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Sample records for brain neural basis

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

    Science.gov (United States)

    Kohyama, Jun

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jun Kohyama

    2016-01-01

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

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

    Science.gov (United States)

    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.

  4. 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

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

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

    2008-12-01

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

  7. The neural basis of impaired self-awareness after traumatic brain injury

    OpenAIRE

    Ham, Timothy E.; Bonnelle, Valerie; Hellyer, Peter; Jilka, Sagar; Ian H Robertson; Leech, Robert; Sharp, David J.

    2013-01-01

    Impaired self-awareness is a disabling consequence of many neurological diseases. Ham et al. use structural and functional MRI to compare patients with high and low levels of performance monitoring after traumatic brain injury. Dysfunction of the insulae and anterior cingulate cortices within the salience network contributes to deficits in self-awareness.

  8. [Neural basis of procedural memory].

    Science.gov (United States)

    Mochizuki-Kawai, Hiroko

    2008-07-01

    Procedural memory is acquired by trial and error. Our daily life is supported by a number of procedural memories such as those for riding bicycle, typing, reading words, etc. Procedural memory is divided into 3 types; motor, perceptual, and cognitive. Here, the author reviews the cognitive and neural basis of procedural memory according to these 3 types. It is reported that the basal ganglia or cerebellum dysfunction causes deficits in procedural memory. Compared with age-matched healthy participants, patients with Parkinson disease (PD), Huntington disease (HD) or spinocerebellar degeneration (SCD) show deterioration in improvements in motor-type procedural memory tasks. Previous neuroimaging studies have reported that motor-type procedural memory may be supported by multiple brain regions, including the frontal and parietal regions as well as the basal ganglia (cerebellum); this was found with a serial reaction time task (SRT task). Although 2 other types of procedural memory are also maintained by multiple brain regions, the related cerebral areas depend on the type of memory. For example, it was suggested that acquisition of the perceptual type of procedural memory (e.g., ability to read mirror images of words) might be maintained by the bilateral fusiform region, while the acquisition of cognitive procedural memory might be supported by the frontal, parietal, or cerebellar regions as well as the basal ganglia. In the future, we need to cleary understand the neural "network" related to the procedural memory. PMID:18646622

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

    Science.gov (United States)

    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

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

    Science.gov (United States)

    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

  11. [Neural basis of maternal behavior].

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2014-01-01

    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. PMID:24961770

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

    Directory of Open Access Journals (Sweden)

    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.

  14. Genetic influences on the neural basis of social cognition

    OpenAIRE

    Skuse, David

    2006-01-01

    The neural basis of social cognition has been the subject of intensive research in both human and non-human primates. Exciting, provocative and yet consistent findings are emerging. A major focus of interest is the role of efferent and afferent connectivity between the amygdala and the neocortical brain regions, now believed to be critical for the processing of social and emotional perceptions. One possible component is a subcortical neural pathway, which permits rapid and preconscious proces...

  15. 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.

    Science.gov (United States)

    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.

  16. The neural basis of bounded rational behavior

    Directory of Open Access Journals (Sweden)

    Coricelli, Giorgio

    2012-03-01

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

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

  17. Neural Basis of Visual Distraction

    Science.gov (United States)

    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…

  18. Molecular basis of neural function

    International Nuclear Information System (INIS)

    The conference proceedings contain abstracts of plenary lectures, of young neurochemists' ESN honorary lectures, lectures at symposia and workshops and poster communications. Twenty abstracts were inputted in INIS. The subject of these were the use of autoradiography for the determination of receptors, cholecystokinin, nicotine, adrenaline, glutamate, aspartate, tranquilizers, for distribution and pharmacokinetics of obidoxime-chloride, for cell proliferation, mitosis of brain cells, DNA repair; radioimmunoassay of cholinesterase, tyrosinase; positron computed tomography of the brain; biological radiation effects on cholinesterase activity; tracer techniques for determination of adrenaline; and studies of the biological repair of nerves. (J.P.)

  19. Brain and language: evidence for neural multifunctionality.

    Science.gov (United States)

    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 basis of bounded rational behavior

    OpenAIRE

    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. ...

  1. Neural basis of interpersonal traits in neurodegenerative diseases.

    Science.gov (United States)

    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.

  2. The neural basis of tactile motion perception

    OpenAIRE

    Pei, Yu-Cheng; Sliman J Bensmaia

    2014-01-01

    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 th...

  3. The neural circuit basis of learning

    Science.gov (United States)

    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

  4. Neural prostheses and brain plasticity

    Science.gov (United States)

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

    2009-12-01

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

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

    Directory of Open Access Journals (Sweden)

    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. Neural network plasticity in the human brain

    OpenAIRE

    Rizk, Sviatlana

    2013-01-01

    The human brain is highly organized within networks. Functionally related neural-assemblies communicate by oscillating synchronously. Intrinsic brain activity contains information on healthy and damaged brain functioning. This thesis investigated the relationship between functional networks and behavior. Furthermore, we assessed functional network plasticity after brain damage and as a result of brain stimulation. In different groups of patients we observed reduced functional connectivity bet...

  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.

    Science.gov (United States)

    Orban, Guy A; Caruana, Fausto

    2014-01-01

    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 anterior intraparietal (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. PMID

  9. 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.

  10. The neural basis of responsibility attribution in decision-making.

    Directory of Open Access Journals (Sweden)

    Peng Li

    Full Text Available Social responsibility links personal behavior with societal expectations and plays a key role in affecting an agent's emotional state following a decision. However, the neural basis of responsibility attribution remains unclear. In two previous event-related brain potential (ERP studies we found that personal responsibility modulated outcome evaluation in gambling tasks. Here we conducted a functional magnetic resonance imaging (fMRI study to identify particular brain regions that mediate responsibility attribution. In a context involving team cooperation, participants completed a task with their teammates and on each trial received feedback about team success and individual success sequentially. We found that brain activity differed between conditions involving team success vs. team failure. Further, different brain regions were associated with reinforcement of behavior by social praise vs. monetary reward. Specifically, right temporoparietal junction (RTPJ was associated with social pride whereas dorsal striatum and dorsal anterior cingulate cortex (ACC were related to reinforcement of behaviors leading to personal gain. The present study provides evidence that the RTPJ is an important region for determining whether self-generated behaviors are deserving of praise in a social context.

  11. The neural basis of responsibility attribution in decision-making.

    Science.gov (United States)

    Li, Peng; Shen, Yue; Sui, Xue; Chen, Changming; Feng, Tingyong; Li, Hong; Holroyd, Clay

    2013-01-01

    Social responsibility links personal behavior with societal expectations and plays a key role in affecting an agent's emotional state following a decision. However, the neural basis of responsibility attribution remains unclear. In two previous event-related brain potential (ERP) studies we found that personal responsibility modulated outcome evaluation in gambling tasks. Here we conducted a functional magnetic resonance imaging (fMRI) study to identify particular brain regions that mediate responsibility attribution. In a context involving team cooperation, participants completed a task with their teammates and on each trial received feedback about team success and individual success sequentially. We found that brain activity differed between conditions involving team success vs. team failure. Further, different brain regions were associated with reinforcement of behavior by social praise vs. monetary reward. Specifically, right temporoparietal junction (RTPJ) was associated with social pride whereas dorsal striatum and dorsal anterior cingulate cortex (ACC) were related to reinforcement of behaviors leading to personal gain. The present study provides evidence that the RTPJ is an important region for determining whether self-generated behaviors are deserving of praise in a social context. PMID:24224053

  12. 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

  13. Exploring the Neural Basis of Cognitive Reserve in Aging

    OpenAIRE

    Steffener, Jason; Stern, Yaakov

    2011-01-01

    The concept of reserve arose from the mismatch between the extent of brain changes or pathology and the clinical manifestations of these brain changes. The cognitive reserve hypothesis posits that individual differences in the flexibility and adaptability of brain networks underlying cognitive function may allow some people to cope better with brain changes than others. Although there is ample epidemiologic evidence for cognitive reserve, the neural substrate of reserve is still a topic of on...

  14. 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

  15. 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.

  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. 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.

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

    NARCIS (Netherlands)

    C.M.A. Pennartz

    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. 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.

  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. 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. PMID:26688301

  2. Neural Prostheses and Brain Plasticity

    OpenAIRE

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

    2009-01-01

    The success of modern neural prostheses is dependent on a complex interplay between the devices’ hardware and software and the dynamic environment in which the devices operate: the patient’s body or ‘wetware’. Over 110,000 severe/profoundly deaf individuals presently receive information enabling auditory awareness and speech perception from cochlear implants. The cochlear implant therefore provides a useful case study for a review of the complex interactions between hardware, software and wet...

  3. Radial basis function neural networks applied to NASA SSME data

    Science.gov (United States)

    Wheeler, Kevin R.; Dhawan, Atam P.

    1993-01-01

    This paper presents a brief report on the application of Radial Basis Function Neural Networks (RBFNN) to the prediction of sensor values for fault detection and diagnosis of the Space Shuttle's Main Engines (SSME). The location of the Radial Basis Function (RBF) node centers was determined with a K-means clustering algorithm. A neighborhood operation about these center points was used to determine the variances of the individual processing notes.

  4. 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)

  5. 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.

  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. Dynamic social power modulates neural basis of math calculation

    OpenAIRE

    Tokiko eHarada; Donna eBridge; Chiao, Joan Y.

    2013-01-01

    Both situational (e.g., perceived power) and sustained social factors (e.g., cultural stereotypes) are known to affect how people academically perform, particularly in the domain of mathematics. The ability to compute even simple mathematics, such as addition, relies on distinct neural circuitry within the inferior parietal and inferior frontal lobes, brain regions where magnitude representation and addition are performed. Despite prior behavioral evidence of social influence on academic pe...

  8. 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.

  9. 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…

  10. 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.

  11. Implementation of Radial Basis Function Neural Network for Image Steganalysis

    OpenAIRE

    Sambasiva Rao Baragada; S. Ramakrishna; M.S. Rao; S. Purushothaman

    2008-01-01

    Steganographic tools and techniques are becoming more potential and widespread. Illegal use of steganography poses serious challenges to the law enforcement agencies. Limited work has been carried out on supervised steganalysis using neural network as a classifier. We present a combined method of identifying the presence of covert information in a carrier image using fisher’s linear discriminant (FLD) function followed by the radial basis function (RBF). Experiments show promising resu...

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

    OpenAIRE

    Jeremy Purcell

    2015-01-01

    Introduction: In acquired dysgraphia, the spelling network is disrupted, typically causing difficulty in correctly spelling some words more than others. Various studies have demonstrated that training can be effective for recovery (e.g., Beeson et al., 2002; Rapp, 2005). However, little is known regarding the neural basis of this recovery. Studying the neural changes associated with recovery can improve understanding of how the damaged brain responds to behavioral treatment, and will be relev...

  13. 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.

  14. 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.

  15. 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.

  16. Implementation of Radial Basis Function Neural Network for Image Steganalysis

    Directory of Open Access Journals (Sweden)

    Sambasiva Rao Baragada

    2008-09-01

    Full Text Available Steganographic tools and techniques are becoming more potential and widespread. Illegal use of steganography poses serious challenges to the law enforcement agencies. Limited work has been carried out on supervised steganalysis using neural network as a classifier. We present a combined method of identifying the presence of covert information in a carrier image using fisher’s linear discriminant (FLD function followed by the radial basis function (RBF. Experiments show promising results when compared to the existing supervised steganalysis methods, but arranging the retrieved information is still a challenging problem.

  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. The neural basis of predicate-argument structure.

    Science.gov (United States)

    Hurford, James R

    2003-06-01

    Neural correlates exist for a basic component of logical formulae, PREDICATE(x). Vision and audition research in primates and humans shows two independent neural pathways; one locates objects in body-centered space, the other attributes properties, such as colour, to objects. In vision these are the dorsal and ventral pathways. In audition, similarly separable "where" and "what" pathways exist. PREDICATE(x) is a schematic representation of the brain's integration of the two processes of delivery by the senses of the location of an arbitrary referent object, mapped in parietal cortex, and analysis of the properties of the referent by perceptual subsystems. The brain computes actions using a few "deictic" variables pointing to objects. Parallels exist between such nonlinguistic variables and linguistic deictic devices. Indexicality and reference have linguistic and nonlinguistic (e.g., visual) versions, sharing the concept of attention. The individual variables of logical formulae are interpreted as corresponding to these mental variables. In computing action, the deictic variables are linked with "semantic" information about the objects, corresponding to logical predicates. Mental scene descriptions are necessary for practical tasks of primates, and preexist language phylogenetically. The type of scene descriptions used by nonhuman primates would be reused for more complex cognitive, ultimately linguistic, purposes. The provision by the brain's sensory/perceptual systems of about four variables for temporary assignment to objects, and the separate processes of perceptual categorization of the objects so identified, constitute a pre-adaptive platform on which an early system for the linguistic description of scenes developed. PMID:14968690

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

    Science.gov (United States)

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

    2014-11-01

    Perceivers extract multiple social dimensions from another's face (e.g., race, emotion), and these dimensions can become linked due to stereotypes (e.g., Black individuals → angry). The current research examined the neural basis of detecting and resolving conflicts between top-down stereotypes and bottom-up visual information in person perception. Participants viewed faces congruent and incongruent with stereotypes, via variations in race and emotion, while neural activity was measured using fMRI. Hand movements en route to race/emotion responses were recorded using mouse-tracking to behaviorally index individual differences in stereotypical associations during categorization. The medial prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) showed stronger activation to faces that violated stereotypical expectancies at the intersection of multiple social categories (i.e., race and emotion). These regions were highly sensitive to the degree of incongruency, exhibiting linearly increasing responses as race and emotion became stereotypically more incongruent. Further, the ACC exhibited greater functional connectivity with the lateral fusiform cortex, a region implicated in face processing, when viewing stereotypically incongruent (relative to congruent) targets. Finally, participants with stronger behavioral tendencies to link race and emotion stereotypically during categorization showed greater dorsolateral prefrontal cortex activation to stereotypically incongruent targets. Together, the findings provide insight into how conflicting stereotypes at the nexus of multiple social dimensions are resolved at the neural level to accurately perceive other people. PMID:25094016

  20. 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.

  1. The brain basis of social synchrony

    OpenAIRE

    Atzil, Shir; Hendler, Talma; Feldman, Ruth

    2013-01-01

    As a social species, humans evolved to detect information from the social behavior of others. Yet, the mechanisms used to evaluate social interactions, the brain networks implicated in such recognition, and whether individual differences in own social behavior determine response to similar behavior in others remain unknown. Here we examined social synchrony as a potentially important mechanism in the evaluation of social behavior and utilized the parenting context, an evolutionarily salient s...

  2. Statistical Physics, Neural Networks, Brain Studies

    Science.gov (United States)

    Toulouse, Gerard

    1999-01-01

    An overview of some aspects of a vast domain, located at the crossroads of physics, biology and computer science is presented: 1) During the last fifteen years, physicists advancing along various pathways have come into contact with biology (computational neurosciences) and engineering (formal neural nets). 2) This move may actually be viewed as one component in a larger picture. A prominent trend of recent years, observable over many countries, has been the establishment of interdisciplinary centers devoted to the study of: cognitive sciences; natural and artificial intelligence; brain, mind and behaviour; perception and action; learning and memory; robotics; man-machine communication, etc. What are the promising lines of development? What opportunities for physicists? An attempt will be made to address such questions, and related issues.

  3. Statistical physics, neural networks, brain studies

    International Nuclear Information System (INIS)

    An overview of some aspects of a vast domain, located at the crossroads of physics, biology and computer science is presented: (1) During the last fifteen years, physicists advancing along various pathways have come into contact with biology (computational neurosciences) and engineering (formal neural nets). (2) This move may actually be viewed as one component in a larger picture. A prominent trend of recent years, observable over many countries, has been the establishment of interdisciplinary centers devoted to the study of: cognitive sciences; natural and artificial intelligence; brain, mind and behaviour; perception and action; learning and memory; robotics; man-machine communication, etc. What are the promising lines of development? What opportunities for physicists? An attempt will be made to address such questions and related issues

  4. 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. PMID:16531040

  5. 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.

  6. 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.

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

    Science.gov (United States)

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

    2014-09-01

    Human beings are constantly engaged in thought. Sometimes thoughts occur repetitively and can become distressing. Up to now the neural bases of these intrusive or unwanted thoughts is largely unexplored. To study the neural correlates of unwanted thoughts, we acquired resting-state fMRI data of 41 female healthy subjects and assessed the self-reported amount of unwanted thoughts during measurement. We analyzed local connectivity by means of regional homogeneity (ReHo) and functional connectivity of a seed region. More unwanted thoughts (state) were associated with lower ReHo in right dorsolateral prefrontal cortex (DLPFC) and higher ReHo in left striatum (putamen). Additional seed-based analysis revealed higher functional connectivity of the left striatum with left inferior frontal gyrus (IFG) in participants reporting more unwanted thoughts. The state-dependent higher connectivty in left striatum was positively correlated with rumination assessed with a dedicated questionnaire focussing on trait aspects. Unwanted thoughts are associated with activity in the fronto-striatal brain circuitry. The reduction of local connectivity in DLPFC could reflect deficiencies in thought suppression processes, whereas the hightened activity in left striatum could imply an imbalance of gating mechanisms housed in basal ganglia. Its functional connectivity to left IFG is discussed as the result of thought-related speech processes. PMID:23929943

  8. Neural stem cell sex dimorphism in aromatase (CYP19 expression: a basis for differential neural fate

    Directory of Open Access Journals (Sweden)

    Jay Waldron

    2010-11-01

    Full Text Available Jay Waldron1, Althea McCourty1, Laurent Lecanu1,21The Research Institute of the McGill University Health Centre, Montreal, Canada; 2Department of Medicine, McGill University, Quebec, CanadaPurpose: Neural stem cell (NSC transplantation and pharmacologic activation of endogenous neurogenesis are two approaches that trigger a great deal of interest as brain repair strategies. However, the success rate of clinical attempts using stem cells to restore neurologic functions altered either after traumatic brain injury or as a consequence of neurodegenerative disease remains rather disappointing. This suggests that factors affecting the fate of grafted NSCs are largely understudied and remain to be characterized. We recently reported that aging differentially affects the neurogenic properties of male and female NSCs. Although the sex steroids androgens and estrogens participate in the regulation of neurogenesis, to our knowledge, research on how gender-based differences affect the capacity of NSCs to differentiate and condition their neural fate is lacking. In the present study, we explored further the role of cell sex as a determining factor of the neural fate followed by differentiating NSCs and its relationship with a potential differential expression of aromatase (CYP19, the testosterone-metabolizing enzyme.Results: Using NSCs isolated from the subventricular zone of three-month-old male and female Long-Evans rats and maintained as neurospheres, we showed that differentiation triggered by retinoic acid resulted in a neural phenotype that depends on cell sex. Differentiated male NSCs mainly expressed markers of neuronal fate, including ßIII-tubulin, microtubule associated protein 2, growth-associated protein 43, and doublecortin. In contrast, female NSCs essentially expressed the astrocyte marker glial fibrillary acidic protein. Quantification of the expression of aromatase showed a very low level of expression in undifferentiated female NSCs

  9. A Neural Basis for the Acquired Capability for Suicide

    Science.gov (United States)

    Deshpande, Gopikrishna; Baxi, Madhura; Witte, Tracy; Robinson, Jennifer L.

    2016-01-01

    The high rate of fatal suicidal behavior (SB) 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 SB. The Interpersonal–Psychological Theory of Suicide has proposed an explanation for the seemingly paradoxical relationship between gender and SB, 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 the acquired 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 model is a first attempt to characterize

  10. A Neural Basis for the Acquired Capability for Suicide.

    Science.gov (United States)

    Deshpande, Gopikrishna; Baxi, Madhura; Witte, Tracy; Robinson, Jennifer L

    2016-01-01

    The high rate of fatal suicidal behavior (SB) 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 SB. The Interpersonal-Psychological Theory of Suicide has proposed an explanation for the seemingly paradoxical relationship between gender and SB, 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 the acquired 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 model is a first attempt to characterize the

  11. 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

  12. 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.

  13. 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. PMID:26417673

  14. 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.

  15. 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. PMID:25037924

  16. Estimating Neural Signal Dynamics in the Human Brain

    Directory of Open Access Journals (Sweden)

    Christopher W Tyler

    2011-06-01

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

  17. BRAIN TUMOR CLASSIFICATION USING NEURAL NETWORK BASED METHODS

    OpenAIRE

    Kalyani A. Bhawar*, Prof. Nitin K. Bhil

    2016-01-01

    MRI (Magnetic resonance Imaging) brain neoplasm pictures Classification may be a troublesome tasks due to the variance and complexity of tumors. This paper presents two Neural Network techniques for the classification of the magnetic resonance human brain images. The proposed Neural Network technique consists of 3 stages, namely, feature extraction, dimensionality reduction, and classification. In the first stage, we have obtained the options connected with tomography pictures victimization d...

  18. Optimal Brain Surgeon on Artificial Neural Networks in

    DEFF Research Database (Denmark)

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

    2012-01-01

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

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

    Science.gov (United States)

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

    2012-10-01

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

  20. 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.

  1. Neural Substrate Expansion for the Restoration of Brain Function.

    Science.gov (United States)

    Chen, H Isaac; Jgamadze, Dennis; Serruya, Mijail D; Cullen, D Kacy; Wolf, John A; Smith, Douglas H

    2016-01-01

    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. PMID:26834579

  2. 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.

  3. 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.

  4. 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.

  5. Experience-dependent neural plasticity in the adult damaged brain

    OpenAIRE

    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 extremity (hand and arm) impairments. A prolonged and widespread process of repair and reorganization of surviving neural circuits is instigated by in...

  6. An Efficient Weather Forecasting System using Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Tiruvenkadam Santhanam

    2011-01-01

    Full Text Available Problem statement: Accurate weather forecasting plays a vital role for planning day to day activities. Neural network has been use in numerous meteorological applications including weather forecasting. Approach: A neural network model has been developed for weather forecasting, based on various factors obtained from meteorological experts. This study evaluates the performance of Radial Basis Function (RBF with Back Propagation (BPN neural network. The back propagation neural network and radial basis function neural network were used to test the performance in order to investigate effective forecasting technique. Results: The prediction accuracy of RBF was 88.49%. Conclusion: The results indicate that proposed radial basis function neural network is better than back propagation neural network.

