations in visual cortex, although low-frequency alpha/beta modulation may also play a key role. Here we used MEG to record cortical oscillations in the context of administration of a cholinergic agonist (physostigmine) during a spatial visual attention task in humans. This cholinergic agonist enhanced spatial attention effects on low-frequency alpha/beta oscillations in visual cortex, an effect correlating with a drug-induced speeding of performance. By contrast, the cholinergic agonist did not alter high-frequency gamma oscillations in visual cortex. Thus, our findings show that cholinergic neuromodulation enhances attentional selection via an impact on oscillatory synchrony in visual cortex, for low rather than high frequencies. We discuss this dissociation between high- and low-frequency oscillations in relation to proposals that lower-frequency oscillations are generated by feedback pathways within visual cortex.

  14. EphrinB3 restricts endogenous neural stem cell migration after traumatic brain injury.

    Science.gov (United States)

    Dixon, Kirsty J; Mier, Jose; Gajavelli, Shyam; Turbic, Alisa; Bullock, Ross; Turnley, Ann M; Liebl, Daniel J

    2016-11-01

    Traumatic brain injury (TBI) leads to a series of pathological events that can have profound influences on motor, sensory and cognitive functions. Conversely, TBI can also stimulate neural stem/progenitor cell proliferation leading to increased numbers of neuroblasts migrating outside their restrictive neurogenic zone to areas of damage in support of tissue integrity. Unfortunately, the factors that regulate migration are poorly understood. Here, we examine whether ephrinB3 functions to restrict neuroblasts from migrating outside the subventricular zone (SVZ) and rostral migratory stream (RMS). We have previously shown that ephrinB3 is expressed in tissues surrounding these regions, including the overlying corpus callosum (CC), and is reduced after controlled cortical impact (CCI) injury. Our current study takes advantage of ephrinB3 knockout mice to examine the influences of ephrinB3 on neuroblast migration into CC and cortex tissues after CCI injury. Both injury and/or ephrinB3 deficiency led to increased neuroblast numbers and enhanced migration outside the SVZ/RMS zones. Application of soluble ephrinB3-Fc molecules reduced neuroblast migration into the CC after injury and limited neuroblast chain migration in cultured SVZ explants. Our findings suggest that ephrinB3 expression in tissues surrounding neurogenic regions functions to restrict neuroblast migration outside the RMS by limiting chain migration.

  15. Functional and anatomical basis for brain plasticity in facial palsy rehabilitation using the masseteric nerve.

    Science.gov (United States)

    Buendia, Javier; Loayza, Francis R; Luis, Elkin O; Celorrio, Marta; Pastor, Maria A; Hontanilla, Bernardo

    2016-03-01

    Several techniques have been described for smile restoration after facial nerve paralysis. When a nerve other than the contralateral facial nerve is used to restore the smile, some controversy appears because of the nonphysiological mechanism of smile recovering. Different authors have reported natural results with the masseter nerve. The physiological pathways which determine whether this is achieved continue to remain unclear. Using functional magnetic resonance imaging, brain activation pattern measuring blood-oxygen-level-dependent (BOLD) signal during smiling and jaw clenching was recorded in a group of 24 healthy subjects (11 females). Effective connectivity of premotor regions was also compared in both tasks. The brain activation pattern was similar for smile and jaw-clenching tasks. Smile activations showed topographic overlap though more extended for smile than clenching. Gender comparisons during facial movements, according to kinematics and BOLD signal, did not reveal significant differences. Effective connectivity results of psychophysiological interaction (PPI) from the same seeds located in bilateral facial premotor regions showed significant task and gender differences (p facial nerve and masseter nerve areas is supported by the broad cortical overlap in the representation of facial and masseter muscles.

  16. Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia

    Science.gov (United States)

    Lee, Phil H.; Baker, Justin T.; Holmes, Avram J.; Jahanshad, Neda; Ge, Tian; Jung, Jae-Yoon; Cruz, Yanela; Manoach, Dara S.; Hibar, Derrek P.; Faskowitz, Joshua; McMahon, Katie L.; de Zubicaray, Greig I.; Martin, Nicolas H.; Wright, Margaret J.; Öngür, Dost; Buckner, Randy; Roffman, Joshua; Thompson, Paul M.; Smoller, Jordan W.

    2016-01-01

    Schizophrenia is a devastating neurodevelopmental disorder with a complex genetic etiology. Widespread cortical gray matter loss has been observed in patients and prodromal samples. However, it remains unresolved whether schizophrenia-associated cortical structure variations arise due to disease etiology or secondary to the illness. Here we address this question using a partitioning-based heritability analysis of genome-wide SNP and neuroimaging data from 1,750 healthy individuals. We find that schizophrenia-associated genetic variants explain a significantly enriched proportion of trait heritability in eight brain phenotypes (FDR=10%). In particular, intracranial volume (ICV) and left superior frontal gyrus thickness exhibit significant and robust associations with schizophrenia genetic risk under varying SNP selection conditions. Cross disorder comparison suggests that the neurogenetic architecture of schizophrenia-associated brain regions is, at least in part, shared with other psychiatric disorders. Our study highlights key neuroanatomical correlates of schizophrenia genetic risk in the general population. These may provide fundamental insights into the complex pathophysiology of the illness, and a potential link to neurocognitive deficits shaping the disorder. PMID:27725656

  17. Is the self a higher-order or fundamental function of the brain? The "basis model of self-specificity" and its encoding by the brain's spontaneous activity.

    Science.gov (United States)

    Northoff, Georg

    2016-01-01

    What is the self? This is a question that has long been discussed in (Western) philosophy where the self is traditionally conceived a higher-order function at the apex or pinnacle of all functions. This tradition has been transferred to recent neuroscience where the self is often considered to be a higher-order cognitive function reflected in memory and other high-level judgements. However, other lines of research demonstrate a close and intimate relationship between self-specificity and more basic functions like perceptions, emotions and reward. This paper focuses on the relationship between self-specificity and other basic functions relating to emotions, reward and perception. I propose the basis model that conceives self-specificity as a fundamental feature of the brain's spontaneous activity. This is supported by recent findings showing rest-self overlap in midline regions as well as findings demonstrating that the resting state can predict subsequent degrees of self-specificity. I conclude that such self-specificity in the brain's spontaneous activity may be central in linking the self to either internal or external stimuli. This may also provide the basis for coding the self as subject in relation to internal (i.e., self-consciousness) or external (i.e., phenomenal consciousness) mental events.

  18. Brain Basics

    Medline Plus

    Full Text Available ... depression. The Growing Brain Inside the Brain: Neurons & Neural Circuits Neurons are the basic working unit of ... but sometimes give rise to disabilities or diseases. neural circuit —A network of neurons and their interconnections. ...

  19. Training the brain: practical applications of neural plasticity from the intersection of cognitive neuroscience, developmental psychology, and prevention science.

    Science.gov (United States)

    Bryck, Richard L; Fisher, Philip A

    2012-01-01

    Prior researchers have shown that the brain has a remarkable ability for adapting to environmental changes. The positive effects of such neural plasticity include enhanced functioning in specific cognitive domains and shifts in cortical representation following naturally occurring cases of sensory deprivation; however, maladaptive changes in brain function and development owing to early developmental adversity and stress have also been well documented. Researchers examining enriched rearing environments in animals have revealed the potential for inducing positive brain plasticity effects and have helped to popularize methods for training the brain to reverse early brain deficits or to boost normal cognitive functioning. In this article, two classes of empirically based methods of brain training in children are reviewed and critiqued: laboratory-based, mental process training paradigms and ecological interventions based upon neurocognitive conceptual models. Given the susceptibility of executive function disruption, special attention is paid to training programs that emphasize executive function enhancement. In addition, a third approach to brain training, aimed at tapping into compensatory processes, is postulated. Study results showing the effectiveness of this strategy in the field of neurorehabilitation and in terms of naturally occurring compensatory processing in human aging lend credence to the potential of this approach. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

  20. Dissecting the social brain: Introducing the EmpaToM to reveal distinct neural networks and brain-behavior relations for empathy and Theory of Mind.

    Science.gov (United States)

    Kanske, Philipp; Böckler, Anne; Trautwein, Fynn-Mathis; Singer, Tania

    2015-11-15

    Successful social interactions require both affect sharing (empathy) and understanding others' mental states (Theory of Mind, ToM). As these two functions have mostly been investigated in isolation, the specificity of the underlying neural networks and the relation of these networks to the respective behavioral indices could not be tested. Here, we present a novel fMRI paradigm (EmpaToM) that independently manipulates both empathy and ToM. Experiments 1a/b (N=90) validated the task with established empathy and ToM paradigms on a behavioral and neural level. Experiment 2 (N=178) employed the EmpaToM and revealed clearly separable neural networks including anterior insula for empathy and ventral temporoparietal junction for ToM. These distinct networks could be replicated in task-free resting state functional connectivity. Importantly, brain activity in these two networks specifically predicted the respective behavioral indices, that is, inter-individual differences in ToM related brain activity predicted inter-individual differences in ToM performance, but not empathic responding, and vice versa. Taken together, the validated EmpaToM allows separation of affective and cognitive routes to understanding others. It may thus benefit future clinical, developmental, and intervention studies on identifying selective impairments and improvement in specific components of social cognition.

  1. What the success of brain imaging implies about the neural code.

    Science.gov (United States)

    Guest, Olivia; Love, Bradley C

    2017-01-19

    The success of fMRI places constraints on the nature of the neural code. The fact that researchers can infer similarities between neural representations, despite fMRI's limitations, implies that certain neural coding schemes are more likely than others. For fMRI to succeed given its low temporal and spatial resolution, the neural code must be smooth at the voxel and functional level such that similar stimuli engender similar internal representations. Through proof and simulation, we determine which coding schemes are plausible given both fMRI's successes and its limitations in measuring neural activity. Deep neural network approaches, which have been forwarded as computational accounts of the ventral stream, are consistent with the success of fMRI, though functional smoothness breaks down in the later network layers. These results have implications for the nature of the neural code and ventral stream, as well as what can be successfully investigated with fMRI.

  2. Preliminary Evidence for Impaired Brain Activity of Neural Reward Processing in Children and Adolescents with Reactive Attachment Disorder.

    Science.gov (United States)

    Tomoda, Akemi

    2016-01-01

    Childhood maltreatment, which markedly increases risks for psychopathology, is associated with structural and functional brain differences. Especially, exposure to parental verbal abuse (PVA) or interparental violence during childhood is associated with negative outcomes such as depression, posttraumatic stress disorder (PTSD), and reduced cognitive abilities. Other forms of childhood maltreatment have been associated with brain structure or developmental alteration. Our earlier studies elucidated potential discernible effects of PVA and witnessing domestic violence during childhood on brain morphology, including gray matter volume or cortical thickness. Brain regions that process and convey the adverse sensory input of the abuse might be modified specifically by such experiences, particularly in subjects exposed to a single type of maltreatment. Exposure to multiple types of maltreatment is more commonly associated with morphological alterations in the corticolimbic regions. These findings fit with preclinical studies showing that sensory cortices are highly plastic structures. Using tasks with high and low monetary rewards while subjects underwent functional MRI, we also examined whether neural activity during reward processing was altered, or not, in children and adolescents with reactive attachment disorder (RAD). Significantly reduced activity in the caudate and nucleus accumbens was observed during a high monetary reward condition in the RAD group compared to the typically developed group. The striatal neural reward activity in the RAD group was also markedly decreased. The present results suggest that dopaminergic dysfunction occurred in the striatum in children and adolescents with RAD, potentially leading to a future risk of psychiatric disorders such as dependence.

  3. Brain targeting by intranasal drug delivery (INDD): a combined effect of trans-neural and para-neuronal pathway.

    Science.gov (United States)

    Mustafa, Gulam; Alrohaimi, Abdulmohsen H; Bhatnagar, Aseem; Baboota, Sanjula; Ali, Javed; Ahuja, Alka

    2016-01-01

    The effectiveness of intranasal drug delivery for brain targeting has emerged as a hope of remedy for various CNS disorders. The nose to brain absorption of therapeutic molecules claims two effective pathways, which include trans-neuronal for immediate action and para-neuronal for delayed action. To evaluate the contribution of both the pathways in absorption of therapeutic molecules and nanocarriers, lidocaine, a nerve-blocking agent, was used to impair the action potential of olfactory nerve. An anti-Parkinson drug ropinirole was covalently complexes with (99m)Tc in presence of SnCl2 using in-house developed reduction technology. The radiolabeled formulations were administered intranasally in lidocaine challenged rabbit and rat. The qualitative and quantitative outcomes of neural and non-neural pathways were estimated using gamma scintigraphy and UHPLC-MS/MS, respectively. The results showed a significant (p ≤ 0.005) increase in radioactivity counts and drug concentration in the brain of rabbit and rat compared to the animal groups challenged with lidocaine. This concludes the significant contribution (p ≤ 0.005) of trans-neuronal and para-neuronal pathway in nose to brain drug delivery. Therefore, results proved that it is an art of a formulator scientist to make the drug carriers to exploit the choice of absorption pathway for their instant and extent of action.

  4. Specific features of modelling rules of monetary policy on the basis of hybrid regression models with a neural component

    Directory of Open Access Journals (Sweden)

    Lukianenko Iryna H.

    2014-01-01

    Full Text Available The article considers possibilities and specific features of modelling economic phenomena with the help of the category of models that unite elements of econometric regressions and artificial neural networks. This category of models contains auto-regression neural networks (AR-NN, regressions of smooth transition (STR/STAR, multi-mode regressions of smooth transition (MRSTR/MRSTAR and smooth transition regressions with neural coefficients (NCSTR/NCSTAR. Availability of the neural network component allows models of this category achievement of a high empirical authenticity, including reproduction of complex non-linear interrelations. On the other hand, the regression mechanism expands possibilities of interpretation of the obtained results. An example of multi-mode monetary rule is used to show one of the cases of specification and interpretation of this model. In particular, the article models and interprets principles of management of the UAH exchange rate that come into force when economy passes from a relatively stable into a crisis state.

  5. The Neural Basis of Risk Ratings: Evidence from a Functional Magnetic Resonance Imaging (fMRI) Study

    Science.gov (United States)

    Vorhold, V.; Giessing, C.; Wiedemann, P. M.; Schutz, H.; Gauggel, S.; Fink, G. R.

