Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.

Science.gov (United States)

Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E

2017-05-01

Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.

Neural substrates of trait impulsivity, anhedonia, and irritability: Mechanisms of heterotypic comorbidity between externalizing disorders and unipolar depression.

Science.gov (United States)

Zisner, Aimee; Beauchaine, Theodore P

2016-11-01

Trait impulsivity, which is often defined as a strong preference for immediate over delayed rewards and results in behaviors that are socially inappropriate, maladaptive, and short-sighted, is a predisposing vulnerability to all externalizing spectrum disorders. In contrast, anhedonia is characterized by chronically low motivation and reduced capacity to experience pleasure, and is common to depressive disorders. Although externalizing and depressive disorders have virtually nonoverlapping diagnostic criteria in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders, heterotypic comorbidity between them is common. Here, we review common neural substrates of trait impulsivity, anhedonia, and irritability, which include both low tonic mesolimbic dopamine activity and low phasic mesolimbic dopamine responding to incentives during reward anticipation and associative learning. We also consider how other neural networks, including bottom-up emotion generation systems and top-down emotion regulation systems, interact with mesolimbic dysfunction to result in alternative manifestations of psychiatric illness. Finally, we present a model that emphasizes a translational, transdiagnostic approach to understanding externalizing/depression comorbidity. This model should refine ways in which internalizing and externalizing disorders are studied, classified, and treated.

Anticipation of high arousal aversive and positive movie clips engages common and distinct neural substrates.

Science.gov (United States)

Greenberg, Tsafrir; Carlson, Joshua M; Rubin, Denis; Cha, Jiook; Mujica-Parodi, Lilianne

2015-04-01

The neural correlates of anxious anticipation have been primarily studied with aversive and neutral stimuli. In this study, we examined the effect of valence on anticipation by using high arousal aversive and positive stimuli and a condition of uncertainty (i.e. either positive or aversive). The task consisted of predetermined cues warning participants of upcoming aversive, positive, 'uncertain' (either aversive or positive) and neutral movie clips. Anticipation of all affective clips engaged common regions including the anterior insula, dorsal anterior cingulate cortex, thalamus, caudate, inferior parietal and prefrontal cortex that are associated with emotional experience, sustained attention and appraisal. In contrast, the nucleus accumbens and medial prefrontal cortex, regions implicated in reward processing, were selectively engaged during anticipation of positive clips (depicting sexually explicit content) and the mid-insula, which has been linked to processing aversive stimuli, was selectively engaged during anticipation of aversive clips (depicting graphic medical procedures); these three areas were also activated during anticipation of 'uncertain' clips reflecting a broad preparatory response for both aversive and positive stimuli. These results suggest that a common circuitry is recruited in anticipation of affective clips regardless of valence, with additional areas preferentially engaged depending on whether expected stimuli are negative or positive. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

The structural neural substrate of subjective happiness.

Science.gov (United States)

Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Kubota, Yasutaka; Sawada, Reiko; Yoshimura, Sayaka; Toichi, Motomi

2015-11-20

Happiness is a subjective experience that is an ultimate goal for humans. Psychological studies have shown that subjective happiness can be measured reliably and consists of emotional and cognitive components. However, the neural substrates of subjective happiness remain unclear. To investigate this issue, we used structural magnetic resonance imaging and questionnaires that assessed subjective happiness, the intensity of positive and negative emotional experiences, and purpose in life. We found a positive relationship between the subjective happiness score and gray matter volume in the right precuneus. Moreover, the same region showed an association with the combined positive and negative emotional intensity and purpose in life scores. Our findings suggest that the precuneus mediates subjective happiness by integrating the emotional and cognitive components of happiness.

Critical Neural Substrates for Correcting Unexpected Trajectory Errors and Learning from Them

Science.gov (United States)

Mutha, Pratik K.; Sainburg, Robert L.; Haaland, Kathleen Y.

2011-01-01

Our proficiency at any skill is critically dependent on the ability to monitor our performance, correct errors and adapt subsequent movements so that errors are avoided in the future. In this study, we aimed to dissociate the neural substrates critical for correcting unexpected trajectory errors and learning to adapt future movements based on…

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

2014-06-17

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

Distinct neural substrates of visuospatial and verbal-analytic reasoning as assessed by Raven's Advanced Progressive Matrices.

Science.gov (United States)

Chen, Zhencai; De Beuckelaer, Alain; Wang, Xu; Liu, Jia

2017-11-24

Recent studies revealed spontaneous neural activity to be associated with fluid intelligence (gF) which is commonly assessed by Raven's Advanced Progressive Matrices, and embeds two types of reasoning: visuospatial and verbal-analytic reasoning. With resting-state fMRI data, using global brain connectivity (GBC) analysis which averages functional connectivity of a voxel in relation to all other voxels in the brain, distinct neural correlates of these two reasoning types were found. For visuospatial reasoning, negative correlations were observed in both the primary visual cortex (PVC) and the precuneus, and positive correlations were observed in the temporal lobe. For verbal-analytic reasoning, negative correlations were observed in the right inferior frontal gyrus (rIFG), dorsal anterior cingulate cortex and temporoparietal junction, and positive correlations were observed in the angular gyrus. Furthermore, an interaction between GBC value and type of reasoning was found in the PVC, rIFG and the temporal lobe. These findings suggest that visuospatial reasoning benefits more from elaborate perception to stimulus features, whereas verbal-analytic reasoning benefits more from feature integration and hypothesis testing. In sum, the present study offers, for different types of reasoning in gF, first empirical evidence of separate neural substrates in the resting brain.

Neural substrates of approach-avoidance conflict decision-making

Science.gov (United States)

Aupperle, Robin L.; Melrose, Andrew J.; Francisco, Alex; Paulus, Martin P.; Stein, Murray B.

2014-01-01

Animal approach-avoidance conflict paradigms have been used extensively to operationalize anxiety, quantify the effects of anxiolytic agents, and probe the neural basis of fear and anxiety. Results from human neuroimaging studies support that a frontal-striatal-amygdala neural circuitry is important for approach-avoidance learning. However, the neural basis of decision-making is much less clear in this context. Thus, we combined a recently developed human approach-avoidance paradigm with functional magnetic resonance imaging (fMRI) to identify neural substrates underlying approach-avoidance conflict decision-making. Fifteen healthy adults completed the approach-avoidance conflict (AAC) paradigm during fMRI. Analyses of variance were used to compare conflict to non-conflict (avoid-threat and approach-reward) conditions and to compare level of reward points offered during the decision phase. Trial-by-trial amplitude modulation analyses were used to delineate brain areas underlying decision-making in the context of approach/avoidance behavior. Conflict trials as compared to the non-conflict trials elicited greater activation within bilateral anterior cingulate cortex (ACC), anterior insula, and caudate, as well as right dorsolateral prefrontal cortex. Right caudate and lateral PFC activation was modulated by level of reward offered. Individuals who showed greater caudate activation exhibited less approach behavior. On a trial-by-trial basis, greater right lateral PFC activation related to less approach behavior. Taken together, results suggest that the degree of activation within prefrontal-striatal-insula circuitry determines the degree of approach versus avoidance decision-making. Moreover, the degree of caudate and lateral PFC activation is related to individual differences in approach-avoidance decision-making. Therefore, the AAC paradigm is ideally suited to probe anxiety-related processing differences during approach-avoidance decision-making. PMID:25224633

A common neural substrate for perceiving and knowing about color

Science.gov (United States)

Simmons, W. Kyle; Ramjee, Vimal; Beauchamp, Michael S.; McRae, Ken; Martin, Alex; Barsalou, Lawrence W.

2013-01-01

Functional neuroimaging research has demonstrated that retrieving information about object-associated colors activates the left fusiform gyrus in posterior temporal cortex. Although regions near the fusiform have previously been implicated in color perception, it remains unclear whether color knowledge retrieval actually activates the color perception system. Evidence to this effect would be particularly strong if color perception cortex was activated by color knowledge retrieval triggered strictly with linguistic stimuli. To address this question, subjects performed two tasks while undergoing fMRI. First, subjects performed a property verification task using only words to assess conceptual knowledge. On each trial, subjects verified whether a named color or motor property was true of a named object (e.g., TAXI-yellow, HAIR-combed). Next, subjects performed a color perception task. A region of the left fusiform gyrus that was highly responsive during color perception also showed greater activity for retrieving color than motor property knowledge. These data provide the first evidence for a direct overlap in the neural bases of color perception and stored information about object-associated color, and they significantly add to accumulating evidence that conceptual knowledge is grounded in the brain’s modality-specific systems. PMID:17575989

Neural Substrates of Similarity and Rule-based Strategies in Judgment

Directory of Open Access Journals (Sweden)

Bettina eVon Helversen

2014-10-01

Full Text Available Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI, we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved.

Functionally segregated neural substrates for arbitrary audiovisual paired-association learning.

Science.gov (United States)

Tanabe, Hiroki C; Honda, Manabu; Sadato, Norihiro

2005-07-06

To clarify the neural substrates and their dynamics during crossmodal association learning, we conducted functional magnetic resonance imaging (MRI) during audiovisual paired-association learning of delayed matching-to-sample tasks. Thirty subjects were involved in the study; 15 performed an audiovisual paired-association learning task, and the remainder completed a control visuo-visual task. Each trial consisted of the successive presentation of a pair of stimuli. Subjects were asked to identify predefined audiovisual or visuo-visual pairs by trial and error. Feedback for each trial was given regardless of whether the response was correct or incorrect. During the delay period, several areas showed an increase in the MRI signal as learning proceeded: crossmodal activity increased in unimodal areas corresponding to visual or auditory areas, and polymodal responses increased in the occipitotemporal junction and parahippocampal gyrus. This pattern was not observed in the visuo-visual intramodal paired-association learning task, suggesting that crossmodal associations might be formed by binding unimodal sensory areas via polymodal regions. In both the audiovisual and visuo-visual tasks, the MRI signal in the superior temporal sulcus (STS) in response to the second stimulus and feedback peaked during the early phase of learning and then decreased, indicating that the STS might be key to the creation of paired associations, regardless of stimulus type. In contrast to the activity changes in the regions discussed above, there was constant activity in the frontoparietal circuit during the delay period in both tasks, implying that the neural substrates for the formation and storage of paired associates are distinct from working memory circuits.

Shared neural substrates of apraxia and aphasia.

Science.gov (United States)

Goldenberg, Georg; Randerath, Jennifer

2015-08-01

Apraxia is regularly associated with aphasia, but there is controversy whether their co-occurrence is the expression of a common basic deficit or results from anatomical proximity of their neural substrates. However, neither aphasia nor apraxia is an indivisible entity. Both diagnoses embrace diverse manifestations that may occur more or less independently from each other. Thus, the question whether apraxia is always accompanied by aphasia may lead to conflicting answers depending on which of their manifestations are considered. We used voxel based lesion symptom mapping (VLSM) for exploring communalities between lesion sites associated with aphasia and with apraxia. Linguistic impairment was assessed by the Aachen Aphasia Test (AAT) subtests naming, comprehension, repetition, written language, and Token Test. Apraxia was examined for imitation of meaningless hand and finger postures and for pantomime of tool use. There were two areas of overlap between aphasia and apraxia. Lesions in the anterior temporal lobe interfered with pantomime of tool use and with all linguistic tests. In the left inferior parietal lobe there was a large area where lesions were associated with defective imitation of hand postures and with poor scores on written language and the Token Test. Within this large area there were also two spots in supramarginal and angular gyrus where lesions were also associated with defective pantomime. We speculate that the coincidence of language impairment and defective pantomime after anterior temporal lesions is due to impaired access to semantic memory. The combination of defective imitation of hand postures with poor scores on Token Test and written language is not easily compatible with a crucial role of parietal regions for the conversion of concepts of intended actions into motor commands. It accords better with a role of left inferior parietal lobe regions for the categorical perception of spatial relationships. Copyright © 2015 Elsevier Ltd. All

A potential neural substrate for processing functional classes of complex acoustic signals.

Directory of Open Access Journals (Sweden)

Isabelle George

Full Text Available Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

Rebalancing the Addicted Brain: Oxytocin Interference with the Neural Substrates of Addiction.

Science.gov (United States)

Bowen, Michael T; Neumann, Inga D

2017-12-01

Drugs that act on the brain oxytocin (OXT) system may provide a much-needed treatment breakthrough for substance-use disorders. Targeting the brain OXT system has the potential to treat addiction to all major classes of addictive substance and to intervene across all stages of the addiction cycle. Emerging evidence suggests that OXT is able to interfere with such a wide range of addictive behaviours for such a wide range of addictive substances by rebalancing core neural systems that become dysregulated over the course of addiction. By improving our understanding of these interactions between OXT and the neural substrates of addiction, we will not only improve our understanding of addiction, but also our ability to effectively treat these devastating disorders. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visuospatial planning in unmedicated major depressive disorder and bipolar disorder : distinct and common neural correlates

NARCIS (Netherlands)

Rive, M. M.; Koeter, M. W. J.; Veltman, D. J.; Schene, A. H.; Ruhe, H. G.

Background Cognitive impairments are an important feature of both remitted and depressed major depressive disorder (MDD) and bipolar disorder (BD). In particular, deficits in executive functioning may hamper everyday functioning. Identifying the neural substrates of impaired executive functioning

Losing the rose tinted glasses: neural substrates of unbiased belief updating in depression

Directory of Open Access Journals (Sweden)

Neil eGarrett

2014-08-01

Full Text Available Recent evidence suggests that a state of good mental health is associated with biased processing of information that supports a positively skewed view of the future. Depression, on the other hand, is associated with unbiased processing of such information. Here, we use brain imaging in conjunction with a belief update task administered to clinically depressed patients and healthy controls to characterize brain activity that supports unbiased belief updating in clinically depressed individuals. Our results reveal that unbiased belief updating in depression is mediated by strong neural coding of estimation errors in response to both good news (in left inferior frontal gyrus and bilateral superior frontal gyrus and bad news (in right inferior parietal lobule and right inferior frontal gyrus regarding the future. In contrast, intact mental health was linked to a relatively attenuated neural coding of bad news about the future. These findings identify a neural substrate mediating the breakdown of biased updating in Major Depression Disorder, which may be essential for mental health.

Neural substrates of decision-making.

Science.gov (United States)

Broche-Pérez, Y; Herrera Jiménez, L F; Omar-Martínez, E

2016-06-01

Decision-making is the process of selecting a course of action from among 2 or more alternatives by considering the potential outcomes of selecting each option and estimating its consequences in the short, medium and long term. The prefrontal cortex (PFC) has traditionally been considered the key neural structure in decision-making process. However, new studies support the hypothesis that describes a complex neural network including both cortical and subcortical structures. The aim of this review is to summarise evidence on the anatomical structures underlying the decision-making process, considering new findings that support the existence of a complex neural network that gives rise to this complex neuropsychological process. Current evidence shows that the cortical structures involved in decision-making include the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). This process is assisted by subcortical structures including the amygdala, thalamus, and cerebellum. Findings to date show that both cortical and subcortical brain regions contribute to the decision-making process. The neural basis of decision-making is a complex neural network of cortico-cortical and cortico-subcortical connections which includes subareas of the PFC, limbic structures, and the cerebellum. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

Sleep modulates the neural substrates of both spatial and contextual memory consolidation.

Directory of Open Access Journals (Sweden)

Géraldine Rauchs

Full Text Available It is known that sleep reshapes the neural representations that subtend the memories acquired while navigating in a virtual environment. However, navigation is not process-pure, as manifold learning components contribute to performance, notably the spatial and contextual memory constituents. In this context, it remains unclear whether post-training sleep globally promotes consolidation of all of the memory components embedded in virtual navigation, or rather favors the development of specific representations. Here, we investigated the effect of post-training sleep on the neural substrates of the consolidation of spatial and contextual memories acquired while navigating in a complex 3D, naturalistic virtual town. Using fMRI, we mapped regional cerebral activity during various tasks designed to tap either the spatial or the contextual memory component, or both, 72 h after encoding with or without sleep deprivation during the first post-training night. Behavioral performance was not dependent upon post-training sleep deprivation, neither in a natural setting that engages both spatial and contextual memory processes nor when looking more specifically at each of these memory representations. At the neuronal level however, analyses that focused on contextual memory revealed distinct correlations between performance and neuronal activity in frontal areas associated with recollection processes after post-training sleep, and in the parahippocampal gyrus associated with familiarity processes in sleep-deprived participants. Likewise, efficient spatial memory was associated with posterior cortical activity after sleep whereas it correlated with parahippocampal/medial temporal activity after sleep deprivation. Finally, variations in place-finding efficiency in a natural setting encompassing spatial and contextual elements were associated with caudate activity after post-training sleep, suggesting the automation of navigation. These data indicate that post

The Neural Basis of and a Common Neural Circuitry in Different Types of Pro-social Behavior

Directory of Open Access Journals (Sweden)

Jun Luo

2018-06-01

Full Text Available Pro-social behaviors are voluntary behaviors that benefit other people or society as a whole, such as charitable donations, cooperation, trust, altruistic punishment, and fairness. These behaviors have been widely described through non self-interest decision-making in behavioral experimental studies and are thought to be increased by social preference motives. Importantly, recent studies using a combination of neuroimaging and brain stimulation, designed to reveal the neural mechanisms of pro-social behaviors, have found that a wide range of brain areas, specifically the prefrontal cortex, anterior insula, anterior cingulate cortex, and amygdala, are correlated or causally related with pro-social behaviors. In this review, we summarize the research on the neural basis of various kinds of pro-social behaviors and describe a common shared neural circuitry of these pro-social behaviors. We introduce several general ways in which experimental economics and neuroscience can be combined to develop important contributions to understanding social decision-making and pro-social behaviors. Future research should attempt to explore the neural circuitry between the frontal lobes and deeper brain areas.

The neural substrates of person perception: spontaneous use of financial and moral status knowledge.

Science.gov (United States)

Cloutier, J; Ambady, N; Meagher, T; Gabrieli, J D E

2012-07-01

The current study examines the effect of status information on the neural substrates of person perception. In an event-related fMRI experiment, participants were presented with photographs of faces preceded with information denoting either: low or high financial status (e.g., "earns $25,000" or "earns $350,000"), or low or high moral status (e.g., "is a tobacco executive" or "does cancer research"). Participants were asked to form an impression of the targets, but were not instructed to explicitly evaluate their social status. Building on previous brain-imaging investigations, regions of interest analyses were performed for brain regions expected to support either cognitive (i.e., intraparietal sulcus) or emotional (i.e., ventromedial prefrontal cortex) components of social status perception. Activation of the intraparietal sulcus was found to be sensitive to the financial status of individuals while activation of the ventromedial prefrontal cortex was sensitive to the moral status of individuals. The implications of these results towards uncovering the neural substrates of status perception and, more broadly, the extended network of brain regions involved in person perception are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

The impact of cultural differences in self-representation on the neural substrates of posttraumatic stress disorder

Directory of Open Access Journals (Sweden)

Belinda J. Liddell

2016-06-01

Full Text Available A significant body of literature documents the neural mechanisms involved in the development and maintenance of posttraumatic stress disorder (PTSD. However, there is very little empirical work considering the influence of culture on these underlying mechanisms. Accumulating cultural neuroscience research clearly indicates that cultural differences in self-representation modulate many of the same neural processes proposed to be aberrant in PTSD. The objective of this review paper is to consider how culture may impact on the neural mechanisms underlying PTSD. We first outline five key affective and cognitive functions and their underlying neural correlates that have been identified as being disrupted in PTSD: (1 fear dysregulation; (2 attentional biases to threat; (3 emotion and autobiographical memory; (4 self-referential processing; and (5 attachment and interpersonal processing. Second, we consider prominent cultural theories and review the empirical research that has demonstrated the influence of cultural variations in self-representation on the neural substrates of these same five affective and cognitive functions. Finally, we propose a conceptual model that suggests that these five processes have major relevance to considering how culture may influence the neural processes underpinning PTSD. Highlights of the article:

The impact of cultural differences in self-representation on the neural substrates of posttraumatic stress disorder.

Science.gov (United States)

Liddell, Belinda J; Jobson, Laura

2016-01-01

A significant body of literature documents the neural mechanisms involved in the development and maintenance of posttraumatic stress disorder (PTSD). However, there is very little empirical work considering the influence of culture on these underlying mechanisms. Accumulating cultural neuroscience research clearly indicates that cultural differences in self-representation modulate many of the same neural processes proposed to be aberrant in PTSD. The objective of this review paper is to consider how culture may impact on the neural mechanisms underlying PTSD. We first outline five key affective and cognitive functions and their underlying neural correlates that have been identified as being disrupted in PTSD: (1) fear dysregulation; (2) attentional biases to threat; (3) emotion and autobiographical memory; (4) self-referential processing; and (5) attachment and interpersonal processing. Second, we consider prominent cultural theories and review the empirical research that has demonstrated the influence of cultural variations in self-representation on the neural substrates of these same five affective and cognitive functions. Finally, we propose a conceptual model that suggests that these five processes have major relevance to considering how culture may influence the neural processes underpinning PTSD.

The neural substrates of procrastination: A voxel-based morphometry study.

Science.gov (United States)

Hu, Yue; Liu, Peiwei; Guo, Yiqun; Feng, Tingyong

2018-03-01

Procrastination is a pervasive phenomenon across different cultures and brings about lots of serious consequences, including performance, subjective well-being, and even public policy. However, little is known about the neural substrates of procrastination. In order to shed light upon this question, we investigated the neuroanatomical substrates of procrastination across two independent samples using voxel-based morphometry (VBM) method. The whole-brain analysis showed procrastination was positively correlated with the graymatter (GM) volume of clusters in the parahippocampal gyrus (PHG) and the orbital frontal cortex (OFC), while negatively correlated with the GM volume of clusters in the inferior frontal gyrus (IFG) and the middle frontal gyrus (MFG) in sample one (151 participants). We further conducted a verification procedure on another sample (108 participants) using region-of-interest analysis to examine the reliability of these results. Results showed procrastination can be predicted by the GM volume of the OFC and the MFG. The present findings suggest that the MFG and OFC, which are the key regions of self-control and emotion regulation, may play an important role in procrastination. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural substrates underlying balanced time perspective: A combined voxel-based morphometry and resting-state functional connectivity study.

Science.gov (United States)

Guo, Yiqun; Chen, Zhiyi; Feng, Tingyong

2017-08-14

Balanced time perspective (BTP), which is defined as a mental ability to switch flexibly among different time perspectives Zimbardo and Boyd (1999), has been suggested to be a central component of positive psychology Boniwell and Zimbardo (2004). BTP reflects individual's cognitive flexibility towards different time frames, which leads to many positive outcomes, including positive mood, subjective wellbeing, emotional intelligence, fluid intelligence, and executive control. However, the neural basis of BTP is still unclear. To address this question, we quantified individual's deviation from the BTP (DBTP), and investigated the neural substrates of DBTP using both voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) methods VBM analysis found that DBTP scores were positively correlated with gray matter volume (GMV) in the ventral precuneus. We further found that DBTP scores were negatively associated with RSFCs between the ventral precuneus seed region and medial prefrontal cortex (mPFC), bilateral temporoparietal junction (TPJ), parahippocampa gyrus (PHG), and middle frontal gyrus (MFG). These brain regions found in both VBM and RSFC analyses are commonly considered as core nodes of the default mode network (DMN) that is known to be involved in many functions, including episodic and autobiographical memory, self-related processing, theory of mind, and imagining the future. These functions of the DMN are also essential to individuals with BTP. Taken together, we provide the first evidence for the structural and functional neural basis of BTP, and highlight the crucial role of the DMN in cultivating an individual's BTP. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of Substrate and Co-Culture on Neural Progenitor Cell Differentiation

Energy Technology Data Exchange (ETDEWEB)

Jones, Erin Boote [Iowa State Univ., Ames, IA (United States)

2008-01-01

In recent years the study of stem and progenitor cells has moved to the forefront of research. Since the isolation of human hematopoietic stem cells in 1988 and the subsequent discovery of a self renewing population of multipotent cells in many tissues, many researchers have envisioned a better understanding of development and potential clinical usage in intractable diseases. Both these goals, however, depend on a solid understanding of the intracellular and extracellular forces that cause stem cells to differentiate to a specific cell fate. Many diseases of large scale cell loss have been suggested as candidates for stem cell based treatments. It is proposed that replacing the function of the damaged or defective cells by specific differentiation of stem or progenitor cells could treat the disease. Before cells can be directed to specific lineages, the mechanisms of differentiation must be better understood. Differentiation in vivo is an intensively complex system that is difficult to study. The goal of this research is to develop further understanding of the effects of soluble and extracellular matrix (ECM) cues on the differentiation of neural progenitor cells with the use of a simplified in vitro culture system. Specific research objectives are to study the differentiation of neural progenitor cells in response to astrocyte conditioned medium and protein substrate composition and concentration. In an effort to reveal the mechanism of the conditioned medium interaction, a test for the presence of a feedback loop between progenitor cells and astrocytes is presented along with an examination of conditioned medium storage temperature, which can reveal enzymatic dependencies. An examination of protein substrate composition and concentration will help to reveal the role of any ECM interactions on differentiation. This thesis is organized into a literature review covering recent advances in use of external modulators of differentiation such as surface coatings, co

What Neural Substrates Trigger the Adept Scientific Pattern Discovery by Biologists?

Science.gov (United States)

Lee, Jun-Ki; Kwon, Yong-Ju

2011-04-01

This study investigated the neural correlates of experts and novices during biological object pattern detection using an fMRI approach in order to reveal the neural correlates of a biologist's superior pattern discovery ability. Sixteen healthy male participants (8 biologists and 8 non-biologists) volunteered for the study. Participants were shown fifteen series of organism pictures and asked to detect patterns amid stimulus pictures. Primary findings showed significant activations in the right middle temporal gyrus and inferior parietal lobule amongst participants in the biologist (expert) group. Interestingly, the left superior temporal gyrus was activated in participants from the non-biologist (novice) group. These results suggested that superior pattern discovery ability could be related to a functional facilitation of the parieto-temporal network, which is particularly driven by the right middle temporal gyrus and inferior parietal lobule in addition to the recruitment of additional brain regions. Furthermore, the functional facilitation of the network might actually pertain to high coherent processing skills and visual working memory capacity. Hence, study results suggested that adept scientific thinking ability can be detected by neuronal substrates, which may be used as criteria for developing and evaluating a brain-based science curriculum and test instrument.

The neural substrates of cognitive flexibility are related to individual differences in preschool irritability: A fNIRS investigation

Directory of Open Access Journals (Sweden)

Yanwei Li

2017-06-01

Full Text Available Preschool (age 3–5 is a phase of rapid development in both cognition and emotion, making this a period in which the neurodevelopment of each domain is particularly sensitive to that of the other. During this period, children rapidly learn how to flexibly shift their attention between competing demands and, at the same time, acquire critical emotion regulation skills to respond to negative affective challenges. The integration of cognitive flexibility and individual differences in irritability may be an important developmental process of early childhood maturation. However, at present it is unclear if they share common neural substrates in early childhood. Our main goal was to examine the neural correlates of cognitive flexibility in preschool children and test for associations with irritability. Forty-six preschool aged children completed a novel, child-appropriate, Stroop task while dorsolateral prefrontal cortex (DLPFC activation was recorded using functional Near Infrared Spectroscopy (fNIRS. Parents rated their child’s irritability. Results indicated that left DLPFC activation was associated with cognitive flexibility and positively correlated with irritability. Right DLPFC activation was also positively correlated with irritability. Results suggest the entwined nature of cognitive and emotional neurodevelopment during a developmental period of rapid and mutual acceleration.

Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation.

Science.gov (United States)

Limb, Charles J; Braun, Allen R

2008-02-27

To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences) was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar) cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance) as well as deactivation of limbic structures (that regulate motivation and emotional tone). This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity.

Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation.

Directory of Open Access Journals (Sweden)

Charles J Limb

Full Text Available To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance as well as deactivation of limbic structures (that regulate motivation and emotional tone. This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity.

A novel neural substrate for the transformation of olfactory inputs into motor output.

Directory of Open Access Journals (Sweden)

Dominique Derjean

2010-12-01

Full Text Available It is widely recognized that animals respond to odors by generating or modulating specific motor behaviors. These reactions are important for daily activities, reproduction, and survival. In the sea lamprey, mating occurs after ovulated females are attracted to spawning sites by male sex pheromones. The ubiquity and reliability of olfactory-motor behavioral responses in vertebrates suggest tight coupling between the olfactory system and brain areas controlling movements. However, the circuitry and the underlying cellular neural mechanisms remain largely unknown. Using lamprey brain preparations, and electrophysiology, calcium imaging, and tract tracing experiments, we describe the neural substrate responsible for transforming an olfactory input into a locomotor output. We found that olfactory stimulation with naturally occurring odors and pheromones induced large excitatory responses in reticulospinal cells, the command neurons for locomotion. We have also identified the anatomy and physiology of this circuit. The olfactory input was relayed in the medial part of the olfactory bulb, in the posterior tuberculum, in the mesencephalic locomotor region, to finally reach reticulospinal cells in the hindbrain. Activation of this olfactory-motor pathway generated rhythmic ventral root discharges and swimming movements. Our study bridges the gap between behavior and cellular neural mechanisms in vertebrates, identifying a specific subsystem within the CNS, dedicated to producing motor responses to olfactory inputs.

Largely overlapping neuronal substrates of reactivity to drug, gambling, food and sexual cues: A comprehensive meta-analysis.

Science.gov (United States)

Noori, Hamid R; Cosa Linan, Alejandro; Spanagel, Rainer

2016-09-01

Cue reactivity to natural and social rewards is essential for motivational behavior. However, cue reactivity to drug rewards can also elicit craving in addicted subjects. The degree to which drug and natural rewards share neural substrates is not known. The objective of this study is to conduct a comprehensive meta-analysis of neuroimaging studies on drug, gambling and natural stimuli (food and sex) to identify the common and distinct neural substrates of cue reactivity to drug and natural rewards. Neural cue reactivity studies were selected for the meta-analysis by means of activation likelihood estimations, followed by sensitivity and clustering analyses of averaged neuronal response patterns. Data from 176 studies (5573 individuals) suggests largely overlapping neural response patterns towards all tested reward modalities. Common cue reactivity to natural and drug rewards was expressed by bilateral neural responses within anterior cingulate gyrus, insula, caudate head, inferior frontal gyrus, middle frontal gyrus and cerebellum. However, drug cues also generated distinct activation patterns in medial frontal gyrus, middle temporal gyrus, posterior cingulate gyrus, caudate body and putamen. Natural (sexual) reward cues induced unique activation of the pulvinar in thalamus. Neural substrates of cue reactivity to alcohol, drugs of abuse, food, sex and gambling are largely overlapping and comprise a network that processes reward, emotional responses and habit formation. This suggests that cue-mediated craving involves mechanisms that are not exclusive for addictive disorders but rather resemble the intersection of information pathways for processing reward, emotional responses, non-declarative memory and obsessive-compulsive behavior. Copyright © 2016 Elsevier B.V. and ECNP. All rights reserved.

The common and distinct neural bases of affect labeling and reappraisal in healthy adults

Directory of Open Access Journals (Sweden)

Lisa Jane Burklund

2014-03-01

Full Text Available Emotion regulation is commonly characterized as involving conscious and intentional attempts to change felt emotions, such as, for example, through reappraisal whereby one intentionally decreases the intensity of one’s emotional response to a particular stimulus or situation by reinterpreting it in a less threatening way. However, there is growing evidence and appreciation that some types of emotion regulation are unintentional or incidental, meaning that affective modulation is a consequence but not an explicit goal. For example, affect labeling involves simply verbally labeling the emotional content of an external stimulus or one’s own affective responses without an intentional goal of altering emotional responses, yet has been associated with reduced affective responses at the neural and experiential levels. Although both intentional and incidental emotional regulation strategies have been associated with diminished limbic responses and self-reported distress, little previous research has directly compared their underlying neural mechanisms. In this study, we examined the extent to which incidental and intentional emotion regulation, namely, affect labeling and reappraisal, produced common and divergent neural and self-report responses to aversive images relative to an observe-only control condition in a sample of healthy older adults (N=39. Affect labeling and reappraisal produced common activations in several prefrontal regulatory regions, with affect labeling producing stronger responses in direct comparisons. Affect labeling and reappraisal were also associated with similar decreases in amygdala activity. Finally, affect labeling and reappraisal were associated with correlated reductions in self-reported distress. Together these results point to common neurocognitive mechanisms involved in affect labeling and reappraisal, supporting the idea that intentional and incidental emotion regulation may utilize overlapping neural processes.

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

Science.gov (United States)

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

2014-01-01

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

A common neural code for perceived and inferred emotion.

Science.gov (United States)

Skerry, Amy E; Saxe, Rebecca

2014-11-26

Although the emotions of other people can often be perceived from overt reactions (e.g., facial or vocal expressions), they can also be inferred from situational information in the absence of observable expressions. How does the human brain make use of these diverse forms of evidence to generate a common representation of a target's emotional state? In the present research, we identify neural patterns that correspond to emotions inferred from contextual information and find that these patterns generalize across different cues from which an emotion can be attributed. Specifically, we use functional neuroimaging to measure neural responses to dynamic facial expressions with positive and negative valence and to short animations in which the valence of a character's emotion could be identified only from the situation. Using multivoxel pattern analysis, we test for regions that contain information about the target's emotional state, identifying representations specific to a single stimulus type and representations that generalize across stimulus types. In regions of medial prefrontal cortex (MPFC), a classifier trained to discriminate emotional valence for one stimulus (e.g., animated situations) could successfully discriminate valence for the remaining stimulus (e.g., facial expressions), indicating a representation of valence that abstracts away from perceptual features and generalizes across different forms of evidence. Moreover, in a subregion of MPFC, this neural representation generalized to trials involving subjectively experienced emotional events, suggesting partial overlap in neural responses to attributed and experienced emotions. These data provide a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion. Copyright © 2014 the authors 0270-6474/14/3315997-12$15.00/0.

Structural neural substrates of reading the mind in the eyes

Directory of Open Access Journals (Sweden)

Wataru eSato

2016-04-01

Full Text Available The ability to read the minds of others in their eyes plays an important role in human adaptation to social environments. Behavioral studies have resulted in the development of a test to measure this ability (Reading the Mind in the Eyes Test, revised version; Eyes Test, and have demonstrated that this ability is consistent over time. Although functional neuroimaging studies revealed brain activation while performing the Eyes Test, the structural neural substrates supporting consistent performance on the Eyes Test remain unclear. In this study we assessed the Eyes Test and analyzed structural magnetic resonance images using voxel-based morphometry in healthy participants. Test performance was positively associated with the gray matter volumes of the dorsomedial prefrontal cortex, inferior parietal lobule (temporoparietal junction, and precuneus in the left hemisphere. These results suggest that the fronto-temporoparietal network structures support the consistent ability to read the mind in the eyes.

Identifying the Neural Substrates of Procrastination: a Resting-State fMRI Study.

Science.gov (United States)

Zhang, Wenwen; Wang, Xiangpeng; Feng, Tingyong

2016-09-12

Procrastination is a prevalent problematic behavior that brings serious consequences to individuals who suffer from it. Although this phenomenon has received increasing attention from researchers, the underpinning neural substrates of it is poorly studied. To examine the neural bases subserving procrastination, the present study employed resting-state fMRI. The main results were as follows: (1) the behavioral procrastination was positively correlated with the regional activity of the ventromedial prefrontal cortex (vmPFC) and the parahippocampal cortex (PHC), while negatively correlated with that of the anterior prefrontal cortex (aPFC). (2) The aPFC-seed connectivity with the anterior medial prefrontal cortex and the posterior cingulate cortex was positively associated with procrastination. (3) The connectivity between vmPFC and several other regions, such as the dorsomedial prefrontal cortex, the bilateral inferior prefrontal cortex showed a negative association with procrastination. These results suggested that procrastination could be attributed to, on the one hand, hyper-activity of the default mode network (DMN) that overrides the prefrontal control signal; while on the other hand, the failure of top-down control exerted by the aPFC on the DMN. Therefore, the present study unravels the biomarkers of procrastination and provides treatment targets for procrastination prevention.

Abnormal neural responses to social exclusion in schizophrenia.

Directory of Open Access Journals (Sweden)

Victoria B Gradin

Full Text Available Social exclusion is an influential concept in politics, mental health and social psychology. Studies on healthy subjects have implicated the medial prefrontal cortex (mPFC, a region involved in emotional and social information processing, in neural responses to social exclusion. Impairments in social interactions are common in schizophrenia and are associated with reduced quality of life. Core symptoms such as delusions usually have a social content. However little is known about the neural underpinnings of social abnormalities. The aim of this study was to investigate the neural substrates of social exclusion in schizophrenia. Patients with schizophrenia and healthy controls underwent fMRI while participating in a popular social exclusion paradigm. This task involves passing a 'ball' between the participant and two cartoon representations of other subjects. The extent of social exclusion (ball not being passed to the participant was parametrically varied throughout the task. Replicating previous findings, increasing social exclusion activated the mPFC in controls. In contrast, patients with schizophrenia failed to modulate mPFC responses with increasing exclusion. Furthermore, the blunted response to exclusion correlated with increased severity of positive symptoms. These data support the hypothesis that the neural response to social exclusion differs in schizophrenia, highlighting the mPFC as a potential substrate of impaired social interactions.

Distinct Neural Substrates for Maintaining Locations and Spatial Relations in Working Memory

Directory of Open Access Journals (Sweden)

Kara J Blacker

2016-11-01

Full Text Available Previous work has demonstrated a distinction between maintenance of two types of spatial information in working memory (WM: spatial locations and spatial relations. While a body of work has investigated the neural mechanisms of sensory-based information like spatial locations, little is known about how spatial relations are maintained in WM. In two experiments, we used fMRI to investigate the involvement of early visual cortex in the maintenance of spatial relations in WM. In both experiments, we found less quadrant-specific BOLD activity in visual cortex when a single spatial relation, compared to a single spatial location, was held in WM. Also across both experiments, we found a consistent set of brain regions that were differentially activated during maintenance of locations versus relations. Maintaining a location, compared to a relation, was associated with greater activity in typical spatial WM regions like posterior parietal cortex and prefrontal regions. Whereas maintaining a relation, compared to a location, was associated with greater activity in the parahippocampal gyrus and precuneus/retrosplenial cortex. Further, in Experiment 2 we manipulated WM load and included trials where participants had to maintain three spatial locations or relations. Under this high load condition, the regions sensitive to locations versus relations were somewhat different than under low load. We also identified regions that were sensitive to load specifically for location or relation maintenance, as well as overlapping regions sensitive to load more generally. These results suggest that the neural substrates underlying WM maintenance of spatial locations and relations are distinct from one another and that the neural representations of these distinct types of spatial information change with load.

Distinct neural substrates of affective and cognitive theory of mind impairment in semantic dementia.

Science.gov (United States)

Bejanin, Alexandre; Chételat, Gaël; Laisney, Mickael; Pélerin, Alice; Landeau, Brigitte; Merck, Catherine; Belliard, Serge; de La Sayette, Vincent; Eustache, Francis; Desgranges, Béatrice

2017-06-01

Using structural MRI, we investigated the brain substrates of both affective and cognitive theory of mind (ToM) in 19 patients with semantic dementia. We also ran intrinsic connectivity analyses to identify the networks to which the substrates belong and whether they are functionally disturbed in semantic dementia. In line with previous studies, we observed a ToM impairment in patients with semantic dementia even when semantic memory was regressed out. Our results also highlighted different neural bases according to the nature (affective or cognitive) of the representations being inferred. The affective ToM deficit was associated with atrophy in the amygdala, suggesting the involvement of emotion-processing deficits in this impairment. By contrast, cognitive ToM performances were correlated with the volume of medial prefrontal and parietal regions, as well as the right frontal operculum. Intrinsic connectivity analyses revealed decreased functional connectivity, mainly between midline cortical regions and temporal regions. They also showed that left medial temporal regions were functionally isolated, a further possible hindrance to normal social cognitive functioning in semantic dementia. Overall, this study addressed for the first time the neuroanatomical substrates of both cognitive and affective ToM disruption in semantic dementia, highlighting disturbed connectivity within the networks that sustain these abilities.

A Neural Signature Encoding Decisions under Perceptual Ambiguity.

Science.gov (United States)

Sun, Sai; Yu, Rongjun; Wang, Shuo

2017-01-01

People often make perceptual decisions with ambiguous information, but it remains unclear whether the brain has a common neural substrate that encodes various forms of perceptual ambiguity. Here, we used three types of perceptually ambiguous stimuli as well as task instructions to examine the neural basis for both stimulus-driven and task-driven perceptual ambiguity. We identified a neural signature, the late positive potential (LPP), that encoded a general form of stimulus-driven perceptual ambiguity. In addition to stimulus-driven ambiguity, the LPP was also modulated by ambiguity in task instructions. To further specify the functional role of the LPP and elucidate the relationship between stimulus ambiguity, behavioral response, and the LPP, we employed regression models and found that the LPP was specifically associated with response latency and confidence rating, suggesting that the LPP encoded decisions under perceptual ambiguity. Finally, direct behavioral ratings of stimulus and task ambiguity confirmed our neurophysiological findings, which could not be attributed to differences in eye movements either. Together, our findings argue for a common neural signature that encodes decisions under perceptual ambiguity but is subject to the modulation of task ambiguity. Our results represent an essential first step toward a complete neural understanding of human perceptual decision making.

Remembering the past and imagining the future: common and distinct neural substrates during event construction and elaboration

OpenAIRE

Addis, Donna Rose; Wong, Alana T.; Schacter, Daniel L.

2006-01-01

People can consciously re-experience past events and pre-experience possible future events. This fMRI study examined the neural regions mediating the construction and elaboration of past and future events. Participants were cued with a noun for 20 seconds and instructed to construct a past or future event within a specified time period (week, year, 5–20 years). Once participants had the event in mind, they made a button press and for the remainder of the 20 seconds elaborated on the event. Im...

Common and distinct neural mechanisms of attentional switching and response conflict.

Science.gov (United States)

Kim, Chobok; Johnson, Nathan F; Gold, Brian T

2012-08-21

The human capacities for overcoming prepotent actions and flexibly switching between tasks represent cornerstones of cognitive control. Functional neuroimaging has implicated a diverse set of brain regions contributing to each of these cognitive control processes. However, the extent to which attentional switching and response conflict draw on shared or distinct neural mechanisms remains unclear. The current study examined the neural correlates of response conflict and attentional switching using event-related functional magnetic resonance imaging (fMRI) and a fully randomized 2×2 design. We manipulated an arrow-word version of the Stroop task to measure conflict and switching in the context of a single task decision, in response to a common set of stimuli. Under these common conditions, both behavioral and imaging data showed significant main effects of conflict and switching but no interaction. However, conjunction analyses identified frontal regions involved in both switching and response conflict, including the dorsal anterior cingulate cortex (dACC) and left inferior frontal junction. In addition, connectivity analyses demonstrated task-dependent functional connectivity patterns between dACC and inferior temporal cortex for attentional switching and between dACC and posterior parietal cortex for response conflict. These results suggest that the brain makes use of shared frontal regions, but can dynamically modulate the connectivity patterns of some of those regions, to deal with attentional switching and response conflict. Copyright © 2012 Elsevier B.V. All rights reserved.

Modification of surface/neuron interfaces for neural cell-type specific responses: a review

International Nuclear Information System (INIS)

Chen, Cen; Kong, Xiangdong; Lee, In-Seop

2016-01-01

Surface/neuron interfaces have played an important role in neural repair including neural prostheses and tissue engineered scaffolds. This comprehensive literature review covers recent studies on the modification of surface/neuron interfaces. These interfaces are identified in cases both where the surfaces of substrates or scaffolds were in direct contact with cells and where the surfaces were modified to facilitate cell adhesion and controlling cell-type specific responses. Different sources of cells for neural repair are described, such as pheochromocytoma neuronal-like cell, neural stem cell (NSC), embryonic stem cell (ESC), mesenchymal stem cell (MSC) and induced pluripotent stem cell (iPS). Commonly modified methods are discussed including patterned surfaces at micro- or nano-scale, surface modification with conducting coatings, and functionalized surfaces with immobilized bioactive molecules. These approaches to control cell-type specific responses have enormous potential implications in neural repair. (paper)

Distinct neural substrates of visuospatial and verbal-analytic reasoning as assessed by Raven's Advanced Progressive Matrices

NARCIS (Netherlands)

Chen, Zhencai; De Beuckelaer, A.; Wang, Xu; Liu, Jia

2017-01-01

Recent studies revealed spontaneous neural activity to be associated with fluid intelligence (gF) which is commonly assessed by Raven’s Advanced Progressive Matrices, and embeds two types of reasoning: visuospatial and verbal-analytic reasoning. With resting-state fMRI data, using global brain

Neural Substrates of Semantic Prospection – Evidence from the Dementias

Science.gov (United States)

Irish, Muireann; Eyre, Nadine; Dermody, Nadene; O’Callaghan, Claire; Hodges, John R.; Hornberger, Michael; Piguet, Olivier

2016-01-01

The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15) and disease-matched behavioral-variant frontotemporal dementia (n = 15), neurodegenerative disorders characterized by significant medial temporal lobe (MTL) and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic) and non-personal (semantic) domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1-weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between gray matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal, and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

Neural Substrates of Semantic Prospection – Evidence from the Dementias

Directory of Open Access Journals (Sweden)

Muireann eIrish

2016-05-01

Full Text Available The ability to envisage personally relevant events at a future time point represents an incredibly sophisticated cognitive endeavor and one that appears to be intimately linked to episodic memory integrity. Far less is known regarding the neurocognitive mechanisms underpinning the capacity to envisage non-personal future occurrences, known as semantic future thinking. Moreover the degree of overlap between the neural substrates supporting episodic and semantic forms of prospection remains unclear. To this end, we sought to investigate the capacity for episodic and semantic future thinking in Alzheimer’s disease (n = 15 and disease-matched behavioral-variant frontotemporal dementia (n = 15, neurodegenerative disorders characterized by significant medial temporal lobe and frontal pathology. Participants completed an assessment of past and future thinking across personal (episodic and non-personal (semantic domains, as part of a larger neuropsychological battery investigating episodic and semantic processing, and their performance was contrasted with 20 age- and education-matched healthy older Controls. Participants underwent whole-brain T1 weighted structural imaging and voxel-based morphometry analysis was conducted to determine the relationship between grey matter integrity and episodic and semantic future thinking. Relative to Controls, both patient groups displayed marked future thinking impairments, extending across episodic and semantic domains. Analyses of covariance revealed that while episodic future thinking deficits could be explained solely in terms of episodic memory proficiency, semantic prospection deficits reflected the interplay between episodic and semantic processing. Distinct neural correlates emerged for each form of future simulation with differential involvement of prefrontal, lateral temporal and medial temporal regions. Notably, the hippocampus was implicated irrespective of future thinking domain, with the suggestion of

Optimization of the selection process of the co-substrates for chicken manure fermentation using neural modeling

Directory of Open Access Journals (Sweden)

Lewicki Andrzej

2016-01-01

Full Text Available Intense development of research equipment leads directly to increasing cognitive abilities. However, along with the raising amount of data generated, the development of the techniques allowing the analysis is also essential. Currently, one of the most dynamically developing branch of computer science and mathematics are the Artificial Neural Networks (ANN. Their main advantage is very high ability to solve the regression and approximation issues. This paper presents the possibility of application of artificial intelligence methods to optimize the selection of co-substrates intended for methane fermentation of chicken manure. 4-layer MLP network has proven to be the optimal structure modeling the obtained empirical data.

A common neural substrate for language production and verbal working memory.

Science.gov (United States)

Acheson, Daniel J; Hamidi, Massihullah; Binder, Jeffrey R; Postle, Bradley R

2011-06-01

Verbal working memory (VWM), the ability to maintain and manipulate representations of speech sounds over short periods, is held by some influential models to be independent from the systems responsible for language production and comprehension [e.g., Baddeley, A. D. Working memory, thought, and action. New York, NY: Oxford University Press, 2007]. We explore the alternative hypothesis that maintenance in VWM is subserved by temporary activation of the language production system [Acheson, D. J., & MacDonald, M. C. Verbal working memory and language production: Common approaches to the serial ordering of verbal information. Psychological Bulletin, 135, 50-68, 2009b]. Specifically, we hypothesized that for stimuli lacking a semantic representation (e.g., nonwords such as mun), maintenance in VWM can be achieved by cycling information back and forth between the stages of phonological encoding and articulatory planning. First, fMRI was used to identify regions associated with two different stages of language production planning: the posterior superior temporal gyrus (pSTG) for phonological encoding (critical for VWM of nonwords) and the middle temporal gyrus (MTG) for lexical-semantic retrieval (not critical for VWM of nonwords). Next, in the same subjects, these regions were targeted with repetitive transcranial magnetic stimulation (rTMS) during language production and VWM task performance. Results showed that rTMS to the pSTG, but not the MTG, increased error rates on paced reading (a language production task) and on delayed serial recall of nonwords (a test of VWM). Performance on a lexical-semantic retrieval task (picture naming), in contrast, was significantly sensitive to rTMS of the MTG. Because rTMS was guided by language production-related activity, these results provide the first causal evidence that maintenance in VWM directly depends on the long-term representations and processes used in speech production.

The Neural Basis of Typewriting: A Functional MRI Study.

Science.gov (United States)

Higashiyama, Yuichi; Takeda, Katsuhiko; Someya, Yoshiaki; Kuroiwa, Yoshiyuki; Tanaka, Fumiaki

2015-01-01

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

The Neural Basis of Typewriting: A Functional MRI Study.

Directory of Open Access Journals (Sweden)

Yuichi Higashiyama

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

The fibroblast growth factor receptor (FGFR) agonist FGF1 and the neural cell adhesion molecule-derived peptide FGL activate FGFR substrate 2alpha differently

DEFF Research Database (Denmark)

Chen, Yongshuo; Li, Shizhong; Berezin, Vladimir

2010-01-01

Activation of fibroblast growth factor (FGF) receptors (FGFRs) both by FGFs and by the neural cell adhesion molecule (NCAM) is crucial in the development and function of the nervous system. We found that FGFR substrate 2alpha (FRS2alpha), Src homologous and collagen A (ShcA), and phospholipase-Cg...

Neural Substrates of Auditory Emotion Recognition Deficits in Schizophrenia.

Science.gov (United States)

Kantrowitz, Joshua T; Hoptman, Matthew J; Leitman, David I; Moreno-Ortega, Marta; Lehrfeld, Jonathan M; Dias, Elisa; Sehatpour, Pejman; Laukka, Petri; Silipo, Gail; Javitt, Daniel C

2015-11-04

and global functional outcome. This study evaluated neural substrates of impaired AER in schizophrenia using a combined event-related potential/resting-state fMRI approach. Patients showed impaired mismatch negativity response to emotionally relevant frequency modulated tones along with impaired functional connectivity between auditory and medial temporal (anterior insula) cortex. These deficits contributed in parallel to impaired AER and accounted for ∼50% of variance in AER performance. Overall, these findings demonstrate the importance of both auditory-level dysfunction and impaired auditory/insula connectivity in the pathophysiology of social cognitive dysfunction in schizophrenia. Copyright © 2015 the authors 0270-6474/15/3514910-13$15.00/0.

Neural basis of acquired amusia and its recovery after stroke

OpenAIRE

Sihvonen, A.J.; Ripollés, P.; Leo, V.; Rodríguez-Fornells, Antoni; Soinila, S.; Särkämö, T.

2016-01-01

Although acquired amusia is a relatively common disorder after stroke, its precise neuroanatomical basis is still unknown. To evaluate which brain regions form the neural substrate for acquired amusia and its recovery, we performed a voxel-based lesion-symptom mapping (VLSM) and morphometry (VBM) study with 77 human stroke subjects. Structural MRIs were acquired at acute and 6 month poststroke stages. Amusia and aphasia were behaviorally assessed at acute and 3 month poststroke stages using t...

The neural substrates associated with attentional resources and difficulty of concurrent processing of the two verbal tasks.

Science.gov (United States)

Mizuno, Kei; Tanaka, Masaaki; Tanabe, Hiroki C; Sadato, Norihiro; Watanabe, Yasuyoshi

2012-07-01

The kana pick-out test has been widely used in Japan to evaluate the ability to divide attention in both adult and pediatric patients. However, the neural substrates underlying the ability to divide attention using the kana pick-out test, which requires participants to pick out individual letters (vowels) in a story while also reading for comprehension, thus requiring simultaneous allocation of attention to both activities, are still unclear. Moreover, outside of the clinical area, neuroimaging studies focused on the mechanisms of divided attention during complex story comprehension are rare. Thus, the purpose of the present study, to clarify the neural substrates of kana pick-out test, improves our current understanding of the basic neural mechanisms of dual task performance in verbal memory function. We compared patterns of activation in the brain obtained during performance of the individual tasks of vowel identification and story comprehension, to levels of activation when participants performed the two tasks simultaneously during the kana pick-out test. We found that activations of the left dorsal inferior frontal gyrus and superior parietal lobule increase in functional connectivity to a greater extent during the dual task condition compared to the two single task conditions. In contrast, activations of the left fusiform gyrus and middle temporal gyrus, which are significantly involved in picking out letters and complex sentences during story comprehension, respectively, were reduced in the dual task condition compared to during the two single task conditions. These results suggest that increased activations of the dorsal inferior frontal gyrus and superior parietal lobule during dual task performance may be associated with the capacity for attentional resources, and reduced activations of the left fusiform gyrus and middle temporal gyrus may reflect the difficulty of concurrent processing of the two tasks. In addition, the increase in synchronization between

A chemically defined substrate for the expansion and neuronal differentiation of human pluripotent stem cell-derived neural progenitor cells.

Science.gov (United States)

Tsai, Yihuan; Cutts, Josh; Kimura, Azuma; Varun, Divya; Brafman, David A

2015-07-01

Due to the limitation of current pharmacological therapeutic strategies, stem cell therapies have emerged as a viable option for treating many incurable neurological disorders. Specifically, human pluripotent stem cell (hPSC)-derived neural progenitor cells (hNPCs), a multipotent cell population that is capable of near indefinite expansion and subsequent differentiation into the various cell types that comprise the central nervous system (CNS), could provide an unlimited source of cells for such cell-based therapies. However the clinical application of these cells will require (i) defined, xeno-free conditions for their expansion and neuronal differentiation and (ii) scalable culture systems that enable their expansion and neuronal differentiation in numbers sufficient for regenerative medicine and drug screening purposes. Current extracellular matrix protein (ECMP)-based substrates for the culture of hNPCs are expensive, difficult to isolate, subject to batch-to-batch variations, and, therefore, unsuitable for clinical application of hNPCs. Using a high-throughput array-based screening approach, we identified a synthetic polymer, poly(4-vinyl phenol) (P4VP), that supported the long-term proliferation and self-renewal of hNPCs. The hNPCs cultured on P4VP maintained their characteristic morphology, expressed high levels of markers of multipotency, and retained their ability to differentiate into neurons. Such chemically defined substrates will eliminate critical roadblocks for the utilization of hNPCs for human neural regenerative repair, disease modeling, and drug discovery. Copyright © 2015. Published by Elsevier B.V.