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

    Science.gov (United States)

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

    2011-09-01

    The study of patients with semantic dementia has revealed important insights into the cognitive and neural architecture of semantic memory. Patients with semantic dementia are known to have difficulty understanding the meanings of environmental sounds from an early stage but little is known about their knowledge for famous tunes, which might be preserved in some cases. Patients with semantic dementia (n = 13), Alzheimer's disease (n = 14) as well as matched healthy control participants (n = 20) underwent a battery of tests designed to assess knowledge of famous tunes, environmental sounds and famous faces, as well as volumetric magnetic resonance imaging. As a group, patients with semantic dementia were profoundly impaired in the recognition of everyday environmental sounds and famous tunes with consistent performance across testing modalities, which is suggestive of a central semantic deficit. A few notable individuals (n = 3) with semantic dementia demonstrated clear preservation of knowledge of known melodies and famous people. Defects in auditory semantics were mild in patients with Alzheimer's disease. Voxel-based morphometry of magnetic resonance brain images showed that the recognition of famous tunes correlated with the degree of right anterior temporal lobe atrophy, particularly in the temporal pole. This area was segregated from the region found to be involved in the recognition of everyday sounds but overlapped considerably with the area that was correlated with the recognition of famous faces. The three patients with semantic dementia with sparing of musical knowledge had significantly less atrophy of the right temporal pole in comparison to the other patients in the semantic dementia group. These findings highlight the role of the right temporal pole in the processing of known tunes and faces. Overlap in this region might reflect that having a unique identity is a quality that is common to both melodies and people. PMID:21857031

  8. Behavioral sensitization to ethanol: Neural basis and factors that influence its acquisition and expression.

    Science.gov (United States)

    Camarini, Rosana; Pautassi, Ricardo Marcos

    2016-07-01

    Ethanol-induced behavioral sensitization (EBS) was first described in 1980, approximately 10 years after the phenomenon was described for psychostimulants. Ethanol acts on γ-aminobutyric acid (GABA) and glutamate receptors as an allosteric agonist and antagonist, respectively, but it also affects many other molecular targets. The multiplicity of factors involved in the behavioral and neurochemical effects of ethanol and the ensuing complexity may explain much of the apparent disparate results, found across different labs, regarding ethanol-induced behavioral sensitization. Although the mesocorticolimbic dopamine system plays an important role in EBS, we provide evidence of the involvement of other neurotransmitter systems, mainly the glutamatergic, GABAergic, and opioidergic systems. This review also analyses the neural underpinnings (e.g., induction of cellular transcription factors such as cyclic adenosine monophosphate response element binding protein and growth factors, such as the brain-derived neurotrophic factor) and other factors that influence the phenomenon, including age, sex, dose, and protocols of drug administration. One of the reasons that make EBS an attractive phenomenon is the assumption, firmly based on empirical evidence, that EBS and addiction-related processes have common molecular and neural basis. Therefore, EBS has been used as a model of addiction processes. We discuss the association between different measures of ethanol-induced reward and EBS. Parallels between the pharmacological basis of EBS and acute motor effects of ethanol are also discussed. PMID:27093941

  9. Neural Plastic Effects of Cognitive Training on Aging Brain

    OpenAIRE

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

    2015-01-01

    Increasing research has evidenced that our brain retains a capacity to change in response to experience until late adulthood. This implies that cognitive training can possibly ameliorate age-associated cognitive decline by inducing training-specific neural plastic changes at both neural and behavioral levels. This longitudinal study examined the behavioral effects of a systematic thirteen-week cognitive training program on attention and working memory of older adults who were at risk of cogni...

  10. Development of neural stem cell in the adult brain

    OpenAIRE

    Duan, Xin; Kang, Eunchai; Liu, Cindy Y.; Ming, Guo-li; Song, Hongjun

    2008-01-01

    New neurons are continuously generated in the dentate gyrus of the mammalian hippocampus and in the subventricular zone of the lateral ventricles throughout life. The origin of these new neurons is believed to be from multipotent adult neural stem cells. Aided by new methodologies, significant progress has been made in the characterization of neural stem cells and their development in the adult brain. Recent studies have also begun to reveal essential extrinsic and intrinsic molecular mechani...

  11. The Basis of Hyperspecificity in Autism: A Preliminary Suggestion Based on Properties of Neural Nets.

    Science.gov (United States)

    McClelland, James L.

    2000-01-01

    This article discusses representation of information in neural networks and the apparent hyperspecificity that is often seen in the application of previously acquired information by children with autism. Hyperspecificity is seen as reflecting a possible feature of the neural codes used to represent concepts in the autistic brain. (Contains 12…

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

    OpenAIRE

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

    2013-01-01

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

  13. Wave forecasting in near real time basis by neural network

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, S.; Mandal, S.; Prabaharan, N.

    ., forecasting of waves become an important aspect of marine environment. This paper presents application of the neural network (NN) with better update algorithms, namely rprop, quickprop and superSAB for wave forecasting. Measured waves off Marmagoa, Goa, India...

  14. The neural basis of unwanted thoughts during resting state

    OpenAIRE

    Kühn, Simone; Vanderhasselt, Marie-Anne; Raedt, Rudi; Gallinar, J

    2013-01-01

    Human beings are constantly engaged in thought. Sometimes thoughts occur repetitively and can become distressing. Up to now the neural bases of these intrusive or unwanted thoughts is largely unexplored. To study the neural correlates of unwanted thoughts, we acquired resting-state fMRI data of 41 female healthy subjects and assessed the self-reported amount of unwanted thoughts during measurement. We analyzed local connectivity by means of regional homogeneity (ReHo) and functional connectiv...

  15. 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

  16. 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.

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

    NARCIS (Netherlands)

    F. van Winden; M. Stallen; K.R. Ridderinkhof

    2009-01-01

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

  18. The neural basis of the speed-accuracy tradeoff

    NARCIS (Netherlands)

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

    2010-01-01

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

  19. Towards a neural basis of interactive alignment in conversation

    Directory of Open Access Journals (Sweden)

    Laura eMenenti

    2012-06-01

    Full Text Available The interactive-alignment account of dialogue proposes that interlocutors achieve conversational success by aligning their understanding of the situation under discussion. Such alignment occurs because they prime each other at different levels of representation (e.g., phonology, syntax, semantics, and this is possible because these representations are shared across production and comprehension. In this paper, we briefly review the behavioural evidence, and then consider how findings from cognitive neuroscience might lend support to this account, on the assumption that alignment of neural activity corresponds to alignment of mental states. We first review work supporting representational parity between production and comprehension, and suggest that neural activity associated with phonological, lexical, and syntactic aspects of production and comprehension are closely related. We next consider evidence for the neural bases of the activation and use of situation models during production and comprehension, and how these demonstrate the activation of non-linguistic conceptual representations associated with language use. We then review evidence for alignment of neural mechanisms that are specific to the act of communication. Finally, we suggest some avenues of further research that need to be explored to test crucial predictions of the interactive alignment account.

  20. 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...

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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. PMID:26527184

  6. 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.

  7. 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.

  8. Neural mechanisms underlying neurooptometric rehabilitation following traumatic brain injury

    Directory of Open Access Journals (Sweden)

    Hudac CM

    2012-01-01

    Full Text Available Caitlin M Hudac1, Srinivas Kota1, James L Nedrow2, Dennis L Molfese1,31Department of Psychology, University of Nebraska-Lincoln, 2Oculi Vision Rehabilitation, 3Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, Lincoln, NEAbstract: Mild to severe traumatic brain injuries have lasting effects on everyday functioning. Issues relating to sensory problems are often overlooked or not addressed until well after the onset of the injury. In particular, vision problems related to ambient vision and the magnocellular pathway often result in posttrauma vision syndrome or visual midline shift syndrome. Symptoms from these syndromes are not restricted to the visual domain. Patients commonly experience proprioceptive, kinesthetic, vestibular, cognitive, and language problems. Neurooptometric rehabilitation often entails the use of corrective lenses, prisms, and binasal occlusion to accommodate the unstable magnocellular system. However, little is known regarding the neural mechanisms engaged during neurooptometric rehabilitation, nor how these mechanisms impact other domains. Event-related potentials from noninvasive electrophysiological recordings can be used to assess rehabilitation progress in patients. In this case report, high-density visual event-related potentials were recorded from one patient with posttrauma vision syndrome and secondary visual midline shift syndrome during a pattern reversal task, both with and without prisms. Results indicate that two factors occurring during the end portion of the P148 component (168–256 milliseconds poststimulus onset map onto two separate neural systems that were engaged with and without neurooptometric rehabilitation. Without prisms, neural sources within somatosensory, language, and executive brain regions engage inefficient magnocellular system processing. However, when corrective prisms were worn, primary visual areas were appropriately engaged. The impact of using early

  9. 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.

  10. 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.

  11. A natural basis for efficient brain-actuated control

    Science.gov (United States)

    Makeig, S.; Enghoff, S.; Jung, T. P.; Sejnowski, T. J.

    2000-01-01

    The prospect of noninvasive brain-actuated control of computerized screen displays or locomotive devices is of interest to many and of crucial importance to a few 'locked-in' subjects who experience near total motor paralysis while retaining sensory and mental faculties. Currently several groups are attempting to achieve brain-actuated control of screen displays using operant conditioning of particular features of the spontaneous scalp electroencephalogram (EEG) including central mu-rhythms (9-12 Hz). A new EEG decomposition technique, independent component analysis (ICA), appears to be a foundation for new research in the design of systems for detection and operant control of endogenous EEG rhythms to achieve flexible EEG-based communication. ICA separates multichannel EEG data into spatially static and temporally independent components including separate components accounting for posterior alpha rhythms and central mu activities. We demonstrate using data from a visual selective attention task that ICA-derived mu-components can show much stronger spectral reactivity to motor events than activity measures for single scalp channels. ICA decompositions of spontaneous EEG would thus appear to form a natural basis for operant conditioning to achieve efficient and multidimensional brain-actuated control in motor-limited and locked-in subjects.

  12. 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. PMID:26736358

  13. 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.

  14. 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

    2016-04-01

    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. PMID:27001827

  15. 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

    2016-04-01

    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.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Renata S Suter

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

  18. Neural Basis of Repetition Priming during Mathematical Cognition: Repetition Suppression or Repetition Enhancement?

    Science.gov (United States)

    Salimpoor, Valorie N.; Chang, Catie; Menon, Vinod

    2010-01-01

    We investigated the neural basis of repetition priming (RP) during mathematical cognition. Previous studies of RP have focused on repetition suppression as the basis of behavioral facilitation, primarily using word and object identification and classification tasks. More recently, researchers have suggested associative stimulus-response learning…

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. Optical imaging of neural and hemodynamic brain activity

    Science.gov (United States)

    Schei, Jennifer Lynn

    Optical imaging technologies can be used to record neural and hemodynamic activity. Neural activity elicits physiological changes that alter the optical tissue properties. Specifically, changes in polarized light are concomitant with neural depolarization. We measured polarization changes from an isolated lobster nerve during action potential propagation using both reflected and transmitted light. In transmission mode, polarization changes were largest throughout the center of the nerve, suggesting that most of the optical signal arose from the inner nerve bundle. In reflection mode, polarization changes were largest near the edges, suggesting that most of the optical signal arose from the outer sheath. To overcome irregular cell orientation found in the brain, we measured polarization changes from a nerve tied in a knot. Our results show that neural activation produces polarization changes that can be imaged even without regular cell orientations. Neural activation expends energy resources and elicits metabolic delivery through blood vessel dilation, increasing blood flow and volume. We used spectroscopic imaging techniques combined with electrophysiological measurements to record evoked neural and hemodynamic responses from the auditory cortex of the rat. By using implantable optics, we measured responses across natural wake and sleep states, as well as responses following different amounts of sleep deprivation. During quiet sleep, evoked metabolic responses were larger compared to wake, perhaps because blood vessels were more compliant. When animals were sleep deprived, evoked hemodynamic responses were smaller following longer periods of deprivation. These results suggest that prolonged neural activity through sleep deprivation may diminish vascular compliance as indicated by the blunted vascular response. Subsequent sleep may allow vessels to relax, restoring their ability to deliver blood. These results also suggest that severe sleep deprivation or chronic

  4. 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)

  5. 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.

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

    Science.gov (United States)

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

    2008-12-01

    Although the influence of long-term musical training on the processing of heard music has been the subject of many studies, the neural basis of music imagery and the effect of musical expertise remain insufficiently understood. By means of magnetoencephalography (MEG) we compared musicians and nonmusicians in a musical imagery task with familiar melodies. Subjects listened to the beginnings of the melodies, continued them in their imagination and then heard a tone which was either a correct or an incorrect further continuation of the melody. Only in musicians was the imagery of these melodies strong enough to elicit an early preattentive brain response to unexpected incorrect continuations of the imagined melodies; this response, the imagery mismatch negativity (iMMN), peaked approximately 175 ms after tone onset and was right-lateralized. In contrast to previous studies the iMMN was not based on a heard but on a purely imagined memory trace. Our results suggest that in trained musicians imagery and perception rely on similar neuronal correlates, and that the musicians' intense musical training has modified this network to achieve a superior ability for imagery and preattentive processing of music. PMID:19046375

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

    NARCIS (Netherlands)

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

    2003-01-01

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

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

    NARCIS (Netherlands)

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

    2003-01-01

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

  9. Neural basis of an inherited speech and language disorder

    Science.gov (United States)

    Vargha-Khadem, F.; Watkins, K. E.; Price, C. J.; Ashburner, J.; Alcock, K. J.; Connelly, A.; Frackowiak, R. S. J.; Friston, K. J.; Pembrey, M. E.; Mishkin, M.; Gadian, D. G.; Passingham, R. E.

    1998-01-01

    Investigation of the three-generation KE family, half of whose members are affected by a pronounced verbal dyspraxia, has led to identification of their core deficit as one involving sequential articulation and orofacial praxis. A positron emission tomography activation study revealed functional abnormalities in both cortical and subcortical motor-related areas of the frontal lobe, while quantitative analyses of magnetic resonance imaging scans revealed structural abnormalities in several of these same areas, particularly the caudate nucleus, which was found to be abnormally small bilaterally. A recent linkage study [Fisher, S., Vargha-Khadem, F., Watkins, K. E., Monaco, A. P. & Pembry, M. E. (1998) Nat. Genet. 18, 168–170] localized the abnormal gene (SPCH1) to a 5.6-centiMorgan interval in the chromosomal band 7q31. The genetic mutation or deletion in this region has resulted in the abnormal development of several brain areas that appear to be critical for both orofacial movements and sequential articulation, leading to marked disruption of speech and expressive language. PMID:9770548

  10. The Rate of Approximation of Gaussian Radial Basis Neural Networks in Continuous Function Space

    Institute of Scientific and Technical Information of China (English)

    Ting Fan XIE; Fei Long CAO

    2013-01-01

    There have been many studies on the dense theorem of approximation by radial basis feedforword neural networks,and some approximation problems by Gaussian radial basis feedforward neural networks (GRBFNs) in some special function space have also been investigated.This paper considers the approximation by the GRBFNs in continuous function space.It is proved that the rate of approximation by GRNFNs with nd neurons to any continuous function f defined on a compact subset K (C) Rd can be controlled by ω(f,n-1/2),where ω(f,t) is the modulus of continuity of the function f.

  11. 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.

  12. 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.

  13. 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.

  14. 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…

  15. Postnatal Neural Stem Cells in Treating Traumatic Brain Injury.

    Science.gov (United States)

    Gazalah, Hussein; Mantash, Sarah; Ramadan, Naify; Al Lafi, Sawsan; El Sitt, Sally; Darwish, Hala; Azari, Hassan; Fawaz, Lama; Ghanem, Noël; Zibara, Kazem; Boustany, Rose-Mary; Kobeissy, Firas; Soueid, Jihane

    2016-01-01

    Traumatic brain injury (TBI) is one of the leading causes of death and disabilities worldwide. It affects approximately 1.5 million people each year and is associated with severe post-TBI symptoms such as sensory and motor deficits. Several neuro-therapeutic approaches ranging from cell therapy interventions such as the use of neural stem cells (NSCs) to drug-based therapies have been proposed for TBI management. Successful cell-based therapies are tightly dependent on reproducible preclinical animal models to ensure safety and optimal therapeutic benefits. In this chapter, we describe the isolation of NSCs from neonatal mouse brain using the neurosphere assay in culture. Subsequently, dissociated neurosphere-derived cells are used for transplantation into the ipsilateral cortex of a controlled cortical impact (CCI) TBI model in C57BL/6 mice. Following intra-cardiac perfusion and brain removal, the success of NSC transplantation is then evaluated using immunofluorescence in order to assess neurogenesis along with gliosis in the ipsilateral coronal brain sections. Behavioral tests including rotarod and pole climbing are conducted to evaluate the motor activity post-treatment intervention. PMID:27604746

  16. [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.

  17. 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.

  18. 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.

  19. Brain micro-ecologies: neural stem cell niches in the adult mammalian brain

    OpenAIRE

    Riquelme, Patricio A; Drapeau, Elodie; Doetsch, Fiona

    2007-01-01

    Neurogenesis persists in two germinal regions in the adult mammalian brain, the subventricular zone of the lateral ventricles and the subgranular zone in the hippocampal formation. Within these two neurogenic niches, specialized astrocytes are neural stem cells, capable of self-renewing and generating neurons and glia. Cues within the niche, from cell–cell interactions to diffusible factors, are spatially and temporally coordinated to regulate proliferation and neurogenesis, ultimately affect...

  20. Altered Brain Activities Associated with Neural Repetition Effects in Mild Cognitive Impairment Patients.

    Science.gov (United States)

    Yu, Jing; Li, Rui; Jiang, Yang; Broster, Lucas S; Li, Juan

    2016-05-11

    Older adults with mild cognitive impairment (MCI) manifest impaired explicit memory. However, studies on implicit memory such as repetition effects in persons with MCI have been limited. In the present study, 17 MCI patients and 16 healthy normal controls (NC) completed a modified delayed-match-to-sample task while undergoing functional magnetic resonance imaging. We aim to examine the neural basis of repetition; specifically, to elucidate whether and how repetition-related brain responses are altered in participants with MCI. When repeatedly rejecting distracters, both NC and MCI showed similar behavioral repetition effects; however, in both whole-brain and region-of-interest analyses of functional data, persons with MCI showed reduced repetition-driven suppression in the middle occipital and middle frontal gyrus. Further, individual difference analysis found that activation in the left middle occipital gyrus was positively correlated with rejecting reaction time and negatively correlated with accuracy rate, suggesting a predictor of repetition behavioral performance. These findings provide new evidence to support the view that neural mechanisms of repetition effect are altered in MCI who manifests compensatory repetition-related brain activities along with their neuropathology. PMID:27176074

  1. Enduring Consequences of Early-Life Infection on Glial and Neural Cell Genesis Within Cognitive Regions of the Brain

    OpenAIRE

    Bland, Sondra T.; Beckley, Jacob T; Young, Sarah; Tsang, Verne; Watkins, Linda R; Steven F. Maier; Staci D. Bilbo

    2009-01-01

    Systemic infection with Escherichia coli on postnatal day (P) 4 in rats results in significantly altered brain cytokine responses and behavioral changes in adulthood, but only in response to a subsequent immune challenge with lipopolysaccharide [LPS]. The basis for these changes may be long-term changes in glial cell function. We assessed glial and neural cell genesis in the hippocampus, parietal cortex (PAR), and pre-frontal cortex (PFC), in neonates just after the infection, as well as in a...

  2. Research on motion compensation method based on neural network of radial basis function

    Institute of Scientific and Technical Information of China (English)

    Zuo Yunbo

    2014-01-01

    The machining precision not only depends on accurate mechanical structure but also depends on motion compensation method. If manufacturing precision of mechanical structure cannot be improved, the motion compensation is a reasonable way to improve motion precision. A motion compensation method based on neural network of radial basis function (RBF) was presented in this paper. It utilized the infinite approximation advantage of RBF neural network to fit the motion error curve. The best hidden neural quantity was optimized by training the motion error data and calculating the total sum of squares. The best curve coefficient matrix was got and used to calculate motion compensation values. The experiments showed that the motion errors could be reduced obviously by utilizing the method in this paper.

  3. 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.

  4. 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.

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

    International Nuclear Information System (INIS)

    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

  6. 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.

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

    OpenAIRE

    Jean-Marc Fellous; Masami Tatsuno

    2014-01-01

    The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits...

  8. Moderate traumatic brain injury promotes proliferation of quiescent neural progenitors in the adult hippocampus

    OpenAIRE

    Gao, Xiang; Enikolopov, Grigori; Chen, Jinhui

    2009-01-01

    Recent evidence shows that traumatic brain injury (TBI) regulates proliferation of neural stem/progenitor cells in the dentate gyrus (DG) of adult hippocampus. There are distinct classes of neural stem/progenitor cells in the adult DG, including quiescent neural progenitors (QNPs), which carry stem cell properties, and their progeny, amplifying neural progenitors (ANPs). The response of each class of progenitors to TBI is not clear. We here used a transgenic reporter Nestin-GFP mouse line, in...

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

    OpenAIRE

    Craig, A.D. (Bud)

    2009-01-01

    A model of awareness based on interoceptive salience is described, which has an endogenous time base that might provide a basis for the human capacity to perceive and estimate time intervals in the range of seconds to subseconds. The model posits that the neural substrate for awareness across time is located in the anterior insular cortex, which fits with recent functional imaging evidence relevant to awareness and time perception. The time base in this model is adaptive and emotional, and th...

  10. 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.

  11. 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.

  12. Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

    OpenAIRE

    Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

    2015-01-01

    Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significa...

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

    Directory of Open Access Journals (Sweden)

    Michael Polanco

    2016-06-01

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

  14. Losing Neutrality: The Neural Basis of Impaired Emotional Control without Sleep.

    Science.gov (United States)

    Simon, Eti Ben; Oren, Noga; Sharon, Haggai; Kirschner, Adi; Goldway, Noam; Okon-Singer, Hadas; Tauman, Rivi; Deweese, Menton M; Keil, Andreas; Hendler, Talma

    2015-09-23

    Sleep deprivation has been shown recently to alter emotional processing possibly associated with reduced frontal regulation. Such impairments can ultimately fail adaptive attempts to regulate emotional processing (also known as cognitive control of emotion), although this hypothesis has not been examined directly. Therefore, we explored the influence of sleep deprivation on the human brain using two different cognitive-emotional tasks, recorded using fMRI and EEG. Both tasks involved irrelevant emotional and neutral distractors presented during a competing cognitive challenge, thus creating a continuous demand for regulating emotional processing. Results reveal that, although participants showed enhanced limbic and electrophysiological reactions to emotional distractors regardless of their sleep state, they were specifically unable to ignore neutral distracting information after sleep deprivation. As a consequence, sleep deprivation resulted in similar processing of neutral and negative distractors, thus disabling accurate emotional discrimination. As expected, these findings were further associated with a decrease in prefrontal connectivity patterns in both EEG and fMRI signals, reflecting a profound decline in cognitive control of emotion. Notably, such a decline was associated with lower REM sleep amounts, supporting a role for REM sleep in overnight emotional processing. Altogether, our findings suggest that losing sleep alters emotional reactivity by lowering the threshold for emotional activation, leading to a maladaptive loss of emotional neutrality. Significance statement: Sleep loss is known as a robust modulator of emotional reactivity, leading to increased anxiety and stress elicited by seemingly minor triggers. In this work, we aimed to portray the neural basis of these emotional impairments and their possible association with frontal regulation of emotional processing, also known as cognitive control of emotion. Using specifically suited EEG and f

  15. Neural Network Based Augmented Reality for Detection of Brain Tumor

    Directory of Open Access Journals (Sweden)

    P.Mithun

    2013-04-01

    Full Text Available The development in technology opened the door of fiction and reached reality. Major medical applications deals on robot-assisted surgery and image guided surgery. Because of this, substantial research is going on to implement Augmented Reality (AR in instruments which incorporate the surgeon’s intuitive capabilities. Augmented reality is the grouping of virtual entity or 3D stuffs which are overlapped on live camera feed information. The decisive aim of augmented reality is to enhancing the virtual video and a 3D object onto a real world on which it will raise the person’s conceptual understanding of the subject. In this paper we described a solution for initial prediction of tumour cells in MRI images of human brain using image processing technique the output of which will be the 3D slicedimage of the human brain. The sliced image is then virtually embedded on the top of human head during the time of surgery so that the surgeon can exactly locate the spot to be operated. Before augmenting the 3D sliced image Artificial neural network is used to select the appropriate image that contains tumor automatically in order to make the system more efficient.