    2007-01-01

    Research investigating risk perception suggests that not only the quantitative parameters used in technical risk assessment (i.e., frequency and severity of harm) but also "qualitative" aspects such as the dread a hazard provokes or its controllability influence risk judgments. It remains to be elucidated, however, which neural mechanism underlie…

  6. Detection of bearing defects in three-phase induction motors using Park’s transform and radial basis function neural networks

    Indian Academy of Sciences (India)

    Izzet Y Önel; K Burak Dalci; İbrahim Senol

    2006-06-01

    This paper investigates the application of induction motor stator current signature analysis (MCSA) using Park’s transform for the detection of rolling element bearing damages in three-phase induction motor. The paper first discusses bearing faults and Park’s transform, and then gives a brief overview of the radial basis function (RBF) neural networks algorithm. Finally, system information and the experimental results are presented. Data acquisition and Park’s transform algorithm are achieved by using LabVIEW and the neural network algorithm is achieved by using MATLAB programming language. Experimental results show that it is possible to detect bearing damage in induction motors using an ANN algorithm.

  7. An adaptive radial basis function neural network (RBFNN control of energy storage system for output tracking of a permanent magnet wind generator

    Directory of Open Access Journals (Sweden)

    Abu H. M. A. Rahim

    2014-03-01

    Full Text Available The converters of a permanent magnet synchronous generator have to be properly controlled to achieve maximum transfer of energy from wind. To achiev e this goal, this article employs an energy storage device consisting of an energy capacitor interfaced through a voltage source converter which is operated through a smart adaptive radial basis function neural network (RBFNN controller. The proposed adaptive strategy employs online neural network training as opposed to conventional procedure requiring offline training of a large data-set. The RBFNN controller was tested for various contingencies in the wind generator system. Th e adaptive online controller is observed to provide excellent damping profile following low grid voltage conditions as well as for other large disturbances. The controlled converter DC capacitor voltage helps maintain a smooth flow of real and reactive power in the system.

  8. Separating neural and vascular effects of caffeine using simultaneous EEG-FMRI: differential effects of caffeine on cognitive and sensorimotor brain responses.

    Science.gov (United States)

    Diukova, Ana; Ware, Jennifer; Smith, Jessica E; Evans, C John; Murphy, Kevin; Rogers, Peter J; Wise, Richard G

    2012-08-01

    The effects of caffeine are mediated through its non-selective antagonistic effects on adenosine A(1) and A(2A) adenosine receptors resulting in increased neuronal activity but also vasoconstriction in the brain. Caffeine, therefore, can modify BOLD FMRI signal responses through both its neural and its vascular effects depending on receptor distributions in different brain regions. In this study we aim to distinguish neural and vascular influences of a single dose of caffeine in measurements of task-related brain activity using simultaneous EEG-FMRI. We chose to compare low-level visual and motor (paced finger tapping) tasks with a cognitive (auditory oddball) task, with the expectation that caffeine would differentially affect brain responses in relation to these tasks. To avoid the influence of chronic caffeine intake, we examined the effect of 250 mg of oral caffeine on 14 non and infrequent caffeine consumers in a double-blind placebo-controlled cross-over study. Our results show that the task-related BOLD signal change in visual and primary motor cortex was significantly reduced by caffeine, while the amplitude and latency of visual evoked potentials over occipital cortex remained unaltered. However, during the auditory oddball task (target versus non-target stimuli) caffeine significantly increased the BOLD signal in frontal cortex. Correspondingly, there was also a significant effect of caffeine in reducing the target evoked response potential (P300) latency in the oddball task and this was associated with a positive potential over frontal cortex. Behavioural data showed that caffeine also improved performance in the oddball task with a significantly reduced number of missed responses. Our results are consistent with earlier studies demonstrating altered flow-metabolism coupling after caffeine administration in the context of our observation of a generalised caffeine-induced reduction in cerebral blood flow demonstrated by arterial spin labelling (19

  9. Efficient and rapid derivation of primitive neural stem cells and generation of brain subtype neurons from human pluripotent stem cells.

    Science.gov (United States)

    Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C

    2013-11-01

    Human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, are unique cell sources for disease modeling, drug discovery screens, and cell therapy applications. The first step in producing neural lineages from hPSCs is the generation of neural stem cells (NSCs). Current methods of NSC derivation involve the time-consuming, labor-intensive steps of an embryoid body generation or coculture with stromal cell lines that result in low-efficiency derivation of NSCs. In this study, we report a highly efficient serum-free pluripotent stem cell neural induction medium that can induce hPSCs into primitive NSCs (pNSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. The pNSCs expressed the neural stem cell markers Pax6, Sox1, Sox2, and Nestin; were negative for Oct4; could be expanded for multiple passages; and could be differentiated into neurons, astrocytes, and oligodendrocytes, in addition to the brain region-specific neuronal subtypes GABAergic, dopaminergic, and motor neurons. Global gene expression of the transcripts of pNSCs was comparable to that of rosette-derived and human fetal-derived NSCs. This work demonstrates an efficient method to generate expandable pNSCs, which can be further differentiated into central nervous system neurons and glia with temporal, spatial, and positional cues of brain regional heterogeneity. This method of pNSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

  10. Nanoparticle-mediated transcriptional modification enhances neuronal differentiation of human neural stem cells following transplantation in rat brain.

    Science.gov (United States)

    Li, Xiaowei; Tzeng, Stephany Y; Liu, Xiaoyan; Tammia, Markus; Cheng, Yu-Hao; Rolfe, Andrew; Sun, Dong; Zhang, Ning; Green, Jordan J; Wen, Xuejun; Mao, Hai-Quan

    2016-04-01

    Strategies to enhance survival and direct the differentiation of stem cells in vivo following transplantation in tissue repair site are critical to realizing the potential of stem cell-based therapies. Here we demonstrated an effective approach to promote neuronal differentiation and maturation of human fetal tissue-derived neural stem cells (hNSCs) in a brain lesion site of a rat traumatic brain injury model using biodegradable nanoparticle-mediated transfection method to deliver key transcriptional factor neurogenin-2 to hNSCs when transplanted with a tailored hyaluronic acid (HA) hydrogel, generating larger number of more mature neurons engrafted to the host brain tissue than non-transfected cells. The nanoparticle-mediated transcription activation method together with an HA hydrogel delivery matrix provides a translatable approach for stem cell-based regenerative therapy.

  11. Neural Network for Quantum Brain Dynamics: 4D CP$^1$+U(1) Gauge Theory on Lattice and its Phase Structure

    CERN Document Server

    Sakane, Shinya; Matsui, Tetsuo

    2016-01-01

    We consider a system of two-level quantum quasi-spins and gauge bosons put on a 3+1D lattice. As a model of neural network of the brain functions, these spins describe neurons quantum-mechanically, and the gauge bosons describes weights of synaptic connections. It is a generalization of the Hopfield model to a quantum network with dynamical synaptic weights. At the microscopic level, this system becomes a model of quantum brain dynamics proposed by Umezawa et al., where spins and gauge field describe water molecules and photons, respectively. We calculate the phase diagram of this system under quantum and thermal fluctuations, and find that there are three phases; confinement, Coulomb, and Higgs phases. Each phase is classified according to the ability to learn patterns and recall them. By comparing the phase diagram with that of classical networks, we discuss the effect of quantum fluctuations and thermal fluctuations (noises in signal propagations) on the brain functions.

  12. The Racer’s Brain – How Domain Expertise is Reflected in the Neural Substrates of Driving

    Directory of Open Access Journals (Sweden)

    Otto eLappi

    2015-11-01

    Full Text Available 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.

  13. Theory of mind and the social brain: implications for understanding the genetic basis of schizophrenia.

    Science.gov (United States)

    Martin, A K; Robinson, G; Dzafic, I; Reutens, D; Mowry, B

    2014-01-01

    Genome-wide association studies in schizophrenia have recently made significant progress in our understanding of the complex genetic architecture of this disorder. Many genetic loci have been identified and now require functional investigation. One approach involves studying their correlation with neuroimaging and neurocognitive endophenotypes. Theory of Mind (ToM) deficits are well established in schizophrenia and they appear to fulfill criteria for being considered an endophenotype. We aim to review the behavioral and neuroimaging-based studies of ToM in schizophrenia, assess its suitability as an endophenotype, discuss current findings, and propose future research directions. Suitable research articles were sourced from a comprehensive literature search and from references identified through other studies. ToM deficits are repeatable, stable, and heritable: First-episode patients, those in remission and unaffected relatives all show deficits. Activation and structural differences in brain regions believed important for ToM are also consistently reported in schizophrenia patients at all stages of illness, although no research to date has examined unaffected relatives. Studies using ToM as an endophenotype are providing interesting genetic associations with both single nucleotide polymorphisms (SNPs) and specific copy number variations (CNVs) such as the 22q11.2 deletion syndrome. We conclude that ToM is an important cognitive endophenotype for consideration in future studies addressing the complex genetic architecture of schizophrenia, and may help identify more homogeneous clinical sub-types for further study.

  14. The role of CXC chemokine ligand (CXCL)12-CXC chemokine receptor (CXCR)4 signalling in the migration of neural stem cells towards a brain tumour

    NARCIS (Netherlands)

    van der Meulen, A. A. E.; Biber, K.; Lukovac, S.; Balasubramaniyan, V.; den Dunnen, W. F. A.; Boddeke, H. W. G. M.; Mooij, J. J. A.

    2009-01-01

    Aims: It has been shown that neural stem cells (NSCs) migrate towards areas of brain injury or brain tumours and that NSCs have the capacity to track infiltrating tumour cells. The possible mechanism behind the migratory behaviour of NSCs is not yet completely understood. As chemokines are involved

  15. The preventive effects of neural stem cells and mesenchymal stem cells intra-ventricular injection on brain stroke in rats

    Directory of Open Access Journals (Sweden)

    Seyed Mojtaba Hosseini

    2015-01-01

    Full Text Available Introduction: Stroke is one of the most important causes of disability in developed countries and, unfortunately, there is no effective treatment for this major problem of central nervous system (CNS; cell therapy may be helpful to recover this disease. In some conditions such as cardiac surgeries and neurosurgeries, there are some possibilities of happening brain stroke. Inflammation of CNS plays an important role in stroke pathogenesis, in addition, apoptosis and neural death could be the other reasons of poor neurological out come after stroke. In this study, we examined the preventive effects of the neural stem cells (NSCs and mesenchymal stem cells (MSCs intra-ventricular injected on stroke in rats. Aim: The aim of this study was to investigate the preventive effects of neural and MSCs for stroke in rats. Materials and Methods: The MSCs were isolated by flashing the femurs and tibias of the male rats with appropriate media. The NSCs were isolated from rat embryo ganglion eminence and they cultured NSCs media till the neurospheres formed. Both NSCs and MSCs were labeled with PKH26-GL. One day before stroke, the cells were injected into lateral ventricle stereotactically. Results: During following for 28 days, the neurological scores indicated that there are better recoveries in the groups received stem cells and they had less lesion volume in their brain measured by hematoxylin and eosin staining. Furthermore, the activities of caspase-3 were lower in the stem cell received groups than control group and the florescent microscopy images showed that the stem cells migrated to various zones of the brains. Conclusion: Both NSCs and MSCs are capable of protecting the CNS against ischemia and they may be good ways to prevent brain stroke consequences situations.

  16. Principles of neural information processing

    CERN Document Server

    Seelen, Werner v

    2016-01-01

    In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...

  17. A neural network that links brain function, white-matter structure and risky behavior.

    Science.gov (United States)

    Kohno, Milky; Morales, Angelica M; Guttman, Zoe; London, Edythe D

    2017-04-01

    The ability to evaluate the balance between risk and reward and to adjust behavior accordingly is fundamental to adaptive decision-making. Although brain-imaging studies consistently have shown involvement of the dorsolateral prefrontal cortex, anterior insula and striatum during risky decision-making, activation in a neural network formed by these regions has not been linked to structural connectivity. Therefore, in this study, white-matter connectivity was measured with diffusion-weighted imaging in 40 healthy research participants who performed the Balloon Analogue Risk Task, a test of risky decision-making, during fMRI. Fractional anisotropy within a network that includes white-matter pathways connecting four regions (the prefrontal cortex, insula and midbrain to the striatum) was positively correlated with the number of risky choices and total amount earned on the task, and with the parametric modulation of activation in regions within the network to the level of risk during choice selection. Furthermore, analysis using a mixed model demonstrated how relationships of the parametric modulation of activation in each of the four aforementioned regions are related to risk probabilities, and how previous trial outcomes and task progression influence the choice to take risk. The present findings provide the first direct evidence that white-matter integrity is linked to function within previously identified components of a network that is activated during risky decision-making, and demonstrate that the integrity of white-matter tracts is critical in consolidating and processing signals between cortical and striatal circuits during the decision-making process.

  18. Brain tissue aspiration neural tube defect Aspiração de tecido cerebral em casos de defeitos de fechamento do tubo neural

    Directory of Open Access Journals (Sweden)

    Luiz Cesar Peres

    2005-09-01

    Full Text Available The study aimed to find out how frequent is brain tissue aspiration and if brain tissue heterotopia could be found in the lung of human neural tube defect cases. Histological sections of each lobe of both lungs of 22 fetuses and newborn with neural tube defect were immunostained for glial fibrillary acidic protein (GFAP. There were 15 (68.2% females and 7 (31.8% males. Age ranged from 18 to 40 weeks of gestation (mean= 31.8. Ten (45.5% were stillborn, the same newborn, and 2 (9.1% were abortuses. Diagnosis were: craniorrhachischisis (9 cases, 40.9%, anencephaly (8 cases, 36,4%, ruptured occipital encephalocele and rachischisis (2 cases, 9.1% each, and early amniotic band disruption sequence (1 case, 4.5%. Only one case (4.5% exhibited GFAP positive cells inside bronchioles and alveoli admixed to epithelial amniotic squames. No heterotopic tissue was observed in the lung interstitium. We concluded that aspiration of brain tissue from the amniotic fluid in neural tube defect cases may happen but it is infrequent and heterotopia was not observed.O objetivo do estudo foi identificar qual a freqüência de aspiração de tecido cerebral e a existência de heterotopia nos pulmões de casos humanos de defeito de fechamento do tubo neural através da reação imuno-histoquímica para proteína fibrilar glial ácida (GFAP em cortes histológicos de todos os lobos de ambos os pulmões de 22 casos de fetos e neonatos com defeito de fechamento do tubo neural. Havia 15 casos femininos (68,2% e 7 masculinos (31,8%, com idade gestacional variando de 18 a 40 semanas (média= 31,8, sendo natimortos e neomortos 10 (45,5% cada e 2 (9,1% abortos. Os diagnósticos foram: Craniorraquisquise (9 casos, 40,9%, anencefalia (8 casos, 36,4%, encefalocele occipital rota e raquisquise (2 casos, 9,1% e 1 (4,5%caso de seqüência de disruptura amniótica precoce. Somente 1 caso (4,5% apresentou células positivas dentro de bronquíolos e alvéolos em meio a células epiteliais

  19. The neural basis of non-verbal communication-enhanced processing of perceived give-me gestures in 9-month-old girls.

    Science.gov (United States)

    Bakker, Marta; Kaduk, Katharina; Elsner, Claudia; Juvrud, Joshua; Gustaf Gredebäck

    2015-01-01

    This study investigated the neural basis of non-verbal communication. Event-related potentials were recorded while 29 nine-month-old infants were presented with a give-me gesture (experimental condition) and the same hand shape but rotated 90°, resulting in a non-communicative hand configuration (control condition). We found different responses in amplitude between the two conditions, captured in the P400 ERP component. Moreover, the size of this effect was modulated by participants' sex, with girls generally demonstrating a larger relative difference between the two conditions than boys.