A chemically defined substrate for the expansion and neuronal differentiation of human pluripotent stem cell-derived neural progenitor cells

Directory of Open Access Journals (Sweden)

Yihuan Tsai

2015-07-01

Full Text Available Due to the limitation of current pharmacological therapeutic strategies, stem cell therapies have emerged as a viable option for treating many incurable neurological disorders. Specifically, human pluripotent stem cell (hPSC-derived neural progenitor cells (hNPCs, a multipotent cell population that is capable of near indefinite expansion and subsequent differentiation into the various cell types that comprise the central nervous system (CNS, could provide an unlimited source of cells for such cell-based therapies. However the clinical application of these cells will require (i defined, xeno-free conditions for their expansion and neuronal differentiation and (ii scalable culture systems that enable their expansion and neuronal differentiation in numbers sufficient for regenerative medicine and drug screening purposes. Current extracellular matrix protein (ECMP-based substrates for the culture of hNPCs are expensive, difficult to isolate, subject to batch-to-batch variations, and, therefore, unsuitable for clinical application of hNPCs. Using a high-throughput array-based screening approach, we identified a synthetic polymer, poly(4-vinyl phenol (P4VP, that supported the long-term proliferation and self-renewal of hNPCs. The hNPCs cultured on P4VP maintained their characteristic morphology, expressed high levels of markers of multipotency, and retained their ability to differentiate into neurons. Such chemically defined substrates will eliminate critical roadblocks for the utilization of hNPCs for human neural regenerative repair, disease modeling, and drug discovery.

Identifying the neural substrates of intrinsic motivation during task performance.

Science.gov (United States)

Lee, Woogul; Reeve, Johnmarshall

2017-10-01

Intrinsic motivation is the inherent tendency to seek out novelty and challenge, to explore and investigate, and to stretch and extend one's capacities. When people imagine performing intrinsically motivating tasks, they show heightened anterior insular cortex (AIC) activity. To fully explain the neural system of intrinsic motivation, however, requires assessing neural activity while people actually perform intrinsically motivating tasks (i.e., while answering curiosity-inducing questions or solving competence-enabling anagrams). Using event-related functional magnetic resonance imaging, we found that the neural system of intrinsic motivation involves not only AIC activity, but also striatum activity and, further, AIC-striatum functional interactions. These findings suggest that subjective feelings of intrinsic satisfaction (associated with AIC activations), reward processing (associated with striatum activations), and their interactions underlie the actual experience of intrinsic motivation. These neural findings are consistent with the conceptualization of intrinsic motivation as the pursuit and satisfaction of subjective feelings (interest and enjoyment) as intrinsic rewards.

Differential neural substrates of working memory and cognitive skill learning in healthy young volunteers

International Nuclear Information System (INIS)

Cho, Sang Soo; Lee, Eun Ju; Yoon, Eun Jin; Kim, Yu Kyeong; Lee, Won Woo; Kim, Sang Eun

2005-01-01

It is known that different neural circuits are involved in working memory and cognitive skill learning that represent explicit and implicit memory functions, respectively. In the present study, we investigated the metabolic correlates of working memory and cognitive skill learning with correlation analysis of FDG PET images. Fourteen right-handed healthy subjects (age, 24 ± 2 yr; 5 males and 9 females) underwent brain FDG PET and neuropsychological testing. Two-back task and weather prediction task were used for the evaluation of working memory and cognitive skill learning, respectively, Correlation between regional glucose metabolism and cognitive task performance was examined using SPM99. A significant positive correlation between 2-back task performance and regional glucose metabolism was found in the prefrontal regions and superior temporal gyri bilaterally. In the first term of weather prediction task the task performance correlated positively with glucose metabolism in the bilateral prefrontal areas, left middle temporal and posterior cingulate gyri, and left thalamus. In the second and third terms of the task, the correlation found in the prefrontal areas, superior temporal and anterior cingulate gyri bilaterally, right insula, left parahippocampal gyrus, and right caudate nucleus. We identified the neural substrates that are related with performance of working memory and cognitive skill learning. These results indicate that brain regions associated with the explicit memory system are recruited in early periods of cognitive skill learning, but additional brain regions including caudate nucleus are involved in late periods of cognitive skill learning

Differential neural substrates of working memory and cognitive skill learning in healthy young volunteers

Energy Technology Data Exchange (ETDEWEB)

Cho, Sang Soo; Lee, Eun Ju; Yoon, Eun Jin; Kim, Yu Kyeong; Lee, Won Woo; Kim, Sang Eun [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of)

2005-07-01

It is known that different neural circuits are involved in working memory and cognitive skill learning that represent explicit and implicit memory functions, respectively. In the present study, we investigated the metabolic correlates of working memory and cognitive skill learning with correlation analysis of FDG PET images. Fourteen right-handed healthy subjects (age, 24 {+-} 2 yr; 5 males and 9 females) underwent brain FDG PET and neuropsychological testing. Two-back task and weather prediction task were used for the evaluation of working memory and cognitive skill learning, respectively, Correlation between regional glucose metabolism and cognitive task performance was examined using SPM99. A significant positive correlation between 2-back task performance and regional glucose metabolism was found in the prefrontal regions and superior temporal gyri bilaterally. In the first term of weather prediction task the task performance correlated positively with glucose metabolism in the bilateral prefrontal areas, left middle temporal and posterior cingulate gyri, and left thalamus. In the second and third terms of the task, the correlation found in the prefrontal areas, superior temporal and anterior cingulate gyri bilaterally, right insula, left parahippocampal gyrus, and right caudate nucleus. We identified the neural substrates that are related with performance of working memory and cognitive skill learning. These results indicate that brain regions associated with the explicit memory system are recruited in early periods of cognitive skill learning, but additional brain regions including caudate nucleus are involved in late periods of cognitive skill learning.

Nano-topography Enhances Communication in Neural Cells Networks

KAUST Repository

Onesto, V.; Cancedda, L.; Coluccio, M. L.; Nanni, M.; Pesce, M.; Malara, N.; Cesarelli, M.; Di Fabrizio, Enzo M.; Amato, F.; Gentile, F.

2017-01-01

Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can

Co-existence of Methanogenesis and Sulfate Reduction with Common Substrates in Sulfate-Rich Estuarine Sediments

Directory of Open Access Journals (Sweden)

Michal Sela-Adler

2017-05-01

Full Text Available The competition between sulfate reducing bacteria and methanogens over common substrates has been proposed as a critical control for methane production. In this study, we examined the co-existence of methanogenesis and sulfate reduction with shared substrates over a large range of sulfate concentrations and rates of sulfate reduction in estuarine systems, where these processes are the key terminal sink for organic carbon. Incubation experiments were carried out with sediment samples from the sulfate-methane transition zone of the Yarqon (Israel estuary with different substrates and inhibitors along a sulfate concentrations gradient from 1 to 10 mM. The results show that methanogenesis and sulfate reduction can co-exist while the microbes share substrates over the tested range of sulfate concentrations and at sulfate reduction rates up to 680 μmol L-1 day-1. Rates of methanogenesis were two orders of magnitude lower than rates of sulfate reduction in incubations with acetate and lactate, suggesting a higher affinity of sulfate reducing bacteria for the available substrates. The co-existence of both processes was also confirmed by the isotopic signatures of δ34S in the residual sulfate and that of δ13C of methane and dissolved inorganic carbon. Copy numbers of dsrA and mcrA genes supported the dominance of sulfate reduction over methanogenesis, while showing also the ability of methanogens to grow under high sulfate concentration and in the presence of active sulfate reduction.

Neural markers of errors as endophenotypes in neuropsychiatric disorders

Directory of Open Access Journals (Sweden)

Dara S Manoach

2013-07-01

Full Text Available Learning from errors is fundamental to adaptive human behavior. It requires detecting errors, evaluating what went wrong, and adjusting behavior accordingly. These dynamic adjustments are at the heart of behavioral flexibility and accumulating evidence suggests that deficient error processing contributes to maladaptively rigid and repetitive behavior in a range of neuropsychiatric disorders. Neuroimaging and electrophysiological studies reveal highly reliable neural markers of error processing. In this review, we evaluate the evidence that abnormalities in these neural markers can serve as sensitive endophenotypes of neuropsychiatric disorders. We describe the behavioral and neural hallmarks of error processing, their mediation by common genetic polymorphisms, and impairments in schizophrenia, obsessive-compulsive disorder, and autism spectrum disorders. We conclude that neural markers of errors meet several important criteria as endophenotypes including heritability, established neuroanatomical and neurochemical substrates, association with neuropsychiatric disorders, presence in syndromally-unaffected family members, and evidence of genetic mediation. Understanding the mechanisms of error processing deficits in neuropsychiatric disorders may provide novel neural and behavioral targets for treatment and sensitive surrogate markers of treatment response. Treating error processing deficits may improve functional outcome since error signals provide crucial information for flexible adaptation to changing environments. Given the dearth of effective interventions for cognitive deficits in neuropsychiatric disorders, this represents a promising approach.

Neural markers of errors as endophenotypes in neuropsychiatric disorders.

Science.gov (United States)

Manoach, Dara S; Agam, Yigal

2013-01-01

Learning from errors is fundamental to adaptive human behavior. It requires detecting errors, evaluating what went wrong, and adjusting behavior accordingly. These dynamic adjustments are at the heart of behavioral flexibility and accumulating evidence suggests that deficient error processing contributes to maladaptively rigid and repetitive behavior in a range of neuropsychiatric disorders. Neuroimaging and electrophysiological studies reveal highly reliable neural markers of error processing. In this review, we evaluate the evidence that abnormalities in these neural markers can serve as sensitive endophenotypes of neuropsychiatric disorders. We describe the behavioral and neural hallmarks of error processing, their mediation by common genetic polymorphisms, and impairments in schizophrenia, obsessive-compulsive disorder, and autism spectrum disorders. We conclude that neural markers of errors meet several important criteria as endophenotypes including heritability, established neuroanatomical and neurochemical substrates, association with neuropsychiatric disorders, presence in syndromally-unaffected family members, and evidence of genetic mediation. Understanding the mechanisms of error processing deficits in neuropsychiatric disorders may provide novel neural and behavioral targets for treatment and sensitive surrogate markers of treatment response. Treating error processing deficits may improve functional outcome since error signals provide crucial information for flexible adaptation to changing environments. Given the dearth of effective interventions for cognitive deficits in neuropsychiatric disorders, this represents a potentially promising approach.

In vitro generation of three-dimensional substrate-adherent embryonic stem cell-derived neural aggregates for application in animal models of neurological disorders.

Science.gov (United States)

Hargus, Gunnar; Cui, Yi-Fang; Dihné, Marcel; Bernreuther, Christian; Schachner, Melitta

2012-05-01

In vitro-differentiated embryonic stem (ES) cells comprise a useful source for cell replacement therapy, but the efficiency and safety of a translational approach are highly dependent on optimized protocols for directed differentiation of ES cells into the desired cell types in vitro. Furthermore, the transplantation of three-dimensional ES cell-derived structures instead of a single-cell suspension may improve graft survival and function by providing a beneficial microenvironment for implanted cells. To this end, we have developed a new method to efficiently differentiate mouse ES cells into neural aggregates that consist predominantly (>90%) of postmitotic neurons, neural progenitor cells, and radial glia-like cells. When transplanted into the excitotoxically lesioned striatum of adult mice, these substrate-adherent embryonic stem cell-derived neural aggregates (SENAs) showed significant advantages over transplanted single-cell suspensions of ES cell-derived neural cells, including improved survival of GABAergic neurons, increased cell migration, and significantly decreased risk of teratoma formation. Furthermore, SENAs mediated functional improvement after transplantation into animal models of Parkinson's disease and spinal cord injury. This unit describes in detail how SENAs are efficiently derived from mouse ES cells in vitro and how SENAs are isolated for transplantation. Furthermore, methods are presented for successful implantation of SENAs into animal models of Huntington's disease, Parkinson's disease, and spinal cord injury to study the effects of stem cell-derived neural aggregates in a disease context in vivo.

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.

Neural cell 3D microtissue formation is marked by cytokines' up-regulation.

Directory of Open Access Journals (Sweden)

Yinzhi Lai

Full Text Available Cells cultured in three dimensional (3D scaffolds as opposed to traditional two-dimensional (2D substrates have been considered more physiologically relevant based on their superior ability to emulate the in vivo environment. Combined with stem cell technology, 3D cell cultures can provide a promising alternative for use in cell-based assays or biosensors in non-clinical drug discovery studies. To advance 3D culture technology, a case has been made for identifying and validating three-dimensionality biomarkers. With this goal in mind, we conducted a transcriptomic expression comparison among neural progenitor cells cultured on 2D substrates, 3D porous polystyrene scaffolds, and as 3D neurospheres (in vivo surrogate. Up-regulation of cytokines as a group in 3D and neurospheres was observed. A group of 13 cytokines were commonly up-regulated in cells cultured in polystyrene scaffolds and neurospheres, suggesting potential for any or a combination from this list to serve as three-dimensionality biomarkers. These results are supportive of further cytokine identification and validation studies with cells from non-neural tissue.

Neural Correlates of Contrast and Humor: Processing Common Features of Verbal Irony

Science.gov (United States)

Obert, Alexandre; Gierski, Fabien; Calmus, Arnaud; Flucher, Aurélie; Portefaix, Christophe; Pierot, Laurent; Kaladjian, Arthur; Caillies, Stéphanie

2016-01-01

Irony is a kind of figurative language used by a speaker to say something that contrasts with the context and, to some extent, lends humor to a situation. However, little is known about the brain regions that specifically support the processing of these two common features of irony. The present study had two main aims: (i) investigate the neural basis of irony processing, by delivering short ironic spoken sentences (and their literal counterparts) to participants undergoing fMRI; and (ii) assess the neural effect of two irony parameters, obtained from normative studies: degree of contrast and humor appreciation. Results revealed activation of the bilateral inferior frontal gyrus (IFG), posterior part of the left superior temporal gyrus, medial frontal cortex, and left caudate during irony processing, suggesting the involvement of both semantic and theory-of-mind networks. Parametric models showed that contrast was specifically associated with the activation of bilateral frontal and subcortical areas, and that these regions were also sensitive to humor, as shown by a conjunction analysis. Activation of the bilateral IFG is consistent with the literature on humor processing, and reflects incongruity detection/resolution processes. Moreover, the activation of subcortical structures can be related to the reward processing of social events. PMID:27851821

Cross-Modal Decoding of Neural Patterns Associated with Working Memory: Evidence for Attention-Based Accounts of Working Memory.

Science.gov (United States)

Majerus, Steve; Cowan, Nelson; Péters, Frédéric; Van Calster, Laurens; Phillips, Christophe; Schrouff, Jessica

2016-01-01

Recent studies suggest common neural substrates involved in verbal and visual working memory (WM), interpreted as reflecting shared attention-based, short-term retention mechanisms. We used a machine-learning approach to determine more directly the extent to which common neural patterns characterize retention in verbal WM and visual WM. Verbal WM was assessed via a standard delayed probe recognition task for letter sequences of variable length. Visual WM was assessed via a visual array WM task involving the maintenance of variable amounts of visual information in the focus of attention. We trained a classifier to distinguish neural activation patterns associated with high- and low-visual WM load and tested the ability of this classifier to predict verbal WM load (high-low) from their associated neural activation patterns, and vice versa. We observed significant between-task prediction of load effects during WM maintenance, in posterior parietal and superior frontal regions of the dorsal attention network; in contrast, between-task prediction in sensory processing cortices was restricted to the encoding stage. Furthermore, between-task prediction of load effects was strongest in those participants presenting the highest capacity for the visual WM task. This study provides novel evidence for common, attention-based neural patterns supporting verbal and visual WM. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Culture-sensitive neural substrates of human cognition: a transcultural neuroimaging approach.

Science.gov (United States)

Han, Shihui; Northoff, Georg

2008-08-01

Our brains and minds are shaped by our experiences, which mainly occur in the context of the culture in which we develop and live. Although psychologists have provided abundant evidence for diversity of human cognition and behaviour across cultures, the question of whether the neural correlates of human cognition are also culture-dependent is often not considered by neuroscientists. However, recent transcultural neuroimaging studies have demonstrated that one's cultural background can influence the neural activity that underlies both high- and low-level cognitive functions. The findings provide a novel approach by which to distinguish culture-sensitive from culture-invariant neural mechanisms of human cognition.

Cultured Neural Networks: Optimization of Patterned Network Adhesiveness and Characterization of their Neural Activity

Directory of Open Access Journals (Sweden)

W. L. C. Rutten

2006-01-01

Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

Fractionating the Neural Substrates of Incidental Recognition Memory

Science.gov (United States)

Greene, Ciara M.; Vidaki, Kleio; Soto, David

2015-01-01

Familiar stimuli are typically accompanied by decreases in neural response relative to the presentation of novel items, but these studies often include explicit instructions to discriminate old and new items; this creates difficulties in partialling out the contribution of top-down intentional orientation to the items based on recognition goals.…

Common brain activations for painful and non-painful aversive stimuli

Directory of Open Access Journals (Sweden)

Hayes Dave J

2012-06-01

Full Text Available Abstract Background Identification of potentially harmful stimuli is necessary for the well-being and self-preservation of all organisms. However, the neural substrates involved in the processing of aversive stimuli are not well understood. For instance, painful and non-painful aversive stimuli are largely thought to activate different neural networks. However, it is presently unclear whether there is a common aversion-related network of brain regions responsible for the basic processing of aversive stimuli. To help clarify this issue, this report used a cross-species translational approach in humans (i.e. meta-analysis and rodents (i.e. systematic review of functional neuroanatomy. Results Animal and human data combined to show a core aversion-related network, consisting of similar cortical (i.e. MCC, PCC, AI, DMPFC, RTG, SMA, VLOFC; see results section or abbreviation section for full names and subcortical (i.e. Amyg, BNST, DS, Hab, Hipp/Parahipp, Hyp, NAc, NTS, PAG, PBN, raphe, septal nuclei, Thal, LC, midbrain regions. In addition, a number of regions appeared to be more involved in pain-related (e.g. sensory cortex or non-pain-related (e.g. amygdala aversive processing. Conclusions This investigation suggests that aversive processing, at the most basic level, relies on similar neural substrates, and that differential responses may be due, in part, to the recruitment of additional structures as well as the spatio-temporal dynamic activity of the network. This network perspective may provide a clearer understanding of why components of this circuit appear dysfunctional in some psychiatric and pain-related disorders.

Nano-topography Enhances Communication in Neural Cells Networks

KAUST Repository

Onesto, V.

2017-08-23

Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can direct nerve cells assembly into computational efficient networks may provide new tools and criteria for tissue engineering and regenerative medicine. In this work, we used information theory approaches and functional multi calcium imaging (fMCI) techniques to examine how information flows in neural networks cultured on surfaces with controlled topography. We found that substrate roughness Sa affects networks topology. In the low nano-meter range, S-a = 0-30 nm, information increases with Sa. Moreover, we found that energy density of a network of cells correlates to the topology of that network. This reinforces the view that information, energy and surface nano-topography are tightly inter-connected and should not be neglected when studying cell-cell interaction in neural tissue repair and regeneration.

Common and unique gray matter correlates of episodic memory dysfunction in frontotemporal dementia and Alzheimer's disease.

Science.gov (United States)

Irish, Muireann; Piguet, Olivier; Hodges, John R; Hornberger, Michael

2014-04-01

Conflicting evidence exists regarding the integrity of episodic memory in the behavioral variant of frontotemporal dementia (bvFTD). Recent converging evidence suggests that episodic memory in progressive cases of bvFTD is compromised to the same extent as in Alzheimer's disease (AD). The underlying neural substrates of these episodic memory deficits, however, likely differ contingent on dementia type. In this study we sought to elucidate the neural substrates of episodic memory performance, across recall and recognition tasks, in both patient groups using voxel-based morphometry (VBM) analyses. We predicted that episodic memory dysfunction would be apparent in both patient groups but would relate to divergent patterns of neural atrophy specific to each dementia type. We assessed episodic memory, across verbal and visual domains, in 19 bvFTD, 18 AD patients, and 19 age- and education-matched controls. Behaviorally, patient groups were indistinguishable for immediate and delayed recall, across verbal and visual domains. Whole-brain VBM analyses revealed regions commonly implicated in episodic retrieval across groups, namely the right temporal pole, right frontal lobe, left paracingulate gyrus, and right anterior hippocampus. Divergent neural networks specific to each group were also identified. Whereas a widespread network including posterior regions such as the posterior cingulate cortex, parietal and occipital cortices was exclusively implicated in AD, the frontal and anterior temporal lobes underpinned the episodic memory deficits in bvFTD. Our results point to distinct neural changes underlying episodic memory decline specific to each dementia syndrome. Copyright © 2013 Wiley Periodicals, Inc.

Neural substrates underlying stimulation-enhanced motor skill learning after stroke.

Science.gov (United States)

Lefebvre, Stéphanie; Dricot, Laurence; Laloux, Patrice; Gradkowski, Wojciech; Desfontaines, Philippe; Evrard, Frédéric; Peeters, André; Jamart, Jacques; Vandermeeren, Yves

2015-01-01

Motor skill learning is one of the key components of motor function recovery after stroke, especially recovery driven by neurorehabilitation. Transcranial direct current stimulation can enhance neurorehabilitation and motor skill learning in stroke patients. However, the neural mechanisms underlying the retention of stimulation-enhanced motor skill learning involving a paretic upper limb have not been resolved. These neural substrates were explored by means of functional magnetic resonance imaging. Nineteen chronic hemiparetic stroke patients participated in a double-blind, cross-over randomized, sham-controlled experiment with two series. Each series consisted of two sessions: (i) an intervention session during which dual transcranial direct current stimulation or sham was applied during motor skill learning with the paretic upper limb; and (ii) an imaging session 1 week later, during which the patients performed the learned motor skill. The motor skill learning task, called the 'circuit game', involves a speed/accuracy trade-off and consists of moving a pointer controlled by a computer mouse along a complex circuit as quickly and accurately as possible. Relative to the sham series, dual transcranial direct current stimulation applied bilaterally over the primary motor cortex during motor skill learning with the paretic upper limb resulted in (i) enhanced online motor skill learning; (ii) enhanced 1-week retention; and (iii) superior transfer of performance improvement to an untrained task. The 1-week retention's enhancement driven by the intervention was associated with a trend towards normalization of the brain activation pattern during performance of the learned motor skill relative to the sham series. A similar trend towards normalization relative to sham was observed during performance of a simple, untrained task without a speed/accuracy constraint, despite a lack of behavioural difference between the dual transcranial direct current stimulation and sham

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

From UBE3A to Angelman syndrome: a substrate perspective

Directory of Open Access Journals (Sweden)

Gabrielle L Sell

2015-09-01

Full Text Available Angelman syndrome (AS is a debilitating neurodevelopmental disorder that is characterized by motor dysfunction, intellectual disability, speech impairment, seizures and common features of autism spectrum disorders (ASDs. Some of these AS related phenotypes can be seen in other neurodevelopmental disorders (Williams, 2011;Tan et al., 2014. AS patients commonly carry mutations that render the maternally inherited UBE3A gene nonfunctional. Duplication of the chromosomal region containing the UBE3A gene is associated with ASDs. Although the causative role for UBE3A gene mutations in AS is well established, a long-standing challenge in AS research has been to identify neural substrates of UBE3A, an E3 ubiquitin ligase. A prevailing hypothesis is that changes in UBE3A protein levels would alter the levels of a collection of protein substrates, giving rise to the unique phenotypic aspects of AS and possibly UBE3A associated ASDs. Interestingly, proteins altered in AS are linked to additional ASDs that are not previously associated with changes in UBE3A, indicating a possible molecular overlap underlying the broad-spectrum phenotypes of these neurogenetic disorders. This idea raises the possibility that there may exist a one-size-fits-all approach to the treatment of neurogenetic disorders with phenotypes overlapping AS. Furthermore, while a comprehensive list of UBE3A substrates and downstream affected pathways should be developed, this is only part of the story. The timing of when UBE3A protein functions, through either changes in UBE3A or possibly substrate expression patterns, appears to be critical for AS phenotype development. These data call for further investigation of UBE3A substrates and their timing of action relevant to AS phenotypes.

Development and Evaluation of Micro-Electrocorticography Arrays for Neural Interfacing Applications

Science.gov (United States)

Schendel, Amelia Ann

Neural interfaces have great promise for both electrophysiological research and therapeutic applications. Whether for the study of neural circuitry or for neural prosthetic or other therapeutic applications, micro-electrocorticography (micro-ECoG) arrays have proven extremely useful as neural interfacing devices. These devices strike a balance between invasiveness and signal resolution, an important step towards eventual human application. The objective of this research was to make design improvements to micro-ECoG devices to enhance both biocompatibility and device functionality. To best evaluate the effectiveness of these improvements, a cranial window imaging method for in vivo monitoring of the longitudinal tissue response post device implant was developed. Employment of this method provided valuable insight into the way tissue grows around micro-ECoG arrays after epidural implantation, spurring a study of the effects of substrate geometry on the meningeal tissue response. The results of the substrate footprint comparison suggest that a more open substrate geometry provides an easy path for the tissue to grow around to the top side of the device, whereas a solid device substrate encourages the tissue to thicken beneath the device, between the electrode sites and the brain. The formation of thick scar tissue between the recording electrode sites and the neural tissue is disadvantageous for long-term recorded signal quality, and thus future micro-ECoG device designs should incorporate open-architecture substrates for enhanced longitudinal in vivo function. In addition to investigating improvements for long-term device reliability, it was also desired to enhance the functionality of micro-ECoG devices for neural electrophysiology research applications. To achieve this goal, a completely transparent graphene-based device was fabricated for use with the cranial window imaging method and optogenetic techniques. The use of graphene as the conductive material provided

The neural substrates of impaired finger tapping regularity after stroke.

Science.gov (United States)

Calautti, Cinzia; Jones, P Simon; Guincestre, Jean-Yves; Naccarato, Marcello; Sharma, Nikhil; Day, Diana J; Carpenter, T Adrian; Warburton, Elizabeth A; Baron, Jean-Claude

2010-03-01

Not only finger tapping speed, but also tapping regularity can be impaired after stroke, contributing to reduced dexterity. The neural substrates of impaired tapping regularity after stroke are unknown. Previous work suggests damage to the dorsal premotor cortex (PMd) and prefrontal cortex (PFCx) affects externally-cued hand movement. We tested the hypothesis that these two areas are involved in impaired post-stroke tapping regularity. In 19 right-handed patients (15 men/4 women; age 45-80 years; purely subcortical in 16) partially to fully recovered from hemiparetic stroke, tri-axial accelerometric quantitative assessment of tapping regularity and BOLD fMRI were obtained during fixed-rate auditory-cued index-thumb tapping, in a single session 10-230 days after stroke. A strong random-effect correlation between tapping regularity index and fMRI signal was found in contralesional PMd such that the worse the regularity the stronger the activation. A significant correlation in the opposite direction was also present within contralesional PFCx. Both correlations were maintained if maximal index tapping speed, degree of paresis and time since stroke were added as potential confounds. Thus, the contralesional PMd and PFCx appear to be involved in the impaired ability of stroke patients to fingertap in pace with external cues. The findings for PMd are consistent with repetitive TMS investigations in stroke suggesting a role for this area in affected-hand movement timing. The inverse relationship with tapping regularity observed for the PFCx and the PMd suggests these two anatomically-connected areas negatively co-operate. These findings have implications for understanding the disruption and reorganization of the motor systems after stroke. Copyright (c) 2009 Elsevier Inc. All rights reserved.

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 ...

The neural substrates of social influence on decision making.

Science.gov (United States)

Tomlin, Damon; Nedic, Andrea; Prentice, Deborah A; Holmes, Philip; Cohen, Jonathan D

2013-01-01

The mechanisms that govern human learning and decision making under uncertainty have been the focus of intense behavioral and, more recently, neuroscientific investigation. Substantial progress has been made in building models of the processes involved, and identifying underlying neural mechanisms using simple, two-alternative forced choice decision tasks. However, less attention has been given to how social information influences these processes, and the neural systems that mediate this influence. Here we sought to address these questions by using tasks similar to ones that have been used to study individual decision making behavior, and adding conditions in which participants were given trial-by-trial information about the performance of other individuals (their choices and/or their rewards) simultaneously playing the same tasks. We asked two questions: How does such information about the behavior of others influence performance in otherwise simple decision tasks, and what neural systems mediate this influence? We found that bilateral insula exhibited a parametric relationship to the degree of misalignment of the individual's performance with those of others in the group. Furthermore, activity in the bilateral insula significantly predicted participants' subsequent choices to align their behavior with others in the group when they were misaligned either in their choices (independent of success) or their degree of success (independent of specific choices). These findings add to the growing body of empirical data suggesting that the insula participates in an important way in social information processing and decision making.

Neural correlates of sad feelings in healthy girls.

Science.gov (United States)

Lévesque, J; Joanette, Y; Mensour, B; Beaudoin, G; Leroux, J-M; Bourgouin, P; Beauregard, M

2003-01-01

Emotional development is indisputably one of the cornerstones of personality development during infancy. According to the differential emotions theory (DET), primary emotions are constituted of three distinct components: the neural-evaluative, the expressive, and the experiential. The DET further assumes that these three components are biologically based and functional nearly from birth. Such a view entails that the neural substrate of primary emotions must be similar in children and adults. Guided by this assumption of the DET, the present functional magnetic resonance imaging study was conducted to identify the neural correlates of sad feelings in healthy children. Fourteen healthy girls (aged 8-10) were scanned while they watched sad film excerpts aimed at externally inducing a transient state of sadness (activation task). Emotionally neutral film excerpts were also presented to the subjects (reference task). The subtraction of the brain activity measured during the viewing of the emotionally neutral film excerpts from that noted during the viewing of the sad film excerpts revealed that sad feelings were associated with significant bilateral activations of the midbrain, the medial prefrontal cortex (Brodmann area [BA] 10), and the anterior temporal pole (BA 21). A significant locus of activation was also noted in the right ventrolateral prefrontal cortex (BA 47). These results are compatible with those of previous functional neuroimaging studies of sadness in adults. They suggest that the neural substrate underlying the subjective experience of sadness is comparable in children and adults. Such a similitude provides empirical support to the DET assumption that the neural substrate of primary emotions is biologically based.

Functional overlap of top-down emotion regulation and generation: an fMRI study identifying common neural substrates between cognitive reappraisal and cognitively generated emotions.

Science.gov (United States)

Otto, Benjamin; Misra, Supriya; Prasad, Aditya; McRae, Kateri

2014-09-01

One factor that influences the success of emotion regulation is the manner in which the regulated emotion was generated. Recent research has suggested that reappraisal, a top-down emotion regulation strategy, is more effective in decreasing self-reported negative affect when emotions were generated from the top-down, versus the bottom-up. On the basis of a process overlap framework, we hypothesized that the neural regions active during reappraisal would overlap more with emotions that were generated from the top-down, rather than from the bottom-up. In addition, we hypothesized that increased neural overlap between reappraisal and the history effects of top-down emotion generation would be associated with increased reappraisal success. The results of several analyses suggested that reappraisal and emotions that were generated from the top-down share a core network of prefrontal, temporal, and cingulate regions. This overlap is specific; no such overlap was observed between reappraisal and emotions that were generated in a bottom-up fashion. This network consists of regions previously implicated in linguistic processing, cognitive control, and self-relevant appraisals, which are processes thought to be crucial to both reappraisal and top-down emotion generation. Furthermore, individuals with high reappraisal success demonstrated greater neural overlap between reappraisal and the history of top-down emotion generation than did those with low reappraisal success. The overlap of these key regions, reflecting overlapping processes, provides an initial insight into the mechanism by which generation history may facilitate emotion regulation.

Using Neural Pattern Classifiers to Quantify the Modularity of Conflict–Control Mechanisms in the Human Brain

Science.gov (United States)

Jiang, Jiefeng; Egner, Tobias

2014-01-01

Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict–control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of “searchlight” classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict–control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict–control were not. Overall, these findings suggest a hybrid neural architecture of conflict–control that entails both modular (domain specific) and global (domain general) components. PMID:23402762

Diminished neural responses predict enhanced intrinsic motivation and sensitivity to external incentive.

Science.gov (United States)

Marsden, Karen E; Ma, Wei Ji; Deci, Edward L; Ryan, Richard M; Chiu, Pearl H

2015-06-01

The duration and quality of human performance depend on both intrinsic motivation and external incentives. However, little is known about the neuroscientific basis of this interplay between internal and external motivators. Here, we used functional magnetic resonance imaging to examine the neural substrates of intrinsic motivation, operationalized as the free-choice time spent on a task when this was not required, and tested the neural and behavioral effects of external reward on intrinsic motivation. We found that increased duration of free-choice time was predicted by generally diminished neural responses in regions associated with cognitive and affective regulation. By comparison, the possibility of additional reward improved task accuracy, and specifically increased neural and behavioral responses following errors. Those individuals with the smallest neural responses associated with intrinsic motivation exhibited the greatest error-related neural enhancement under the external contingency of possible reward. Together, these data suggest that human performance is guided by a "tonic" and "phasic" relationship between the neural substrates of intrinsic motivation (tonic) and the impact of external incentives (phasic).

Perceptual asymmetry reveals neural substrates underlying stereoscopic transparency.

Science.gov (United States)

Tsirlin, Inna; Allison, Robert S; Wilcox, Laurie M

2012-02-01

We describe a perceptual asymmetry found in stereoscopic perception of overlaid random-dot surfaces. Specifically, the minimum separation in depth needed to perceptually segregate two overlaid surfaces depended on the distribution of dots across the surfaces. With the total dot density fixed, significantly larger inter-plane disparities were required for perceptual segregation of the surfaces when the front surface had fewer dots than the back surface compared to when the back surface was the one with fewer dots. We propose that our results reflect an asymmetry in the signal strength of the front and back surfaces due to the assignment of the spaces between the dots to the back surface by disparity interpolation. This hypothesis was supported by the results of two experiments designed to reduce the imbalance in the neuronal response to the two surfaces. We modeled the psychophysical data with a network of inter-neural connections: excitatory within-disparity and inhibitory across disparity, where the spread of disparity was modulated according to figure-ground assignment. These psychophysical and computational findings suggest that stereoscopic transparency depends on both inter-neural interactions of disparity-tuned cells and higher-level processes governing figure ground segregation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Selective attention modulates neural substrates of repetition priming and "implicit" visual memory: suppressions and enhancements revealed by FMRI.

Science.gov (United States)

Vuilleumier, Patrik; Schwartz, Sophie; Duhoux, Stéphanie; Dolan, Raymond J; Driver, Jon

2005-08-01

Attention can enhance processing for relevant information and suppress this for ignored stimuli. However, some residual processing may still arise without attention. Here we presented overlapping outline objects at study, with subjects attending to those in one color but not the other. Attended objects were subsequently recognized on a surprise memory test, whereas there was complete amnesia for ignored items on such direct explicit testing; yet reliable behavioral priming effects were found on indirect testing. Event-related fMRI examined neural responses to previously attended or ignored objects, now shown alone in the same or mirror-reversed orientation as before, intermixed with new items. Repetition-related decreases in fMRI responses for objects previously attended and repeated in the same orientation were found in the right posterior fusiform, lateral occipital, and left inferior frontal cortex. More anterior fusiform regions also showed some repetition decreases for ignored objects, irrespective of orientation. View-specific repetition decreases were found in the striate cortex, particularly for previously attended items. In addition, previously ignored objects produced some fMRI response increases in the bilateral lingual gyri, relative to new objects. Selective attention at exposure can thus produce several distinct long-term effects on processing of stimuli repeated later, with neural response suppression stronger for previously attended objects, and some response enhancement for previously ignored objects, with these effects arising in different brain areas. Although repetition decreases may relate to positive priming phenomena, the repetition increases for ignored objects shown here for the first time might relate to processes that can produce "negative priming" in some behavioral studies. These results reveal quantitative and qualitative differences between neural substrates of long-term repetition effects for attended versus unattended objects.

Neural substrates underlying the tendency to accept anger-infused ultimatum offers during dynamic social interactions.

Science.gov (United States)

Gilam, Gadi; Lin, Tamar; Raz, Gal; Azrielant, Shir; Fruchter, Eyal; Ariely, Dan; Hendler, Talma

2015-10-15

In managing our way through interpersonal conflict, anger might be crucial in determining whether the dispute escalates to aggressive behaviors or resolves cooperatively. The Ultimatum Game (UG) is a social decision-making paradigm that provides a framework for studying interpersonal conflict over division of monetary resources. Unfair monetary UG-offers elicit anger and while accepting them engages regulatory processes, rejecting them is regarded as an aggressive retribution. Ventro-medial prefrontal-cortex (vmPFC) activity has been shown to relate to idiosyncratic tendencies in accepting unfair offers possibly through its role in emotion regulation. Nevertheless, standard UG paradigms lack fundamental aspects of real-life social interactions in which one reacts to other people in a response contingent fashion. To uncover the neural substrates underlying the tendency to accept anger-infused ultimatum offers during dynamic social interactions, we incorporated on-line verbal negotiations with an obnoxious partner in a repeated-UG during fMRI scanning. We hypothesized that vmPFC activity will differentiate between individuals with high or low monetary gains accumulated throughout the game and reflect a divergence in the associated emotional experience. We found that as individuals gained more money, they reported less anger but also more positive feelings and had slower sympathetic response. In addition, high-gain individuals had increased vmPFC activity, but also decreased brainstem activity, which possibly reflected the locus coeruleus. During the more angering unfair offers, these individuals had increased dorsal-posterior Insula (dpI) activity which functionally coupled to the medial-thalamus (mT). Finally, both vmPFC activity and dpI-mT connectivity contributed to increased gain, possibly by modulating the ongoing subjective emotional experience. These ecologically valid findings point towards a neural mechanism that might nurture pro-social interactions by

Neural Substrates of Spontaneous Narrative Production in Focal Neurodegenerative Disease

Science.gov (United States)

Gola, Kelly A.; Thorne, Avril; Veldhuisen, Lisa D.; Felix, Cordula M.; Hankinson, Sarah; Pham, Julie; Shany-Ur, Tal; Schauer, Guido P.; Stanley, Christine M.; Glenn, Shenly; Miller, Bruce L.; Rankin, Katherine P.

2016-01-01

Conversational storytelling integrates diverse cognitive and socio-emotional abilities that critically differ across neurodegenerative disease groups and may have diagnostic relevance and predict anatomic changes. The present study employed mixed methods discourse and quantitative analyses to delineate patterns of storytelling across focal neurodegenerative disease groups, and to clarify the neuroanatomical contributions to common storytelling characteristics in these patients. Transcripts of spontaneous social interactions of 46 participants (15 behavioral variant frontotemporal dementia (bvFTD), 7 semantic variant primary progressive aphasia (svPPA), 12 Alzheimer's disease (AD), and 12 healthy older normal controls) were analysed for storytelling characteristics and frequency, and videos of the interactions were rated for patients' social attentiveness. Compared to controls, svPPAs also told more stories and autobiographical stories, and perseverated on aspects of self during storytelling. ADs told fewer autobiographical stories than NCs, and svPPAs and bvFTDs failed to attend to social cues. Storytelling characteristics were associated with a processing speed and mental flexibility, and voxel-based anatomic analysis of structural magnetic resonance imaging revealed that temporal organization, evaluations, and social attention correlated with atrophy corresponding to known intrinsic connectivity networks, including the default mode, limbic, salience, and stable task control networks. Differences in spontaneous storytelling among neurodegenerative groups elucidated diverse cognitive, socio-emotional, and neural contributions to narrative production, with implications for diagnostic screening and therapeutic intervention. PMID:26485159

Disgust proneness and associated neural substrates in obesity.

Science.gov (United States)

Watkins, Tristan J; Di Iorio, Christina R; Olatunji, Bunmi O; Benningfield, Margaret M; Blackford, Jennifer U; Dietrich, Mary S; Bhatia, Monisha; Theiss, Justin D; Salomon, Ronald M; Niswender, Kevin; Cowan, Ronald L

2016-03-01

Defects in experiencing disgust may contribute to obesity by allowing for the overconsumption of food. However, the relationship of disgust proneness and its associated neural locus has yet to be explored in the context of obesity. Thirty-three participants (17 obese, 16 lean) completed the Disgust Propensity and Sensitivity Scale-Revised and a functional magnetic resonance imaging paradigm where images from 4 categories (food, contaminates, contaminated food or fixation) were randomly presented. Independent two-sample t-tests revealed significantly lower levels of Disgust Sensitivity for the obese group (mean score = 14.7) compared with the lean group (mean score = 17.6, P = 0.026). The obese group had less activation in the right insula than the lean group when viewing contaminated food images. Multiple regression with interaction analysis revealed one left insula region where the association of Disgust Sensitivity scores with activation differed by group when viewing contaminated food images. These interaction effects were driven by the negative correlation of Disgust Sensitivity scores with beta values extracted from the left insula in the obese group (r = -0.59) compared with a positive correlation in the lean group (r = 0.65). Given these body mass index-dependent differences in Disgust Sensitivity and neural responsiveness to disgusting food images, it is likely that altered Disgust Sensitivity may contribute to obesity. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Using neural pattern classifiers to quantify the modularity of conflict-control mechanisms in the human brain.

Science.gov (United States)

Jiang, Jiefeng; Egner, Tobias

2014-07-01

Resolving conflicting sensory and motor representations is a core function of cognitive control, but it remains uncertain to what degree control over different sources of conflict is implemented by shared (domain general) or distinct (domain specific) neural resources. Behavioral data suggest conflict-control to be domain specific, but results from neuroimaging studies have been ambivalent. Here, we employed multivoxel pattern analyses that can decode a brain region's informational content, allowing us to distinguish incidental activation overlap from actual shared information processing. We trained independent sets of "searchlight" classifiers on functional magnetic resonance imaging data to decode control processes associated with stimulus-conflict (Stroop task) and ideomotor-conflict (Simon task). Quantifying the proportion of domain-specific searchlights (capable of decoding only one type of conflict) and domain-general searchlights (capable of decoding both conflict types) in each subject, we found both domain-specific and domain-general searchlights, though the former were more common. When mapping anatomical loci of these searchlights across subjects, neural substrates of stimulus- and ideomotor-specific conflict-control were found to be anatomically consistent across subjects, whereas the substrates of domain-general conflict-control were not. Overall, these findings suggest a hybrid neural architecture of conflict-control that entails both modular (domain specific) and global (domain general) components. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A common functional neural network for overt production of speech and gesture.

Science.gov (United States)

Marstaller, L; Burianová, H

2015-01-22

The perception of co-speech gestures, i.e., hand movements that co-occur with speech, has been investigated by several studies. The results show that the perception of co-speech gestures engages a core set of frontal, temporal, and parietal areas. However, no study has yet investigated the neural processes underlying the production of co-speech gestures. Specifically, it remains an open question whether Broca's area is central to the coordination of speech and gestures as has been suggested previously. The objective of this study was to use functional magnetic resonance imaging to (i) investigate the regional activations underlying overt production of speech, gestures, and co-speech gestures, and (ii) examine functional connectivity with Broca's area. We hypothesized that co-speech gesture production would activate frontal, temporal, and parietal regions that are similar to areas previously found during co-speech gesture perception and that both speech and gesture as well as co-speech gesture production would engage a neural network connected to Broca's area. Whole-brain analysis confirmed our hypothesis and showed that co-speech gesturing did engage brain areas that form part of networks known to subserve language and gesture. Functional connectivity analysis further revealed a functional network connected to Broca's area that is common to speech, gesture, and co-speech gesture production. This network consists of brain areas that play essential roles in motor control, suggesting that the coordination of speech and gesture is mediated by a shared motor control network. Our findings thus lend support to the idea that speech can influence co-speech gesture production on a motoric level. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

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.

The insula: a critical neural substrate for craving and drug seeking under conflict and risk.

Science.gov (United States)

Naqvi, Nasir H; Gaznick, Natassia; Tranel, Daniel; Bechara, Antoine

2014-05-01

Drug addiction is characterized by the inability to control drug use when it results in negative consequences or conflicts with more adaptive goals. Our previous work showed that damage to the insula disrupted addiction to cigarette smoking-the first time that the insula was shown to be a critical neural substrate for addiction. Here, we review those findings, as well as more recent studies that corroborate and extend them, demonstrating the role of the insula in (1) incentive motivational processes that drive addictive behavior, (2) control processes that moderate or inhibit addictive behavior, and (3) interoceptive processes that represent bodily states associated with drug use. We then describe a theoretical framework that attempts to integrate these seemingly disparate findings. In this framework, the insula functions in the recall of interoceptive drug effects during craving and drug seeking under specific conditions where drug taking is perceived as risky and/or where there is conflict between drug taking and more adaptive goals. We describe this framework in an evolutionary context and discuss its implications for understanding the mechanisms of behavior change in addiction treatments. © 2014 New York Academy of Sciences.

Neural substrates of reliability-weighted visual-tactile multisensory integration

Directory of Open Access Journals (Sweden)

Michael S Beauchamp

2010-06-01

Full Text Available As sensory systems deteriorate in aging or disease, the brain must relearn the appropriate weights to assign each modality during multisensory integration. Using blood-oxygen level dependent functional magnetic resonance imaging (BOLD fMRI of human subjects, we tested a model for the neural mechanisms of sensory weighting, termed “weighted connections”. This model holds that the connection weights between early and late areas vary depending on the reliability of the modality, independent of the level of early sensory cortex activity. When subjects detected viewed and felt touches to the hand, a network of brain areas was active, including visual areas in lateral occipital cortex, somatosensory areas in inferior parietal lobe, and multisensory areas in the intraparietal sulcus (IPS. In agreement with the weighted connection model, the connection weight measured with structural equation modeling between somatosensory cortex and IPS increased for somatosensory-reliable stimuli, and the connection weight between visual cortex and IPS increased for visual-reliable stimuli. This double dissociation of connection strengths was similar to the pattern of behavioral responses during incongruent multisensory stimulation, suggesting that weighted connections may be a neural mechanism for behavioral reliability weighting.for behavioral reliability weighting.

Common and dissociable neural correlates associated with component processes of inductive reasoning.

Science.gov (United States)

Jia, Xiuqin; Liang, Peipeng; Lu, Jie; Yang, Yanhui; Zhong, Ning; Li, Kuncheng

2011-06-15

The ability to draw numerical inductive reasoning requires two key cognitive processes, identification and extrapolation. This study aimed to identify the neural correlates of both component processes of numerical inductive reasoning using event-related fMRI. Three kinds of tasks: rule induction (RI), rule induction and application (RIA), and perceptual judgment (Jud) were solved by twenty right-handed adults. Our results found that the left superior parietal lobule (SPL) extending into the precuneus and left dorsolateral prefrontal cortex (DLPFC) were commonly recruited in the two components. It was also observed that the fronto-parietal network was more specific to identification, whereas the striatal-thalamic network was more specific to extrapolation. The findings suggest that numerical inductive reasoning is mediated by the coordination of multiple brain areas including the prefrontal, parietal, and subcortical regions, of which some are more specific to demands on only one of these two component processes, whereas others are sensitive to both. Copyright © 2011 Elsevier Inc. All rights reserved.

Nanoengineered Polystyrene Surfaces with Nanopore Array Pattern Alters Cytoskeleton Organization and Enhances Induction of Neural Differentiation of Human Adipose-Derived Stem Cells.

Science.gov (United States)

Jung, Ae Ryang; Kim, Richard Y; Kim, Hyung Woo; Shrestha, Kshitiz Raj; Jeon, Seung Hwan; Cha, Kyoung Je; Park, Yong Hyun; Kim, Dong Sung; Lee, Ji Youl

2015-07-01

Human adipose-derived stem cells (hADSCs) can differentiate into various cell types depending on chemical and topographical cues. One topographical cue recently noted to be successful in inducing differentiation is the nanoengineered polystyrene surface containing nanopore array-patterned substrate (NP substrate), which is designed to mimic the nanoscale topographical features of the extracellular matrix. In this study, efficacies of NP and flat substrates in inducing neural differentiation of hADSCs were examined by comparing their substrate-cell adhesion rates, filopodia growth, nuclei elongation, and expression of neural-specific markers. The polystyrene nano Petri dishes containing NP substrates were fabricated by a nano injection molding process using a nickel electroformed nano-mold insert (Diameter: 200 nm. Depth of pore: 500 nm. Center-to-center distance: 500 nm). Cytoskeleton and filopodia structures were observed by scanning electron microscopy and F-actin staining, while cell adhesion was tested by vinculin staining after 24 and 48 h of seeding. Expression of neural specific markers was examined by real-time quantitative polymerase chain reaction and immunocytochemistry. Results showed that NP substrates lead to greater substrate-cell adhesion, filopodia growth, nuclei elongation, and expression of neural specific markers compared to flat substrates. These results not only show the advantages of NP substrates, but they also suggest that further study into cell-substrate interactions may yield great benefits for biomaterial engineering.

Neural substrates of sexual desire in individuals with problematic hypersexual behavior

Directory of Open Access Journals (Sweden)

Ji-Woo eSeok

2015-11-01

Full Text Available Studies on the characteristics of individuals with hypersexual disorder have been accumulating due to increasing concerns about problematic hypersexual behavior (PHB. Currently, relatively little is known about the underlying behavioral and neural mechanisms of sexual desire. Our study aimed to investigate the neural correlates of sexual desire with event-related functional magnetic resonance imaging (fMRI. Twenty-three individuals with PHB and 22 age-matched healthy controls were scanned while they passively viewed sexual and nonsexual stimuli. The subjects’ levels of sexual desire were assessed in response to each sexual stimulus. Relative to controls, individuals with PHB experienced more frequent and enhanced sexual desire during exposure to sexual stimuli. Greater activation was observed in the caudate nucleus, inferior parietal lobe, dorsal anterior cingulate gyrus, thalamus, and dorsolateral prefrontal cortex in the PHB group than in the control group. In addition, the hemodynamic patterns in the activated areas differed between the groups. Consistent with the findings of brain imaging studies of substance and behavior addiction, individuals with the behavioral characteristics of PHB and enhanced desire exhibited altered activation in the prefrontal cortex and subcortical regions. In conclusion, our results will help to characterize the behaviors and associated neural mechanisms of individuals with PHB.

Neural Substrates for Processing Task-Irrelevant Sad Images in Adolescents

Science.gov (United States)

Wang, Lihong; Huettel, Scott; De Bellis, Michael D.

2008-01-01

Neural systems related to cognitive and emotional processing were examined in adolescents using event-related functional magnetic resonance imaging (fMRI). Ten healthy adolescents performed an emotional oddball task. Subjects detected infrequent circles (targets) within a continual stream of phase-scrambled images (standards). Sad and neutral…

Distinct and Shared Endophenotypes of Neural Substrates in Bipolar and Major Depressive Disorders.

Directory of Open Access Journals (Sweden)

Toshio Matsubara

Full Text Available Little is known about disorder-specific biomarkers of bipolar disorder (BD and major depressive disorder (MDD. Our aim was to determine a neural substrate that could be used to distinguish BD from MDD. Our study included a BD group (10 patients with BD, 10 first-degree relatives (FDRs of individuals with BD, MDD group (17 patients with MDD, 17 FDRs of individuals with MDD, and 27 healthy individuals. Structural and functional brain abnormalities were evaluated by voxel-based morphometry and a trail making test (TMT, respectively. The BD group showed a significant main effect of diagnosis in the gray matter (GM volume of the anterior cingulate cortex (ACC; p = 0.01 and left insula (p < 0.01. FDRs of individuals with BD showed significantly smaller left ACC GM volume than healthy subjects (p < 0.01, and patients with BD showed significantly smaller ACC (p < 0.01 and left insular GM volume (p < 0.01 than healthy subjects. The MDD group showed a tendency toward a main effect of diagnosis in the right and left insular GM volume. The BD group showed a significantly inverse correlation between the left insular GM volume and TMT-A scores (p < 0.05. Our results suggest that the ACC volume could be a distinct endophenotype of BD, while the insular volume could be a shared BD and MDD endophenotype. Moreover, the insula could be associated with cognitive decline and poor outcome in BD.

Common Sense in Choice: The Effect of Sensory Modality on Neural Value Representations

Science.gov (United States)

2018-01-01

Abstract Although it is well established that the ventromedial prefrontal cortex (vmPFC) represents value using a common currency across categories of rewards, it is unknown whether the vmPFC represents value irrespective of the sensory modality in which alternatives are presented. In the current study, male and female human subjects completed a decision-making task while their neural activity was recorded using functional magnetic resonance imaging. On each trial, subjects chose between a safe alternative and a lottery, which was presented visually or aurally. A univariate conjunction analysis revealed that the anterior portion of the vmPFC tracks subjective value (SV) irrespective of the sensory modality. Using a novel cross-modality multivariate classifier, we were able to decode auditory value based on visual trials and vice versa. In addition, we found that the visual and auditory sensory cortices, which were identified using functional localizers, are also sensitive to the value of stimuli, albeit in a modality-specific manner. Whereas both primary and higher-order auditory cortices represented auditory SV (aSV), only a higher-order visual area represented visual SV (vSV). These findings expand our understanding of the common currency network of the brain and shed a new light on the interplay between sensory and value information processing. PMID:29619408

Common Sense in Choice: The Effect of Sensory Modality on Neural Value Representations.

Science.gov (United States)

Shuster, Anastasia; Levy, Dino J

2018-01-01

Although it is well established that the ventromedial prefrontal cortex (vmPFC) represents value using a common currency across categories of rewards, it is unknown whether the vmPFC represents value irrespective of the sensory modality in which alternatives are presented. In the current study, male and female human subjects completed a decision-making task while their neural activity was recorded using functional magnetic resonance imaging. On each trial, subjects chose between a safe alternative and a lottery, which was presented visually or aurally. A univariate conjunction analysis revealed that the anterior portion of the vmPFC tracks subjective value (SV) irrespective of the sensory modality. Using a novel cross-modality multivariate classifier, we were able to decode auditory value based on visual trials and vice versa. In addition, we found that the visual and auditory sensory cortices, which were identified using functional localizers, are also sensitive to the value of stimuli, albeit in a modality-specific manner. Whereas both primary and higher-order auditory cortices represented auditory SV (aSV), only a higher-order visual area represented visual SV (vSV). These findings expand our understanding of the common currency network of the brain and shed a new light on the interplay between sensory and value information processing.

Exploring the Neural Substrates of Phonological Recovery for Symposium: Neural Correlates of Recovery and Rehabilitation

Directory of Open Access Journals (Sweden)

Pelagie M Beeson

2015-10-01

All participants improved written language abilities in response to treatment, but one subgroup was limited in their ability to regain phonological skills. Both anterior and posterior components of the perisylvian phonological network were damaged in that group. These findings are consistent with fMRI activation when healthy adults write nonwords, and provide insight regarding neural support necessary for phonological rehabilitation.

Common and distinct neural correlates of facial emotion processing in social anxiety disorder and Williams syndrome: A systematic review and voxel-based meta-analysis of functional resonance imaging studies.