  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...... for investigating how to best combine human and machine design capabilities to create more complex artificial brains....

  17. 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.

  18. The Neural Basis of Economic Decision-Making in the Ultimatum Game

    Science.gov (United States)

    Sanfey, Alan G.; Rilling, James K.; Aronson, Jessica A.; Nystrom, Leigh E.; Cohen, Jonathan D.

    2003-06-01

    The nascent field of neuroeconomics seeks to ground economic decision- making in the biological substrate of the brain. We used functional magnetic resonance imaging of Ultimatum Game players to investigate neural substrates of cognitive and emotional processes involved in economic decision-making. In this game, two players split a sum of money; one player proposes a division and the other can accept or reject this. We scanned players as they responded to fair and unfair proposals. Unfair offers elicited activity in brain areas related to both emotion (anterior insula) and cognition (dorsolateral prefrontal cortex). Further, significantly heightened activity in anterior insula for rejected unfair offers suggests an important role for emotions in decision-making.

  19. 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.

  20. Characterization of TLX Expression in Neural Stem Cells and Progenitor Cells in Adult Brains

    OpenAIRE

    Shengxiu Li; Guoqiang Sun; Kiyohito Murai; Peng Ye; Yanhong Shi

    2012-01-01

    TLX has been shown to play an important role in regulating the self-renewal and proliferation of neural stem cells in adult brains. However, the cellular distribution of endogenous TLX protein in adult brains remains to be elucidated. In this study, we used immunostaining with a TLX-specific antibody to show that TLX is expressed in both neural stem cells and transit-amplifying neural progenitor cells in the subventricular zone (SVZ) of adult mouse brains. Then, using a double thymidine analo...

  1. Brain structural basis of cognitive reappraisal and expressive suppression

    OpenAIRE

    Hermann, Andrea; Bieber, Alexandra; Keck, Tanja; Vaitl, Dieter; Stark, Rudolf

    2013-01-01

    Cognitive reappraisal and expressive suppression, two major emotion regulation strategies, are differentially related to emotional well-being. The aim of this study was to test the association of individual differences in these two emotion regulation strategies with gray matter volume of brain regions that have been shown to be involved in the regulation of emotions. Based on high-resolution magnetic resonance images of 96 young adults voxel-based morphometry was used to analyze the gray matt...

  2. 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.

  3. 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.

  4. 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.

  5. 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. PMID:27503706

  6. 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.

  7. Evolutionary Basis of Human Running and Its Impact on Neural Function.

    Science.gov (United States)

    Schulkin, Jay

    2016-01-01

    Running is not unique to humans, but it is seemingly a basic human capacity. This article addresses the evolutionary origins of humans running long distances, the basic physical capability of running, and the neurogenesis of aerobic fitness. This article more specifically speaks to the conditions that set the stage for the act of running, and then looks at brain expression, and longer-term consequences of running within a context of specific morphological features and diverse information molecules that participate in our capacity for running and sport. While causal factors are not known, we do know that physiological factors are involved in running and underlie neural function. Multiple themes about running are discussed in this article, including neurogenesis, neural plasticity, and memory enhancement. Aerobic exercise increases anterior hippocampus size. This expansion is linked to the improvement of memory, which reflects the improvement of learning as a function of running activity in animal studies. Higher fitness is associated with greater expansion, not only of the hippocampus, but of several other brain regions. PMID:27462208

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

    CERN Document Server

    Sundararajan, N; Wei Lu Ying

    1999-01-01

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

  9. 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. PMID:16718651

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

    Science.gov (United States)

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

    2014-08-28

    Due to the effort of several research teams across the world, today we have a solid base of knowledge on the liquid contained in the brain cavities, its composition, and biological roles. Although the cerebrospinal fluid (CSF) is among the most relevant parts of the central nervous system from the physiological point of view, it seems that it is not a permanent and stable entity because its composition and biological properties evolve across life. So, we can talk about different CSFs during the vertebrate life span. In this review, we focus on the CSF in an interesting period, early in vertebrate development before the formation of the choroid plexus. This specific entity is called "embryonic CSF." Based on the structure of the compartment, CSF composition, origin and circulation, and its interaction with neuroepithelial precursor cells (the target cells) we can conclude that embryonic CSF is different from the CSF in later developmental stages and from the adult CSF. This article presents arguments that support the singularity of the embryonic CSF, mainly focusing on its influence on neural precursor behavior during development and in adult life. PMID:25165044

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

    International Nuclear Information System (INIS)

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

  12. 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.

  13. Anatomical basis of sun compass navigation I: the general layout of the monarch butterfly brain.

    Science.gov (United States)

    Heinze, Stanley; Reppert, Steven M

    2012-06-01

    Each fall, eastern North American monarch butterflies (Danaus plexippus) use a time-compensated sun compass to migrate to their overwintering grounds in central Mexico. The sun compass mechanism involves the neural integration of skylight cues with timing information from circadian clocks to maintain a constant heading. The neuronal substrates for the necessary interactions between compass neurons in the central complex, a prominent structure of the central brain, and circadian clocks are largely unknown. To begin to unravel these neural substrates, we performed 3D reconstructions of all neuropils of the monarch brain based on anti-synapsin labeling. Our work characterizes 21 well-defined neuropils (19 paired, 2 unpaired), as well as all synaptic regions between the more classically defined neuropils. We also studied the internal organization of all major neuropils on brain sections, using immunocytochemical stainings against synapsin, serotonin, and γ-aminobutyric acid. Special emphasis was placed on describing the neuroarchitecture of sun-compass-related brain regions and outlining their homologies to other migratory species. In addition to finding many general anatomical similarities to other insects, interspecies comparison also revealed several features that appear unique to the monarch brain. These distinctive features were especially apparent in the visual system and the mushroom body. Overall, we provide a comprehensive analysis of the brain anatomy of the monarch butterfly that will ultimately aid our understanding of the neuronal processes governing animal migration. PMID:22473804

  14. 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.

  15. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is......In contemporary consciousness studies the phenomenon of neural plasticity has received little attention despite the fact that neural plasticity is of still increased interest in neuroscience. We will, however, argue that neural plasticity could be of great importance to consciousness studies....... If consciousness is related to neural processes it seems, at least prima facie, that the ability of the neural structures to change should be reflected in a theory of this relationship "Neural plasticity" refers to the fact that the brain can change due to its own activity. The brain is not static but rather...

  16. 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.

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    Yoshio Sakurai

    2016-08-01

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

  19. 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. PMID:22010887

  20. 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.

  1. Neural dysregulation of peripheral insulin action and blood pressure by brain endoplasmic reticulum stress

    OpenAIRE

    Purkayastha, Sudarshana; Zhang, Hai; Zhang, Guo; Ahmed, Zaghloul; Wang, Yi; Cai, Dongsheng

    2011-01-01

    Chronic endoplasmic reticulum (ER) stress was recently revealed to affect hypothalamic neuroendocrine pathways that regulate feeding and body weight. However, it remains unexplored whether brain ER stress could use a neural route to rapidly cause the peripheral disorders that underlie the development of type 2 diabetes (T2D) and the metabolic syndrome. Using a pharmacologic model that delivered ER stress inducer thapsigargin into the brain, this study demonstrated that a short-term brain ER s...

  2. Neural, not gonadal, origin of brain sex differences in a gynandromorphic finch

    OpenAIRE

    Agate, Robert J.; Grisham, William; Wade, Juli; Mann, Suzanne; Wingfield, John; Schanen, Carolyn; Palotie, Aarno; Arnold, Arthur P.

    2003-01-01

    In mammals and birds, sex differences in brain function and disease are thought to derive exclusively from sex differences in gonadal hormone secretions. For example, testosterone in male mammals acts during fetal and neonatal life to cause masculine neural development. However, male and female brain cells also differ in genetic sex; thus, sex chromosome genes acting within cells could contribute to sex differences in cell function. We analyzed the sexual phenotype of the brain of a rare gyna...

  3. Taurine Induces Proliferation of Neural Stem Cells and Synapse Development in the Developing Mouse Brain

    OpenAIRE

    Mattu Chetana Shivaraj; Guillaume Marcy; Guoliang Low; Jae Ryun Ryu; Xianfeng Zhao; Rosales, Francisco J.; Goh, Eyleen L.K.

    2012-01-01

    Taurine is a sulfur-containing amino acid present in high concentrations in mammalian tissues. It has been implicated in several processes involving brain development and neurotransmission. However, the role of taurine in hippocampal neurogenesis during brain development is still unknown. Here we show that taurine regulates neural progenitor cell (NPC) proliferation in the dentate gyrus of the developing brain as well as in cultured early postnatal (P5) hippocampal progenitor cells and hippoc...

  4. 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.

  5. Tumourigenicity and Immunogenicity of Induced Neural Stem Cell Grafts Versus Induced Pluripotent Stem Cell Grafts in Syngeneic Mouse Brain

    Science.gov (United States)

    Gao, Mou; Yao, Hui; Dong, Qin; Zhang, Hongtian; Yang, Zhijun; Yang, Yang; Zhu, Jianwei; Xu, Minhui; Xu, Ruxiang

    2016-01-01

    Along with the development of stem cell-based therapies for central nervous system (CNS) disease, the safety of stem cell grafts in the CNS, such as induced pluripotent stem cells (iPSCs) and induced neural stem cells (iNSCs), should be of primary concern. To provide scientific basis for evaluating the safety of these stem cells, we determined their tumourigenicity and immunogenicity in syngeneic mouse brain. Both iPSCs and embryonic stem cells (ESCs) were able to form tumours in the mouse brain, leading to tissue destruction along with immune cell infiltration. In contrast, no evidence of tumour formation, brain injury or immune rejection was observed with iNSCs, neural stem cells (NSCs) or mesenchymal stem cells (MSCs). With the help of gene ontology (GO) enrichment analysis, we detected significantly elevated levels of chemokines in the brain tissue and serum of mice that developed tumours after ESC or iPSC transplantation. Moreover, we also investigated the interactions between chemokines and NF-κB signalling and found that NF-κB activation was positively correlated with the constantly rising levels of chemokines, and vice versa. In short, iNSC grafts, which lacked any resulting tumourigenicity or immunogenicity, are safer than iPSC grafts. PMID:27417157

  6. 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...

  7. The neural basis of regret and relief during a sequential risk-taking task.

    Science.gov (United States)

    Liu, Zhiyuan; Li, Lin; Zheng, Li; Hu, Zengxi; Roberts, Ian D; Guo, Xiuyan; Yang, Guang

    2016-07-01

    Regret and relief are associated with counterfactual thinking and are sensitive to various social contexts. In the present fMRI study, we investigated the neural basis for regret and relief and how social context (following vs. not following advice) modulates them by employing a sequential risk-taking task. Participants were asked to open a series of boxes consecutively until they decided to stop. Each box contained a reward (gold), except for one that contained an adverse stimulus (devil), which caused the participant to lose all the gold collected in that trial. Before each trial, participants received advice about when to stop, which they then chose to follow or not. Behaviorally, subjective regret and relief were primarily dependent on the number of missed chances and the trade-off between obtained gains and missed chances, respectively. Participants felt less regret when they chose not to follow the advice than when they did. At the neural level, striatum, vmPFC/mOFC, and vACC activations were associated with greater relief. Meanwhile, dmPFC and left superior temporal gyrus were associated with greater regret. Additionally, dACC showed stronger activation in the Not-Follow context than the Follow context. PMID:27102420

  8. Artificial neural network modeling of fixed bed biosorption using radial basis approach

    Science.gov (United States)

    Saha, Dipendu; Bhowal, Avijit; Datta, Siddhartha

    2010-04-01

    In modern day scenario, biosorption is a cost effective separation technology for the removal of various pollutants from wastewater and waste streams from various process industries. The difficulties associated in rigorous mathematical modeling of a fixed bed bio-adsorbing systems due to the complexities of the process often makes the development of pure black-box artificial neural network (ANN) models particularly useful in this field. In this work, radial basis function network has been employed as ANN to model the breakthrough curves in fixed bed biosorption. The prediction has been compared to the experimental breakthrough curves of Cadmium, Lanthanum and a dye available in the literature. Results show that this network gives fairly accurate representation of the actual breakthrough curves. The results obtained from ANN modeling approach shows the better agreement between experimental and predicted breakthrough curves as the error for all these situations are within 6%.

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

    Institute of Scientific and Technical Information of China (English)

    YAO,Xiao-Jun(姚小军); LIU,Man-Cang(刘满仓); ZHANG,Xiao-Yun(张晓昀); ZHANG,Rui-Sheng(张瑞生); HU,Zhi-De(胡之德); FAN,Bo-Tao(范波涛)

    2002-01-01

    Quantitative structure-property relatioonship (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 structure alone are used to describe the molecular structures. A subset of the calculated 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 urilized to construct the linear and non-linear correlation model,respectively. The optimal QSPR model developedis based on a 7-17-1 RBFNNs architecture using seven calculated molecular descriptors. The root mean square errorsin predictions for the training, predicting and overall data sets are 0.284, 0.327 and 0.291 log P units, respectively.

  10. 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.

  11. 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.).

  12. 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.

  13. On-line Transient Stability Assessment through Generator Rotor Angles Prediction Using Radial Basis Function Neural Network

    OpenAIRE

    Shahbaz A. Siddiqui; Kusum Verma; K. R. Niazi; Manoj Fozdar

    2014-01-01

    On-line Transient Stability Assessment (TSA) is challenging task due to the large number of variables involved and continuously varying operating conditions. This study proposes an on-line transient stability assessment methodology based on the predicted values of generator rotor angles under varying operating conditions for predefined contingency set through Radial Basis Function Neural Network (RBFNN). The real and reactive power loads are taken as input features for training of the neural ...

  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. 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.

  16. 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…

  17. Bi-parental care contributes to sexually dimorphic neural cell genesis in the adult mammalian brain.

    Directory of Open Access Journals (Sweden)

    Gloria K Mak

    Full Text Available Early life events can modulate brain development to produce persistent physiological and behavioural phenotypes that are transmissible across generations. However, whether neural precursor cells are altered by early life events, to produce persistent and transmissible behavioural changes, is unknown. Here, we show that bi-parental care, in early life, increases neural cell genesis in the adult rodent brain in a sexually dimorphic manner. Bi-parentally raised male mice display enhanced adult dentate gyrus neurogenesis, which improves hippocampal neurogenesis-dependent learning and memory. Female mice display enhanced adult white matter oligodendrocyte production, which increases proficiency in bilateral motor coordination and preference for social investigation. Surprisingly, single parent-raised male and female offspring, whose fathers and mothers received bi-parental care, respectively, display a similar enhancement in adult neural cell genesis and phenotypic behaviour. Therefore, neural plasticity and behavioural effects due to bi-parental care persist throughout life and are transmitted to the next generation.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    Michael L Hendrickson

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

  20. Using brain-computer interfaces to induce neural plasticity and restore function

    Science.gov (United States)

    Grosse-Wentrup, Moritz; Mattia, Donatella; Oweiss, Karim

    2011-04-01

    Analyzing neural signals and providing feedback in realtime is one of the core characteristics of a brain-computer interface (BCI). As this feature may be employed to induce neural plasticity, utilizing BCI technology for therapeutic purposes is increasingly gaining popularity in the BCI community. In this paper, we discuss the state-of-the-art of research on this topic, address the principles of and challenges in inducing neural plasticity by means of a BCI, and delineate the problems of study design and outcome evaluation arising in this context. We conclude with a list of open questions and recommendations for future research in this field.

  1. 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.

  2. 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.

  3. 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.

  4. 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…

  5. 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…

  6. 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…

  7. 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…

  8. 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.

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

    OpenAIRE

    LillianMay; KristaByers-Heinlein; JuditGervain

    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. T...

  10. 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...

  11. 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

    2014-01-01

    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. PMID:25237902

  12. Radial Basis Function Based Neural Network for Motion Detection in Dynamic Scenes.

    Science.gov (United States)

    Huang, Shih-Chia; Do, Ben-Hsiang

    2014-01-01

    Motion detection, the process which segments moving objects in video streams, is the first critical process and plays an important role in video surveillance systems. Dynamic scenes are commonly encountered in both indoor and outdoor situations and contain objects such as swaying trees, spouting fountains, rippling water, moving curtains, and so on. However, complete and accurate motion detection in dynamic scenes is often a challenging task. This paper presents a novel motion detection approach based on radial basis function artificial neural networks to accurately detect moving objects not only in dynamic scenes but also in static scenes. The proposed method involves two important modules: a multibackground generation module and a moving object detection module. The multibackground generation module effectively generates a flexible probabilistic model through an unsupervised learning process to fulfill the property of either dynamic background or static background. Next, the moving object detection module achieves complete and accurate detection of moving objects by only processing blocks that are highly likely to contain moving objects. This is accomplished by two procedures: the block alarm procedure and the object extraction procedure. The detection results of our method were evaluated by qualitative and quantitative comparisons with other state-of-the-art methods based on a wide range of natural video sequences. The overall results show that the proposed method substantially outperforms existing methods with Similarity and F1 accuracy rates of 69.37% and 65.50%, respectively. PMID:24108721

  13. 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.

  14. 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.

  15. Design and Modeling of RF Power Amplifiers with Radial Basis Function Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ali Reza Zirak

    2016-06-01

    Full Text Available A radial basis function (RBF artificial neural network model for a designed high efficiency radio frequency class-F power amplifier (PA is presented in this paper. The presented amplifier is designed at 1.8 GHz operating frequency with 12 dB of gain and 36 dBm of 1dB output compression point. The obtained power added efficiency (PAE for the presented PA is 76% under 26 dBm input power. The proposed RBF model uses input and DC power of the PA as inputs variables and considers output power as the output variable. The presented RBF network models the designed class-F PA as a block, which could be applied in circuit design. The presented model could be used to model any RF power amplifier. The obtained results show a good agreement between real data and predicted values by RBF model. The results clearly show that the presented RBF network is more precise than multilayer perceptron (MLP model. According to the results, better than 84% and 92% improvement is achieved in MAE and RMSE, respectively.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. Brain Allometry and Neural Plasticity in the Bumblebee Bombus occidentalis

    OpenAIRE

    Riveros, Andre J.; Gronenberg, Wulfila

    2010-01-01

    Brain plasticity is a common phenomenon across animals and in many cases it is associated with behavioral transitions. In social insects, such as bees, wasps and ants, plasticity in a particular brain compartment involved in multisensory integration (the mushroom body) has been associated with transitions between tasks differing in cognitive demands. However, in most of these cases, transitions between tasks are age-related, requiring the experimental manipulation of the age structure in the ...

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

    Science.gov (United States)

    Kleim, Jeffrey A.; Jones, Theresa A.

    2008-01-01

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

  2. Radial Basis Function-Sparse Partial Least Squares for Application to Brain Imaging Data

    Directory of Open Access Journals (Sweden)

    Hisako Yoshida

    2013-01-01

    Full Text Available Magnetic resonance imaging (MRI data is an invaluable tool in brain morphology research. Here, we propose a novel statistical method for investigating the relationship between clinical characteristics and brain morphology based on three-dimensional MRI data via radial basis function-sparse partial least squares (RBF-sPLS. Our data consisted of MRI image intensities for multimillion voxels in a 3D array along with 73 clinical variables. This dataset represents a suitable application of RBF-sPLS because of a potential correlation among voxels as well as among clinical characteristics. Additionally, this method can simultaneously select both effective brain regions and clinical characteristics based on sparse modeling. This is in contrast to existing methods, which consider prespecified brain regions because of the computational difficulties involved in processing high-dimensional data. RBF-sPLS employs dimensionality reduction in order to overcome this obstacle. We have applied RBF-sPLS to a real dataset composed of 102 chronic kidney disease patients, while a comparison study used a simulated dataset. RBF-sPLS identified two brain regions of interest from our patient data: the temporal lobe and the occipital lobe, which are associated with aging and anemia, respectively. Our simulation study suggested that such brain regions are extracted with excellent accuracy using our method.

  3. 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.

  4. 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.

  5. Traumatic brain injury: a review of characteristics, molecular basis and management.

    Science.gov (United States)

    Wang, Ke; Cui, Daming; Gao, Liang

    2016-01-01

    Traumatic brain injury (TBI) is a critical cause of hospitalization, disability, and death worldwide. The global increase in the incidence of TBI poses a significant socioeconomic burden. Guidelines for the management of acute TBI mostly pertain to emergency treatment. Comprehensive gene expression analysis is currently available for several animal models of TBI, along with enhanced understanding of the molecular mechanisms activated during injury and subsequent recovery. The current review focuses on the characteristics, molecular basis and management of TBI. PMID:27100477

  6. Unsupervised Neural Techniques Applied to MR Brain Image Segmentation

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    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.

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

    OpenAIRE

    Voytek, Bradley; Robert T Knight

    2015-01-01

    Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this paper we begin from the perspective that successful interregional communication relies upon the transient synchronization be...

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

    Science.gov (United States)

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

    2015-09-01

    In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate. PMID:26163042

  9. Brain Computer Interface. Comparison of Neural Networks Classifiers.

    OpenAIRE

    Martínez Pérez, Jose Luis; Barrientos Cruz, Antonio

    2008-01-01

    Brain Computer Interface is an emerging technology that allows new output paths to communicate the user’s intentions without use of normal output ways, such as muscles or nerves (Wolpaw, J. R.; et al., 2002).In order to obtain its objective BCI devices shall make use of classifier which translate the inputs provided by user’s brain signal to commands for external devices. The primary uses of this technology will benefit persons with some kind blocking disease as for example: ALS, brainstem st...

  10. 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.

  11. 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

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    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

  12. 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.

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

    OpenAIRE

    Sebastian Ludyga; Thomas Gronwald; Kuno Hottenrott

    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 (...

  14. 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.

  15. 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.

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

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    Kim Woo-Young

    2008-01-01

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

  17. 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.

  18. Neural basis of irony comprehension in children with autism: the role of prosody and context

    OpenAIRE

    Wang, A. Ting; Lee, Susan S.; Sigman, Marian; Dapretto, Mirella

    2006-01-01

    While individuals with autism spectrum disorders (ASD) are typically impaired in interpreting the communicative intent of others, little is known about the neural bases of higher-level pragmatic impairments. Here, we used functional MRI (fMRI) to examine the neural circuitry underlying deficits in understanding irony in high-functioning children with ASD. Participants listened to short scenarios and decided whether the speaker was sincere or ironic. Three types of scenarios were used in which...

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

    Science.gov (United States)

    Armenta Salas, Michelle; Helms Tillery, Stephen I

    2016-01-01

    The neural mechanisms that take place during learning and adaptation can be directly probed with brain-machine interfaces (BMIs). We developed a BMI controlled paradigm that enabled us to enforce learning by introducing perturbations which changed the relationship between neural activity and the BMI's output. We introduced a uniform perturbation to the system, through a visuomotor rotation (VMR), and a non-uniform perturbation, through a decorrelation task. The controller in the VMR was essentially unchanged, but produced an output rotated at 30° from the neurally specified output. The controller in the decorrelation trials decoupled the activity of neurons that were highly correlated in the BMI task by selectively forcing the preferred directions of these cell pairs to be orthogonal. We report that movement errors were larger in the decorrelation task, and subjects needed more trials to restore performance back to baseline. During learning, we measured decreasing trends in preferred direction changes and cross-correlation coefficients regardless of task type. Conversely, final adaptations in neural tunings were dependent on the type controller used (VMR or decorrelation). These results hint to the similar process the neural population might engage while adapting to new tasks, and how, through a global process, the neural system can arrive to individual solutions. PMID:27601981

  20. 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.