  20. Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control.

    Science.gov (United States)

    Liu, Xilin; Zhang, Milin; Richardson, Andrew G; Lucas, Timothy H; Van der Spiegel, Jan

    2016-12-16

    This paper presents a bidirectional brain machine interface (BMI) microsystem designed for closed-loop neuroscience research, especially experiments in freely behaving animals. The system-on-chip (SoC) consists of 16-channel neural recording front-ends, neural feature extraction units, 16-channel programmable neural stimulator back-ends, in-channel programmable closed-loop controllers, global analog-digital converters (ADC), and peripheral circuits. The proposed neural feature extraction units includes 1) an ultra low-power neural energy extraction unit enabling a 64-step natural logarithmic domain frequency tuning, and 2) a current-mode action potential (AP) detection unit with time-amplitude window discriminator. A programmable proportional-integral-derivative (PID) controller has been integrated in each channel enabling a various of closed-loop operations. The implemented ADCs include a 10-bit voltage-mode successive approximation register (SAR) ADC for the digitization of the neural feature outputs and/or local field potential (LFP) outputs, and an 8-bit current-mode SAR ADC for the digitization of the action potential outputs. The multi-mode stimulator can be programmed to perform monopolar or bipolar, symmetrical or asymmetrical charge balanced stimulation with a maximum current of 4 mA in an arbitrary channel configuration. The chip has been fabricated in 0.18 μ m CMOS technology, occupying a silicon area of 3.7 mm (2). The chip dissipates 56 μW/ch on average. General purpose low-power microcontroller with Bluetooth module are integrated in the system to provide wireless link and SoC configuration. Methods, circuit techniques and system topology proposed in this work can be used in a wide range of relevant neurophysiology research, especially closed-loop BMI experiments.

  1. Characterization of neural stem/progenitor cells expressing VEGF and its receptors in the subventricular zone of newborn piglet brain.

    Science.gov (United States)

    Ara, Jahan; Fekete, Saskia; Zhu, Anli; Frank, Melissa

    2010-09-01

    Neural stem/progenitor cell (NSP) biology and neurogenesis in adult central nervous system (CNS) are important both towards potential future therapeutic applications for CNS repair, and for the fundamental function of the CNS. In the present study, we report the characterization of NSP population from subventricular zone (SVZ) of neonatal piglet brain using in vivo and in vitro systems. We show that the nestin and vimentin-positive neural progenitor cells are present in the SVZ of the lateral ventricles of neonatal piglet brain. In vitro, piglet NSPs proliferated as neurospheres, expressed the typical protein of neural progenitors, nestin and a range of well-established neurodevelopmental markers. Upon dissociation and subculture, piglet NSPs differentiated into neurons and glial cells. Clonal analysis demonstrates that piglet NSPs are multipotent and retain the capacity to generate both glia and neurons. These cells expressed VEGF, VEGFR1, VEGFR2 and Neuropilin-1 and -2 mRNAs. Real time PCR revealed that SVZ NSPs from newborn piglet expressed total VEGF and all VEGF splice variants. These findings show that piglet NSPs may be helpful to more effectively design growth factor based strategies to enhance endogenous precursor cells for cell transplantation studies potentially leading to the application of this strategy in the nervous system disease and injury.

  2. Where does brain neural activation in aesthetic responses to visual art occur? Meta-analytic evidence from neuroimaging studies.

    Science.gov (United States)

    Boccia, M; Barbetti, S; Piccardi, L; Guariglia, C; Ferlazzo, F; Giannini, A M; Zaidel, D W

    2016-01-01

    Here we aimed at finding the neural correlates of the general aspect of visual aesthetic experience (VAE) and those more strictly correlated with the content of the artworks. We applied a general activation likelihood estimation (ALE) meta-analysis to 47 fMRI experiments described in 14 published studies. We also performed four separate ALE analyses in order to identify the neural substrates of reactions to specific categories of artworks, namely portraits, representation of real-world-visual-scenes, abstract paintings, and body sculptures. The general ALE revealed that VAE relies on a bilateral network of areas, and the individual ALE analyses revealed different maximal activation for the artworks' categories as function of their content. Specifically, different content-dependent areas of the ventral visual stream are involved in VAE, but a few additional brain areas are involved as well. Thus, aesthetic-related neural responses to art recruit widely distributed networks in both hemispheres including content-dependent brain areas of the ventral visual stream. Together, the results suggest that aesthetic responses are not independent of sensory, perceptual, and cognitive processes.

  3. Implementation of neural networks for classification of moss and lichen samples on the basis of gamma-ray spectrometric analysis.

    Science.gov (United States)

    Dragović, Snezana; Onjia, Antonije; Dragović, Ranko; Bacić, Goran

    2007-07-01

    Mosses and lichens have an important role in biomonitoring. The objective of this study is to develop a neural network model to classify these plants according to geographical origin. A three-layer feed-forward neural network was used. The activities of radionuclides ((226)Ra, (238)U, (235)U, (40)K, (232)Th, (134)Cs, (137)Cs and (7)Be) detected in plant samples by gamma-ray spectrometry were used as inputs for neural network. Five different training algorithms with different number of samples in training sets were tested and compared, in order to find the one with the minimum root mean square error. The best predictive power for the classification of plants from 12 regions was achieved using a network with 5 hidden layer nodes and 3,000 training epochs, using the online back-propagation randomized training algorithm. Implementation of this model to experimental data resulted in satisfactory classification of moss and lichen samples in terms of their geographical origin. The average classification rate obtained in this study was (90.7 +/- 4.8)%.

  4. Possible promotion of neuronal differentiation in fetal rat brain neural progenitor cells after sustained exposure to static magnetism.

    Science.gov (United States)

    Nakamichi, Noritaka; Ishioka, Yukichi; Hirai, Takao; Ozawa, Shusuke; Tachibana, Masaki; Nakamura, Nobuhiro; Takarada, Takeshi; Yoneda, Yukio

    2009-08-15

    We have previously shown significant potentiation of Ca(2+) influx mediated by N-methyl-D-aspartate receptors, along with decreased microtubules-associated protein-2 (MAP2) expression, in hippocampal neurons cultured under static magnetism without cell death. In this study, we investigated the effects of static magnetism on the functionality of neural progenitor cells endowed to proliferate for self-replication and differentiate into neuronal, astroglial, and oligodendroglial lineages. Neural progenitor cells were isolated from embryonic rat neocortex and hippocampus, followed by culture under static magnetism at 100 mT and subsequent determination of the number of cells immunoreactive for a marker protein of particular progeny lineages. Static magnetism not only significantly decreased proliferation of neural progenitor cells without affecting cell viability, but also promoted differentiation into cells immunoreactive for MAP2 with a concomitant decrease in that for an astroglial marker, irrespective of the presence of differentiation inducers. In neural progenitors cultured under static magnetism, a significant increase was seen in mRNA expression of several activator-type proneural genes, such as Mash1, Math1, and Math3, together with decreased mRNA expression of the repressor type Hes5. These results suggest that sustained static magnetism could suppress proliferation for self-renewal and facilitate differentiation into neurons through promoted expression of activator-type proneural genes by progenitor cells in fetal rat brain.

  5. [Adverse Sensory Input of Childhood Maltreatment Modified by Early Experience Ascertaining the Neural Basis of Neurodevelopmental and Attachment Disorders].

    Science.gov (United States)

    Tomoda, Akemi

    2015-01-01

    Childhood maltreatment, which markedly increases the risk of psychopathology such as depression, PTSD, and reduced cognitive abilities, is associated with structural and functional brain differences. Our earlier studies elucidated potential discernible effects on the brain morphology of childhood maltreatment on the gray matter volume or cortical thickness. Further, our preliminary studies revealed a significantly reduced gray matter volume (GMV) in the left primary visual cortex (Brodmann area 17) in the reactive attachment disorder (RAD) group compared to the typically developed group. These visual cortex GMV abnormalities may also be associated with such visual stimulus-induced emotion regulation impairments of RAD, leading to an increase in the risk of future psychopathology. Brain regions that process and convey the adverse sensory input of the abuse might be modified specifically by such experiences, particularly in subjects exposed to a single type of maltreatment. Thus, exposure to multiple types of maltreatment is more commonly associated with morphological alterations in corticolimbic regions.

  6. Modeling and optimization of microbial hyaluronic acid production by Streptococcus zooepidemicus using radial basis function neural network coupling quantum-behaved particle swarm optimization algorithm.

    Science.gov (United States)

    Liu, Long; Sun, Jun; Xu, Wenbo; Du, Guocheng; Chen, Jian

    2009-01-01

    Hyaluronic acid (HA) is a natural biopolymer with unique physiochemical and biological properties and finds a wide range of applications in biomedical and cosmetic fields. It is important to increase HA production to meet the increasing HA market demand. This work is aimed to model and optimize the amino acids addition to enhance HA production of Streptococcus zooepidemicus with radial basis function (RBF) neural network coupling quantum-behaved particle swarm optimization (QPSO) algorithm. In the RBF-QPSO approach, RBF neural network is used as a bioprocess modeling tool and QPSO algorithm is applied to conduct the optimization with the established RBF neural network black model as the objective function. The predicted maximum HA yield was 6.92 g/L under the following conditions: arginine 0.062 g/L, cysteine 0.036 g/L, and lysine 0.043 g/L. The optimal amino acids addition allowed HA yield increased from 5.0 g/L of the control to 6.7 g/L in the validation experiments. Moreover, the modeling and optimization capacity of the RBF-QPSO approach was compared with that of response surface methodology (RSM). It was indicated that the RBF-QPSO approach gave a slightly better modeling and optimization result compared with RSM. The developed RBF-QPSO approach in this work may be helpful for the modeling and optimization of the other multivariable, nonlinear, time-variant bioprocesses.

  7. Structural Basis by Which Alternative Splicing Modulates the Organizer Activity of FGF8 in the Brain

    Energy Technology Data Exchange (ETDEWEB)

    Olsen,S.; Li, J.; Eliseenkova, A.; Ibrahimi, O.; Lao, Z.; Zhang, F.; Linhardt, R.; Joyner, A.; Mohammadi, M.

    2006-01-01

    Two of the four human FGF8 splice isoforms, FGF8a and FGF8b, are expressed in the mid-hindbrain region during development. Although the only difference between these isoforms is the presence of an additional 11 amino acids at the N terminus of FGF8b, these isoforms possess remarkably different abilities to pattern the midbrain and anterior hindbrain. To reveal the structural basis by which alternative splicing modulates the organizing activity of FGF8, we solved the crystal structure of FGF8b in complex with the 'c' splice isoform of FGF receptor 2 (FGFR2c). Using surface plasmon resonance (SPR), we also characterized the receptor-binding specificity of FGF8a and FGF8b, the 'b' isoform of FGF17 (FGF17b), and FGF18. The FGF8b-FGFR2c structure shows that alternative splicing permits a single additional contact between phenylalanine 32 (F32) of FGF8b and a hydrophobic groove within Ig domain 3 of the receptor that is also present in FGFR1c, FGFR3c, and FGFR4. Consistent with the structure, mutation of F32 to alanine reduces the affinity of FGF8b toward all these receptors to levels characteristic of FGF8a. More importantly, analysis of the mid-hindbrain patterning ability of the FGF8b{sup F32A} mutant in chick embryos and murine midbrain explants shows that this mutation functionally converts FGF8b to FGF8a. Moreover, our data suggest that the intermediate receptor-binding affinities of FGF17b and FGF18, relative to FGF8a and FGF8b, also account for the distinct patterning abilities of these two ligands. We also show that the mode of FGF8 receptor-binding specificity is distinct from that of other FGFs and provide the first biochemical evidence for a physiological FGF8b-FGFR1c interaction during mid-hindbrain development. Consistent with the indispensable role of FGF8 in embryonic development, we show that the FGF8 mode of receptor binding appeared as early as in nematodes and has been preserved throughout evolution.

  8. Branding and a child’s brain: an fMRI study of neural responses to logos

    Science.gov (United States)

    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. PMID:22997054

  9. How treatment affects the brain: meta-analysis evidence of neural substrates underpinning drug therapy and psychotherapy in major depression.

    Science.gov (United States)

    Boccia, Maddalena; Piccardi, Laura; Guariglia, Paola

    2016-06-01

    The idea that modifications of affect, behavior and cognition produced by psychotherapy are mediated by biological underpinnings predates the advent of the modern neurosciences. Recently, several studies demonstrated that psychotherapy outcomes are linked to modifications in specific brain regions. This opened the debate over the similarities and dissimilarities between psychotherapy and pharmacotherapy. In this study, we used activation likelihood estimation meta-analysis to investigate the effects of psychotherapy (PsyTh) and pharmacotherapy (DrugTh) on brain functioning in Major Depression (MD). Our results demonstrate that the two therapies modify different neural circuits. Specifically, PsyTh induces selective modifications in the left inferior and superior frontal gyri, middle temporal gyrus, lingual gyrus and middle cingulate cortex, as well as in the right middle frontal gyrus and precentral gyrus. Otherwise, DrugTh selectively affected brain activation in the right insula in MD patients. These results are in line with previous evidence of the synergy between psychotherapy and pharmacotherapy but they also demonstrate that the two therapies have different neural underpinnings.

  10. Transport and metabolism at blood-brain interfaces and in neural cells: relevance to bilirubin-induced encephalopathy

    Directory of Open Access Journals (Sweden)

    Silvia eGazzin

    2012-05-01

    Full Text Available Bilirubin, the end-product of heme catabolism, circulates in non pathological plasma mostly as a protein-bound species. When bilirubin concentration builds up, the free fraction of the molecule increases. Unbound bilirubin then diffuses across blood-brain interfaces into the brain, where it accumulates and exerts neurotoxic effects. In this classical view of bilirubin neurotoxicity, blood-brain interfaces act merely as structural barriers impeding the penetration of the pigment-bound carrier protein, and neural cells are considered as passive targets of its toxicity. Yet, the role of blood-brain interfaces in the occurrence of bilirubin encephalopathy appears more complex than being simple barriers to the diffusion of bilirubin, and neural cells such as astrocytes and neurons can play an active role in controlling the balance between the neuroprotective and neurotoxic effects of bilirubin. This article reviews the emerging in vivo and in vitro data showing that transport and metabolic detoxification mechanisms at the blood-brain and blood-CSF barriers may modulate bilirubin flux across both cellular interfaces, and that these protective functions can be affected in chronic hyperbilirubinemia. Then the in vivo and in vitro arguments in favor of the physiological antioxidant function of intracerebral bilirubin are presented, as well as with the potential role of transporters such as ABCC-1 and metabolizing enzymes such as cytochromes P-450 in setting the cerebral cell- and structure-specific toxicity of bilirubin following hyperbilirubinemia. The relevance of these data to the pathophysiology of bilirubin-induced neurological diseases is discussed.