Science.gov (United States)

Binelli, C; Subirà, S; Batalla, A; Muñiz, A; Sugranyés, G; Crippa, J A; Farré, M; Pérez-Jurado, L; Martín-Santos, R

2014-11-01

Social Anxiety Disorder (SAD) and Williams-Beuren Syndrome (WS) are two conditions which seem to be at opposite ends in the continuum of social fear but show compromised abilities in some overlapping areas, including some social interactions, gaze contact and processing of facial emotional cues. The increase in the number of neuroimaging studies has greatly expanded our knowledge of the neural bases of facial emotion processing in both conditions. However, to date, SAD and WS have not been compared. We conducted a systematic review of functional magnetic resonance imaging (fMRI) studies comparing SAD and WS cases to healthy control participants (HC) using facial emotion processing paradigms. Two researchers conducted comprehensive PubMed/Medline searches to identify all fMRI studies of facial emotion processing in SAD and WS. The following search key-words were used: "emotion processing"; "facial emotion"; "social anxiety"; "social phobia"; "Williams syndrome"; "neuroimaging"; "functional magnetic resonance"; "fMRI" and their combinations, as well as terms specifying individual facial emotions. We extracted spatial coordinates from each study and conducted two separate voxel-wise activation likelihood estimation meta-analyses, one for SAD and one for WS. Twenty-two studies met the inclusion criteria: 17 studies of SAD and five of WS. We found evidence for both common and distinct patterns of neural activation. Limbic engagement was common to SAD and WS during facial emotion processing, although we observed opposite patterns of activation for each disorder. Compared to HC, SAD cases showed hyperactivation of the amygdala, the parahippocampal gyrus and the globus pallidus. Compared to controls, participants with WS showed hypoactivation of these regions. Differential activation in a number of regions specific to either condition was also identified: SAD cases exhibited greater activation of the insula, putamen, the superior temporal gyrus, medial frontal regions and

Introduction to the special section on the neural substrate of analogical reasoning and metaphor comprehension.

Science.gov (United States)

Bassok, Miriam; Dunbar, Kevin N; Holyoak, Keith J

2012-03-01

The special section on the neural substrate of relational reasoning includes 4 articles that address the processes and brain regions involved in analogical reasoning (Green, Kraemer, Fugelsang, Gray, & Dunbar, 2011; Maguire, McClelland, Donovan, Tillman, & Krawczyk, 2011) and in metaphor comprehension (Chettih, Durgin, & Grodner, 2011; Prat, Mason, & Just, 2011). We see this work as an example of how neuroscience approaches to cognition can lead to increased understanding of cognitive processes. In this brief introduction, we first situate the 4 articles in the context of prior cognitive neuroscience work on relational reasoning. We then highlight the main issues explored in these articles: different sources of complexity and difficulty in relational processing, potential differences between the roles of the 2 hemispheres, and the impact of individual differences in various cognitive abilities. The 4 articles illustrate a range of methodologies, including functional magnetic resonance imaging (fMRI; Green et al., 2011; Prat et al., 2011), event-related potentials (ERPs; Maguire et al., 2011), and different types of semantic priming (Chettih et al., 2011; Prat et al., 2011). They highlight the connections between research on analogy and on metaphor comprehension and suggest, collectively, that a cognitive neuroscience approach to relational reasoning can lead to converging conclusions. 2012 APA, all rights reserved

The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

Science.gov (United States)

Goñi, Joaquín; Aznárez-Sanado, Maite; Arrondo, Gonzalo; Fernández-Seara, María; Loayza, Francis R; Heukamp, Franz H; Pastor, María A

2011-03-09

Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD) signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC) and left and right pre-supplementary motor areas (pre-SMA) and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively) of the uncertainty associated to an economic decision making paradigm.

Using Brain Stimulation to Disentangle Neural Correlates of Conscious Vision

Directory of Open Access Journals (Sweden)

Tom Alexander de Graaf

2014-09-01

Full Text Available Research into the neural correlates of consciousness (NCCs has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as fMRI or EEG do not always afford inference on the role these brain processes play in conscious vision. Such empirical neural correlates of consciousness could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical neural correlates of consciousness.

Neural correlates underlying musical semantic memory.

Science.gov (United States)

Groussard, M; Viader, F; Landeau, B; Desgranges, B; Eustache, F; Platel, H

2009-07-01

Numerous functional imaging studies have examined the neural basis of semantic memory mainly using verbal and visuospatial materials. Musical material also allows an original way to explore semantic memory processes. We used PET imaging to determine the neural substrates that underlie musical semantic memory using different tasks and stimuli. The results of three PET studies revealed a greater involvement of the anterior part of the temporal lobe. Concerning clinical observations and our neuroimaging data, the musical lexicon (and most widely musical semantic memory) appears to be sustained by a temporo-prefrontal cerebral network involving right and left cerebral regions.

The neural substrates of impaired prosodic detection in schizophrenia and its sensorial antecedents.

Science.gov (United States)

Leitman, David I; Hoptman, Matthew J; Foxe, John J; Saccente, Erica; Wylie, Glenn R; Nierenberg, Jay; Jalbrzikowski, Maria; Lim, Kelvin O; Javitt, Daniel C

2007-03-01

Individuals with schizophrenia show severe deficits in their ability to decode emotions based upon vocal inflection (affective prosody). This study examined neural substrates of prosodic dysfunction in schizophrenia with voxelwise analysis of diffusion tensor magnetic resonance imaging (MRI). Affective prosodic performance was assessed in 19 patients with schizophrenia and 19 comparison subjects with the Voice Emotion Identification Task (VOICEID), along with measures of basic pitch perception and executive processing (Wisconsin Card Sorting Test). Diffusion tensor MRI fractional anisotropy valves were used for voxelwise correlation analyses. In a follow-up experiment, performance on a nonaffective prosodic perception task was assessed in an additional cohort of 24 patients and 17 comparison subjects. Patients showed significant deficits in VOICEID and Distorted Tunes Task performance. Impaired VOICEID performance correlated significantly with lower fractional anisotropy values within primary and secondary auditory pathways, orbitofrontal cortex, corpus callosum, and peri-amygdala white matter. Impaired Distorted Tunes Task performance also correlated with lower fractional anisotropy in auditory and amygdalar pathways but not prefrontal cortex. Wisconsin Card Sorting Test performance in schizophrenia correlated primarily with prefrontal fractional anisotropy. In the follow-up study, significant deficits were observed as well in nonaffective prosodic performance, along with significant intercorrelations among sensory, affective prosodic, and nonaffective measures. Schizophrenia is associated with both structural and functional disturbances at the level of primary auditory cortex. Such deficits contribute significantly to patients' inability to decode both emotional and semantic aspects of speech, highlighting the importance of sensorial abnormalities in social communicatory dysfunction in schizophrenia.

Neural substrates of social facilitation effects on incentive-based performance

Science.gov (United States)

Chib, Vikram S; Adachi, Ryo; O’Doherty, John P

2018-01-01

Abstract Throughout our lives we must perform tasks while being observed by others. Previous studies have shown that the presence of an audience can cause increases in an individual’s performance as compared to when they are not being observed—a phenomenon called ‘social facilitation’. However, the neural mechanisms underlying this effect, in the context of skilled-task performance for monetary incentives, are not well understood. We used functional magnetic resonance imaging to monitor brain activity while healthy human participants performed a skilled-task during conditions in which they were paid based on their performance and observed and not observed by an audience. We found that during social facilitation, social signals represented in the dorsomedial prefrontal cortex (dmPFC) enhanced reward value computations in ventromedial prefrontal cortex (vmPFC). We also found that functional connectivity between dmPFC and ventral striatum was enhanced when participants exhibited social facilitation effects, indicative of a means by which social signals serve to modulate brain regions involved in regulating behavioral motivation. These findings illustrate how neural processing of social judgments gives rise to the enhanced motivational state that results in social facilitation of incentive-based performance. PMID:29648653

Explicit versus implicit neural processing of musical emotions

OpenAIRE

Bogert, Brigitte; Numminen-Kontti, Taru; Gold, Benjamin; Sams, Mikko; Numminen, Jussi; Burunat, Iballa; Lampinen, Jouko; Brattico, Elvira

2016-01-01

Music is often used to regulate emotions and mood. Typically, music conveys and induces emotions even when one does not attend to them. Studies on the neural substrates of musical emotions have, however, only examined brain activity when subjects have focused on the emotional content of the music. Here we address with functional magnetic resonance imaging (fMRI) the neural processing of happy, sad, and fearful music with a paradigm in which 56 subjects were instructed to either classify the e...

Neural substrates of cognitive control under the belief of getting neurofeedback training

Directory of Open Access Journals (Sweden)

Manuel eNinaus

2013-12-01

Full Text Available Learning to modulate one’s own brain activity is the fundament of neurofeedback (NF applications. Besides the neural networks directly involved in the generation and modulation of the neurophysiological parameter being specifically trained, more general determinants of NF efficacy such as self-referential processes and cognitive control have been frequently disregarded. Nonetheless, deeper insight into these cognitive mechanisms and their neuronal underpinnings sheds light on various open NF related questions concerning individual differences, brain-computer interface (BCI illiteracy as well as a more general model of NF learning. In this context, we investigated the neuronal substrate of these more general regulatory mechanisms that are engaged when participants believe that they are receiving NF. Twenty healthy participants (40-63 years, 10 female performed a sham NF paradigm during fMRI scanning. All participants were novices to NF-experiments and were instructed to voluntarily modulate their own brain activity based on a visual display of moving color bars. However, the bar depicted a recording and not the actual brain activity of participants. Reports collected at the end of the experiment indicate that participants were unaware of the sham feedback. In comparison to a passive watching condition, bilateral insula, anterior cingulate cortex and supplementary motor and dorsomedial and lateral prefrontal area were activated when participants actively tried to control the bar. In contrast, when merely watching moving bars, increased activation in the left angular gyrus was observed. These results show that the intention to control a moving bar is sufficient to engage a broad frontoparietal and cingulo-opercular network involved in cognitive control. The results of the present study indicate that tasks such as those generally employed in NF training recruit the neuronal correlates of cognitive control even when only sham NF is presented.

The neural substrate and functional integration of uncertainty in decision making: an information theory approach.

Directory of Open Access Journals (Sweden)

Joaquín Goñi

Full Text Available Decision making can be regarded as the outcome of cognitive processes leading to the selection of a course of action among several alternatives. Borrowing a central measurement from information theory, Shannon entropy, we quantified the uncertainties produced by decisions of participants within an economic decision task under different configurations of reward probability and time. These descriptors were used to obtain blood oxygen level-dependent (BOLD signal correlates of uncertainty and two clusters codifying the Shannon entropy of task configurations were identified: a large cluster including parts of the right middle cingulate cortex (MCC and left and right pre-supplementary motor areas (pre-SMA and a small cluster at the left anterior thalamus. Subsequent functional connectivity analyses using the psycho-physiological interactions model identified areas involved in the functional integration of uncertainty. Results indicate that clusters mostly located at frontal and temporal cortices experienced an increased connectivity with the right MCC and left and right pre-SMA as the uncertainty was higher. Furthermore, pre-SMA was also functionally connected to a rich set of areas, most of them associative areas located at occipital and parietal lobes. This study provides a map of the human brain segregation and integration (i.e., neural substrate and functional connectivity respectively of the uncertainty associated to an economic decision making paradigm.

Neural Correlates of Consumer Buying Motivations: A 7T functional Magnetic Resonance Imaging (fMRI Study

Directory of Open Access Journals (Sweden)

Adam M. Goodman

2017-09-01

Full Text Available Consumer buying motivations can be distinguished into three categories: functional, experiential, or symbolic motivations (Keller, 1993. Although prior neuroimaging studies have examined the neural substrates which enable these motivations, direct comparisons between these three types of consumer motivations have yet to be made. In the current study, we used 7 Tesla (7T functional magnetic resonance imaging (fMRI to assess the neural correlates of each motivation by instructing participants to view common consumer goods while emphasizing either functional, experiential, or symbolic values of these products. The results demonstrated mostly consistent activations between symbolic and experiential motivations. Although, these motivations differed in that symbolic motivation was associated with medial frontal gyrus (MFG activation, whereas experiential motivation was associated with posterior cingulate cortex (PCC activation. Functional motivation was associated with dorsolateral prefrontal cortex (DLPFC activation, as compared to other motivations. These findings provide a neural basis for how symbolic and experiential motivations may be similar, yet different in subtle ways. Furthermore, the dissociation of functional motivation within the DLPFC supports the notion that this motivation relies on executive function processes relatively more than hedonic motivation. These findings provide a better understanding of the underlying neural functioning which may contribute to poor self-control choices.

Cocaine action on peripheral, non-monoamine neural substrates as a trigger of electroencephalographic desynchronization and electromyographic activation following i.v. administration in freely moving rats.

Science.gov (United States)

Smirnov, M S; Kiyatkin, E A

2010-01-20

Many important physiological, behavioral and subjective effects of i.v. cocaine (COC) are exceptionally rapid and transient, suggesting a possible involvement of peripheral neural substrates in their triggering. In the present study, we used high-speed electroencephalographic (EEG) and electromyographic (EMG) recordings (4-s resolution) in freely moving rats to characterize the central electrophysiological effects of i.v. COC at low doses within a self-administration range (0.25-1.0 mg/kg). We found that COC induces rapid, strong, and prolonged desynchronization of cortical EEG (decrease in alpha and increase in beta and gamma activity) and activation of the neck EMG that begin within 2-6 s following the start of a 10-s injection; immediate components of both effects were dose-independent. The rapid effects of COC were mimicked by i.v. COC methiodide (COC-MET), a derivative that cannot cross the blood-brain barrier. At equimolar doses (0.33-1.33 mg/kg), COC-MET had equally fast and strong effects on EEG and EMG total powers, decreasing alpha and increasing beta and gamma activities. Rapid EEG desynchronization and EMG activation was also induced by i.v. procaine, a structurally similar, short-acting local anesthetic with virtually no effects on monoamine uptake; at equipotential doses (1.25-5.0 mg/kg), these effects were weaker and shorter in duration than those of COC. Surprisingly, i.v. saline injection delivered during slow-wave sleep (but not during quiet wakefulness) also induced a transient EEG desynchronization but without changes in EMG and motor activity; these effects were significantly weaker and much shorter than those induced by all tested drugs. These data suggest that in awake animals, i.v. COC induces rapid cortical activation and a subsequent motor response via its action on peripheral non-monoamine neural elements, involving neural transmission via visceral sensory pathways. By providing a rapid neural signal and triggering neural activation, such

Identification of Common Neural Circuit Disruptions in Cognitive Control Across Psychiatric Disorders.

Science.gov (United States)

McTeague, Lisa M; Huemer, Julia; Carreon, David M; Jiang, Ying; Eickhoff, Simon B; Etkin, Amit

2017-07-01

Cognitive deficits are a common feature of psychiatric disorders. The authors investigated the nature of disruptions in neural circuitry underlying cognitive control capacities across psychiatric disorders through a transdiagnostic neuroimaging meta-analysis. A PubMed search was conducted for whole-brain functional neuroimaging articles published through June 2015 that compared activation in patients with axis I disorders and matched healthy control participants during cognitive control tasks. Tasks that probed performance or conflict monitoring, response inhibition or selection, set shifting, verbal fluency, and recognition or working memory were included. Activation likelihood estimation meta-analyses were conducted on peak voxel coordinates. The 283 experiments submitted to meta-analysis included 5,728 control participants and 5,493 patients with various disorders (schizophrenia, bipolar or unipolar depression, anxiety disorders, and substance use disorders). Transdiagnostically abnormal activation was evident in the left prefrontal cortex as well as the anterior insula, the right ventrolateral prefrontal cortex, the right intraparietal sulcus, and the midcingulate/presupplementary motor area. Disruption was also observed in a more anterior cluster in the dorsal cingulate cortex, which overlapped with a network of structural perturbation that the authors previously reported in a transdiagnostic meta-analysis of gray matter volume. These findings demonstrate a common pattern of disruption across major psychiatric disorders that parallels the "multiple-demand network" observed in intact cognition. This network interfaces with the anterior-cingulo-insular or "salience network" demonstrated to be transdiagnostically vulnerable to gray matter reduction. Thus, networks intrinsic to adaptive, flexible cognition are vulnerable to broad-spectrum psychopathology. Dysfunction in these networks may reflect an intermediate transdiagnostic phenotype, which could be leveraged

A Common Neural Substrate for Language Production and Verbal Working Memory

Science.gov (United States)

Acheson, Daniel J.; Hamidi, Massihullah; Binder, Jeffrey R.; Postle, Bradley R.

2011-01-01

Verbal working memory (VWM), the ability to maintain and manipulate representations of speech sounds over short periods, is held by some influential models to be independent from the systems responsible for language production and comprehension [e.g., Baddeley, A. D. "Working memory, thought, and action." New York, NY: Oxford University Press,…

Common faults in turbines and applying neural networks in order to fault diagnostic by vibration analysis

International Nuclear Information System (INIS)

Masoudifar, M.; AghaAmini, M.

2001-01-01

Today the fault diagnostic of the rotating machinery based on the vibration analysis is an effective method in designing predictive maintenance programs. In this method, vibration level of the turbines is monitored and if it is higher than the allowable limit, vibrational data will be analyzed and the growing faults will be detected. But because of the high complexity of the system monitoring, the interpretation of the measured data is more difficult. Therefore, design of the fault diagnostic expert systems by using the expert's technical experiences and knowledge; seem to be the best solution. In this paper,at first several common faults in turbines are studied and the how applying the neural networks to interpret the vibrational data for fault diagnostic is explained

Using brain stimulation to disentangle neural correlates of conscious vision.

Science.gov (United States)

de Graaf, Tom A; Sack, Alexander T

2014-01-01

Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs.

A neural substrate for object permanence in monkey inferotemporal cortex

OpenAIRE

Puneeth, NC; Arun, SP

2016-01-01

We take it for granted that objects continue to exist after being occluded. This knowledge ? known as object permanence ? is present even in childhood, but its neural basis is not fully understood. Here, we show that monkey inferior temporal (IT) neurons carry potential signals of object permanence even in animals that received no explicit behavioral training. We compared two conditions with identical visual stimulation: the same object emerged from behind an occluder as expected following it...

Substrates of neuropsychological functioning in stimulant dependence: a review of functional neuroimaging research

NARCIS (Netherlands)

Crunelle, Cleo L.; Veltman, Dick J.; Booij, Jan; Emmerik-van Oortmerssen, Katelijne; den Brink, Wim

2012-01-01

Stimulant dependence is associated with neuropsychological impairments. Here, we summarize and integrate the existing neuroimaging literature on the neural substrates of neuropsychological (dys) function in stimulant dependence, including cocaine, (meth-) amphetamine, ecstasy and nicotine

Substrates of neuropsychological functioning in stimulant dependence: a review of functional neuroimaging research

NARCIS (Netherlands)

Crunelle, C.L.; Veltman, D.J.; Booij, J.; van Emmerik-van Oortmerssen, K.; van den Brink, W.

2012-01-01

Stimulant dependence is associated with neuropsychological impairments. Here, we summarize and integrate the existing neuroimaging literature on the neural substrates of neuropsychological (dys)function in stimulant dependence, including cocaine, (meth-)amphetamine, ecstasy and nicotine dependence,

Mechanically flexible optically transparent porous mono-crystalline silicon substrate

KAUST Repository

Rojas, Jhonathan Prieto; Syed, Ahad A.; Hussain, Muhammad Mustafa

2012-01-01

For the first time, we present a simple process to fabricate a thin (≥5μm), mechanically flexible, optically transparent, porous mono-crystalline silicon substrate. Relying only on reactive ion etching steps, we are able to controllably peel off a thin layer of the original substrate. This scheme is cost favorable as it uses a low-cost silicon <100> wafer and furthermore it has the potential for recycling the remaining part of the wafer that otherwise would be lost and wasted during conventional back-grinding process. Due to its porosity, it shows see-through transparency and potential for flexible membrane applications, neural probing and such. Our process can offer flexible, transparent silicon from post high-thermal budget processed device wafer to retain the high performance electronics on flexible substrates. © 2012 IEEE.

Six networks on a universal neuromorphic computing substrate

Directory of Open Access Journals (Sweden)

Thomas ePfeil

2013-02-01

Full Text Available In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

Six networks on a universal neuromorphic computing substrate.

Science.gov (United States)

Pfeil, Thomas; Grübl, Andreas; Jeltsch, Sebastian; Müller, Eric; Müller, Paul; Petrovici, Mihai A; Schmuker, Michael; Brüderle, Daniel; Schemmel, Johannes; Meier, Karlheinz

2013-01-01

In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

Science.gov (United States)

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

The neural substrates of semantic memory deficits in early Alzheimer's disease: Clues from semantic priming effects and FDG-PET

International Nuclear Information System (INIS)

Giffard, B.; Laisney, M.; Mezenge, F.; De la Sayette, V.; Eustache, F.; Desgranges, B.

2008-01-01

The neural substrates responsible for semantic dysfunction during the early stages of AD have yet to be clearly identified. After a brief overview of the literature on normal and pathological semantic memory, we describe a new approach, designed to provide fresh insights into semantic deficits in AD. We mapped the correlations between resting-state brain glucose utilisation measured by FDG-PET and semantic priming scores in a group of 17 AD patients. The priming task, which yields a particularly pure measurement of semantic memory, was composed of related pairs of words sharing an attribute relationship (e.g. tiger-stripe). The priming scores correlated positively with the metabolism of the superior temporal areas on both sides, especially the right side, and this correlation was shown to be specific to the semantic priming effect.This pattern of results is discussed in the light of recent theoretical models of semantic memory, and suggests that a dysfunction of the right superior temporal cortex may contribute to early semantic deficits, characterised by the loss of specific features of concepts in AD. (authors)

Photosensitive-polyimide based method for fabricating various neural electrode architectures

Directory of Open Access Journals (Sweden)

Yasuhiro X Kato

2012-06-01

Full Text Available An extensive photosensitive polyimide (PSPI-based method for designing and fabricating various neural electrode architectures was developed. The method aims to broaden the design flexibility and expand the fabrication capability for neural electrodes to improve the quality of recorded signals and integrate other functions. After characterizing PSPI’s properties for micromachining processes, we successfully designed and fabricated various neural electrodes even on a non-flat substrate using only one PSPI as an insulation material and without the time-consuming dry etching processes. The fabricated neural electrodes were an electrocorticogram electrode, a mesh intracortical electrode with a unique lattice-like mesh structure to fixate neural tissue, and a guide cannula electrode with recording microelectrodes placed on the curved surface of a guide cannula as a microdialysis probe. In vivo neural recordings using anesthetized rats demonstrated that these electrodes can be used to record neural activities repeatedly without any breakage and mechanical failures, which potentially promises stable recordings for long periods of time. These successes make us believe that this PSPI-based fabrication is a powerful method, permitting flexible design and easy optimization of electrode architectures for a variety of electrophysiological experimental research with improved neural recording performance.

A new neural observer for an anaerobic bioreactor.

Science.gov (United States)

Belmonte-Izquierdo, R; Carlos-Hernandez, S; Sanchez, E N

2010-02-01

In this paper, a recurrent high order neural observer (RHONO) for anaerobic processes is proposed. The main objective is to estimate variables of methanogenesis: biomass, substrate and inorganic carbon in a completely stirred tank reactor (CSTR). The recurrent high order neural network (RHONN) structure is based on the hyperbolic tangent as activation function. The learning algorithm is based on an extended Kalman filter (EKF). The applicability of the proposed scheme is illustrated via simulation. A validation using real data from a lab scale process is included. Thus, this observer can be successfully implemented for control purposes.

Neural substrates of view-invariant object recognition developed without experiencing rotations of the objects.

Science.gov (United States)

Okamura, Jun-Ya; Yamaguchi, Reona; Honda, Kazunari; Wang, Gang; Tanaka, Keiji

2014-11-05

One fails to recognize an unfamiliar object across changes in viewing angle when it must be discriminated from similar distractor objects. View-invariant recognition gradually develops as the viewer repeatedly sees the objects in rotation. It is assumed that different views of each object are associated with one another while their successive appearance is experienced in rotation. However, natural experience of objects also contains ample opportunities to discriminate among objects at each of the multiple viewing angles. Our previous behavioral experiments showed that after experiencing a new set of object stimuli during a task that required only discrimination at each of four viewing angles at 30° intervals, monkeys could recognize the objects across changes in viewing angle up to 60°. By recording activities of neurons from the inferotemporal cortex after various types of preparatory experience, we here found a possible neural substrate for the monkeys' performance. For object sets that the monkeys had experienced during the task that required only discrimination at each of four viewing angles, many inferotemporal neurons showed object selectivity covering multiple views. The degree of view generalization found for these object sets was similar to that found for stimulus sets with which the monkeys had been trained to conduct view-invariant recognition. These results suggest that the experience of discriminating new objects in each of several viewing angles develops the partially view-generalized object selectivity distributed over many neurons in the inferotemporal cortex, which in turn bases the monkeys' emergent capability to discriminate the objects across changes in viewing angle. Copyright © 2014 the authors 0270-6474/14/3415047-13$15.00/0.

Glucocorticoids in the prefrontal cortex enhance memory consolidation and impair working memory by a common neural mechanism

Science.gov (United States)

Barsegyan, Areg; Mackenzie, Scott M.; Kurose, Brian D.; McGaugh, James L.; Roozendaal, Benno

2010-01-01

It is well established that acute administration of adrenocortical hormones enhances the consolidation of memories of emotional experiences and, concurrently, impairs working memory. These different glucocorticoid effects on these two memory functions have generally been considered to be independently regulated processes. Here we report that a glucocorticoid receptor agonist administered into the medial prefrontal cortex (mPFC) of male Sprague-Dawley rats both enhances memory consolidation and impairs working memory. Both memory effects are mediated by activation of a membrane-bound steroid receptor and depend on noradrenergic activity within the mPFC to increase levels of cAMP-dependent protein kinase. These findings provide direct evidence that glucocorticoid effects on both memory consolidation and working memory share a common neural influence within the mPFC. PMID:20810923

Neural substrates of embodied natural beauty and social endowed beauty: An fMRI study.

Science.gov (United States)

Zhang, Wei; He, Xianyou; Lai, Siyan; Wan, Juan; Lai, Shuxian; Zhao, Xueru; Li, Darong

2017-08-02

What are the neural mechanisms underlying beauty based on objective parameters and beauty based on subjective social construction? This study scanned participants with fMRI while they performed aesthetic judgments on concrete pictographs and abstract oracle bone scripts. Behavioral results showed both pictographs and oracle bone scripts were judged to be more beautiful when they referred to beautiful objects and positive social meanings, respectively. Imaging results revealed regions associated with perceptual, cognitive, emotional and reward processing were commonly activated both in beautiful judgments of pictographs and oracle bone scripts. Moreover, stronger activations of orbitofrontal cortex (OFC) and motor-related areas were found in beautiful judgments of pictographs, whereas beautiful judgments of oracle bone scripts were associated with putamen activity, implying stronger aesthetic experience and embodied approaching for beauty were elicited by the pictographs. In contrast, only visual processing areas were activated in the judgments of ugly pictographs and negative oracle bone scripts. Results provide evidence that the sense of beauty is triggered by two processes: one based on the objective parameters of stimuli (embodied natural beauty) and the other based on the subjective social construction (social endowed beauty).

Substrate-induced instability in gas microstrip detectors

International Nuclear Information System (INIS)

Bateman, J.E.; Connolly, J.F.

1992-12-01

The results of a programme of research into substrate-induced gain instability in gas microstrip detectors are reported. Information has been collected on a wide range of substrates including many commonly available glasses and ceramics. A theoretical model of the gain instability is proposed. While we have not yet found an acceptable substrate for the construction of high flux detectors our experience points to electronically conductive glasses as the most promising source of a stable substrate. (Author)

Common Ion Effects In Zeoponic Substrates: Dissolution And Cation Exchange Variations Due to Additions of Calcite, Dolomite and Wollastonite

Science.gov (United States)

Beiersdorfer, R. E.; Ming, D. W.; Galindo, C., Jr.

2003-01-01

c1inoptilolite-rich tuff-hydroxyapatite mixture (zeoponic substrate) has the potential to serve as a synthetic soil-additive for plant growth. Essential plant macro-nutrients such as calcium, phosphorous, magnesium, ammonium and potassium are released into solution via dissolution of the hydroxyapatite and cation exchange on zeolite charged sites. Plant growth experiments resulting in low yield for wheat have been attributed to a Ca deficiency caused by a high degree of cation exchange by the zeolite. Batch-equilibration experiments were performed in order to determine if the Ca deficiency can be remedied by the addition of a second Ca-bearing, soluble, mineral such as calcite, dolomite or wollastonite. Variations in the amount of calcite, dolomite or wollastonite resulted in systematic changes in the concentrations of Ca and P. The addition of calcite, dolomite or wollastonite to the zeoponic substrate resulted in an exponential decrease in the phosphorous concentration in solution. The exponential rate of decay was greatest for calcite (5.60 wt. % -I), intermediate for wollastonite (2.85 wt.% -I) and least for dolomite (1.58 wt.% -I). Additions of the three minerals resulted in linear increases in the calcium concentration in solution. The rate of increase was greatest for calcite (3.64), intermediate for wollastonite (2.41) and least for dolomite (0.61). The observed changes in P and Ca concentration are consistent with the solubilities of calcite, dolomite and wollastonite and with changes expected from a common ion effect with Ca. Keywords: zeolite, zeoponics, common-ion effect, clinoptilolite, hydroxyapatite

Cellular therapy after spinal cord injury using neural progenitor cells

NARCIS (Netherlands)

Vroemen, Maurice

2006-01-01

In this thesis, the possibilities and limitations of cell-based therapies after spinal cord injury are explored. Particularly, the potential of adult derived neural progenitor cell (NPC) grafts to function as a permissive substrate for axonal regeneration was investigated. It was found that syngenic

Neural substrates and behavioral profiles of romantic jealousy and its temporal dynamics.

Science.gov (United States)

Sun, Yan; Yu, Hongbo; Chen, Jie; Liang, Jie; Lu, Lin; Zhou, Xiaolin; Shi, Jie

2016-06-07

Jealousy is not only a way of experiencing love but also a stabilizer of romantic relationships, although morbid romantic jealousy is maladaptive. Being engaged in a formal romantic relationship can tune one's romantic jealousy towards a specific target. Little is known about how the human brain processes romantic jealousy by now. Here, by combining scenario-based imagination and functional MRI, we investigated the behavioral and neural correlates of romantic jealousy and their development across stages (before vs. after being in a formal relationship). Romantic jealousy scenarios elicited activations primarily in the basal ganglia (BG) across stages, and were significantly higher after the relationship was established in both the behavioral rating and BG activation. The intensity of romantic jealousy was related to the intensity of romantic happiness, which mainly correlated with ventral medial prefrontal cortex activation. The increase in jealousy across stages was associated with the tendency for interpersonal aggression. These results bridge the gap between the theoretical conceptualization of romantic jealousy and its neural correlates and shed light on the dynamic changes in jealousy.

Neural substrates of the impaired effort expenditure decision making in schizophrenia.

Science.gov (United States)

Huang, Jia; Yang, Xin-Hua; Lan, Yong; Zhu, Cui-Ying; Liu, Xiao-Qun; Wang, Ye-Fei; Cheung, Eric F C; Xie, Guang-Rong; Chan, Raymond C K

2016-09-01

Unwillingness to expend more effort to pursue high value rewards has been associated with motivational anhedonia in schizophrenia (SCZ) and abnormal dopamine activity in the nucleus accumbens (NAcc). The authors hypothesized that dysfunction of the NAcc and the associated forebrain regions are involved in the impaired effort expenditure decision-making of SCZ. A 2 (reward magnitude: low vs. high) × 3 (probability: 20% vs. 50% vs. 80%) event-related fMRI design in the effort-expenditure for reward task (EEfRT) was used to examine the neural response of 23 SCZ patients and 23 demographically matched control participants when the participants made effort expenditure decisions to pursue uncertain rewards. SCZ patients were significantly less likely to expend high level of effort in the medium (50%) and high (80%) probability conditions than healthy controls. The neural response in the NAcc, the posterior cingulate gyrus and the left medial frontal gyrus in SCZ patients were weaker than healthy controls and did not linearly increase with an increase in reward magnitude and probability. Moreover, NAcc activity was positively correlated with the willingness to expend high-level effort and concrete consummatory pleasure experience. NAcc and posterior cingulate dysfunctions in SCZ patients may be involved in their impaired effort expenditure decision-making. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Chemo-mechanical control of neural stem cell differentiation

Science.gov (United States)

Geishecker, Emily R.

Cellular processes such as adhesion, proliferation, and differentiation are controlled in part by cell interactions with the microenvironment. Cells can sense and respond to a variety of stimuli, including soluble and insoluble factors (such as proteins and small molecules) and externally applied mechanical stresses. Mechanical properties of the environment, such as substrate stiffness, have also been suggested to play an important role in cell processes. The roles of both biochemical and mechanical signaling in fate modification of stem cells have been explored independently. However, very few studies have been performed to study well-controlled chemo-mechanotransduction. The objective of this work is to design, synthesize, and characterize a chemo-mechanical substrate to encourage neuronal differentiation of C17.2 neural stem cells. In Chapter 2, Polyacrylamide (PA) gels of varying stiffnesses are functionalized with differing amounts of whole collagen to investigate the role of protein concentration in combination with substrate stiffness. As expected, neurons on the softest substrate were more in number and neuronal morphology than those on stiffer substrates. Neurons appeared locally aligned with an expansive network of neurites. Additional experiments would allow for statistical analysis to determine if and how collagen density impacts C17.2 differentiation in combination with substrate stiffness. Due to difficulties associated with whole protein approaches, a similar platform was developed using mixed adhesive peptides, derived from fibronectin and laminin, and is presented in Chapter 3. The matrix elasticity and peptide concentration can be individually modulated to systematically probe the effects of chemo-mechanical signaling on differentiation of C17.2 cells. Polyacrylamide gel stiffness was confirmed using rheological techniques and found to support values published by Yeung et al. [1]. Cellular growth and differentiation were assessed by cell counts

Effects of topography on the functional development of human neural progenitor cells.

Science.gov (United States)

Wu, Ze-Zhi; Kisaalita, William S; Wang, Lina; Zachman, Angela L; Zhao, Yiping; Hasneen, Kowser; Machacek, Dave; Stice, Steven L

2010-07-01

We have fabricated a topographical substrate with a packed polystyrene bead array for the development of cell-based assay systems targeting voltage-gated calcium channels (VGCCs). Human neural progenitor cells (H945RB.3) cultured on both flat and topographical substrates were analyzed in terms of morphological spreading, neuronal commitment, resting membrane potential (V(m)) establishment and VGCC function development. We found, by SEM imaging, that arrayed substrates, formed with both sub-micrometer (of 0.51 microm in mean diameter) and micrometer (of 1.98 microm in mean diameter) beads, were capable of promoting the spreading of the progenitor cells as compared with the flat polystyrene surfaces. With the micrometer beads, it was found that arrayed substrates facilitated the neural progenitor cells' maintenance of less negative V(m) values upon differentiation with bFGF starvation, which favored predominant neuronal commitment. Almost all the progenitor cells were responsive to 50 mM K(+) depolarization with an increase in [Ca(2+)](i) either before or upon differentiation, suggesting the expression of functional VGCCs. Compared to the flat polystyrene surfaces, microbead arrayed substrates facilitated the development of higher VGCC responsiveness by the progenitor cells upon differentiation. The enhancement of both VGCC responsiveness and cell spreading by arrays of micrometer beads was most significant on day 14 into differentiation, which was the latest time point of measurement in this study. This study thus rationalized the possibility for future substrate topography engineering to manipulate ion channel function and to meet the challenge of low VGCC responsiveness found in early drug discovery.

Neural mechanisms of social dominance

Science.gov (United States)

Watanabe, Noriya; Yamamoto, Miyuki

2015-01-01

In a group setting, individuals' perceptions of their own level of dominance or of the dominance level of others, and the ability to adequately control their behavior based on these perceptions are crucial for living within a social environment. Recent advances in neural imaging and molecular technology have enabled researchers to investigate the neural substrates that support the perception of social dominance and the formation of a social hierarchy in humans. At the systems' level, recent studies showed that dominance perception is represented in broad brain regions which include the amygdala, hippocampus, striatum, and various cortical networks such as the prefrontal, and parietal cortices. Additionally, neurotransmitter systems such as the dopaminergic and serotonergic systems, modulate and are modulated by the formation of the social hierarchy in a group. While these monoamine systems have a wide distribution and multiple functions, it was recently found that the Neuropeptide B/W contributes to the perception of dominance and is present in neurons that have a limited projection primarily to the amygdala. The present review discusses the specific roles of these neural regions and neurotransmitter systems in the perception of dominance and in hierarchy formation. PMID:26136644

Neural mechanisms of social dominance

Directory of Open Access Journals (Sweden)

Noriya eWatanabe

2015-06-01

Full Text Available In a group setting, individuals’ perceptions of their own level of dominance or of the dominance level of others, and the ability to adequately control their behavior based on these perceptions are crucial for living within a social environment. Recent advances in neural imaging and molecular technology have enabled researchers to investigate the neural substrates that support the perception of social dominance and the formation of a social hierarchy in humans. At the systems’ level, recent studies showed that dominance perception is represented in broad brain regions which include the amygdala, hippocampus, striatum, and various cortical networks such as the prefrontal, and parietal cortices. Additionally, neurotransmitter systems such as the dopaminergic and serotonergic systems, modulate and are modulated by the formation of the social hierarchy in a group. While these monoamine systems have a wide distribution and multiple functions, it was recently found that the Neuropeptide B/W contributes to the perception of dominance and is present in neurons that have a limited projection primarily to the amygdala. The present review discusses the specific roles of these neural regions and neurotransmitter systems in the perception of dominance and in hierarchy formation.

Application Of Artificial Neural Networks In Modeling Of Manufactured Front Metallization Contact Resistance For Silicon Solar Cells

Directory of Open Access Journals (Sweden)

Musztyfaga-Staszuk M.

2015-09-01

Full Text Available This paper presents the application of artificial neural networks for prediction contact resistance of front metallization for silicon solar cells. The influence of the obtained front electrode features on electrical properties of solar cells was estimated. The front electrode of photovoltaic cells was deposited using screen printing (SP method and next to manufactured by two methods: convectional (1. co-fired in an infrared belt furnace and unconventional (2. Selective Laser Sintering. Resistance of front electrodes solar cells was investigated using Transmission Line Model (TLM. Artificial neural networks were obtained with the use of Statistica Neural Network by Statsoft. Created artificial neural networks makes possible the easy modelling of contact resistance of manufactured front metallization and allows the better selection of production parameters. The following technological recommendations for the screen printing connected with co-firing and selective laser sintering technology such as optimal paste composition, morphology of the silicon substrate, co-firing temperature and the power and scanning speed of the laser beam to manufacture the front electrode of silicon solar cells were experimentally selected in order to obtain uniformly melted structure well adhered to substrate, of a small front electrode substrate joint resistance value. The prediction possibility of contact resistance of manufactured front metallization is valuable for manufacturers and constructors. It allows preserving the customers’ quality requirements and bringing also measurable financial advantages.

Age-related neural correlates of cognitive task performance under increased postural load

NARCIS (Netherlands)

Van Impe, A; Bruijn, S M; Coxon, J P; Wenderoth, N; Sunaert, S; Duysens, J; Swinnen, S P

2013-01-01

Behavioral studies suggest that postural control requires increased cognitive control and visuospatial processing with aging. Consequently, performance can decline when concurrently performing a postural and a demanding cognitive task. We aimed to identify the neural substrate underlying this

Neural Representations of Physics Concepts.

Science.gov (United States)

Mason, Robert A; Just, Marcel Adam

2016-06-01

We used functional MRI (fMRI) to assess neural representations of physics concepts (momentum, energy, etc.) in juniors, seniors, and graduate students majoring in physics or engineering. Our goal was to identify the underlying neural dimensions of these representations. Using factor analysis to reduce the number of dimensions of activation, we obtained four physics-related factors that were mapped to sets of voxels. The four factors were interpretable as causal motion visualization, periodicity, algebraic form, and energy flow. The individual concepts were identifiable from their fMRI signatures with a mean rank accuracy of .75 using a machine-learning (multivoxel) classifier. Furthermore, there was commonality in participants' neural representation of physics; a classifier trained on data from all but one participant identified the concepts in the left-out participant (mean accuracy = .71 across all nine participant samples). The findings indicate that abstract scientific concepts acquired in an educational setting evoke activation patterns that are identifiable and common, indicating that science education builds abstract knowledge using inherent, repurposed brain systems. © The Author(s) 2016.

Neural substrates of negativity bias in women with and without major depression.

Science.gov (United States)

Gollan, Jackie K; Connolly, Megan; Buchanan, Angel; Hoxha, Denada; Rosebrock, Laina; Cacioppo, John; Csernansky, John; Wang, Xue

2015-07-01

The functional localization of negativity bias, an influential index of emotion information processing, has yet to be identified. Depressed (n=47) and healthy participants (n=58) completed a clinical interview for DSM-IV Axis I disorders, symptom checklists, a behavioral task to measure negativity bias, and then viewed positive and negative images of social and nonsocial scenes during an event-related fMRI task. Two subsamples of participants with high (i.e., 75%; n=26) and low (i.e., 25%; n=26) negativity bias scores were as included in subsequent analyses to examine neural differences. Depressed participants with a higher, relative to lower, negative bias showed significantly greater neural activation in the left inferior frontal gyrus. High negativity bias evokes a distinctive pattern of brain activation in the frontal cortex of depressed participants. Increased activation occurred in the left inferior frontal gyrus, related to Brodmann area 44, which is associated with language and semantic processing, response inhibition, and cognitive reappraisal. This finding may reflect an abnormality in integrative emotional processing rather than processing of individual emotional dimensions in depressed participants with negativity bias. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

The neural substrates of semantic memory deficits in early Alzheimer's disease: Clues from semantic priming effects and FDG-PET

Energy Technology Data Exchange (ETDEWEB)

Giffard, B.; Laisney, M.; Mezenge, F.; De la Sayette, V.; Eustache, F.; Desgranges, B. [Univ Caen Basse Normandie, INSERM, U923, Unite Rech, EPHE, Lab Neuropsychol, CHU Cote Nacre, GIP Cyceron, F-14033 Caen (France)

2008-07-01

The neural substrates responsible for semantic dysfunction during the early stages of AD have yet to be clearly identified. After a brief overview of the literature on normal and pathological semantic memory, we describe a new approach, designed to provide fresh insights into semantic deficits in AD. We mapped the correlations between resting-state brain glucose utilisation measured by FDG-PET and semantic priming scores in a group of 17 AD patients. The priming task, which yields a particularly pure measurement of semantic memory, was composed of related pairs of words sharing an attribute relationship (e.g. tiger-stripe). The priming scores correlated positively with the metabolism of the superior temporal areas on both sides, especially the right side, and this correlation was shown to be specific to the semantic priming effect.This pattern of results is discussed in the light of recent theoretical models of semantic memory, and suggests that a dysfunction of the right superior temporal cortex may contribute to early semantic deficits, characterised by the loss of specific features of concepts in AD. (authors)

The effect of micro-ECoG substrate footprint on the meningeal tissue response

Science.gov (United States)

Schendel, Amelia A.; Nonte, Michael W.; Vokoun, Corinne; Richner, Thomas J.; Brodnick, Sarah K.; Atry, Farid; Frye, Seth; Bostrom, Paige; Pashaie, Ramin; Thongpang, Sanitta; Eliceiri, Kevin W.; Williams, Justin C.

2014-08-01

Objective. There is great interest in designing implantable neural electrode arrays that maximize function while minimizing tissue effects and damage. Although it has been shown that substrate geometry plays a key role in the tissue response to intracortically implanted, penetrating neural interfaces, there has been minimal investigation into the effect of substrate footprint on the tissue response to surface electrode arrays. This study investigates the effect of micro-electrocorticography (micro-ECoG) device geometry on the longitudinal tissue response. Approach. The meningeal tissue response to two micro-ECoG devices with differing geometries was evaluated. The first device had each electrode site and trace individually insulated, with open regions in between, while the second device had a solid substrate, in which all 16 electrode sites were embedded in a continuous insulating sheet. These devices were implanted bilaterally in rats, beneath cranial windows, through which the meningeal tissue response was monitored for one month after implantation. Electrode site impedance spectra were also monitored during the implantation period. Main results. It was observed that collagenous scar tissue formed around both types of devices. However, the distribution of the tissue growth was different between the two array designs. The mesh devices experienced thick tissue growth between the device and the cranial window, and minimal tissue growth between the device and the brain, while the solid device showed the opposite effect, with thick tissue forming between the brain and the electrode sites. Significance. These data suggest that an open architecture device would be more ideal for neural recording applications, in which a low impedance path from the brain to the electrode sites is critical for maximum recording quality.

Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

Science.gov (United States)

Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

2017-10-01

This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

Simple neural substrate predicts complex rhythmic structure in duetting birds

Science.gov (United States)

Amador, Ana; Trevisan, M. A.; Mindlin, G. B.

2005-09-01

Horneros (Furnarius Rufus) are South American birds well known for their oven-looking nests and their ability to sing in couples. Previous work has analyzed the rhythmic organization of the duets, unveiling a mathematical structure behind the songs. In this work we analyze in detail an extended database of duets. The rhythms of the songs are compatible with the dynamics presented by a wide class of dynamical systems: forced excitable systems. Compatible with this nonlinear rule, we build a biologically inspired model for how the neural and the anatomical elements may interact to produce the observed rhythmic patterns. This model allows us to synthesize songs presenting the acoustic and rhythmic features observed in real songs. We also make testable predictions in order to support our hypothesis.

Neural Specialization for Speech in the First Months of Life

Science.gov (United States)

Shultz, Sarah; Vouloumanos, Athena; Bennett, Randi H.; Pelphrey, Kevin

2014-01-01

How does the brain's response to speech change over the first months of life? Although behavioral findings indicate that neonates' listening biases are sharpened over the first months of life, with a species-specific preference for speech emerging by 3 months, the neural substrates underlying this developmental change are unknown. We…

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.

Outcome dependency alters the neural substrates of impression formation

Science.gov (United States)

Ames, Daniel L.; Fiske, Susan T.

2015-01-01

How do people maintain consistent impressions of other people when other people are often inconsistent? The present research addresses this question by combining recent neuroscientific insights with ecologically meaningful behavioral methods. Participants formed impressions of real people whom they met in a personally involving situation. fMRI and supporting behavioral data revealed that outcome dependency (i.e., depending on another person for a desired outcome) alters previously identified neural dynamics of impression formation. Consistent with past research, a functional localizer identified a region of dorsomedial PFC previously linked to social impression formation. In the main task, this ROI revealed the predicted patterns of activity across outcome dependency conditions: greater BOLD response when information confirmed (vs. violated) social expectations if participants were outcome-independent and the reverse pattern if participants were outcome-dependent. We suggest that, although social perceivers often discount expectancy-disconfirming information as noise, being dependent on another person for a desired outcome focuses impression-formation processing on the most diagnostic information, rather than on the most tractable information. PMID:23850465

Hybrid neural network model for simulating sorbitol synthesis by glucose-fructose oxidoreductase in Zymomonas mobilis CP4

Directory of Open Access Journals (Sweden)

Bravo S.

2004-01-01

Full Text Available A hybrid neural network model for simulating the process of enzymatic reduction of fructose to sorbitol process catalyzed by glucose-fructose oxidoreductase in Zymomonas mobilis CP4 is presented. Data used to derive and validate the model was obtained from experiments carried out under different conditions of pH, temperature and concentrations of both substrates (glucose and fructose involved in the reaction. Sonicated and lyophilized cells were used as source of the enzyme. The optimal pH for sorbitol synthesis at 30º C is 6.5. For a value of pH of 6, the optimal temperature is 35º C. The neural network in the model computes the value of the kinetic relationship. The hybrid neural network model is able to simulate changes in the substrates and product concentrations during sorbitol synthesis under pH and temperature conditions ranging between 5 and 7.5 and 25 and 40º C, respectively. Under these conditions the rate of sorbitol synthesis shows important differences. Values computed using the hybrid neural network model have an average error of 1.7·10-3 mole.

Artificial neural networks for plasma spectroscopy analysis

International Nuclear Information System (INIS)

Morgan, W.L.; Larsen, J.T.; Goldstein, W.H.

1992-01-01

Artificial neural networks have been applied to a variety of signal processing and image recognition problems. Of the several common neural models the feed-forward, back-propagation network is well suited for the analysis of scientific laboratory data, which can be viewed as a pattern recognition problem. The authors present a discussion of the basic neural network concepts and illustrate its potential for analysis of experiments by applying it to the spectra of laser produced plasmas in order to obtain estimates of electron temperatures and densities. Although these are high temperature and density plasmas, the neural network technique may be of interest in the analysis of the low temperature and density plasmas characteristic of experiments and devices in gaseous electronics

The Neural Foundations of Reaction and Action in Aversive Motivation.

Science.gov (United States)

Campese, Vincent D; Sears, Robert M; Moscarello, Justin M; Diaz-Mataix, Lorenzo; Cain, Christopher K; LeDoux, Joseph E

2016-01-01

Much of the early research in aversive learning concerned motivation and reinforcement in avoidance conditioning and related paradigms. When the field transitioned toward the focus on Pavlovian threat conditioning in isolation, this paved the way for the clear understanding of the psychological principles and neural and molecular mechanisms responsible for this type of learning and memory that has unfolded over recent decades. Currently, avoidance conditioning is being revisited, and with what has been learned about associative aversive learning, rapid progress is being made. We review, below, the literature on the neural substrates critical for learning in instrumental active avoidance tasks and conditioned aversive motivation.

Brain substrates of implicit and explicit memory: the importance of concurrently acquired neural signals of both memory types.

Science.gov (United States)

Voss, Joel L; Paller, Ken A

2008-11-01

A comprehensive understanding of human memory requires cognitive and neural descriptions of memory processes along with a conception of how memory processing drives behavioral responses and subjective experiences. One serious challenge to this endeavor is that an individual memory process is typically operative within a mix of other contemporaneous memory processes. This challenge is particularly disquieting in the context of implicit memory, which, unlike explicit memory, transpires without the subject necessarily being aware of memory retrieval. Neural correlates of implicit memory and neural correlates of explicit memory are often investigated in different experiments using very different memory tests and procedures. This strategy poses difficulties for elucidating the interactions between the two types of memory process that may result in explicit remembering, and for determining the extent to which certain neural processing events uniquely contribute to only one type of memory. We review recent studies that have succeeded in separately assessing neural correlates of both implicit memory and explicit memory within the same paradigm using event-related brain potentials (ERPs) and functional magnetic resonance imaging (fMRI), with an emphasis on studies from our laboratory. The strategies we describe provide a methodological framework for achieving valid assessments of memory processing, and the findings support an emerging conceptualization of the distinct neurocognitive events responsible for implicit and explicit memory.

Short-term synaptic plasticity and heterogeneity in neural systems

Science.gov (United States)

Mejias, J. F.; Kappen, H. J.; Longtin, A.; Torres, J. J.

2013-01-01

We review some recent results on neural dynamics and information processing which arise when considering several biophysical factors of interest, in particular, short-term synaptic plasticity and neural heterogeneity. The inclusion of short-term synaptic plasticity leads to enhanced long-term memory capacities, a higher robustness of memory to noise, and irregularity in the duration of the so-called up cortical states. On the other hand, considering some level of neural heterogeneity in neuron models allows neural systems to optimize information transmission in rate coding and temporal coding, two strategies commonly used by neurons to codify information in many brain areas. In all these studies, analytical approximations can be made to explain the underlying dynamics of these neural systems.

Pre-evaluated safe human iPSC-derived neural stem cells promote functional recovery after spinal cord injury in common marmoset without tumorigenicity.

Directory of Open Access Journals (Sweden)

Yoshiomi Kobayashi

Full Text Available Murine and human iPSC-NS/PCs (induced pluripotent stem cell-derived neural stem/progenitor cells promote functional recovery following transplantation into the injured spinal cord in rodents. However, for clinical applicability, it is critical to obtain proof of the concept regarding the efficacy of grafted human iPSC-NS/PCs (hiPSC-NS/PCs for the repair of spinal cord injury (SCI in a non-human primate model. This study used a pre-evaluated "safe" hiPSC-NS/PC clone and an adult common marmoset (Callithrix jacchus model of contusive SCI. SCI was induced at the fifth cervical level (C5, followed by transplantation of hiPSC-NS/PCs at 9 days after injury. Behavioral analyses were performed from the time of the initial injury until 12 weeks after SCI. Grafted hiPSC-NS/PCs survived and differentiated into all three neural lineages. Furthermore, transplantation of hiPSC-NS/PCs enhanced axonal sparing/regrowth and angiogenesis, and prevented the demyelination after SCI compared with that in vehicle control animals. Notably, no tumor formation occurred for at least 12 weeks after transplantation. Quantitative RT-PCR showed that mRNA expression levels of human neurotrophic factors were significantly higher in cultured hiPSC-NS/PCs than in human dermal fibroblasts (hDFs. Finally, behavioral tests showed that hiPSC-NS/PCs promoted functional recovery after SCI in the common marmoset. Taken together, these results indicate that pre-evaluated safe hiPSC-NS/PCs are a potential source of cells for the treatment of SCI in the clinic.

Lithium - an update on the mechanisms of action. Part two: neural ...

African Journals Online (AJOL)

... has a complicated multitude of diverse effects in the human nervous system. This new data is helping us understand the neurobiology of bipolar disorder. The focus of this review will be to distil this new knowledge.This, the second of a two part review will focus principally on neural effects and neuroanatomical substrates.

Differentiation between non-neural and neural contributors to ankle joint stiffness in cerebral palsy.

Science.gov (United States)

de Gooijer-van de Groep, Karin L; de Vlugt, Erwin; de Groot, Jurriaan H; van der Heijden-Maessen, Hélène C M; Wielheesen, Dennis H M; van Wijlen-Hempel, Rietje M S; Arendzen, J Hans; Meskers, Carel G M

2013-07-23

Spastic paresis in cerebral palsy (CP) is characterized by increased joint stiffness that may be of neural origin, i.e. improper muscle activation caused by e.g. hyperreflexia or non-neural origin, i.e. altered tissue viscoelastic properties (clinically: "spasticity" vs. "contracture"). Differentiation between these components is hard to achieve by common manual tests. We applied an assessment instrument to obtain quantitative measures of neural and non-neural contributions to ankle joint stiffness in CP. Twenty-three adolescents with CP and eleven healthy subjects were seated with their foot fixated to an electrically powered single axis footplate. Passive ramp-and-hold rotations were applied over full ankle range of motion (RoM) at low and high velocities. Subject specific tissue stiffness, viscosity and reflexive torque were estimated from ankle angle, torque and triceps surae EMG activity using a neuromuscular model. In CP, triceps surae reflexive torque was on average 5.7 times larger (p = .002) and tissue stiffness 2.1 times larger (p = .018) compared to controls. High tissue stiffness was associated with reduced RoM (p therapy.