  1. 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. PMID:26977450

  2. 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.

  3. 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.

  4. 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.

  5. Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganization.

    Science.gov (United States)

    Pohlmeyer, Eric A; Mahmoudi, Babak; Geng, Shijia; Prins, Noeline W; Sanchez, Justin C

    2014-01-01

    Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder's neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled. PMID:24498055

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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. PMID:27147955

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. On-line Transient Stability Assessment through Generator Rotor Angles Prediction Using Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Shahbaz A. Siddiqui

    2014-10-01

    Full Text Available On-line Transient Stability Assessment (TSA is challenging task due to the large number of variables involved and continuously varying operating conditions. This study proposes an on-line transient stability assessment methodology based on the predicted values of generator rotor angles under varying operating conditions for predefined contingency set through Radial Basis Function Neural Network (RBFNN. The real and reactive power loads are taken as input features for training of the neural network. Principal Component Analysis (PCA is used for dimensionality reduction of the input data set to select informative features. The proposed method is tested on IEEE-39 bus test system and the results obtained for transient stability assessment through predicted rotor angles are promising.

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

    Science.gov (United States)

    Meghabghab, George

    2001-01-01

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

  18. Partially flexible MEMS neural probe composed of polyimide and sucrose gel for reducing brain damage during and after implantation

    International Nuclear Information System (INIS)

    This paper presents a flexible microelectromechanical systems (MEMS) neural probe that minimizes neuron damage and immune response, suitable for chronic recording applications. MEMS neural probes with various features such as high electrode densities have been actively investigated for neuron stimulation and recording to study brain functions. However, successful recording of neural signals in chronic application using rigid silicon probes still remains challenging because of cell death and macrophages accumulated around the electrodes over time from continuous brain movement. Thus, in this paper, we propose a new flexible MEMS neural probe that consists of two segments: a polyimide-based, flexible segment for connection and a rigid segment composed of thin silicon for insertion. While the flexible connection segment is designed to reduce the long-term chronic neuron damage, the thin insertion segment is designed to minimize the brain damage during the insertion process. The proposed flexible neural probe was successfully fabricated using the MEMS process on a silicon on insulator wafer. For a successful insertion, a biodegradable sucrose gel is coated on the flexible segment to temporarily increase the probe stiffness to prevent buckling. After the insertion, the sucrose gel dissolves inside the brain exposing the polyimide probe. By performing an insertion test, we confirm that the flexible probe has enough stiffness. In addition, by monitoring immune responses and brain histology, we successfully demonstrate that the proposed flexible neural probe incurs fivefold less neural damage than that incurred by a conventional silicon neural probe. Therefore, the presented flexible neural probe is a promising candidate for recording stable neural signals for long-time chronic applications. (paper)

  19. 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.

  20. In Vivo Targeted Magnetic Resonance Imaging of Endogenous Neural Stem Cells in the Adult Rodent Brain

    Directory of Open Access Journals (Sweden)

    Xiao-Mei Zhong

    2015-01-01

    Full Text Available Neural stem cells in the adult mammalian brain have a significant level of neurogenesis plasticity. In vivo monitoring of adult endogenous NSCs would be of great benefit to the understanding of the neurogenesis plasticity under normal and pathological conditions. Here we show the feasibility of in vivo targeted MR imaging of endogenous NSCs in adult mouse brain by intraventricular delivery of monoclonal anti-CD15 antibody conjugated superparamagnetic iron oxide nanoparticles. After intraventricular administration of these nanoparticles, the subpopulation of NSCs in the anterior subventricular zone and the beginning of the rostral migratory stream could be in situ labeled and were in vivo visualized with 7.0-T MR imaging during a period from 1 day to 7 days after the injection. Histology confirmed that the injected targeted nanoparticles were specifically bound to CD15 positive cells and their surrounding extracellular matrix. Our results suggest that in vivo targeted MR imaging of endogenous neural stem cells in adult rodent brain could be achieved by using anti-CD15-SPIONs as the molecular probe; and this targeting imaging strategy has the advantage of a rapid in vivo monitoring of the subpopulation of endogenous NSCs in adult brains.

  1. Neural, cognitive, and neuroimaging markers of the suicidal brain

    Directory of Open Access Journals (Sweden)

    Sobanski T

    2015-05-01

    Full Text Available Thomas Sobanski,1 Karl-Jürgen Bär,2 Gerd Wagner2 1Department of Psychiatry, Psychotherapy and Psychosomatic Medicine, Thüringen-Kliniken "Georgius Agricola" GmbH, Saalfeld, Germany; 2Department of Psychiatry and Psychotherapy, Psychiatric Brain and Body Research Group Jena, Jena University Hospital, Jena, GermanyAbstract: Suicidal behavior (SB is characterized by the occurrence of suicide attempts with substantial intent to die. SB is a major health problem worldwide. In the great majority of cases, SB occurs in patients suffering from psychiatric disorders, mainly from affective disorders or schizophrenia. Despite this high association, there is growing evidence from genetic studies that SB might represent a psychiatric condition on its own. This review provides an overview of the most significant neurobiological and neurocognitive findings in SB. We provide evidence for specific dysfunctions within the serotonergic system, for distinct morphological abnormalities in the gray and white matter composition as well as for neurofunctional alterations in the fronto-striatal network. Additionally, the putative role of impulsivity and hopelessness as trait-like risk factors for SB is outlined. Both the personality traits are associated with altered prefrontal cortex function and deficits in cognitive and affective control similar to the findings in SB. Given the difficulties of clinical risk assessment, there is a need to identify specific markers that can predict SB more reliably. Some recent neurocognitive and functional/structural neuroimaging findings might be appropriate to use as SB indicators in the close future.Keywords: suicidal behavior, biological markers, serotonin, hopelessness, impulsivity, major depressive disorder, fMRI, PET, SPECT

  2. 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.

  3. The Racer's Brain - How Domain Expertise is Reflected in the Neural Substrates of Driving.

    Science.gov (United States)

    Lappi, Otto

    2015-01-01

    A fundamental question in human brain plasticity is how sensory, motor, and cognitive functions adapt in the process of skill acquisition extended over a period of many years. Recently, there has emerged a growing interest in cognitive neuroscience on studying the functional and structural differences in the brains of elite athletes. Elite performance in sports, music, or the arts, allows us to observe sensorimotor and cognitive performance at the limits of human capability. In this mini-review, we look at driving expertise. The emerging brain imaging literature on the neural substrates of real and simulated driving is reviewed (for the first time), and used as the context for interpreting recent findings on the differences between racing drivers and non-athlete controls. Also the cognitive psychology and cognitive neuroscience of expertise are discussed. PMID:26635586

  4. Patterns of theta oscillation reflect the neural basis of individual differences in epistemic motivation.

    Science.gov (United States)

    Mussel, Patrick; Ulrich, Natalie; Allen, John J B; Osinsky, Roman; Hewig, Johannes

    2016-01-01

    Theta oscillations in the EEG have been shown to reflect ongoing cognitive processes related to mental effort. Here, we show that the pattern of theta oscillation in response to varying cognitive demands reflects stable individual differences in the personality trait epistemic motivation: Individuals with high levels of epistemic motivation recruit relatively more cognitive resources in response to situations possessing high, compared to low, cognitive demand; individuals with low levels do not show such a specific response. Our results provide direct evidence for the theory of the construct need for cognition and add to our understanding of the neural processes underlying theta oscillations. More generally, we provide an explanation how individual differences in personality traits might be represented on a neural level. PMID:27380648

  5. Neural plasticity in human brain connectivity: the effects of long term deep brain stimulation of the subthalamic nucleus in Parkinson's disease.

    Directory of Open Access Journals (Sweden)

    Tim J van Hartevelt

    Full Text Available BACKGROUND: Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson's Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. RESULTS: We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson's Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson's Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. CONCLUSIONS: The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain

  6. Tracking Neural Modulation Depth by Dual Sequential Monte Carlo Estimation on Point Processes for Brain-Machine Interfaces.

    Science.gov (United States)

    Wang, Yiwen; She, Xiwei; Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Zhang, Shaomin; Zheng, Xiaoxiang; Principe, Jose

    2016-08-01

    Classic brain-machine interface (BMI) approaches decode neural signals from the brain responsible for achieving specific motor movements, which subsequently command prosthetic devices. Brain activities adaptively change during the control of the neuroprosthesis in BMIs, where the alteration of the preferred direction and the modulation of the gain depth are observed. The static neural tuning models have been limited by fixed codes, resulting in a decay of decoding performance over the course of the movement and subsequent instability in motor performance. To achieve stable performance, we propose a dual sequential Monte Carlo adaptive point process method, which models and decodes the gradually changing modulation depth of individual neuron over the course of a movement. We use multichannel neural spike trains from the primary motor cortex of a monkey trained to perform a target pursuit task using a joystick. Our results show that our computational approach successfully tracks the neural modulation depth over time with better goodness-of-fit than classic static neural tuning models, resulting in smaller errors between the true kinematics and the estimations in both simulated and real data. Our novel decoding approach suggests that the brain may employ such strategies to achieve stable motor output, i.e., plastic neural tuning is a feature of neural systems. BMI users may benefit from this adaptive algorithm to achieve more complex and controlled movement outcomes. PMID:26584486

  7. Brain–immune interactions and the neural basis of disease-avoidant ingestive behaviour

    OpenAIRE

    Pacheco-López, Gustavo; Bermúdez-Rattoni, Federico

    2011-01-01

    Neuro–immune interactions are widely manifested in animal physiology. Since immunity competes for energy with other physiological functions, it is subject to a circadian trade-off between other energy-demanding processes, such as neural activity, locomotion and thermoregulation. When immunity is challenged, this trade-off is tilted to an adaptive energy protecting and reallocation strategy that is identified as ‘sickness behaviour’. We review diverse disease-avoidant behaviours in the context...

  8. 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.

  9. 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.

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

    Science.gov (United States)

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

    2015-10-01

    Gestures play an important role in face-to-face communication and have been increasingly studied via functional magnetic resonance imaging. Although a large amount of data has been provided to describe the neural substrates of gesture comprehension, these findings have never been quantitatively summarized and the conclusion is still unclear. This activation likelihood estimation meta-analysis investigated the brain networks underpinning gesture comprehension while considering the impact of gesture type (co-speech gestures vs. speech-independent gestures) and task demand (implicit vs. explicit) on the brain activation of gesture comprehension. The meta-analysis of 31 papers showed that as hand actions, gestures involve a perceptual-motor network important for action recognition. As meaningful symbols, gestures involve a semantic network for conceptual processing. Finally, during face-to-face interactions, gestures involve a network for social emotive processes. Our finding also indicated that gesture type and task demand influence the involvement of the brain networks during gesture comprehension. The results highlight the complexity of gesture comprehension, and suggest that future research is necessary to clarify the dynamic interactions among these networks. PMID:26271719

  11. 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.

  12. 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

  13. 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:…

  14. The brain decade in debate: II. Panic or anxiety? From animal models to a neurobiological basis

    Directory of Open Access Journals (Sweden)

    R. Andreatini

    2001-02-01

    Full Text Available This article is a transcription of an electronic symposium sponsored by the Brazilian Society of Neuroscience and Behavior (SBNeC. Invited researchers from the European Union, North America and Brazil discussed two issues on anxiety, namely whether panic is a very intense anxiety or something else, and what aspects of clinical anxiety are reproduced by animal models. Concerning the first issue, most participants agreed that generalized anxiety and panic disorder are different on the basis of clinical manifestations, drug response and animal models. Also, underlying brain structures, neurotransmitter modulation and hormonal changes seem to involve important differences. It is also common knowledge that existing animal models generate different types of fear/anxiety. A challenge for future research is to establish a good correlation between animal models and nosological classification.

  15. 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

  16. 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. PMID:22997054

  17. 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.

  18. 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.

  19. 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. PMID:26595929

  20. Brain-Controlled Neuromuscular Stimulation to Drive Neural Plasticity and Functional Recovery

    Science.gov (United States)

    Ethier, C.; Gallego, J.A.; Miller, L.E.

    2015-01-01

    There is mounting evidence that appropriately timed neuromuscular stimulation can induce neural plasticity and generate functional recovery from motor disorders. This review addresses the idea that coordinating stimulation with a patient’s voluntary effort might further enhance neurorehabilitation. Studies in cell cultures and behaving animals have delineated the rules underlying neural plasticity when single neurons are used as triggers. However, the rules governing more complex stimuli and larger networks are less well understood. We argue that functional recovery might be optimized if stimulation were modulated by a brain machine interface, to matched the details of the patient’s voluntary intent. The potential of this novel approach highlights the need for a better understanding of the complex rules underlying this form of plasticity. PMID:25827275

  1. Shared neural basis of social and non-social reward deficits in chronic cocaine users.

    Science.gov (United States)

    Tobler, Philippe N; Preller, Katrin H; Campbell-Meiklejohn, Daniel K; Kirschner, Matthias; Kraehenmann, Rainer; Stämpfli, Philipp; Herdener, Marcus; Seifritz, Erich; Quednow, Boris B

    2016-06-01

    Changed reward functions have been proposed as a core feature of stimulant addiction, typically observed as reduced neural responses to non-drug-related rewards. However, it was unclear yet how specific this deficit is for different types of non-drug rewards arising from social and non-social reinforcements. We used functional neuroimaging in cocaine users to investigate explicit social reward as modeled by agreement of music preferences with music experts. In addition, we investigated non-social reward as modeled by winning desired music pieces. The study included 17 chronic cocaine users and 17 matched stimulant-naive healthy controls. Cocaine users, compared with controls, showed blunted neural responses to both social and non-social reward. Activation differences were located in the ventromedial prefrontal cortex overlapping for both reward types and, thus, suggesting a non-specific deficit in the processing of non-drug rewards. Interestingly, in the posterior lateral orbitofrontal cortex, social reward responses of cocaine users decreased with the degree to which they were influenced by social feedback from the experts, a response pattern that was opposite to that observed in healthy controls. The present results suggest that cocaine users likely suffer from a generalized impairment in value representation as well as from an aberrant processing of social feedback. PMID:26969866

  2. 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.

  3. 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.

  4. 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

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

    Directory of Open Access Journals (Sweden)

    Anna-Lena Hallmann

    2016-05-01

    Full Text Available Reprogramming technology enables the production of neural progenitor cells (NPCs from somatic cells by direct transdifferentiation. However, little is known on how neural programs in these induced neural stem cells (iNSCs differ from those of alternative stem cell populations in vitro and in vivo. Here, we performed transcriptome analyses on murine iNSCs in comparison to brain-derived neural stem cells (NSCs and pluripotent stem cell-derived NPCs, which revealed distinct global, neural, metabolic and cell cycle-associated marks in these populations. iNSCs carried a hindbrain/posterior cell identity, which could be shifted towards caudal, partially to rostral but not towards ventral fates in vitro. iNSCs survived after transplantation into the rodent brain and exhibited in vivo-characteristics, neural and metabolic programs similar to transplanted NSCs. However, iNSCs vastly retained caudal identities demonstrating cell-autonomy of regional programs in vivo. These data could have significant implications for a variety of in vitro- and in vivo-applications using iNSCs.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. Defining the neural basis of appetite and obesity: from genes to behaviour.

    Science.gov (United States)

    Farooqi, I Sadaf

    2014-06-01

    Obesity represents one of the biggest public health challenges facing us today. Urbanisation, sedentary lifestyles and the availability of inexpensive, highly palatable foods have promoted the increasing prevalence of obesity over the past 30 years. However, some people gain weight more easily than others, and there is strong evidence that, within a given environment, this variance in body weight is influenced by genetic factors. This article discusses how genetic studies have contributed to our understanding of the mechanisms involved in the regulation of body weight. We now understand that weight is regulated by neural mechanisms that regulate appetite and energy expenditure and that disruption of these pathways can result in severe obesity in some patients. These studies provide a framework for investigating patients and ultimately may guide the development of more rational, targeted therapies for genetically susceptible individuals with severe obesity. PMID:24889574

  11. Activating Endogenous Neural Precursor Cells Using Metformin Leads to Neural Repair and Functional Recovery in a Model of Childhood Brain Injury

    Directory of Open Access Journals (Sweden)

    Parvati Dadwal

    2015-08-01

    Full Text Available The development of cell replacement strategies to repair the injured brain has gained considerable attention, with a particular interest in mobilizing endogenous neural stem and progenitor cells (known as neural precursor cells [NPCs] to promote brain repair. Recent work demonstrated metformin, a drug used to manage type II diabetes, promotes neurogenesis. We sought to determine its role in neural repair following brain injury. We find that metformin administration activates endogenous NPCs, expanding the size of the NPC pool and promoting NPC migration and differentiation in the injured neonatal brain in a hypoxia-ischemia (H/I injury model. Importantly, metformin treatment following H/I restores sensory-motor function. Lineage tracking reveals that metformin treatment following H/I causes an increase in the absolute number of subependyma-derived NPCs relative to untreated H/I controls in areas associated with sensory-motor function. Hence, activation of endogenous NPCs is a promising target for therapeutic intervention in childhood brain injury models.

  12. The Drosophila neural lineages: a model system to study brain development and circuitry.

    Science.gov (United States)

    Spindler, Shana R; Hartenstein, Volker

    2010-06-01

    In Drosophila, neurons of the central nervous system are grouped into units called lineages. Each lineage contains cells derived from a single neuroblast. Due to its clonal nature, the Drosophila brain is a valuable model system to study neuron development and circuit formation. To better understand the mechanisms underlying brain development, genetic manipulation tools can be utilized within lineages to visualize, knock down, or over-express proteins. Here, we will introduce the formation and development of lineages, discuss how one can utilize this model system, offer a comprehensive list of known lineages and their respective markers, and then briefly review studies that have utilized Drosophila neural lineages with a look at how this model system can benefit future endeavors. PMID:20306203

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. The neural basis of the interaction between theory of mind and moral judgment

    OpenAIRE

    Young, Liane; Cushman, Fiery; Hauser, Marc; Saxe, Rebecca

    2007-01-01

    Is the basis of criminality an act that causes harm, or an act undertaken with the belief that one will cause harm? The present study takes a cognitive neuroscience approach to investigating how information about an agent's beliefs and an action's consequences contribute to moral judgment. We build on prior developmental evidence showing that these factors contribute differentially to the young child's moral judgments coupled with neurobiological evidence suggesting a role for the right tempo...

  18. Adaptive movable neural interfaces for monitoring single neurons in the brain

    Directory of Open Access Journals (Sweden)

    Jit eMuthuswamy

    2011-09-01

    Full Text Available Implantable microelectrodes that are currently used to monitor neuronal activity in the brain in vivo have serious limitations both in acute and chronic experiments. Movable microelectrodes that adapt their position in the brain to maximize the quality of neuronal recording have been suggested and tried as a potential solution to overcome the challenges with the current fixed implantable microelectrodes. While the results so far suggest that movable microelectrodes improve the quality and stability of neuronal recordings from the brain in vivo, the bulky nature of the technologies involved in making these movable microelectrodes limits the throughput (number of neurons that can be recorded from at any given time of these implantable devices. Emerging technologies involving the use of microscale motors and electrodes promise to overcome this limitation. This review summarizes some of the most recent efforts in developing movable neural interfaces using microscale technologies that adapt their position in response to changes in the quality of the neuronal recordings. Key gaps in our understanding of the brain-electrode interface are highlighted. Emerging discoveries in these areas will lead to success in the development of a reliable and stable interface with single neurons that will impact basic neurophysiological studies and emerging cortical prosthetic technologies.

  19. Autonomous control for mechanically stable navigation of microscale implants in brain tissue to record neural activity.

    Science.gov (United States)

    Anand, Sindhu; Kumar, Swathy Sampath; Muthuswamy, Jit

    2016-08-01

    Emerging neural prosthetics require precise positional tuning and stable interfaces with single neurons for optimal function over a lifetime. In this study, we report an autonomous control to precisely navigate microscale electrodes in soft, viscoelastic brain tissue without visual feedback. The autonomous control optimizes signal-to-noise ratio (SNR) of single neuronal recordings in viscoelastic brain tissue while maintaining quasi-static mechanical stress conditions to improve stability of the implant-tissue interface. Force-displacement curves from microelectrodes in in vivo rodent experiments are used to estimate viscoelastic parameters of the brain. Using a combination of computational models and experiments, we determined an optimal movement for the microelectrodes with bidirectional displacements of 3:2 ratio between forward and backward displacements and a inter-movement interval of 40 s for minimizing mechanical stress in the surrounding brain tissue. A regulator with the above optimal bidirectional motion for the microelectrodes in in vivo experiments resulted in significant reduction in the number of microelectrode movements (0.23 movements/min) and longer periods of stable SNR (53 % of the time) compared to a regulator using a conventional linear, unidirectional microelectrode movement (with 1.48 movements/min and stable SNR 23 % of the time). PMID:27457752

  20. Neural signatures of third-party punishment: evidence from penetrating traumatic brain injury.

    Science.gov (United States)

    Glass, Leila; Moody, Lara; Grafman, Jordan; Krueger, Frank

    2016-02-01

    The ability to survive within a cooperative society depends on impartial third-party punishment (TPP) of social norm violations. Two cognitive mechanisms have been postulated as necessary for the successful completion of TPP: evaluation of legal responsibility and selection of a suitable punishment given the magnitude of the crime. Converging neuroimaging research suggests two supporting domain-general networks; a mentalizing network for evaluation of legal responsibility and a central-executive network for determination of punishment. A whole-brain voxel-based lesion-symptom mapping approach was used in conjunction with a rank-order TPP task to identify brain regions necessary for TPP in a large sample of patients with penetrating traumatic brain injury. Patients who demonstrated atypical TPP had specific lesions in core regions of the mentalizing (dorsomedial prefrontal cortex [PFC], ventromedial PFC) and central-executive (bilateral dorsolateral PFC, right intraparietal sulcus) networks. Altruism and executive functioning (concept formation skills) were significant predictors of TPP: altruism was uniquely associated with TPP in patients with lesions in right dorsolateral PFC and executive functioning was uniquely associated with TPP in individuals with lesions in left PFC. Our findings contribute to the extant literature to support underlying neural networks associated with TPP, with specific brain-behavior causal relationships confirming recent functional neuroimaging research.

  1. 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. PMID:26276809

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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. PMID:26819767

  7. 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.

  8. 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.

  9. 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. PMID:26672048

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

    Science.gov (United States)

    D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  16. 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. PMID:25797834

  17. 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

    2016-01-01

    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. PMID:27669249

  18. 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.

  19. 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.

  20. A Computationally Inexpensive Optimal Guidance via Radial-Basis-Function Neural Network for Autonomous Soft Landing on Asteroids.

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    Full Text Available Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP. Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm.

  1. 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.

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

    OpenAIRE

    Kathrin Hemmer; Mingyue Zhang; Thea van Wüllen; Marna Sakalem; Natalia Tapia; Aidos Baumuratov; Christian Kaltschmidt; Barbara Kaltschmidt; Hans R. Schöler; Weiqi Zhang; Jens C. Schwamborn

    2014-01-01

    Summary 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 ...