  11. Modeling pathological brain rhythms: constructing a neural mass model from single cell dynamics

    NARCIS (Netherlands)

    Zandt, B.J.; Visser, S.; Putten, van M.J.A.M.; Haken, ten B.

    2013-01-01

    Neural mass models (NMM) describe neural activity on a macroscopic scale, which can be compared to the electroencephalogram (EEG). This allows a better understanding of the processes responsible for various EEG patterns, including pathological rhythms as diffuse slowing or burst-suppression [1]. U

  12. Brain Machine Interface: Analysis of segmented EEG Signal Classification Using Short-Time PCA and Recurrent Neural Networks

    Directory of Open Access Journals (Sweden)

    C. R. Hema

    2008-01-01

    Full Text Available Brain machine interface provides a communication channel between the human brain and an external device. Brain interfaces are studied to provide rehabilitation to patients with neurodegenerative diseases; such patients loose all communication pathways except for their sensory and cognitive functions. One of the possible rehabilitation methods for these patients is to provide a brain machine interface (BMI for communication; the BMI uses the electrical activity of the brain detected by scalp EEG electrodes. Classification of EEG signals extracted during mental tasks is a technique for designing a BMI. In this paper a BMI design using five mental tasks from two subjects were studied, a combination of two tasks is studied per subject. An Elman recurrent neural network is proposed for classification of EEG signals. Two feature extraction algorithms using overlapped and non overlapped signal segments are analyzed. Principal component analysis is used for extracting features from the EEG signal segments. Classification performance of overlapping EEG signal segments is observed to be better in terms of average classification with a range of 78.5% to 100%, while the non overlapping EEG signal segments show better classification in terms of maximum classifications.

  13. Organization of the sleep-related neural systems in the brain of the minke whale (Balaenoptera acutorostrata).

    Science.gov (United States)

    Dell, Leigh-Anne; Karlsson, Karl Ae; Patzke, Nina; Spocter, Muhammad A; Siegel, Jerome M; Manger, Paul R

    2016-07-01

    The current study analyzed the nuclear organization of the neural systems related to the control and regulation of sleep and wake in the basal forebrain, diencephalon, midbrain, and pons of the minke whale, a mysticete cetacean. While odontocete cetaceans sleep in an unusual manner, with unihemispheric slow wave sleep (USWS) and suppressed REM sleep, it is unclear whether the mysticete whales show a similar sleep pattern. Previously, we detailed a range of features in the odontocete brain that appear to be related to odontocete-type sleep, and here present our analysis of these features in the minke whale brain. All neural elements involved in sleep regulation and control found in bihemispheric sleeping mammals and the harbor porpoise were present in the minke whale, with no specific nuclei being absent, and no novel nuclei being present. This qualitative similarity relates to the cholinergic, noradrenergic, serotonergic and orexinergic systems, and the GABAergic elements of these nuclei. Quantitative analysis revealed that the numbers of pontine cholinergic (274,242) and noradrenergic (203,686) neurons, and hypothalamic orexinergic neurons (277,604), are markedly higher than other large-brained bihemispheric sleeping mammals. Small telencephalic commissures (anterior, corpus callosum, and hippocampal), an enlarged posterior commissure, supernumerary pontine cholinergic and noradrenergic cells, and an enlarged peripheral division of the dorsal raphe nuclear complex of the minke whale, all indicate that the suite of neural characteristics thought to be involved in the control of USWS and the suppression of REM in the odontocete cetaceans are present in the minke whale. J. Comp. Neurol. 524:2018-2035, 2016. © 2015 Wiley Periodicals, Inc.

  14. Analysis of pull-in instability of geometrically nonlinear microbeam using radial basis artificial neural network based on couple stress theory.

    Science.gov (United States)

    Heidari, Mohammad; Heidari, Ali; Homaei, Hadi

    2014-01-01

    The static pull-in instability of beam-type microelectromechanical systems (MEMS) is theoretically investigated. Two engineering cases including cantilever and double cantilever microbeam are considered. Considering the midplane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, capable of capturing the size effect. By selecting a range of geometric parameters such as beam lengths, width, thickness, gaps, and size effect, we identify the static pull-in instability voltage. A MAPLE package is employed to solve the nonlinear differential governing equations to obtain the static pull-in instability voltage of microbeams. Radial basis function artificial neural network with two functions has been used for modeling the static pull-in instability of microcantilever beam. The network has four inputs of length, width, gap, and the ratio of height to scale parameter of beam as the independent process variables, and the output is static pull-in voltage of microbeam. Numerical data, employed for training the network, and capabilities of the model have been verified in predicting the pull-in instability behavior. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 4.55% in predicting pull-in voltage of cantilever microbeam. Further analysis of pull-in instability of beam under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach. The results reveal significant influences of size effect and geometric parameters on the static pull-in instability voltage of MEMS.

  15. 社会情绪与社会行为的脑机制%The Brain Basis of Social Emotion and Social Behavior

    Institute of Scientific and Technical Information of China (English)

    周晓林; 于宏波

    2015-01-01

    社会情绪指在社会交互中产生、并对人的社会行为或倾向产生影响的情绪反应,如内疚、感激和嫉妒。因其与道德行为、社会合作和群体决策等领域的密切联系,社会情绪一直是社会心理学、政治学和社会学等学科的重要研究领域。然而社会情绪的神经机制长久以来并不为人所知。近年来,随着脑成像技术的发展,特别是人际互动范式与脑成像的结合,社会情绪的神经机制逐渐成为社会认知神经科学的热门主题。本文综述了近十年来社会情绪神经机制的研究成果,并尝试提出该领域未来可能的发展方向:结合神经科学手段(如脑成像、脑损伤等)和计算模型(如强化学习),揭示复杂社会情绪和行为背后的心理、神经和计算基础。%Social emotions are those arising in and influencing social interactions,e.g.,guilt,gratitude and envy. Given that social emotions are closely related to moral cognition,interpersonal cooperation and collective decision-making,they have remained one of the central research topics in social and moral psychology,political sciences and sociology. However,the biological basis of social emotions remains largely unknown. Recently, advances in functional brain imaging methodology allow psychologists and neuroscience researchers to look more closely into the underlying neural mechanisms of social emotions. We review the findings of this new trend of research and propose some directions which we believe are promising approaches to the understanding of human sociality,namely,combining neuroscience methods(e.g.,functional brain imaging),computational modeling (e.g.,reinforcement learning) and interpersonal paradigms to reveal the psychological,neuroscientific and computational principles underlying the complex human social emotions and behaviors.

  16. Quantum Brain?

    CERN Document Server

    Mershin, A; Skoulakis, E M C

    2000-01-01

    In order to create a novel model of memory and brain function, we focus our approach on the sub-molecular (electron), molecular (tubulin) and macromolecular (microtubule) components of the neural cytoskeleton. Due to their size and geometry, these systems may be approached using the principles of quantum physics. We identify quantum-physics derived mechanisms conceivably underlying the integrated yet differentiated aspects of memory encoding/recall as well as the molecular basis of the engram. We treat the tubulin molecule as the fundamental computation unit (qubit) in a quantum-computational network that consists of microtubules (MTs), networks of MTs and ultimately entire neurons and neural networks. We derive experimentally testable predictions of our quantum brain hypothesis and perform experiments on these.

  17. Vasoactive intestinal peptide is a local mediator in a gut-brain neural axis activating intestinal gluconeogenesis.

    Science.gov (United States)

    De Vadder, F; Plessier, F; Gautier-Stein, A; Mithieux, G

    2015-03-01

    Intestinal gluconeogenesis (IGN) promotes metabolic benefits through activation of a gut-brain neural axis. However, the local mediator activating gluconeogenic genes in the enterocytes remains unknown. We show that (i) vasoactive intestinal peptide (VIP) signaling through VPAC1 receptor activates the intestinal glucose-6-phosphatase gene in vivo, (ii) the activation of IGN by propionate is counteracted by VPAC1 antagonism, and (iii) VIP-positive intrinsic neurons in the submucosal plexus are increased under the action of propionate. These data support the role of VIP as a local neuromodulator released by intrinsic enteric neurons and responsible for the induction of IGN through a VPAC1 receptor-dependent mechanism in enterocytes.

  18. EEG-Based Classification of Motor Imagery Tasks Using Fractal Dimension and Neural Network for Brain-Computer Interface

    Science.gov (United States)

    Phothisonothai, Montri; Nakagawa, Masahiro

    In this study, we propose a method of classifying a spontaneous electroencephalogram (EEG) approach to a brain-computer interface. Ten subjects, aged 21-32 years, volunteered to imagine left-and right- hand movements. An independent component analysis based on a fixed-point algorithm is used to eliminate the activities found in the EEG signals. We use a fractal dimension value to reveal the embedded potential responses in the human brain. The different fractal dimension values between the relaxing and imaging periods are computed. Featured data is classified by a three-layer feed-forward neural network based on a simple backpropagation algorithm. Two conventional methods, namely, the use of the autoregressive (AR) model and the band power estimation (BPE) as features, and the linear discriminant analysis (LDA) as a classifier, are selected for comparison in this study. Experimental results show that the proposed method is more effective than the conventional methods.

  19. Neural networks improve brain cancer detection with Raman spectroscopy in the presence of operating room light artifacts

    Science.gov (United States)

    Jermyn, Michael; Desroches, Joannie; Mercier, Jeanne; Tremblay, Marie-Andrée; St-Arnaud, Karl; Guiot, Marie-Christine; Petrecca, Kevin; Leblond, Frederic

    2016-09-01

    Invasive brain cancer cells cannot be visualized during surgery and so they are often not removed. These residual cancer cells give rise to recurrences. In vivo Raman spectroscopy can detect these invasive cancer cells in patients with grade 2 to 4 gliomas. The robustness of this Raman signal can be dampened by spectral artifacts generated by lights in the operating room. We found that artificial neural networks (ANNs) can overcome these spectral artifacts using nonparametric and adaptive models to detect complex nonlinear spectral characteristics. Coupling ANN with Raman spectroscopy simplifies the intraoperative use of Raman spectroscopy by limiting changes required to the standard neurosurgical workflow. The ability to detect invasive brain cancer under these conditions may reduce residual cancer remaining after surgery and improve patient survival.

  20. Lab-on-a-brain: Implantable micro-optical fluidic devices for neural cell analysis in vivo

    Science.gov (United States)

    Takehara, Hiroaki; Nagaoka, Akira; Noguchi, Jun; Akagi, Takanori; Kasai, Haruo; Ichiki, Takanori

    2014-10-01

    The high-resolution imaging of neural cells in vivo has brought about great progress in neuroscience research. Here, we report a novel experimental platform, where the intact brain of a living mouse can be studied with the aid of a surgically implanted micro-optical fluidic device; acting as an interface between neurons and the outer world. The newly developed device provides the functions required for the long-term and high-resolution observation of the fine structures of neurons by two-photon laser scanning microscopy and the microfluidic delivery of chemicals or drugs directly into the brain. A proof-of-concept experiment of single-synapse stimulation by two-photon uncaging of caged glutamate and observation of dendritic spine shrinkage over subsequent days demonstrated a promising use for the present technology.

  1. Neural Basis of Working Memory Enhancement after Acute Aerobic Exercise: fMRI Study of Preadolescent Children

    OpenAIRE

    Ai-Guo Chen; Li-Na Zhu; Jun Yan; Heng-Chan Yin

    2016-01-01

    Working memory lies at the core of cognitive function and plays a crucial role in children’s learning, reasoning, problem solving, and intellectual activity. Behavioral findings have suggested that acute aerobic exercise improves children’s working memory; however, there is still very little knowledge about whether a single session of aerobic exercise can alter working memory’s brain activation patterns, as assessed by functional magnetic resonance imaging (fMRI). Therefore, we investigated t...

  2. Brain Basics

    Medline Plus

    Full Text Available ... can lead to mental disorders, such as depression. The Growing Brain Inside the Brain: Neurons & Neural Circuits ... tailored treatments, and possibly prevention of such illnesses. The Working Brain Neurotransmitters Everything we do relies on ...

  3. Automatic labeling of molecular biomarkers on a cell-by-cell basis in immunohistochemistry images using convolutional neural networks

    Science.gov (United States)

    Sheikhzadeh, Fahime; Carraro, Anita; Korbelik, Jagoda; MacAulay, Calum; Guillaud, Martial; Ward, Rabab K.

    2016-03-01

    This paper addresses the problem of classifying cells expressing different biomarkers. A deep learning based method that can automatically localize and count the cells expressing each of the different biomarkers is proposed. To classify the cells, a Convolutional Neural Network (CNN) was employed. Images of Immunohistochemistry (IHC) stained slides that contain these cells were digitally scanned. The images were taken from digital scans of IHC stained cervical tissues, acquired for a clinical trial. More than 4,500 RGB images of cells were used to train the CNN. To evaluate our method, the cells were first manually labeled based on the expressing biomarkers. Then we performed the classification on 156 randomly selected images of cells that were not used in training the CNN. The accuracy of the classification was 92% in this preliminary data set. The results have shown that this method has a good potential in developing an automatic method for immunohistochemical analysis.

  4. [Theoretic basis on the same therapeutic program for different degenerative brain diseases in terms of the Governor Vessel: Alzheimer's disease and Parkinson's disease].