The neural mechanisms of semantic and response conflicts: an fMRI study of practice-related effects in the Stroop task.

Science.gov (United States)

Chen, Zhencai; Lei, Xu; Ding, Cody; Li, Hong; Chen, Antao

2013-02-01

Previous studies have demonstrated that there are separate neural mechanisms underlying semantic and response conflicts in the Stroop task. However, the practice effects of these conflicts need to be elucidated and the possible involvements of common neural mechanisms are yet to be established. We employed functional magnetic resonance imaging (fMRI) in a 4-2 mapping practice-related Stroop task to determine the neural substrates under these conflicts. Results showed that different patterns of brain activations are associated with practice in the attentional networks (e.g., dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and posterior parietal cortex (PPC)) for both conflicts, response control regions (e.g., inferior frontal junction (IFJ), inferior frontal gyrus (IFG)/insula, and pre-supplementary motor areas (pre-SMA)) for semantic conflict, and posterior cortex for response conflict. We also found areas of common activation in the left hemisphere within the attentional networks, for the early practice stage in semantic conflict and the late stage in "pure" response conflict using conjunction analysis. The different practice effects indicate that there are distinct mechanisms underlying these two conflict types: semantic conflict practice effects are attributable to the automation of stimulus processing, conflict and response control; response conflict practice effects are attributable to the proportional increase of conflict-related cognitive resources. In addition, the areas of common activation suggest that the semantic conflict effect may contain a partial response conflict effect, particularly at the beginning of the task. These findings indicate that there are two kinds of response conflicts contained in the key-pressing Stroop task: the vocal-level (mainly in the early stage) and key-pressing (mainly in the late stage) response conflicts; thus, the use of the subtraction method for the exploration of semantic and response conflicts

Integration of active devices on smart polymers for neural interfaces

Science.gov (United States)

Avendano-Bolivar, Adrian Emmanuel

The increasing ability to ever more precisely identify and measure neural interactions and other phenomena in the central and peripheral nervous systems is revolutionizing our understanding of the human body and brain. To facilitate further understanding, more sophisticated neural devices, perhaps using microelectronics processing, must be fabricated. Materials often used in these neural interfaces, while compatible with these fabrication processes, are not optimized for long-term use in the body and are often orders of magnitude stiffer than the tissue with which they interact. Using the smart polymer substrates described in this work, suitability for processing as well as chronic implantation is demonstrated. We explore how to integrate reliable circuitry onto these flexible, biocompatible substrates that can withstand the aggressive environment of the body. To increase the capabilities of these devices beyond individual channel sensing and stimulation, active electronics must also be included onto our systems. In order to add this functionality to these substrates and explore the limits of these devices, we developed a process to fabricate single organic thin film transistors with mobilities up to 0.4 cm2/Vs and threshold voltages close to 0V. A process for fabricating organic light emitting diodes on flexible substrates is also addressed. We have set a foundation and demonstrated initial feasibility for integrating multiple transistors onto thin-film flexible devices to create new applications, such as matrix addressable functionalized electrodes and organic light emitting diodes. A brief description on how to integrate waveguides for their use in optogenetics is addressed. We have built understanding about device constraints on mechanical, electrical and in vivo reliability and how various conditions affect the electronics' lifetime. We use a bi-layer gate dielectric using an inorganic material such as HfO 2 combined with organic Parylene-c. A study of

The SEEKING mind: primal neuro-affective substrates for appetitive incentive states and their pathological dynamics in addictions and depression.

Science.gov (United States)

Alcaro, Antonio; Panksepp, Jaak

2011-10-01

Appetitive motivation and incentive states are essential functions sustained by a common emotional brain process, the SEEKING disposition, which drives explorative and approach behaviors, sustains goal-directed activity, promotes anticipatory cognitions, and evokes feelings of positive excitement which control reward-learning. All such functions are orchestrated by the same "archetypical" neural processes, activated in ancient subcortical areas and transported to the forebrain by the mesolimbic dopamine (ML-DA) system. In mammals, the neurophysiology of the SEEKING urge is expressed by DA-promoted high-frequency oscillations, in the form of transient and synchronized gamma waves (>30Hz) emerging in limbic forebrain and diffusing throughout basal ganglia-thalamocortical (BG-T-C) circuits. These patterns may be considered basic "SEEKING neurodynamic impulses" which represent the primary-process exploratory disposition getting integrated with information relative to the external and the internal environment. Abnormal manifestation of SEEKING and its neural substrates are evident in clinical depression and addiction. Specifically, depression is characterized by reduced recruitment of SEEKING, while addictions reflect re-organizations of the SEEKING disposition around ultra-specific appetitive memories and compulsive activities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Hydrological performance of dual-substrate-layer green roofs using porous inert substrates with high sorption capacities.

Science.gov (United States)

Wang, Xiaoou; Tian, Yimei; Zhao, Xinhua; Peng, Chenrui

2017-06-01

Given that the common medium in existing green roofs is a single layer composed of organic and inorganic substrates, seven pilot-scale dual-substrate-layer extensive green roofs (G1-G7), which include nutrition and adsorption substrate layers, were constructed in this study. The effectiveness of porous inert substrates (activated charcoal, zeolite, pumice, lava, vermiculite and expanded perlite) used as the adsorption substrate for stormwater retention was investigated. A single-substrate-layer green roof (G8) was built for comparison with G1-G7. Despite the larger total rainfall depth (mm) of six types of simulated rains (43.2, 54.6, 76.2, 87.0, 85.2 and 86.4, respectively), the total percent retention of G1-G7 varied between 14% and 82% with an average of 43%, exhibiting better runoff-retaining capacity than G8 based on the maximum potential rainfall storage depth per unit height of adsorption substrate. Regression analysis showed that there was a logarithmic relationship between cumulative rainfall depth with non-zero runoff and stormwater retention for G1-G4 and a linear relationship for G5-G8. To enhance the water retention capacity and extend the service life of dual-substrate-layer extensive green roofs, the mixture of activated charcoal and/or pumice with expanded perlite and/or vermiculite is more suitable as the adsorption substrate than the mixture containing lava and/or zeolite.

A neural substrate for object permanence in monkey inferotemporal cortex.

Science.gov (United States)

Puneeth, N C; Arun, S P

2016-08-03

We take it for granted that objects continue to exist after being occluded. This knowledge - known as object permanence - is present even in childhood, but its neural basis is not fully understood. Here, we show that monkey inferior temporal (IT) neurons carry potential signals of object permanence even in animals that received no explicit behavioral training. We compared two conditions with identical visual stimulation: the same object emerged from behind an occluder as expected following its occlusion, or unexpectedly after occlusion of a different object. Some neurons produced a larger (surprise) signal when the object emerged unexpectedly, whereas other neurons produced a larger (match) signal when the object reappeared as expected. Neurons carrying match signals also reinstated selective delay period activity just before the object emerged. Thus, signals related to object permanence are present in IT neurons and may arise through an interplay of memory and match computations.

NMDA Receptor Signaling Is Important for Neural Tube Formation and for Preventing Antiepileptic Drug-Induced Neural Tube Defects.

Science.gov (United States)

Sequerra, Eduardo B; Goyal, Raman; Castro, Patricio A; Levin, Jacqueline B; Borodinsky, Laura N

2018-05-16

Failure of neural tube closure leads to neural tube defects (NTDs), which can have serious neurological consequences or be lethal. Use of antiepileptic drugs (AEDs) during pregnancy increases the incidence of NTDs in offspring by unknown mechanisms. Here we show that during Xenopus laevis neural tube formation, neural plate cells exhibit spontaneous calcium dynamics that are partially mediated by glutamate signaling. We demonstrate that NMDA receptors are important for the formation of the neural tube and that the loss of their function induces an increase in neural plate cell proliferation and impairs neural cell migration, which result in NTDs. We present evidence that the AED valproic acid perturbs glutamate signaling, leading to NTDs that are rescued with varied efficacy by preventing DNA synthesis, activating NMDA receptors, or recruiting the NMDA receptor target ERK1/2. These findings may prompt mechanistic identification of AEDs that do not interfere with neural tube formation. SIGNIFICANCE STATEMENT Neural tube defects are one of the most common birth defects. Clinical investigations have determined that the use of antiepileptic drugs during pregnancy increases the incidence of these defects in the offspring by unknown mechanisms. This study discovers that glutamate signaling regulates neural plate cell proliferation and oriented migration and is necessary for neural tube formation. We demonstrate that the widely used antiepileptic drug valproic acid interferes with glutamate signaling and consequently induces neural tube defects, challenging the current hypotheses arguing that they are side effects of this antiepileptic drug that cause the increased incidence of these defects. Understanding the mechanisms of neurotransmitter signaling during neural tube formation may contribute to the identification and development of antiepileptic drugs that are safer during pregnancy. Copyright © 2018 the authors 0270-6474/18/384762-12$15.00/0.

Neural computation and the computational theory of cognition.

Science.gov (United States)

Piccinini, Gualtiero; Bahar, Sonya

2013-04-01

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism-neural processes are computations in the generic sense. After that, we reject on empirical grounds the common assimilation of neural computation to either analog or digital computation, concluding that neural computation is sui generis. Analog computation requires continuous signals; digital computation requires strings of digits. But current neuroscientific evidence indicates that typical neural signals, such as spike trains, are graded like continuous signals but are constituted by discrete functional elements (spikes); thus, typical neural signals are neither continuous signals nor strings of digits. It follows that neural computation is sui generis. Finally, we highlight three important consequences of a proper understanding of neural computation for the theory of cognition. First, understanding neural computation requires a specially designed mathematical theory (or theories) rather than the mathematical theories of analog or digital computation. Second, several popular views about neural computation turn out to be incorrect. Third, computational theories of cognition that rely on non-neural notions of computation ought to be replaced or reinterpreted in terms of neural computation. Copyright © 2012 Cognitive Science Society, Inc.

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

Surface-modified microelectrode array with flake nanostructure for neural recording and stimulation

Energy Technology Data Exchange (ETDEWEB)

Kim, Ju-Hyun; Choi, Yang-Kyu [Nano-Oriented Bio-Electronics Lab, Department of Electrical Engineering, College of Information Science and Technology, KAIST, Daejeon 305-701 (Korea, Republic of); Kang, Gyumin; Nam, Yoonkey, E-mail: ynam@kaist.ac.kr, E-mail: ykchoi@ee.kaist.ac.kr [Department of Bio and Brain Engineering, KAIST, KAIST Institute for Nano-Century, Daejeon 305-701 (Korea, Republic of)

2010-02-26

A novel microelectrode modification method is reported for neural electrode engineering with a flake nanostructure (nanoflake). The nanoflake-modified electrodes are fabricated by combining conventional lithography and electrochemical deposition to implement a microelectrode array (MEA) on a glass substrate. The unique geometrical properties of nanoflake sharp tips and valleys are studied by optical, electrochemical and electrical methods in order to verify the advantages of using nanoflakes for neural recording devices. The in vitro recording and stimulation of cultured hippocampal neurons are demonstrated on the nanoflake-modified MEA and the clear action potentials are observed due to the nanoflake impedance reduction effect.

Intelligent neural network diagnostic system

International Nuclear Information System (INIS)

Mohamed, A.H.

2010-01-01

Recently, artificial neural network (ANN) has made a significant mark in the domain of diagnostic applications. Neural networks are used to implement complex non-linear mappings (functions) using simple elementary units interrelated through connections with adaptive weights. The performance of the ANN is mainly depending on their topology structure and weights. Some systems have been developed using genetic algorithm (GA) to optimize the topology of the ANN. But, they suffer from some limitations. They are : (1) The computation time requires for training the ANN several time reaching for the average weight required, (2) Slowness of GA for optimization process and (3) Fitness noise appeared in the optimization of ANN. This research suggests new issues to overcome these limitations for finding optimal neural network architectures to learn particular problems. This proposed methodology is used to develop a diagnostic neural network system. It has been applied for a 600 MW turbo-generator as a case of real complex systems. The proposed system has proved its significant performance compared to two common methods used in the diagnostic applications.

Visual Working Memory Enhances the Neural Response to Matching Visual Input.

Science.gov (United States)

Gayet, Surya; Guggenmos, Matthias; Christophel, Thomas B; Haynes, John-Dylan; Paffen, Chris L E; Van der Stigchel, Stefan; Sterzer, Philipp

2017-07-12

Visual working memory (VWM) is used to maintain visual information available for subsequent goal-directed behavior. The content of VWM has been shown to affect the behavioral response to concurrent visual input, suggesting that visual representations originating from VWM and from sensory input draw upon a shared neural substrate (i.e., a sensory recruitment stance on VWM storage). Here, we hypothesized that visual information maintained in VWM would enhance the neural response to concurrent visual input that matches the content of VWM. To test this hypothesis, we measured fMRI BOLD responses to task-irrelevant stimuli acquired from 15 human participants (three males) performing a concurrent delayed match-to-sample task. In this task, observers were sequentially presented with two shape stimuli and a retro-cue indicating which of the two shapes should be memorized for subsequent recognition. During the retention interval, a task-irrelevant shape (the probe) was briefly presented in the peripheral visual field, which could either match or mismatch the shape category of the memorized stimulus. We show that this probe stimulus elicited a stronger BOLD response, and allowed for increased shape-classification performance, when it matched rather than mismatched the concurrently memorized content, despite identical visual stimulation. Our results demonstrate that VWM enhances the neural response to concurrent visual input in a content-specific way. This finding is consistent with the view that neural populations involved in sensory processing are recruited for VWM storage, and it provides a common explanation for a plethora of behavioral studies in which VWM-matching visual input elicits a stronger behavioral and perceptual response. SIGNIFICANCE STATEMENT Humans heavily rely on visual information to interact with their environment and frequently must memorize such information for later use. Visual working memory allows for maintaining such visual information in the mind

Cut loose and run: The complex role of ADAM proteases during neural crest cell development.

Science.gov (United States)

Alfandari, Dominique; Taneyhill, Lisa A

2018-02-24

ADAM metalloproteases have been shown to play critical roles during development. In this review, we will describe functional evidence that implicates ADAM proteins during the genesis, migration and differentiation of neural crest cells. We will restrict our analysis to the transmembrane ADAMs as other reviews have addressed the role of extracellular metalloproteases (Christian et al. [2013] Critical Reviews in Biochemistry and Molecular Biology 48:544-560). This review will describe advances that have been obtained mainly through the use of two vertebrate model systems, the frog, and avian embryos. The role of the principal substrates of ADAMs, the cadherins, has been extensively described in other reviews, most recently in (Cousin [1997] Mechanisms of Development 148:79-88; Taneyhill and Schiffmacher [2017] Genesis, 55). The function of ADAMs in the migration of other cell types, including the immune system, wound healing and cancer has been described previously in (Dreymueller et al. [2017] Mediators of Inflammation 2017: 9621724). Our goal is to illustrate both the importance of ADAMs in controlling neural crest behavior and how neural crest cells have helped us understand the molecular interactions, substrates, and functions of ADAM proteins in vivo. © 2018 Wiley Periodicals, Inc.

Astrocyte glycogen as an emergency fuel under conditions of glucose deprivation or intense neural activity.

Science.gov (United States)

Brown, Angus M; Ransom, Bruce R

2015-02-01

Energy metabolism in the brain is a complex process that is incompletely understood. Although glucose is agreed as the main energy support of the brain, the role of glucose is not clear, which has led to controversies that can be summarized as follows: the fate of glucose, once it enters the brain is unclear. It is not known the form in which glucose enters the cells (neurons and glia) within the brain, nor the degree of metabolic shuttling of glucose derived metabolites between cells, with a key limitation in our knowledge being the extent of oxidative metabolism, and how increased tissue activity alters this. Glycogen is present within the brain and is derived from glucose. Glycogen is stored in astrocytes and acts to provide short-term delivery of substrates to neural elements, although it may also contribute an important component to astrocyte metabolism. The roles played by glycogen awaits further study, but to date its most important role is in supporting neural elements during increased firing activity, where signaling molecules, proposed to be elevated interstitial K(+), indicative of elevated neural firing rates, activate glycogen phosphorylase leading to increased production of glycogen derived substrate.

The neural substrate of analogical reasoning: an fMRI study.

Science.gov (United States)

Luo, Qian; Perry, Conrad; Peng, Danling; Jin, Zhen; Xu, Duo; Ding, Guosheng; Xu, Shiyong

2003-10-01

This study investigated the anatomical substrate of analogical reasoning using functional magnetic resonance imaging. In the study, subjects performed a verbal analogy task (e.g., soldier is to army as drummer is to band) and, to control for activation caused by purely semantic access, a semantic judgment task. Significant activation differences between the verbal analogy and the semantic judgment task were found bilaterally in the prefrontal cortex (right BA 11/BA 47 and left BA45), the fusiform gyrus, and the basal ganglia; left lateralized in the postero-superior temporal gyrus (BA 22) and the (para) hippocampal region; and right lateralized in the anterior cingulate. The role of these areas in analogical reasoning is discussed.

Routes to the past: Neural substrates of direct and generative autobiographical memory retrieval

OpenAIRE

Addis, Donna Rose; Knapp, Katie; Roberts, Reece P.; Schacter, Daniel L.

2011-01-01

Models of autobiographical memory propose two routes to retrieval depending on cue specificity. When available cues are specific and personally-relevant, a memory can be directly accessed. However, when available cues are generic, one must engage a generative retrieval process to produce more specific cues to successfully access a relevant memory. The current study sought to characterize the neural bases of these retrieval processes. During functional magnetic resonance imaging (fMRI), partic...

Effects of the BDNF Val66Met polymorphism on neural responses to facial emotion.

Science.gov (United States)

Mukherjee, Prerona; Whalley, Heather C; McKirdy, James W; McIntosh, Andrew M; Johnstone, Eve C; Lawrie, Stephen M; Hall, Jeremy

2011-03-31

The brain derived neurotrophic factor (BDNF) Val66Met polymorphism has been associated with affective disorders, but its role in emotion processing has not been fully established. Due to the clinically heterogeneous nature of these disorders, studying the effect of genetic variation in the BDNF gene on a common attribute such as fear processing may elucidate how the BDNF Val66Met polymorphism impacts brain function. Here we use functional magnetic resonance imaging examine the effect of the BDNF Val66Met genotype on neural activity for fear processing. Forty healthy participants performed an implicit fear task during scanning, where subjects made gender judgments from facial images with neutral or fearful emotion. Subjects were tested for facial emotion recognition post-scan. Functional connectivity was investigated using psycho-physiological interactions. Subjects were genotyped for the BDNF Val66Met polymorphism and the measures compared between genotype groups. Met carriers showed overactivation in the anterior cingulate cortex (ACC), brainstem and insula bilaterally for fear processing, along with reduced functional connectivity from the ACC to the left hippocampus, and impaired fear recognition ability. The results show that during fear processing, Met allele carriers show an increased neural response in regions previously implicated in mediating autonomic arousal. Further, the Met carriers show decreased functional connectivity with the hippocampus, which may reflect differential retrieval of emotional associations. Together, these effects show significant differences in the neural substrate for fear processing with genetic variation in BDNF. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Noradrenergic modulation of neural erotic stimulus perception.

Science.gov (United States)

Graf, Heiko; Wiegers, Maike; Metzger, Coraline Danielle; Walter, Martin; Grön, Georg; Abler, Birgit

2017-09-01

We recently investigated neuromodulatory effects of the noradrenergic agent reboxetine and the dopamine receptor affine amisulpride in healthy subjects on dynamic erotic stimulus processing. Whereas amisulpride left sexual functions and neural activations unimpaired, we observed detrimental activations under reboxetine within the caudate nucleus corresponding to motivational components of sexual behavior. However, broadly impaired subjective sexual functioning under reboxetine suggested effects on further neural components. We now investigated the same sample under these two agents with static erotic picture stimulation as alternative stimulus presentation mode to potentially observe further neural treatment effects of reboxetine. 19 healthy males were investigated under reboxetine, amisulpride and placebo for 7 days each within a double-blind cross-over design. During fMRI static erotic picture were presented with preceding anticipation periods. Subjective sexual functions were assessed by a self-reported questionnaire. Neural activations were attenuated within the caudate nucleus, putamen, ventral striatum, the pregenual and anterior midcingulate cortex and in the orbitofrontal cortex under reboxetine. Subjective diminished sexual arousal under reboxetine was correlated with attenuated neural reactivity within the posterior insula. Again, amisulpride left neural activations along with subjective sexual functioning unimpaired. Neither reboxetine nor amisulpride altered differential neural activations during anticipation of erotic stimuli. Our results verified detrimental effects of noradrenergic agents on neural motivational but also emotional and autonomic components of sexual behavior. Considering the overlap of neural network alterations with those evoked by serotonergic agents, our results suggest similar neuromodulatory effects of serotonergic and noradrenergic agents on common neural pathways relevant for sexual behavior. Copyright © 2017 Elsevier B.V. and

Games in the Brain: Neural Substrates of Gambling Addiction.

Science.gov (United States)

Murch, W Spencer; Clark, Luke

2016-10-01

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

Region stability analysis and tracking control of memristive recurrent neural network.

Science.gov (United States)

Bao, Gang; Zeng, Zhigang; Shen, Yanjun

2018-02-01

Memristor is firstly postulated by Leon Chua and realized by Hewlett-Packard (HP) laboratory. Research results show that memristor can be used to simulate the synapses of neurons. This paper presents a class of recurrent neural network with HP memristors. Firstly, it shows that memristive recurrent neural network has more compound dynamics than the traditional recurrent neural network by simulations. Then it derives that n dimensional memristive recurrent neural network is composed of [Formula: see text] sub neural networks which do not have a common equilibrium point. By designing the tracking controller, it can make memristive neural network being convergent to the desired sub neural network. At last, two numerical examples are given to verify the validity of our result. Copyright © 2017 Elsevier Ltd. All rights reserved.

Natural language acquisition in large scale neural semantic networks

Science.gov (United States)

Ealey, Douglas

This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

Predicting CYP2C19 Catalytic Parameters for Enantioselective Oxidations Using Artificial Neural Networks and a Chirality Code

Science.gov (United States)

Hartman, Jessica H.; Cothren, Steven D.; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A.; Miller, Grover P.

2013-01-01

Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (kcat, Km, and kcat/Km), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (kcat and Km) were more consistent with experimental values than those for catalytic efficiency (kcat/Km). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds. PMID:23673224

Phase Diagram of Spiking Neural Networks

Directory of Open Access Journals (Sweden)

Hamed eSeyed-Allaei

2015-03-01

Full Text Available In computer simulations of spiking neural networks, often it is assumed that every two neurons of the network are connected by a probablilty of 2%, 20% of neurons are inhibitory and 80% are excitatory. These common values are based on experiments, observations. but here, I take a different perspective, inspired by evolution. I simulate many networks, each with a different set of parameters, and then I try to figure out what makes the common values desirable by nature. Networks which are configured according to the common values, have the best dynamic range in response to an impulse and their dynamic range is more robust in respect to synaptic weights. In fact, evolution has favored networks of best dynamic range. I present a phase diagram that shows the dynamic ranges of different networks of different parameteres. This phase diagram gives an insight into the space of parameters -- excitatory to inhibitory ratio, sparseness of connections and synaptic weights. It may serve as a guideline to decide about the values of parameters in a simulation of spiking neural network.

Forecasting PM10 in metropolitan areas: Efficacy of neural networks

International Nuclear Information System (INIS)

Fernando, H.J.S.; Mammarella, M.C.; Grandoni, G.; Fedele, P.; Di Marco, R.; Dimitrova, R.; Hyde, P.

2012-01-01

Deterministic photochemical air quality models are commonly used for regulatory management and planning of urban airsheds. These models are complex, computer intensive, and hence are prohibitively expensive for routine air quality predictions. Stochastic methods are becoming increasingly popular as an alternative, which relegate decision making to artificial intelligence based on Neural Networks that are made of artificial neurons or ‘nodes’ capable of ‘learning through training’ via historic data. A Neural Network was used to predict particulate matter concentration at a regulatory monitoring site in Phoenix, Arizona; its development, efficacy as a predictive tool and performance vis-à-vis a commonly used regulatory photochemical model are described in this paper. It is concluded that Neural Networks are much easier, quicker and economical to implement without compromising the accuracy of predictions. Neural Networks can be used to develop rapid air quality warning systems based on a network of automated monitoring stations.Highlights: ► Neural Network is an alternative technique to photochemical modelling. ► Neutral Networks can be as effective as traditional air photochemical modelling. ► Neural Networks are much easier and quicker to implement in health warning system. - Neutral networks are as effective as photochemical modelling for air quality predictions, but are much easier, quicker and economical to implement in air pollution (or health) warning systems.

Autism spectrum disorders and drug addiction: Common pathways, common molecules, distinct disorders?

Directory of Open Access Journals (Sweden)

Patrick E. Rothwell

2016-02-01

Full Text Available Autism spectrum disorders (ASDs and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP and methyl CpG-binding protein-2 (MECP2, which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction.

Autism Spectrum Disorders and Drug Addiction: Common Pathways, Common Molecules, Distinct Disorders?

Science.gov (United States)

Rothwell, Patrick E

2016-01-01

Autism spectrum disorders (ASDs) and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP) and methyl CpG-binding protein-2 (MECP2), which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction.

Modulation of multiple memory systems: from neurotransmitters to metabolic substrates.

Science.gov (United States)

Gold, Paul E; Newman, Lori A; Scavuzzo, Claire J; Korol, Donna L

2013-11-01

This article reviews evidence showing that neurochemical modulators can regulate the relative participation of the hippocampus and striatum in learning and memory tasks. For example, relative release of acetylcholine increases in the hippocampus and striatum reflects the relative engagement of these brain systems during learning of place and response tasks. Acetylcholine release is regulated in part by available brain glucose levels, which themselves are dynamically modified during learning. Recent findings suggest that glucose acts through astrocytes to deliver lactate to neurons. Brain glycogen is contained in astrocytes and provides a capacity to deliver energy substrates to neurons when needed, a need that can be generated by training on tasks that target hippocampal and striatal processing mechanisms. These results integrate an increase in blood glucose after epinephrine release from the adrenal medulla with provision of brain energy substrates, including lactate released from astrocytes. Together, the availability of peripheral and central energy substrates regulate the processing of learning and memory within and across multiple neural systems. Dysfunctions of the physiological steps that modulate memory--from hormones to neurotransmitters to metabolic substrates--may contribute importantly to some of the cognitive impairments seen during normal aging and during neurodegenerative diseases. Copyright © 2013 Wiley Periodicals, Inc.

Neural substrates underlying effort, time, and risk-based decision making in motivated behavior.

Science.gov (United States)

Bailey, Matthew R; Simpson, Eleanor H; Balsam, Peter D

2016-09-01

All mobile organisms rely on adaptive motivated behavior to overcome the challenges of living in an environment in which essential resources may be limited. A variety of influences ranging from an organism's environment, experiential history, and physiological state all influence a cost-benefit analysis which allows motivation to energize behavior and direct it toward specific goals. Here we review the substantial amount of research aimed at discovering the interconnected neural circuits which allow organisms to carry-out the cost-benefit computations which allow them to behave in adaptive ways. We specifically focus on how the brain deals with different types of costs, including effort requirements, delays to reward and payoff riskiness. An examination of this broad literature highlights the importance of the extended neural circuits which enable organisms to make decisions about these different types of costs. This involves Cortical Structures, including the Anterior Cingulate Cortex (ACC), the Orbital Frontal Cortex (OFC), the Infralimbic Cortex (IL), and prelimbic Cortex (PL), as well as the Baso-Lateral Amygdala (BLA), the Nucleus Accumbens (NAcc), the Ventral Pallidal (VP), the Sub Thalamic Nucleus (STN) among others. Some regions are involved in multiple aspects of cost-benefit computations while the involvement of other regions is restricted to information relating to specific types of costs. Copyright © 2016 Elsevier Inc. All rights reserved.

Routes to the past: neural substrates of direct and generative autobiographical memory retrieval.

Science.gov (United States)

Addis, Donna Rose; Knapp, Katie; Roberts, Reece P; Schacter, Daniel L

2012-02-01

Models of autobiographical memory propose two routes to retrieval depending on cue specificity. When available cues are specific and personally-relevant, a memory can be directly accessed. However, when available cues are generic, one must engage a generative retrieval process to produce more specific cues to successfully access a relevant memory. The current study sought to characterize the neural bases of these retrieval processes. During functional magnetic resonance imaging (fMRI), participants were shown personally-relevant cues to elicit direct retrieval, or generic cues (nouns) to elicit generative retrieval. We used spatiotemporal partial least squares to characterize the spatial and temporal characteristics of the networks associated with direct and generative retrieval. Both retrieval tasks engaged regions comprising the autobiographical retrieval network, including hippocampus, and medial prefrontal and parietal cortices. However, some key neural differences emerged. Generative retrieval differentially recruited lateral prefrontal and temporal regions early on during the retrieval process, likely supporting the strategic search operations and initial recovery of generic autobiographical information. However, many regions were activated more strongly during direct versus generative retrieval, even when we time-locked the analysis to the successful recovery of events in both conditions. This result suggests that there may be fundamental differences between memories that are accessed directly and those that are recovered via the iterative search and retrieval process that characterizes generative retrieval. Copyright © 2011 Elsevier Inc. All rights reserved.

Musical Audio Synthesis Using Autoencoding Neural Nets

OpenAIRE

Sarroff, Andy; Casey, Michael A.

2014-01-01

With an optimal network topology and tuning of hyperpa-\\ud rameters, artificial neural networks (ANNs) may be trained\\ud to learn a mapping from low level audio features to one\\ud or more higher-level representations. Such artificial neu-\\ud ral networks are commonly used in classification and re-\\ud gression settings to perform arbitrary tasks. In this work\\ud we suggest repurposing autoencoding neural networks as\\ud musical audio synthesizers. We offer an interactive musi-\\ud cal audio synt...

Brain oscillatory substrates of visual short-term memory capacity.

Science.gov (United States)

Sauseng, Paul; Klimesch, Wolfgang; Heise, Kirstin F; Gruber, Walter R; Holz, Elisa; Karim, Ahmed A; Glennon, Mark; Gerloff, Christian; Birbaumer, Niels; Hummel, Friedhelm C

2009-11-17

The amount of information that can be stored in visual short-term memory is strictly limited to about four items. Therefore, memory capacity relies not only on the successful retention of relevant information but also on efficient suppression of distracting information, visual attention, and executive functions. However, completely separable neural signatures for these memory capacity-limiting factors remain to be identified. Because of its functional diversity, oscillatory brain activity may offer a utile solution. In the present study, we show that capacity-determining mechanisms, namely retention of relevant information and suppression of distracting information, are based on neural substrates independent of each other: the successful maintenance of relevant material in short-term memory is associated with cross-frequency phase synchronization between theta (rhythmical neural activity around 5 Hz) and gamma (> 50 Hz) oscillations at posterior parietal recording sites. On the other hand, electroencephalographic alpha activity (around 10 Hz) predicts memory capacity based on efficient suppression of irrelevant information in short-term memory. Moreover, repetitive transcranial magnetic stimulation at alpha frequency can modulate short-term memory capacity by influencing the ability to suppress distracting information. Taken together, the current study provides evidence for a double dissociation of brain oscillatory correlates of visual short-term memory capacity.

Battery-Free Love-Wave-Based Neural Probe and Its Wireless Characterizations

Science.gov (United States)

Jung, In Ki; Fu, Chen; Lee, Keekeun

2013-06-01

A wireless Love-wave-based neural probe that utilizes a one-port reflective delay line was developed for both reading and stimulating neurons in the brain. Poly(methyl methacrylate) (PMMA) as a waveguide layer and gold (Au) electrodes were structured on the top of a 41° YX LiNbO3 piezoelectric substrate, following the parameters extracted from coupling-of-mode (COM) modeling. For a one-port reflective delay line, single-phase unidirectional transducers (SPUDTs) and three shorted grating reflectors were employed, which made possible the implementation of a wireless and battery-free neural probe. The fabricated Love-wave-based neural probes were wirelessly measured using two antennas with a 440 MHz central frequency and a network analyzer. Sharp reflection peaks with a high signal-to-noise ratio were observed from the reflection peaks. The probe was immersed in 0.9% saline solution while applying input DC voltages. Good linearity, high sensitivity, and reproducibility were observed depending on DC applied voltage, in the range from 0 to 500 mV. The sensitivity obtained from the DC firings (artificial neural firings) was ˜0.04 µs/VDC, indicating that this prototype probe is very promising for the wireless reading and stimulation of neural firings in in vivo animal testing.

Neural mechanisms underlying morphine withdrawal in addicted patients: a review

Directory of Open Access Journals (Sweden)

Nima Babhadiashar

2015-06-01

Full Text Available Morphine is one of the most potent alkaloid in opium, which has substantial medical uses and needs and it is the first active principle purified from herbal source. Morphine has commonly been used for relief of moderate to severe pain as it acts directly on the central nervous system; nonetheless, its chronic abuse increases tolerance and physical dependence, which is commonly known as opiate addiction. Morphine withdrawal syndrome is physiological and behavioral symptoms that stem from prolonged exposure to morphine. A majority of brain regions are hypofunctional over prolonged abstinence and acute morphine withdrawal. Furthermore, several neural mechanisms are likely to contribute to morphine withdrawal. The present review summarizes the literature pertaining to neural mechanisms underlying morphine withdrawal. Despite the fact that morphine withdrawal is a complex process, it is suggested that neural mechanisms play key roles in morphine withdrawal.

Analysis of Al2O3—parylene C bilayer coatings and impact of microelectrode topography on long term stability of implantable neural arrays

Science.gov (United States)

Caldwell, Ryan; Mandal, Himadri; Sharma, Rohit; Solzbacher, Florian; Tathireddy, Prashant; Rieth, Loren

2017-08-01

Objective. Performance of many dielectric coatings for neural electrodes degrades over time, contributing to loss of neural signals and evoked percepts. Studies using planar test substrates have found that a novel bilayer coating of atomic-layer deposited (ALD) Al2O3 and parylene C is a promising candidate for neural electrode applications, exhibiting superior stability to parylene C alone. However, initial results from bilayer encapsulation testing on non-planar devices have been less positive. Our aim was to evaluate ALD Al2O3-parylene C coatings using novel test paradigms, to rigorously evaluate dielectric coatings for neural electrode applications by incorporating neural electrode topography into test structure design. Approach. Five test devices incorporated three distinct topographical features common to neural electrodes, derived from the utah electrode array (UEA). Devices with bilayer (52 nm Al2O3  +  6 µm parylene C) were evaluated against parylene C controls (N  ⩾  6 per device type). Devices were aged in phosphate buffered saline at 67 °C for up to 311 d, and monitored through: (1) leakage current to evaluate encapsulation lifetimes (>1 nA during 5VDC bias indicated failure), and (2) wideband (1-105 Hz) impedance. Main results. Mean-times-to-failure (MTTFs) ranged from 12 to 506 d for bilayer-coated devices, versus 10 to  >2310 d for controls. Statistical testing (log-rank test, α  =  0.05) of failure rates gave mixed results but favored the control condition. After failure, impedance loss for bilayer devices continued for months and manifested across the entire spectrum, whereas the effect was self-limiting after several days, and restricted to frequencies  physiological fluids may improve performance. Testing frameworks which take neural electrode complexities into account will be well suited to reliably evaluate such encapsulation schemes.

Non-invasive neural stimulation

Science.gov (United States)

Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

2017-05-01

Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

Behavioral and Physiological Neural Network Analyses: A Common Pathway toward Pattern Recognition and Prediction

Science.gov (United States)

Ninness, Chris; Lauter, Judy L.; Coffee, Michael; Clary, Logan; Kelly, Elizabeth; Rumph, Marilyn; Rumph, Robin; Kyle, Betty; Ninness, Sharon K.

2012-01-01

Using 3 diversified datasets, we explored the pattern-recognition ability of the Self-Organizing Map (SOM) artificial neural network as applied to diversified nonlinear data distributions in the areas of behavioral and physiological research. Experiment 1 employed a dataset obtained from the UCI Machine Learning Repository. Data for this study…

Recurrent Neural Network for Computing Outer Inverse.

Science.gov (United States)

Živković, Ivan S; Stanimirović, Predrag S; Wei, Yimin

2016-05-01

Two linear recurrent neural networks for generating outer inverses with prescribed range and null space are defined. Each of the proposed recurrent neural networks is based on the matrix-valued differential equation, a generalization of dynamic equations proposed earlier for the nonsingular matrix inversion, the Moore-Penrose inversion, as well as the Drazin inversion, under the condition of zero initial state. The application of the first approach is conditioned by the properties of the spectrum of a certain matrix; the second approach eliminates this drawback, though at the cost of increasing the number of matrix operations. The cases corresponding to the most common generalized inverses are defined. The conditions that ensure stability of the proposed neural network are presented. Illustrative examples present the results of numerical simulations.

The motivation and pleasure dimension of negative symptoms: neural substrates and behavioral outputs.

Science.gov (United States)

Kring, Ann M; Barch, Deanna M

2014-05-01

A range of emotional and motivation impairments have long been clinically documented in people with schizophrenia, and there has been a resurgence of interest in understanding the psychological and neural mechanisms of the so-called "negative symptoms" in schizophrenia, given their lack of treatment responsiveness and their role in constraining function and life satisfaction in this illness. Negative symptoms comprise two domains, with the first covering diminished motivation and pleasure across a range of life domains and the second covering diminished verbal and non-verbal expression and communicative output. In this review, we focus on four aspects of the motivation/pleasure domain, providing a brief review of the behavioral and neural underpinnings of this domain. First, we cover liking or in-the-moment pleasure: immediate responses to pleasurable stimuli. Second, we cover anticipatory pleasure or wanting, which involves prediction of a forthcoming enjoyable outcome (reward) and feeling pleasure in anticipation of that outcome. Third, we address motivation, which comprises effort computation, which involves figuring out how much effort is needed to achieve a desired outcome, planning, and behavioral response. Finally, we cover the maintenance emotional states and behavioral responses. Throughout, we consider the behavioral manifestations and brain representations of these four aspects of motivation/pleasure deficits in schizophrenia. We conclude with directions for future research as well as implications for treatment. Copyright © 2013 Elsevier B.V. and ECNP. All rights reserved.

A graph-Laplacian-based feature extraction algorithm for neural spike sorting.

Science.gov (United States)

Ghanbari, Yasser; Spence, Larry; Papamichalis, Panos

2009-01-01

Analysis of extracellular neural spike recordings is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering which is performed in the feature space. This paper proposes a new feature extraction method (which we call Graph Laplacian Features, GLF) based on minimizing the graph Laplacian and maximizing the weighted variance. The algorithm is compared with Principal Components Analysis (PCA, the most commonly-used feature extraction method) using simulated neural data. The results show that the proposed algorithm produces more compact and well-separated clusters compared to PCA. As an added benefit, tentative cluster centers are output which can be used to initialize a subsequent clustering stage.

Polyurethane/poly(vinyl alcohol hydrogel coating improves the cytocompatibility of neural electrodes

Directory of Open Access Journals (Sweden)

Mei Li

2015-01-01

Full Text Available Neural electrodes, the core component of neural prostheses, are usually encapsulated in polydimethylsiloxane (PDMS. However, PDMS can generate a tissue response after implantation. Based on the physicochemical properties and excellent biocompatibility of polyurethane (PU and poly(vinyl alcohol (PVA when used as coating materials, we synthesized PU/PVA hydrogel coatings and coated the surface of PDMS using plasma treatment, and the cytocompatibility to rat pheochromocytoma (PC12 cells was assessed. Protein adsorption tests indicated that the amount of protein adsorption onto the PDMS substrate was reduced by 92% after coating with the hydrogel. Moreover, the PC12 cells on the PU/PVA-coated PDMS showed higher cell density and longer and more numerous neurites than those on the uncoated PDMS. These results indicate that the PU/PVA hydrogel is cytocompatible and a promising coating material for neural electrodes to improve their biocompatibility.

Response variance in functional maps: neural darwinism revisited.

Directory of Open Access Journals (Sweden)

Hirokazu Takahashi

Full Text Available The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Response variance in functional maps: neural darwinism revisited.

Science.gov (United States)

Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

2013-01-01

The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.

Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

Science.gov (United States)

Lee, Chuen-Chien

1991-01-01

Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

Research of convolutional neural networks for traffic sign recognition

OpenAIRE

Stadalnikas, Kasparas

2017-01-01

In this thesis the convolutional neural networks application for traffic sign recognition is analyzed. Thesis describes the basic operations, techniques that are commonly used to apply in the image classification using convolutional neural networks. Also, this paper describes the data sets used for traffic sign recognition, their problems affecting the final training results. The paper reviews most popular existing technologies – frameworks for developing the solution for traffic sign recogni...

Analysis of neural data

CERN Document Server

Kass, Robert E; Brown, Emery N

2014-01-01

Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

Adhesion modification of neural stem cells induced by nanoscale ripple patterns

International Nuclear Information System (INIS)

Pedraz, P; Casado, S; Rodriguez, V; Ayuso-Sacido, A; Gnecco, E; Giordano, M C; Mongeot, F Buatier de

2016-01-01

We have studied the influence of anisotropic nanopatterns (ripples) on the adhesion and morphology of mouse neural stem cells (C17.2) on glass substrates using cell viability assay, optical microscopy and atomic force microscopy. The ripples were produced by defocused ion beam sputtering with inert Ar ions, which physically remove atoms from the surface at the energy of 800 eV. The ripple periodicity (∼200 nm) is comparable to the thickness of the cytoplasmatic microspikes (filopodia) which link the stem cells to the substrate. All methods show that the cell adhesion is significantly lowered compared to the same type of cells on flat glass surfaces. Furthermore, the AFM analysis reveals that the filopodia tend to be trapped parallel or perpendicular to the ripples, which limits the spreading of the stem cell on the rippled substrate. This opens the perspective of controlling the micro-adhesion of stem cells and the orientation of their filopodia by tuning the anisotropic substrate morphology without chemical reactions occurring at the surface. (paper)

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.

Readout from iconic memory and selective spatial attention involve similar neural processes.

Science.gov (United States)

Ruff, Christian C; Kristjánsson, Arni; Driver, Jon

2007-10-01

Iconic memory and spatial attention are often considered separately, but they may have functional similarities. Here we provide functional magnetic resonance imaging evidence for some common underlying neural effects. Subjects judged three visual stimuli in one hemifield of a bilateral array comprising six stimuli. The relevant hemifield for partial report was indicated by an auditory cue, administered either before the visual array (precue, spatial attention) or shortly after the array (postcue, iconic memory). Pre- and postcues led to similar activity modulations in lateral occipital cortex contralateral to the cued side. This finding indicates that readout from iconic memory can have some neural effects similar to those of spatial attention. We also found common bilateral activation of a fronto-parietal network for postcue and precue trials. These neuroimaging data suggest that some common neural mechanisms underlie selective spatial attention and readout from iconic memory. Some differences were also found; compared with precues, postcues led to higher activity in the right middle frontal gyrus.

Neural substrates of interpreting actions and emotions from body postures.

Science.gov (United States)

Kana, Rajesh K; Travers, Brittany G

2012-04-01

Accurately reading the body language of others may be vital for navigating the social world, and this ability may be influenced by factors, such as our gender, personality characteristics and neurocognitive processes. This fMRI study examined the brain activation of 26 healthy individuals (14 women and 12 men) while they judged the action performed or the emotion felt by stick figure characters appearing in different postures. In both tasks, participants activated areas associated with visual representation of the body, motion processing and emotion recognition. Behaviorally, participants demonstrated greater ease in judging the physical actions of the characters compared to judging their emotional states, and participants showed more activation in areas associated with emotion processing in the emotion detection task, whereas they showed more activation in visual, spatial and action-related areas in the physical action task. Gender differences emerged in brain responses, such that men showed greater activation than women in the left dorsal premotor cortex in both tasks. Finally, participants higher in self-reported empathy demonstrated greater activation in areas associated with self-referential processing and emotion interpretation. These results suggest that empathy levels and sex of the participant may affect neural responses to emotional body language.

A developmental perspective on the neural bases of human empathy.

Science.gov (United States)

Tousignant, Béatrice; Eugène, Fanny; Jackson, Philip L

2017-08-01

While empathy has been widely studied in philosophical and psychological literatures, recent advances in social neuroscience have shed light on the neural correlates of this complex interpersonal phenomenon. In this review, we provide an overview of brain imaging studies that have investigated the neural substrates of human empathy. Based on existing models of the functional architecture of empathy, we review evidence of the neural underpinnings of each main component, as well as their development from infancy. Although early precursors of affective sharing and self-other distinction appear to be present from birth, recent findings also suggest that even higher-order components of empathy such as perspective-taking and emotion regulation demonstrate signs of development during infancy. This merging of developmental and social neuroscience literature thus supports the view that ontogenic development of empathy is rooted in early infancy, well before the emergence of verbal abilities. With age, the refinement of top-down mechanisms may foster more appropriate empathic responses, thus promoting greater altruistic motivation and prosocial behaviors. Copyright © 2016 Elsevier Inc. All rights reserved.

Concentration of radiocesium in cultivated mushrooms and substrates

International Nuclear Information System (INIS)

Miyake, Sadaaki; Higasa, Mamoru; Urabe, Ken-ichi; Haraguchi, Masato; Omura, Toshitaka

2008-01-01

Concentrations of 134 Cs, 137 Cs and 40 K in mushrooms cultivated in Saitama prefecture and those substrates were measured by gamma-ray spectrometry. In all mushrooms and substrates, 134 Cs was not detected. Concentrations of 137 Cs in mushrooms were in the range of 0.012 - 2.1 Bq/kg·fresh, and those in substrates were in the range of 0.080 - 1.8 Bq/kg·dry. Concentrations of 137 Cs in mushrooms varied widely with mushroom species, and the average concentration of 137 Cs in Lentinus edodes (Shiitake) was over 30 times higher than that in Pleurotus ostreatus (Hiratake). Mushroom-to-substrate concentration ratios of 137 Cs (fresh/dry) were 0.11-0.53. They were higher than the reported transfer factors for common agricultural plants. (author)

Atypical neural substrates of Embedded Figures Task performance in children with Autism Spectrum Disorders

OpenAIRE

Lee, Philip S.; Foss-Feig, Jennifer; Henderson, Joshua G.; Kenworthy, Lauren E.; Gilotty, Lisa; Gaillard, William D.; Vaidya, Chandan J.

2007-01-01

Superior performance on the Embedded Figures Task (EFT) has been attributed to weak central coherence in perceptual processing in Autism Spectrum Disorders (ASD). The present study used functional magnetic resonance imaging to examine the neural basis of EFT performance in 7-12 year old ASD children and age and IQ matched controls. ASD children activated only a subset of the distributed network of regions activated in controls. In frontal cortex, control children activated left dorsolateral, ...

Visual memory and visual mental imagery recruit common control and sensory regions of the brain.

Science.gov (United States)

Slotnick, Scott D; Thompson, William L; Kosslyn, Stephen M

2012-01-01

Separate lines of research have shown that visual memory and visual mental imagery are mediated by frontal-parietal control regions and can rely on occipital-temporal sensory regions of the brain. We used fMRI to assess the degree to which visual memory and visual mental imagery rely on the same neural substrates. During the familiarization/study phase, participants studied drawings of objects. During the test phase, words corresponding to old and new objects were presented. In the memory test, participants responded "remember," "know," or "new." In the imagery test, participants responded "high vividness," "moderate vividness," or "low vividness." Visual memory (old-remember) and visual imagery (old-high vividness) were commonly associated with activity in frontal-parietal control regions and occipital-temporal sensory regions. In addition, visual memory produced greater activity than visual imagery in parietal and occipital-temporal regions. The present results suggest that visual memory and visual imagery rely on highly similar--but not identical--cognitive processes.

Neural correlates of the food/non-food visual distinction.

Science.gov (United States)

Tsourides, Kleovoulos; Shariat, Shahriar; Nejati, Hossein; Gandhi, Tapan K; Cardinaux, Annie; Simons, Christopher T; Cheung, Ngai-Man; Pavlovic, Vladimir; Sinha, Pawan

2016-03-01

An evolutionarily ancient skill we possess is the ability to distinguish between food and non-food. Our goal here is to identify the neural correlates of visually driven 'edible-inedible' perceptual distinction. We also investigate correlates of the finer-grained likability assessment. Our stimuli depicted food or non-food items with sub-classes of appealing or unappealing exemplars. Using data-classification techniques drawn from machine-learning, as well as evoked-response analyses, we sought to determine whether these four classes of stimuli could be distinguished based on the patterns of brain activity they elicited. Subjects viewed 200 images while in a MEG scanner. Our analyses yielded two successes and a surprising failure. The food/non-food distinction had a robust neural counterpart and emerged as early as 85 ms post-stimulus onset. The likable/non-likable distinction too was evident in the neural signals when food and non-food stimuli were grouped together, or when only the non-food stimuli were included in the analyses. However, we were unable to identify any neural correlates of this distinction when limiting the analyses only to food stimuli. Taken together, these positive and negative results further our understanding of the substrates of a set of ecologically important judgments and have clinical implications for conditions like eating-disorders and anhedonia. Copyright © 2016 Elsevier B.V. All rights reserved.

Barratt Impulsivity and Neural Regulation of Physiological Arousal.

Directory of Open Access Journals (Sweden)

Sheng Zhang

Full Text Available Theories of personality have posited an increased arousal response to external stimulation in impulsive individuals. However, there is a dearth of studies addressing the neural basis of this association.We recorded skin conductance in 26 individuals who were assessed with Barratt Impulsivity Scale (BIS-11 and performed a stop signal task during functional magnetic resonance imaging. Imaging data were processed and modeled with Statistical Parametric Mapping. We used linear regressions to examine correlations between impulsivity and skin conductance response (SCR to salient events, identify the neural substrates of arousal regulation, and examine the relationship between the regulatory mechanism and impulsivity.Across subjects, higher impulsivity is associated with greater SCR to stop trials. Activity of the ventromedial prefrontal cortex (vmPFC negatively correlated to and Granger caused skin conductance time course. Furthermore, higher impulsivity is associated with a lesser strength of Granger causality of vmPFC activity on skin conductance, consistent with diminished control of physiological arousal to external stimulation. When men (n = 14 and women (n = 12 were examined separately, however, there was evidence suggesting association between impulsivity and vmPFC regulation of arousal only in women.Together, these findings confirmed the link between Barratt impulsivity and heightened arousal to salient stimuli in both genders and suggested the neural bases of altered regulation of arousal in impulsive women. More research is needed to explore the neural processes of arousal regulation in impulsive individuals and in clinical conditions that implicate poor impulse control.

Barratt Impulsivity and Neural Regulation of Physiological Arousal.

Science.gov (United States)

Zhang, Sheng; Hu, Sien; Hu, Jianping; Wu, Po-Lun; Chao, Herta H; Li, Chiang-shan R

2015-01-01

Theories of personality have posited an increased arousal response to external stimulation in impulsive individuals. However, there is a dearth of studies addressing the neural basis of this association. We recorded skin conductance in 26 individuals who were assessed with Barratt Impulsivity Scale (BIS-11) and performed a stop signal task during functional magnetic resonance imaging. Imaging data were processed and modeled with Statistical Parametric Mapping. We used linear regressions to examine correlations between impulsivity and skin conductance response (SCR) to salient events, identify the neural substrates of arousal regulation, and examine the relationship between the regulatory mechanism and impulsivity. Across subjects, higher impulsivity is associated with greater SCR to stop trials. Activity of the ventromedial prefrontal cortex (vmPFC) negatively correlated to and Granger caused skin conductance time course. Furthermore, higher impulsivity is associated with a lesser strength of Granger causality of vmPFC activity on skin conductance, consistent with diminished control of physiological arousal to external stimulation. When men (n = 14) and women (n = 12) were examined separately, however, there was evidence suggesting association between impulsivity and vmPFC regulation of arousal only in women. Together, these findings confirmed the link between Barratt impulsivity and heightened arousal to salient stimuli in both genders and suggested the neural bases of altered regulation of arousal in impulsive women. More research is needed to explore the neural processes of arousal regulation in impulsive individuals and in clinical conditions that implicate poor impulse control.

Functional neural substrates of posterior cortical atrophy patients.

Science.gov (United States)

Shames, H; Raz, N; Levin, Netta

2015-07-01

Posterior cortical atrophy (PCA) is a neurodegenerative syndrome in which the most pronounced pathologic involvement is in the occipito-parietal visual regions. Herein, we aimed to better define the cortical reflection of this unique syndrome using a thorough battery of behavioral and functional MRI (fMRI) tests. Eight PCA patients underwent extensive testing to map their visual deficits. Assessments included visual functions associated with lower and higher components of the cortical hierarchy, as well as dorsal- and ventral-related cortical functions. fMRI was performed on five patients to examine the neuronal substrate of their visual functions. The PCA patient cohort exhibited stereopsis, saccadic eye movements and higher dorsal stream-related functional impairments, including simultant perception, image orientation, figure-from-ground segregation, closure and spatial orientation. In accordance with the behavioral findings, fMRI revealed intact activation in the ventral visual regions of face and object perception while more dorsal aspects of perception, including motion and gestalt perception, revealed impaired patterns of activity. In most of the patients, there was a lack of activity in the word form area, which is known to be linked to reading disorders. Finally, there was evidence of reduced cortical representation of the peripheral visual field, corresponding to the behaviorally assessed peripheral visual deficit. The findings are discussed in the context of networks extending from parietal regions, which mediate navigationally related processing, visually guided actions, eye movement control and working memory, suggesting that damage to these networks might explain the wide range of deficits in PCA patients.

Normalization as a canonical neural computation

Science.gov (United States)

Carandini, Matteo; Heeger, David J.

2012-01-01

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation. PMID:22108672

Introduction to neural networks in high energy physics

International Nuclear Information System (INIS)

Therhaag, J.

2013-01-01

Artificial neural networks are a well established tool in high energy physics, playing an important role in both online and offline data analysis. Nevertheless they are often perceived as black boxes which perform obscure operations beyond the control of the user, resulting in a skepticism against any results that may be obtained using them. The situation is not helped by common explanations which try to draw analogies between artificial neural networks and the human brain, for the brain is an even more complex black box itself. In this introductory text, I will take a problem-oriented approach to neural network techniques, showing how the fundamental concepts arise naturally from the demand to solve classification tasks which are frequently encountered in high energy physics. Particular attention is devoted to the question how probability theory can be used to control the complexity of neural networks. (authors)

Experiments in Neural-Network Control of a Free-Flying Space Robot

Science.gov (United States)

Wilson, Edward

1995-01-01

Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype. The first issue concerns the importance of true system level design of the control system. A new hybrid strategy is developed here, in depth, for the beneficial integration of neural networks into the total control system. A second important issue in neural network control concerns incorporating a priori knowledge into the neural network. In many applications, it is possible to get a reasonably accurate controller using conventional means. If this prior information is used purposefully to provide a starting point for the optimizing capabilities of the neural network, it can provide much faster initial learning. In a step towards addressing this issue, a new generic Fully Connected Architecture (FCA) is developed for use with backpropagation. A third issue is that neural networks are commonly trained using a gradient based optimization method such as backpropagation; but many real world systems have Discrete Valued Functions (DVFs) that do not permit gradient based optimization. One example is the on-off thrusters that are common on spacecraft. A new technique is developed here that now extends backpropagation learning for use with DVFs. The fourth issue is that the speed of adaptation is often a limiting factor in the implementation of a neural network control system. This issue has been strongly resolved in the research by drawing on the above new contributions.