  3. Performance enhancement at the cost of potential brain plasticity: neural ramifications of nootropic drugs in the healthy developing brain

    Science.gov (United States)

    Urban, Kimberly R.; Gao, Wen-Jun

    2014-01-01

    Cognitive enhancement is perhaps one of the most intriguing and controversial topics in neuroscience today. Currently, the main classes of drugs used as potential cognitive enhancers include psychostimulants (methylphenidate (MPH), amphetamine), but wakefulness-promoting agents (modafinil) and glutamate activators (ampakine) are also frequently used. Pharmacologically, substances that enhance the components of the memory/learning circuits—dopamine, glutamate (neuronal excitation), and/or norepinephrine—stand to improve brain function in healthy individuals beyond their baseline functioning. In particular, non-medical use of prescription stimulants such as MPH and illicit use of psychostimulants for cognitive enhancement have seen a recent rise among teens and young adults in schools and college campuses. However, this enhancement likely comes with a neuronal, as well as ethical, cost. Altering glutamate function via the use of psychostimulants may impair behavioral flexibility, leading to the development and/or potentiation of addictive behaviors. Furthermore, dopamine and norepinephrine do not display linear effects; instead, their modulation of cognitive and neuronal function maps on an inverted-U curve. Healthy individuals run the risk of pushing themselves beyond optimal levels into hyperdopaminergic and hypernoradrenergic states, thus vitiating the very behaviors they are striving to improve. Finally, recent studies have begun to highlight potential damaging effects of stimulant exposure in healthy juveniles. This review explains how the main classes of cognitive enhancing drugs affect the learning and memory circuits, and highlights the potential risks and concerns in healthy individuals, particularly juveniles and adolescents. We emphasize the performance enhancement at the potential cost of brain plasticity that is associated with the neural ramifications of nootropic drugs in the healthy developing brain. PMID:24860437

  4. Performance enhancement at the cost of potential brain plasticity: neural ramifications of nootropic drugs in the healthy developing brain.

    Science.gov (United States)

    Urban, Kimberly R; Gao, Wen-Jun

    2014-01-01

    Cognitive enhancement is perhaps one of the most intriguing and controversial topics in neuroscience today. Currently, the main classes of drugs used as potential cognitive enhancers include psychostimulants (methylphenidate (MPH), amphetamine), but wakefulness-promoting agents (modafinil) and glutamate activators (ampakine) are also frequently used. Pharmacologically, substances that enhance the components of the memory/learning circuits-dopamine, glutamate (neuronal excitation), and/or norepinephrine-stand to improve brain function in healthy individuals beyond their baseline functioning. In particular, non-medical use of prescription stimulants such as MPH and illicit use of psychostimulants for cognitive enhancement have seen a recent rise among teens and young adults in schools and college campuses. However, this enhancement likely comes with a neuronal, as well as ethical, cost. Altering glutamate function via the use of psychostimulants may impair behavioral flexibility, leading to the development and/or potentiation of addictive behaviors. Furthermore, dopamine and norepinephrine do not display linear effects; instead, their modulation of cognitive and neuronal function maps on an inverted-U curve. Healthy individuals run the risk of pushing themselves beyond optimal levels into hyperdopaminergic and hypernoradrenergic states, thus vitiating the very behaviors they are striving to improve. Finally, recent studies have begun to highlight potential damaging effects of stimulant exposure in healthy juveniles. This review explains how the main classes of cognitive enhancing drugs affect the learning and memory circuits, and highlights the potential risks and concerns in healthy individuals, particularly juveniles and adolescents. We emphasize the performance enhancement at the potential cost of brain plasticity that is associated with the neural ramifications of nootropic drugs in the healthy developing brain. PMID:24860437

  5. 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.

  6. 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…

  7. 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%.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Neural organization and visual processing in the anterior optic tubercle of the honeybee brain.

    Science.gov (United States)

    Mota, Theo; Yamagata, Nobuhiro; Giurfa, Martin; Gronenberg, Wulfila; Sandoz, Jean-Christophe

    2011-08-10

    The honeybee Apis mellifera represents a valuable model for studying the neural segregation and integration of visual information. Vision in honeybees has been extensively studied at the behavioral level and, to a lesser degree, at the physiological level using intracellular electrophysiological recordings of single neurons. However, our knowledge of visual processing in honeybees is still limited by the lack of functional studies of visual processing at the circuit level. Here we contribute to filling this gap by providing a neuroanatomical and neurophysiological characterization at the circuit level of a practically unstudied visual area of the bee brain, the anterior optic tubercle (AOTu). First, we analyzed the internal organization and neuronal connections of the AOTu. Second, we established a novel protocol for performing optophysiological recordings of visual circuit activity in the honeybee brain and studied the responses of AOTu interneurons during stimulation of distinct eye regions. Our neuroanatomical data show an intricate compartmentalization and connectivity of the AOTu, revealing a dorsoventral segregation of the visual input to the AOTu. Light stimuli presented in different parts of the visual field (dorsal, lateral, or ventral) induce distinct patterns of activation in AOTu output interneurons, retaining to some extent the dorsoventral input segregation revealed by our neuroanatomical data. In particular, activity patterns evoked by dorsal and ventral eye stimulation are clearly segregated into distinct AOTu subunits. Our results therefore suggest an involvement of the AOTu in the processing of dorsoventrally segregated visual information in the honeybee brain. PMID:21832175

  13. Adaptor protein LNK is a negative regulator of brain neural stem cell proliferation after stroke.

    Science.gov (United States)

    Ahlenius, Henrik; Devaraju, Karthikeyan; Monni, Emanuela; Oki, Koichi; Wattananit, Somsak; Darsalia, Vladimer; Iosif, Robert E; Torper, Olof; Wood, James C; Braun, Sebastian; Jagemann, Lucas; Nuber, Ulrike A; Englund, Elisabet; Jacobsen, Sten-Eirik W; Lindvall, Olle; Kokaia, Zaal

    2012-04-11

    Ischemic stroke causes transient increase of neural stem and progenitor cell (NSPC) proliferation in the subventricular zone (SVZ), and migration of newly formed neuroblasts toward the damaged area where they mature to striatal neurons. The molecular mechanisms regulating this plastic response, probably involved in structural reorganization and functional recovery, are poorly understood. The adaptor protein LNK suppresses hematopoietic stem cell self-renewal, but its presence and role in the brain are poorly understood. Here we demonstrate that LNK is expressed in NSPCs in the adult mouse and human SVZ. Lnk(-/-) mice exhibited increased NSPC proliferation after stroke, but not in intact brain or following status epilepticus. Deletion of Lnk caused increased NSPC proliferation while overexpression decreased mitotic activity of these cells in vitro. We found that Lnk expression after stroke increased in SVZ through the transcription factors STAT1/3. LNK attenuated insulin-like growth factor 1 signaling by inhibition of AKT phosphorylation, resulting in reduced NSPC proliferation. Our findings identify LNK as a stroke-specific, endogenous negative regulator of NSPC proliferation, and suggest that LNK signaling is a novel mechanism influencing plastic responses in postischemic brain. PMID:22496561

  14. 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.

  15. 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

  16. Regulation of pre-otic brain development by the cephalic neural crest.

    Science.gov (United States)

    Creuzet, Sophie E

    2009-09-15

    Emergence of the neural crest (NC) is considered an essential asset in the evolution of the chordate phylum, as specific vertebrate traits such as peripheral nervous system, cephalic skeletal tissues, and head development are linked to the NC and its derivatives. It has been proposed that the emergence of the NC was responsible for the formation of a "new head" characterized by the spectacular development of the forebrain and associated sense organs. It was previously shown that removal of the cephalic NC (CNC) prevents the formation of the facial structures but also results in anencephaly. This article reports on the molecular mechanisms whereby the CNC controls cephalic neurulation and brain morphogenesis. This study demonstrates that molecular variations of Gremlin and Noggin level in CNC account for morphological changes in brain size and development. CNC cells act in these processes through a multi-step control and exert cumulative effects counteracting bone morphogenetic protein signaling produced by the neighboring tissues (e.g., adjacent neuroepithelium, ventro-medial mesoderm, superficial ectoderm). These data provide an explanation for the fact that acquisition of the NC during the protochordate-to-vertebrate transition has coincided with a large increase of brain vesicles. PMID:19720987

  17. Musical skills and neural functions. The legacy of the brains of musicians.

    Science.gov (United States)

    Bentivoglio, Marina

    2003-11-01

    An overview of the history of debates on the correlation of musical skills with neurological functions in health and disease is presented. Selected biographical sketches of composers (Hildegard von Bingen, Mozart, Donizetti, Mussorgsky, and Ravel), whose neurological disease may have influenced musical creativity, are discussed. The search for information on the localization of skills in the brains of musicians is reviewed. The relation of mental ability to brain structure is a prominent theme in the history of neuroscience, and the effort to localize musical skills dates back to the excesses of phrenology in the early nineteenth century. The phrenological tables included an "organ of music" among the sites subserving intellectual capabilities, mapped on the basis of palpation of the head bumps. Since the second half of the nineteenth century, when the study of brain physiology, anatomy, and pathology had a remarkable development and impact on the neurosciences, structural features of the brain, particularly the cerebral cortex, of individuals with peculiar talents, including musical skills, have been examined to search for clues on the localization of mental phenomena. These studies, which continued in the twentieth century, are currently difficult to validate in view of the rigor imposed by current scientific standards. However, the issue of localization of functions in the musical brain is still debated and is now at the forefront of the neurosciences, exploiting especially functional neuroimaging. The historical overview of these problems is certainly exemplary of progress of knowledge, but also warns against excessive "localizationist" efforts. PMID:14681147

  18. 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.

  19. 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 ...

  20. 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 ...

  1. 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

  2. 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

  3. Advanced biomaterial strategies to transplant preformed micro-tissue engineered neural networks into the brain

    Science.gov (United States)

    Harris, J. P.; Struzyna, L. A.; Murphy, P. L.; Adewole, D. O.; Kuo, E.; Cullen, D. K.

    2016-02-01

    Objective. Connectome disruption is a hallmark of many neurological diseases and trauma with no current strategies to restore lost long-distance axonal pathways in the brain. We are creating transplantable micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of embedded neurons and long axonal tracts to integrate with the nervous system to physically reconstitute lost axonal pathways. Approach. We advanced micro-tissue engineering techniques to generate micro-TENNs consisting of discrete populations of mature primary cerebral cortical neurons spanned by long axonal fascicles encased in miniature hydrogel micro-columns. Further, we improved the biomaterial encasement scheme by adding a thin layer of low viscosity carboxymethylcellulose (CMC) to enable needle-less insertion and rapid softening for mechanical similarity with brain tissue. Main results. The engineered architecture of cortical micro-TENNs facilitated robust neuronal viability and axonal cytoarchitecture to at least 22 days in vitro. Micro-TENNs displayed discrete neuronal populations spanned by long axonal fasciculation throughout the core, thus mimicking the general systems-level anatomy of gray matter—white matter in the brain. Additionally, micro-columns with thin CMC-coating upon mild dehydration were able to withstand a force of 893 ± 457 mN before buckling, whereas a solid agarose cylinder of similar dimensions was predicted to withstand less than 150 μN of force. This thin CMC coating increased the stiffness by three orders of magnitude, enabling needle-less insertion into brain while significantly reducing the footprint of previous needle-based delivery methods to minimize insertion trauma. Significance. Our novel micro-TENNs are the first strategy designed for minimally invasive implantation to facilitate nervous system repair by simultaneously providing neuronal replacement and physical reconstruction of long-distance axon pathways in the brain

  4. Fat1 interacts with Fat4 to regulate neural tube closure, neural progenitor proliferation and apical constriction during mouse brain development.

    Science.gov (United States)

    Badouel, Caroline; Zander, Mark A; Liscio, Nicole; Bagherie-Lachidan, Mazdak; Sopko, Richelle; Coyaud, Etienne; Raught, Brian; Miller, Freda D; McNeill, Helen

    2015-08-15

    Mammalian brain development requires coordination between neural precursor proliferation, differentiation and cellular organization to create the intricate neuronal networks of the adult brain. Here, we examined the role of the atypical cadherins Fat1 and Fat4 in this process. We show that mutation of Fat1 in mouse embryos causes defects in cranial neural tube closure, accompanied by an increase in the proliferation of cortical precursors and altered apical junctions, with perturbations in apical constriction and actin accumulation. Similarly, knockdown of Fat1 in cortical precursors by in utero electroporation leads to overproliferation of radial glial precursors. Fat1 interacts genetically with the related cadherin Fat4 to regulate these processes. Proteomic analysis reveals that Fat1 and Fat4 bind different sets of actin-regulating and junctional proteins. In vitro data suggest that Fat1 and Fat4 form cis-heterodimers, providing a mechanism for bringing together their diverse interactors. We propose a model in which Fat1 and Fat4 binding coordinates distinct pathways at apical junctions to regulate neural progenitor proliferation, neural tube closure and apical constriction.

  5. Plasticity of brain wave network interactions and evolution across physiologic states

    OpenAIRE

    Liu, Kang K. L.; Bartsch, Ronny P.; Lin, Aijing; Mantegna, Rosario N.; Ivanov, Plamen Ch.

    2015-01-01

    Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other a...

  6. Brain-derived neurotrophic factor and neural plasticity in a rat model of spinal cord transection

    Institute of Scientific and Technical Information of China (English)

    Ruxin Xing; Jia Liu; Hua Jin; Ping Dai; Tinghua Wang

    2011-01-01

    The present study employed a rat model of T10 spinal cord transection. Western blot analyses revealed increased brain-derived neurotrophic factor (BDNF) expression in spinal cord segments caudal to the transection site following injection of replication incompetent herpes simplex virus vector (HSV-BDNF) into the subarachnoid space. In addition, hindlimb locomotor functions were improved. In contrast, BDNF levels decreased following treatment with replication defective herpes simplex virus vector construct small interference BDNF (HSV-siBDNF). Moreover, hindlimb locomotor functions gradually worsened. Compared with the replication incompetent herpes simplex virus vector control group, extracellular signal regulated kinase1/2 expression increased in the HSV-BDNF group on days 14 and 28 after spinal cord transection, but expression was reduced in the HSV-siBDNF group. These results suggested that BDNF plays an important role in neural plasticity via extracellular signal regulated kinase1/2 signaling pathway in a rat model of adult spinal cord transection.

  7. 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.

  8. 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.

  9. Novel theory of the human brain: information-commutation basis of architecture and principles of operation

    Directory of Open Access Journals (Sweden)

    Bryukhovetskiy AS

    2015-02-01

    Full Text Available Andrey S Bryukhovetskiy Center for Biomedical Technologies, Federal Research and Clinical Center for Specialized Types of Medical Assistance and Medical Technologies of the Federal Medical Biological Agency, NeuroVita Clinic of Interventional and Restorative Neurology and Therapy, Moscow, Russia Abstract: Based on the methodology of the informational approach and research of the genome, proteome, and complete transcriptome profiles of different cells in the nervous tissue of the human brain, the author proposes a new theory of information-commutation organization and architecture of the human brain which is an alternative to the conventional systemic connective morphofunctional paradigm of the brain framework. Informational principles of brain operation are defined: the modular principle, holographic principle, principle of systematicity of vertical commutative connection and complexity of horizontal commutative connection, regulatory principle, relay principle, modulation principle, “illumination” principle, principle of personalized memory and intellect, and principle of low energy consumption. The author demonstrates that the cortex functions only as a switchboard and router of information, while information is processed outside the nervous tissue of the brain in the intermeningeal space. The main structural element of information-commutation in the brain is not the neuron, but information-commutation modules that are subdivided into receiver modules, transmitter modules, and subscriber modules, forming a vertical architecture of nervous tissue in the brain as information lines and information channels, and a horizontal architecture as central, intermediate, and peripheral information-commutation platforms. Information in information-commutation modules is transferred by means of the carriers that are characteristic to the specific information level from inductome to genome, transcriptome, proteome, metabolome, secretome, and magnetome

  10. Neural reflections of meaning in gesture, language, and action

    OpenAIRE

    Willems, Roel Mathieu

    2009-01-01

    We gesture when we speak. In this thesis the neural basis in the healthy human brain of integration of action-related (gestural) and visual (pictures) information with spoken language was investigated.

  11. Evolvable synthetic neural system

    Science.gov (United States)

    Curtis, Steven A. (Inventor)

    2009-01-01

    An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

  12. Neural stem cells secrete factors facilitating brain regeneration upon constitutive Raf-Erk activation.

    Science.gov (United States)

    Rhee, Yong-Hee; Yi, Sang-Hoon; Kim, Joo Yeon; Chang, Mi-Yoon; Jo, A-Young; Kim, Jinyoung; Park, Chang-Hwan; Cho, Je-Yoel; Choi, Young-Jin; Sun, Woong; Lee, Sang-Hun

    2016-01-01

    The intracellular Raf-Erk signaling pathway is activated during neural stem cell (NSC) proliferation, and neuronal and astrocytic differentiation. A key question is how this signal can evoke multiple and even opposing NSC behaviors. We show here, using a constitutively active Raf (ca-Raf), that Raf-Erk activation in NSCs induces neuronal differentiation in a cell-autonomous manner. By contrast, it causes NSC proliferation and the formation of astrocytes in an extrinsic autocrine/paracrine manner. Thus, treatment of NSCs with medium (CM) conditioned in ca-Raf-transduced NSCs (Raf-CM; RCM) became activated to form proliferating astrocytes resembling radial glial cells (RGCs) or adult-type NSCs. Infusion of Raf-CM into injured mouse brains caused expansion of the NSC population in the subventricular zone, followed by the formation of new neurons that migrated to the damaged site. Our study shows an example how molecular mechanisms dissecting NSC behaviors can be utilized to develop regenerative therapies in brain disorders. PMID:27554447

  13. 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.

  14. 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.

  15. Brain-computer interfaces: an overview of the hardware to record neural signals from the cortex.

    Science.gov (United States)

    Stieglitz, Thomas; Rubehn, Birthe; Henle, Christian; Kisban, Sebastian; Herwik, Stanislav; Ruther, Patrick; Schuettler, Martin

    2009-01-01

    Brain-computer interfaces (BCIs) record neural signals from cortical origin with the objective to control a user interface for communication purposes, a robotic artifact or artificial limb as actuator. One of the key components of such a neuroprosthetic system is the neuro-technical interface itself, the electrode array. In this chapter, different designs and manufacturing techniques will be compared and assessed with respect to scaling and assembling limitations. The overview includes electroencephalogram (EEG) electrodes and epicortical brain-machine interfaces to record local field potentials (LFPs) from the surface of the cortex as well as intracortical needle electrodes that are intended to record single-unit activity. Two exemplary complementary technologies for micromachining of polyimide-based arrays and laser manufacturing of silicone rubber are presented and discussed with respect to spatial resolution, scaling limitations, and system properties. Advanced silicon micromachining technologies have led to highly sophisticated intracortical electrode arrays for fundamental neuroscientific applications. In this chapter, major approaches from the USA and Europe will be introduced and compared concerning complexity, modularity, and reliability. An assessment of the different technological solutions comparable to a strength weaknesses opportunities, and threats (SWOT) analysis might serve as guidance to select the adequate electrode array configuration for each control paradigm and strategy to realize robust, fast, and reliable BCIs. PMID:19660664

  16. Fatigue in Multiple Sclerosis: Neural Correlates and the Role of Non-Invasive Brain Stimulation.

    Science.gov (United States)

    Chalah, Moussa A; Riachi, Naji; Ahdab, Rechdi; Créange, Alain; Lefaucheur, Jean-Pascal; Ayache, Samar S

    2015-01-01

    Multiple sclerosis (MS) is a chronic progressive inflammatory disease of the central nervous system (CNS) 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 affects their quality of life. Despite its significant prevalence and impact, the underlying pathophysiological 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. Radiological, physiological, and endocrine data 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 suggestion of their potential mechanisms of action in this context. Specific issues related to the value of transcranial direct current stimulation (tDCS) will be addressed. PMID:26648845

  17. 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).

  18. Process modeling and parameter optimization using radial basis function neural network and genetic algorithm for laser welding of dissimilar materials

    Science.gov (United States)

    Ai, Yuewei; Shao, Xinyu; Jiang, Ping; Li, Peigen; Liu, Yang; Yue, Chen

    2015-11-01

    The welded joints of dissimilar materials have been widely used in automotive, ship and space industries. The joint quality is often evaluated by weld seam geometry, microstructures and mechanical properties. To obtain the desired weld seam geometry and improve the quality of welded joints, this paper proposes a process modeling and parameter optimization method to obtain the weld seam with minimum width and desired depth of penetration for laser butt welding of dissimilar materials. During the process, Taguchi experiments are conducted on the laser welding of the low carbon steel (Q235) and stainless steel (SUS301L-HT). The experimental results are used to develop the radial basis function neural network model, and the process parameters are optimized by genetic algorithm. The proposed method is validated by a confirmation experiment. Simultaneously, the microstructures and mechanical properties of the weld seam generated from optimal process parameters are further studied by optical microscopy and tensile strength test. Compared with the unoptimized weld seam, the welding defects are eliminated in the optimized weld seam and the mechanical properties are improved. The results show that the proposed method is effective and reliable for improving the quality of welded joints in practical production.

  19. 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.

  20. An expert system with radial basis function neural network based on decision trees for predicting sediment transport in sewers.

    Science.gov (United States)

    Ebtehaj, Isa; Bonakdari, Hossein; Zaji, Amir Hossein

    2016-01-01

    In this study, an expert system with a radial basis function neural network (RBF-NN) based on decision trees (DT) is designed to predict sediment transport in sewer pipes at the limit of deposition. First, sensitivity analysis is carried out to investigate the effect of each parameter on predicting the densimetric Froude number (Fr). The results indicate that utilizing the ratio of the median particle diameter to pipe diameter (d/D), ratio of median particle diameter to hydraulic radius (d/R) and volumetric sediment concentration (C(V)) as the input combination leads to the best Fr prediction. Subsequently, the new hybrid DT-RBF method is presented. The results of DT-RBF are compared with RBF and RBF-particle swarm optimization (PSO), which uses PSO for RBF training. It appears that DT-RBF is more accurate (R(2) = 0.934, MARE = 0.103, RMSE = 0.527, SI = 0.13, BIAS = -0.071) than the two other RBF methods. Moreover, the proposed DT-RBF model offers explicit expressions for use by practicing engineers. PMID:27386995

  1. 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.

  2. Neural basis of phonological awareness in beginning readers with familial risk of dyslexia-Results from shallow orthography.

    Science.gov (United States)

    Dębska, Agnieszka; Łuniewska, Magdalena; Chyl, Katarzyna; Banaszkiewicz, Anna; Żelechowska, Agata; Wypych, Marek; Marchewka, Artur; Pugh, Kenneth R; Jednoróg, Katarzyna

    2016-05-15

    Phonological processing ability is a key factor in reading acquisition, predicting its later success or causing reading problems when it is weakened. Our aim here was to establish the neural correlates of auditory word rhyming (a standard phonological measure) in 102 young children with (FHD+) and without familial history of dyslexia (FHD-) in a shallow orthography (i.e. Polish). Secondly, in order to gain a deeper understanding on how schooling shapes brain activity to phonological awareness, a comparison was made of children who had had formal literacy instruction for several months (in first grade) and those who had not yet had any formal instruction in literacy (in kindergarten). FHD+ children compared to FHD- children in the first grade scored lower in an early print task and showed longer reaction times in the in-scanner rhyme task. No behavioral differences between FHD+ and FHD- were found in the kindergarten group. On the neuronal level, overall familial risk was associated with reduced activation in the bilateral temporal, tempo-parietal and inferior temporal-occipital regions, as well as the bilateral inferior and middle frontal gyri. Subcortically, hypoactivation was found in the bilateral thalami, caudate, and right putamen in FHD+. A main effect of the children's grade was present only in the left inferior frontal gyrus, where reduced activation for rhyming was shown in first-graders. Several regions in the ventral occipital cortex, including the fusiform gyrus, and in the right middle frontal and postcentral gyri, displayed an interaction between familial risk and grade. The present results show strong influence of familial risk that may actually increase with formal literacy instruction. PMID:26931814

  3. 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.