    Science.gov (United States)

    Wu, Junyan; Wang, Jie; Zhang, Junlong

    2015-05-01

    Through the consultation of TCM ancient classical theory, the relationship of kidney essence, marrow and brain is analyzed. It is discovered that the degenerative brain diseases, represented by Alzheimer's disease (AD) and Parkinson's disease (PD) share the same etiological basis as "kidney essence deficiency and brain marrow emptiness" and have the mutual pathological outcomes as yang qi declining. The Governor Vessel gathers yang qi of the whole body and maintains the normal functional activity of zangfu organs in the human body through the storage, regulation and invigoration of yang qi. It is viewed that the theory of the Governor Vessel is applied to treat the different degenerative brain diseases, which provides the theoretic support and practice guide for the thought of TCM as the same therapeutic program for the different diseases. As a result, the degenerative brain diseases can be retarded and the approach is provided to the effective prevention and treatment of degenerative diseases in central nerve system:

  5. Neural network-based crop growth model to predict processing tomato yield on a site-specific basis using remotely sensed data

    Science.gov (United States)

    Koller, Michal

    Remote sensing is one of the major data acquisition tools available to rapidly acquire soil and plant related information over a wide area for use in precision agriculture. Green canopy has very specific reflectance characteristics distinguishing it from other materials such as soil and dry vegetative matter. Reflectance values in red (R) and near infra-red (NIR) spectral bands have been widely used for calculating normalized difference vegetation index (NDVI). Many researchers have related NDVI values to plant vigor, water stress, leaf area index (LAI) and/or yield. However, vegetative indices such as NDVI are usually sensitive to background reflectance characteristics. Often soil adjusted vegetation indices (SAVI) are used to minimize the background effect. In this study we have developed a relationship between the processing tomato yield and SAVI based on the R and NIR reflectance. Eight three band (R, NIR and green) aerial images were obtained at approximately two-week intervals during the 2000 processing tomato growing season. These images were analyzed to obtain SAVI values which were in turn related to LAI using regression techniques. A tuned neural network was developed to predict daily LAI values based on the biweekly experimental LAI values derived from aerial images. The coefficients of multiple determination between the actual LAI and neural network predicted LAI values were greater than 0.96 for all 56 grid points. The LAI values were numerically integrated over the whole growing season to obtain cumulative leaf area index days (CLAID). The CLAID values predicted from the neural network correlated very well with experimentally derived CLAID values (coefficient of determination, r2 = 0.83) indicating that the neural network model simulated processing tomato growth well. A crop growth model that was capable of predicting crop yield based on neural network predicted LAI values and CIMIS weather data was developed. Although predicted yield tended to be low

  6. Beyond neural cubism: promoting a multidimensional view of brain disorders by enhancing the integration of neurology and psychiatry in education.

    Science.gov (United States)

    Taylor, Joseph J; Williams, Nolan R; George, Mark S

    2015-05-01

    Cubism was an influential early-20th-century art movement characterized by angular, disjointed imagery. The two-dimensional appearance of Cubist figures and objects is created through juxtaposition of angles. The authors posit that the constrained perspectives found in Cubism may also be found in the clinical classification of brain disorders. Neurological disorders are often separated from psychiatric disorders as if they stemmed from different organ systems. Maintaining two isolated clinical disciplines fractionalizes the brain in the same way that Pablo Picasso fractionalized figures and objects in his Cubist art. This Neural Cubism perpetuates a clinical divide that does not reflect the scope and depth of neuroscience. All brain disorders are complex and multidimensional, with aberrant circuitry and resultant psychopharmacology manifesting as altered behavior, affect, mood, or cognition. Trainees should receive a multidimensional education based on modern neuroscience, not a partial education based on clinical precedent. The authors briefly outline the rationale for increasing the integration of neurology and psychiatry and discuss a nested model with which clinical neuroscientists (neurologists and psychiatrists) can approach and treat brain disorders.

  7. Human neural progenitor cell engraftment increases neurogenesis and microglial recruitment in the brain of rats with stroke.

    Directory of Open Access Journals (Sweden)

    Zahra Hassani

    Full Text Available MAIN OBJECTIVES: Stem cell transplantation is to date one of the most promising therapies for chronic ischemic stroke. The human conditionally immortalised neural stem cell line, CTX0E03, has demonstrable efficacy in a rodent model of stroke and is currently in clinical trials. Nonetheless, the mechanisms by which it promotes brain repair are not fully characterised. This study investigated the cellular events occurring after CTX0E03 transplantation in the brains of rats that underwent ischemic stroke. METHODS: We focused on the endogenous proliferative activity of the host brain in response to cell transplantation and determined the identity of the proliferating cells using markers for young neurons (doublecortin, Dcx and microglia (CD11b. So as to determine the chronology of events occurring post-transplantation, we analysed the engrafted brains one week and four weeks post-transplantation. RESULTS: We observed a significantly greater endogenous proliferation in the striatum of ischemic brains receiving a CTX0E03 graft compared to vehicle-treated ischemic brains. A significant proportion of these proliferative cells were found to be Dcx+ striatal neuroblasts. Further, we describe an enhanced immune response after CTX0E03 engraftment, as shown by a significant increase of proliferating CD11b+ microglial cells. CONCLUSIONS: Our study demonstrates that few Dcx+ neuroblasts are proliferative in normal conditions, and that this population of proliferative neuroblasts is increased in response to stroke. We further show that CTX0E03 transplantation after stroke leads to the maintenance of this proliferative activity. Interestingly, the preservation of neuronal proliferative activity upon CTX0E03 transplantation is preceded and accompanied by a high rate of proliferating microglia. Our study suggests that microglia might mediate in part the effect of CTX0E03 transplantation on neuronal proliferation in ischemic stroke conditions.

  8. A Hybrid Approach by Integrating Brain Storm Optimization Algorithm with Grey Neural Network for Stock Index Forecasting

    Directory of Open Access Journals (Sweden)

    Yanqiu Sun

    2014-01-01

    Full Text Available Stock index forecasting is an important tool for both the investors and the government organizations. However, due to the inherent large volatility, high noise, and nonlinearity of the stock index, stock index forecasting has been a challenging task for a long time. This paper aims to develop a novel hybrid stock index forecasting model named BSO-GNN based on the brain storm optimization (BSO approach and the grey neural network (GNN model by taking full advantage of the grey model in dealing with data with small samples and the neural network in handling nonlinear fitting problems. Moreover, the new developed BSO-GNN, which initializes the parameters in grey neural network with the BSO algorithm, has great capability in overcoming the deficiencies of the traditional GNN model with randomly initialized parameters through solving the local optimum and low forecasting accuracy problems. The performance of the proposed BSO-GNN model is evaluated under the normalization and nonnormalization preprocessing situations. Experimental results from the Shanghai Stock Exchange (SSE Composite Index, the Shenzhen Composite Index, and the HuShen 300 Index opening price forecasting show that the proposed BSO-GNN model is effective and robust in the stock index forecasting and superior to the individual GNN model.

  9. Induced Neural Stem Cells Achieve Long-Term Survival and Functional Integration in the Adult Mouse Brain

    Directory of Open Access Journals (Sweden)

    Kathrin Hemmer

    2014-09-01

    Full Text Available Differentiated cells can be converted directly into multipotent neural stem cells (i.e., induced neural stem cells [iNSCs]. iNSCs offer an attractive alternative to induced pluripotent stem cell (iPSC technology with regard to regenerative therapies. Here, we show an in vivo long-term analysis of transplanted iNSCs in the adult mouse brain. iNSCs showed sound in vivo long-term survival rates without graft overgrowths. The cells displayed a neural multilineage potential with a clear bias toward astrocytes and a permanent downregulation of progenitor and cell-cycle markers, indicating that iNSCs are not predisposed to tumor formation. Furthermore, the formation of synaptic connections as well as neuronal and glial electrophysiological properties demonstrated that differentiated iNSCs migrated, functionally integrated, and interacted with the existing neuronal circuitry. We conclude that iNSC long-term transplantation is a safe procedure; moreover, it might represent an interesting tool for future personalized regenerative applications.

  10. Functional gene polymorphisms in the serotonin system and traumatic life events modulate the neural basis of fear acquisition and extinction.

    Directory of Open Access Journals (Sweden)

    Andrea Hermann

    Full Text Available Fear acquisition and extinction are crucial mechanisms in the etiology and maintenance of anxiety disorders. Moreover, they might play a pivotal role in conveying the influence of genetic and environmental factors on the development of a (more or less stronger proneness for, or resilience against psychopathology. There are only few insights in the neurobiology of genetically and environmentally based individual differences in fear learning and extinction. In this functional magnetic resonance imaging study, 74 healthy subjects were investigated. These were invited according to 5-HTTLPR/rs25531 (S+ vs. L(AL(A; triallelic classification and TPH2 (G(-703T (T+ vs. T- genotype. The aim was to investigate the influence of genetic factors and traumatic life events on skin conductance responses (SCRs and neural responses (amygdala, insula, dorsal anterior cingulate cortex (dACC and ventromedial prefrontal cortex (vmPFC during acquisition and extinction learning in a differential fear conditioning paradigm. Fear acquisition was characterized by stronger late conditioned and unconditioned responses in the right insula in 5-HTTLPR S-allele carriers. During extinction traumatic life events were associated with reduced amygdala activation in S-allele carriers vs. non-carriers. Beyond that, T-allele carriers of the TPH2 (G(-703T polymorphism with a higher number of traumatic life events showed enhanced responsiveness in the amygdala during acquisition and in the vmPFC during extinction learning compared with non-carriers. Finally, a combined effect of the two polymorphisms with higher responses in S- and T-allele carriers was found in the dACC during extinction. The results indicate an increased expression of conditioned, but also unconditioned fear responses in the insula in 5-HTTLPR S-allele carriers. A combined effect of the two polymorphisms on dACC activation during extinction might be associated with prolonged fear expression. Gene

  11. Interactions of primary neuroepithelial progenitor and brain endothelial cells: distinct effect on neural progenitor maintenance and differentiation by soluble factors and direct contact

    Institute of Scientific and Technical Information of China (English)

    Miguel A Gama Sosa; Rita De Gasperi; Anne B Rocher; Gissel M Perez; Keila Simons; Daniel E Cruz; Patrick R Hof; Gregory A Elder

    2007-01-01

    Neurovascular interactions are crucial for the normal development of the central nervous system. To study such interactions in primary cultures, we developed a procedure to simultaneously isolate neural progenitor and endothelial cell fractions from embryonic mouse brains. Depending on the culture conditions endothelial cells were found to favor maintenance of the neuroprogenitor phenotype through the production of soluble factors, or to promote neuronal differentiation of neural progenitors through direct contact. These apparently opposing effects could reflect differential cellular interactions needed for the proper development of the brain.

  12. Environmental enrichment promotes neural remodeling in newborn rats with hypoxic-ischemic brain damage

    Institute of Scientific and Technical Information of China (English)

    Chuanjun Liu; Yankui Guo; Yalu Li; Zhenying Yang

    2011-01-01

    We evaluated the effect of hypoxic-ischemic brain damage and treatment with early environmental enrichment intervention on development of newborn rats, as evaluated by light and electron microscopy and morphometry. Early intervention with environmental enrichment intelligence training attenuated brain edema and neuronal injury, promoted neuronal repair, and increased neuronal plasticity in the frontal lobe cortex of the newborn rats with hypoxic-ischemic brain damage.

  13. Neural basis of understanding communicative actions: Changes associated with knowing the actor's intention and the meanings of the actions.

    Science.gov (United States)

    Möttönen, Riikka; Farmer, Harry; Watkins, Kate E

    2016-01-29

    People can communicate by using hand actions, e.g., signs. Understanding communicative actions requires that the observer knows that the actor has an intention to communicate and the meanings of the actions. Here, we investigated how this prior knowledge affects processing of observed actions. We used functional MRI to determine changes in action processing when non-signers were told that the observed actions are communicative (i.e., signs) and learned the meanings of half of the actions. Processing of hand actions activated the left and right inferior frontal gyrus (IFG, BA 44 and 45) when the communicative intention of the actor was known, even when the meanings of the actions remained unknown. These regions were not active when the observers did not know about the communicative nature of the hand actions. These findings suggest that the left and right IFG play a role in understanding the intention of the actor, but do not process visuospatial features of the communicative actions. Knowing the meanings of the hand actions further enhanced activity in the anterior part of the IFG (BA 45), the inferior parietal lobule and posterior inferior and middle temporal gyri in the left hemisphere. These left-hemisphere language regions could provide a link between meanings and observed actions. In sum, the findings provide evidence for the segregation of the networks involved in the neural processing of visuospatial features of communicative hand actions and those involved in understanding the actor's intention and the meanings of the actions.

  14. Comparative determination of phosphate and silicate using molybdenum blue by radial basis function and feed-forward neural networks assisted by principal component analysis.

    Science.gov (United States)

    Afkhami, Abbas; Abbasi-Tarighat, Maryam

    2008-06-01

    In the present study, chemometric analysis of visible spectral data of phospho-and silico-molybdenum blue complexes was used to develop artificial neural networks (ANNs) for the simultaneous determination of the phosphate and silicate. Combinations of principal component analysis (PCA) with feed-forward neural networks (FFNNs) and radial basis function networks (RBFNs) were built and investigated. The structures of the models were simplified by using the corresponding important principal components as input instead of the original spectra. Number of inputs and hidden nodes, learning rate, transfer functions and number of epochs and SPREAD values were optimized. Performances of methods were tested with root mean square errors prediction (RMSEP, %), using synthetic solutions. The obtained satisfactory results indicate the applicability of this ANN approach based on PCA input selection for determination in highly spectral overlapping. The results obtained by FFNNs and by RBF networks were compared. The applicability of methods was investigated for synthetic samples, for detergent formulations, and for a river water sample.

  15. Application of principal component-radial basis function neural networks (PC-RBFNN) for the detection of water-adulterated bayberry juice by near-infrared spectroscopy

    Institute of Scientific and Technical Information of China (English)

    Li-juan XIE; Xing-qian YE; Dong-hong LIU; Yi-bin YING

    2008-01-01

    Near-infrared (NIR) spectroscopy combined with chemometrics techniques was used to classify the pure bayberry juice and the one adulterated with 10% (w/w) and 20% (w/w) water. Principal component analysis (PCA) was applied to reduce the dimensions of spectral data, give information regarding a potential capability of separation of objects, and provide principal component (PC) scores for radial basis function neural networks (RBFNN). RBFNN was used to detect bayberry juice adulterant. Multiplicative scatter correction (MSC) and standard normal variate (SNV) transformation were used to preprocess spectra. The results demonstrate that PC-RBFNN with optimum parameters can separate pure bayberry juice samples from water-adulterated bayberry at a recognition rate of 97.62%, but cannot clearly detect water levels in the adulterated bayberry juice. We conclude that NIR technology can be successfully applied to detect water-adulterated bayberry juice.

  16. Animal models of autism with a particular focus on the neural basis of changes in social behaviour: an update article.

    Science.gov (United States)

    Olexová, Lucia; Talarovičová, Alžbeta; Lewis-Evans, Ben; Borbélyová, Veronika; Kršková, Lucia

    2012-12-01

    Research on autism has been gaining more and more attention. However, its aetiology is not entirely known and several factors are thought to contribute to the development of this neurodevelopmental disorder. These potential contributing factors range from genetic heritability to environmental effects. A significant number of reviews have already been published on different aspects of autism research as well as focusing on using animal models to help expand current knowledge around its aetiology. However, the diverse range of symptoms and possible causes of autism have resulted in as equally wide variety of animal models of autism. In this update article we focus only on the animal models with neurobehavioural characteristics of social deficit related to autism and present an overview of the animal models with alterations in brain regions, neurotransmitters, or hormones that are involved in a decrease in sociability.