Mechanisms to medicines: elucidating neural and molecular substrates of fear extinction to identify novel treatments for anxiety disorders.

Science.gov (United States)

Bukalo, Olena; Pinard, Courtney R; Holmes, Andrew

2014-10-01

The burden of anxiety disorders is growing, but the efficacy of available anxiolytic treatments remains inadequate. Cognitive behavioural therapy for anxiety disorders focuses on identifying and modifying maladaptive patterns of thinking and behaving, and has a testable analogue in rodents in the form of fear extinction. A large preclinical literature has amassed in recent years describing the neural and molecular basis of fear extinction in rodents. In this review, we discuss how this work is being harnessed to foster translational research on anxiety disorders and facilitate the search for new anxiolytic treatments. We begin by summarizing the anatomical and functional connectivity of a medial prefrontal cortex (mPFC)-amygdala circuit that subserves fear extinction, including new insights from optogenetics. We then cover some of the approaches that have been taken to model impaired fear extinction and associated impairments with mPFC-amygdala dysfunction. The principal goal of the review is to evaluate evidence that various neurotransmitter and neuromodulator systems mediate fear extinction by modulating the mPFC-amygdala circuitry. To that end, we describe studies that have tested how fear extinction is impaired or facilitated by pharmacological manipulations of dopamine, noradrenaline, 5-HT, GABA, glutamate, neuropeptides, endocannabinoids and various other systems, which either directly target the mPFC-amygdala circuit, or produce behavioural effects that are coincident with functional changes in the circuit. We conclude that there are good grounds to be optimistic that the progress in defining the molecular substrates of mPFC-amygdala circuit function can be effectively leveraged to identify plausible candidates for extinction-promoting therapies for anxiety disorders. © 2014 The British Pharmacological Society.

Artificial neural network based approach to transmission lines protection

International Nuclear Information System (INIS)

Joorabian, M.

1999-05-01

The aim of this paper is to present and accurate fault detection technique for high speed distance protection using artificial neural networks. The feed-forward multi-layer neural network with the use of supervised learning and the common training rule of error back-propagation is chosen for this study. Information available locally at the relay point is passed to a neural network in order for an assessment of the fault location to be made. However in practice there is a large amount of information available, and a feature extraction process is required to reduce the dimensionality of the pattern vectors, whilst retaining important information that distinguishes the fault point. The choice of features is critical to the performance of the neural networks learning and operation. A significant feature in this paper is that an artificial neural network has been designed and tested to enhance the precision of the adaptive capabilities for distance protection

Nonlinear signal processing using neural networks: Prediction and system modelling

Energy Technology Data Exchange (ETDEWEB)

Lapedes, A.; Farber, R.

1987-06-01

The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

On the neural mechanisms subserving consciousness and attention

Directory of Open Access Journals (Sweden)

Catherine eTallon-Baudry

2012-01-01

Full Text Available Consciousness, as described in the experimental literature, is a multi-faceted phenomenon, that impinges on other well-studied concepts such as attention and control. Do consciousness and attention refer to different aspects of the same core phenomenon, or do they correspond to distinct functions? One possibility to address this question is to examine the neural mechanisms underlying consciousness and attention. If consciousness and attention pertain to the same concept, they should rely on shared neural mechanisms. Conversely, if their underlying mechanisms are distinct, then consciousness and attention should be considered as distinct entities. This paper therefore reviews neurophysiological facts arguing in favor or against a tight relationship between consciousness and attention. Three neural mechanisms that have been associated with both attention and consciousness are examined (neural amplification, involvement of the fronto-parietal network, and oscillatory synchrony, to conclude that the commonalities between attention and consciousness at the neural level may have been overestimated. Last but not least, experiments in which both attention and consciousness were probed at the neural level point toward a dissociation between the two concepts. It therefore appears from this review that consciousness and attention rely on distinct neural properties, although they can interact at the behavioral level. It is proposed that a "cumulative influence model", in which attention and consciousness correspond to distinct neural mechanisms feeding a single decisional process leading to behavior, fits best with available neural and behavioral data. In this view, consciousness should not be considered as a top-level executive function but should rather be defined by its experiential properties.

A neural model for temporal order judgments and their active recalibration: a common mechanism for space and time?

Directory of Open Access Journals (Sweden)

Mingbo eCai

2012-11-01

Full Text Available When observers experience a constant delay between their motor actions and sensory feedback, their perception of the temporal order between actions and sensations adapt (Stetson et al., 2006a. We present here a novel neural model that can explain temporal order judgments (TOJs and their recalibration. Our model employs three ubiquitous features of neural systems: 1 information pooling, 2 opponent processing, and 3 synaptic scaling. Specifically, the model proposes that different populations of neurons encode different delays between motor-sensory events, the outputs of these populations feed into rivaling neural populations (encoding before and after, and the activity difference between these populations determines the perceptual judgment. As a consequence of synaptic scaling of input weights, motor acts which are consistently followed by delayed sensory feedback will cause the network to recalibrate its point of subjective simultaneity. The structure of our model raises the possibility that recalibration of TOJs is a temporal analogue to the motion aftereffect. In other words, identical neural mechanisms may be used to make perceptual determinations about both space and time. Our model captures behavioral recalibration results for different numbers of adapting trials and different adapting delays. In line with predictions of the model, we additionally demonstrate that temporal recalibration can last through time, in analogy to storage of the motion aftereffect.

Sensorimotor learning biases choice behavior: a learning neural field model for decision making.

Directory of Open Access Journals (Sweden)

Christian Klaes

Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action

Real-time sensing of epithelial cell-cell and cell-substrate interactions by impedance spectroscopy on porous substrates

Energy Technology Data Exchange (ETDEWEB)

Mondal, D.; RoyChaudhuri, C., E-mail: chirosreepram@yahoo.com [Department of Electronics and Telecommunication Engineering, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103 (India); Pal, D. [Department of Aerospace Engineering and Applied Mechanics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103 (India)

2015-07-28

Oxidized porous silicon (PS) is a common topographical biocompatible substrate that potentially provides a distinct in vitro environment for better understanding of in vivo behavior. But in the reported studies on oxidized PS, cell-cell and cell-substrate interactions have been detected only by fluorescent labeling. This paper is the first attempt to investigate real-time sensing of these interactions on HaCaT cells by label-free impedance spectroscopy on oxidized PS of two pore diameters (50 and 500 nm). One of the major requirements for successful impedance spectroscopy measurement is to restrict the channeling of electric field lines through the pores. To satisfy this criterion, we have designed the pore depths after analyzing the penetration of the medium by using computational fluid dynamics simulation. A distributed electrical model was also developed for estimating the various cellular attributes by considering a pseudorandom distribution of pores. It is observed from the impedance measurements and from the model that the proliferation rate increases for 50 nm pores but decreases for 500 nm pores compared to that for planar substrates. The rate of decrease in cell substrate separation (h) in the initial stage is more than the rate of increase in cell-cell junction resistance (R{sub b}) corresponding to the initial adhesion phase of cells. It is observed that R{sub b} and h are higher for 50 nm pores than those for planar substrates, corresponding to the fact that substrates more conducive toward cell adhesion encourage cell-cell interactions than direct cell-substrate interactions. Thus, the impedance spectroscopy coupled with the proposed theoretical framework for PS substrates can sense and quantify the cellular interactions.

Real-time sensing of epithelial cell-cell and cell-substrate interactions by impedance spectroscopy on porous substrates

International Nuclear Information System (INIS)

Mondal, D.; RoyChaudhuri, C.; Pal, D.

2015-01-01

Oxidized porous silicon (PS) is a common topographical biocompatible substrate that potentially provides a distinct in vitro environment for better understanding of in vivo behavior. But in the reported studies on oxidized PS, cell-cell and cell-substrate interactions have been detected only by fluorescent labeling. This paper is the first attempt to investigate real-time sensing of these interactions on HaCaT cells by label-free impedance spectroscopy on oxidized PS of two pore diameters (50 and 500 nm). One of the major requirements for successful impedance spectroscopy measurement is to restrict the channeling of electric field lines through the pores. To satisfy this criterion, we have designed the pore depths after analyzing the penetration of the medium by using computational fluid dynamics simulation. A distributed electrical model was also developed for estimating the various cellular attributes by considering a pseudorandom distribution of pores. It is observed from the impedance measurements and from the model that the proliferation rate increases for 50 nm pores but decreases for 500 nm pores compared to that for planar substrates. The rate of decrease in cell substrate separation (h) in the initial stage is more than the rate of increase in cell-cell junction resistance (R b ) corresponding to the initial adhesion phase of cells. It is observed that R b and h are higher for 50 nm pores than those for planar substrates, corresponding to the fact that substrates more conducive toward cell adhesion encourage cell-cell interactions than direct cell-substrate interactions. Thus, the impedance spectroscopy coupled with the proposed theoretical framework for PS substrates can sense and quantify the cellular interactions

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

DEFF Research Database (Denmark)

Hjerrild, M.; Stensballe, A.; Rasmussen, T.E.

2004-01-01

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

Identification of phosphorylation sites in protein kinase A substrates using artificial neural networks and mass spectrometry

DEFF Research Database (Denmark)

Hjerrild, Majbrit; Stensballe, Allan; Rasmussen, Thomas E

2011-01-01

Protein phosphorylation plays a key role in cell regulation and identification of phosphorylation sites is important for understanding their functional significance. Here, we present an artificial neural network algorithm: NetPhosK (http://www.cbs.dtu.dk/services/NetPhosK/) that predicts protein...

Photopolymerized materials and patterning for improved performance of neural prosthetics

Science.gov (United States)

Tuft, Bradley William

correlates with the maximum feature slope. Neurite alignment is compared on unpatterned, unidirectional, and multidirectional photopolymerized micropatterns. The effect of substrate rigidity on neurite alignment to physical cues was determined by maintaining equivalent pattern microfeatures, afforded by the reaction control of photopolymerization, while concomitantly altering the composition of several copolymer platforms to tune matrix stiffness. For each platform, neurite alignment to unidirectional patterns increases with increasing substrate rigidity. Interestingly, SGN neurites respond to material stiffness cues that are orders of magnitude higher (GPa) than what is typically ascribed to neural environments (kPa). Finally, neurite behavior at bioactive borders of various adhesion modulating molecules was evaluated on micropatterned materials to determine which cues took precedence in establishing neurite directionality. At low microfeatures aspect ratios, neurites align to the pattern direction but are then caused to turn and repel from or turn and align to bioactive borders. Conversely, physical cues dominate neurite path-finding as pattern feature slope increases, i.e. aspect ratio of sloping photopolymerized features increases, causing neurites to readily cross bioactive borders. The photopolymerization method developed in this work to generate micro and nanopatterned materials serves as an additional surface engineering tool that enables investigation of cell-material interactions including directed de novo neurite growth. The results of this interdisciplinary effort contribute substantially to polymer neural regeneration technology and will lead to development of advanced biomaterials that improve neural prosthetic tissue integration and performance by spatially directing nerve growth.

Central neural pathways for thermoregulation

Science.gov (United States)

Morrison, Shaun F.; Nakamura, Kazuhiro

2010-01-01

Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160

Neural correlates of self-deception and impression-management.

Science.gov (United States)

Farrow, Tom F D; Burgess, Jenny; Wilkinson, Iain D; Hunter, Michael D

2015-01-01

Self-deception and impression-management comprise two types of deceptive, but generally socially acceptable behaviours, which are common in everyday life as well as being present in a number of psychiatric disorders. We sought to establish and dissociate the 'normal' brain substrates of self-deception and impression-management. Twenty healthy participants underwent fMRI scanning at 3T whilst completing the 'Balanced Inventory of Desirable Responding' test under two conditions: 'fake good', giving the most desirable impression possible and 'fake bad' giving an undesirable impression. Impression-management scores were more malleable to manipulation via 'faking' than self-deception scores. Response times to self-deception questions and 'fake bad' instructions were significantly longer than to impression-management questions and 'fake good' instructions respectively. Self-deception and impression-management manipulation and 'faking bad' were associated with activation of medial prefrontal cortex (mPFC) and left ventrolateral prefrontal cortex (vlPFC). Impression-management manipulation was additionally associated with activation of left dorsolateral prefrontal cortex and left posterior middle temporal gyrus. 'Faking bad' was additionally associated with activation of right vlPFC, left temporo-parietal junction and right cerebellum. There were no supra-threshold activations associated with 'faking good'. Our neuroimaging data suggest that manipulating self-deception and impression-management and more specifically 'faking bad' engages a common network comprising mPFC and left vlPFC. Shorter response times and lack of dissociable neural activations suggests that 'faking good', particularly when it comes to impression-management, may be our most practiced 'default' mode. Copyright © 2014 Elsevier Ltd. All rights reserved.

Neural Reactivity to Emotional Faces May Mediate the Relationship between Childhood Empathy and Adolescent Prosocial Behavior

Science.gov (United States)

Flournoy, John C.; Pfeifer, Jennifer H.; Moore, William E.; Tackman, Allison M.; Masten, Carrie L.; Mazziotta, John C.; Iacoboni, Marco; Dapretto, Mirella

2016-01-01

Reactivity to others' emotions not only can result in empathic concern (EC), an important motivator of prosocial behavior, but can also result in personal distress (PD), which may hinder prosocial behavior. Examining neural substrates of emotional reactivity may elucidate how EC and PD differentially influence prosocial behavior. Participants…

Low Back Pain - Management Perspective Of A commonly Encountered Problem

Directory of Open Access Journals (Sweden)

Parharaj S S

2004-01-01

Full Text Available Low Back pain is a very common symptom affecting the general population, incurring a huge annual societal cost. In spite of this, it remains very commonly misdiagnosed and maltreated. The majority of benign chronic low back pain patients suffer from a combination of myofascial frozen back syndrome with or without an overly of psychosocioeconomic factors. Neural compression causes are less frequent. A though evaluation of the patient to select the most rational therapeutic approach is necessary. In majority of the patients, a well planned out rehabilitation programme is useful. Surgery is indicated in a minority with neural compression or spinal instability, motivation is essential as rehabilitation and surgery have a high failure rate in inadequately motivated patients with psychosocioeconomic dysfunction.

Comparison of Back propagation neural network and Back propagation neural network Based Particle Swarm intelligence in Diagnostic Breast Cancer

Directory of Open Access Journals (Sweden)

Farahnaz SADOUGHI

2014-03-01

Full Text Available Breast cancer is the most commonly diagnosed cancer and the most common cause of death in women all over the world. Use of computer technology supporting breast cancer diagnosing is now widespread and pervasive across a broad range of medical areas. Early diagnosis of this disease can greatly enhance the chances of long-term survival of breast cancer victims. Artificial Neural Networks (ANN as mainly method play important role in early diagnoses breast cancer. This paper studies Levenberg Marquardet Backpropagation (LMBP neural network and Levenberg Marquardet Backpropagation based Particle Swarm Optimization(LMBP-PSO for the diagnosis of breast cancer. The obtained results show that LMBP and LMBP based PSO system provides higher classification efficiency. But LMBP based PSO needs minimum training and testing time. It helps in developing Medical Decision System (MDS for breast cancer diagnosing. It can also be used as secondary observer in clinical decision making.

Precision Scaling of Neural Networks for Efficient Audio Processing

OpenAIRE

Ko, Jong Hwan; Fromm, Josh; Philipose, Matthai; Tashev, Ivan; Zarar, Shuayb

2017-01-01

While deep neural networks have shown powerful performance in many audio applications, their large computation and memory demand has been a challenge for real-time processing. In this paper, we study the impact of scaling the precision of neural networks on the performance of two common audio processing tasks, namely, voice-activity detection and single-channel speech enhancement. We determine the optimal pair of weight/neuron bit precision by exploring its impact on both the performance and ...

Age-related difference in the effective neural connectivity associated with probabilistic category learning

International Nuclear Information System (INIS)

Yoon, Eun Jin; Cho, Sang Soo; Kim, Hee Jung; Bang, Seong Ae; Park, Hyun Soo; Kim, Yu Kyeong; Kim, Sang Eun

2007-01-01

Although it is well known that explicit memory is affected by the deleterious changes in brain with aging, but effect of aging in implicit memory such as probabilistic category learning (PCL) is not clear. To identify the effect of aging on the neural interaction for successful PCL, we investigated the neural substrates of PCL and the age-related changes of the neural network between these brain regions. 23 young (age, 252 y; 11 males) and 14 elderly (673 y; 7 males) healthy subjects underwent FDG PET during a resting state and 150-trial weather prediction (WP) task. Correlations between the WP hit rates and regional glucose metabolism were assessed using SPM2 (P diff (37) = 142.47, P<0.005), Systematic comparisons of each path revealed that frontal crosscallosal and the frontal to parahippocampal connection were most responsible for the model differences (P<0.05). For the successful PCL, the elderly recruits the basal ganglia implicit memory system but MTL recruitment differs from the young. The inadequate MTL correlation pattern in the elderly is may be caused by the changes of the neural pathway related with explicit memory. These neural changes can explain the decreased performance of PCL in elderly subjects

On the nature and evolution of the neural bases of human language

Science.gov (United States)

Lieberman, Philip

2002-01-01

the brains of human beings and other species provides insight into the evolution of the brain bases of human language. The neural substrate that regulated motor control in the common ancestor of apes and humans most likely was modified to enhance cognitive and linguistic ability. Speech communication played a central role in this process. However, the process that ultimately resulted in the human brain may have started when our earliest hominid ancestors began to walk.

Preparation and surface characterization of plasma-treated and biomolecular-micropatterned polymer substrates

Science.gov (United States)

Langowski, Bryan Alfred

A micropatterning process creates distinct microscale domains on substrate surfaces that differ from the surfaces' original chemical/physical properties. Numerous micropatterning methods exist, each having relative advantages and disadvantages in terms of cost, ease, reproducibility, and versatility. Polymeric surfaces micropatterned with biomolecules have many applications, but are specifically utilized in tissue engineering as cell scaffolds that attempt to controlled tissue generation in vivo and ex vivo. As the physical and chemical cues presented by micropatterned substrates control resulting cellular behavior, characterization of these cues via surface-sensitive analytical techniques is essential in developing cell scaffolds that mimic complex in vivo physicochemical environments. The initial focus of this thesis is the chemical and physical characterization of plasma-treated, microcontact-printed (muCP) polymeric substrates used to direct nerve cell behavior. Unmodified and oxygen plasma-treated poly(methyl methacrylate) (PMMA) substrates were analyzed by surface sensitive techniques to monitor plasma-induced chemical and physical modifications. Additionally, protein-micropattern homogeneity and size were microscopically evaluated. Lastly, poly(dimethylsiloxane) (PDMS) stamps and contaminated PMMA substrates were characterized by spectroscopic and microscopic methods to identify a contamination source during microcontact printing. The final focus of this thesis is the development of microscale plasma-initiated patterning (muPIP) as a versatile, reproducible micropatterning method. Using muPIP, polymeric substrates were micropatterned with several biologically relevant inks. Polymeric substrates were characterized following muPIP by surface-sensitive techniques to identify the technique's underlying physical and chemical bases. In addition, neural stem cell response to muPIP-generated laminin micropatterns was microscopically and biologically evaluated

Highly Sensitive Filter Paper Substrate for SERS Trace Explosives Detection

Directory of Open Access Journals (Sweden)

Pedro M. Fierro-Mercado

2012-01-01

Full Text Available We report on a novel and extremely low-cost surface-enhanced Raman spectroscopy (SERS substrate fabricated depositing gold nanoparticles on common lab filter paper using thermal inkjet technology. The paper-based substrate combines all advantages of other plasmonic structures fabricated by more elaborate techniques with the dynamic flexibility given by the inherent nature of the paper for an efficient sample collection, robustness, and stability. We describe the fabrication, characterization, and SERS activity of our substrate using 2,4,6-trinitrotoluene, 2,4-dinitrotoluene, and 1,3,5-trinitrobenzene as analytes. The paper-based SERS substrates presented a high sensitivity and excellent reproducibility for analytes employed, demonstrating a direct application in forensic science and homeland security.

Artificial neural networks application for solid fuel slagging intensity predictions

Directory of Open Access Journals (Sweden)

Kakietek Sławomir

2017-01-01

Full Text Available Slagging issues present in pulverized steam boilers very often lead to heat transfer problems, corrosion and not planned outages of boilers which increase the cost of energy production and decrease the efficiency of energy production. Slagging especially occurs in regions with reductive atmospheres which nowadays are very common due to very strict limitations in NOx emissions. Moreover alternative fuels like biomass which are also used in combustion systems from two decades in order to decrease CO2 emissions also usually increase the risk of slagging. Thus the prediction of slagging properties of fuels is not the minor issue which can be neglected before purchasing or mixing of fuels. This however is rather difficult to estimate and even commonly known standard laboratory methods like fusion temperature determination or special indexers calculated on the basis of proximate and ultimate analyses, very often have no reasonable correlation to real boiler fuel behaviour. In this paper the method of determination of slagging properties of solid fuels based on laboratory investigation and artificial neural networks were presented. A fuel data base with over 40 fuels was created. Neural networks simulations were carried out in order to predict the beginning temperature and intensity of slagging. Reasonable results were obtained for some of tested neural networks, especially for hybrid feedforward networks with PCA technique. Consequently neural network model will be used in Common Intelligent Boiler Operation Platform (CIBOP being elaborated within CERUBIS research project for two BP-1150 and BB-1150 steam boilers. The model among others enables proper fuel selection in order to minimize slagging risk.

Culture in the mind's mirror: how anthropology and neuroscience can inform a model of the neural substrate for cultural imitative learning.

Science.gov (United States)

Losin, Elizabeth A Reynolds; Dapretto, Mirella; Iacoboni, Marco

2009-01-01

Cultural neuroscience, the study of how cultural experience shapes the brain, is an emerging subdiscipline in the neurosciences. Yet, a foundational question to the study of culture and the brain remains neglected by neuroscientific inquiry: "How does cultural information get into the brain in the first place?" Fortunately, the tools needed to explore the neural architecture of cultural learning - anthropological theories and cognitive neuroscience methodologies - already exist; they are merely separated by disciplinary boundaries. Here we review anthropological theories of cultural learning derived from fieldwork and modeling; since cultural learning theory suggests that sophisticated imitation abilities are at the core of human cultural learning, we focus our review on cultural imitative learning. Accordingly we proceed to discuss the neural underpinnings of imitation and other mechanisms important for cultural learning: learning biases, mental state attribution, and reinforcement learning. Using cultural neuroscience theory and cognitive neuroscience research as our guides, we then propose a preliminary model of the neural architecture of cultural learning. Finally, we discuss future studies needed to test this model and fully explore and explain the neural underpinnings of cultural imitative learning.

Mitochondrial metabolism in early neural fate and its relevance for neuronal disease modeling.

Science.gov (United States)

Lorenz, Carmen; Prigione, Alessandro

2017-12-01

Modulation of energy metabolism is emerging as a key aspect associated with cell fate transition. The establishment of a correct metabolic program is particularly relevant for neural cells given their high bioenergetic requirements. Accordingly, diseases of the nervous system commonly involve mitochondrial impairment. Recent studies in animals and in neural derivatives of human pluripotent stem cells (PSCs) highlighted the importance of mitochondrial metabolism for neural fate decisions in health and disease. The mitochondria-based metabolic program of early neurogenesis suggests that PSC-derived neural stem cells (NSCs) may be used for modeling neurological disorders. Understanding how metabolic programming is orchestrated during neural commitment may provide important information for the development of therapies against conditions affecting neural functions, including aging and mitochondrial disorders. Copyright © 2017. Published by Elsevier Ltd.

Mechanisms to medicines: elucidating neural and molecular substrates of fear extinction to identify novel treatments for anxiety disorders

Science.gov (United States)

Bukalo, Olena; Pinard, Courtney R; Holmes, Andrew

2014-01-01

The burden of anxiety disorders is growing, but the efficacy of available anxiolytic treatments remains inadequate. Cognitive behavioural therapy for anxiety disorders focuses on identifying and modifying maladaptive patterns of thinking and behaving, and has a testable analogue in rodents in the form of fear extinction. A large preclinical literature has amassed in recent years describing the neural and molecular basis of fear extinction in rodents. In this review, we discuss how this work is being harnessed to foster translational research on anxiety disorders and facilitate the search for new anxiolytic treatments. We begin by summarizing the anatomical and functional connectivity of a medial prefrontal cortex (mPFC)–amygdala circuit that subserves fear extinction, including new insights from optogenetics. We then cover some of the approaches that have been taken to model impaired fear extinction and associated impairments with mPFC–amygdala dysfunction. The principal goal of the review is to evaluate evidence that various neurotransmitter and neuromodulator systems mediate fear extinction by modulating the mPFC–amygdala circuitry. To that end, we describe studies that have tested how fear extinction is impaired or facilitated by pharmacological manipulations of dopamine, noradrenaline, 5-HT, GABA, glutamate, neuropeptides, endocannabinoids and various other systems, which either directly target the mPFC–amygdala circuit, or produce behavioural effects that are coincident with functional changes in the circuit. We conclude that there are good grounds to be optimistic that the progress in defining the molecular substrates of mPFC–amygdala circuit function can be effectively leveraged to identify plausible candidates for extinction-promoting therapies for anxiety disorders. Linked Articles This article is part of a themed section on Animal Models in Psychiatry Research. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2014

q-state Potts-glass neural network based on pseudoinverse rule

International Nuclear Information System (INIS)

Xiong Daxing; Zhao Hong

2010-01-01

We study the q-state Potts-glass neural network with the pseudoinverse (PI) rule. Its performance is investigated and compared with that of the counterpart network with the Hebbian rule instead. We find that there exists a critical point of q, i.e., q cr =14, below which the storage capacity and the retrieval quality can be greatly improved by introducing the PI rule. We show that the dynamics of the neural networks constructed with the two learning rules respectively are quite different; but however, regardless of the learning rules, in the q-state Potts-glass neural networks with q≥3 there is a common novel dynamical phase in which the spurious memories are completely suppressed. This property has never been noticed in the symmetric feedback neural networks. Free from the spurious memories implies that the multistate Potts-glass neural networks would not be trapped in the metastable states, which is a favorable property for their applications.

A fuzzy Hopfield neural network for medical image segmentation

International Nuclear Information System (INIS)

Lin, J.S.; Cheng, K.S.; Mao, C.W.

1996-01-01

In this paper, an unsupervised parallel segmentation approach using a fuzzy Hopfield neural network (FHNN) is proposed. The main purpose is to embed fuzzy clustering into neural networks so that on-line learning and parallel implementation for medical image segmentation are feasible. The idea is to cast a clustering problem as a minimization problem where the criteria for the optimum segmentation is chosen as the minimization of the Euclidean distance between samples to class centers. In order to generate feasible results, a fuzzy c-means clustering strategy is included in the Hopfield neural network to eliminate the need of finding weighting factors in the energy function, which is formulated and based on a basic concept commonly used in pattern classification, called the within-class scatter matrix principle. The suggested fuzzy c-means clustering strategy has also been proven to be convergent and to allow the network to learn more effectively than the conventional Hopfield neural network. The fuzzy Hopfield neural network based on the within-class scatter matrix shows the promising results in comparison with the hard c-means method

Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

Directory of Open Access Journals (Sweden)

L. Khaouane

2013-03-01

Full Text Available This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively. Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

EEG in the classroom: Synchronised neural recordings during video presentation

DEFF Research Database (Denmark)

Poulsen, Andreas Trier; Kamronn, Simon Due; Dmochowski, Jacek

2017-01-01

We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional......-evoked neural responses, known to be modulated by attention, can be tracked for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom....

Musical and verbal semantic memory: two distinct neural networks?

Science.gov (United States)

Groussard, M; Viader, F; Hubert, V; Landeau, B; Abbas, A; Desgranges, B; Eustache, F; Platel, H

2010-02-01

Semantic memory has been investigated in numerous neuroimaging and clinical studies, most of which have used verbal or visual, but only very seldom, musical material. Clinical studies have suggested that there is a relative neural independence between verbal and musical semantic memory. In the present study, "musical semantic memory" is defined as memory for "well-known" melodies without any knowledge of the spatial or temporal circumstances of learning, while "verbal semantic memory" corresponds to general knowledge about concepts, again without any knowledge of the spatial or temporal circumstances of learning. Our aim was to compare the neural substrates of musical and verbal semantic memory by administering the same type of task in each modality. We used high-resolution PET H(2)O(15) to observe 11 young subjects performing two main tasks: (1) a musical semantic memory task, where the subjects heard the first part of familiar melodies and had to decide whether the second part they heard matched the first, and (2) a verbal semantic memory task with the same design, but where the material consisted of well-known expressions or proverbs. The musical semantic memory condition activated the superior temporal area and inferior and middle frontal areas in the left hemisphere and the inferior frontal area in the right hemisphere. The verbal semantic memory condition activated the middle temporal region in the left hemisphere and the cerebellum in the right hemisphere. We found that the verbal and musical semantic processes activated a common network extending throughout the left temporal neocortex. In addition, there was a material-dependent topographical preference within this network, with predominantly anterior activation during musical tasks and predominantly posterior activation during semantic verbal tasks. Copyright (c) 2009 Elsevier Inc. All rights reserved.

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

Science.gov (United States)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

Neural mechanisms of information storage in visual short-term memory.

Science.gov (United States)

Serences, John T

2016-11-01

The capacity to briefly memorize fleeting sensory information supports visual search and behavioral interactions with relevant stimuli in the environment. Traditionally, studies investigating the neural basis of visual short term memory (STM) have focused on the role of prefrontal cortex (PFC) in exerting executive control over what information is stored and how it is adaptively used to guide behavior. However, the neural substrates that support the actual storage of content-specific information in STM are more controversial, with some attributing this function to PFC and others to the specialized areas of early visual cortex that initially encode incoming sensory stimuli. In contrast to these traditional views, I will review evidence suggesting that content-specific information can be flexibly maintained in areas across the cortical hierarchy ranging from early visual cortex to PFC. While the factors that determine exactly where content-specific information is represented are not yet entirely clear, recognizing the importance of task-demands and better understanding the operation of non-spiking neural codes may help to constrain new theories about how memories are maintained at different resolutions, across different timescales, and in the presence of distracting information. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neural Mechanisms of Information Storage in Visual Short-Term Memory

Science.gov (United States)

Serences, John T.

2016-01-01

The capacity to briefly memorize fleeting sensory information supports visual search and behavioral interactions with relevant stimuli in the environment. Traditionally, studies investigating the neural basis of visual short term memory (STM) have focused on the role of prefrontal cortex (PFC) in exerting executive control over what information is stored and how it is adaptively used to guide behavior. However, the neural substrates that support the actual storage of content-specific information in STM are more controversial, with some attributing this function to PFC and others to the specialized areas of early visual cortex that initially encode incoming sensory stimuli. In contrast to these traditional views, I will review evidence suggesting that content-specific information can be flexibly maintained in areas across the cortical hierarchy ranging from early visual cortex to PFC. While the factors that determine exactly where content-specific information is represented are not yet entirely clear, recognizing the importance of task-demands and better understanding the operation of non-spiking neural codes may help to constrain new theories about how memories are maintained at different resolutions, across different timescales, and in the presence of distracting information. PMID:27668990

ANALYSIS OF WATER RELATIONS OF SUBSTRATES USED IN GREEN ROOF SYSTEMS

Directory of Open Access Journals (Sweden)

Anna Baryła

2014-10-01

Full Text Available Green roofs, as the restoration of biologically active area, are fairly common and effective method of storm water management in urban areas. Depend on the design of the green roof and the type of substrate, they are able to retain 50–90% of rainwater. The aim of the study was to determine the physicochemical properties of two substrates used in the construction of green roofs (intensive and extensive. Water retention of substrates was compared to water retention of substrates undelined with the drainage layer made from crushed autoclaved aerated concrete. In the experiment, which uses drainage layer, higher drying the top layer of the substrate was observed, which may be related to high water absorption drainage material. The effluent from the substrate using aerated concrete as a drainage layer amounted to an average of 22–51% of the volume of water supplied to the extensive substrate, whereas 19–46% of the volume of water supplied to the intensive substrate. The effluent from the substrate without the drainage layer amounted 40-48% of the volume of water supplied.

Commonalities and differences in the neural representations of English, Portuguese, and Mandarin sentences: When knowledge of the brain-language mappings for two languages is better than one.

Science.gov (United States)

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

2017-12-01

This study extended cross-language semantic decoding (based on a concept's fMRI signature) to the decoding of sentences across three different languages (English, Portuguese and Mandarin). A classifier was trained on either the mapping between words and activation patterns in one language or the mappings in two languages (using an equivalent amount of training data), and then tested on its ability to decode the semantic content of a third language. The model trained on two languages was reliably more accurate than a classifier trained on one language for all three pairs of languages. This two-language advantage was selective to abstract concept domains such as social interactions and mental activity. Representational Similarity Analyses (RSA) of the inter-sentence neural similarities resulted in similar clustering of sentences in all the three languages, indicating a shared neural concept space among languages. These findings identify semantic domains that are common across these three languages versus those that are more language or culture-specific. Copyright © 2017 Elsevier Inc. All rights reserved.

The influence of substrate material on ascidian larval settlement.

Science.gov (United States)

Chase, Anna L; Dijkstra, Jennifer A; Harris, Larry G

2016-05-15

Submerged man-made structures present novel habitat for marine organisms and often host communities that differ from those on natural substrates. Although many factors are known to contribute to these differences, few studies have directly examined the influence of substrate material on organism settlement. We quantified larval substrate preferences of two species of ascidians, Ciona intestinalis (cryptogenic, formerly C. intestinalis type B) and Botrylloides violaceus (non-native), on commonly occurring natural (granite) and man-made (concrete, high-density polyethylene, PVC) marine materials in laboratory trials. Larvae exhibited species-specific settlement preferences, but generally settled more often than expected by chance on concrete and HDPE. Variation in settlement between materials may reflect preferences for rougher substrates, or may result from the influence of leached chemicals on ascidian settlement. These findings indicate that an experimental plate material can influence larval behavior and may help us understand how substrate features may contribute to differences in settlement in the field. Copyright © 2016 Elsevier Ltd. All rights reserved.

Glassy carbon MEMS for novel origami-styled 3D integrated intracortical and epicortical neural probes

Science.gov (United States)

Goshi, Noah; Castagnola, Elisa; Vomero, Maria; Gueli, Calogero; Cea, Claudia; Zucchini, Elena; Bjanes, David; Maggiolini, Emma; Moritz, Chet; Kassegne, Sam; Ricci, Davide; Fadiga, Luciano

2018-06-01

We report on a novel technology for microfabricating 3D origami-styled micro electro-mechanical systems (MEMS) structures with glassy carbon (GC) features and a supporting polymer substrate. GC MEMS devices that open to form 3D microstructures are microfabricated from GC patterns that are made through pyrolysis of polymer precursors on high-temperature resisting substrates like silicon or quartz and then transferring the patterned devices to a flexible substrate like polyimide followed by deposition of an insulation layer. The devices on flexible substrate are then folded into 3D form in an origami-fashion. These 3D MEMS devices have tunable mechanical properties that are achieved by selectively varying the thickness of the polymeric substrate and insulation layers at any desired location. This technology opens new possibilities by enabling microfabrication of a variety of 3D GC MEMS structures suited to applications ranging from biochemical sensing to implantable microelectrode arrays. As a demonstration of the technology, a neural signal recording microelectrode array platform that integrates both surface (cortical) and depth (intracortical) GC microelectrodes onto a single flexible thin-film device is introduced. When the device is unfurled, a pre-shaped shank of polyimide automatically comes off the substrate and forms the penetrating part of the device in a 3D fashion. With the advantage of being highly reproducible and batch-fabricated, the device introduced here allows for simultaneous recording of electrophysiological signals from both the brain surface (electrocorticography—ECoG) and depth (single neuron). Our device, therefore, has the potential to elucidate the roles of underlying neurons on the different components of µECoG signals. For in vivo validation of the design capabilities, the recording sites are coated with a poly(3,4-ethylenedioxythiophene)—polystyrene sulfonate—carbon nanotube composite, to improve the electrical conductivity of the

Neural substrates of levodopa-responsive gait disorders and freezing in advanced Parkinson's disease: a kinesthetic imagery approach

NARCIS (Netherlands)

Maillet, A.; Thobois, S.; Fraix, V.; Redoute, J.; Bars, D. Le; Lavenne, F.; Derost, P.; Durif, F.; Bloem, B.R.; Krack, P.; Pollak, P.; Debu, B.

2015-01-01

Gait disturbances, including freezing of gait, are frequent and disabling symptoms of Parkinson's disease. They often respond poorly to dopaminergic treatments. Although recent studies have shed some light on their neural correlates, their modulation by dopaminergic treatment remains quite unknown.

Disorder generated by interacting neural networks: application to econophysics and cryptography

International Nuclear Information System (INIS)

Kinzel, Wolfgang; Kanter, Ido

2003-01-01

When neural networks are trained on their own output signals they generate disordered time series. In particular, when two neural networks are trained on their mutual output they can synchronize; they relax to a time-dependent state with identical synaptic weights. Two applications of this phenomenon are discussed for (a) econophysics and (b) cryptography. (a) When agents competing in a closed market (minority game) are using neural networks to make their decisions, the total system relaxes to a state of good performance. (b) Two partners communicating over a public channel can find a common secret key

Molecular Modeling of Peroxidase and Polyphenol Oxidase: Substrate Specificity and Active Site Comparison

Directory of Open Access Journals (Sweden)

Lalida Shank

2010-09-01

Full Text Available Peroxidases (POD and polyphenol oxidase (PPO are enzymes that are well known to be involved in the enzymatic browning reaction of fruits and vegetables with different catalytic mechanisms. Both enzymes have some common substrates, but each also has its specific substrates. In our computational study, the amino acid sequence of grape peroxidase (ABX was used for the construction of models employing homology modeling method based on the X-ray structure of cytosolic ascorbate peroxidase from pea (PDB ID:1APX, whereas the model of grape polyphenol oxidase was obtained directly from the available X-ray structure (PDB ID:2P3X. Molecular docking of common substrates of these two enzymes was subsequently studied. It was found that epicatechin and catechin exhibited high affinity with both enzymes, even though POD and PPO have different binding pockets regarding the size and the key amino acids involved in binding. Predicted binding modes of substrates with both enzymes were also compared. The calculated docking interaction energy of trihydroxybenzoic acid related compounds shows high affinity, suggesting specificity and potential use as common inhibitor to grape ascorbate peroxidase and polyphenol oxidase.

Affective neural response to restricted interests in autism spectrum disorders.

Science.gov (United States)

Cascio, Carissa J; Foss-Feig, Jennifer H; Heacock, Jessica; Schauder, Kimberly B; Loring, Whitney A; Rogers, Baxter P; Pryweller, Jennifer R; Newsom, Cassandra R; Cockhren, Jurnell; Cao, Aize; Bolton, Scott

2014-01-01

Restricted interests are a class of repetitive behavior in autism spectrum disorders (ASD) whose intensity and narrow focus often contribute to significant interference with daily functioning. While numerous neuroimaging studies have investigated executive circuits as putative neural substrates of repetitive behavior, recent work implicates affective neural circuits in restricted interests. We sought to explore the role of affective neural circuits and determine how restricted interests are distinguished from hobbies or interests in typical development. We compared a group of children with ASD to a typically developing (TD) group of children with strong interests or hobbies, employing parent report, an operant behavioral task, and functional imaging with personalized stimuli based on individual interests. While performance on the operant task was similar between the two groups, parent report of intensity and interference of interests was significantly higher in the ASD group. Both the ASD and TD groups showed increased BOLD response in widespread affective neural regions to the pictures of their own interest. When viewing pictures of other children's interests, the TD group showed a similar pattern, whereas BOLD response in the ASD group was much more limited. Increased BOLD response in the insula and anterior cingulate cortex distinguished the ASD from the TD group, and parent report of the intensity and interference with daily life of the child's restricted interest predicted insula response. While affective neural network response and operant behavior are comparable in typical and restricted interests, the narrowness of focus that clinically distinguishes restricted interests in ASD is reflected in more interference in daily life and aberrantly enhanced insula and anterior cingulate response to individuals' own interests in the ASD group. These results further support the involvement of affective neural networks in repetitive behaviors in ASD. © 2013 The

Implementation of neural networks on 'Connection Machine'

International Nuclear Information System (INIS)

Belmonte, Ghislain

1990-12-01

This report is a first approach to the notion of neural networks and their possible applications within the framework of artificial intelligence activities of the Department of Applied Mathematics of the Limeil-Valenton Research Center. The first part is an introduction to the field of neural networks; the main neural network models are described in this section. The applications of neural networks in the field of classification have mainly been studied because they could more particularly help to solve some of the decision support problems dealt with by the C.E.A. As the neural networks perform a large number of parallel operations, it was therefore logical to use a parallel architecture computer: the Connection Machine (which uses 16384 processors and is located at E.T.C.A. Arcueil). The second part presents some generalities on the parallelism and the Connection Machine, and two implementations of neural networks on Connection Machine. The first of these implementations concerns one of the most used algorithms to realize the learning of neural networks: the Gradient Retro-propagation algorithm. The second one, less common, concerns a network of neurons destined mainly to the recognition of forms: the Fukushima Neocognitron. The latter is studied by the C.E.A. of Bruyeres-le-Chatel in order to realize an embedded system (including hardened circuits) for the fast recognition of forms [fr

Aligned nanowire growth using lithography-assisted bonding of a polycarbonate template for neural probe electrodes

International Nuclear Information System (INIS)

Yoon, Hargsoon; Deshpande, Devesh C; Ramachandran, Vasuda; Varadan, Vijay K

2008-01-01

This research presents a fabrication method of vertically aligned nanowires on substrates using lithography-assisted template bonding (LATB) towards developing highly efficient electrodes for biomedical applications at low cost. A polycarbonate template containing cylindrical nanopores is attached to a substrate and the nanopores are selectively opened with a modified lithography process. Vertically aligned nanowires are grown by electrochemical deposition through these open pores on polyimide film and silicon substrates. The process of opening the nanopores is optimized to yield uniform growth of nanowires. The morphological, crystalline, and electrochemical properties of the resulting vertically aligned nanowires are discussed using scanning electron microscopy (SEM), x-ray diffraction (XRD), and electrochemical analysis tools. The potential application of this simple and inexpensive fabrication technology is discussed in the development of neural probe electrodes

Supervised neural network modeling: an empirical investigation into learning from imbalanced data with labeling errors.

Science.gov (United States)

Khoshgoftaar, Taghi M; Van Hulse, Jason; Napolitano, Amri

2010-05-01

Neural network algorithms such as multilayer perceptrons (MLPs) and radial basis function networks (RBFNets) have been used to construct learners which exhibit strong predictive performance. Two data related issues that can have a detrimental impact on supervised learning initiatives are class imbalance and labeling errors (or class noise). Imbalanced data can make it more difficult for the neural network learning algorithms to distinguish between examples of the various classes, and class noise can lead to the formulation of incorrect hypotheses. Both class imbalance and labeling errors are pervasive problems encountered in a wide variety of application domains. Many studies have been performed to investigate these problems in isolation, but few have focused on their combined effects. This study presents a comprehensive empirical investigation using neural network algorithms to learn from imbalanced data with labeling errors. In particular, the first component of our study investigates the impact of class noise and class imbalance on two common neural network learning algorithms, while the second component considers the ability of data sampling (which is commonly used to address the issue of class imbalance) to improve their performances. Our results, for which over two million models were trained and evaluated, show that conclusions drawn using the more commonly studied C4.5 classifier may not apply when using neural networks.

A comparison of supervised classification methods for the prediction of substrate type using multibeam acoustic and legacy grain-size data.

Directory of Open Access Journals (Sweden)

David Stephens

Full Text Available Detailed seabed substrate maps are increasingly in demand for effective planning and management of marine ecosystems and resources. It has become common to use remotely sensed multibeam echosounder data in the form of bathymetry and acoustic backscatter in conjunction with ground-truth sampling data to inform the mapping of seabed substrates. Whilst, until recently, such data sets have typically been classified by expert interpretation, it is now obvious that more objective, faster and repeatable methods of seabed classification are required. This study compares the performances of a range of supervised classification techniques for predicting substrate type from multibeam echosounder data. The study area is located in the North Sea, off the north-east coast of England. A total of 258 ground-truth samples were classified into four substrate classes. Multibeam bathymetry and backscatter data, and a range of secondary features derived from these datasets were used in this study. Six supervised classification techniques were tested: Classification Trees, Support Vector Machines, k-Nearest Neighbour, Neural Networks, Random Forest and Naive Bayes. Each classifier was trained multiple times using different input features, including i the two primary features of bathymetry and backscatter, ii a subset of the features chosen by a feature selection process and iii all of the input features. The predictive performances of the models were validated using a separate test set of ground-truth samples. The statistical significance of model performances relative to a simple baseline model (Nearest Neighbour predictions on bathymetry and backscatter were tested to assess the benefits of using more sophisticated approaches. The best performing models were tree based methods and Naive Bayes which achieved accuracies of around 0.8 and kappa coefficients of up to 0.5 on the test set. The models that used all input features didn't generally perform well

Improving the Robustness of Deep Neural Networks via Stability Training

OpenAIRE

Zheng, Stephan; Song, Yang; Leung, Thomas; Goodfellow, Ian

2016-01-01

In this paper we address the issue of output instability of deep neural networks: small perturbations in the visual input can significantly distort the feature embeddings and output of a neural network. Such instability affects many deep architectures with state-of-the-art performance on a wide range of computer vision tasks. We present a general stability training method to stabilize deep networks against small input distortions that result from various types of common image processing, such...

Hearing loss impacts neural alpha oscillations under adverse listening conditions

OpenAIRE

Petersen, Eline B.; Wöstmann, Malte; Obleser, Jonas; Stenfelt, Stefan; Lunner, Thomas

2015-01-01

Degradations in external, acoustic stimulation have long been suspected to increase the load on working memory (WM). One neural signature of WM load is enhanced power of alpha oscillations (6–12 Hz). However, it is unknown to what extent common internal, auditory degradation, that is, hearing impairment, affects the neural mechanisms of WM when audibility has been ensured via amplification. Using an adapted auditory Sternberg paradigm, we varied the orthogonal factors memory load and backgrou...

Dissociation between the neural correlates of conscious face perception and visual attention.

Science.gov (United States)

Navajas, Joaquin; Nitka, Aleksander W; Quian Quiroga, Rodrigo

2017-08-01

Given the higher chance to recognize attended compared to unattended stimuli, the specific neural correlates of these two processes, attention and awareness, tend to be intermingled in experimental designs. In this study, we dissociated the neural correlates of conscious face perception from the effects of visual attention. To do this, we presented faces at the threshold of awareness and manipulated attention through the use of exogenous prestimulus cues. We show that the N170 component, a scalp EEG marker of face perception, was modulated independently by attention and by awareness. An earlier P1 component was not modulated by either of the two effects and a later P3 component was indicative of awareness but not of attention. These claims are supported by converging evidence from (a) modulations observed in the average evoked potentials, (b) correlations between neural and behavioral data at the single-subject level, and (c) single-trial analyses. Overall, our results show a clear dissociation between the neural substrates of attention and awareness. Based on these results, we argue that conscious face perception is triggered by a boost in face-selective cortical ensembles that can be modulated by, but are still independent from, visual attention. © 2017 Society for Psychophysiological Research.

Visualising substrate-fingermark interactions: Solid-state NMR spectroscopy of amino acid reagent development on cellulose substrates.

Science.gov (United States)

Spindler, Xanthe; Shimmon, Ronald; Roux, Claude; Lennard, Chris

2015-05-01

Most spectroscopic studies of the reaction products formed by ninhydrin, 1,2-indanedione-zinc (Ind-Zn) and 1,8-diazafluoren-9-one (DFO) when reacted with amino acids or latent fingermarks on paper substrates are focused on visible absorption or luminescence spectroscopy. In addition, structural elucidation studies are typically limited to solution-based mass spectrometry or liquid nuclear magnetic resonance (NMR) spectroscopy, which does not provide an accurate representation of the fingermark development process on common paper substrates. The research presented in this article demonstrates that solid-state carbon-13 magic angle spinning NMR ((13)C-MAS-NMR) is a technique that can not only be utilised for structural studies of fingermark enhancement reagents, but is a promising technique for characterising the effect of paper chemistry on fingermark deposition and enhancement. The latter opens up a research area that has been under-explored to date but has the potential to improve our understanding of how fingermark secretions and enhancement reagents interact with paper substrates. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Neural networks and its application in biomedical engineering

International Nuclear Information System (INIS)

Husnain, S.K.; Bhatti, M.I.

2002-01-01

Artificial network (ANNs) is an information processing system that has certain performance characteristics in common with biological neural networks. A neural network is characterized by connections between the neurons, method of determining the weights on the connections and its activation functions while a biological neuron has three types of components that are of particular interest in understanding an artificial neuron: its dendrites, soma, and axon. The actin of the chemical transmitter modifies the incoming signal. The study of neural networks is an extremely interdisciplinary field. Computer-based diagnosis is an increasingly used method that tries to improve the quality of health care. Systems on Neural Networks have been developed extensively in the last ten years with the hope that medical diagnosis and therefore medical care would improve dramatically. The addition of a symbolic processing layer enhances the ANNs in a number of ways. It is, for instance, possible to supplement a network that is purely diagnostic with a level that recommends or nodes in order to more closely simulate the nervous system. (author)

Neural Alterations in Acquired Age-Related Hearing Loss

Directory of Open Access Journals (Sweden)

Raksha Anand Mudar

2016-06-01

Full Text Available Hearing loss is one of the most prevalent chronic health conditions in older adults. Growing evidence suggests that hearing loss is associated with reduced cognitive functioning and incident dementia. In this mini-review, we briefly examine literature on anatomical and functional alterations in the brains of adults with acquired age-associated hearing loss, which may underlie the cognitive consequences observed in this population, focusing on studies that have used structural and functional magnetic resonance imaging, diffusion tensor imaging, and event-related electroencephalography. We discuss structural and functional alterations observed in the temporal and frontal cortices and the limbic system. These neural alterations are discussed in the context of common cause, information-degradation, and sensory-deprivation hypotheses, and we suggest possible rehabilitation strategies. Although we are beginning to learn more about changes in neural architecture and functionality related to age-associated hearing loss, much work remains to be done. Understanding the neural alterations will provide objective markers for early identification of neural consequences of age-associated hearing loss and for evaluating benefits of intervention approaches.

Discrete Neural Correlates for the Recognition of Negative Emotions: Insights from Frontotemporal Dementia

Science.gov (United States)

Kumfor, Fiona; Irish, Muireann; Hodges, John R.; Piguet, Olivier

2013-01-01

Patients with frontotemporal dementia have pervasive changes in emotion recognition and social cognition, yet the neural changes underlying these emotion processing deficits remain unclear. The multimodal system model of emotion proposes that basic emotions are dependent on distinct brain regions, which undergo significant pathological changes in frontotemporal dementia. As such, this syndrome may provide important insight into the impact of neural network degeneration upon the innate ability to recognise emotions. This study used voxel-based morphometry to identify discrete neural correlates involved in the recognition of basic emotions (anger, disgust, fear, sadness, surprise and happiness) in frontotemporal dementia. Forty frontotemporal dementia patients (18 behavioural-variant, 11 semantic dementia, 11 progressive nonfluent aphasia) and 27 healthy controls were tested on two facial emotion recognition tasks: The Ekman 60 and Ekman Caricatures. Although each frontotemporal dementia group showed impaired recognition of negative emotions, distinct associations between emotion-specific task performance and changes in grey matter intensity emerged. Fear recognition was associated with the right amygdala; disgust recognition with the left insula; anger recognition with the left middle and superior temporal gyrus; and sadness recognition with the left subcallosal cingulate, indicating that discrete neural substrates are necessary for emotion recognition in frontotemporal dementia. The erosion of emotion-specific neural networks in neurodegenerative disorders may produce distinct profiles of performance that are relevant to understanding the neurobiological basis of emotion processing. PMID:23805313

Development and oviposition preference of house flies and stable flies (Diptera: Muscidae) in six substrates from Florida equine facilities

Science.gov (United States)

House flies, Musca domestica L., and stable flies, Stomoxys calcitrans (L.), (Diptera: Muscidae), common pests on equine facilities, were studied in the laboratory to determine their oviposition preferences and larval development on six substrates commonly found on equine facilities. The substrates...

Integrated evolutionary computation neural network quality controller for automated systems

Energy Technology Data Exchange (ETDEWEB)

Patro, S.; Kolarik, W.J. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Industrial Engineering

1999-06-01

With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time.

Neural Cell Chip Based Electrochemical Detection of Nanotoxicity.

Science.gov (United States)

Kafi, Md Abdul; Cho, Hyeon-Yeol; Choi, Jeong Woo

2015-07-02

Development of a rapid, sensitive and cost-effective method for toxicity assessment of commonly used nanoparticles is urgently needed for the sustainable development of nanotechnology. A neural cell with high sensitivity and conductivity has become a potential candidate for a cell chip to investigate toxicity of environmental influences. A neural cell immobilized on a conductive surface has become a potential tool for the assessment of nanotoxicity based on electrochemical methods. The effective electrochemical monitoring largely depends on the adequate attachment of a neural cell on the chip surfaces. Recently, establishment of integrin receptor specific ligand molecules arginine-glycine-aspartic acid (RGD) or its several modifications RGD-Multi Armed Peptide terminated with cysteine (RGD-MAP-C), C(RGD)₄ ensure farm attachment of neural cell on the electrode surfaces either in their two dimensional (dot) or three dimensional (rod or pillar) like nano-scale arrangement. A three dimensional RGD modified electrode surface has been proven to be more suitable for cell adhesion, proliferation, differentiation as well as electrochemical measurement. This review discusses fabrication as well as electrochemical measurements of neural cell chip with particular emphasis on their use for nanotoxicity assessments sequentially since inception to date. Successful monitoring of quantum dot (QD), graphene oxide (GO) and cosmetic compound toxicity using the newly developed neural cell chip were discussed here as a case study. This review recommended that a neural cell chip established on a nanostructured ligand modified conductive surface can be a potential tool for the toxicity assessments of newly developed nanomaterials prior to their use on biology or biomedical technologies.