  4. Combined age- and trauma-related proteomic changes in rat neocortex: a basis for brain vulnerability

    OpenAIRE

    Mehan, Neal D.; Strauss, Kenneth I

    2011-01-01

    This proteomic study investigates the widely observed clinical phenomenon, that after comparable brain injuries, geriatric patients fare worse and recover less cognitive and neurologic function than younger victims. Utilizing a rat traumatic brain injury model, sham surgery or a neocortical contusion was induced in 3 age groups. Geriatric (21 months) rats performed worse on behavioral measures than young adults (12–16 weeks) and juveniles (5– 6 weeks). Motor coordination and certain cognitive...

  5. Abnormal neural connectivity in schizophrenia and fMRI-brain computer interface as a potential therapeutic approach

    Directory of Open Access Journals (Sweden)

    Sergio eRuiz

    2013-03-01

    Full Text Available Considering that single locations of structural and functional abnormalities are insufficient to explain the diverse psychopathology of schizophrenia, new models have postulated that the impairments associated with the disease arise from a failure to integrate the activity of local and distributed neural circuits: the abnormal neural connectivity hypothesis. In the last years, new evidence coming from neuroimaging have supported and expanded this theory. However, despite the increasing evidence that schizophrenia is a disorder of neural connectivity, so far there are no treatments that have shown to produce a significant change in brain connectivity, or that have been specifically designed to alleviate this problem. Brain-Computer Interfaces based on real-time functional Magnetic Resonance Imaging (fMRI-BCI are novel techniques that have allowed subjects to achieve self-regulation of circumscribed brain regions. In recent studies, experiments with this technology have resulted in new findings suggesting that this methodology could be used to train subjects to enhance brain connectivity, and therefore could potentially be used as a therapeutic tool in mental disorders including schizophrenia.The present article summarizes the findings coming from hemodynamics-based neuroimaging that support the abnormal connectivity hypothesis in schizophrenia, and discusses a new approach that could address this problem.

  6. 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.

  7. Tracking Single Units in Chronic, Large Scale, Neural Recordings for Brain Machine Interface Applications

    Directory of Open Access Journals (Sweden)

    Ahmed eEleryan

    2014-07-01

    Full Text Available In the study of population coding in neurobiological systems, tracking unit identity may be critical to assess possible changes in the coding properties of neuronal constituents over prolonged periods of time. Ensuring unit stability is even more critical for reliable neural decoding of motor variables in intra-cortically controlled brain-machine interfaces (BMIs. Variability in intrinsic spike patterns, tuning characteristics, and single-unit identity over chronic use is a major challenge to maintaining this stability, requiring frequent daily calibration of neural decoders in BMI sessions by an experienced human operator. Here, we report on a unit-stability tracking algorithm that efficiently and autonomously identifies putative single-units that are stable across many sessions using a relatively short duration recording interval at the start of each session. The algorithm first builds a database of features extracted from units' average spike waveforms and firing patterns across many days of recording. It then uses these features to decide whether spike occurrences on the same channel on one day belong to the same unit recorded on another day or not. We assessed the overall performance of the algorithm for different choices of features and classifiers trained using human expert judgment, and quantified it as a function of accuracy and execution time. Overall, we found a trade-off between accuracy and execution time with increasing data volumes from chronically implanted rhesus macaques, with an average of 12 seconds processing time per channel at ~90% classification accuracy. Furthermore, 77% of the resulting putative single-units matched those tracked by human experts. These results demonstrate that over the span of a few months of recordings, automated unit tracking can be performed with high accuracy and used to streamline the calibration phase during BMI sessions.

  8. 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

  9. Neural processing of calories in brain reward areas can be modulated by reward sensitivity

    Directory of Open Access Journals (Sweden)

    Inge eVan Rijn

    2016-01-01

    Full Text Available A food’s reward value is dependent on its caloric content. Furthermore, a food’s acute reward value also depends on hunger state. The drive to obtain rewards (reward sensitivity, however, differs between individuals. Here, we assessed the association between brain responses to calories in the mouth and trait reward sensitivity in different hunger states. Firstly, we assessed this in data from a functional neuroimaging study (van Rijn et al., 2015, in which participants (n=30 tasted simple solutions of a non-caloric sweetener with or without a non-sweet carbohydrate (maltodextrin during hunger and satiety. Secondly, we expanded these analyses to regular drinks by assessing the same relationship in data from a study in which soft drinks sweetened with either sucrose or a non-caloric sweetener were administered during hunger (n=18 (Griffioen-Roose et al., 2013. First, taste activation by the non-caloric solution/soft drink was subtracted from that by the caloric solution/soft drink to eliminate sweetness effects and retain activation induced by calories. Subsequently, this difference in taste activation was correlated with reward sensitivity as measured with the BAS drive subscale of the Behavioral Activation System (BAS questionnaire.When participants were hungry and tasted calories from the simple solution, brain activation in the right ventral striatum (caudate, right amygdala and anterior cingulate cortex (bilaterally correlated negatively with BAS drive scores. In contrast, when participants were satiated, taste responses correlated positively with BAS drive scores in the left caudate. These results were not replicated for soft drinks. Thus, neural responses to oral calories from maltodextrin were modulated by reward sensitivity in reward-related brain areas. This was not the case for sucrose. This may be due to the direct detection of maltodextrin, but not sucrose in the oral cavity. Also, in a familiar beverage, detection of calories per

  10. 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

  11. 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, Joost

    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

  12. 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...

  13. Mammalian Target of Rapamycin: Its Role in Early Neural Development and in Adult and Aged Brain Function.

    Science.gov (United States)

    Garza-Lombó, Carla; Gonsebatt, María E

    2016-01-01

    The kinase mammalian target of rapamycin (mTOR) integrates signals triggered by energy, stress, oxygen levels, and growth factors. It regulates ribosome biogenesis, mRNA translation, nutrient metabolism, and autophagy. mTOR participates in various functions of the brain, such as synaptic plasticity, adult neurogenesis, memory, and learning. mTOR is present during early neural development and participates in axon and dendrite development, neuron differentiation, and gliogenesis, among other processes. Furthermore, mTOR has been shown to modulate lifespan in multiple organisms. This protein is an important energy sensor that is present throughout our lifetime its role must be precisely described in order to develop therapeutic strategies and prevent diseases of the central nervous system. The aim of this review is to present our current understanding of the functions of mTOR in neural development, the adult brain and aging. PMID:27378854

  14. 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.

  15. 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

  16. Transplantation of human neural stem cells restores cognition in an immunodeficient rodent model of traumatic brain injury

    OpenAIRE

    Haus, DL; Lopez-Velazquez, L; Gold, EM; Cunningham, KM; Perez, H; Anderson, AJ; Cummings, BJ

    2016-01-01

    Traumatic brain injury (TBI) in humans can result in permanent tissue damage and has been linked to cognitive impairment that lasts years beyond the initial insult. Clinically effective treatment strategies have yet to be developed. Transplantation of human neural stem cells (hNSCs) has the potential to restore cognition lost due to injury, however, the vast majority of rodent TBI/hNSC studies to date have evaluated cognition only at early time points, typically

  17. Brain injury expands the numbers of neural stem cells and progenitors in the SVZ by enhancing their responsiveness to EGF

    Directory of Open Access Journals (Sweden)

    Deborah A Lazzarino

    2009-05-01

    Full Text Available There is an increase in the numbers of neural precursors in the SVZ (subventricular zone after moderate ischaemic injuries, but the extent of stem cell expansion and the resultant cell regeneration is modest. Therefore our studies have focused on understanding the signals that regulate these processes towards achieving a more robust amplification of the stem/progenitor cell pool. The goal of the present study was to evaluate the role of the EGFR [EGF (epidermal growth factor receptor] in the regenerative response of the neonatal SVZ to hypoxic/ischaemic injury. We show that injury recruits quiescent cells in the SVZ to proliferate, that they divide more rapidly and that there is increased EGFR expression on both putative stem cells and progenitors. With the amplification of the precursors in the SVZ after injury there is enhanced sensitivity to EGF, but not to FGF (fibroblast growth factor-2. EGF-dependent SVZ precursor expansion, as measured using the neurosphere assay, is lost when the EGFR is pharmacologically inhibited, and forced expression of a constitutively active EGFR is sufficient to recapitulate the exaggerated proliferation of the neural stem/progenitors that is induced by hypoxic/ischaemic brain injury. Cumulatively, our results reveal that increased EGFR signalling precedes that increase in the abundance of the putative neural stem cells and our studies implicate the EGFR as a key regulator of the expansion of SVZ precursors in response to brain injury. Thus modulating EGFR signalling represents a potential target for therapies to enhance brain repair from endogenous neural precursors following hypoxic/ischaemic and other brain injuries.

  18. Depletion of neural stem cells from the subventricular zone of adult mouse brain using cytosine b‐Arabinofuranoside

    OpenAIRE

    Ghanbari, Amir; Esmaeilpour, Tahereh; Bahmanpour, Soghra; Golmohammadi, Mohammad Ghasem; Sharififar, Sharareh; Azari, Hassan

    2015-01-01

    Abstract Introduction Neural stem cells (NSCs) reside along the ventricular axis of the mammalian brain. They divide infrequently to maintain themselves and the down‐stream progenitors. Due to the quiescent property of NSCs, attempts to deplete these cells using antimitotic agents such as cytosine b‐Aarabinofuranoside (Ara‐C) have not been successful. We hypothesized that implementing infusion gaps in Ara‐C kill paradigms would recruit the quiescent NSCs and subsequently eliminate them from t...

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

    OpenAIRE

    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.

    2012-01-01

    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 ...

  20. Neural Decoding and "Inner" Psychophysics: A Distance-to-Bound Approach for Linking Mind, Brain, and Behavior

    Directory of Open Access Journals (Sweden)

    J. Brendan eRitchie

    2016-04-01

    Full Text Available 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.

  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. 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

  3. Age related-changes in the neural basis of self-generation in verbal paired associate learning

    Directory of Open Access Journals (Sweden)

    Jennifer Vannest

    2015-01-01

    Full Text Available Verbal information is better retained when it is self-generated rather than when it is received passively. The application of self-generation procedures has been found to improve memory in healthy elderly and in individuals with impaired cognition. Overall, the available studies support the notion that active participation in verbal encoding engages memory mechanisms that supplement those used during passive observation. Thus, the objective of this study was to investigate the age-related changes in the neural mechanisms involved in the encoding of paired-associates using a self-generation method that has been shown to improve memory performance across the lifespan. Subjects were 113 healthy right-handed adults (Edinburgh Handedness Inventory >50; 67 females ages 18–76, native speakers of English with no history of neurological or psychiatric disorders. Subjects underwent fMRI at 3 T while performing didactic learning (“read” or self-generation learning (“generate” of 30 word pairs per condition. After fMRI, recognition memory for the second word in each pair was evaluated outside of the scanner. On the post-fMRI testing more “generate” words were correctly recognized than “read” words (p < 0.001 with older adults recognizing the “generated” words less accurately (p < 0.05. Independent component analysis of fMRI data identified task-related brain networks. Several components were positively correlated with the task reflecting multiple cognitive processes involved in self-generated encoding; other components correlated negatively with the task, including components of the default-mode network. Overall, memory performance on generated words decreased with age, but the benefit from self-generation remained consistently significant across ages. Independent component analysis of the neuroimaging data revealed an extensive set of components engaged in self-generation learning compared with didactic learning, and identified

  4. 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.

  5. 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. PMID:23519971

  6. 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 di...

  7. A recurrent neural network for closed-loop intracortical brain-machine interface decoders

    Science.gov (United States)

    Sussillo, David; Nuyujukian, Paul; Fan, Joline M.; Kao, Jonathan C.; Stavisky, Sergey D.; Ryu, Stephen; Shenoy, Krishna

    2012-04-01

    Recurrent neural networks (RNNs) are useful tools for learning nonlinear relationships in time series data with complex temporal dependences. In this paper, we explore the ability of a simplified type of RNN, one with limited modifications to the internal weights called an echostate network (ESN), to effectively and continuously decode monkey reaches during a standard center-out reach task using a cortical brain-machine interface (BMI) in a closed loop. We demonstrate that the RNN, an ESN implementation termed a FORCE decoder (from first order reduced and controlled error learning), learns the task quickly and significantly outperforms the current state-of-the-art method, the velocity Kalman filter (VKF), using the measure of target acquire time. We also demonstrate that the FORCE decoder generalizes to a more difficult task by successfully operating the BMI in a randomized point-to-point task. The FORCE decoder is also robust as measured by the success rate over extended sessions. Finally, we show that decoded cursor dynamics are more like naturalistic hand movements than those of the VKF. Taken together, these results suggest that RNNs in general, and the FORCE decoder in particular, are powerful tools for BMI decoder applications.

  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. 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.

  10. 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. PMID:27211331

  11. Novel theory of the human brain: information-commutation basis of architecture and principles of operation

    OpenAIRE

    Bryukhovetskiy AS

    2015-01-01

    Andrey S Bryukhovetskiy Center for Biomedical Technologies, Federal Research and Clinical Center for Specialized Types of Medical Assistance and Medical Technologies of the Federal Medical Biological Agency, NeuroVita Clinic of Interventional and Restorative Neurology and Therapy, Moscow, Russia Abstract: Based on the methodology of the informational approach and research of the genome, proteome, and complete transcriptome profiles of different cells in the nervous tissue of the human brain,...

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

    OpenAIRE

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

    2007-01-01

    Parenting behavior critically shapes human infants’ current and future behavior. The parent–infant relationship provides infants with their first social experiences, forming templates of what they can expect from others and how to best meet others’ expectations. In this review, we focus on the neurobiology of parenting behavior, including our own functional magnetic resonance imaging (fMRI) brain imaging experiments of parents. We begin with a discussion of background, perspectives and caveat...

  13. 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 < 0.001). The hypothesis of brain plasticity between the facial nerve and masseter nerve areas is supported by the broad cortical overlap in the representation of facial and masseter muscles. PMID:26683008

  14. 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.

  15. Development of a Stereotaxic Device for Low Impact Implantation of Neural Constructs or Pieces of Neural Tissues into the Mammalian Brain

    Directory of Open Access Journals (Sweden)

    Andrzej Jozwiak

    2014-01-01

    Full Text Available Implanting pieces of tissue or scaffolding material into the mammalian central nervous system (CNS is wrought with difficulties surrounding the size of tools needed to conduct such implants and the ability to maintain the orientation and integrity of the constructs during and after their transplantation. Here, novel technology has been developed that allows for the implantation of neural constructs or intact pieces of neural tissue into the CNS with low trauma. By “laying out” (instead of forcibly expelling the implantable material from a thin walled glass capillary, this technology has the potential to enhance neural transplantation procedures by reducing trauma to the host brain during implantation and allowing for the implantation of engineered/dissected tissues or constructs in such a way that their orientation and integrity are maintained in the host. Such technology may be useful for treating various CNS disorders which require the reestablishment of point-to-point contacts (e.g., Parkinson’s disease across the adult CNS, an environment which is not normally permissive to axonal growth.

  16. 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. PMID:27150924

  17. 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.

  18. Regional difference of radiosensitivity of neural cells in the fetal brain of mice on day 13 of gestation

    International Nuclear Information System (INIS)

    Pregnant Slc: ICR mice were exposed to a single whole-body X-irradiation at a dose of 12.5 R or 25 R on day 13 of gestation. After irradiation, fetuses were obtained from mothers at 1- or 3-hour intervals and coronal histological sections were made. Pyknotic cells were counted in the ventricular zone of brain mantle, hippocampal anlage and olfactory bulb. In the 25 R group, peak incidences of pyknotic cells in brain mantle, hippocampal anlage and olfactory bulb were 13.2 %, 6.9 % and 2.2 %, respectively. In the 12.5 R group, these were 6.0 %, 3.2 % and 1.7 %, respectively. This result indicates that neural cells in the ventricular zone of brain mantle are the most radiosensitive among the cerebral regions examined in day-13 mouse fetuses. (author)

  19. 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.

  20. 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.

  1. 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. PMID:26505808

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. Molecular basis of thyroid hormone regulation of myelin basic protein gene expression in rodent brain.

    Science.gov (United States)

    Farsetti, A; Mitsuhashi, T; Desvergne, B; Robbins, J; Nikodem, V M

    1991-12-01

    Regulation of myelin basic protein (MBP) gene expression by thyroid hormone has been investigated in rodent brain. Quantitation of the 4 major alternatively spliced transcripts by RNase protection assay showed that the individual mRNAs, corresponding to MBP isoforms 21.5, 18.5, 17, and 14 kDa, were decreased from 2- to 17-fold at all ages studied (4-60 days) in hypothyroid animals when compared to euthyroid, but the timing of onset of expression was not altered. MBP mRNA was also reduced in young adult rats thyroidectomized at the age of 5-6 weeks and was restored to normal by thyroxine administration. Nuclear run-off assays showed that the rate of MBP gene transcription is dependent on thyroid state. Co-transfection of MBP (-256/+1)-chloramphenicol acetyltransferase chimeric gene with a plasmid expressing thyroid hormone receptor alpha, and in the presence of 3,5,3'-triiodothyronine, into NIH3T3 or NG108-15, increased chloramphenicol acetyltransferase expression 4-fold. Using a footprinting technique and Spodoptera frugiperda 9 (Sf9) nuclear extract infected with baculovirus expressing TR alpha, we have identified a single DNA-binding site (-186/-163) for the receptor. A part of this region contains the AGGACA sequence found in thyroid hormone-responsive elements of other 3,5,3'-triiodothyronine-regulated genes. Our finding of a specific hormone-receptor interaction with the MBP promoter region is the first direct demonstration of a thyroid hormone-responsive element in a brain-specific gene. PMID:1720778

  8. 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...

  9. 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.

  10. An Investigation into Food Preferences and the Neural Basis of Food-Related Incentive Motivation in Prader-Willi Syndrome

    Science.gov (United States)

    Hinton, E. C.; Holland, A. J.; Gellatly, M. S. N.; Soni, S.; Owen, A. M.

    2006-01-01

    Background: Research into the excessive eating behaviour associated with Prader-Willi syndrome (PWS) to date has focused on homeostatic and behavioural investigations. The aim of this study was to examine the role of the reward system in such eating behaviour, in terms of both the pattern of food preferences and the neural substrates of incentive…

  11. 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.

  12. 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.

  13. 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. PMID:26164169

  14. 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

  15. Extremely low-frequency electromagnetic fields enhance the proliferation and differentiation of neural progenitor cells cultured from ischemic brains.

    Science.gov (United States)

    Cheng, Yannan; Dai, Yiqin; Zhu, Ximin; Xu, Haochen; Cai, Ping; Xia, Ruohong; Mao, Lizhen; Zhao, Bing-Qiao; Fan, Wenying

    2015-10-21

    In the mammalian brain, neurogenesis persists throughout the embryonic period and adulthood in the subventricular zone of the lateral ventricle and the granular zone (dentate gyrus) of the hippocampus. Newborn neural progenitor cells (NPCs) in the two regions play a critical role in structural and functional plasticity and neural regeneration after brain injury. Previous studies have reported that extremely low-frequency electromagnetic fields (ELF-EMF) could promote osteogenesis, angiogenesis, and cardiac stem cells' differentiation, which indicates that ELF-EMF might be an effective tool for regenerative therapy. The present studies were carried out to examine the effects of ELF-EMF on hippocampal NPCs cultured from embryonic and adult ischemic brains. We found that exposure to ELF-EMF (50 Hz, 0.4 mT) significantly enhanced the proliferation capability both in embryonic NPCs and in ischemic NPCs. Neuronal differentiation was also enhanced after 7 days of cumulative ELF-EMF exposure, whereas glial differentiation was not influenced markedly. The expression of phosphorylated Akt increased during the proliferation process when ischemic NPCs were exposed to ELF-EMF. However, blockage of the Akt pathway abolished the ELF-EMF-induced proliferation of ischemic NPCs. These data show that ELF-EMF promotes neurogenesis of ischemic NPCs and suggest that this effect may occur through the Akt pathway.Video abstract, Supplemental Digital Content 1, http://links.lww.com/WNR/A347. PMID:26339991

  16. 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.

  17. Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

    Science.gov (United States)

    Sadeghi-Goughari, M.; Mojra, A.; Sadeghi, S.

    2016-02-01

    Intraoperative Thermal Imaging (ITI) is a new minimally invasive diagnosis technique that can potentially locate margins of brain tumor in order to achieve maximum tumor resection with least morbidity. This study introduces a new approach to ITI based on artificial tactile sensing (ATS) technology in conjunction with artificial neural networks (ANN) and feasibility and applicability of this method in diagnosis and localization of brain tumors is investigated. In order to analyze validity and reliability of the proposed method, two simulations were performed. (i) An in vitro experimental setup was designed and fabricated using a resistance heater embedded in agar tissue phantom in order to simulate heat generation by a tumor in the brain tissue; and (ii) A case report patient with parafalcine meningioma was presented to simulate ITI in the neurosurgical procedure. In the case report, both brain and tumor geometries were constructed from MRI data and tumor temperature and depth of location were estimated. For experimental tests, a novel assisted surgery robot was developed to palpate the tissue phantom surface to measure temperature variations and ANN was trained to estimate the simulated tumor’s power and depth. Results affirm that ITI based ATS is a non-invasive method which can be useful to detect, localize and characterize brain tumors.

  18. Parameter estimation of brain tumors using intraoperative thermal imaging based on artificial tactile sensing in conjunction with artificial neural network

    International Nuclear Information System (INIS)

    Intraoperative Thermal Imaging (ITI) is a new minimally invasive diagnosis technique that can potentially locate margins of brain tumor in order to achieve maximum tumor resection with least morbidity. This study introduces a new approach to ITI based on artificial tactile sensing (ATS) technology in conjunction with artificial neural networks (ANN) and feasibility and applicability of this method in diagnosis and localization of brain tumors is investigated. In order to analyze validity and reliability of the proposed method, two simulations were performed. (i) An in vitro experimental setup was designed and fabricated using a resistance heater embedded in agar tissue phantom in order to simulate heat generation by a tumor in the brain tissue; and (ii) A case report patient with parafalcine meningioma was presented to simulate ITI in the neurosurgical procedure. In the case report, both brain and tumor geometries were constructed from MRI data and tumor temperature and depth of location were estimated. For experimental tests, a novel assisted surgery robot was developed to palpate the tissue phantom surface to measure temperature variations and ANN was trained to estimate the simulated tumor’s power and depth. Results affirm that ITI based ATS is a non-invasive method which can be useful to detect, localize and characterize brain tumors. (paper)

  19. 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.

  20. 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.