  17. Neural circuit changes mediating lasting brain and behavioral response to predator stress.

    Science.gov (United States)

    Adamec, Robert E; Blundell, Jacqueline; Burton, Paul

    2005-01-01

    This paper reviews recent work which points to critical neural circuitry involved in lasting changes in anxiety like behavior following unprotected exposure of rats to cats (predator stress). Predator stress may increase anxiety like behavior in a variety of behavioral tests including: elevated plus maze, light dark box, acoustic startle, and social interaction. Studies of neural transmission in two limbic pathways, combined with path and covariance analysis relating physiology to behavior, suggest long term potentiation like changes in one or both of these pathways in the right hemisphere accounts for stress induced changes in all behaviors changed by predator stress except light dark box and social interaction. Findings will be discussed within the context of what is known about neural substrates activated by predator odor.

  18. Motor-related brain activity during action observation: a neural substrate for electrocorticographic brain-computer interfaces after spinal cord injury

    Directory of Open Access Journals (Sweden)

    Jennifer L Collinger

    2014-02-01

    Full Text Available After spinal cord injury (SCI, motor commands from the brain are unable to reach peripheral nerves and muscles below the level of the lesion. Action observation, in which a person observes someone else performing an action, has been used to augment traditional rehabilitation paradigms. Similarly, action observation can be used to derive the relationship between brain activity and movement kinematics for a motor-based brain-computer interface (BCI even when the user cannot generate overt movements. BCIs use brain signals to control external devices to replace functions that have been lost due to SCI or other motor impairment. Previous studies have reported congruent motor cortical activity during observed and overt movements using magnetoencephalography (MEG and functional magnetic resonance imaging (fMRI. Recent single-unit studies using intracortical microelectrodes also demonstrated that a large number of motor cortical neurons had similar firing rate patterns between overt and observed movements. Given the increasing interest in electrocorticography (ECoG-based BCIs, our goal was to identify whether action observation-related cortical activity could be recorded using ECoG during grasping tasks. Specifically, we aimed to identify congruent neural activity during observed and executed movements in both the sensorimotor rhythm (10-40 Hz and the high-gamma band (65-115 Hz which contains significant movement-related information. We observed significant motor-related high-gamma band activity during action observation in both able-bodied individuals and one participant with a complete C4 SCI. Furthermore, in able-bodied participants, both the low and high frequency bands demonstrated congruent activity between action execution and observation. Our results suggest that action observation could be an effective and critical procedure for deriving the mapping from ECoG signals to intended movement for an ECoG-based BCI system for individuals with

  19. Detection of neural stem cells function in rats with traumatic brain injury by manganese-enhanced magnetic resonance imaging

    Institute of Scientific and Technical Information of China (English)

    TANG Hai-liang; SUN Hua-ping; WU Xing; SHA Hong-ying; FENG Xiao-yuan; ZHU Jian-hong

    2011-01-01

    Background Previously we had successfully tracked adult human neural stem cells (NSCs) labeled with superparamagnetic iron oxide particles (SPIOs) in host human brain after transplantation In vivo non-invasively by magnetic resonance imaging (MRI). However, the function of the transplanted NSCs could not be evaluated by the method. In the study, we applied manganese-enhanced MRI (ME-MRI) to detect NSCs function after implantation in brain of rats with traumatic brain injury (TBI) In vivo.Methods Totally 40 TBI rats were randomly divided into 4 groups with 10 rats in each group. In group 1, the TBI rats did not receive NSCs transplantation. MnCl2-4H2O was intravenously injected, hyperosmolar mannitol was delivered to disrupt rightside blood brain barrier, and its contralateral forepaw was electrically stimulated. In group 2, the TBI rats received NSCs (labeled with SPIO) transplantation, and the ME-MRI procedure was same to group 1. In group 3, the TBI rats received NSCs (labeled with SPIO) transplantation, and the ME-MRI procedure was same to group 1, but diltiazem was introduced during the electrical stimulation period. In group 4, the TBI rats received phosphate buffered saline (PBS) injection, and the ME-MRI procedure was same to group 1.Results Hyperintense signals were detected by ME-MRI in the cortex areas associated with somatosensory in TBI rats of group 2. These signals, which could not be induced in TBI rats of groups 1 and 4, disappeared when diltiazem was introduced in TBI rats of group 3.Conclusion In this initial study, we mapped implanted NSCs activity and its functional participation within local brain area in TBI rats by ME-MRI technique, paving the way for further pre-clinical research.

  20. Serum protein fingerprinting coupled with artificial neural network distinguishes glioma from healthy population or brain benign tumor

    Institute of Scientific and Technical Information of China (English)

    LIU Jian; ZHENG Shu; YU Jie-kai; ZHANG Jian-min; CHEN Zhe

    2005-01-01

    To screen and evaluate protein biomarkers for the detection of gliomas (Astrocytoma grade Ⅰ-Ⅳ) from healthy individuals and gliomas from brain benign tumors by using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) coupled with an artificial neural network (ANN) algorithm. SELDI-TOF-MS protein fingerprinting of serum from 105 brain tumor patients and healthy individuals, included 28 patients with glioma (Astrocytoma Ⅰ-Ⅳ), 37 patients with brain benign tumor, and 40 age-matched healthy individuals. Two thirds of the total samples of every compared pair as training set were used to set up discriminating patterns, and one third of total samples of every compared pair as test set were used to cross-validate; simultaneously, discriminate-cluster analysis derived SPSS 10.0 software was used to compare Astrocytoma grade Ⅰ-Ⅱ with grade Ⅲ-Ⅳ ones. An accuracy of 95.7%, sensitivity of 88.9%, specificity of 100%, positive predictive value of 90% and negative predictive value of 100% were obtained in a blinded test set comparing gliomas patients with healthy individuals; an accuracy of 86.4%, sensitivity of 88.9%, specificity of 84.6%, positive predictive value of 90% and negative predictive value of 85.7% were obtained when patient's gliomas was compared with benign brain tumor. Total accuracy of 85.7%, accuracy of grade Ⅰ-Ⅱ Astrocytoma was 86.7%, accuracy ofⅢ-Ⅳ Astrocytoma was 84.6% were obtained when grade Ⅰ-Ⅱ Astrocytoma was compared with grade Ⅲ-Ⅳ ones (discriminant analysis). SELDI-TOF-MS combined with bioinformatics tools, could greatly facilitate the discovery of better biomarkers. The high sensitivity and specificity achieved by the use of selected biomarkers showed great potential application for the discrimination of gliomas patients from healthy individuals and glioma from brain benign tumors.

  1. Distribution and localization of fibroblast growth factor-8 in rat brain and nerve cells during neural stem/progenitor cell differentiation

    Institute of Scientific and Technical Information of China (English)

    Jiang Lu; Dongsheng Li; Kehuan Lu

    2012-01-01

    The present study explored the distribution and localization of fibroblast growth factor-8 and its potential receptor,fibroblast growth factor receptor-3,in adult rat brain in vivo and in nerve cells during differentiation of neural stem/progenitor cells in vitro.Immunohistochemistry was used to examine the distribution of fibroblast growth factor-8 in adult rat brain in vivo.Localization of fibroblast growth factor-8 and fibroblast growth factor receptor-3 in cells during neural stem/progenitor cell differentiation in vitro was detected by immunofluorescence.Flow cytometry and immunofluorescence were used to evaluate the effect of an anti-fibroblast growth factor-8 antibody on neural stem/progenitor cell differentiation and expansion in vitro.Results from this study confirmed that fibroblast growth factor-8 was mainly distributed in adult midbrain,namely the substantia nigra,compact part,dorsal tier,substantia nigra and reticular part,but was not detected in the forebrain comprising the caudate putamen and striatum.Unusual results were obtained in retrosplenial locations of adult rat brain.We found that fibroblast growth factor-8 and fibroblast growth factor receptor-3 were distributed on the cell membrane and in the cytoplasm of nerve cells using immunohistochemistry and immunofluorescence analyses.We considered that the distribution of fibroblast growth factor-8 and fibroblast growth factor receptor-3 in neural cells corresponded to the characteristics of fibroblast growth factor-8,a secretory factor.Addition of an anti-fibroblast growth factor-8 antibody to cultures significantly affected the rate of expansion and differentiation of neural stem/progenitor cells.In contrast,addition of recombinant fibroblast growth factor-8 to differentiation medium promoted neural stem/progenitor cell differentiation and increased the final yields of dopaminergic neurons and total neurons.Our study may help delineate the important roles of fibroblast growth factor-8 in brain

  2. Neural Mechanisms Linking Mild Traumatic Brain Injury and Anxiety States in an Animal Model

    Science.gov (United States)

    2012-03-01

    region cortices) as defined by Paxinos and Watson (1998). The volume of each brain region of interest was measured from cresyl violet stained...Kurume Med. J. 56, 49-59. Paxinos , C., Watson, C., 1997. The Rat Brain in Stereotaxic Coordinates, 3rd ed. Academic Press, New York. 30 Ptito

  3. Neural and Behavioral Sequelae of Blast-Related Traumatic Brain Injury

    Science.gov (United States)

    2012-11-01

    bipolar disorder, schizophrenia ) with the exception of post-traumatic stress disorder (PTSD), penetrating gunshot wound to the brain or contraindications...matter degeneration16, increased levels of mortality, brain edema17, and downregulation of genes associated with hippocampal neurogenesis.18

  4. A Review on Effect of Estrogen on Neural Growth and Sexual Dimorphism in the Brain

    Directory of Open Access Journals (Sweden)

    Robel Abay

    2015-10-01

    Full Text Available In addition to the usual classic views of estrogen’s actions in the brain as regulator of ovulation and reproductive behavior in the female; estrogens also play important roles in the male brain as well, where they can be generated from circulating testosterone by local aromatase enzymes or can also be synthesized de novo by neurons and glia and have profound effects on volumetric differences in different brain regions, promotion and inhibition of neurite growth, regulation of synaptic patterning, organizational and activational process of brain sex differentiation. Estrogen has opposite as well as similar effects in male and female brains. These differences include sex dimorphisms in the ability of estrogen to influence synaptic plasticity, neurotransmission, neurodegeneration, and cognition. A large part of sex differences is due to the organization of the underlying circuitry.

  5. Dynamic gesture recognition based on Laguerre orthogonal basis neural network%基于Laguerre正交基神经网络的动态手势识别

    Institute of Scientific and Technical Information of China (English)

    李文生; 解梅; 姚琼

    2011-01-01

    As a powerful tool for learning highly nonlinear system,BP neural networks are widely used in the field of nonlinear system identification such as pattern recognition.However,due to its shortcomings such as slow convergence rate,the danger of over fitting and low recognition accuracy,the traditional BP neural networks perform poorly in dynamic gesture recognition,especially for online dynamic gesture training.In this paper,a novel method of dynamic gesture learning and recognition based on Laguerre orthogonal basis feed-forward neural network was put forward.First,based on polynomial interpolation and matrix theory,a three-layer MIMO feed-forward neural network which hidden layer neurons are activated by a group of Laguerre orthogonal polynomial functions was constructed.In our research,the weights-updating formula for the neural networks was derived by adopting the standard BP training method,and then a pseudo-inverse based method which could determine the network weights directly without lengthy iterative training was proposed.Second,a rapid algorithm to detect and track the fingertips in real time based on machine vision was proposed.At first,a 2D color histogram on HSV color space was computed as the result of on-line training of fingertip colors,and it was used as the basis of fingertip detection and tracking;Then color probability distribution I(x,y) of the target was calculated through back-projection on the 2D color histogram and transformed into a binary image B(x,y) according to a given threshold;Then the target region of fingertips was determinated through edge detection and the centroid positions of targets could be calculated;At last,the trajectories of fingertips could be acquired by tracking the centroids of the fingertips through MDF(Minimum Distance First) and characteristic vectors of the dynamic gestures could be obtained.Third,some pre-obtained dynamic gestures that include characteristic vectors of gestrues and expected outputs were

  6. Mapping the brain's orchestration during speech comprehension: task-specific facilitation of regional synchrony in neural networks

    Directory of Open Access Journals (Sweden)

    Keil Andreas

    2004-10-01

    Full Text Available Abstract Background How does the brain convert sounds and phonemes into comprehensible speech? In the present magnetoencephalographic study we examined the hypothesis that the coherence of electromagnetic oscillatory activity within and across brain areas indicates neurophysiological processes linked to speech comprehension. Results Amplitude-modulated (sinusoidal 41.5 Hz auditory verbal and nonverbal stimuli served to drive steady-state oscillations in neural networks involved in speech comprehension. Stimuli were presented to 12 subjects in the following conditions (a an incomprehensible string of words, (b the same string of words after being introduced as a comprehensible sentence by proper articulation, and (c nonverbal stimulations that included a 600-Hz tone, a scale, and a melody. Coherence, defined as correlated activation of magnetic steady state fields across brain areas and measured as simultaneous activation of current dipoles in source space (Minimum-Norm-Estimates, increased within left- temporal-posterior areas when the sound string was perceived as a comprehensible sentence. Intra-hemispheric coherence was larger within the left than the right hemisphere for the sentence (condition (b relative to all other conditions, and tended to be larger within the right than the left hemisphere for nonverbal stimuli (condition (c, tone and melody relative to the other conditions, leading to a more pronounced hemispheric asymmetry for nonverbal than verbal material. Conclusions We conclude that coherent neuronal network activity may index encoding of verbal information on the sentence level and can be used as a tool to investigate auditory speech comprehension.

  7. [Effect of salvianolic acid B on neural cells damage and neurogenesis after brain ischemia-reperfusion in rats].

    Science.gov (United States)

    Zhong, Jing; Tang, Min-ke; Zhang, Yan; Xu, Qiu-ping; Zhang, Jun-tian

    2007-07-01

    This study is to observe the effect of salvianolic acid B (Sal B) on neural cells damage and neurogenesis in sub-granular zone (SGZ) and sub-ventricular zone (SVZ) after brain ischemia-reperfusion (I/R) in rats. A modified middle cerebral artery occlusion (MCAO) model of focal cerebral ischemia-reperfusion was used. The rats were divided into four groups: sham control group, ischemia-reperfusion group, Sal B 1 and 10 mg x kg(-1) groups. Sal B was consecutively administrated once a day by ip injection after MCAO. The neurogenesis in SGZ and SVZ was investigated by BrdU method 7 days after MCAO. The Nissl staining for neurons in the hippocampal CA1 and cerebral cortex was performed 14 days after MCAO. A beam-walking test was used to monitor the motor function recovery. We found that brain ischemia resulted in an increase of BrdU positive cells both in ipsilateral SGZ and SVZ at 7th day after MCAO. Sal B (10 mg x kg(-1)) significantly increased further the number of BrdU positive cells both in SGZ and SVZ (P loss and improved motor function recovery after brain ischemia in rats.

  8. When first language is not first: an functional magnetic resonance imaging investigation of the neural basis of diglossia in Arabic.