Neural Cell Chip Based Electrochemical Detection of Nanotoxicity

Directory of Open Access Journals (Sweden)

Md. Abdul Kafi

2015-07-01

Full Text Available Development of a rapid, sensitive and cost-effective method for toxicity assessment of commonly used nanoparticles is urgently needed for the sustainable development of nanotechnology. A neural cell with high sensitivity and conductivity has become a potential candidate for a cell chip to investigate toxicity of environmental influences. A neural cell immobilized on a conductive surface has become a potential tool for the assessment of nanotoxicity based on electrochemical methods. The effective electrochemical monitoring largely depends on the adequate attachment of a neural cell on the chip surfaces. Recently, establishment of integrin receptor specific ligand molecules arginine-glycine-aspartic acid (RGD or its several modifications RGD-Multi Armed Peptide terminated with cysteine (RGD-MAP-C, C(RGD4 ensure farm attachment of neural cell on the electrode surfaces either in their two dimensional (dot or three dimensional (rod or pillar like nano-scale arrangement. A three dimensional RGD modified electrode surface has been proven to be more suitable for cell adhesion, proliferation, differentiation as well as electrochemical measurement. This review discusses fabrication as well as electrochemical measurements of neural cell chip with particular emphasis on their use for nanotoxicity assessments sequentially since inception to date. Successful monitoring of quantum dot (QD, graphene oxide (GO and cosmetic compound toxicity using the newly developed neural cell chip were discussed here as a case study. This review recommended that a neural cell chip established on a nanostructured ligand modified conductive surface can be a potential tool for the toxicity assessments of newly developed nanomaterials prior to their use on biology or biomedical technologies.

Similar patterns of neural activity predict memory function during encoding and retrieval.

Science.gov (United States)

Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural Correlates of Single- and Dual-Task Walking in the Real World

Directory of Open Access Journals (Sweden)

Sara Pizzamiglio

2017-09-01

Full Text Available Recent developments in mobile brain-body imaging (MoBI technologies have enabled studies of human locomotion where subjects are able to move freely in more ecologically valid scenarios. In this study, MoBI was employed to describe the behavioral and neurophysiological aspects of three different commonly occurring walking conditions in healthy adults. The experimental conditions were self-paced walking, walking while conversing with a friend and lastly walking while texting with a smartphone. We hypothesized that gait performance would decrease with increased cognitive demands and that condition-specific neural activation would involve condition-specific brain areas. Gait kinematics and high density electroencephalography (EEG were recorded whilst walking around a university campus. Conditions with dual tasks were accompanied by decreased gait performance. Walking while conversing was associated with an increase of theta (θ and beta (β neural power in electrodes located over left-frontal and right parietal regions, whereas walking while texting was associated with a decrease of β neural power in a cluster of electrodes over the frontal-premotor and sensorimotor cortices when compared to walking whilst conversing. In conclusion, the behavioral “signatures” of common real-life activities performed outside the laboratory environment were accompanied by differing frequency-specific neural “biomarkers”. The current findings encourage the study of the neural biomarkers of disrupted gait control in neurologically impaired patients.

Potential Mechanisms and Functions of Intermittent Neural Synchronization

Directory of Open Access Journals (Sweden)

Sungwoo Ahn

2017-05-01

Full Text Available Neural synchronization is believed to play an important role in different brain functions. Synchrony in cortical and subcortical circuits is frequently variable in time and not perfect. Few long intervals of desynchronized dynamics may be functionally different from many short desynchronized intervals although the average synchrony may be the same. Recent analysis of imperfect synchrony in different neural systems reported one common feature: neural oscillations may go out of synchrony frequently, but primarily for a short time interval. This study explores potential mechanisms and functional advantages of this short desynchronizations dynamics using computational neuroscience techniques. We show that short desynchronizations are exhibited in coupled neurons if their delayed rectifier potassium current has relatively large values of the voltage-dependent activation time-constant. The delayed activation of potassium current is associated with generation of quickly-rising action potential. This “spikiness” is a very general property of neurons. This may explain why very different neural systems exhibit short desynchronization dynamics. We also show how the distribution of desynchronization durations may be independent of the synchronization strength. Finally, we show that short desynchronization dynamics requires weaker synaptic input to reach a pre-set synchrony level. Thus, this dynamics allows for efficient regulation of synchrony and may promote efficient formation of synchronous neural assemblies.

Is synaesthesia more common in autism?

OpenAIRE

Baron-Cohen, Simon; Johnson, Donielle; Asher, Julian; Wheelwright, Sally; Fisher, Simon E; Gregersen, Peter K; Allison, Carrie

2013-01-01

Background Synaesthesia is a neurodevelopmental condition in which a sensation in one modality triggers a perception in a second modality. Autism (shorthand for Autism Spectrum Conditions) is a neurodevelopmental condition involving social-communication disability alongside resistance to change and unusually narrow interests or activities. Whilst on the surface they appear distinct, they have been suggested to share common atypical neural connectivity. Methods In the present study, we carried...

Community structure analysis of rejection sensitive personality profiles: A common neural response to social evaluative threat?

Science.gov (United States)

Kortink, Elise D; Weeda, Wouter D; Crowley, Michael J; Gunther Moor, Bregtje; van der Molen, Melle J W

2018-06-01

Monitoring social threat is essential for maintaining healthy social relationships, and recent studies suggest a neural alarm system that governs our response to social rejection. Frontal-midline theta (4-8 Hz) oscillatory power might act as a neural correlate of this system by being sensitive to unexpected social rejection. Here, we examined whether frontal-midline theta is modulated by individual differences in personality constructs sensitive to social disconnection. In addition, we examined the sensitivity of feedback-related brain potentials (i.e., the feedback-related negativity and P3) to social feedback. Sixty-five undergraduate female participants (mean age = 19.69 years) participated in the Social Judgment Paradigm, a fictitious peer-evaluation task in which participants provided expectancies about being liked/disliked by peer strangers. Thereafter, they received feedback signaling social acceptance/rejection. A community structure analysis was employed to delineate personality profiles in our data. Results provided evidence of two subgroups: one group scored high on attachment-related anxiety and fear of negative evaluation, whereas the other group scored high on attachment-related avoidance and low on fear of negative evaluation. In both groups, unexpected rejection feedback yielded a significant increase in theta power. The feedback-related negativity was sensitive to unexpected feedback, regardless of valence, and was largest for unexpected rejection feedback. The feedback-related P3 was significantly enhanced in response to expected social acceptance feedback. Together, these findings confirm the sensitivity of frontal midline theta oscillations to the processing of social threat, and suggest that this alleged neural alarm system behaves similarly in individuals that differ in personality constructs relevant to social evaluation.

Neural substrate of body size: illusory feeling of shrinking of the waist.

Directory of Open Access Journals (Sweden)

H Henrik Ehrsson

2005-12-01

Full Text Available The perception of the size and shape of one's body (body image is a fundamental aspect of how we experience ourselves. We studied the neural correlates underlying perceived changes in the relative size of body parts by using a perceptual illusion in which participants felt that their waist was shrinking. We scanned the brains of the participants using functional magnetic resonance imaging. We found that activity in the cortices lining the left postcentral sulcus and the anterior part of the intraparietal sulcus reflected the illusion of waist shrinking, and that this activity was correlated with the reported degree of shrinking. These results suggest that the perceived changes in the size and shape of body parts are mediated by hierarchically higher-order somatosensory areas in the parietal cortex. Based on this finding we suggest that relative size of body parts is computed by the integration of more elementary somatic signals from different body segments.

Neural Network-Based Resistance Spot Welding Control and Quality Prediction

Energy Technology Data Exchange (ETDEWEB)

Allen, J.D., Jr.; Ivezic, N.D.; Zacharia, T.

1999-07-10

This paper describes the development and evaluation of neural network-based systems for industrial resistance spot welding process control and weld quality assessment. The developed systems utilize recurrent neural networks for process control and both recurrent networks and static networks for quality prediction. The first section describes a system capable of both welding process control and real-time weld quality assessment, The second describes the development and evaluation of a static neural network-based weld quality assessment system that relied on experimental design to limit the influence of environmental variability. Relevant data analysis methods are also discussed. The weld classifier resulting from the analysis successfldly balances predictive power and simplicity of interpretation. The results presented for both systems demonstrate clearly that neural networks can be employed to address two significant problems common to the resistance spot welding industry, control of the process itself, and non-destructive determination of resulting weld quality.

Neural Basis of Acquired Amusia and Its Recovery after Stroke.

Science.gov (United States)

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

2016-08-24

Although acquired amusia is a relatively common disorder after stroke, its precise neuroanatomical basis is still unknown. To evaluate which brain regions form the neural substrate for acquired amusia and its recovery, we performed a voxel-based lesion-symptom mapping (VLSM) and morphometry (VBM) study with 77 human stroke subjects. Structural MRIs were acquired at acute and 6 month poststroke stages. Amusia and aphasia were behaviorally assessed at acute and 3 month poststroke stages using the Scale and Rhythm subtests of the Montreal Battery of Evaluation of Amusia (MBEA) and language tests. VLSM analyses indicated that amusia was associated with a lesion area comprising the superior temporal gyrus, Heschl's gyrus, insula, and striatum in the right hemisphere, clearly different from the lesion pattern associated with aphasia. Parametric analyses of MBEA Pitch and Rhythm scores showed extensive lesion overlap in the right striatum, as well as in the right Heschl's gyrus and superior temporal gyrus. Lesions associated with Rhythm scores extended more superiorly and posterolaterally. VBM analysis of volume changes from the acute to the 6 month stage showed a clear decrease in gray matter volume in the right superior and middle temporal gyri in nonrecovered amusic patients compared with nonamusic patients. This increased atrophy was more evident in anterior temporal areas in rhythm amusia and in posterior temporal and temporoparietal areas in pitch amusia. Overall, the results implicate right temporal and subcortical regions as the crucial neural substrate for acquired amusia and highlight the importance of different temporal lobe regions for the recovery of amusia after stroke. Lesion studies are essential in uncovering the brain regions causally linked to a given behavior or skill. For music perception ability, previous lesion studies of amusia have been methodologically limited in both spatial accuracy and time domain as well as by small sample sizes, providing

Decoherence and Entanglement Simulation in a Model of Quantum Neural Network Based on Quantum Dots

Directory of Open Access Journals (Sweden)

Altaisky Mikhail V.

2016-01-01

Full Text Available We present the results of the simulation of a quantum neural network based on quantum dots using numerical method of path integral calculation. In the proposed implementation of the quantum neural network using an array of single-electron quantum dots with dipole-dipole interaction, the coherence is shown to survive up to 0.1 nanosecond in time and up to the liquid nitrogen temperature of 77K.We study the quantum correlations between the quantum dots by means of calculation of the entanglement of formation in a pair of quantum dots on the GaAs based substrate with dot size of 100 ÷ 101 nanometer and interdot distance of 101 ÷ 102 nanometers order.

Functional magnetic resonance imaging reveals different neural substrates for the effects of orexin-1 and orexin-2 receptor antagonists.

Directory of Open Access Journals (Sweden)

Alessandro Gozzi

Full Text Available Orexins are neuro-modulatory peptides involved in the control of diverse physiological functions through interaction with two receptors, orexin-1 (OX1R and orexin-2 (OX2R. Recent evidence in pre-clinical models points toward a putative dichotomic role of the two receptors, with OX2R predominantly involved in the regulation of the sleep/wake cycle and arousal, and the OX1R being more specifically involved in reward processing and motivated behaviour. However, the specific neural substrates underlying these distinct processes in the rat brain remain to be elucidated. Here we used functional magnetic resonance imaging (fMRI in the rat to map the modulatory effect of selective OXR blockade on the functional response produced by D-amphetamine, a psychostimulant and arousing drug that stimulates orexigenic activity. OXR blockade was produced by GSK1059865 and JNJ1037049, two novel OX1R and OX2R antagonists with unprecedented selectivity at the counter receptor type. Both drugs inhibited the functional response to D-amphetamine albeit with distinct neuroanatomical patterns: GSK1059865 focally modulated functional responses in striatal terminals, whereas JNJ1037049 induced a widespread pattern of attenuation characterised by a prominent cortical involvement. At the same doses tested in the fMRI study, JNJ1037049 exhibited robust hypnotic properties, while GSK1059865 failed to display significant sleep-promoting effects, but significantly reduced drug-seeking behaviour in cocaine-induced conditioned place preference. Collectively, these findings highlight an essential contribution of the OX2R in modulating cortical activity and arousal, an effect that is consistent with the robust hypnotic effect exhibited by JNJ1037049. The subcortical and striatal pattern observed with GSK1059865 represent a possible neurofunctional correlate for the modulatory role of OX1R in controlling reward-processing and goal-oriented behaviours in the rat.

Conserved gene regulatory module specifies lateral neural borders across bilaterians.

Science.gov (United States)

Li, Yongbin; Zhao, Di; Horie, Takeo; Chen, Geng; Bao, Hongcun; Chen, Siyu; Liu, Weihong; Horie, Ryoko; Liang, Tao; Dong, Biyu; Feng, Qianqian; Tao, Qinghua; Liu, Xiao

2017-08-01

The lateral neural plate border (NPB), the neural part of the vertebrate neural border, is composed of central nervous system (CNS) progenitors and peripheral nervous system (PNS) progenitors. In invertebrates, PNS progenitors are also juxtaposed to the lateral boundary of the CNS. Whether there are conserved molecular mechanisms determining vertebrate and invertebrate lateral neural borders remains unclear. Using single-cell-resolution gene-expression profiling and genetic analysis, we present evidence that orthologs of the NPB specification module specify the invertebrate lateral neural border, which is composed of CNS and PNS progenitors. First, like in vertebrates, the conserved neuroectoderm lateral border specifier Msx/vab-15 specifies lateral neuroblasts in Caenorhabditis elegans Second, orthologs of the vertebrate NPB specification module ( Msx/vab-15 , Pax3/7/pax-3 , and Zic/ref-2 ) are significantly enriched in worm lateral neuroblasts. In addition, like in other bilaterians, the expression domain of Msx/vab-15 is more lateral than those of Pax3/7/pax-3 and Zic/ref- 2 in C. elegans Third, we show that Msx/vab-15 regulates the development of mechanosensory neurons derived from lateral neural progenitors in multiple invertebrate species, including C. elegans , Drosophila melanogaster , and Ciona intestinalis We also identify a novel lateral neural border specifier, ZNF703/tlp-1 , which functions synergistically with Msx/vab- 15 in both C. elegans and Xenopus laevis These data suggest a common origin of the molecular mechanism specifying lateral neural borders across bilaterians.

Power electronics substrate for direct substrate cooling

Science.gov (United States)

Le, Khiet [Mission Viejo, CA; Ward, Terence G [Redondo Beach, CA; Mann, Brooks S [Redondo Beach, CA; Yankoski, Edward P [Corona, CA; Smith, Gregory S [Woodland Hills, CA

2012-05-01

Systems and apparatus are provided for power electronics substrates adapted for direct substrate cooling. A power electronics substrate comprises a first surface configured to have electrical circuitry disposed thereon, a second surface, and a plurality of physical features on the second surface. The physical features are configured to promote a turbulent boundary layer in a coolant impinged upon the second surface.

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.

Neural electrical activity and neural network growth.

Science.gov (United States)

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sequential and parallel image restoration: neural network implementations.

Science.gov (United States)

Figueiredo, M T; Leitao, J N

1994-01-01

Sequential and parallel image restoration algorithms and their implementations on neural networks are proposed. For images degraded by linear blur and contaminated by additive white Gaussian noise, maximum a posteriori (MAP) estimation and regularization theory lead to the same high dimension convex optimization problem. The commonly adopted strategy (in using neural networks for image restoration) is to map the objective function of the optimization problem into the energy of a predefined network, taking advantage of its energy minimization properties. Departing from this approach, we propose neural implementations of iterative minimization algorithms which are first proved to converge. The developed schemes are based on modified Hopfield (1985) networks of graded elements, with both sequential and parallel updating schedules. An algorithm supported on a fully standard Hopfield network (binary elements and zero autoconnections) is also considered. Robustness with respect to finite numerical precision is studied, and examples with real images are presented.

Abnormality Detection in Mammography using Deep Convolutional Neural Networks

OpenAIRE

Xi, Pengcheng; Shu, Chang; Goubran, Rafik

2018-01-01

Breast cancer is the most common cancer in women worldwide. The most common screening technology is mammography. To reduce the cost and workload of radiologists, we propose a computer aided detection approach for classifying and localizing calcifications and masses in mammogram images. To improve on conventional approaches, we apply deep convolutional neural networks (CNN) for automatic feature learning and classifier building. In computer-aided mammography, deep CNN classifiers cannot be tra...

Psychosocial versus physiological stress – meta-analyses on deactivations and activations of the neural correlates of stress reactions

Science.gov (United States)

Kogler, Lydia; Mueller, Veronika I.; Chang, Amy; Eickhoff, Simon B.; Fox, Peter T.; Gur, Ruben C.; Derntl, Birgit

2015-01-01

Stress is present in everyday life in various forms and situations. Two stressors frequently investigated are physiological and psychosocial stress. Besides similar subjective and hormonal responses, it has been suggested that they also share common neural substrates. The current study used activation-likelihood-estimation meta-analysis to test this assumption by integrating results of previous neuroimaging studies on stress processing. Reported results are cluster-level FWE corrected. The inferior frontal gyrus (IFG) and the anterior insula (AI) were the only regions that demonstrated overlapping activation for both stressors. Analysis of physiological stress showed consistent activation of cognitive and affective components of pain processing such as the insula, striatum, or the middle cingulate cortex. Contrarily, analysis across psychosocial stress revealed consistent activation of the right superior temporal gyrus and deactivation of the striatum. Notably, parts of the striatum appeared to be functionally specified: the dorsal striatum was activated in physiological stress, whereas the ventral striatum was deactivated in psychosocial stress. Additional functional connectivity and decoding analyses further characterized this functional heterogeneity and revealed higher associations of the dorsal striatum with motor regions and of the ventral striatum with reward processing. Based on our meta-analytic approach, activation of the IFG and the AI seems to indicate a global neural stress reaction. While physiological stress activates a motoric fight-or-flight reaction, during psychosocial stress attention is shifted towards emotion regulation and goal-directed behavior, and reward processing is reduced. Our results show the significance of differentiating physiological and psychosocial stress in neural engagement. Furthermore, the assessment of deactivations in addition to activations in stress research is highly recommended. PMID:26123376

The COP9 signalosome converts temporal hormone signaling to spatial restriction on neural competence.

Directory of Open Access Journals (Sweden)

Yi-Chun Huang

2014-11-01

Full Text Available During development, neural competence is conferred and maintained by integrating spatial and temporal regulations. The Drosophila sensory bristles that detect mechanical and chemical stimulations are arranged in stereotypical positions. The anterior wing margin (AWM is arrayed with neuron-innervated sensory bristles, while posterior wing margin (PWM bristles are non-innervated. We found that the COP9 signalosome (CSN suppresses the neural competence of non-innervated bristles at the PWM. In CSN mutants, PWM bristles are transformed into neuron-innervated, which is attributed to sustained expression of the neural-determining factor Senseless (Sens. The CSN suppresses Sens through repression of the ecdysone signaling target gene broad (br that encodes the BR-Z1 transcription factor to activate sens expression. Strikingly, CSN suppression of BR-Z1 is initiated at the prepupa-to-pupa transition, leading to Sens downregulation, and termination of the neural competence of PWM bristles. The role of ecdysone signaling to repress br after the prepupa-to-pupa transition is distinct from its conventional role in activation, and requires CSN deneddylating activity and multiple cullins, the major substrates of deneddylation. Several CSN subunits physically associate with ecdysone receptors to represses br at the transcriptional level. We propose a model in which nuclear hormone receptors cooperate with the deneddylation machinery to temporally shutdown downstream target gene expression, conferring a spatial restriction on neural competence at the PWM.

Reduced tract integrity of the model for social communication is a neural substrate of social communication deficits in autism spectrum disorder.

Science.gov (United States)

Lo, Yu-Chun; Chen, Yu-Jen; Hsu, Yung-Chin; Tseng, Wen-Yih Isaac; Gau, Susan Shur-Fen

2017-05-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with social communication deficits as one of the core symptoms. Recently, a five-level model for the social communication has been proposed in which white matter tracts corresponding to each level of the model are identified. Given that the model for social communication subserves social language functions, we hypothesized that the tract integrity of the model for social communication may be reduced in ASD, and the reduction may be related to social communication deficits. Sixty-two right-handed boys with ASD and 55 typically developing (TD) boys received clinical evaluations, intelligence tests, the Social Communication Questionnaire (SCQ), and MRI scans. Generalized fractional anisotropy (GFA) was measured by diffusion spectrum imaging to indicate the microstructural integrity of the tracts for each level of the social communication model. Group difference in the tract integrity and its relationship with the SCQ subscales of social communication and social interaction were investigated. We found that the GFA values of the superior longitudinal fasciculus III (SLF III, level 1) and the frontal aslant tracts (FAT, level 2) were decreased in ASD compared to TD. Moreover, the GFA values of the SLF III and the FAT were associated with the social interaction subscale in ASD. The tract integrity of the model for social communication is reduced in ASD, and the reduction is associated with impaired social interaction. Our results support that reduced tract integrity of the model for social communication might be a neural substrate of social communication deficits in ASD. © 2016 Association for Child and Adolescent Mental Health.

Permutation parity machines for neural cryptography.

Science.gov (United States)

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-06-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Permutation parity machines for neural cryptography

International Nuclear Information System (INIS)

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-01-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Applying Gradient Descent in Convolutional Neural Networks

Science.gov (United States)

Cui, Nan

2018-04-01

With the development of the integrated circuit and computer science, people become caring more about solving practical issues via information technologies. Along with that, a new subject called Artificial Intelligent (AI) comes up. One popular research interest of AI is about recognition algorithm. In this paper, one of the most common algorithms, Convolutional Neural Networks (CNNs) will be introduced, for image recognition. Understanding its theory and structure is of great significance for every scholar who is interested in this field. Convolution Neural Network is an artificial neural network which combines the mathematical method of convolution and neural network. The hieratical structure of CNN provides it reliable computer speed and reasonable error rate. The most significant characteristics of CNNs are feature extraction, weight sharing and dimension reduction. Meanwhile, combining with the Back Propagation (BP) mechanism and the Gradient Descent (GD) method, CNNs has the ability to self-study and in-depth learning. Basically, BP provides an opportunity for backwardfeedback for enhancing reliability and GD is used for self-training process. This paper mainly discusses the CNN and the related BP and GD algorithms, including the basic structure and function of CNN, details of each layer, the principles and features of BP and GD, and some examples in practice with a summary in the end.

Shared neural coding for social hierarchy and reward value in primate amygdala.

Science.gov (United States)

Munuera, Jérôme; Rigotti, Mattia; Salzman, C Daniel

2018-03-01

The social brain hypothesis posits that dedicated neural systems process social information. In support of this, neurophysiological data have shown that some brain regions are specialized for representing faces. It remains unknown, however, whether distinct anatomical substrates also represent more complex social variables, such as the hierarchical rank of individuals within a social group. Here we show that the primate amygdala encodes the hierarchical rank of individuals in the same neuronal ensembles that encode the rewards associated with nonsocial stimuli. By contrast, orbitofrontal and anterior cingulate cortices lack strong representations of hierarchical rank while still representing reward values. These results challenge the conventional view that dedicated neural systems process social information. Instead, information about hierarchical rank-which contributes to the assessment of the social value of individuals within a group-is linked in the amygdala to representations of rewards associated with nonsocial stimuli.

Label-Free Raman Hyperspectral Imaging of Single Cells Cultured on Polymer Substrates.

Science.gov (United States)

Sinjab, Faris; Sicilia, Giovanna; Shipp, Dustin W; Marlow, Maria; Notingher, Ioan

2017-12-01

While Raman hyperspectral imaging has been widely used for label-free mapping of biomolecules in cells, these measurements require the cells to be cultured on weakly Raman scattering substrates. However, many applications in biological sciences and engineering require the cells to be cultured on polymer substrates that often generate large Raman scattering signals. Here, we discuss the theoretical limits of the signal-to-noise ratio in the Raman spectra of cells in the presence of polymer signals and how optical aberrations may affect these measurements. We show that Raman spectra of cells cultured on polymer substrates can be obtained using automatic subtraction of the polymer signals and demonstrate the capabilities of these methods in two important applications: tissue engineering and in vitro toxicology screening of drugs. Apart from their scientific and technological importance, these applications are examples of the two most common measurement configurations: (1) cells cultured on an optically thick polymer substrate measured using an immersion/dipping objective; and (2) cells cultured on a transparent polymer substrate and measured using an inverted optical microscope. In these examples, we show that Raman hyperspectral data sets with sufficient quality can be successfully acquired to map the distribution of common biomolecules in cells, such as nucleic acids, proteins, and lipids, as well as detecting the early stages of apoptosis. We also discuss strategies for further improvements that could expand the application of Raman hyperspectral imaging on polymer substrates even further in biomedical sciences and engineering.

Portable Rule Extraction Method for Neural Network Decisions Reasoning

Directory of Open Access Journals (Sweden)

Darius PLIKYNAS

2005-08-01

Full Text Available Neural network (NN methods are sometimes useless in practical applications, because they are not properly tailored to the particular market's needs. We focus thereinafter specifically on financial market applications. NNs have not gained full acceptance here yet. One of the main reasons is the "Black Box" problem (lack of the NN decisions explanatory power. There are though some NN decisions rule extraction methods like decompositional, pedagogical or eclectic, but they suffer from low portability of the rule extraction technique across various neural net architectures, high level of granularity, algorithmic sophistication of the rule extraction technique etc. The authors propose to eliminate some known drawbacks using an innovative extension of the pedagogical approach. The idea is exposed by the use of a widespread MLP neural net (as a common tool in the financial problems' domain and SOM (input data space clusterization. The feedback of both nets' performance is related and targeted through the iteration cycle by achievement of the best matching between the decision space fragments and input data space clusters. Three sets of rules are generated algorithmically or by fuzzy membership functions. Empirical validation of the common financial benchmark problems is conducted with an appropriately prepared software solution.

[Folic acid: Primary prevention of neural tube defects. Literature Review].

Science.gov (United States)

Llamas Centeno, M J; Miguélez Lago, C

2016-03-01

Neural tube defects (NTD) are the most common congenital malformations of the nervous system, they have a multifactorial etiology, are caused by exposure to chemical, physical or biological toxic agents, factors deficiency, diabetes, obesity, hyperthermia, genetic alterations and unknown causes. Some of these factors are associated with malnutrition by interfering with the folic acid metabolic pathway, the vitamin responsible for neural tube closure. Its deficit produce anomalies that can cause abortions, stillbirths or newborn serious injuries that cause disability, impaired quality of life and require expensive treatments to try to alleviate in some way the alterations produced in the embryo. Folic acid deficiency is considered the ultimate cause of the production of neural tube defects, it is clear the reduction in the incidence of Espina Bifida after administration of folic acid before conception, this leads us to want to further study the action of folic acid and its application in the primary prevention of neural tube defects. More than 40 countries have made the fortification of flour with folate, achieving encouraging data of decrease in the prevalence of neural tube defects. This paper attempts to make a literature review, which clarify the current situation and future of the prevention of neural tube defects.

End-to-End Neural Optical Music Recognition of Monophonic Scores

Directory of Open Access Journals (Sweden)

Jorge Calvo-Zaragoza

2018-04-01

Full Text Available Optical Music Recognition is a field of research that investigates how to computationally decode music notation from images. Despite the efforts made so far, there are hardly any complete solutions to the problem. In this work, we study the use of neural networks that work in an end-to-end manner. This is achieved by using a neural model that combines the capabilities of convolutional neural networks, which work on the input image, and recurrent neural networks, which deal with the sequential nature of the problem. Thanks to the use of the the so-called Connectionist Temporal Classification loss function, these models can be directly trained from input images accompanied by their corresponding transcripts into music symbol sequences. We also present the Printed Music Scores dataset, containing more than 80,000 monodic single-staff real scores in common western notation, that is used to train and evaluate the neural approach. In our experiments, it is demonstrated that this formulation can be carried out successfully. Additionally, we study several considerations about the codification of the output musical sequences, the convergence and scalability of the neural models, as well as the ability of this approach to locate symbols in the input score.

Energy Expenditure and Substrate Oxidation in Response to Side-Alternating Whole Body Vibration across Three Commonly-Used Vibration Frequencies.

Directory of Open Access Journals (Sweden)

Elie-Jacques Fares

Full Text Available There is increasing recognition about the importance of enhancing energy expenditure (EE for weight control through increases in low-intensity physical activities comparable with daily life (1.5-4 METS. Whole-body vibration (WBV increases EE modestly and could present both a useful adjuvant for obesity management and tool for metabolic phenotyping. However, it is unclear whether a "dose-response" exists between commonly-used vibration frequencies (VF and EE, nor if WBV influences respiratory quotient (RQ, and hence substrate oxidation. We aimed to investigate the EE-VF and RQ-VF relationships across three different frequencies (30, 40, and 50Hz.EE and RQ were measured in 8 healthy young adults by indirect calorimetry at rest, and subsequently during side-alternating WBV at one of 3 VFs (30, 40, and 50 Hz. Each frequency was assessed over 5 cycles of intermittent WBV (30s vibration/30s rest, separated by 5 min seated rest. During the WBV participants stood on the platform with knees flexed sufficiently to maintain comfort, prevent transmission of vibration to the upper body, and minimise voluntary physical exertion. Repeatability was assessed across 3 separate days in a subset of 4 individuals. In order to assess any sequence/habituation effect, an additional group of 6 men underwent 5 cycles of intermittent WBV (30s vibration/30s rest at 40 Hz, separated by 5 min seated rest.Side-alternating WBV increased EE relative to standing, non-vibration levels (+36%, p<0.001. However, no differences in EE were observed across VFs. Similarly, no effect of VF on RQ was found, nor did WBV alter RQ relative to standing without vibration.No relationship could be demonstrated between EE and VF in the range of 30-50Hz, and substrate oxidation did not change in response to WBV. Furthermore, the thermogenic effect of intermittent WBV, whilst robust, was quantitatively small (<2 METS.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

Science.gov (United States)

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

Common and distinct neural correlates of emotional processing in Bipolar Disorder and Major Depressive Disorder: A voxel-based meta-analysis of functional magnetic resonance imaging studies

International Nuclear Information System (INIS)

Delvecchio, Giuseppe; Frangou, Sophia; Fossati, Philippe; Boyer, Patrice; Brambilla, Paolo; Falkai, Peter; Gruber, Olivier; Hietala, Jarmo; Lawrie, Stephen M.; Martinot, Jean-Luc; McIntosh, Andrew M.; Meisenzahl, Eva

2012-01-01

Neuroimaging studies have consistently shown functional brain abnormalities in patients with Bipolar Disorder (BD) and Major Depressive Disorder (MDD). However, the extent to which these two disorders are associated with similar or distinct neural changes remains unclear. We conducted a systematic review of functional magnetic resonance imaging studies comparing BD and MDD patients to healthy participants using facial affect processing paradigms. Relevant spatial coordinates from twenty original studies were subjected to quantitative Activation Likelihood Estimation meta-analyses based on 168 BD and 189 MDD patients and 344 healthy controls. We identified common and distinct patterns of neural engagement for BD and MDD within the facial affect processing network. Both disorders were associated with increased engagement of limbic regions. Diagnosis-specific differences were observed in cortical, thalamic and striatal regions. Decreased ventro-lateral prefrontal cortical engagement was associated with BD while relative hypo-activation of the sensorimotor cortices was seen in MDD. Increased responsiveness in the thalamus and basal ganglia were associated with BD. These findings were modulated by stimulus valence. These data suggest that whereas limbic over-activation is reported consistently in patients with mood disorders, future research should consider the relevance of a wider network of regions in formulating conceptual models of BD and MDD. (authors)

Networks of neuroblastoma cells on porous silicon substrates reveal a small world topology

KAUST Repository

Marinaro, Giovanni; La Rocca, Rosanna; Toma, Andrea; Barberio, Marianna; Cancedda, Laura; Di Fabrizio, Enzo M.; Decuzzi, Paolo C W; Gentile, Francesco T.

2015-01-01

The human brain is a tightly interweaving network of neural cells where the complexity of the network is given by the large number of its constituents and its architecture. The topological structure of neurons in the brain translates into its increased computational capabilities, low energy consumption, and nondeterministic functions, which differentiate human behavior from artificial computational schemes. In this manuscript, we fabricated porous silicon chips with a small pore size ranging from 8 to 75 nm and large fractal dimensions up to Df ∼ 2.8. In culturing neuroblastoma N2A cells on the described substrates, we found that those cells adhere more firmly to and proliferate on the porous surfaces compared to the conventional nominally flat silicon substrates, which were used as controls. More importantly, we observed that N2A cells on the porous substrates create highly clustered, small world topology patterns. We conjecture that neurons with a similar architecture may elaborate information more efficiently than in random or regular grids. Moreover, we hypothesize that systems of neurons on nano-scale geometry evolve in time to form networks in which the propagation of information is maximized. This journal is

Prior Knowledge about Objects Determines Neural Color Representation in Human Visual Cortex.

Science.gov (United States)

Vandenbroucke, A R E; Fahrenfort, J J; Meuwese, J D I; Scholte, H S; Lamme, V A F

2016-04-01

To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and de Ruiter 2008). Here, we investigated the influence of object knowledge on the neural substrates underlying subjective color vision. In a functional magnetic resonance imaging experiment, human subjects viewed a color that lay midway between red and green (ambiguous with respect to its distance from red and green) presented on either typical red (e.g., tomato), typical green (e.g., clover), or semantically meaningless (nonsense) objects. Using decoding techniques, we could predict whether subjects viewed the ambiguous color on typical red or typical green objects based on the neural response of veridical red and green. This shift of neural response for the ambiguous color did not occur for nonsense objects. The modulation of neural responses was observed in visual areas (V3, V4, VO1, lateral occipital complex) involved in color and object processing, as well as frontal areas. This demonstrates that object memory influences wavelength information relatively early in the human visual system to produce subjective color vision. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Neural Vascular Mechanism for the Cerebral Blood Flow Autoregulation after Hemorrhagic Stroke

Directory of Open Access Journals (Sweden)

Ming Xiao

2017-01-01

Full Text Available During the initial stages of hemorrhagic stroke, including intracerebral hemorrhage and subarachnoid hemorrhage, the reflex mechanisms are activated to protect cerebral perfusion, but secondary dysfunction of cerebral flow autoregulation will eventually reduce global cerebral blood flow and the delivery of metabolic substrates, leading to generalized cerebral ischemia, hypoxia, and ultimately, neuronal cell death. Cerebral blood flow is controlled by various regulatory mechanisms, including prevailing arterial pressure, intracranial pressure, arterial blood gases, neural activity, and metabolic demand. Evoked by the concept of vascular neural network, the unveiled neural vascular mechanism gains more and more attentions. Astrocyte, neuron, pericyte, endothelium, and so forth are formed as a communicate network to regulate with each other as well as the cerebral blood flow. However, the signaling molecules responsible for this communication between these new players and blood vessels are yet to be definitively confirmed. Recent evidence suggested the pivotal role of transcriptional mechanism, including but not limited to miRNA, lncRNA, exosome, and so forth, for the cerebral blood flow autoregulation. In the present review, we sought to summarize the hemodynamic changes and underline neural vascular mechanism for cerebral blood flow autoregulation in stroke-prone state and after hemorrhagic stroke and hopefully provide more systematic and innovative research interests for the pathophysiology and therapeutic strategies of hemorrhagic stroke.

Visual NNet: An Educational ANN's Simulation Environment Reusing Matlab Neural Networks Toolbox

Science.gov (United States)

Garcia-Roselló, Emilio; González-Dacosta, Jacinto; Lado, Maria J.; Méndez, Arturo J.; Garcia Pérez-Schofield, Baltasar; Ferrer, Fátima

2011-01-01

Artificial Neural Networks (ANN's) are nowadays a common subject in different curricula of graduate and postgraduate studies. Due to the complex algorithms involved and the dynamic nature of ANN's, simulation software has been commonly used to teach this subject. This software has usually been developed specifically for learning purposes, because…

Effects of detergent on calcium-activated neutral proteinase (CANP) of neural and non-neural tissues in rat. A comparative study

International Nuclear Information System (INIS)

Banik, N.L.; Chakrabarti, A.K.; Hogan, E.L.

1987-01-01

Homogenates of brain, liver, kidney, heart and skeletal muscle of rat were prepared in 0.32 M-sucrose containing 2 mM EDTA. The CANP activity was assayed using 14 C-azocasein as substrate in 50 mM Tris acetate buffer, pH 7.4, 0.1% Triton X-100 and 5 mM-β-mercaptoethanol, with and without CaCl 2 . Addition to CNS membranes of other non-ionic detergents including sodium deoxycholate, β-D-thiogluco-pyranoside, and cetyltrimethyl-ammonium bromide activated the enzyme to varying extent depending on the detergent concentration. The ionic detergent sodium dodecyl sulfate abolished CANP activity completely in all preparations and this effect could not be reversed by non-ionic detergents. The most interesting feature of the Triton X-100 effect was a ten-fold increase of CNS CANP activity whereas non-neural CANP was not at all induced by Triton. CNS CANP was found mainly in the particulate fraction and only 30% in cytosol. In contrast, non-neural CANP was present mainly in cytosol. These results suggest that the bulk of CANP is membrane bound in CNS and differs from other tissue where it remains cytosolic

Imaging the neural circuitry and chemical control of aggressive motivation

Directory of Open Access Journals (Sweden)

Blanchard D Caroline

2008-11-01

Full Text Available Abstract Background With the advent of functional magnetic resonance imaging (fMRI in awake animals it is possible to resolve patterns of neuronal activity across the entire brain with high spatial and temporal resolution. Synchronized changes in neuronal activity across multiple brain areas can be viewed as functional neuroanatomical circuits coordinating the thoughts, memories and emotions for particular behaviors. To this end, fMRI in conscious rats combined with 3D computational analysis was used to identifying the putative distributed neural circuit involved in aggressive motivation and how this circuit is affected by drugs that block aggressive behavior. Results To trigger aggressive motivation, male rats were presented with their female cage mate plus a novel male intruder in the bore of the magnet during image acquisition. As expected, brain areas previously identified as critical in the organization and expression of aggressive behavior were activated, e.g., lateral hypothalamus, medial basal amygdala. Unexpected was the intense activation of the forebrain cortex and anterior thalamic nuclei. Oral administration of a selective vasopressin V1a receptor antagonist SRX251 or the selective serotonin reuptake inhibitor fluoxetine, drugs that block aggressive behavior, both caused a general suppression of the distributed neural circuit involved in aggressive motivation. However, the effect of SRX251, but not fluoxetine, was specific to aggression as brain activation in response to a novel sexually receptive female was unaffected. Conclusion The putative neural circuit of aggressive motivation identified with fMRI includes neural substrates contributing to emotional expression (i.e. cortical and medial amygdala, BNST, lateral hypothalamus, emotional experience (i.e. hippocampus, forebrain cortex, anterior cingulate, retrosplenial cortex and the anterior thalamic nuclei that bridge the motor and cognitive components of aggressive responding

The common neural bases between sexual desire and love: a multilevel kernel density fMRI analysis.

Science.gov (United States)

Cacioppo, Stephanie; Bianchi-Demicheli, Francesco; Frum, Chris; Pfaus, James G; Lewis, James W

2012-04-01

One of the most difficult dilemmas in relationship science and couple therapy concerns the interaction between sexual desire and love. As two mental states of intense longing for union with others, sexual desire and love are, in fact, often difficult to disentangle from one another. The present review aims to help understand the differences and similarities between these two mental states using a comprehensive statistical meta-analyses of all functional magnetic resonance imaging (fMRI) studies on sexual desire and love. Systematic retrospective review of pertinent neuroimaging literature. Review of published literature on fMRI studies illustrating brain regions associated with love and sexual desire to date. Sexual desire and love not only show differences but also recruit a striking common set of brain areas that mediate somatosensory integration, reward expectation, and social cognition. More precisely, a significant posterior-to-anterior insular pattern appears to track sexual desire and love progressively. This specific pattern of activation suggests that love builds upon a neural circuit for emotions and pleasure, adding regions associated with reward expectancy, habit formation, and feature detection. In particular, the shared activation within the insula, with a posterior-to-anterior pattern, from desire to love, suggests that love grows out of and is a more abstract representation of the pleasant sensorimotor experiences that characterize desire. From these results, one may consider desire and love on a spectrum that evolves from integrative representations of affective visceral sensations to an ultimate representation of feelings incorporating mechanisms of reward expectancy and habit learning. © 2012 International Society for Sexual Medicine.

Neural network classifier of attacks in IP telephony

Science.gov (United States)

Safarik, Jakub; Voznak, Miroslav; Mehic, Miralem; Partila, Pavol; Mikulec, Martin

2014-05-01

Various types of monitoring mechanism allow us to detect and monitor behavior of attackers in VoIP networks. Analysis of detected malicious traffic is crucial for further investigation and hardening the network. This analysis is typically based on statistical methods and the article brings a solution based on neural network. The proposed algorithm is used as a classifier of attacks in a distributed monitoring network of independent honeypot probes. Information about attacks on these honeypots is collected on a centralized server and then classified. This classification is based on different mechanisms. One of them is based on the multilayer perceptron neural network. The article describes inner structure of used neural network and also information about implementation of this network. The learning set for this neural network is based on real attack data collected from IP telephony honeypot called Dionaea. We prepare the learning set from real attack data after collecting, cleaning and aggregation of this information. After proper learning is the neural network capable to classify 6 types of most commonly used VoIP attacks. Using neural network classifier brings more accurate attack classification in a distributed system of honeypots. With this approach is possible to detect malicious behavior in a different part of networks, which are logically or geographically divided and use the information from one network to harden security in other networks. Centralized server for distributed set of nodes serves not only as a collector and classifier of attack data, but also as a mechanism for generating a precaution steps against attacks.

Differential neural network configuration during human path integration

Science.gov (United States)

Arnold, Aiden E. G. F; Burles, Ford; Bray, Signe; Levy, Richard M.; Iaria, Giuseppe

2014-01-01

Path integration is a fundamental skill for navigation in both humans and animals. Despite recent advances in unraveling the neural basis of path integration in animal models, relatively little is known about how path integration operates at a neural level in humans. Previous attempts to characterize the neural mechanisms used by humans to visually path integrate have suggested a central role of the hippocampus in allowing accurate performance, broadly resembling results from animal data. However, in recent years both the central role of the hippocampus and the perspective that animals and humans share similar neural mechanisms for path integration has come into question. The present study uses a data driven analysis to investigate the neural systems engaged during visual path integration in humans, allowing for an unbiased estimate of neural activity across the entire brain. Our results suggest that humans employ common task control, attention and spatial working memory systems across a frontoparietal network during path integration. However, individuals differed in how these systems are configured into functional networks. High performing individuals were found to more broadly express spatial working memory systems in prefrontal cortex, while low performing individuals engaged an allocentric memory system based primarily in the medial occipito-temporal region. These findings suggest that visual path integration in humans over short distances can operate through a spatial working memory system engaging primarily the prefrontal cortex and that the differential configuration of memory systems recruited by task control networks may help explain individual biases in spatial learning strategies. PMID:24808849

Are the neural substrates of memory the final common pathway in posttraumatic stress disorder (PTSD)?

OpenAIRE

Elzinga, B.M.; Bremner, J.D.

2002-01-01

A model for the posttraumatic stress disorder (PTSD) as a disorder of memory is presented drawing both on psychological and neurobiological data. Evidence on intrusive memories and deficits in declarative memory function in PTSD-patients is reviewed in relation to three brain areas that are involved in memory functioning and the stress response: the hippocampus, amygdala, and the prefrontal cortex. Neurobiological studies have shown that the noradrenergic stress-system is involved in enhanced...

Are the neural substrates of memory the final common pathway in posttraumatic stress disorder (PTSD)?

Science.gov (United States)

Elzinga, B M; Bremner, J D

2002-06-01

A model for the posttraumatic stress disorder (PTSD) as a disorder of memory is presented drawing both on psychological and neurobiological data. Evidence on intrusive memories and deficits in declarative memory function in PTSD-patients is reviewed in relation to three brain areas that are involved in memory functioning and the stress response: the hippocampus, amygdala, and the prefrontal cortex. Neurobiological studies have shown that the noradrenergic stress-system is involved in enhanced encoding of emotional memories, sensitization, and fear conditioning, by way of its effects on the amygdala. Chronic stress also affects the hippocampus, a brain area involved in declarative memories, suggesting that hippocampal dysfunction may partly account for the deficits in declarative memory in PTSD-patients. Deficits in the medial prefrontal cortex, a structure that normally inhibits the amygdala, may further enhance the effects of the amygdala, thereby increasing the frequency and intensity of the traumatic memories. Thus, by way of its influence on these brain structures, exposure to severe stress may simultaneously result in strong emotional reactions and in difficulties to recall the emotional event. This model is also relevant for understanding the distinction between declarative and non-declarative memory-functions in processing trauma-related information in PTSD. Implications of our model are reviewed.

Neural Tube Defects, Folic Acid and Methylation

Science.gov (United States)

Imbard, Apolline; Benoist, Jean-François; Blom, Henk J.

2013-01-01

Neural tube defects (NTDs) are common complex congenital malformations resulting from failure of the neural tube closure during embryogenesis. It is established that folic acid supplementation decreases the prevalence of NTDs, which has led to national public health policies regarding folic acid. To date, animal studies have not provided sufficient information to establish the metabolic and/or genomic mechanism(s) underlying human folic acid responsiveness in NTDs. However, several lines of evidence suggest that not only folates but also choline, B12 and methylation metabolisms are involved in NTDs. Decreased B12 vitamin and increased total choline or homocysteine in maternal blood have been shown to be associated with increased NTDs risk. Several polymorphisms of genes involved in these pathways have also been implicated in risk of development of NTDs. This raises the question whether supplementation with B12 vitamin, betaine or other methylation donors in addition to folic acid periconceptional supplementation will further reduce NTD risk. The objective of this article is to review the role of methylation metabolism in the onset of neural tube defects. PMID:24048206

On the origin of reproducible sequential activity in neural circuits

Science.gov (United States)

Afraimovich, V. S.; Zhigulin, V. P.; Rabinovich, M. I.

2004-12-01

Robustness and reproducibility of sequential spatio-temporal responses is an essential feature of many neural circuits in sensory and motor systems of animals. The most common mathematical images of dynamical regimes in neural systems are fixed points, limit cycles, chaotic attractors, and continuous attractors (attractive manifolds of neutrally stable fixed points). These are not suitable for the description of reproducible transient sequential neural dynamics. In this paper we present the concept of a stable heteroclinic sequence (SHS), which is not an attractor. SHS opens the way for understanding and modeling of transient sequential activity in neural circuits. We show that this new mathematical object can be used to describe robust and reproducible sequential neural dynamics. Using the framework of a generalized high-dimensional Lotka-Volterra model, that describes the dynamics of firing rates in an inhibitory network, we present analytical results on the existence of the SHS in the phase space of the network. With the help of numerical simulations we confirm its robustness in presence of noise in spite of the transient nature of the corresponding trajectories. Finally, by referring to several recent neurobiological experiments, we discuss possible applications of this new concept to several problems in neuroscience.

Activity in part of the neural correlates of consciousness reflects integration.

Science.gov (United States)

Eriksson, Johan

2017-10-01

Integration is commonly viewed as a key process for generating conscious experiences. Accordingly, there should be increased activity within the neural correlates of consciousness when demands on integration increase. We used fMRI and "informational masking" to isolate the neural correlates of consciousness and measured how the associated brain activity changed as a function of required integration. Integration was manipulated by comparing the experience of hearing simple reoccurring tones to hearing harmonic tone triplets. The neural correlates of auditory consciousness included superior temporal gyrus, lateral and medial frontal regions, cerebellum, and also parietal cortex. Critically, only activity in left parietal cortex increased significantly as a function of increasing demands on integration. We conclude that integration can explain part of the neural activity associated with the generation conscious experiences, but that much of associated brain activity apparently reflects other processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Morphological neural networks

Energy Technology Data Exchange (ETDEWEB)

Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

1996-12-31

The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

Integration of f-MWCNT Sensor and Printed Circuits on Paper Substrate

OpenAIRE

Xie, Li; Feng, Yi; Mantysalo, Matti; Chen, Qiang; Zheng, Li-Rong

2013-01-01

The integration of sensors endows the packages with intelligence and interactivity. This paper is considered the most suitable substrate of smart packages because it is cost-effective, light, flexible, and recyclable. However, common concern exists regarding the reliability of paper-based system against bending and folding. In this paper, inkjet-printing of silver nanoparticles is used to form circuit pattern as well as interconnections for system integration on paper substrate. A humidity se...

Application of artificial neural networks in analysis of CHF experimental data in round tubes

International Nuclear Information System (INIS)

Huang Yanping; Chen Bingde; Lang Xuemei; Wang Xiaojun; Shan Jianqiang; Jia Dounan

2004-01-01

Artificial neural networks (ANNs) are applied successfully to analyze the critical heat flux (CHF) experimental data from some round tubes in this paper. A set of software adopting artificial neural network method for predicting CHF in round tube and a set of CHF database are gotten. Comparing with common CHF correlations and CHF look-up table, ANN method has stronger ability of allow-wrong and nice robustness. The CHF predicting software adopting artificial neural network technology can improve the predicting accuracy in a wider parameter range, and is easier to update and to use. The artificial neural network method used in this paper can be applied to some similar physical problems. (authors)

Amphioxus and lamprey AP-2 genes: implications for neural crest evolution and migration patterns

Science.gov (United States)

Meulemans, Daniel; Bronner-Fraser, Marianne

2002-01-01

The neural crest is a uniquely vertebrate cell type present in the most basal vertebrates, but not in cephalochordates. We have studied differences in regulation of the neural crest marker AP-2 across two evolutionary transitions: invertebrate to vertebrate, and agnathan to gnathostome. Isolation and comparison of amphioxus, lamprey and axolotl AP-2 reveals its extensive expansion in the vertebrate dorsal neural tube and pharyngeal arches, implying co-option of AP-2 genes by neural crest cells early in vertebrate evolution. Expression in non-neural ectoderm is a conserved feature in amphioxus and vertebrates, suggesting an ancient role for AP-2 genes in this tissue. There is also common expression in subsets of ventrolateral neurons in the anterior neural tube, consistent with a primitive role in brain development. Comparison of AP-2 expression in axolotl and lamprey suggests an elaboration of cranial neural crest patterning in gnathostomes. However, migration of AP-2-expressing neural crest cells medial to the pharyngeal arch mesoderm appears to be a primitive feature retained in all vertebrates. Because AP-2 has essential roles in cranial neural crest differentiation and proliferation, the co-option of AP-2 by neural crest cells in the vertebrate lineage was a potentially crucial event in vertebrate evolution.

The Neural Correlates of Abstract and Concrete Words: Evidence from Brain-Damaged Patients

OpenAIRE

Papagno, Costanza; Martello, Giorgia; Mattavelli, Giulia

2013-01-01

Neuropsychological and activation studies on the neural correlates of abstract and concrete words have produced contrasting results. The present study explores the anatomical substrates of abstract/concrete words in 22 brain-damaged patients with a single vascular lesion either in the right or left hemisphere. One hundred and twenty (60 concrete and 60 abstract) noun triplets were used for a semantic similarity judgment task. We found a significant interaction in word type × group since left ...

Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches.

Science.gov (United States)

Crichton, Gamal; Guo, Yufan; Pyysalo, Sampo; Korhonen, Anna

2018-05-21

Link prediction in biomedical graphs has several important applications including predicting Drug-Target Interactions (DTI), Protein-Protein Interaction (PPI) prediction and Literature-Based Discovery (LBD). It can be done using a classifier to output the probability of link formation between nodes. Recently several works have used neural networks to create node representations which allow rich inputs to neural classifiers. Preliminary works were done on this and report promising results. However they did not use realistic settings like time-slicing, evaluate performances with comprehensive metrics or explain when or why neural network methods outperform. We investigated how inputs from four node representation algorithms affect performance of a neural link predictor on random- and time-sliced biomedical graphs of real-world sizes (∼ 6 million edges) containing information relevant to DTI, PPI and LBD. We compared the performance of the neural link predictor to those of established baselines and report performance across five metrics. In random- and time-sliced experiments when the neural network methods were able to learn good node representations and there was a negligible amount of disconnected nodes, those approaches outperformed the baselines. In the smallest graph (∼ 15,000 edges) and in larger graphs with approximately 14% disconnected nodes, baselines such as Common Neighbours proved a justifiable choice for link prediction. At low recall levels (∼ 0.3) the approaches were mostly equal, but at higher recall levels across all nodes and average performance at individual nodes, neural network approaches were superior. Analysis showed that neural network methods performed well on links between nodes with no previous common neighbours; potentially the most interesting links. Additionally, while neural network methods benefit from large amounts of data, they require considerable amounts of computational resources to utilise them. Our results indicate

Neural Reactivity to Emotional Faces Mediates the Relationship Between Childhood Empathy and Adolescent Prosocial Behavior

Science.gov (United States)

Flournoy, John C.; Pfeifer, Jennifer H.; Moore, William E.; Tackman, Allison; Masten, Carrie L.; Mazziotta, John C.; Iacoboni, Marco; Dapretto, Mirella

2017-01-01

Reactivity to others' emotions can result in empathic concern (EC), an important motivator of prosocial behavior, but can also result in personal distress (PD), which may hinder prosocial behavior. Examining neural substrates of emotional reactivity may elucidate how EC and PD differentially influence prosocial behavior. Participants (N=57) provided measures of EC, PD, prosocial behavior, and neural responses to emotional expressions at age 10 and 13. Initial EC predicted subsequent prosocial behavior. Initial EC and PD predicted subsequent reactivity to emotions in the inferior frontal gyrus (IFG) and inferior parietal lobule, respectively. Activity in the IFG, a region linked to mirror neuron processes, as well as cognitive control and language, mediated the relation between initial EC and subsequent prosocial behavior. PMID:28262939

Buckling Behavior of Substrate Supported Graphene Sheets

Directory of Open Access Journals (Sweden)

Kuijian Yang

2016-01-01

Full Text Available The buckling of graphene sheets on substrates can significantly degrade their performance in materials and devices. Therefore, a systematic investigation on the buckling behavior of monolayer graphene sheet/substrate systems is carried out in this paper by both molecular mechanics simulations and theoretical analysis. From 70 simulation cases of simple-supported graphene sheets with different sizes under uniaxial compression, two different buckling modes are investigated and revealed to be dominated by the graphene size. Especially, for graphene sheets with length larger than 3 nm and width larger than 1.1 nm, the buckling mode depends only on the length/width ratio. Besides, it is revealed that the existence of graphene substrate can increase the critical buckling stress and strain to 4.39 N/m and 1.58%, respectively, which are about 10 times those for free-standing graphene sheets. Moreover, for graphene sheets with common size (longer than 20 nm, both theoretical and simulation results show that the critical buckling stress and strain are dominated only by the adhesive interactions with substrate and independent of the graphene size. Results in this work provide valuable insight and guidelines for the design and application of graphene-derived materials and nano-electromechanical systems.

Railway track circuit fault diagnosis using recurrent neural networks

NARCIS (Netherlands)

de Bruin, T.D.; Verbert, K.A.J.; Babuska, R.