  1. 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. PMID:26588800

  2. Neural tension technique is no different from random passive movements in reducing spasticity in patients with traumatic brain injury

    DEFF Research Database (Denmark)

    Lorentzen, Jakob; Nielsen, Dorthe; Holm, Karl;

    2012-01-01

    by three raters before and after a single treatment session. Results: Objective stiffness measured with the hand-held device showed no significant changes for the NTT or RPM (p = 0.09-0.79). The subjective measures showed significant changes after the NTT for the non-blinded rater (MAS: p ...Purpose: Neural tension technique (NTT) is a therapy believed to reduce spasticity and to increase range of motion (ROM). This study compared the ability of NTT and random passive movements (RPMs) to reduce spasticity in the knee flexors in 10 spastic patients with brain injury. Methods: An RCT...

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Marta eBakker

    2015-02-01

    Full Text Available 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 degrees, 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.

  5. Chondroitin sulphate-mediated fusion of brain neural folds in rat embryos.

    Science.gov (United States)

    Alonso, M I; Moro, J A; Martín, C; de la Mano, A; Carnicero, E; Martínez-Alvarez, C; Navarro, N; Cordero, J; Gato, A

    2009-01-01

    Previous studies have demonstrated that during neural fold fusion in different species, an apical extracellular material rich in glycoconjugates is involved. However, the composition and the biological role of this material remain undetermined. In this paper, we show that this extracellular matrix in rat increases notably prior to contact between the neural folds, suggesting the dynamic behaviour of the secretory process. Immunostaining has allowed us to demonstrate that this extracellular matrix contains chondroitin sulphate proteoglycan (CSPG), with a spatio-temporal distribution pattern, suggesting a direct relationship with the process of adhesion. The degree of CSPG involvement in cephalic neural fold fusion in rat embryos was determined by treatment with specific glycosidases.In vitro rat embryo culture and microinjection techniques were employed to carry out selective digestion, with chondroitinase AC, of the CSPG on the apical surface of the neural folds; this was done immediately prior to the bonding of the cephalic neural folds. In all the treated embryos, cephalic defects of neural fold fusion could be detected. These results show that CSPG plays an important role in the fusion of the cephalic neural folds in rat embryos, which implies that this proteoglycan could be involved in cellular recognition and adhesion. PMID:18836253

  6. Brain Basics

    Medline Plus

    Full Text Available ... as depression. The Growing Brain Inside the Brain: Neurons & Neural Circuits Neurons are the basic working unit of the brain ... specialized for the function of conducting messages. A neuron has three basic parts: Cell body which includes ...

  7. Brain Basics

    Medline Plus

    Full Text Available ... The Growing Brain Inside the Brain: Neurons & Neural Circuits Neurons are the basic working unit of the ... distant nerve cells (via axons) to form brain circuits. These circuits control specific body functions such as ...

  8. Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

    Science.gov (United States)

    Jafari, Mehdi; Kasaei, Shohreh

    2012-01-01

    Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

  9. The Wellcome Prize Lecture. A map of auditory space in the mammalian brain: neural computation and development.

    Science.gov (United States)

    King, A J

    1993-09-01

    The experiments described in this review have demonstrated that the SC contains a two-dimensional map of auditory space, which is synthesized within the brain using a combination of monaural and binaural localization cues. There is also an adaptive fusion of auditory and visual space in this midbrain nucleus, providing for a common access to the motor pathways that control orientation behaviour. This necessitates a highly plastic relationship between the visual and auditory systems, both during postnatal development and in adult life. Because of the independent mobility of difference sense organs, gating mechanisms are incorporated into the auditory representation to provide up-to-date information about the spatial orientation of the eyes and ears. The SC therefore provides a valuable model system for studying a number of important issues in brain function, including the neural coding of sound location, the co-ordination of spatial information between different sensory systems, and the integration of sensory signals with motor outputs. PMID:8240794

  10. 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.

  11. 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.

  12. Structural basis by which alternative splicing modulates the organizer activity of FGF8 in the brain

    Science.gov (United States)

    Olsen, Shaun K.; Li, James Y.H.; Bromleigh, Carrie; Eliseenkova, Anna V.; Ibrahimi, Omar A.; Lao, Zhimin; Zhang, Fuming; Linhardt, Robert J.; Joyner, Alexandra L.; Mohammadi, Moosa

    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 FGF8bF32A 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. PMID:16384934

  13. Longitudinal evidence for functional specialization of the neural circuit supporting working memory in the human brain

    OpenAIRE

    Finn, Amy S.; Sheridan, Margaret A.; Hudson Kam, Carla L.; Hinshaw, Stephen; D’Esposito, Mark

    2010-01-01

    Although children perform more poorly than adults on many cognitive measures, they are better able to learn things such as language and music. These differences could result from the delayed specialization of neural circuits and asynchronies in the maturation of neural substrates required for learning. Working memory—the ability to hold information in mind that is no longer present in the environment—comprises a set of cognitive processes required for many, if not all, forms of learning. A cr...

  14. Illuminating the Effects of Stroke on the Diabetic Brain: Insights From Imaging Neural and Vascular Networks in Experimental Animal Models.

    Science.gov (United States)

    Reeson, Patrick; Jeffery, Andrew; Brown, Craig E

    2016-07-01

    Type 1 diabetes is known to cause circulatory problems in the eyes, heart, and limbs, and the brain is no exception. Because of the insidious effects of diabetes on brain circulation, patients with diabetes are two to four times more likely to have an ischemic stroke and are less likely to regain functions that are lost. To provide a more mechanistic understanding of this clinically significant problem, imaging studies have focused on how stroke affects neural and vascular networks in experimental models of type 1 diabetes. The emerging picture is that diabetes leads to maladaptive changes in the cerebrovascular system that ultimately limit neuronal rewiring and recovery of functions after stroke. At the cellular and systems level, diabetes is associated with abnormal cerebral blood flow in surviving brain regions and greater disruption of the blood-brain barrier. The abnormal vascular responses to stroke can be partly attributed to aberrant vascular endothelial growth factor (VEGF) signaling because genetic or pharmacological inhibition of VEGF signaling can mitigate vascular dysfunction and improve stroke recovery in diabetic animals. These experimental studies offer new insights and strategies for optimizing stroke recovery in diabetic populations. PMID:27329953

  15. Signalling through the type 1 insulin-like growth factor receptor (IGF1R interacts with canonical Wnt signalling to promote neural proliferation in developing brain

    Directory of Open Access Journals (Sweden)

    Qichen Hu

    2012-07-01

    Full Text Available Signalling through the IGF1R [type 1 IGF (insulin-like growth factor receptor] and canonical Wnt signalling are two signalling pathways that play critical roles in regulating neural cell generation and growth. To determine whether the signalling through the IGF1R can interact with the canonical Wnt signalling pathway in neural cells in vivo, we studied mutant mice with altered IGF signalling. We found that in mice with blunted IGF1R expression specifically in nestin-expressing neural cells (IGF1RNestin−KO mice the abundance of neural β-catenin was significantly reduced. Blunting IGF1R expression also markedly decreased: (i the activity of a LacZ (β-galactosidase reporter transgene that responds to Wnt nuclear signalling (LacZTCF reporter transgene and (ii the number of proliferating neural precursors. In contrast, overexpressing IGF-I (insulin-like growth factor I in brain markedly increased the activity of the LacZTCF reporter transgene. Consistently, IGF-I treatment also markedly increased the activity of the LacZTCF reporter transgene in embryonic neuron cultures that are derived from LacZTCF Tg (transgenic mice. Importantly, increasing the abundance of β-catenin in IGF1RNestin−KO embryonic brains by suppressing the activity of GSK3β (glycogen synthase kinase-3β significantly alleviated the phenotypic changes induced by IGF1R deficiency. These phenotypic changes includes: (i retarded brain growth, (ii reduced precursor proliferation and (iii decreased neuronal number. Our current data, consistent with our previous study of cultured oligodendrocytes, strongly support the concept that IGF signalling interacts with canonical Wnt signalling in the developing brain to promote neural proliferation. The interaction of IGF and canonical Wnt signalling plays an important role in normal brain development by promoting neural precursor proliferation.

  16. 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.

  17. 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.

  18. 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.

  19. Induced neural stem cells achieve long-term survival and functional integration in the adult mouse brain.

    Science.gov (United States)

    Hemmer, Kathrin; Zhang, Mingyue; van Wüllen, Thea; Sakalem, Marna; Tapia, Natalia; Baumuratov, Aidos; Kaltschmidt, Christian; Kaltschmidt, Barbara; Schöler, Hans R; Zhang, Weiqi; Schwamborn, Jens C

    2014-09-01

    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. PMID:25241741

  20. 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.

  1. Elevation of Brain Magnesium Potentiates Neural Stem Cell Proliferation in the Hippocampus of Young and Aged Mice.

    Science.gov (United States)

    Jia, Shanshan; Liu, Yunpeng; Shi, Yang; Ma, Yihe; Hu, Yixin; Wang, Meiyan; Li, Xue

    2016-09-01

    In the adult brain, neural stem cells (NSCs) can self-renew and generate all neural lineage types, and they persist in the sub-granular zone (SGZ) of the hippocampus and the sub-ventricular zone (SVZ) of the cortex. Here, we show that dietary-supplemented - magnesium-L-threonate (MgT), a novel magnesium compound designed to elevate brain magnesium regulates the NSC pool in the adult hippocampus. We found that administration of both short- and long-term regimens of MgT, increased the number of hippocampal NSCs. We demonstrated that in young mice, dietary supplementation with MgT significantly enhanced NSC proliferation in the SGZ. Importantly, in aged mice that underwent long-term (12-month) supplementation with MgT, MgT did not deplete the hippocampal NSC reservoir but rather curtailed the age-associated decline in NSC proliferation. We further established an association between extracellular magnesium concentrations and NSC self-renewal in vitro by demonstrating that elevated Mg(2+) concentrations can maintain or increase the number of cultured hippocampal NSCs. Our study also suggests that key signaling pathways for cell growth and proliferation may be candidate targets for Mg(2+) 's effects on NSC self-renewal. J. Cell. Physiol. 231: 1903-1912, 2016. © 2016 Wiley Periodicals, Inc. PMID:26754806

  2. 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.

  3. Educating the blind brain: a panorama of neural bases of vision and of training programs in organic neurovisual deficits

    Directory of Open Access Journals (Sweden)

    Olivier A. Coubard

    2014-12-01

    Full Text Available Vision is a complex function, which is achieved by movements of the eyes to properly foveate targets at any location in 3D space and to continuously refresh neural information in the different visual pathways. The visual system involves five routes originating in the retinas but varying in their destination within the brain: the occipital cortex, but also the superior colliculus, the pretectum, the supra-chiasmatic nucleus, the nucleus of the optic tract and terminal dorsal, medial and lateral nuclei. Visual pathway architecture obeys systematization in sagittal and transversal planes so that visual information from left/right and upper/lower hemi-retinas, corresponding respectively to right/left and lower/upper visual fields, is processed ipsilaterally and ipsialtitudinally to hemi-retinas in left/right hemispheres and upper/lower fibers. Organic neurovisual deficits may occur at any level of this circuitry from the optic nerve to subcortical and cortical destinations, resulting in low or high-level visual deficits. In this didactic review article, we provide a panorama of the neural bases of eye movements and visual systems, and of related neurovisual deficits. Additionally, we briefly review the different schools of rehabilitation of organic neurovisual deficits, and show that whatever the emphasis is put on action or perception, benefits may be observed at both motor and perceptual levels. Given the extent of its neural bases in the brain, vision in its motor and perceptual aspects is also a useful tool to assess and modulate central nervous system in general.

  4. Novel neural network model combining radial basis function, competitive Hebbian learning rule, and fuzzy simplified adaptive resonance theory

    Science.gov (United States)

    Baraldi, Andrea; Parmiggiani, Flavio

    1997-10-01

    In the first part of this paper a new on-line fully self- organizing artificial neural network model (FSONN), pursuing dynamic generation and removal of neurons and synaptic links, is proposed. The model combines properties of the self- organizing map (SOM), fuzzy c-means (FCM), growing neural gas (GNG) and fuzzy simplified adaptive resonance theory (Fuzzy SART) algorithms. In the second part of the paper experimental results are provided and discussed. Our conclusion is that the proposed connectionist model features several interesting properties, such as the following: (1) the system requires no a priori knowledge of the dimension, size and/or adjacency structure of the network; (2) with respect to other connectionist models found in the literature, the system can be employed successfully in: (a) a vector quantization; (b) density function estimation; and (c) structure detection in input data to be mapped topologically correctly onto an output lattice pursuing dimensionality reduction; and (3) the system is computationally efficient, its processing time increasing linearly with the number of neurons and synaptic links.

  5. 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.

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

    OpenAIRE

    Robel Abay

    2015-01-01

    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 patter...

  7. 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.

  8. Is there evidence for neural compensation in attention deficit hyperactivity disorder? A review of the functional neuroimaging literature

    OpenAIRE

    Fassbender, Catherine; Schweitzer, Julie B.

    2006-01-01

    This article reviews evidence for the presence of a compensatory, alternative, neural system and its possible link to associated processing strategies in children and adults with attention deficit hyperactivity disorder (ADHD). The article presents findings on a region by region basis that suggests ADHD should be characterized not only by neural hypo-activity, as it is commonly thought but neural hyperactivity as well, in regions of the brain that may relate to compensatory brain and behavior...

  9. 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.

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Rapid fluctuations in extracellular brain glucose levels induced by natural arousing stimuli and intravenous cocaine: fueling the brain during neural activation

    Science.gov (United States)

    Lenoir, Magalie

    2012-01-01

    Glucose, a primary energetic substrate for neural activity, is continuously influenced by two opposing forces that tend to either decrease its extracellular levels due to enhanced utilization in neural cells or increase its levels due to entry from peripheral circulation via enhanced cerebral blood flow. How this balance is maintained under physiological conditions and changed during neural activation remains unclear. To clarify this issue, enzyme-based glucose sensors coupled with high-speed amperometry were used in freely moving rats to evaluate fluctuations in extracellular glucose levels induced by brief audio stimulus, tail pinch (TP), social interaction with another rat (SI), and intravenous cocaine (1 mg/kg). Measurements were performed in nucleus accumbens (NAcc) and substantia nigra pars reticulata (SNr), which drastically differ in neuronal activity. In NAcc, where most cells are powerfully excited after salient stimulation, glucose levels rapidly (latency 2–6 s) increased (30–70 μM or 6–14% over baseline) by all stimuli; the increase differed in magnitude and duration for each stimulus. In SNr, where most cells are transiently inhibited by salient stimuli, TP, SI, and cocaine induced a biphasic glucose response, with the initial decrease (−20–40 μM or 5–10% below baseline) followed by a reboundlike increase. The critical role of neuronal activity in mediating the initial glucose response was confirmed by monitoring glucose currents after local microinjections of glutamate (GLU) or procaine (PRO). While intra-NAcc injection of GLU transiently increased glucose levels in this structure, intra-SNr PRO injection resulted in rapid, transient decreases in SNr glucose. Therefore, extracellular glucose levels in the brain change very rapidly after physiological and pharmacological stimulation, the response is structure specific, and the pattern of neuronal activity appears to be a critical factor determining direction and magnitude of physiological

  15. Definition of genetic events directing the development of distinct types of brain tumors from postnatal neural stem/progenitor cells.

    Science.gov (United States)

    Hertwig, Falk; Meyer, Katharina; Braun, Sebastian; Ek, Sara; Spang, Rainer; Pfenninger, Cosima V; Artner, Isabella; Prost, Gaëlle; Chen, Xinbin; Biegel, Jaclyn A; Judkins, Alexander R; Englund, Elisabet; Nuber, Ulrike A

    2012-07-01

    Although brain tumors are classified and treated based upon their histology, the molecular factors involved in the development of various tumor types remain unknown. In this study, we show that the type and order of genetic events directs the development of gliomas, central nervous system primitive neuroectodermal tumors, and atypical teratoid/rhabdoid-like tumors from postnatal mouse neural stem/progenitor cells (NSC/NPC). We found that the overexpression of specific genes led to the development of these three different brain tumors from NSC/NPCs, and manipulation of the order of genetic events was able to convert one established tumor type into another. In addition, loss of the nuclear chromatin-remodeling factor SMARCB1 in rhabdoid tumors led to increased phosphorylation of eIF2α, a central cytoplasmic unfolded protein response (UPR) component, suggesting a role for the UPR in these tumors. Consistent with this, application of the proteasome inhibitor bortezomib led to an increase in apoptosis of human cells with reduced SMARCB1 levels. Taken together, our findings indicate that the order of genetic events determines the phenotypes of brain tumors derived from a common precursor cell pool, and suggest that the UPR may represent a therapeutic target in atypical teratoid/rhabdoid tumors. PMID:22719073

  16. [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.

  17. 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.

  18. Arborization pattern of engrailed-positive neural lineages reveal neuromere boundaries in the Drosophila brain neuropil.

    Science.gov (United States)

    Kumar, Abhilasha; Fung, S; Lichtneckert, Robert; Reichert, Heinrich; Hartenstein, Volker

    2009-11-01

    The Drosophila brain is a highly complex structure composed of thousands of neurons that are interconnected in numerous exquisitely organized neuropil structures such as the mushroom bodies, central complex, antennal lobes, and other specialized neuropils. While the neurons of the insect brain are known to derive in a lineage-specific fashion from a stereotyped set of segmentally organized neuroblasts, the developmental origin and neuromeric organization of the neuropil formed by these neurons is still unclear. In this study we used genetic labeling techniques to characterize the neuropil innervation pattern of engrailed-expressing brain lineages of known neuromeric origin. We show that the neurons of these lineages project to and form most arborizations, in particular all of their proximal branches, in the same brain neuropil compartments in embryonic, larval and adult stages. Moreover, we show that engrailed-positive neurons of differing neuromeric origin respect boundaries between neuromere-specific compartments in the brain. This is confirmed by an analysis of the arborization pattern of empty spiracles-expressing lineages. These findings indicate that arborizations of lineages deriving from different brain neuromeres innervate a nonoverlapping set of neuropil compartments. This supports a model for neuromere-specific brain neuropil, in which a given lineage forms its proximal arborizations predominantly in the compartments that correspond to its neuromere of origin. PMID:19711412

  19. 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…

  20. 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…

  1. 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.

  2. 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.

  3. Neural Computations Mediating One-Shot Learning in the Human Brain

    OpenAIRE

    Janelle Weaver

    2015-01-01

    Much learning occurs gradually through trial and error, but rare and important experiences require one-shot learning; a new study explores how the brain switches between these two strategies for identifying causal relationships. Read the Research Article.

  4. 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.

  5. Modeling the dynamics of human brain activity with recurrent neural networks

    OpenAIRE

    Güçlü, Umut; Marcel A J van Gerven

    2016-01-01

    Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of stimuli to features (feature model) and a linear transformation of features to responses (response model). While there has been extensive work on developing better feature models, the work on developing better response models has been rather limited. Here, we...

  6. The Drosophila neural lineages: a model system to study brain development and circuitry

    OpenAIRE

    Spindler, Shana R; Hartenstein, Volker

    2010-01-01

    In Drosophila, neurons of the central nervous system are grouped into units called lineages. Each lineage contains cells derived from a single neuroblast. Due to its clonal nature, the Drosophila brain is a valuable model system to study neuron development and circuit formation. To better understand the mechanisms underlying brain development, genetic manipulation tools can be utilized within lineages to visualize, knock down, or over-express proteins. Here, we will introduce the formation an...

  7. Neural Signatures of Autism Spectrum Disorders: Insights into Brain Network Dynamics

    OpenAIRE

    Hernandez, Leanna M.; Rudie, Jeffrey D.; Green, Shulamite A.; Bookheimer, Susan; Dapretto, Mirella

    2014-01-01

    Neuroimaging investigations of autism spectrum disorders (ASDs) have advanced our understanding of atypical brain function and structure, and have recently converged on a model of altered network-level connectivity. Traditional task-based functional magnetic resonance imaging (MRI) and volume-based structural MRI studies have identified widespread atypicalities in brain regions involved in social behavior and other core ASD-related behavioral deficits. More recent advances in MR-neuroimaging ...

  8. Intravenous transplantation of bone marrow mesenchymal stem cells promotes neural regeneration after traumatic brain injury

    OpenAIRE

    Anbari, Fatemeh; Khalili, Mohammad Ali; Bahrami, Ahmad Reza; Khoradmehr, Arezoo; Sadeghian, Fatemeh; Fesahat, Farzaneh; Nabi, Ali

    2014-01-01

    To investigate the supplement of lost nerve cells in rats with traumatic brain injury by intravenous administration of allogenic bone marrow mesenchymal stem cells, this study established a Wistar rat model of traumatic brain injury by weight drop impact acceleration method and administered 3 × 106 rat bone marrow mesenchymal stem cells via the lateral tail vein. At 14 days after cell transplantation, bone marrow mesenchymal stem cells differentiated into neurons and astrocytes in injured rat...

  9. Brain

    Science.gov (United States)

    ... will return after updating. Resources Archived Modules Updates Brain Cerebrum The cerebrum is the part of the ... the outside of the brain and spinal cord. Brain Stem The brain stem is the part of ...

  10. 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.

  11. 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

  12. 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.

  13. 局部表象产生中行为性别差异的神经基础%Neural Basis of Behavioral Sex Difference during Local Image Generation

    Institute of Scientific and Technical Information of China (English)

    赵庆柏; 张小菲; 隋丹妮; 周治金; 陈其才; 周宗奎

    2013-01-01

    行为研究发现女性具有更好的局部表象产生能力,但其神经基础尚不清楚.研究采用事件相关电位技术以及小世界网络分析方法,探索局部表象产生中性别差异的大脑信息加工基础.结果显示在局部表象产生中,女性行为反应较男性更快,表象产生诱发的P300-650平均波幅更小,且大脑功能网络的平均路径长度更短.深入分析发现,反应时与脑网络的平均路径长度之间成正相关.该结果意味着低耗高效的大脑信息加工模式是女性具有更好的局部表象能力的神经基础.%Previous behavioral studies reported that females performed faster than males in generating the local details of image. However, the neural basis of behavioral sex difference during local image generation is not clear. Generally, reaction time is considered as an index of speed of brain information processing. And the small-world topology of functional brain connectivity could provide high global and local efficiency of parallel information processing. Therefore, it was speculated that stronger small-world effect underlay females' faster reaction time during local image generation. Total 28 people (14 males and 14 females) participated in the experiment and they were informed to observe a set of experimental pictures and then generate corresponding mental image to the global or local cue. The reaction time and event-related potential were recorded. The behavioral and electrophysiological data obtained in the experiment were analyzed by ANOVA and small-world measures, respectively. Results showed that females had the shorter reaction time, the smaller P300-650 amplitude and the shorter average path length of brain network in local image generation. Additionally, there was a positive correlation between the reaction time and the average path length. The present findings suggested that the lower cost and higher efficiency of brain information processing supported the better

  14. The neural basis of the abnormal self-referential processing and its impact on cognitive control in depressed patients.