    Science.gov (United States)

    Nevat, Michael; Khateb, Asaid; Prior, Anat

    2014-11-01

    In Arabic, the language used for everyday conversation ('spoken Arabic' - SA) differs markedly from literary Arabic (LA), which is used for written communication and formal functions. This fact raises questions regarding the cognitive status of the two varieties and their processing in the brain. Previous studies using auditory stimuli suggested that LA is processed by Arabic native speakers as a second language. The current study examined this issue in the visual modality. Functional magnetic resonance imaging (fMRI) responses were collected while Arabic-Hebrew bilinguals performed a semantic categorization task on visually presented words in LA, SA and Hebrew. Performance on LA was better than SA and Hebrew, which did not differ from each other. Activation in SA was stronger than in LA in left inferior frontal, precentral, parietal and occipito-temporal regions, and stronger than in Hebrew in left precentral and parietal regions. Activation in SA was also less lateralized than activation for LA and Hebrew, which did not differ from each other in terms of lateralization, though activation for Hebrew was more extensive in both hemispheres than activation for LA. Altogether, these results indicate an advantage for LA in the current study, presumably due to participants' proficiency in reading in this language. Stronger activation for SA appears to be due to the relative unfamiliarity of written word forms in SA, which could also explain differences in performance between the two languages. However, the stronger activation observed in the left parietal cortex may also reflect stronger associations among words in SA.

  9. Neural Coding of Formant-Exaggerated Speech in the Infant Brain

    Science.gov (United States)

    Zhang, Yang; Koerner, Tess; Miller, Sharon; Grice-Patil, Zach; Svec, Adam; Akbari, David; Tusler, Liz; Carney, Edward

    2011-01-01

    Speech scientists have long proposed that formant exaggeration in infant-directed speech plays an important role in language acquisition. This event-related potential (ERP) study investigated neural coding of formant-exaggerated speech in 6-12-month-old infants. Two synthetic /i/ vowels were presented in alternating blocks to test the effects of…

  10. Neural Stem Cell Delivery of Therapeutic Antibodies to Treat Breast Cancer Brain Metastases

    Science.gov (United States)

    2009-10-01

    and Engineering Neural Stem Cells for Delivery of Genetically Encoded 259 References 1. Snyder, EY., Deichter, DL., Walsh, C., Arnold- Aldea , S...acquired with a Zeiss Axio Imager M1m microscope equipped with a digital camera, using 10x or 20x air objectives. Digital images were analyzed using

  11. The Processing of Verbs and Nouns in Neural Networks: Insights from Synthetic Brain Imaging

    Science.gov (United States)

    Cangelosi, Angelo; Parisi, Domenico

    2004-01-01

    The paper presents a computational model of language in which linguistic abilities evolve in organisms that interact with an environment. Each individual's behavior is controlled by a neural network and we study the consequences in the network's internal functional organization of learning to process different classes of words. Agents are selected…

  12. Bird brains and songs : Neural mechanisms of auditory memory and perception in zebra finches

    NARCIS (Netherlands)

    Gobes, S.M.H.

    2009-01-01

    Songbirds, such as zebra finches, learn their songs from a ‘tutor’ (usually the father), early in life. There are strong parallels between the behavioural, cognitive and neural processes that underlie vocal learning in humans and songbirds. In both cases there is a sensitive period for auditory lear

  13. Neural Basis of Creative Thinking during Four Stages%创造性思维四阶段的神经基础

    Institute of Scientific and Technical Information of China (English)

    詹慧佳; 刘昌; 沈汪兵

    2015-01-01

    Wallas put forward an important creative process model and defined four stages of creativity as follows: preparation, incubation, illumination, and verification. The investigations of brain state before the presentation of a creative problem show that the neural activity of the preparation stage is associate with medial PFC/ACC and temporal areas. The neuroscientific researches on presentation of a hint during incubation, delayed insight and mind-wandering reflect the neural correlates of incubation, and the main active brain regions during this stage include hippocampus and ventrolateral PFC. The last two stages are associated with a neural network consisting of several brain regions including PFC, ACC, superior temporal gyrus, hippocampus, precunes, cunes, lingual gyrus and cerebellum et al. The PFC and ACC are involved in different kinds of insight problem solving; the superior temporal gyrus is responsible for the formation of remote associations; the hippocampus is associated with the process of mental set breaking and formation of novel associations; the lateral prefrontal cortex is responsible for mental set shifting; the precunes, left middle/inferior frontal gyrus and lingual gyrus participate in the process of prototype activation. In addition, the verification of the details of solution is found to rely on the left lateral prefrontal cortex. Future studies can be improved in the aspects of research subjects, contents and methods, so that the process of creative thinking can be investigated systematically.%华莱士(Wallas)四阶段论是创造性思维过程研究的重要模型,该模型认为创造性思维包括准备期、酝酿期、明朗期、验证期。相关神经机制研究表明,准备期主要包括题目呈现前大脑状态和静息状态的研究,内侧额叶/ACC及颞叶构成准备期网络;酝酿期主要包括酝酿期提示、延迟顿悟以及心智游移的相关研究,这一阶段涉及左右脑的共同参与,海马

  14. Polyploidization of glia in neural development links tissue growth to blood-brain barrier integrity.

    Science.gov (United States)

    Unhavaithaya, Yingdee; Orr-Weaver, Terry L

    2012-01-01

    Proper development requires coordination in growth of the cell types composing an organ. Many plant and animal cells are polyploid, but how these polyploid tissues contribute to organ growth is not well understood. We found the Drosophila melanogaster subperineurial glia (SPG) to be polyploid, and ploidy is coordinated with brain mass. Inhibition of SPG polyploidy caused rupture of the septate junctions necessary for the blood-brain barrier. Thus, the increased SPG cell size resulting from polyploidization is required to maintain the SPG envelope surrounding the growing brain. Polyploidization likely is a conserved strategy to coordinate tissue growth during organogenesis, with potential vertebrate examples.

  15. Hierarchical random cellular neural networks for system-level brain-like signal processing.

    Science.gov (United States)

    Kozma, Robert; Puljic, Marko

    2013-09-01

    Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms.

  16. Techniques and instrumental complex for research of influence of microwaves encoded by brain neural signals on biological objects’ psycho physiological state

    Science.gov (United States)

    Gurkovskiy, B. V.; Zhuravlev, B. V.; Onishchenko, E. M.; Simakov, A. B.; Trifonova, N. Yu; Voronov, Yu A.

    2016-10-01

    New instrumental technique for research of the psycho-physiological reactions of the bio-objects under the microwave electromagnetic radiation, modulated by interval patterns of neural activity in the brain registered under different biological motivations, are suggested. The preliminary results of these new tool tests in real psycho physiological experiments on rats are presented.

  17. Cavitation Induced Structural and Neural Damage in Live Brain Tissue Slices: Relevance to TBI

    Science.gov (United States)

    2014-09-29

    the value of this experimental platform to investigate the single bubble cavitation- induced damage in a biological tissue is illustrated with an...Lei Wu, Malisa Sarntinoranont, Huikai Xie1. Refractive index measurement of acute rat brain tissue slices using optical coherence tomography, Optics...b-TBI, i.e. what is “broken”, in the brain during exposure to shock loading is currently unknown. While blast waves are well known to have negative

  18. Morphogenetic movements in the neural plate and neural tube: mouse.

    Science.gov (United States)

    Massarwa, R'ada; Ray, Heather J; Niswander, Lee

    2014-01-01

    The neural tube (NT), the embryonic precursor of the vertebrate brain and spinal cord, is generated by a complex and highly dynamic morphological process. In mammals, the initially flat neural plate bends and lifts bilaterally to generate the neural folds followed by fusion of the folds at the midline during the process of neural tube closure (NTC). Failures in any step of this process can lead to neural tube defects (NTDs), a common class of birth defects that occur in approximately 1 in 1000 live births. These severe birth abnormalities include spina bifida, a failure of closure at the spinal level; craniorachischisis, a failure of NTC along the entire body axis; and exencephaly, a failure of the cranial neural folds to close which leads to degeneration of the exposed brain tissue termed anencephaly. The mouse embryo presents excellent opportunities to explore the genetic basis of NTC in mammals; however, its in utero development has also presented great challenges in generating a deeper understanding of how gene function regulates the cell and tissue behaviors that drive this highly dynamic process. Recent technological advances are now allowing researchers to address these questions through visualization of NTC dynamics in the mouse embryo in real time, thus offering new insights into the morphogenesis of mammalian NTC.

  19. Nop2 is expressed during proliferation of neural stem cells and in adult mouse and human brain.

    Science.gov (United States)

    Kosi, Nina; Alić, Ivan; Kolačević, Matea; Vrsaljko, Nina; Jovanov Milošević, Nataša; Sobol, Margarita; Philimonenko, Anatoly; Hozák, Pavel; Gajović, Srećko; Pochet, Roland; Mitrečić, Dinko

    2015-02-09

    The nucleolar protein 2 gene encodes a protein specific for the nucleolus. It is assumed that it plays a role in the synthesis of ribosomes and regulation of the cell cycle. Due to its link to cell proliferation, higher expression of Nop2 indicates a worse tumor prognosis. In this work we used Nop2(gt1gaj) gene trap mouse strain. While lethality of homozygous animals suggested a vital role of this gene, heterozygous animals allowed the detection of expression of Nop2 in various tissues, including mouse brain. Histochemistry, immunohistochemistry and immunoelectron microscopy techniques, applied to a mature mouse brain, human brain and on mouse neural stem cells revealed expression of Nop2 in differentiating cells, including astrocytes, as well as in mature neurons. Nop2 was detected in various regions of mouse and human brain, mostly in large pyramidal neurons. In the human, Nop2 was strongly expressed in supragranular and infragranular layers of the somatosensory cortex and in layer III of the cingulate cortex. Also, Nop2 was detected in CA1 and the subiculum of the hippocampus. Subcellular analyses revealed predominant location of Nop2 within the dense fibrillar component of the nucleolus. To test if Nop2 expression correlates to cell proliferation occurring during tissue regeneration, we induced strokes in mice by middle cerebral artery occlusion. Two weeks after stroke, the number of Nop2/nestin double positive cells in the region affected by ischemia and the periventricular zone substantially increased. Our findings suggest a newly discovered role of Nop2 in both mature neurons and in cells possibly involved in the regeneration of nervous tissue.

  20. Novel Dynamics Observed in a Spiking Neural Network Model of the NTS in the Rat Hind-brain

    Science.gov (United States)

    Zhou, Jingyi; Schaffer, J. David; Dilorenzo, Patricia; Laramee, Craig

    2012-02-01

    The Nucleus of the Solitary Tract (NTS) is a hind-brain structure in the rat that is the first way-station in taste processing. Its structure and function are poorly understood. Recently our group produced a model, implemented as a spiking neural network (SNN), that successfully replicated experimental data. The model's topology was manually devised and the parameters were set by a genetic algorithm. In order to better understand its information processing capabilities, we probed the model with a variety of input spike patterns and observed a striking winner-take-all decision-making dynamic. We show how the topology and tuned parameters enable this decision to depend on precise spike timing events. It is curious that the experimental data upon which the model was originally evolved did not include winner-take-all examples; this was an emergent capability. It remains for additional experiments on rats to confirm or reject this model prediction.

  1. Long-term survival of human neural stem cells in the ischemic rat brain upon transient immunosuppression.

    Directory of Open Access Journals (Sweden)

    Laura Rota Nodari

    Full Text Available Understanding the physiology of human neural stem cells (hNSCs in the context of cell therapy for neurodegenerative disorders is of paramount importance, yet large-scale studies are hampered by the slow-expansion rate of these cells. To overcome this issue, we previously established immortal, non-transformed, telencephalic-diencephalic hNSCs (IhNSCs from the fetal brain. Here, we investigated the fate of these IhNSC's immediate progeny (i.e. neural progenitors; IhNSC-Ps upon unilateral implantation into the corpus callosum or the hippocampal fissure of adult rat brain, 3 days after global ischemic injury. One month after grafting, approximately one fifth of the IhNSC-Ps had survived and migrated through the corpus callosum, into the cortex or throughout the dentate gyrus of the hippocampus. By the fourth month, they had reached the ipsilateral subventricular zone, CA1-3 hippocampal layers and the controlateral hemisphere. Notably, these results could be accomplished using transient immunosuppression, i.e administering cyclosporine for 15 days following the ischemic event. Furthermore, a concomitant reduction of reactive microglia (Iba1+ cells and of glial, GFAP+ cells was also observed in the ipsilateral hemisphere as compared to the controlateral one. IhNSC-Ps were not tumorigenic and, upon in vivo engraftment, underwent differentiation into GFAP+ astrocytes, and β-tubulinIII+ or MAP2+ neurons, which displayed GABAergic and GLUTAmatergic markers. Electron microscopy analysis pointed to the formation of mature synaptic contacts between host and donor-derived neurons, showing the full maturation of the IhNSC-P-derived neurons and their likely functional integration into the host tissue. Thus, IhNSC-Ps possess long-term survival and engraftment capacity upon transplantation into the globally injured ischemic brain, into which they can integrate and mature into neurons, even under mild, transient immunosuppressive conditions. Most notably

  2. Design and validation of a real-time spiking-neural-network decoder for brain-machine interfaces

    Science.gov (United States)

    Dethier, Julie; Nuyujukian, Paul; Ryu, Stephen I.; Shenoy, Krishna V.; Boahen, Kwabena

    2013-06-01

    Objective. Cortically-controlled motor prostheses aim to restore functions lost to neurological disease and injury. Several proof of concept demonstrations have shown encouraging results, but barriers to clinical translation still remain. In particular, intracortical prostheses must satisfy stringent power dissipation constraints so as not to damage cortex. Approach. One possible solution is to use ultra-low power neuromorphic chips to decode neural signals for these intracortical implants. The first step is to explore in simulation the feasibility of translating decoding algorithms for brain-machine interface (BMI) applications into spiking neural networks (SNNs). Main results. Here we demonstrate the validity of the approach by implementing an existing Kalman-filter-based decoder in a simulated SNN using the Neural Engineering Framework (NEF), a general method for mapping control algorithms onto SNNs. To measure this system’s robustness and generalization, we tested it online in closed-loop BMI experiments with two rhesus monkeys. Across both monkeys, a Kalman filter implemented using a 2000-neuron SNN has comparable performance to that of a Kalman filter implemented using standard floating point techniques. Significance. These results demonstrate the tractability of SNN implementations of statistical signal processing algorithms on different monkeys and for several tasks, suggesting that a SNN decoder, implemented on a neuromorphic chip, may be a feasible computational platform for low-power fully-implanted prostheses. The validation of this closed-loop decoder system and the demonstration of its robustness and generalization hold promise for SNN implementations on an ultra-low power neuromorphic chip using the NEF.

  3. Neural signatures of social conformity: A coordinate-based activation likelihood estimation meta-analysis of functional brain imaging studies.