2017-01-01

Timely detection and identification of faults in railway track circuits are crucial for the safety and availability of railway networks. In this paper, the use of the long-short-term memory (LSTM) recurrent neural network is proposed to accomplish these tasks based on the commonly available

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

Neural correlates of depth of strategic reasoning in medial prefrontal cortex

Science.gov (United States)

Coricelli, Giorgio; Nagel, Rosemarie

2009-01-01

We used functional MRI (fMRI) to investigate human mental processes in a competitive interactive setting—the “beauty contest” game. This game is well-suited for investigating whether and how a player's mental processing incorporates the thinking process of others in strategic reasoning. 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. According to this model, high-level reasoners expect the others to behave strategically, whereas low-level reasoners choose based on the expectation that others will choose randomly. The data show that high-level reasoning and a measure of strategic IQ (related to winning in the game) correlate with the neural activity in the medial prefrontal cortex, demonstrating its crucial role in successful mentalizing. This supports a cognitive hierarchy model of human brain and behavior. PMID:19470476

Optogenetic interrogation of neural circuits: technology for probing mammalian brain structures

Science.gov (United States)

Zhang, Feng; Gradinaru, Viviana; Adamantidis, Antoine R; Durand, Remy; Airan, Raag D; de Lecea, Luis; Deisseroth, Karl

2015-01-01

Elucidation of the neural substrates underlying complex animal behaviors depends on precise activity control tools, as well as compatible readout methods. Recent developments in optogenetics have addressed this need, opening up new possibilities for systems neuroscience. Interrogation of even deep neural circuits can be conducted by directly probing the necessity and sufficiency of defined circuit elements with millisecond-scale, cell type-specific optical perturbations, coupled with suitable readouts such as electrophysiology, optical circuit dynamics measures and freely moving behavior in mammals. Here we collect in detail our strategies for delivering microbial opsin genes to deep mammalian brain structures in vivo, along with protocols for integrating the resulting optical control with compatible readouts (electrophysiological, optical and behavioral). The procedures described here, from initial virus preparation to systems-level functional readout, can be completed within 4–5 weeks. Together, these methods may help in providing circuit-level insight into the dynamics underlying complex mammalian behaviors in health and disease. PMID:20203662

Parametric models to relate spike train and LFP dynamics with neural information processing.

Science.gov (United States)

Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan

2012-01-01

Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial

Neural Based Orthogonal Data Fitting The EXIN Neural Networks

CERN Document Server

Cirrincione, Giansalvo

2008-01-01

Written by three leaders in the field of neural based algorithms, Neural Based Orthogonal Data Fitting proposes several neural networks, all endowed with a complete theory which not only explains their behavior, but also compares them with the existing neural and traditional algorithms. The algorithms are studied from different points of view, including: as a differential geometry problem, as a dynamic problem, as a stochastic problem, and as a numerical problem. All algorithms have also been analyzed on real time problems (large dimensional data matrices) and have shown accurate solutions. Wh

Sex differences in the neural substrates of spatial working memory during adolescence are not mediated by endogenous testosterone.

Science.gov (United States)

Alarcón, Gabriela; Cservenka, Anita; Fair, Damien A; Nagel, Bonnie J

2014-12-17

Adolescence is a developmental period characterized by notable changes in behavior, physical attributes, and an increase in endogenous sex steroid hormones, which may impact cognitive functioning. Moreover, sex differences in brain structure are present, leading to differences in neural function and cognition. Here, we examine sex differences in performance and blood oxygen level-dependent (BOLD) activation in a sample of adolescents during a spatial working memory (SWM) task. We also examine whether endogenous testosterone levels mediate differential brain activity between the sexes. Adolescents between ages 10 and 16 years completed a SWM functional magnetic resonance imaging (fMRI) task, and serum hormone levels were assessed within seven days of scanning. While there were no sex differences in task performance (accuracy and reaction time), differences in BOLD response between girls and boys emerged, with girls deactivating brain regions in the default mode network and boys showing increased response in SWM-related brain regions of the frontal cortex. These results suggest that adolescent boys and girls adopted distinct neural strategies, while maintaining spatial cognitive strategies that facilitated comparable cognitive performance of a SWM task. A nonparametric bootstrapping procedure revealed that testosterone did not mediate sex-specific brain activity, suggesting that sex differences in BOLD activation during SWM may be better explained by other factors, such as early organizational effects of sex steroids or environmental influences. Elucidating sex differences in neural function and the influence of gonadal hormones can serve as a basis of comparison for understanding sexually dimorphic neurodevelopment and inform sex-specific psychopathology that emerges in adolescence. Copyright © 2014 Elsevier B.V. All rights reserved.

A review on the neural bases of episodic odor memory: from laboratory-based to autobiographical approaches

Science.gov (United States)

Saive, Anne-Lise; Royet, Jean-Pierre; Plailly, Jane

2014-01-01

Odors are powerful cues that trigger episodic memories. However, in light of the amount of behavioral data describing the characteristics of episodic odor memory, the paucity of information available on the neural substrates of this function is startling. Furthermore, the diversity of experimental paradigms complicates the identification of a generic episodic odor memory network. We conduct a systematic review of the literature depicting the current state of the neural correlates of episodic odor memory in healthy humans by placing a focus on the experimental approaches. Functional neuroimaging data are introduced by a brief characterization of the memory processes investigated. We present and discuss laboratory-based approaches, such as odor recognition and odor associative memory, and autobiographical approaches, such as the evaluation of odor familiarity and odor-evoked autobiographical memory. We then suggest the development of new laboratory-ecological approaches allowing for the controlled encoding and retrieval of specific multidimensional events that could open up new prospects for the comprehension of episodic odor memory and its neural underpinnings. While large conceptual differences distinguish experimental approaches, the overview of the functional neuroimaging findings suggests relatively stable neural correlates of episodic odor memory. PMID:25071494

A review on the neural bases of episodic odor memory: from laboratory-based to autobiographical approaches

Directory of Open Access Journals (Sweden)

Anne-Lise eSaive

2014-07-01

Full Text Available Odors are powerful cues that trigger episodic memories. However, in light of the amount of behavioral data describing the characteristics of episodic odor memory, the paucity of information available on the neural substrates of this function is startling. Furthermore, the diversity of experimental paradigms complicates the identification of a generic episodic odor memory network. We conduct a systematic review of the literature depicting the current state of the neural correlates of episodic odor memory in healthy humans by placing a focus on the experimental approaches. Functional neuroimaging data are introduced by a brief characterization of the memory processes investigated. We present and discuss laboratory-based approaches, such as odor recognition and odor associative memory, and autobiographical approaches, such as the evaluation of odor familiarity and odor-evoked autobiographical memory. We then suggest the development of new laboratory-ecological approaches allowing for the controlled encoding and retrieval of specific multidimensional events that could open up new prospects for the comprehension of episodic odor memory and its neural underpinnings. While large conceptual differences distinguish experimental approaches, the overview of the functional neuroimaging findings suggests relatively stable neural correlates of episodic odor memory.

ATM deficiency results in accumulation of DNA-topoisomerase I covalent intermediates in neural cells.

Directory of Open Access Journals (Sweden)

Meryem Alagoz

Full Text Available Accumulation of peptide-linked DNA breaks contributes to neurodegeration in humans. This is typified by defects in tyrosyl DNA phosphodiesterase 1 (TDP1 and human hereditary ataxia. TDP1 primarily operates at single-strand breaks (SSBs created by oxidative stress or by collision of transcription machinery with topoisomerase I intermediates (Top1-CCs. Cellular and cell-free studies have shown that Top1 at stalled Top1-CCs is first degraded to a small peptide resulting in Top1-SSBs, which are the primary substrates for TDP1. Here we established an assay to directly compare Top1-SSBs and Top1-CCs. We subsequently employed this assay to reveal an increased steady state level of Top1-CCs in neural cells lacking Atm; the protein mutated in ataxia telangiectasia. Our data suggest that the accumulation of endogenous Top1-CCs in Atm-/- neural cells is primarily due to elevated levels of reactive oxygen species. Biochemical purification of Top1-CCs from neural cell extract and the use of Top1 poisons further confirmed a role for Atm during the formation/resolution of Top1-CCs. Finally, we report that global transcription is reduced in Atm-/- neural cells and fails to recover to normal levels following Top1-mediated DNA damage. Together, these data identify a distinct role for ATM during the formation/resolution of neural Top1-CCs and suggest that their accumulation contributes to the neuropathology of ataxia telangiectasia.

DWI-based neural fingerprinting technology: a preliminary study on stroke analysis.

Science.gov (United States)

Ye, Chenfei; Ma, Heather Ting; Wu, Jun; Yang, Pengfei; Chen, Xuhui; Yang, Zhengyi; Ma, Jingbo

2014-01-01

Stroke is a common neural disorder in neurology clinics. Magnetic resonance imaging (MRI) has become an important tool to assess the neural physiological changes under stroke, such as diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Quantitative analysis of MRI images would help medical doctors to localize the stroke area in the diagnosis in terms of structural information and physiological characterization. However, current quantitative approaches can only provide localization of the disorder rather than measure physiological variation of subtypes of ischemic stroke. In the current study, we hypothesize that each kind of neural disorder would have its unique physiological characteristics, which could be reflected by DWI images on different gradients. Based on this hypothesis, a DWI-based neural fingerprinting technology was proposed to classify subtypes of ischemic stroke. The neural fingerprint was constructed by the signal intensity of the region of interest (ROI) on the DWI images under different gradients. The fingerprint derived from the manually drawn ROI could classify the subtypes with accuracy 100%. However, the classification accuracy was worse when using semiautomatic and automatic method in ROI segmentation. The preliminary results showed promising potential of DWI-based neural fingerprinting technology in stroke subtype classification. Further studies will be carried out for enhancing the fingerprinting accuracy and its application in other clinical practices.

Approach to design neural cryptography: a generalized architecture and a heuristic rule.

Science.gov (United States)

Mu, Nankun; Liao, Xiaofeng; Huang, Tingwen

2013-06-01

Neural cryptography, a type of public key exchange protocol, is widely considered as an effective method for sharing a common secret key between two neural networks on public channels. How to design neural cryptography remains a great challenge. In this paper, in order to provide an approach to solve this challenge, a generalized network architecture and a significant heuristic rule are designed. The proposed generic framework is named as tree state classification machine (TSCM), which extends and unifies the existing structures, i.e., tree parity machine (TPM) and tree committee machine (TCM). Furthermore, we carefully study and find that the heuristic rule can improve the security of TSCM-based neural cryptography. Therefore, TSCM and the heuristic rule can guide us to designing a great deal of effective neural cryptography candidates, in which it is possible to achieve the more secure instances. Significantly, in the light of TSCM and the heuristic rule, we further expound that our designed neural cryptography outperforms TPM (the most secure model at present) on security. Finally, a series of numerical simulation experiments are provided to verify validity and applicability of our results.

Detecting atrial fibrillation by deep convolutional neural networks.

Science.gov (United States)

Xia, Yong; Wulan, Naren; Wang, Kuanquan; Zhang, Henggui

2018-02-01

Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning. The short-term Fourier transform (STFT) and stationary wavelet transform (SWT) were used to analyze ECG segments to obtain two-dimensional (2-D) matrix input suitable for deep convolutional neural networks. Then, two different deep convolutional neural network models corresponding to STFT output and SWT output were developed. Our new method did not require detection of P or R peaks, nor feature designs for classification, in contrast to existing algorithms. Finally, the performances of the two models were evaluated and compared with those of existing algorithms. Our proposed method demonstrated favorable performances on ECG segments as short as 5 s. The deep convolutional neural network using input generated by STFT, presented a sensitivity of 98.34%, specificity of 98.24% and accuracy of 98.29%. For the deep convolutional neural network using input generated by SWT, a sensitivity of 98.79%, specificity of 97.87% and accuracy of 98.63% was achieved. The proposed method using deep convolutional neural networks shows high sensitivity, specificity and accuracy, and, therefore, is a valuable tool for AF detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Measures of Coupling between Neural Populations Based on Granger Causality Principle.

Science.gov (United States)

Kaminski, Maciej; Brzezicka, Aneta; Kaminski, Jan; Blinowska, Katarzyna J

2016-01-01

This paper shortly reviews the measures used to estimate neural synchronization in experimental settings. Our focus is on multivariate measures of dependence based on the Granger causality (G-causality) principle, their applications and performance in respect of robustness to noise, volume conduction, common driving, and presence of a "weak node." Application of G-causality measures to EEG, intracranial signals and fMRI time series is addressed. G-causality based measures defined in the frequency domain allow the synchronization between neural populations and the directed propagation of their electrical activity to be determined. The time-varying G-causality based measure Short-time Directed Transfer Function (SDTF) supplies information on the dynamics of synchronization and the organization of neural networks. Inspection of effective connectivity patterns indicates a modular structure of neural networks, with a stronger coupling within modules than between them. The hypothetical plausible mechanism of information processing, suggested by the identified synchronization patterns, is communication between tightly coupled modules intermitted by sparser interactions providing synchronization of distant structures.

Competition and Cooperation in Neural Nets : U.S.-Japan Joint Seminar

CERN Document Server

Arbib, Michael

1982-01-01

The human brain, wi th its hundred billion or more neurons, is both one of the most complex systems known to man and one of the most important. The last decade has seen an explosion of experimental research on the brain, but little theory of neural networks beyond the study of electrical properties of membranes and small neural circuits. Nonetheless, a number of workers in Japan, the United States and elsewhere have begun to contribute to a theory which provides techniques of mathematical analysis and computer simulation to explore properties of neural systems containing immense numbers of neurons. Recently, it has been gradually recognized that rather independent studies of the dynamics of pattern recognition, pattern format::ion, motor control, self-organization, etc. , in neural systems do in fact make use of common methods. We find that a "competition and cooperation" type of interaction plays a fundamental role in parallel information processing in the brain. The present volume brings together 23 papers ...

Constructing general partial differential equations using polynomial and neural networks.

Science.gov (United States)

Zjavka, Ladislav; Pedrycz, Witold

2016-01-01

Sum fraction terms can approximate multi-variable functions on the basis of discrete observations, replacing a partial differential equation definition with polynomial elementary data relation descriptions. Artificial neural networks commonly transform the weighted sum of inputs to describe overall similarity relationships of trained and new testing input patterns. Differential polynomial neural networks form a new class of neural networks, which construct and solve an unknown general partial differential equation of a function of interest with selected substitution relative terms using non-linear multi-variable composite polynomials. The layers of the network generate simple and composite relative substitution terms whose convergent series combinations can describe partial dependent derivative changes of the input variables. This regression is based on trained generalized partial derivative data relations, decomposed into a multi-layer polynomial network structure. The sigmoidal function, commonly used as a nonlinear activation of artificial neurons, may transform some polynomial items together with the parameters with the aim to improve the polynomial derivative term series ability to approximate complicated periodic functions, as simple low order polynomials are not able to fully make up for the complete cycles. The similarity analysis facilitates substitutions for differential equations or can form dimensional units from data samples to describe real-world problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bidirectional Joint Representation Learning with Symmetrical Deep Neural Networks for Multimodal and Crossmodal Applications

OpenAIRE

Vukotic , Vedran; Raymond , Christian; Gravier , Guillaume

2016-01-01

International audience; Common approaches to problems involving multiple modalities (classification, retrieval, hyperlinking, etc.) are early fusion of the initial modalities and crossmodal translation from one modality to the other. Recently, deep neural networks, especially deep autoencoders, have proven promising both for crossmodal translation and for early fusion via multimodal embedding. In this work, we propose a flexible cross-modal deep neural network architecture for multimodal and ...

Bacterial protease uses distinct thermodynamic signatures for substrate recognition.

Science.gov (United States)

Bezerra, Gustavo Arruda; Ohara-Nemoto, Yuko; Cornaciu, Irina; Fedosyuk, Sofiya; Hoffmann, Guillaume; Round, Adam; Márquez, José A; Nemoto, Takayuki K; Djinović-Carugo, Kristina

2017-06-06

Porphyromonas gingivalis and Porphyromonas endodontalis are important bacteria related to periodontitis, the most common chronic inflammatory disease in humans worldwide. Its comorbidity with systemic diseases, such as type 2 diabetes, oral cancers and cardiovascular diseases, continues to generate considerable interest. Surprisingly, these two microorganisms do not ferment carbohydrates; rather they use proteinaceous substrates as carbon and energy sources. However, the underlying biochemical mechanisms of their energy metabolism remain unknown. Here, we show that dipeptidyl peptidase 11 (DPP11), a central metabolic enzyme in these bacteria, undergoes a conformational change upon peptide binding to distinguish substrates from end products. It binds substrates through an entropy-driven process and end products in an enthalpy-driven fashion. We show that increase in protein conformational entropy is the main-driving force for substrate binding via the unfolding of specific regions of the enzyme ("entropy reservoirs"). The relationship between our structural and thermodynamics data yields a distinct model for protein-protein interactions where protein conformational entropy modulates the binding free-energy. Further, our findings provide a framework for the structure-based design of specific DPP11 inhibitors.

Autism as an adaptive common variant pathway for human brain development

Directory of Open Access Journals (Sweden)

Mark H. Johnson

2017-06-01

Full Text Available While research on focal perinatal lesions has provided evidence for recovery of function, much less is known about processes of brain adaptation resulting from mild but widespread disturbances to neural processing over the early years (such as alterations in synaptic efficiency. Rather than being viewed as a direct behavioral consequence of life-long neural dysfunction, I propose that autism is best viewed as the end result of engaging adaptive processes during a sensitive period. From this perspective, autism is not appropriately described as a disorder of neurodevelopment, but rather as an adaptive common variant pathway of human functional brain development.

Predicting physical time series using dynamic ridge polynomial neural networks.

Directory of Open Access Journals (Sweden)

Dhiya Al-Jumeily

Full Text Available Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.

Context-Dependent Neural Modulations in the Perception of Duration.

Science.gov (United States)

Murai, Yuki; Yotsumoto, Yuko

2016-01-01

Recent neuroimaging studies have revealed that distinct brain networks are recruited in the perception of sub- and supra-second timescales, whereas psychophysical studies have suggested that there are common or continuous mechanisms for perceiving these two durations. The present study aimed to elucidate the neural implementation of such continuity by examining the neural correlates of peri-second timing. We measured neural activity during a duration reproduction task using functional magnetic resonance imaging. Our results replicate the findings of previous studies in showing that separate neural networks are recruited for sub-versus supra-second time perception: motor systems including the motor cortex and the supplementary motor area for sub-second perception, and the frontal, parietal, and auditory cortical areas for supra-second perception. We further found that the peri-second perception activated both the sub- and supra-second networks, and that the timing system that processed duration perception in previous trials was more involved in subsequent peri-second processing. These results indicate that the sub- and supra-second timing systems overlap at around 1 s, and cooperate to optimally encode duration based on the hysteresis of previous trials.

Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome.

Science.gov (United States)

Wlodarski, Tomasz; Kutner, Jan; Towpik, Joanna; Knizewski, Lukasz; Rychlewski, Leszek; Kudlicki, Andrzej; Rowicka, Maga; Dziembowski, Andrzej; Ginalski, Krzysztof

2011-01-01

Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity). Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

Comprehensive structural and substrate specificity classification of the Saccharomyces cerevisiae methyltransferome.

Directory of Open Access Journals (Sweden)

Tomasz Wlodarski

Full Text Available Methylation is one of the most common chemical modifications of biologically active molecules and it occurs in all life forms. Its functional role is very diverse and involves many essential cellular processes, such as signal transduction, transcriptional control, biosynthesis, and metabolism. Here, we provide further insight into the enzymatic methylation in S. cerevisiae by conducting a comprehensive structural and functional survey of all the methyltransferases encoded in its genome. Using distant homology detection and fold recognition, we found that the S. cerevisiae methyltransferome comprises 86 MTases (53 well-known and 33 putative with unknown substrate specificity. Structural classification of their catalytic domains shows that these enzymes may adopt nine different folds, the most common being the Rossmann-like. We also analyzed the domain architecture of these proteins and identified several new domain contexts. Interestingly, we found that the majority of MTase genes are periodically expressed during yeast metabolic cycle. This finding, together with calculated isoelectric point, fold assignment and cellular localization, was used to develop a novel approach for predicting substrate specificity. Using this approach, we predicted the general substrates for 24 of 33 putative MTases and confirmed these predictions experimentally in both cases tested. Finally, we show that, in S. cerevisiae, methylation is carried out by 34 RNA MTases, 32 protein MTases, eight small molecule MTases, three lipid MTases, and nine MTases with still unknown substrate specificity.

Neural Markers and Rehabilitation of Executive Functioning in Veterans with TBI and PTSD

Science.gov (United States)

2016-10-01

1 Award Number: W81XWH-11-1-0796 TITLE: Neural Markers and Rehabilitation of Executive Functioning in Veterans with TBI and PTSD PRINCIPAL...30Sept2015 - 29Sept2016 4. TITLE AND SUBTITLE: Neural Markers and Rehabilitation of Executive Functioning in Veterans with TBI and PTSD 5a. CONTRACT... met criteria for TBI during military service, 48.8% of whom reported multiple head injuries. The most common mechanisms of injury included blast

Neural correlates of processing "self-conscious" vs. "basic" emotions.

Science.gov (United States)

Gilead, Michael; Katzir, Maayan; Eyal, Tal; Liberman, Nira

2016-01-29

Self-conscious emotions are prevalent in our daily lives and play an important role in both normal and pathological behavior. Despite their immense significance, the neural substrates that are involved in the processing of such emotions are surprisingly under-studied. In light of this, we conducted an fMRI study in which participants thought of various personal events which elicited feelings of negative and positive self-conscious (i.e., guilt, pride) or basic (i.e., anger, joy) emotions. We performed a conjunction analysis to investigate the neural correlates associated with processing events that are related to self-conscious vs. basic emotions, irrespective of valence. The results show that processing self-conscious emotions resulted in activation within frontal areas associated with self-processing and self-control, namely, the mPFC extending to the dACC, and within the lateral-dorsal prefrontal cortex. Processing basic emotions resulted in activation throughout relatively phylogenetically-ancient regions of the cortex, namely in visual and tactile processing areas and in the insular cortex. Furthermore, self-conscious emotions differentially activated the mPFC such that the negative self-conscious emotion (guilt) was associated with a more dorsal activation, and the positive self-conscious emotion (pride) was associated with a more ventral activation. We discuss how these results shed light on the nature of mental representations and neural systems involved in self-reflective and affective processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural correlates of central inhibition during physical fatigue.

Directory of Open Access Journals (Sweden)

Masaaki Tanaka

Full Text Available Central inhibition plays a pivotal role in determining physical performance during physical fatigue. Classical conditioning of central inhibition is believed to be associated with the pathophysiology of chronic fatigue. We tried to determine whether classical conditioning of central inhibition can really occur and to clarify the neural mechanisms of central inhibition related to classical conditioning during physical fatigue using magnetoencephalography (MEG. Eight right-handed volunteers participated in this study. We used metronome sounds as conditioned stimuli and maximum handgrip trials as unconditioned stimuli to cause central inhibition. Participants underwent MEG recording during imagery of maximum grips of the right hand guided by metronome sounds for 10 min. Thereafter, fatigue-inducing maximum handgrip trials were performed for 10 min; the metronome sounds were started 5 min after the beginning of the handgrip trials. The next day, neural activities during imagery of maximum grips of the right hand guided by metronome sounds were measured for 10 min. Levels of fatigue sensation and sympathetic nerve activity on the second day were significantly higher relative to those of the first day. Equivalent current dipoles (ECDs in the posterior cingulated cortex (PCC, with latencies of approximately 460 ms, were observed in all the participants on the second day, although ECDs were not identified in any of the participants on the first day. We demonstrated that classical conditioning of central inhibition can occur and that the PCC is involved in the neural substrates of central inhibition related to classical conditioning during physical fatigue.

Cracking in thin films of colloidal particles on elastomeric substrates

Science.gov (United States)

Smith, Michael; Sharp, James

2012-02-01

The drying of thin colloidal films of particles is a common industrial problem (e.g paint drying, ceramic coatings). An often undesirable side effect is the appearance of cracks. As the liquid in a suspension evaporates, particles are forced into contact both with each other and the substrate, forming a fully wetted film. Under carefully controlled conditions the observed cracks grow orthogonal to the drying front, spaced at regular intervals along it. In this work we investigated the role of the substrate in constraining the film. Atomic force microscopy, was used to image the particle arrangements on the top and bottom surfaces of films, dried on liquid and glass substrates. We present convincing evidence that the interface prevents particle rearrangements at the bottom of the film, leading to a mismatch strain between upper and lower surfaces of the film which appears to drive cracking. We show that when the modulus of the substrate becomes comparable to the stresses measured in the films, the crack spacing is significantly altered. We also show that cracks do not form on liquid substrates. These combined experiments highlight the importance of substrate constraint in the crack formation mechanism.[4pt] [1] M.I. Smith, J.S. Sharp, Langmuir 27, 8009 (2011)

Determining the Relationship Between Co-creation and Innovation by Neural Networks

DEFF Research Database (Denmark)

di Tollo, Giacomo; Tanev, Stoyan; Slim, Kassis Mohamed

2014-01-01

The growing complexity of markets, business development and administration has fostered the application of more sophisticated quantitative methods aiming at the analysis of common features and differences amongst different businesses. Amongst those quantitative methods, Neural Networks are gainin...

Neural networks

International Nuclear Information System (INIS)

Denby, Bruce; Lindsey, Clark; Lyons, Louis

1992-01-01

The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

Tracing tremor: Neural correlates of essential tremor and its treatment

NARCIS (Netherlands)

Buijink, A.W.G.

2016-01-01

This thesis focusses on the neural correlates and treatment of the neurological movement disorder essential tremor (ET). ET, one of the most common movement disorders in clinical neurology, is characterized by an action and intention tremor of mainly the hands, hampering daily life activities.

Controlling droplet-based deposition uniformity of long silver nanowires by micrometer scale substrate patterning

International Nuclear Information System (INIS)

Basu, Nandita; Cross, Graham L W

2015-01-01

We report control of droplet-deposit uniformity of long silver nanowires suspended in solutions by microscopic influence of the liquid contact line. Substrates with microfabricated line patterns with a pitch far smaller than mean wire length lead to deposit thickness uniformity compared to unpatterned substrates. For high boiling-point solvents, two significant effects were observed: The substrate patterns suppressed coffee ring staining, and the wire deposits exhibited a common orientation lying perpendicular over top the lines. The latter result is completely distinct from previously reported substrate groove channeling effects. This work shows that microscopic influence of the droplet contact line geometry including the contact angle by altered substrate wetting allows significant and advantageous influence of deposition patterns of wire-like solutes as the drop dries. (paper)

Mechanisms of Deformation and Fracture of Thin Coatings on Different Substrates in Instrumented Indentation

Science.gov (United States)

Eremina, G. M.; Smolin, A. Yu.; Psakhie, S. G.

2018-04-01

Mechanical properties of thin surface layers and coatings are commonly studied using instrumented indentation and scratch testing, where the mechanical response of the coating - substrate system essentially depends on the substrate material. It is quite difficult to distinguish this dependence and take it into account in the course of full-scale experiments due to a multivariative and nonlinear character of the influence. In this study the process of instrumented indentation of a hardening coating formed on different substrates is investigated numerically by the method of movable cellular automata. As a result of modeling, we identified the features of the substrate material influence on the derived mechanical characteristics of the coating - substrate systems and the processes of their deformation and fracture.

Modeling of the pyruvate production with Escherichia coli: comparison of mechanistic and neural networks-based models.

Science.gov (United States)

Zelić, B; Bolf, N; Vasić-Racki, D

2006-06-01

Three different models: the unstructured mechanistic black-box model, the input-output neural network-based model and the externally recurrent neural network model were used to describe the pyruvate production process from glucose and acetate using the genetically modified Escherichia coli YYC202 ldhA::Kan strain. The experimental data were used from the recently described batch and fed-batch experiments [ Zelić B, Study of the process development for Escherichia coli-based pyruvate production. PhD Thesis, University of Zagreb, Faculty of Chemical Engineering and Technology, Zagreb, Croatia, July 2003. (In English); Zelić et al. Bioproc Biosyst Eng 26:249-258 (2004); Zelić et al. Eng Life Sci 3:299-305 (2003); Zelić et al Biotechnol Bioeng 85:638-646 (2004)]. The neural networks were built out of the experimental data obtained in the fed-batch pyruvate production experiments with the constant glucose feed rate. The model validation was performed using the experimental results obtained from the batch and fed-batch pyruvate production experiments with the constant acetate feed rate. Dynamics of the substrate and product concentration changes was estimated using two neural network-based models for biomass and pyruvate. It was shown that neural networks could be used for the modeling of complex microbial fermentation processes, even in conditions in which mechanistic unstructured models cannot be applied.

Meninges harbor cells expressing neural precursor markers during development and adulthood.

Science.gov (United States)

Bifari, Francesco; Berton, Valeria; Pino, Annachiara; Kusalo, Marijana; Malpeli, Giorgio; Di Chio, Marzia; Bersan, Emanuela; Amato, Eliana; Scarpa, Aldo; Krampera, Mauro; Fumagalli, Guido; Decimo, Ilaria

2015-01-01

Brain and skull developments are tightly synchronized, allowing the cranial bones to dynamically adapt to the brain shape. At the brain-skull interface, meninges produce the trophic signals necessary for normal corticogenesis and bone development. Meninges harbor different cell populations, including cells forming the endosteum of the cranial vault. Recently, we and other groups have described the presence in meninges of a cell population endowed with neural differentiation potential in vitro and, after transplantation, in vivo. However, whether meninges may be a niche for neural progenitor cells during embryonic development and in adulthood remains to be determined. In this work we provide the first description of the distribution of neural precursor markers in rat meninges during development up to adulthood. We conclude that meninges share common properties with the classical neural stem cell niche, as they: (i) are a highly proliferating tissue; (ii) host cells expressing neural precursor markers such as nestin, vimentin, Sox2 and doublecortin; and (iii) are enriched in extracellular matrix components (e.g., fractones) known to bind and concentrate growth factors. This study underlines the importance of meninges as a potential niche for endogenous precursor cells during development and in adulthood.

Neural substrates of interactive musical improvisation: an FMRI study of 'trading fours' in jazz.

Directory of Open Access Journals (Sweden)

Gabriel F Donnay

Full Text Available Interactive generative musical performance provides a suitable model for communication because, like natural linguistic discourse, it involves an exchange of ideas that is unpredictable, collaborative, and emergent. Here we show that interactive improvisation between two musicians is characterized by activation of perisylvian language areas linked to processing of syntactic elements in music, including inferior frontal gyrus and posterior superior temporal gyrus, and deactivation of angular gyrus and supramarginal gyrus, brain structures directly implicated in semantic processing of language. These findings support the hypothesis that musical discourse engages language areas of the brain specialized for processing of syntax but in a manner that is not contingent upon semantic processing. Therefore, we argue that neural regions for syntactic processing are not domain-specific for language but instead may be domain-general for communication.

Neural substrates of interactive musical improvisation: an FMRI study of 'trading fours' in jazz.

Science.gov (United States)

Donnay, Gabriel F; Rankin, Summer K; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J

2014-01-01

Interactive generative musical performance provides a suitable model for communication because, like natural linguistic discourse, it involves an exchange of ideas that is unpredictable, collaborative, and emergent. Here we show that interactive improvisation between two musicians is characterized by activation of perisylvian language areas linked to processing of syntactic elements in music, including inferior frontal gyrus and posterior superior temporal gyrus, and deactivation of angular gyrus and supramarginal gyrus, brain structures directly implicated in semantic processing of language. These findings support the hypothesis that musical discourse engages language areas of the brain specialized for processing of syntax but in a manner that is not contingent upon semantic processing. Therefore, we argue that neural regions for syntactic processing are not domain-specific for language but instead may be domain-general for communication.

ADAM13 Induces Cranial Neural Crest by Cleaving Class B Ephrins and Regulating Wnt Signaling

Science.gov (United States)

Wei, Shuo; Xu, Guofeng; Bridges, Lance C.; Williams, Phoebe; White, Judith M.; DeSimone, Douglas W.

2010-01-01

SUMMARY The cranial neural crest (CNC) are multipotent embryonic cells that contribute to craniofacial structures and other cells and tissues of the vertebrate head. During embryogenesis, CNC is induced at the neural plate boundary through the interplay of several major signaling pathways. Here we report that the metalloproteinase activity of ADAM13 is required for early induction of CNC in Xenopus. In both cultured cells and X. tropicalis embryos, membrane-bound Ephrins (Efns) B1 and B2 were identified as substrates for ADAM13. ADAM13 upregulates canonical Wnt signaling and early expression of the transcription factor snail2, whereas EfnB1 inhibits the canonical Wnt pathway and snail2 expression. We propose that by cleaving class B Efns, ADAM13 promotes canonical Wnt signaling and early CNC induction. PMID:20708595

The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults.

Science.gov (United States)

Habeck, C; Gazes, Y; Razlighi, Q; Steffener, J; Brickman, A; Barulli, D; Salthouse, T; Stern, Y

2016-01-15

derivation of these networks, we also observed some brain-behavioral correlations, notably for the fluid-reasoning network whose network score correlated with performance on the memory and fluid-reasoning tasks. While age did not influence the expression of this RANN, the slope of the association between network score and fluid-reasoning performance was negatively associated with higher ages. These results provide support for the hypothesis that a set of specific, age-invariant neural networks underlies these four RAs, and that these networks maintain their cognitive specificity and level of intensity across age. Activation common to all 12 tasks was identified as another activation pattern resulting from a mean-contrast Partial-Least-Squares technique. This common pattern did show associations with age and some subject demographics for some of the reference domains, lending support to the overall conclusion that aspects of neural processing that are specific to any cognitive reference ability stay constant across age, while aspects that are common to all reference abilities differ across age. Copyright © 2015 Elsevier Inc. All rights reserved.

Emotional Intent Modulates The Neural Substrates Of Creativity: An fMRI Study of Emotionally Targeted Improvisation in Jazz Musicians.

Science.gov (United States)

McPherson, Malinda J; Barrett, Frederick S; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J

2016-01-04

Emotion is a primary motivator for creative behaviors, yet the interaction between the neural systems involved in creativity and those involved in emotion has not been studied. In the current study, we addressed this gap by using fMRI to examine piano improvisation in response to emotional cues. We showed twelve professional jazz pianists photographs of an actress representing a positive, negative or ambiguous emotion. Using a non-ferromagnetic thirty-five key keyboard, the pianists improvised music that they felt represented the emotion expressed in the photographs. Here we show that activity in prefrontal and other brain networks involved in creativity is highly modulated by emotional context. Furthermore, emotional intent directly modulated functional connectivity of limbic and paralimbic areas such as the amygdala and insula. These findings suggest that emotion and creativity are tightly linked, and that the neural mechanisms underlying creativity may depend on emotional state.

Large-scale Topographical Screen for Investigation of Physical Neural-Guidance Cues

Science.gov (United States)

Li, Wei; Tang, Qing Yuan; Jadhav, Amol D.; Narang, Ankit; Qian, Wei Xian; Shi, Peng; Pang, Stella W.

2015-03-01

A combinatorial approach was used to present primary neurons with a large library of topographical features in the form of micropatterned substrate for high-throughput screening of physical neural-guidance cues that can effectively promote different aspects of neuronal development, including axon and dendritic outgrowth. Notably, the neuronal-guidance capability of specific features was automatically identified using a customized image processing software, thus significantly increasing the screening throughput with minimal subjective bias. Our results indicate that the anisotropic topographies promote axonal and in some cases dendritic extension relative to the isotropic topographies, while dendritic branching showed preference to plain substrates over the microscale features. The results from this work can be readily applied towards engineering novel biomaterials with precise surface topography that can serve as guidance conduits for neuro-regenerative applications. This novel topographical screening strategy combined with the automated processing capability can also be used for high-throughput screening of chemical or genetic regulatory factors in primary neurons.

Artificial Neural Network Model for Predicting Compressive

Directory of Open Access Journals (Sweden)

Salim T. Yousif

2013-05-01

Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

Common and distinct brain networks underlying panic and social anxiety disorders.

Science.gov (United States)

Kim, Yong-Ku; Yoon, Ho-Kyoung

2018-01-03

Although panic disorder (PD) and phobic disorders are independent anxiety disorders with distinct sets of diagnostic criteria, there is a high level of overlap between them in terms of pathogenesis and neural underpinnings. Functional connectivity research using resting-state functional magnetic resonance imaging (rsfMRI) shows great potential in identifying the similarities and differences between PD and phobias. Understanding common and distinct networks between PD and phobic disorders is critical for identifying both specific and general neural characteristics of these disorders. We review recent rsfMRI studies and explore the clinical relevance of resting-state functional connectivity (rsFC) in PD and phobias. Although findings differ between studies, there are some meaningful, consistent findings. Social anxiety disorder (SAD) and PD share common default mode network alterations. Alterations within the sensorimotor network are observed primarily in PD. Increased connectivity in the salience network is consistently reported in SAD. This review supports hypotheses that PD and phobic disorders share common rsFC abnormalities and that the different clinical phenotypes between the disorders come from distinct brain functional network alterations. Copyright © 2017 Elsevier Inc. All rights reserved.

The Neural Substrates of Recognition Memory for Verbal Information: Spanning the Divide between Short- and Long-Term Memory

Science.gov (United States)

Buchsbaum, Bradley R.; Padmanabhan, Aarthi; Berman, Karen Faith

2011-01-01

One of the classic categorical divisions in the history of memory research is that between short-term and long-term memory. Indeed, because memory for the immediate past (a few seconds) and memory for the relatively more remote past (several seconds and beyond) are assumed to rely on distinct neural systems, more often than not, memory research…

Phytochemicals for taming agitated immune-endocrine-neural axis.

Science.gov (United States)

Patel, Seema

2017-07-01

Homeostasis of immune-endocrine-neural axis is paramount for human health. If this axis gets agitated due to age, genetic variations, environmental exposures or lifestyle assaults, a cascade of adverse reactions occurs in human body. Cytokines, hormones and neurotransmitters, the effector molecules of this axis behave erratically, leading to a gamut of neural, endocrine, autoimmune, and metabolic diseases. Current panel of drugs can tackle some of them but not in a sustainable, benign way as a myriad of side effects, causal of them have been documented. In this context, phytochemicals, the secondary metabolites of plants seem beneficial. These bioactive constituents encompassing polyphenols, alkaloids, flavonoids, terpenoids, tannins, lignans, stilbenoids (resveratrol), saponins, polysaccharides, glycosides, and lectins etc. have been proven to exert antioxidant, anti-inflammatory, hypolipidemic, hypotensive, antidiabetic, anticancer, immunomodulatory, anti-allergic, analgesic, hepatoprotective, neuroprotective, dermatoprotective, and antimicrobial properties, among a litany of other biological effects. This review presents a holistic perspective of common afflictions resultant of immune-endocrine-neural axis disruption, and the phytochemicals capable of restoring their normalcy and mitigating the ailments. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Prevalence of neural tube defect and hydrocephalus in Northern ...

African Journals Online (AJOL)

All the cases reported in this study were open neural tube defect (NTD). The most common defect was hydrocephalus occurring in 33 patients representing 57.9%, with spinal bifida occurring in 21 patients representing 38.6%. Encephalocele or cranium bifida occurred in only 5.3% (3 patients). Among the spinal bifida cases ...

In situ X-ray scattering of perovskite solar cell active layers roll-to-roll coated on flexible substrates

DEFF Research Database (Denmark)

Rossander, Lea Hildebrandt; Larsen-Olsen, Thue T.; Dam, Henrik Friis

2016-01-01

crystallographic developments between the substrates, especially seen through the behaviour of a crystalline precursor which survived longer on the flexible substrates than on glass. Additionally, the common degradation product PbI2 was absent on the thickest flexible substrate. This leads us to conjecture...

Evaluation of common genetic variants in 82 candidate genes as risk factors for neural tube defects

LENUS (Irish Health Repository)

Pangilinan, Faith

2012-08-02

AbstractBackgroundNeural tube defects (NTDs) are common birth defects (~1 in 1000 pregnancies in the US and Europe) that have complex origins, including environmental and genetic factors. A low level of maternal folate is one well-established risk factor, with maternal periconceptional folic acid supplementation reducing the occurrence of NTD pregnancies by 50-70%. Gene variants in the folate metabolic pathway (e.g., MTHFR rs1801133 (677 C > T) and MTHFD1 rs2236225 (R653Q)) have been found to increase NTD risk. We hypothesized that variants in additional folate\\/B12 pathway genes contribute to NTD risk.MethodsA tagSNP approach was used to screen common variation in 82 candidate genes selected from the folate\\/B12 pathway and NTD mouse models. We initially genotyped polymorphisms in 320 Irish triads (NTD cases and their parents), including 301 cases and 341 Irish controls to perform case–control and family based association tests. Significantly associated polymorphisms were genotyped in a secondary set of 250 families that included 229 cases and 658 controls. The combined results for 1441 SNPs were used in a joint analysis to test for case and maternal effects.ResultsNearly 70 SNPs in 30 genes were found to be associated with NTDs at the p < 0.01 level. The ten strongest association signals (p-value range: 0.0003–0.0023) were found in nine genes (MFTC, CDKN2A, ADA, PEMT, CUBN, GART, DNMT3A, MTHFD1 and T (Brachyury)) and included the known NTD risk factor MTHFD1 R653Q (rs2236225). The single strongest signal was observed in a new candidate, MFTC rs17803441 (OR = 1.61 [1.23-2.08], p = 0.0003 for the minor allele). Though nominally significant, these associations did not remain significant after correction for multiple hypothesis testing.ConclusionsTo our knowledge, with respect to sample size and scope of evaluation of candidate polymorphisms, this is the largest NTD genetic association study reported to date. The scale of the study and the

Evaluation of common genetic variants in 82 candidate genes as risk factors for neural tube defects

Directory of Open Access Journals (Sweden)

Pangilinan Faith

2012-08-01

Full Text Available Abstract Background Neural tube defects (NTDs are common birth defects (~1 in 1000 pregnancies in the US and Europe that have complex origins, including environmental and genetic factors. A low level of maternal folate is one well-established risk factor, with maternal periconceptional folic acid supplementation reducing the occurrence of NTD pregnancies by 50-70%. Gene variants in the folate metabolic pathway (e.g., MTHFR rs1801133 (677 C > T and MTHFD1 rs2236225 (R653Q have been found to increase NTD risk. We hypothesized that variants in additional folate/B12 pathway genes contribute to NTD risk. Methods A tagSNP approach was used to screen common variation in 82 candidate genes selected from the folate/B12 pathway and NTD mouse models. We initially genotyped polymorphisms in 320 Irish triads (NTD cases and their parents, including 301 cases and 341 Irish controls to perform case–control and family based association tests. Significantly associated polymorphisms were genotyped in a secondary set of 250 families that included 229 cases and 658 controls. The combined results for 1441 SNPs were used in a joint analysis to test for case and maternal effects. Results Nearly 70 SNPs in 30 genes were found to be associated with NTDs at the p MFTC, CDKN2A, ADA, PEMT, CUBN, GART, DNMT3A, MTHFD1 and T (Brachyury and included the known NTD risk factor MTHFD1 R653Q (rs2236225. The single strongest signal was observed in a new candidate, MFTC rs17803441 (OR = 1.61 [1.23-2.08], p = 0.0003 for the minor allele. Though nominally significant, these associations did not remain significant after correction for multiple hypothesis testing. Conclusions To our knowledge, with respect to sample size and scope of evaluation of candidate polymorphisms, this is the largest NTD genetic association study reported to date. The scale of the study and the stringency of correction are likely to have contributed to real associations failing to survive

Neural stem cell proliferation and differentiation in the conductive PEDOT-HA/Cs/Gel scaffold for neural tissue engineering.

Science.gov (United States)

Wang, Shuping; Guan, Shui; Xu, Jianqiang; Li, Wenfang; Ge, Dan; Sun, Changkai; Liu, Tianqing; Ma, Xuehu

2017-09-26

Engineering scaffolds with excellent electro-activity is increasingly important in tissue engineering and regenerative medicine. Herein, conductive poly(3,4-ethylenedioxythiophene) doped with hyaluronic acid (PEDOT-HA) nanoparticles were firstly synthesized via chemical oxidant polymerization. A three-dimensional (3D) PEDOT-HA/Cs/Gel scaffold was then developed by introducing PEDOT-HA nanoparticles into a chitosan/gelatin (Cs/Gel) matrix. HA, as a bridge, not only was used as a dopant, but also combined PEDOT into the Cs/Gel via chemical crosslinking. The PEDOT-HA/Cs/Gel scaffold was used as a conductive substrate for neural stem cell (NSC) culture in vitro. The results demonstrated that the PEDOT-HA/Cs/Gel scaffold had excellent biocompatibility for NSC proliferation and differentiation. 3D confocal fluorescence images showed cells attached on the channel surface of Cs/Gel and PEDOT-HA/Cs/Gel scaffolds with a normal neuronal morphology. Compared to the Cs/Gel scaffold, the PEDOT-HA/Cs/Gel scaffold not only promoted NSC proliferation with up-regulated expression of Ki67, but also enhanced NSC differentiation into neurons and astrocytes with up-regulated expression of β tubulin-III and GFAP, respectively. It is expected that this electro-active and bio-active PEDOT-HA/Cs/Gel scaffold will be used as a conductive platform to regulate NSC behavior for neural tissue engineering.

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

Science.gov (United States)

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

2015-01-01

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

DWI-Based Neural Fingerprinting Technology: A Preliminary Study on Stroke Analysis

Directory of Open Access Journals (Sweden)

Chenfei Ye

2014-01-01

Full Text Available Stroke is a common neural disorder in neurology clinics. Magnetic resonance imaging (MRI has become an important tool to assess the neural physiological changes under stroke, such as diffusion weighted imaging (DWI and diffusion tensor imaging (DTI. Quantitative analysis of MRI images would help medical doctors to localize the stroke area in the diagnosis in terms of structural information and physiological characterization. However, current quantitative approaches can only provide localization of the disorder rather than measure physiological variation of subtypes of ischemic stroke. In the current study, we hypothesize that each kind of neural disorder would have its unique physiological characteristics, which could be reflected by DWI images on different gradients. Based on this hypothesis, a DWI-based neural fingerprinting technology was proposed to classify subtypes of ischemic stroke. The neural fingerprint was constructed by the signal intensity of the region of interest (ROI on the DWI images under different gradients. The fingerprint derived from the manually drawn ROI could classify the subtypes with accuracy 100%. However, the classification accuracy was worse when using semiautomatic and automatic method in ROI segmentation. The preliminary results showed promising potential of DWI-based neural fingerprinting technology in stroke subtype classification. Further studies will be carried out for enhancing the fingerprinting accuracy and its application in other clinical practices.

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

Science.gov (United States)

Blumenfeld, Zack; Brontë-Stewart, Helen

2015-12-01

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

An efficient optical architecture for sparsely connected neural networks

Science.gov (United States)

Hine, Butler P., III; Downie, John D.; Reid, Max B.

1990-01-01

An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.

Molecular regionalization of the developing amphioxus neural tube challenges major partitions of the vertebrate brain.

Science.gov (United States)

Albuixech-Crespo, Beatriz; López-Blanch, Laura; Burguera, Demian; Maeso, Ignacio; Sánchez-Arrones, Luisa; Moreno-Bravo, Juan Antonio; Somorjai, Ildiko; Pascual-Anaya, Juan; Puelles, Eduardo; Bovolenta, Paola; Garcia-Fernàndez, Jordi; Puelles, Luis; Irimia, Manuel; Ferran, José Luis

2017-04-01

All vertebrate brains develop following a common Bauplan defined by anteroposterior (AP) and dorsoventral (DV) subdivisions, characterized by largely conserved differential expression of gene markers. However, it is still unclear how this Bauplan originated during evolution. We studied the relative expression of 48 genes with key roles in vertebrate neural patterning in a representative amphioxus embryonic stage. Unlike nonchordates, amphioxus develops its central nervous system (CNS) from a neural plate that is homologous to that of vertebrates, allowing direct topological comparisons. The resulting genoarchitectonic model revealed that the amphioxus incipient neural tube is unexpectedly complex, consisting of several AP and DV molecular partitions. Strikingly, comparison with vertebrates indicates that the vertebrate thalamus, pretectum, and midbrain domains jointly correspond to a single amphioxus region, which we termed Di-Mesencephalic primordium (DiMes). This suggests that these domains have a common developmental and evolutionary origin, as supported by functional experiments manipulating secondary organizers in zebrafish and mice.

Imaging Posture Veils Neural Signals

Directory of Open Access Journals (Sweden)

Robert T Thibault

2016-10-01

Full Text Available Whereas modern brain imaging often demands holding body positions incongruent with everyday life, posture governs both neural activity and cognitive performance. Humans commonly perform while upright; yet, many neuroimaging methodologies require participants to remain motionless and adhere to non-ecological comportments within a confined space. This inconsistency between ecological postures and imaging constraints undermines the transferability and generalizability of many a neuroimaging assay.Here we highlight the influence of posture on brain function and behavior. Specifically, we challenge the tacit assumption that brain processes and cognitive performance are comparable across a spectrum of positions. We provide an integrative synthesis regarding the increasingly prominent influence of imaging postures on autonomic function, mental capacity, sensory thresholds, and neural activity. Arguing that neuroimagers and cognitive scientists could benefit from considering the influence posture wields on both general functioning and brain activity, we examine existing imaging technologies and the potential of portable and versatile imaging devices (e.g., functional near infrared spectroscopy. Finally, we discuss ways that accounting for posture may help unveil the complex brain processes of everyday cognition.

Evolvable Neural Software System

Science.gov (United States)

Curtis, Steven A.

2009-01-01

The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

Neural substrates of male parochial altruism are modulated by testosterone and behavioral strategy.

Science.gov (United States)

Reimers, Luise; Büchel, Christian; Diekhof, Esther K

2017-08-01

Parochial altruism refers to ingroup favoritism and outgroup hostility and has recently been linked to testosterone. Here, we investigated the neurobiological mechanism of parochial altruism in male soccer fans playing the ultimatum game (UG) against ingroup and outgroup members (i.e., fans of the favorite or of a rivalling team) using functional magnetic resonance imaging. Our results suggest that individual differences in altruistic tendency influence the tendency for parochialism. While altruistic subjects rejected unfair offers independent of team membership, the more self-oriented 'pro-selfs' displayed a stronger ingroup bias and rejected outgroup offers more often. However, during a second session that introduced a team competition the altruists adapted to this parochial pattern. Behavioral strategy was further characterized by dissociable and context-dependent correlations between endogenous testosterone and neural responses in the anterior insula and the ventromedial prefrontal cortex. In sum, the present findings indicate that parochial altruism is shaped by individual differences in testosterone and behavioral strategy. In that way the results are in line with evolutionary theories of both individual and group selection. Copyright © 2017 Elsevier Inc. All rights reserved.

A model of interval timing by neural integration.

Science.gov (United States)

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

Parametric optimization for floating drum anaerobic bio-digester using Response Surface Methodology and Artificial Neural Network

Directory of Open Access Journals (Sweden)

S. Sathish

2016-12-01

Full Text Available The main purpose of this study to increase the optimal conditions for biogas yield from anaerobic digestion of agricultural waste (Rice Straw using Response Surface Methodology (RSM and Artificial Neural Network (ANN. In the development of predictive models temperature, pH, substrate concentration and agitation time are conceived as model variables. The experimental results show that the liner model terms of temperature, substrate concentration and pH, agitation time have significance of interactive effects (p < 0.05. The results manifest that the optimum process parameters affected on biogas yield increase from the ANN model when compared to RSM model. The ANN model indicates that it is much more accurate and reckons the values of maximum biogas yield when compared to RSM model.

Neural Representation. A Survey-Based Analysis of the Notion

Directory of Open Access Journals (Sweden)

Oscar Vilarroya

2017-08-01

Full Text Available The word representation (as in “neural representation”, and many of its related terms, such as to represent, representational and the like, play a central explanatory role in neuroscience literature. For instance, in “place cell” literature, place cells are extensively associated with their role in “the representation of space.” In spite of its extended use, we still lack a clear, universal and widely accepted view on what it means for a nervous system to represent something, on what makes a neural activity a representation, and on what is re-presented. The lack of a theoretical foundation and definition of the notion has not hindered actual research. My aim here is to identify how active scientists use the notion of neural representation, and eventually to list a set of criteria, based on actual use, that can help in distinguishing between genuine or non-genuine neural-representation candidates. In order to attain this objective, I present first the results of a survey of authors within two domains, place-cell and multivariate pattern analysis (MVPA research. Based on the authors’ replies, and on a review of neuroscientific research, I outline a set of common properties that an account of neural representation seems to require. I then apply these properties to assess the use of the notion in two domains of the survey, place-cell and MVPA studies. I conclude by exploring a shift in the notion of representation suggested by recent literature.

Measures of coupling between neural populations based on Granger causality principle

Directory of Open Access Journals (Sweden)

Maciej Kaminski

2016-10-01

Full Text Available This paper shortly reviews the measures used to estimate neural synchronization in experimental settings. Our focus is on multivariate measures of dependence based on the Granger causality (G-causality principle, their applications and performance in respect of robustness to noise, volume conduction, common driving, and presence of a weak node. Application of G-causality measures to EEG, intracranial signals and fMRI time series is addressed. G-causality based measures defined in the frequency domain allow the synchronization between neural populations and the directed propagation of their electrical activity to be determined. The time-varying G-causality based measure Short-time Directed Transfer Function (SDTF supplies information on the dynamics of synchronization and the organization of neural networks. Inspection of effective connectivity patterns indicates a modular structure of neural networks, with a stronger coupling within modules than between them. The hypothetical plausible mechanism of information processing, suggested by the identified synchronization patterns, is communication between tightly coupled modules intermitted by sparser interactions providing synchronization of distant structures.

An investigation of the neural substrates of mind wandering induced by viewing traditional Chinese landscape paintings

Directory of Open Access Journals (Sweden)

Tingting eWang

2015-01-01

Full Text Available The present study was conducted to investigate whether the calming effect induced by viewing traditional Chinese landscape paintings would make disengagement from that mental state more difficult, as measured by performance on a cognitive control task. In Experiment 1 we examined the subjective experience of viewing traditional Chinese landscape paintings vs. realistic oil landscape paintings in a behavioral study. Our results confirmed that, as predicted, traditional Chinese landscape paintings induce greater levels of relaxation and mind wandering and lower levels of object-oriented absorption and recognition, compared to realistic oil landscape paintings. In Experiment 2 we used functional Magnetic Resonance Imaging (fMRI to explore the behavioural and neural effects of viewing traditional Chinese landscape paintings on a task requiring cognitive control (i.e., the flanker task—administered immediately following exposure to paintings. Contrary to our prediction, the behavioural data demonstrated that compared to realistic oil landscape paintings, exposure to traditional Chinese landscape paintings had no effect on performance on the flanker task. However, the neural data demonstrated an interaction effect such that there was greater activation in the inferior parietal cortex (IPC and the superior frontal gyrus (SFG on incongruent compared with congruent flanker trials when participants switched from viewing traditional Chinese landscape paintings to the flanker task than when they switched from realistic oil landscape paintings. These results suggest that switching from traditional Chinese landscape paintings placed greater demands on the brain’s attention and working memory networks during the flanker task than did switching from realistic oil landscape paintings.