    Science.gov (United States)

    Wagner, Gerd; Schachtzabel, Claudia; Peikert, Gregor; Bär, Karl-Jürgen

    2015-07-01

    Persistent pondering over negative self-related thoughts is a central feature of depressive psychopathology. In this study, we sought to investigate the neural correlates of abnormal negative self-referential processing (SRP) in patients with Major Depressive Disorder and its impact on subsequent cognitive control-related neuronal activation. We hypothesized aberrant activation dynamics during the period of negative and neutral SRP in the rostral anterior cingulate cortex (rACC) and in the amygdala in patients with major depressive disorder. Additionally, we assumed abnormal activation in the fronto-cingulate network during Stroop task execution. 19 depressed patients and 20 healthy controls participated in the study. Using an event-related functional magnetic resonance imaging (fMRI) design, negative, positive and neutral self-referential statements were displayed for 6.5 s and followed by incongruent or congruent Stroop conditions. The data were analyzed with SPM8. In contrast to controls, patients exhibited no significant valence-dependent rACC activation differences during SRP. A novel finding was the significant activation of the amygdala and the reward-processing network during presentation of neutral self-referential stimuli relative to baseline and to affective stimuli in patients. The fMRI analysis of the Stroop task revealed a reduced BOLD activation in the right fronto-parietal network of patients in the incongruent condition after negative SRP only. Thus, the inflexible activation in the rACC may correspond to the inability of depressed patients to shift their attention away from negative self-related stimuli. The accompanying negative affect and task-irrelevant emotional processing may compete for neuronal resources with cognitive control processes and lead thereby to deficient cognitive performance associated with decreased fronto-parietal activation. PMID:25872899

  15. Transcriptomic gene-network analysis of exposure to silver nanoparticle reveals potentially neurodegenerative progression in mouse brain neural cells.

    Science.gov (United States)

    Lin, Ho-Chen; Huang, Chin-Lin; Huang, Yuh-Jeen; Hsiao, I-Lun; Yang, Chung-Wei; Chuang, Chun-Yu

    2016-08-01

    Silver nanoparticles (AgNPs) are commonly used in daily living products. AgNPs can induce inflammatory response in neuronal cells, and potentially develop neurological disorders. The gene networks in response to AgNPs-induced neurodegenerative progression have not been clarified in various brain neural cells. This study found that 3-5nm AgNPs were detectable to enter the nuclei of mouse neuronal cells after 24-h of exposure. The differentially expressed genes in mouse brain neural cells exposure to AgNPs were further identified using Phalanx Mouse OneArray® chip, and permitted to explore the gene network pathway regulating in neurodegenerative progression according to Cytoscape analysis. In focal adhesion pathway of ALT astrocytes, AgNPs induced the gene expression of RasGRF1 and reduced its downstream BCL2 gene for apoptosis. In cytosolic DNA sensing pathway of microglial BV2 cells, AgNPs reduced the gene expression of TREX1 and decreased IRF7 to release pro-inflammatory cytokines for inflammation and cellular activation. In MAPK pathway of neuronal N2a cells, AgNPs elevated GADD45α gene expression, and attenuated its downstream PTPRR gene to interfere with neuron growth and differentiation. Moreover, AgNPs induced beta amyloid deposition in N2a cells, and decreased PSEN1 and PSEN2, which may disrupt calcium homeostasis and presynaptic dysfunction for Alzheimer's disease development. These findings suggested that AgNPs exposure reveals the potency to induce the progression of neurodegenerative disorder. PMID:27131904

  16. 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.

  17. 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.

  18. Where in the Brain Is Depression?

    OpenAIRE

    Pandya, Mayur; Altinay, Murat; Malone, Donald A; Anand, Amit

    2012-01-01

    Major Depressive Disorder is a serious medical illness which is responsible for considerable morbidity and disability. Despite decades of research, the neural basis for depression is still incompletely understood. In this review, evidence from neuroimaging, neuropsychiatric and brain stimulations studies are explored to answer the question regarding the localization of depression in the brain. Neuroimaging studies indicate that although many regions of the brain have been repeatedly implicate...

  19. Common and distinct neural targets of treatment: changing brain function in substance addiction

    OpenAIRE

    Konova, Anna B.; Moeller, Scott J.; Goldstein, Rita Z.

    2013-01-01

    Neuroimaging offers an opportunity to examine the neurobiological effects of therapeutic interventions for human drug addiction. Using activation likelihood estimation, the aim of the current meta-analysis was to quantitatively summarize functional neuroimaging studies of pharmacological and cognitive-based interventions for drug addiction, with an emphasis on their common and distinct neural targets. More exploratory analyses also contrasted subgroups of studies based on specific study and s...

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

    Science.gov (United States)

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

    2012-01-01

    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.

  1. Plasticity in the neural coding of auditory space in the mammalian brain

    Science.gov (United States)

    King, Andrew J.; Parsons, Carl H.; Moore, David R.

    2000-10-01

    Sound localization relies on the neural processing of monaural and binaural spatial cues that arise from the way sounds interact with the head and external ears. Neurophysiological studies of animals raised with abnormal sensory inputs show that the map of auditory space in the superior colliculus is shaped during development by both auditory and visual experience. An example of this plasticity is provided by monaural occlusion during infancy, which leads to compensatory changes in auditory spatial tuning that tend to preserve the alignment between the neural representations of visual and auditory space. Adaptive changes also take place in sound localization behavior, as demonstrated by the fact that ferrets raised and tested with one ear plugged learn to localize as accurately as control animals. In both cases, these adjustments may involve greater use of monaural spectral cues provided by the other ear. Although plasticity in the auditory space map seems to be restricted to development, adult ferrets show some recovery of sound localization behavior after long-term monaural occlusion. The capacity for behavioral adaptation is, however, task dependent, because auditory spatial acuity and binaural unmasking (a measure of the spatial contribution to the "cocktail party effect") are permanently impaired by chronically plugging one ear, both in infancy but especially in adulthood. Experience-induced plasticity allows the neural circuitry underlying sound localization to be customized to individual characteristics, such as the size and shape of the head and ears, and to compensate for natural conductive hearing losses, including those associated with middle ear disease in infancy.

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

    Directory of Open Access Journals (Sweden)

    Hackjin Kim

    2006-07-01

    Full Text Available 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.

  3. Neural network of Gaussian radial basis functions applied to the problem of identification of nuclear accidents in a PWR nuclear power plant

    International Nuclear Information System (INIS)

    Highlights: • It is presented a new method based on Artificial Neural Network (ANN) developed to deal with accident identification in PWR nuclear power plants. • Obtained results have shown the efficiency of the referred technique. • Results obtained with this method are as good as or even better to similar optimization tools available in the literature. - Abstract: The task of monitoring a nuclear power plant consists on determining, continuously and in real time, the state of the plant’s systems in such a way to give indications of abnormalities to the operators and enable them to recognize anomalies in system behavior. The monitoring is based on readings of a large number of meters and alarm indicators which are located in the main control room of the facility. On the occurrence of a transient or of an accident on the nuclear power plant, even the most experienced operators can be confronted with conflicting indications due to the interactions between the various components of the plant systems; since a disturbance of a system can cause disturbances on another plant system, thus the operator may not be able to distinguish what is cause and what is the effect. This cognitive overload, to which operators are submitted, causes a difficulty in understanding clearly the indication of an abnormality in its initial phase of development and in taking the appropriate and immediate corrective actions to face the system failure. With this in mind, computerized monitoring systems based on artificial intelligence that could help the operators to detect and diagnose these failures have been devised and have been the subject of research. Among the techniques that can be used in such development, radial basis functions (RBFs) neural networks play an important role due to the fact that they are able to provide good approximations to functions of a finite number of real variables. This paper aims to present an application of a neural network of Gaussian radial basis

  4. Neural substrates of driving behaviour

    OpenAIRE

    Spiers, H. J.; Maguire, E. A.

    2007-01-01

    Driving a vehicle is an indispensable daily behaviour for many people, yet we know little about how it is supported by the brain. Given that driving in the real world involves the engagement of many cognitive systems that rapidly change to meet varying environmental demands, identifying its neural basis presents substantial problems. By employing a unique combination of functional magnetic resonance imaging (fMRI), an accurate interactive virtual simulation of a bustling central London (UK) a...

  5. Elevation of brain glucose and polyol-pathway intermediates with accompanying brain-copper deficiency in patients with Alzheimer’s disease: metabolic basis for dementia

    OpenAIRE

    Jingshu Xu; Paul Begley; Stephanie J. Church; Stefano Patassini; Selina McHarg; Nina Kureishy; Hollywood, Katherine A; Waldvogel, Henry J; Hong Liu; Shaoping Zhang; Wanchang Lin; Karl Herholz; Clinton Turner; Synek, Beth J.; Curtis, Maurice A.

    2016-01-01

    Impairment of brain-glucose uptake and brain-copper regulation occurs in Alzheimer’s disease (AD). Here we sought to further elucidate the processes that cause neurodegeneration in AD by measuring levels of metabolites and metals in brain regions that undergo different degrees of damage. We employed mass spectrometry (MS) to measure metabolites and metals in seven post-mortem brain regions of nine AD patients and nine controls, and plasma-glucose and plasma-copper levels in an ante-mortem cas...

  6. 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.

  7. 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

    2009-01-01

    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…

  8. 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 ...

  9. Structural MRI studies of language function in the undamaged brain

    OpenAIRE

    Richardson, F. M.; Price, C.J.

    2009-01-01

    In recent years, the demonstration that structural changes can occur in the human brain beyond those associated with development, ageing and neuropathology has revealed a new approach to studying the neural basis of behaviour. In this review paper, we focus on structural imaging studies of language that have utilised behavioural measures in order to investigate the neural correlates of language skills in the undamaged brain. We report studies that have used two different techniques: voxel-bas...

  10. Influence of hyperbaric oxygen on the differentiation of hypoxic/ischemic brain-derived neural stem cells

    Institute of Scientific and Technical Information of China (English)

    Zhengrong Peng; Sue Wang; Pingtian Xiao

    2009-01-01

    BACKGROUND: It has been previously shown that hyperbaric oxygen may promote proliferation of neural stem cells and reduce death of endogenous neural stem cells (NSCs).OBJECTIVE: To explore the effects of hyperbaric oxygen on the differentiation of hypoxic/ischemic brain-derived NSCs into neuron-like cells and compare with high-concentration oxygen and high pressure.DESIGN, TIME AND SETTING: An in vitro contrast study, performed at Laboratory of Neurology,Central South University between January and May 2006.MATERIALS: A hyperbaric oxygen chamber (YLC 0.5/1A) was provided by Wuhan Shipping Design Research Institute; mouse anti-rat microtubute-associated protein 2 monoclonal antibody by Jingmei Company, Beijing; mouse anti-rat glial fibrillary acidic protein monoclonal antibody by Neo Markers,USA; mouse anti-rat galactocerebroside monoclonal antibody by Santa Cruz Biotechnology Inc.,USA; and goat anti-mouse fluorescein isothiocyanate-labeled secondary antibody by Wuhan Boster Bioengineering Co., Ltd., China.METHODS: Brain-derived NSCs isolated from brain tissues of neonatal Sprague Dawiey rats werecloned and passaged, and assigned into five groups: normal control, model, high-concentration oxygen, high pressure, and hyperbaric oxygen groups. Cells in the four groups, excluding the normal control group, were incubated in serum-containing DMEM/F12 culture medium. Hypoxic/ischemic models of NSCs were established in an incubator comprising 93% N2, 5% CO2, and 2% O2.Thereafter, cells were continuously cultured as follows: compressed air (0.2 MPa, 1 hour, once a day)in the high pressure group, compressed air+a minimum of 80% O2 in the hyperbaric oxygen group,and a minimum of 80% O2 in the high-concentration oxygen group. Cells in the normal control and model groups were cultured as normal.MAIN OUTCOME MEASURES: At day 7 after culture, glial fibrillary acidic protein,microtubule-associated protein 2, and galactocerebroside immunofluorescence staining were examined to

  11. Human fetal brain-derived neural stem/progenitor cells grafted into the adult epileptic brain restrain seizures in rat models of temporal lobe epilepsy.

    Directory of Open Access Journals (Sweden)

    Haejin Lee

    Full Text Available Cell transplantation has been suggested as an alternative therapy for temporal lobe epilepsy (TLE because this can suppress spontaneous recurrent seizures in animal models. To evaluate the therapeutic potential of human neural stem/progenitor cells (huNSPCs for treating TLE, we transplanted huNSPCs, derived from an aborted fetal telencephalon at 13 weeks of gestation and expanded in culture as neurospheres over a long time period, into the epileptic hippocampus of fully kindled and pilocarpine-treated adult rats exhibiting TLE. In vitro, huNSPCs not only produced all three central nervous system neural cell types, but also differentiated into ganglionic eminences-derived γ-aminobutyric acid (GABA-ergic interneurons and released GABA in response to the depolarization induced by a high K+ medium. NSPC grafting reduced behavioral seizure duration, afterdischarge duration on electroencephalograms, and seizure stage in the kindling model, as well as the frequency and the duration of spontaneous recurrent motor seizures in pilocarpine-induced animals. However, NSPC grafting neither improved spatial learning or memory function in pilocarpine-treated animals. Following transplantation, grafted cells showed extensive migration around the injection site, robust engraftment, and long-term survival, along with differentiation into β-tubulin III+ neurons (∼34%, APC-CC1+ oligodendrocytes (∼28%, and GFAP+ astrocytes (∼8%. Furthermore, among donor-derived cells, ∼24% produced GABA. Additionally, to explain the effect of seizure suppression after NSPC grafting, we examined the anticonvulsant glial cell-derived neurotrophic factor (GDNF levels in host hippocampal astrocytes and mossy fiber sprouting into the supragranular layer of the dentate gyrus in the epileptic brain. Grafted cells restored the expression of GDNF in host astrocytes but did not reverse the mossy fiber sprouting, eliminating the latter as potential mechanism. These results suggest

  12. In-Vivo Characterization of Glassy Carbon Micro-Electrode Arrays for Neural Applications and Histological Analysis of the Brain Tissue

    Science.gov (United States)

    Vomero, Maria

    The aim of this work is to fabricate and characterize glassy carbon Microelectrode Arrays (MEAs) for sensing and stimulating neural activity, and conduct histological analysis of the brain tissue after the implant to determine long-term performance. Neural applications often require robust electrical and electrochemical response over a long period of time, and for those applications we propose to replace the commonly used noble metals like platinum, gold and iridium with glassy carbon. We submit that such material has the potential to improve the performances of traditional neural prostheses, thanks to better charge transfer capabilities and higher electrochemical stability. Great interest and attention is given in this work, in particular, to the investigation of tissue response after several weeks of implants in rodents' brain motor cortex and the associated materials degradation. As part of this work, a new set of devices for Electrocorticography (ECoG) has been designed and fabricated to improve durability and quality of the previous generation of devices, designed and manufactured by the same research group in 2014. In-vivo long-term impedance measurements and brain activity recordings were performed to test the functionality of the neural devices. In-vitro electrical characterization of the carbon electrodes, as well as the study of the adhesion mechanisms between glassy carbon and different substrates is also part of the research described in this book.

  13. THEORY OF MIND AND THE WHOLE BRAIN FUNCTIONAL CONNECTIVITY: BEHAVIORAL AND NEURAL EVIDENCES WITH THE AMSTERDAM RESTING STATE QUESTIONNAIRE

    Directory of Open Access Journals (Sweden)

    ANTONELLA eMARCHETTI

    2015-12-01

    Full Text Available A topic of common interest to psychologists and philosophers is the spontaneous flow of thoughts when the individual is awake but not involved in cognitive demands. This argument, classically referred to as the stream of consciousness of James, is now known in the psychological literature as Mind-Wandering. Although of great interest, this construct has been scarcely investigated so far. Diaz and colleagues (2013 created the Amsterdam Resting State Questionnaire (ARSQ, composed of 27 items, distributed in seven factors: discontinuity of mind, theory of mind (ToM, self, planning, sleepiness, comfort and somatic awareness. The present study aims at: testing psychometric properties of the ARSQ in a sample of 670 Italian subjects; exploring the neural correlates of a subsample of participants (N=28 divided into two groups on the basis of the scores obtained in the ToM factor. Results show a satisfactory reliability of the original factional structure in the Italian sample. In the subjects with a high mean in the ToM factor compared to low mean subjects, functional MRI revealed: a network (48 nodes with higher functional connectivity (FC with a dominance of the left hemisphere; an increased within-lobe FC in frontal and insular lobes. In both neural and behavioral terms, our results support the idea that the mind, which does not rest even when explicitly asked to do so, has various and interesting mentalistic-like contents.

  14. Transplantation of human neural stem/progenitor cells overexpressing galectin-1 improves functional recovery from focal brain ischemia in the mongolian gerbil

    Directory of Open Access Journals (Sweden)

    Yamane Junichi

    2011-09-01

    Full Text Available Abstract Transplantation of human neural stem/progenitor cells (hNSPCs is a promising method to regenerate tissue from damage and recover function in various neurological diseases including brain ischemia. Galectin-1(Gal1 is a lectin that is expressed in damaged brain areas after ischemia. Here, we characterized the detailed Gal1 expression pattern in an animal model of brain ischemia. After brain ischemia, Gal1 was expressed in reactive astrocytes within and around the infarcted region, and its expression diminished over time. Previously, we showed that infusion of human Gal1 protein (hGal1 resulted in functional recovery after brain ischemia but failed to reduce the volume of the ischemic region. This prompted us to examine whether the combination of hNSPCs-transplantation and stable delivery of hGal1 around the ischemic region could reduce the ischemic volume and promote better functional recovery after brain ischemia. In this study, we transplanted hNSPCs that stably overexpressed hGal1 (hGal1-hNSPCs in a model of unilateral focal brain ischemia using Mongolian gerbils. Indeed, we found that transplantation of hGal1-hNSPCs both reduced the ischemic volume and improved deficits in motor function after brain ischemia to a greater extent than the transplantation of hNSPCs alone. This study provides evidence for a potential application of hGal1 with hNSPCs-transplantation in the treatment of brain ischemia.

  15. Hyperbaric oxygen treatment promotes neural stem cell proliferation in the subventricular zone of neonatal rats with hypoxic-ischemic brain damage

    Institute of Scientific and Technical Information of China (English)

    Zhichun Feng; Jing Liu; Rong Ju

    2013-01-01

    Hyperbaric oxygen therapy for the treatment of neonatal hypoxic-ischemic brain damage has been used clinically for many years, but its effectiveness remains controversial. In addition, the mechanism of this potential neuroprotective effect remains unclear. This study aimed to investigate the influence of hyperbaric oxygen on the proliferation of neural stem cells in the subventricular zone of neonatal Sprague-Dawley rats (7 days old) subjected to hypoxic-ischemic brain damage. Six hours after modeling, rats were treated with hyperbaric oxygen once daily for 7 days. Immunohistochemistry revealed that the number of 5-bromo-2′-deoxyuridine positive and nestin positive cells in the subventricular zone of neonatal rats increased at day 3 after hypoxic-ischemic brain damage and peaked at day 5. After hyperbaric oxygen treatment, the number of 5-bromo-2′- deoxyuridine positive and nestin positive cells began to increase at day 1, and was significantly higher than that in normal rats and model rats until day 21. Hematoxylin-eosin staining showed that hyperbaric oxygen treatment could attenuate pathological changes to brain tissue in neonatal rats, and reduce the number of degenerating and necrotic nerve cells. Our experimental findings indicate that hyperbaric oxygen treatment enhances the proliferation of neural stem cells in the subventricular zone of neonatal rats with hypoxic-ischemic brain damage, and has therapeutic potential for promoting neurological recovery following brain injury.

  16. Neural stem cells and neuro/gliogenesis in the central nervous system: understanding the structural and functional plasticity of the developing, mature, and diseased brain.

    Science.gov (United States)

    Yamaguchi, Masahiro; Seki, Tatsunori; Imayoshi, Itaru; Tamamaki, Nobuaki; Hayashi, Yoshitaka; Tatebayashi, Yoshitaka; Hitoshi, Seiji

    2016-05-01

    Neurons and glia in the central nervous system (CNS) originate from neural stem cells (NSCs). Knowledge of the mechanisms of neuro/gliogenesis from NSCs is fundamental to our understanding of how complex brain architecture and function develop. NSCs are present not only in the developing brain but also in the mature brain in adults. Adult neurogenesis likely provides remarkable plasticity to the mature brain. In addition, recent progress in basic research in mental disorders suggests an etiological link with impaired neuro/gliogenesis in particular brain regions. Here, we review the recent progress and discuss future directions in stem cell and neuro/gliogenesis biology by introducing several topics presented at a joint meeting of the Japanese Association of Anatomists and the Physiological Society of Japan in 2015. Collectively, these topics indicated that neuro/gliogenesis from NSCs is a common event occurring in many brain regions at various ages in animals. Given that significant structural and functional changes in cells and neural networks are accompanied by neuro/gliogenesis from NSCs and the integration of newly generated cells into the network, stem cell and neuro/gliogenesis biology provides a good platform from which to develop an integrated understanding of the structural and functional plasticity that underlies the development of the CNS, its remodeling in adulthood, and the recovery from diseases that affect it. PMID:26578509

  17. 径向基神经网络预测氯氮平血药浓度%Plasma Concentration of Clozapine Predicted by Radial Basis Function Neural Networks

    Institute of Scientific and Technical Information of China (English)

    刘朝晖; 黄榕波; 陈庆强; 温预关; 李明亚

    2011-01-01

    目的:评价用径向基(RBF)神经网络所建立的预测氯氮平稳态血药浓度模型的预测性能.方法:将数据分为训练集、校验集和测试集来建立获取输入、输出变量两者间关系的RBF网络模型,其中以患者的性别、年龄、体重、剂量、血压、多项生理生化指标等37项参数为输入变量,氯氮平稳态血药浓度为输出变量.用训练集和校验集的网络计算输出值与目标输出值之间的均方差(MSE)和相关系数(R)来综合评价网络模型的学习效果,用测试集的网络计算输出值与目标输出值之间的MSE和R来评价网络模型的预测性能.结果:当扩展系数(SP)值为3.0时,训练集的MSE为1.33 ×10(-5),R值为0.99985,校验集的MSE为0.002 833,R值为0.971 86,测试集的MSE为0.005 439,R值为0.93676,网络模型的预测效果和泛化能力较好.结论:RBF网络用于预测氯氮平稳态血药浓度的研究是可行和有效的.%OBJECTIVE: To evaluate the performance of a model for predicting the steady-state plasma concentration of clozapine established by radial basis function (RBF) neural network. METHODS: The data was divided into training set, validation set and test set to establish the RBF neural network model which had obtained the relationships between input variables and output variable. Input variables included 37 parameters, such as patients' gender, age, body weight, dosage, blood pressure and multiple physiological and biochemical indexes. Output variable was steady-state plasma concentration of clozapine. The effect of RBF neural network model was evaluated comprehensively using mean square (MSE) and coefficient correlation (R) between the computed output value and objective output value of training set and validation set. And predictive performance of the model was evaluated by MSE and R between the computed output value and objective output value of test set. RESULTS: When the value of SP was 3.0, the MSE and R values of the

  18. 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.

  19. The cell biology of neural stem and progenitor cells and its significance for their proliferation versus differentiation during mammalian brain development.

    Science.gov (United States)

    Farkas, Lilla M; Huttner, Wieland B

    2008-12-01

    The switch of neural stem and progenitor cells from proliferation to differentiation during development is a crucial determinant of brain size. This switch is intimately linked to the architecture of the two principal classes of neural stem and progenitor cells, the apical (neuroepithelial, radial glial) and basal (intermediate) progenitors, which in turn is crucial for their symmetric versus asymmetric divisions. Focusing on the developing rodent neocortex, we discuss here recent advances in understanding the cell biology of apical and basal progenitors, place key regulatory molecules into subcellular context, and highlight their roles in the control of proliferation versus differentiation. PMID:18930817

  20. 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.