    Science.gov (United States)

    Wu, Haiyan; Luo, Yi; Feng, Chunliang

    2016-12-01

    People often align their behaviors with group opinions, known as social conformity. Many neuroscience studies have explored the neuropsychological mechanisms underlying social conformity. Here we employed a coordinate-based meta-analysis on neuroimaging studies of social conformity with the purpose to reveal the convergence of the underlying neural architecture. We identified a convergence of reported activation foci in regions associated with normative decision-making, including ventral striatum (VS), dorsal posterior medial frontal cortex (dorsal pMFC), and anterior insula (AI). Specifically, consistent deactivation of VS and activation of dorsal pMFC and AI are identified when people's responses deviate from group opinions. In addition, the deviation-related responses in dorsal pMFC predict people's conforming behavioral adjustments. These are consistent with current models that disagreement with others might evoke "error" signals, cognitive imbalance, and/or aversive feelings, which are plausibly detected in these brain regions as control signals to facilitate subsequent conforming behaviors. Finally, group opinions result in altered neural correlates of valuation, manifested as stronger responses of VS to stimuli endorsed than disliked by others.

  4. Scaling of brain metabolism and blood flow in relation to capillary and neural scaling.

    Science.gov (United States)

    Karbowski, Jan

    2011-01-01

    Brain is one of the most energy demanding organs in mammals, and its total metabolic rate scales with brain volume raised to a power of around 5/6. This value is significantly higher than the more common exponent 3/4 relating whole body resting metabolism with body mass and several other physiological variables in animals and plants. This article investigates the reasons for brain allometric distinction on a level of its microvessels. Based on collected empirical data it is found that regional cerebral blood flow CBF across gray matter scales with cortical volume V as CBF ~ V(-1/6), brain capillary diameter increases as V(1/12), and density of capillary length decreases as V(-1/6). It is predicted that velocity of capillary blood is almost invariant (~V(ε)), capillary transit time scales as V(1/6), capillary length increases as V(1/6+ε), and capillary number as V(2/3-ε), where ε is typically a small correction for medium and large brains, due to blood viscosity dependence on capillary radius. It is shown that the amount of capillary length and blood flow per cortical neuron are essentially conserved across mammals. These results indicate that geometry and dynamics of global neuro-vascular coupling have a proportionate character. Moreover, cerebral metabolic, hemodynamic, and microvascular variables scale with allometric exponents that are simple multiples of 1/6, rather than 1/4, which suggests that brain metabolism is more similar to the metabolism of aerobic than resting body. Relation of these findings to brain functional imaging studies involving the link between cerebral metabolism and blood flow is also discussed.

  5. Scaling of brain metabolism and blood flow in relation to capillary and neural scaling.

    Directory of Open Access Journals (Sweden)

    Jan Karbowski

    Full Text Available Brain is one of the most energy demanding organs in mammals, and its total metabolic rate scales with brain volume raised to a power of around 5/6. This value is significantly higher than the more common exponent 3/4 relating whole body resting metabolism with body mass and several other physiological variables in animals and plants. This article investigates the reasons for brain allometric distinction on a level of its microvessels. Based on collected empirical data it is found that regional cerebral blood flow CBF across gray matter scales with cortical volume V as CBF ~ V(-1/6, brain capillary diameter increases as V(1/12, and density of capillary length decreases as V(-1/6. It is predicted that velocity of capillary blood is almost invariant (~V(ε, capillary transit time scales as V(1/6, capillary length increases as V(1/6+ε, and capillary number as V(2/3-ε, where ε is typically a small correction for medium and large brains, due to blood viscosity dependence on capillary radius. It is shown that the amount of capillary length and blood flow per cortical neuron are essentially conserved across mammals. These results indicate that geometry and dynamics of global neuro-vascular coupling have a proportionate character. Moreover, cerebral metabolic, hemodynamic, and microvascular variables scale with allometric exponents that are simple multiples of 1/6, rather than 1/4, which suggests that brain metabolism is more similar to the metabolism of aerobic than resting body. Relation of these findings to brain functional imaging studies involving the link between cerebral metabolism and blood flow is also discussed.

  6. Application of Near Infrared Diffuse Reflectance Spectroscopy with Radial Basis Function Neural Network to Determination of Rifampincin Isoniazid and Pyrazinamide Tablets

    Institute of Scientific and Technical Information of China (English)

    DU Lin-na; WU Li-hang; LU Jia-hui; GUO Wei-liang; MENG Qing-fan; JIANG Chao-jun; SHEN Si-le; TENG Li-rong

    2007-01-01

    Partial least squares(PLS), back-propagation neural network (BPNN) and radial basis function neural network(RBFNN) were respectively used for estalishing quantative analysis models with near infrared(NIR) diffuse reflectance spectra for determining the contents of rifampincin(RMP), isoniazid(INH) and pyrazinamide(PZA) in rifampicin isoniazid and pyrazinamide tablets. Savitzky-Golay smoothing, first derivative, second derivative, fast Fourier transform(FFT) and standard normal variate(SNV) transformation methods were applied to pretreating raw NIR diffuse reflectance spectra. The raw and pretreated spectra were divided into several regions, depending on the average spectrum and RSD spectrum. Principal component analysis(PCA) method was used for analyzing the raw and pretreated spectra in different regions in order to reduce the dimensions of input data. The optimum spectral regions and the models' parameters were chosen by comparing the root mean square error of cross-validation(RMSECV) values which were obtained by leave-one-out cross-validation method. The RMSECV values of the RBFNN models for determining the contents of RMP, INH and PZA were 0.00288, 0.00226 and 0.00341, respectively. Using these models for predicting the contents of INH, RMP and PZA in prediction set, the RMSEP values were 0.00266, 0.00227 and 0.00411, respectively. These results are better than those obtained from PLS models and BPNN models. With additional advantages of fast calculation speed and less dependence on the initial conditions, RBFNN is a suitable tool to model complex systems.

  7. Neural mechanisms of subclinical depressive symptoms in women: a pilot functional brain imaging study

    Directory of Open Access Journals (Sweden)

    Felder Jennifer N

    2012-09-01

    Full Text Available Abstract Background Studies of individuals who do not meet criteria for major depressive disorder (MDD but with subclinical levels of depressive symptoms may aid in the identification of neurofunctional abnormalities that possibly precede and predict the development of MDD. The purpose of this study was to evaluate relations between subclinical levels of depressive symptoms and neural activation patterns during tasks previously shown to differentiate individuals with and without MDD. Methods Functional magnetic resonance imaging (fMRI was used to assess neural activations during active emotion regulation, a resting state scan, and reward processing. Participants were twelve females with a range of depressive symptoms who did not meet criteria for MDD. Results Increased depressive symptom severity predicted (1 decreased left midfrontal gyrus activation during reappraisal of sad stimuli; (2 increased right midfrontal gyrus activation during distraction from sad stimuli; (3 increased functional connectivity between a precuneus seed region and left orbitofrontal cortex during a resting state scan; and (4 increased paracingulate activation during non-win outcomes during a reward-processing task. Conclusions These pilot data shed light on relations between subclinical levels of depressive symptoms in the absence of a formal MDD diagnosis and neural activation patterns. Future studies will be needed to test the utility of these activation patterns for predicting MDD onset in at-risk samples.

  8. Visual awareness suppression by pre-stimulus brain stimulation; a neural effect.

    Science.gov (United States)

    Jacobs, Christianne; Goebel, Rainer; Sack, Alexander T

    2012-01-02

    Transcranial magnetic stimulation (TMS) has established the functional relevance of early visual cortex (EVC) for visual awareness with great temporal specificity non-invasively in conscious human volunteers. Many studies have found a suppressive effect when TMS was applied over EVC 80-100 ms after the onset of the visual stimulus (post-stimulus TMS time window). Yet, few studies found task performance to also suffer when TMS was applied even before visual stimulus presentation (pre-stimulus TMS time window). This pre-stimulus TMS effect, however, remains controversially debated and its origin had mainly been ascribed to TMS-induced eye-blinking artifacts. Here, we applied chronometric TMS over EVC during the execution of a visual discrimination task, covering an exhaustive range of visual stimulus-locked TMS time windows ranging from -80 pre-stimulus to 300 ms post-stimulus onset. Electrooculographical (EoG) recordings, sham TMS stimulation, and vertex TMS stimulation controlled for different types of non-neural TMS effects. Our findings clearly reveal TMS-induced masking effects for both pre- and post-stimulus time windows, and for both objective visual discrimination performance and subjective visibility. Importantly, all effects proved to be still present after post hoc removal of eye blink trials, suggesting a neural origin for the pre-stimulus TMS suppression effect on visual awareness. We speculate based on our data that TMS exerts its pre-stimulus effect via generation of a neural state which interacts with subsequent visual input.

  9. Is avoiding an aversive outcome rewarding? Neural substrates of avoidance learning in the human brain.

    Science.gov (United States)

    Kim, Hackjin; Shimojo, Shinsuke; O'Doherty, John P

    2006-07-01

    Avoidance learning poses a challenge for reinforcement-based theories of instrumental conditioning, because once an aversive outcome is successfully avoided an individual may no longer experience extrinsic reinforcement for their behavior. One possible account for this is to propose that avoiding an aversive outcome is in itself a reward, and thus avoidance behavior is positively reinforced on each trial when the aversive outcome is successfully avoided. In the present study we aimed to test this possibility by determining whether avoidance of an aversive outcome recruits the same neural circuitry as that elicited by a reward itself. We scanned 16 human participants with functional MRI while they performed an instrumental choice task, in which on each trial they chose from one of two actions in order to either win money or else avoid losing money. Neural activity in a region previously implicated in encoding stimulus reward value, the medial orbitofrontal cortex, was found to increase, not only following receipt of reward, but also following successful avoidance of an aversive outcome. This neural signal may itself act as an intrinsic reward, thereby serving to reinforce actions during instrumental avoidance.

  10. The neural basis of trait self-esteem revealed by the amplitude of low-frequency fluctuations and resting state functional connectivity.

    Science.gov (United States)

    Pan, Weigang; Liu, Congcong; Yang, Qian; Gu, Yan; Yin, Shouhang; Chen, Antao

    2016-03-01

    Self-esteem is an affective, self-evaluation of oneself and has a significant effect on mental and behavioral health. Although research has focused on the neural substrates of self-esteem, little is known about the spontaneous brain activity that is associated with trait self-esteem (TSE) during the resting state. In this study, we used the resting-state functional magnetic resonance imaging (fMRI) signal of the amplitude of low-frequency fluctuations (ALFFs) and resting state functional connectivity (RSFC) to identify TSE-related regions and networks. We found that a higher level of TSE was associated with higher ALFFs in the left ventral medial prefrontal cortex (vmPFC) and lower ALFFs in the left cuneus/lingual gyrus and right lingual gyrus. RSFC analyses revealed that the strengths of functional connectivity between the left vmPFC and bilateral hippocampus were positively correlated with TSE; however, the connections between the left vmPFC and right inferior frontal gyrus and posterior superior temporal sulcus were negatively associated with TSE. Furthermore, the strengths of functional connectivity between the left cuneus/lingual gyrus and right dorsolateral prefrontal cortex and anterior cingulate cortex were positively related to TSE. These findings indicate that TSE is linked to core regions in the default mode network and social cognition network, which is involved in self-referential processing, autobiographical memory and social cognition.

  11. Opaque for the reader but transparent for the brain: neural signatures of morphological complexity.

    Science.gov (United States)

    Meinzer, Marcus; Lahiri, Aditi; Flaisch, Tobias; Hannemann, Ronny; Eulitz, Carsten

    2009-07-01

    Within linguistics, words with a complex internal structure are commonly assumed to be decomposed into their constituent morphemes (e.g., un-help-ful). Nevertheless, an ongoing debate concerns the brain structures that subserve this process. Using functional magnetic resonance imaging, the present study varied the internal complexity of derived words while keeping the external surface structure constant as well as controlling relevant parameters that could affect word recognition. This allowed us to tease apart brain activations specifically related to morphological processing from those related to possible confounds of perceptual cues like word length or affix type. Increased task-related activity in left inferior frontal, bilateral temporo-occipital and right parietal areas was specifically related to the processing of derivations with high complex internal structure relative to those with low complex internal structure. Our results show, that morphologically complex words are decomposed and that the brain processes the degree of internal complexity of word derivations.

  12. Interfaces, syntactic movement, and neural activation: A new perspective on the implementation of language in the brain

    DEFF Research Database (Denmark)

    Christensen, Ken Ramshøj

    2008-01-01

    Studies of language deficits as well as neuroimaging studies indicate that syntactic processing of displaced constituents is implemented in the brain as a distributed cortical network of modules. The data from the present fMRI study on two types of syntactic movement in Danish offers further...... support for such a distributed syntactic network. These results, together with the results from a number of other fMRI studies in the literature, form the basis for the Domain Hypothesis according to which differential activation in the subcomponents of the cortical network reflects computation...

  13. Neural Tube Defects

    Science.gov (United States)

    Neural tube defects are birth defects of the brain, spine, or spinal cord. They happen in the ... that she is pregnant. The two most common neural tube defects are spina bifida and anencephaly. In ...

  14. Implanted neural progenitor cells regulate glial reaction to brain injury and establish gap junctions with host glial cells.

    Science.gov (United States)

    Talaverón, Rocío; Matarredona, Esperanza R; de la Cruz, Rosa R; Macías, David; Gálvez, Victoria; Pastor, Angel M

    2014-04-01

    Transplantation of neural stem/progenitor cells (NPCs) in the lesioned brain is able to restore morphological and physiological alterations induced by different injuries. The local microenvironment created at the site of grafting and the communication between grafted and host cells are crucial in the beneficial effects attributed to the NPC implants. We have previously described that NPC transplantation in an animal model of central axotomy restores firing properties and synaptic coverage of lesioned neurons and modulates their trophic factor content. In this study, we aim to explore anatomical relationships between implanted NPCs and host glia that might account for the implant-induced neuroprotective effects. Postnatal rat subventricular zone NPCs were isolated and grafted in adult rats after transection of the medial longitudinal fascicle. Brains were removed and analyzed eight weeks later. Immunohistochemistry for different glial markers revealed that NPC-grafted animals displayed significantly greater microglial activation than animals that received only vehicle injections. Implanted NPCs were located in close apposition to activated microglia and reactive astrocytes. The gap junction protein connexin43 was present in NPCs and glial cells at the lesion site and was often found interposed within adjacent implanted and glial cells. Gap junctions were identified between implanted NPCs and host astrocytes and less frequently between NPCs and microglia. Our results show that implanted NPCs modulate the glial reaction to lesion and establish the possibility of communication through gap junctions between grafted and host glial cells which might be involved in the restorative effects of NPC implants.

  15. Functional recovery after transplantation of neural stem cells modified by brain-derived neurotrophic factor in rats with cerebral ischaemia.