Examining overlap in behavioral and neural representations of morals, facts, and preferences.

Science.gov (United States)

Theriault, Jordan; Waytz, Adam; Heiphetz, Larisa; Young, Liane

2017-11-01

Metaethical judgments refer to judgments about the information expressed by moral claims. Moral objectivists generally believe that moral claims are akin to facts, whereas moral subjectivists generally believe that moral claims are more akin to preferences. Evidence from developmental and social psychology has generally favored an objectivist view; however, this work has typically relied on few examples, and analyses have disallowed statistical generalizations beyond these few stimuli. The present work addresses whether morals are represented as fact-like or preference-like, using behavioral and neuroimaging methods, in combination with statistical techniques that can (a) generalize beyond our sample stimuli, and (b) test whether particular item features are associated with neural activity. Behaviorally, and contrary to prior work, morals were perceived as more preference-like than fact-like. Neurally, morals and preferences elicited common magnitudes and spatial patterns of activity, particularly within the dorsal-medial prefrontal cortex (DMPFC), a critical region for social cognition. This common DMPFC activity for morals and preferences was present across whole-brain conjunctions, and in individually localized functional regions of interest (targeting the theory of mind network). By contrast, morals and facts did not elicit any neural activity in common. Follow-up item analyses suggested that the activity elicited in common by morals and preferences was explained by their shared tendency to evoke representations of mental states. We conclude that morals are represented as far more subjective than prior work has suggested. This conclusion is consistent with recent theoretical research, which has argued that morality is fundamentally about regulating social relationships. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Neural systems language: a formal modeling language for the systematic description, unambiguous communication, and automated digital curation of neural connectivity.

Science.gov (United States)

Brown, Ramsay A; Swanson, Larry W

2013-09-01

Systematic description and the unambiguous communication of findings and models remain among the unresolved fundamental challenges in systems neuroscience. No common descriptive frameworks exist to describe systematically the connective architecture of the nervous system, even at the grossest level of observation. Furthermore, the accelerating volume of novel data generated on neural connectivity outpaces the rate at which this data is curated into neuroinformatics databases to synthesize digitally systems-level insights from disjointed reports and observations. To help address these challenges, we propose the Neural Systems Language (NSyL). NSyL is a modeling language to be used by investigators to encode and communicate systematically reports of neural connectivity from neuroanatomy and brain imaging. NSyL engenders systematic description and communication of connectivity irrespective of the animal taxon described, experimental or observational technique implemented, or nomenclature referenced. As a language, NSyL is internally consistent, concise, and comprehensible to both humans and computers. NSyL is a promising development for systematizing the representation of neural architecture, effectively managing the increasing volume of data on neural connectivity and streamlining systems neuroscience research. Here we present similar precedent systems, how NSyL extends existing frameworks, and the reasoning behind NSyL's development. We explore NSyL's potential for balancing robustness and consistency in representation by encoding previously reported assertions of connectivity from the literature as examples. Finally, we propose and discuss the implications of a framework for how NSyL will be digitally implemented in the future to streamline curation of experimental results and bridge the gaps among anatomists, imagers, and neuroinformatics databases. Copyright © 2013 Wiley Periodicals, Inc.

Chaotic diagonal recurrent neural network

International Nuclear Information System (INIS)

Wang Xing-Yuan; Zhang Yi

2012-01-01

We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

Computational modeling of neural plasticity for self-organization of neural networks.

Science.gov (United States)

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

The neural basis of monitoring goal progress

Directory of Open Access Journals (Sweden)

Yael eBenn

2014-09-01

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

Unsatisfied relatedness, not competence or autonomy, increases trait anger through the right amygdala.

Science.gov (United States)

Wang, Yinan; Kong, Feng; Kong, Xiangzhen; Zhao, Yuanfang; Lin, Danhua; Liu, Jia

2017-10-01

Anger is a common negative emotion in social life. Behavioral research suggests that unsatisfied relatedness, autonomy, and competence are related to anger. However, it remains unclear whether these unsatisfied needs all contribute to anger or just a particular unsatisfied need is the main source of anger. In addition, little is known about the neural substrate between unsatisfied needs and anger. To address these two questions, we used voxel-based morphometry (VBM) to explore the neural substrate underlying the relation between unsatisfied needs and trait anger. Behaviorally, we found that although all three unsatisfied needs were correlated with trait anger, unsatisfied relatedness was the only factor that was uniquely related to trait anger. Neurally, the gray matter volume of the right amygdala was correlated with trait anger, which fits nicely with the role of the amygdala as a core region for processing anger. Importantly, the right amygdala mediated the total effect of unsatisfied relatedness on trait anger, even after controlling for general personality dispositions. Our results contribute to the theoretical conceptualization of anger by elucidating the unique role of unsatisfied relatedness in anger and the neural substrate underlying such relation.

SERS substrates fabricated using ceramic filters for the detection of bacteria

Science.gov (United States)

Mosier-Boss, P. A.; Sorensen, K. C.; George, R. D.; Obraztsova, A.

2016-01-01

SERS substrates were fabricated by filtering either Ag or Au colloidal particles onto rigid, ceramic filters - onto which suspensions of bacteria were then filtered. SERS spectra of the bacteria were obtained using a Raman spectrometer that has an 'orbital raster scan' capability. It was shown that bacteria samples prepared in this manner were uniformly distributed onto the surface of the SERS substrate. The effect of common buffer systems on the SERS spectra was investigated and the utility of using the SERS technique for speciation of bacteria was explored.

Neural correlates of dynamically evolving interpersonal ties predict prosocial behaviour

Directory of Open Access Journals (Sweden)

Johannes Jacobus Fahrenfort

2012-03-01

Full Text Available There is a growing interest for the determinants of human choice behaviour in social settings. Upon initial contact, investment choices in social settings can be inherently risky, as the degree to which the other person will reciprocate is unknown. Nevertheless, people have been shown to exhibit prosocial behaviour even in one-shot laboratory settings where all interaction has been taken away. A logical step has been to link such behaviour to trait empathy-related neurobiological networks. However, as a social interaction unfolds, the degree of uncertainty with respect to the expected payoff of choice behaviour may change as a function of the interaction. Here we attempt to capture this factor. We show that the interpersonal tie one develops with another person during interaction - rather than trait empathy - motivates investment in a public good that is shared with an anonymous interaction partner. We examined how individual differences in trait empathy and interpersonal ties modulate neural responses to imposed monetary sharing. After, but not before interaction in a public good game, sharing prompted activation of neural systems associated with reward (striatum, empathy (anterior insular cortex [AIC] and anterior cingulate cortex [ACC] as well as altruism and social significance (posterior superior temporal sulcus [pSTS]. Although these activations could be linked to both empathy and interpersonal ties, only tie-related pSTS activation predicted prosocial behaviour during subsequent interaction, suggesting a neural substrate for keeping track of social relevance.

Progressive and Regressive Developmental Changes in Neural Substrates for Face Processing: Testing Specific Predictions of the Interactive Specialization Account

Science.gov (United States)

Joseph, Jane E.; Gathers, Ann D.; Bhatt, Ramesh S.

2011-01-01

Face processing undergoes a fairly protracted developmental time course but the neural underpinnings are not well understood. Prior fMRI studies have only examined progressive changes (i.e. increases in specialization in certain regions with age), which would be predicted by both the Interactive Specialization (IS) and maturational theories of…

Techniques for extracting single-trial activity patterns from large-scale neural recordings

Science.gov (United States)

Churchland, Mark M; Yu, Byron M; Sahani, Maneesh; Shenoy, Krishna V

2008-01-01

Summary Large, chronically-implanted arrays of microelectrodes are an increasingly common tool for recording from primate cortex, and can provide extracellular recordings from many (order of 100) neurons. While the desire for cortically-based motor prostheses has helped drive their development, such arrays also offer great potential to advance basic neuroscience research. Here we discuss the utility of array recording for the study of neural dynamics. Neural activity often has dynamics beyond that driven directly by the stimulus. While governed by those dynamics, neural responses may nevertheless unfold differently for nominally identical trials, rendering many traditional analysis methods ineffective. We review recent studies – some employing simultaneous recording, some not – indicating that such variability is indeed present both during movement generation, and during the preceding premotor computations. In such cases, large-scale simultaneous recordings have the potential to provide an unprecedented view of neural dynamics at the level of single trials. However, this enterprise will depend not only on techniques for simultaneous recording, but also on the use and further development of analysis techniques that can appropriately reduce the dimensionality of the data, and allow visualization of single-trial neural behavior. PMID:18093826

Application of artificial neural networks in particle physics

International Nuclear Information System (INIS)

Kolanoski, H.

1995-04-01

The application of Artificial Neural Networks in Particle Physics is reviewed. Most common is the use of feed-forward nets for event classification and function approximation. This network type is best suited for a hardware implementation and special VLSI chips are available which are used in fast trigger processors. Also discussed are fully connected networks of the Hopfield type for pattern recognition in tracking detectors. (orig.)

Nanowire FET Based Neural Element for Robotic Tactile Sensing Skin

Directory of Open Access Journals (Sweden)

William Taube Navaraj

2017-09-01

Full Text Available This paper presents novel Neural Nanowire Field Effect Transistors (υ-NWFETs based hardware-implementable neural network (HNN approach for tactile data processing in electronic skin (e-skin. The viability of Si nanowires (NWs as the active material for υ-NWFETs in HNN is explored through modeling and demonstrated by fabricating the first device. Using υ-NWFETs to realize HNNs is an interesting approach as by printing NWs on large area flexible substrates it will be possible to develop a bendable tactile skin with distributed neural elements (for local data processing, as in biological skin in the backplane. The modeling and simulation of υ-NWFET based devices show that the overlapping areas between individual gates and the floating gate determines the initial synaptic weights of the neural network - thus validating the working of υ-NWFETs as the building block for HNN. The simulation has been further extended to υ-NWFET based circuits and neuronal computation system and this has been validated by interfacing it with a transparent tactile skin prototype (comprising of 6 × 6 ITO based capacitive tactile sensors array integrated on the palm of a 3D printed robotic hand. In this regard, a tactile data coding system is presented to detect touch gesture and the direction of touch. Following these simulation studies, a four-gated υ-NWFET is fabricated with Pt/Ti metal stack for gates, source and drain, Ni floating gate, and Al2O3 high-k dielectric layer. The current-voltage characteristics of fabricated υ-NWFET devices confirm the dependence of turn-off voltages on the (synaptic weight of each gate. The presented υ-NWFET approach is promising for a neuro-robotic tactile sensory system with distributed computing as well as numerous futuristic applications such as prosthetics, and electroceuticals.

Automatic detection of photoresist residual layer in lithography using a neural classification approach

KAUST Repository

Gereige, Issam

2012-09-01

Photolithography is a fundamental process in the semiconductor industry and it is considered as the key element towards extreme nanoscale integration. In this technique, a polymer photo sensitive mask with the desired patterns is created on the substrate to be etched. Roughly speaking, the areas to be etched are not covered with polymer. Thus, no residual layer should remain on these areas in order to insure an optimal transfer of the patterns on the substrate. In this paper, we propose a nondestructive method based on a classification approach achieved by artificial neural network for automatic residual layer detection from an ellipsometric signature. Only the case of regular defect, i.e. homogenous residual layer, will be considered. The limitation of the method will be discussed. Then, an experimental result on a 400 nm period grating manufactured with nanoimprint lithography is analyzed with our method. © 2012 Elsevier B.V. All rights reserved.

Assessment of Automotive Coatings Used on Different Metallic Substrates

Directory of Open Access Journals (Sweden)

W. Bensalah

2014-01-01

Full Text Available Four epoxy primers commonly used in the automotive industry were applied by gravity pneumatic spray gun over metallic substrates, specifically, steel, electrogalvanized steel, hot-dip galvanized steel, and aluminum. A two-component polyurethane resin was used as topcoat. To evaluate the performance of the different coating systems, the treated panels were submitted to mechanical testing using Persoz hardness, impact resistance, cupping, lattice method, and bending. Tribological properties of different coating systems were conducted using pin on disc machine. Immersion tests were carried out in 5% NaCl and immersion tests in 3% NaOH solutions. Results showed which of the coating systems is more suitable for each substrate in terms of mechanical, tribological, and anticorrosive performance.

A Study of Recurrent and Convolutional Neural Networks in the Native Language Identification Task

KAUST Repository

Werfelmann, Robert

2018-05-24

Native Language Identification (NLI) is the task of predicting the native language of an author from their text written in a second language. The idea is to find writing habits that transfer from an author’s native language to their second language. Many approaches to this task have been studied, from simple word frequency analysis, to analyzing grammatical and spelling mistakes to find patterns and traits that are common between different authors of the same native language. This can be a very complex task, depending on the native language and the proficiency of the author’s second language. The most common approach that has seen very good results is based on the usage of n-gram features of words and characters. In this thesis, we attempt to extract lexical, grammatical, and semantic features from the sentences of non-native English essays using neural networks. The training and testing data was obtained from a large corpus of publicly available essays written by authors of several countries around the world. The neural network models consisted of Long Short-Term Memory and Convolutional networks using the sentences of each document as the input. Additional statistical features were generated from the text to complement the predictions of the neural networks, which were then used as feature inputs to a Support Vector Machine, making the final prediction. Results show that Long Short-Term Memory neural network can improve performance over a naive bag of words approach, but with a much smaller feature set. With more fine-tuning of neural network hyperparameters, these results will likely improve significantly.

Neural chips, neural computers and application in high and superhigh energy physics experiments

International Nuclear Information System (INIS)

Nikityuk, N.M.; )

2001-01-01

Architecture peculiarity and characteristics of series of neural chips and neural computes used in scientific instruments are considered. Tendency of development and use of them in high energy and superhigh energy physics experiments are described. Comparative data which characterize the efficient use of neural chips for useful event selection, classification elementary particles, reconstruction of tracks of charged particles and for search of hypothesis Higgs particles are given. The characteristics of native neural chips and accelerated neural boards are considered [ru

A comparison between wavelet based static and dynamic neural network approaches for runoff prediction

Science.gov (United States)

Shoaib, Muhammad; Shamseldin, Asaad Y.; Melville, Bruce W.; Khan, Mudasser Muneer

2016-04-01

In order to predict runoff accurately from a rainfall event, the multilayer perceptron type of neural network models are commonly used in hydrology. Furthermore, the wavelet coupled multilayer perceptron neural network (MLPNN) models has also been found superior relative to the simple neural network models which are not coupled with wavelet. However, the MLPNN models are considered as static and memory less networks and lack the ability to examine the temporal dimension of data. Recurrent neural network models, on the other hand, have the ability to learn from the preceding conditions of the system and hence considered as dynamic models. This study for the first time explores the potential of wavelet coupled time lagged recurrent neural network (TLRNN) models for runoff prediction using rainfall data. The Discrete Wavelet Transformation (DWT) is employed in this study to decompose the input rainfall data using six of the most commonly used wavelet functions. The performance of the simple and the wavelet coupled static MLPNN models is compared with their counterpart dynamic TLRNN models. The study found that the dynamic wavelet coupled TLRNN models can be considered as alternative to the static wavelet MLPNN models. The study also investigated the effect of memory depth on the performance of static and dynamic neural network models. The memory depth refers to how much past information (lagged data) is required as it is not known a priori. The db8 wavelet function is found to yield the best results with the static MLPNN models and with the TLRNN models having small memory depths. The performance of the wavelet coupled TLRNN models with large memory depths is found insensitive to the selection of the wavelet function as all wavelet functions have similar performance.

Sensitivity of the Action Observation Network to Physical and Observational Learning

NARCIS (Netherlands)

Cross, E.S.; Kraemer, D.J.M.; Hamilton, A.F.D.C.; Kelley, W.M.; Grafton, S.T.

2009-01-01

Human motor skills can be acquired by observation without the benefit of immediate physical practice. The current study tested if physical rehearsal and observational learning share common neural substrates within an action observation network (AON) including premotor and inferior parietal regions,

Anger in brain and body: the neural and physiological perturbation of decision-making by emotion.

Science.gov (United States)

Garfinkel, Sarah N; Zorab, Emma; Navaratnam, Nakulan; Engels, Miriam; Mallorquí-Bagué, Núria; Minati, Ludovico; Dowell, Nicholas G; Brosschot, Jos F; Thayer, Julian F; Critchley, Hugo D

2016-01-01

Emotion and cognition are dynamically coupled to bodily arousal: the induction of anger, even unconsciously, can reprioritise neural and physiological resources toward action states that bias cognitive processes. Here we examine behavioural, neural and bodily effects of covert anger processing and its influence on cognition, indexed by lexical decision-making. While recording beat-to-beat blood pressure, the words ANGER or RELAX were presented subliminally just prior to rapid word/non-word reaction-time judgements of letter-strings. Subliminal ANGER primes delayed the time taken to reach rapid lexical decisions, relative to RELAX primes. However, individuals with high trait anger were speeded up by subliminal anger primes. ANGER primes increased systolic blood pressure and the magnitude of this increase predicted reaction time prolongation. Within the brain, ANGER trials evoked an enhancement of activity within dorsal pons and an attenuation of activity within visual occipitotemporal and attentional parietal cortices. Activity within periaqueductal grey matter, occipital and parietal regions increased linearly with evoked blood pressure changes, indicating neural substrates through which covert anger impairs semantic decisions, putatively through its expression as visceral arousal. The behavioural and physiological impact of anger states compromises the efficiency of cognitive processing through action-ready changes in autonomic response that skew regional neural activity. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Neural tissue-spheres

DEFF Research Database (Denmark)

Andersen, Rikke K; Johansen, Mathias; Blaabjerg, Morten

2007-01-01

By combining new and established protocols we have developed a procedure for isolation and propagation of neural precursor cells from the forebrain subventricular zone (SVZ) of newborn rats. Small tissue blocks of the SVZ were dissected and propagated en bloc as free-floating neural tissue...... content, thus allowing experimental studies of neural precursor cells and their niche...

Artificial Neural Networks in the prediction of insolvency. A paradigm shift to traditional business practices recipes

Directory of Open Access Journals (Sweden)

Marcia M. Lastre Valdes

2014-06-01

Full Text Available In this paper a review and analysis of the major theories and models that address the prediction of corporate bankruptcy and insolvency is made. Neural networks are a tool of most recent appearance, although in recent years have received considerable attention from the academic and professional world, and have started to be implemented in different models testing organizations insolvency based on neural computation. The purpose of this paper is to yield evidence of the usefulness of Artificial Neural Networks in the problem of bankruptcy prediction insolence or so compare its predictive ability with the methods commonly used in that context. The findings suggest that high predictive capabilities can be achieved  using artificial neural networks, with qualitative and quantitative variables.

Fabrication and characterization of conductive anodic aluminum oxide substrates

Science.gov (United States)

Altuntas, Sevde; Buyukserin, Fatih

2014-11-01

Biomaterials that allow the utilization of electrical, chemical and topographic cues for improved neuron-material interaction and neural regeneration hold great promise for nerve tissue engineering applications. The nature of anodic aluminum oxide (AAO) membranes intrinsically provides delicate control over topographic and chemical cues for enhanced cell interaction; however their use in nerve regeneration is still very limited. Herein, we report the fabrication and characterization of conductive AAO (CAAO) surfaces for the ultimate goal of integrating electrical cues for improved nerve tissue behavior on the nanoporous substrate material. Parafilm was used as a protecting polymer film, for the first time, in order to obtain large area (50 cm2) free-standing AAO membranes. Carbon (C) was then deposited on the AAO surface via sputtering. Morphological characterization of the CAAO surfaces revealed that the pores remain open after the deposition process. The presence of C on the material surface and inside the nanopores was confirmed by XPS and EDX studies. Furthermore, I-V curves of the surface were used to extract surface resistance values and conductive AFM demonstrated that current signals can only be achieved where conductive C layer is present. Finally, novel nanoporous C films with controllable pore diameters and one dimensional (1-D) C nanostructures were obtained by the dissolution of the template AAO substrate.

Dynamics of Preferential Substrate Recognition in HIV-1 Protease: Redefining the Substrate Envelope

Science.gov (United States)

Özen, Ayşegül; Haliloğlu, Türkan; Schiffer, Celia A.

2011-01-01

HIV-1 protease (PR) permits viral maturation by processing the Gag and Gag-Pro-Pol polyproteins. Though HIV-1 PR inhibitors (PIs) are used in combination antiviral therapy, the emergence of drug resistance has limited their efficacy. The rapid evolution of HIV-1 necessitates the consideration of drug resistance in novel drug-design strategies. Drug-resistant HIV-1 PR variants, while no longer efficiently inhibited, continue to efficiently hydrolyze the natural viral substrates. Though highly diverse in sequence, the HIV-1 PR substrates bind in a conserved three-dimensional shape we defined as the “substrate envelope”. We previously showed that resistance mutations arise where PIs protrude beyond the substrate envelope, as these regions are crucial for drug binding but not for substrate recognition. Here, we extend this model by considering the role of protein dynamics in the interaction of HIV-1 PR with its substrates. Seven molecular dynamics simulations of PR-substrate complexes were performed to estimate the conformational flexibility of substrates in their complexes. Interdependency of the substrate-protease interactions may compensate for the variations in cleavage-site sequences, and explain how a diverse set of sequences can be recognized as substrates by the same enzyme. This diversity may be essential for regulating sequential processing of substrates. We also define a dynamic substrate envelope as a more accurate representation of PR-substrate interactions. This dynamic substrate envelope, described by a probability distribution function, is a powerful tool for drug design efforts targeting ensembles of resistant HIV-1 PR variants with the aim of developing drugs that are less susceptible to resistance. PMID:21762811

Quantitative isotope incorporation reveals substrate partitioning in a coastal microbial community.

Science.gov (United States)

Mayali, Xavier; Weber, Peter K

2018-05-01

To quantitatively link microbial identity with biogeochemical function, we carried out 14 simultaneous stable isotope probing experiments with organic and inorganic C and N substrates to measure the isotope incorporation by over one hundred co-occurring eukaryotic and prokaryotic populations in a coastal community. We found that nitrate was the most commonly incorporated substrate, and that light-driven carbon fixation was carried out by some bacterial taxa from the Flavobacteriales and OM60 (NOR5) clade, in addition to photoautotrophic phytoplankton. We found that organisms that incorporated starch, maltose, glucose, lactose and bicarbonate were phylogenetically clustered, suggesting that specific bacterial lineages specialized in the incorporation of these substrates. The data further revealed that coastal microorganisms spanned a range of resource utilization strategies from generalists to specialists and demonstrated a high level of substrate partitioning, with two thirds of taxa exhibiting unique substrate incorporation patterns and the remaining third shared by no more than three OTUs each. Specialists exhibited more extreme incorporation levels (high or low), whereas generalists displayed more intermediate activity levels. These results shed valuable insights into the bottom-up ecological strategies enabling the persistence of high microbial diversity in aquatic ecosystems.

Brain substrates of implicit and explicit memory: The importance of concurrently acquired neural signals of both memory types

OpenAIRE

Voss, Joel L.; Paller, Ken A.

2008-01-01

A comprehensive understanding of human memory requires cognitive and neural descriptions of memory processes along with a conception of how memory processing drives behavioral responses and subjective experiences. One serious challenge to this endeavor is that an individual memory process is typically operative within a mix of other contemporaneous memory processes. This challenge is particularly disquieting in the context of implicit memory, which, unlike explicit memory, transpires without ...

Neural associations of the early retinotopic cortex with the lateral occipital complex during visual perception.

Directory of Open Access Journals (Sweden)

Delong Zhang

Full Text Available Previous studies have demonstrated that the early retinotopic cortex (ERC, i.e., V1/V2/V3 is highly associated with the lateral occipital complex (LOC during visual perception. However, it remains largely unclear how to evaluate their associations in quantitative way. The present study tried to apply a multivariate pattern analysis (MVPA to quantify the neural activity in ERC and its association with that of the LOC when participants saw visual images. To this end, we assessed whether low-level visual features (Gabor features could predict the neural activity in the ERC and LOC according to a voxel-based encoding model (VBEM, and then quantified the association of the neural activity between these regions by using an analogical VBEM. We found that the Gabor features remarkably predicted the activity of the ERC (e.g., the predicted accuracy was 52.5% for a participant instead of that of the LOC (4.2%. Moreover, the MVPA approach can also be used to establish corresponding relationships between the activity patterns in the LOC and those in the ERC (64.2%. In particular, we found that the integration of the Gabor features and LOC visual information could dramatically improve the 'prediction' of ERC activity (88.3%. Overall, the present study provides new evidences for the possibility of quantifying the association of the neural activity between the regions of ERC and LOC. This approach will help to provide further insights into the neural substrates of the visual processing.

Autism as an adaptive common variant pathway for human brain development.

Science.gov (United States)

Johnson, Mark H

2017-06-01

While research on focal perinatal lesions has provided evidence for recovery of function, much less is known about processes of brain adaptation resulting from mild but widespread disturbances to neural processing over the early years (such as alterations in synaptic efficiency). Rather than being viewed as a direct behavioral consequence of life-long neural dysfunction, I propose that autism is best viewed as the end result of engaging adaptive processes during a sensitive period. From this perspective, autism is not appropriately described as a disorder of neurodevelopment, but rather as an adaptive common variant pathway of human functional brain development. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Atypical neural substrates of Embedded Figures Task performance in children with Autism Spectrum Disorder.

Science.gov (United States)

Lee, Philip S; Foss-Feig, Jennifer; Henderson, Joshua G; Kenworthy, Lauren E; Gilotty, Lisa; Gaillard, William D; Vaidya, Chandan J

2007-10-15

Superior performance on the Embedded Figures Task (EFT) has been attributed to weak central coherence in perceptual processing in Autism Spectrum Disorder (ASD). The present study used functional magnetic resonance imaging to examine the neural basis of EFT performance in 7- to 12-year-old ASD children and age- and IQ-matched controls. ASD children activated only a subset of the distributed network of regions activated in controls. In frontal cortex, control children activated left dorsolateral, medial and dorsal premotor regions whereas ASD children only activated the dorsal premotor region. In parietal and occipital cortices, activation was bilateral in control children but unilateral (left superior parietal and right occipital) in ASD children. Further, extensive bilateral ventral temporal activation was observed in control, but not ASD children. ASD children performed the EFT at the same level as controls but with reduced cortical involvement, suggesting that disembedded visual processing is accomplished parsimoniously by ASD relative to typically developing brains.

A neural network clustering algorithm for the ATLAS silicon pixel detector

CERN Document Server

Aad, Georges; Abdallah, Jalal; Abdel Khalek, Samah; Abdinov, Ovsat; Aben, Rosemarie; Abi, Babak; Abolins, Maris; AbouZeid, Ossama; Abramowicz, Halina; Abreu, Henso; Abreu, Ricardo; Abulaiti, Yiming; Acharya, Bobby Samir; Adamczyk, Leszek; Adams, David; Adelman, Jahred; Adomeit, Stefanie; Adye, Tim; Agatonovic-Jovin, Tatjana; Aguilar-Saavedra, Juan Antonio; Agustoni, Marco; Ahlen, Steven; Ahmadov, Faig; Aielli, Giulio; Akerstedt, Henrik; Åkesson, Torsten Paul Ake; Akimoto, Ginga; Akimov, Andrei; Alberghi, Gian Luigi; Albert, Justin; Albrand, Solveig; Alconada Verzini, Maria Josefina; Aleksa, Martin; Aleksandrov, Igor; Alexa, Calin; Alexander, Gideon; Alexandre, Gauthier; Alexopoulos, Theodoros; Alhroob, Muhammad; Alimonti, Gianluca; Alio, Lion; Alison, John; Allbrooke, Benedict; Allison, Lee John; Allport, Phillip; Almond, John; Aloisio, Alberto; Alonso, Alejandro; Alonso, Francisco; Alpigiani, Cristiano; Altheimer, Andrew David; Alvarez Gonzalez, Barbara; Alviggi, Mariagrazia; Amako, Katsuya; Amaral Coutinho, Yara; Amelung, Christoph; Amidei, Dante; Amor Dos Santos, Susana Patricia; Amorim, Antonio; Amoroso, Simone; Amram, Nir; Amundsen, Glenn; Anastopoulos, Christos; Ancu, Lucian Stefan; Andari, Nansi; Andeen, Timothy; Anders, Christoph Falk; Anders, Gabriel; Anderson, Kelby; Andreazza, Attilio; Andrei, George Victor; Anduaga, Xabier; Angelidakis, Stylianos; Angelozzi, Ivan; Anger, Philipp; Angerami, Aaron; Anghinolfi, Francis; Anisenkov, Alexey; Anjos, Nuno; Annovi, Alberto; Antonaki, Ariadni; Antonelli, Mario; Antonov, Alexey; Antos, Jaroslav; Anulli, Fabio; Aoki, Masato; Aperio Bella, Ludovica; Apolle, Rudi; Arabidze, Giorgi; Aracena, Ignacio; Arai, Yasuo; Araque, Juan Pedro; Arce, Ayana; Arguin, Jean-Francois; Argyropoulos, Spyridon; Arik, Metin; Armbruster, Aaron James; Arnaez, Olivier; Arnal, Vanessa; Arnold, Hannah; Arratia, Miguel; Arslan, Ozan; Artamonov, Andrei; Artoni, Giacomo; Asai, Shoji; Asbah, Nedaa; Ashkenazi, Adi; Åsman, Barbro; Asquith, Lily; Assamagan, Ketevi; Astalos, Robert; Atkinson, Markus; Atlay, Naim Bora; Auerbach, Benjamin; Augsten, Kamil; Aurousseau, Mathieu; Avolio, Giuseppe; Azuelos, Georges; Azuma, Yuya; Baak, Max; Baas, Alessandra; Bacci, Cesare; Bachacou, Henri; Bachas, Konstantinos; Backes, Moritz; Backhaus, Malte; Backus Mayes, John; Badescu, Elisabeta; Bagiacchi, Paolo; Bagnaia, Paolo; Bai, Yu; Bain, Travis; Baines, John; Baker, Oliver Keith; Balek, Petr; Balli, Fabrice; Banas, Elzbieta; Banerjee, Swagato; Bannoura, Arwa A E; Bansal, Vikas; Bansil, Hardeep Singh; Barak, Liron; Baranov, Sergei; Barberio, Elisabetta Luigia; Barberis, Dario; Barbero, Marlon; Barillari, Teresa; Barisonzi, Marcello; Barklow, Timothy; Barlow, Nick; Barnett, Bruce; Barnett, Michael; Barnovska, Zuzana; Baroncelli, Antonio; Barone, Gaetano; Barr, Alan; Barreiro, Fernando; Barreiro Guimarães da Costa, João; Bartoldus, Rainer; Barton, Adam Edward; Bartos, Pavol; Bartsch, Valeria; Bassalat, Ahmed; Basye, Austin; Bates, Richard; Batkova, Lucia; Batley, Richard; Battaglia, Marco; Battistin, Michele; Bauer, Florian; Bawa, Harinder Singh; Beau, Tristan; Beauchemin, Pierre-Hugues; Beccherle, Roberto; Bechtle, Philip; Beck, Hans Peter; Becker, Anne Kathrin; Becker, Sebastian; Beckingham, Matthew; Becot, Cyril; Beddall, Andrew; Beddall, Ayda; Bedikian, Sourpouhi; Bednyakov, Vadim; Bee, Christopher; Beemster, Lars; Beermann, Thomas; Begel, Michael; Behr, Katharina; Belanger-Champagne, Camille; Bell, Paul; Bell, William; Bella, Gideon; Bellagamba, Lorenzo; Bellerive, Alain; Bellomo, Massimiliano; Belotskiy, Konstantin; Beltramello, Olga; Benary, Odette; Benchekroun, Driss; Bendtz, Katarina; Benekos, Nektarios; Benhammou, Yan; Benhar Noccioli, Eleonora; Benitez Garcia, Jorge-Armando; Benjamin, Douglas; Bensinger, James; Benslama, Kamal; Bentvelsen, Stan; Berge, David; Bergeaas Kuutmann, Elin; Berger, Nicolas; Berghaus, Frank; Beringer, Jürg; Bernard, Clare; Bernat, Pauline; Bernius, Catrin; Bernlochner, Florian Urs; Berry, Tracey; Berta, Peter; Bertella, Claudia; Bertoli, Gabriele; Bertolucci, Federico; Bertsche, David; Besana, Maria Ilaria; Besjes, Geert-Jan; Bessidskaia, Olga; Bessner, Martin Florian; Besson, Nathalie; Betancourt, Christopher; Bethke, Siegfried; Bhimji, Wahid; Bianchi, Riccardo-Maria; Bianchini, Louis; Bianco, Michele; Biebel, Otmar; Bieniek, Stephen Paul; Bierwagen, Katharina; Biesiada, Jed; Biglietti, Michela; Bilbao De Mendizabal, Javier; Bilokon, Halina; Bindi, Marcello; Binet, Sebastien; Bingul, Ahmet; Bini, Cesare; Black, Curtis; Black, James; Black, Kevin; Blackburn, Daniel; Blair, Robert; Blanchard, Jean-Baptiste; Blazek, Tomas; Bloch, Ingo; Blocker, Craig; Blum, Walter; Blumenschein, Ulrike; Bobbink, Gerjan; Bobrovnikov, Victor; Bocchetta, Simona Serena; Bocci, Andrea; Bock, Christopher; Boddy, Christopher Richard; Boehler, Michael; Boek, Thorsten Tobias; Bogaerts, Joannes Andreas; Bogdanchikov, Alexander; Bogouch, Andrei; Bohm, Christian; Bohm, Jan; Boisvert, Veronique; Bold, Tomasz; Boldea, Venera; Boldyrev, Alexey; Bomben, Marco; Bona, Marcella; Boonekamp, Maarten; Borisov, Anatoly; Borissov, Guennadi; Borri, Marcello; Borroni, Sara; Bortfeldt, Jonathan; Bortolotto, Valerio; Bos, Kors; Boscherini, Davide; Bosman, Martine; Boterenbrood, Hendrik; Boudreau, Joseph; Bouffard, Julian; Bouhova-Thacker, Evelina Vassileva; Boumediene, Djamel Eddine; Bourdarios, Claire; Bousson, Nicolas; Boutouil, Sara; Boveia, Antonio; Boyd, James; Boyko, Igor; Bracinik, Juraj; Brandt, Andrew; Brandt, Gerhard; Brandt, Oleg; Bratzler, Uwe; Brau, Benjamin; Brau, James; Braun, Helmut; Brazzale, Simone Federico; Brelier, Bertrand; Brendlinger, Kurt; Brennan, Amelia Jean; Brenner, Richard; Bressler, Shikma; Bristow, Kieran; Bristow, Timothy Michael; Britton, Dave; Brochu, Frederic; Brock, Ian; Brock, Raymond; Bromberg, Carl; Bronner, Johanna; Brooijmans, Gustaaf; Brooks, Timothy; Brooks, William; Brosamer, Jacquelyn; Brost, Elizabeth; Brown, Jonathan; Bruckman de Renstrom, Pawel; Bruncko, Dusan; Bruneliere, Renaud; Brunet, Sylvie; Bruni, Alessia; Bruni, Graziano; Bruschi, Marco; Bryngemark, Lene; Buanes, Trygve; Buat, Quentin; Bucci, Francesca; Buchholz, Peter; Buckingham, Ryan; Buckley, Andrew; Buda, Stelian Ioan; Budagov, Ioulian; Buehrer, Felix; Bugge, Lars; Bugge, Magnar Kopangen; Bulekov, Oleg; Bundock, Aaron Colin; Burckhart, Helfried; Burdin, Sergey; Burghgrave, Blake; Burke, Stephen; Burmeister, Ingo; Busato, Emmanuel; Büscher, Daniel; Büscher, Volker; Bussey, Peter; Buszello, Claus-Peter; Butler, Bart; Butler, John; Butt, Aatif Imtiaz; Buttar, Craig; Butterworth, Jonathan; Butti, Pierfrancesco; Buttinger, William; Buzatu, Adrian; Byszewski, Marcin; Cabrera Urbán, Susana; Caforio, Davide; Cakir, Orhan; Calafiura, Paolo; Calandri, Alessandro; Calderini, Giovanni; Calfayan, Philippe; Calkins, Robert; Caloba, Luiz; Calvet, David; Calvet, Samuel; Camacho Toro, Reina; Camarda, Stefano; Cameron, David; Caminada, Lea Michaela; Caminal Armadans, Roger; Campana, Simone; Campanelli, Mario; Campoverde, Angel; Canale, Vincenzo; Canepa, Anadi; Cano Bret, Marc; Cantero, Josu; Cantrill, Robert; Cao, Tingting; Capeans Garrido, Maria Del Mar; Caprini, Irinel; Caprini, Mihai; Capua, Marcella; Caputo, Regina; Cardarelli, Roberto; Carli, Tancredi; Carlino, Gianpaolo; Carminati, Leonardo; Caron, Sascha; Carquin, Edson; Carrillo-Montoya, German D; Carter, Janet; Carvalho, João; Casadei, Diego; Casado, Maria Pilar; Casolino, Mirkoantonio; Castaneda-Miranda, Elizabeth; Castelli, Angelantonio; Castillo Gimenez, Victoria; Castro, Nuno Filipe; Catastini, Pierluigi; Catinaccio, Andrea; Catmore, James; Cattai, Ariella; Cattani, Giordano; Caughron, Seth; Cavaliere, Viviana; Cavalli, Donatella; Cavalli-Sforza, Matteo; Cavasinni, Vincenzo; Ceradini, Filippo; Cerio, Benjamin; Cerny, Karel; Santiago Cerqueira, Augusto; Cerri, Alessandro; Cerrito, Lucio; Cerutti, Fabio; Cerv, Matevz; Cervelli, Alberto; Cetin, Serkant Ali; Chafaq, Aziz; Chakraborty, Dhiman; Chalupkova, Ina; Chang, Philip; Chapleau, Bertrand; Chapman, John Derek; Charfeddine, Driss; Charlton, Dave; Chau, Chav Chhiv; Chavez Barajas, Carlos Alberto; Cheatham, Susan; Chegwidden, Andrew; Chekanov, Sergei; Chekulaev, Sergey; Chelkov, Gueorgui; Chelstowska, Magda Anna; Chen, Chunhui; Chen, Hucheng; Chen, Karen; Chen, Liming; Chen, Shenjian; Chen, Xin; Chen, Yujiao; Cheng, Hok Chuen; Cheng, Yangyang; Cheplakov, Alexander; Cherkaoui El Moursli, Rajaa; Chernyatin, Valeriy; Cheu, Elliott; Chevalier, Laurent; Chiarella, Vitaliano; Chiefari, Giovanni; Childers, John Taylor; Chilingarov, Alexandre; Chiodini, Gabriele; Chisholm, Andrew; Chislett, Rebecca Thalatta; Chitan, Adrian; Chizhov, Mihail; Chouridou, Sofia; Chow, Bonnie Kar Bo; Chromek-Burckhart, Doris; Chu, Ming-Lee; Chudoba, Jiri; Chwastowski, Janusz; Chytka, Ladislav; Ciapetti, Guido; Ciftci, Abbas Kenan; Ciftci, Rena; Cinca, Diane; Cindro, Vladimir; Ciocio, Alessandra; Cirkovic, Predrag; Citron, Zvi Hirsh; Citterio, Mauro; Ciubancan, Mihai; Clark, Allan G; Clark, Philip James; Clarke, Robert; Cleland, Bill; Clemens, Jean-Claude; Clement, Christophe; Coadou, Yann; Cobal, Marina; Coccaro, Andrea; Cochran, James H; Coffey, Laurel; Cogan, Joshua Godfrey; Coggeshall, James; Cole, Brian; Cole, Stephen; Colijn, Auke-Pieter; Collot, Johann; Colombo, Tommaso; Colon, German; Compostella, Gabriele; Conde Muiño, Patricia; Coniavitis, Elias; Conidi, Maria Chiara; Connell, Simon Henry; Connelly, Ian; Consonni, Sofia Maria; Consorti, Valerio; Constantinescu, Serban; Conta, Claudio; Conti, Geraldine; Conventi, Francesco; Cooke, Mark; Cooper, Ben; Cooper-Sarkar, Amanda; Cooper-Smith, Neil; Copic, Katherine; Cornelissen, Thijs; Corradi, Massimo; Corriveau, Francois; Corso-Radu, Alina; Cortes-Gonzalez, Arely; Cortiana, Giorgio; Costa, Giuseppe; Costa, María José; Costanzo, Davide; Côté, David; Cottin, Giovanna; Cowan, Glen; Cox, Brian; Cranmer, Kyle; Cree, Graham; Crépé-Renaudin, Sabine; Crescioli, Francesco; Cribbs, Wayne Allen; Crispin Ortuzar, Mireia; Cristinziani, Markus; Croft, Vince; Crosetti, Giovanni; Cuciuc, Constantin-Mihai; Cuhadar Donszelmann, Tulay; Cummings, Jane; Curatolo, Maria; Cuthbert, Cameron; Czirr, Hendrik; Czodrowski, Patrick; Czyczula, Zofia; D'Auria, Saverio; D'Onofrio, Monica; Da Cunha Sargedas De Sousa, Mario Jose; Da Via, Cinzia; Dabrowski, Wladyslaw; Dafinca, Alexandru; Dai, Tiesheng; Dale, Orjan; Dallaire, Frederick; Dallapiccola, Carlo; Dam, Mogens; Daniells, Andrew Christopher; Dano Hoffmann, Maria; Dao, Valerio; Darbo, Giovanni; Darmora, Smita; Dassoulas, James; Dattagupta, Aparajita; Davey, Will; David, Claire; Davidek, Tomas; Davies, Eleanor; Davies, Merlin; Davignon, Olivier; Davison, Adam; Davison, Peter; Davygora, Yuriy; Dawe, Edmund; Dawson, Ian; Daya-Ishmukhametova, Rozmin; De, Kaushik; de Asmundis, Riccardo; De Castro, Stefano; De Cecco, Sandro; De Groot, Nicolo; de Jong, Paul; De la Torre, Hector; De Lorenzi, Francesco; De Nooij, Lucie; De Pedis, Daniele; De Salvo, Alessandro; De Sanctis, Umberto; De Santo, Antonella; De Vivie De Regie, Jean-Baptiste; Dearnaley, William James; Debbe, Ramiro; Debenedetti, Chiara; Dechenaux, Benjamin; Dedovich, Dmitri; Deigaard, Ingrid; Del Peso, Jose; Del Prete, Tarcisio; Deliot, Frederic; Delitzsch, Chris Malena; Deliyergiyev, Maksym; Dell'Acqua, Andrea; Dell'Asta, Lidia; Dell'Orso, Mauro; Della Pietra, Massimo; della Volpe, Domenico; Delmastro, Marco; Delsart, Pierre-Antoine; Deluca, Carolina; Demers, Sarah; Demichev, Mikhail; Demilly, Aurelien; Denisov, Sergey; Derendarz, Dominik; Derkaoui, Jamal Eddine; Derue, Frederic; Dervan, Paul; Desch, Klaus Kurt; Deterre, Cecile; Deviveiros, Pier-Olivier; Dewhurst, Alastair; Dhaliwal, Saminder; Di Ciaccio, Anna; Di Ciaccio, Lucia; Di Domenico, Antonio; Di Donato, Camilla; Di Girolamo, Alessandro; Di Girolamo, Beniamino; Di Mattia, Alessandro; Di Micco, Biagio; Di Nardo, Roberto; Di Simone, Andrea; Di Sipio, Riccardo; Di Valentino, David; Dias, Flavia; Diaz, Marco Aurelio; Diehl, Edward; Dietrich, Janet; Dietzsch, Thorsten; Diglio, Sara; Dimitrievska, Aleksandra; Dingfelder, Jochen; Dionisi, Carlo; Dita, Petre; Dita, Sanda; Dittus, Fridolin; Djama, Fares; Djobava, Tamar; Barros do Vale, Maria Aline; Do Valle Wemans, André; Doan, Thi Kieu Oanh; Dobos, Daniel; Doglioni, Caterina; Doherty, Tom; Dohmae, Takeshi; Dolejsi, Jiri; Dolezal, Zdenek; Dolgoshein, Boris; Donadelli, Marisilvia; Donati, Simone; Dondero, Paolo; Donini, Julien; Dopke, Jens; Doria, Alessandra; Dova, Maria-Teresa; Doyle, Tony; Dris, Manolis; Dubbert, Jörg; Dube, Sourabh; Dubreuil, Emmanuelle; Duchovni, Ehud; Duckeck, Guenter; Ducu, Otilia Anamaria; Duda, Dominik; Dudarev, Alexey; Dudziak, Fanny; Duflot, Laurent; Duguid, Liam; Dührssen, Michael; Dunford, Monica; Duran Yildiz, Hatice; Düren, Michael; Durglishvili, Archil; Dwuznik, Michal; Dyndal, Mateusz; Ebke, Johannes; Edson, William; Edwards, Nicholas Charles; Ehrenfeld, Wolfgang; Eifert, Till; Eigen, Gerald; Einsweiler, Kevin; Ekelof, Tord; El Kacimi, Mohamed; Ellert, Mattias; Elles, Sabine; Ellinghaus, Frank; Ellis, Nicolas; Elmsheuser, Johannes; Elsing, Markus; Emeliyanov, Dmitry; Enari, Yuji; Endner, Oliver Chris; Endo, Masaki; Engelmann, Roderich; Erdmann, Johannes; Ereditato, Antonio; Eriksson, Daniel; Ernis, Gunar; Ernst, Jesse; Ernst, Michael; Ernwein, Jean; Errede, Deborah; Errede, Steven; Ertel, Eugen; Escalier, Marc; Esch, Hendrik; Escobar, Carlos; Esposito, Bellisario; Etienvre, Anne-Isabelle; Etzion, Erez; Evans, Hal; Ezhilov, Alexey; Fabbri, Laura; Facini, Gabriel; Fakhrutdinov, Rinat; Falciano, Speranza; Falla, Rebecca Jane; Faltova, Jana; Fang, Yaquan; Fanti, Marcello; Farbin, Amir; Farilla, Addolorata; Farooque, Trisha; Farrell, Steven; Farrington, Sinead; Farthouat, Philippe; Fassi, Farida; Fassnacht, Patrick; Fassouliotis, Dimitrios; Favareto, Andrea; Fayard, Louis; Federic, Pavol; Fedin, Oleg; Fedorko, Wojciech; Fehling-Kaschek, Mirjam; Feigl, Simon; Feligioni, Lorenzo; Feng, Cunfeng; Feng, Eric; Feng, Haolu; Fenyuk, Alexander; Fernandez Perez, Sonia; Ferrag, Samir; Ferrando, James; Ferrari, Arnaud; Ferrari, Pamela; Ferrari, Roberto; Ferreira de Lima, Danilo Enoque; Ferrer, Antonio; Ferrere, Didier; Ferretti, Claudio; Ferretto Parodi, Andrea; Fiascaris, Maria; Fiedler, Frank; Filipčič, Andrej; Filipuzzi, Marco; Filthaut, Frank; Fincke-Keeler, Margret; Finelli, Kevin Daniel; Fiolhais, Miguel; Fiorini, Luca; Firan, Ana; Fischer, Adam; Fischer, Julia; Fisher, Wade Cameron; Fitzgerald, Eric Andrew; Flechl, Martin; Fleck, Ivor; Fleischmann, Philipp; Fleischmann, Sebastian; Fletcher, Gareth Thomas; Fletcher, Gregory; Flick, Tobias; Floderus, Anders; Flores Castillo, Luis; Florez Bustos, Andres Carlos; Flowerdew, Michael; Formica, Andrea; Forti, Alessandra; Fortin, Dominique; Fournier, Daniel; Fox, Harald; Fracchia, Silvia; Francavilla, Paolo; Franchini, Matteo; Franchino, Silvia; Francis, David; Franklin, Melissa; Franz, Sebastien; Fraternali, Marco; French, Sky; Friedrich, Conrad; Friedrich, Felix; Froidevaux, Daniel; Frost, James; Fukunaga, Chikara; Fullana Torregrosa, Esteban; Fulsom, Bryan Gregory; Fuster, Juan; Gabaldon, Carolina; Gabizon, Ofir; Gabrielli, Alessandro; Gabrielli, Andrea; Gadatsch, Stefan; Gadomski, Szymon; Gagliardi, Guido; Gagnon, Pauline; Galea, Cristina; Galhardo, Bruno; Gallas, Elizabeth; Gallo, Valentina Santina; Gallop, Bruce; Gallus, Petr; Galster, Gorm Aske Gram Krohn; Gan, KK; Gandrajula, Reddy Pratap; Gao, Jun; Gao, Yongsheng; Garay Walls, Francisca; Garberson, Ford; García, Carmen; García Navarro, José Enrique; Garcia-Sciveres, Maurice; Gardner, Robert; Garelli, Nicoletta; Garonne, Vincent; Gatti, Claudio; Gaudio, Gabriella; Gaur, Bakul; Gauthier, Lea; Gauzzi, Paolo; Gavrilenko, Igor; Gay, Colin; Gaycken, Goetz; Gazis, Evangelos; Ge, Peng; Gecse, Zoltan; Gee, Norman; Geerts, Daniël Alphonsus Adrianus; Geich-Gimbel, Christoph; Gellerstedt, Karl; Gemme, Claudia; Gemmell, Alistair; Genest, Marie-Hélène; Gentile, Simonetta; George, Matthias; George, Simon; Gerbaudo, Davide; Gershon, Avi; Ghazlane, Hamid; Ghodbane, Nabil; Giacobbe, Benedetto; Giagu, Stefano; Giangiobbe, Vincent; Giannetti, Paola; Gianotti, Fabiola; Gibbard, Bruce; Gibson, Stephen; Gilchriese, Murdock; Gillam, Thomas; Gillberg, Dag; Gilles, Geoffrey; Gingrich, Douglas; Giokaris, Nikos; Giordani, MarioPaolo; Giordano, Raffaele; Giorgi, Filippo Maria; Giorgi, Francesco Michelangelo; Giraud, Pierre-Francois; Giugni, Danilo; Giuliani, Claudia; Giulini, Maddalena; Gjelsten, Børge Kile; Gkaitatzis, Stamatios; Gkialas, Ioannis; Gladilin, Leonid; Glasman, Claudia; Glatzer, Julian; Glaysher, Paul; Glazov, Alexandre; Glonti, George; Goblirsch-Kolb, Maximilian; Goddard, Jack Robert; Godfrey, Jennifer; Godlewski, Jan; Goeringer, Christian; Goldfarb, Steven; Golling, Tobias; Golubkov, Dmitry; Gomes, Agostinho; Gomez Fajardo, Luz Stella; Gonçalo, Ricardo; Goncalves Pinto Firmino Da Costa, Joao; Gonella, Laura; González de la Hoz, Santiago; Gonzalez Parra, Garoe; Gonzalez-Sevilla, Sergio; Goossens, Luc; Gorbounov, Petr Andreevich; Gordon, Howard; Gorelov, Igor; Gorini, Benedetto; Gorini, Edoardo; Gorišek, Andrej; Gornicki, Edward; Goshaw, Alfred; Gössling, Claus; Gostkin, Mikhail Ivanovitch; Gouighri, Mohamed; Goujdami, Driss; Goulette, Marc Phillippe; Goussiou, Anna; Goy, Corinne; Gozpinar, Serdar; Grabas, Herve Marie Xavier; Graber, Lars; Grabowska-Bold, Iwona; Grafström, Per; Grahn, Karl-Johan; Gramling, Johanna; Gramstad, Eirik; Grancagnolo, Sergio; Grassi, Valerio; Gratchev, Vadim; Gray, Heather; Graziani, Enrico; Grebenyuk, Oleg; Greenwood, Zeno Dixon; Gregersen, Kristian; Gregor, Ingrid-Maria; Grenier, Philippe; Griffiths, Justin; Grillo, Alexander; Grimm, Kathryn; Grinstein, Sebastian; Gris, Philippe Luc Yves; Grishkevich, Yaroslav; Grivaz, Jean-Francois; Grohs, Johannes Philipp; Grohsjean, Alexander; Gross, Eilam; Grosse-Knetter, Joern; Grossi, Giulio Cornelio; Groth-Jensen, Jacob; Grout, Zara Jane; Guan, Liang; Guescini, Francesco; Guest, Daniel; Gueta, Orel; Guicheney, Christophe; Guido, Elisa; Guillemin, Thibault; Guindon, Stefan; Gul, Umar; Gumpert, Christian; Gunther, Jaroslav; Guo, Jun; Gupta, Shaun; Gutierrez, Phillip; Gutierrez Ortiz, Nicolas Gilberto; Gutschow, Christian; Guttman, Nir; Guyot, Claude; Gwenlan, Claire; Gwilliam, Carl; Haas, Andy; Haber, Carl; Hadavand, Haleh Khani; Haddad, Nacim; Haefner, Petra; Hageböck, Stephan; Hajduk, Zbigniew; Hakobyan, Hrachya; Haleem, Mahsana; Hall, David; Halladjian, Garabed; Hamacher, Klaus; Hamal, Petr; Hamano, Kenji; Hamer, Matthias; Hamilton, Andrew; Hamilton, Samuel; Hamnett, Phillip George; Han, Liang; Hanagaki, Kazunori; Hanawa, Keita; Hance, Michael; Hanke, Paul; Hanna, Remie; Hansen, Jørgen Beck; Hansen, Jorn Dines; Hansen, Peter Henrik; Hara, Kazuhiko; Hard, Andrew; Harenberg, Torsten; Hariri, Faten; Harkusha, Siarhei; Harper, Devin; Harrington, Robert; Harris, Orin; Harrison, Paul Fraser; Hartjes, Fred; Hasegawa, Satoshi; Hasegawa, Yoji; Hasib, A; Hassani, Samira; Haug, Sigve; Hauschild, Michael; Hauser, Reiner; Havranek, Miroslav; Hawkes, Christopher; Hawkings, Richard John; Hawkins, Anthony David; Hayashi, Takayasu; Hayden, Daniel; Hays, Chris; Hayward, Helen; Haywood, Stephen; Head, Simon; Heck, Tobias; Hedberg, Vincent; Heelan, Louise; Heim, Sarah; Heim, Timon; Heinemann, Beate; Heinrich, Lukas; Hejbal, Jiri; Helary, Louis; Heller, Claudio; Heller, Matthieu; Hellman, Sten; Hellmich, Dennis; Helsens, Clement; Henderson, James; Henderson, Robert; Heng, Yang; Hengler, Christopher; Henrichs, Anna; Henriques Correia, Ana Maria; Henrot-Versille, Sophie; Hensel, Carsten; Herbert, Geoffrey Henry; Hernández Jiménez, Yesenia; Herrberg-Schubert, Ruth; Herten, Gregor; Hertenberger, Ralf; Hervas, Luis; Hesketh, Gavin Grant; Hessey, Nigel; Hickling, Robert; Higón-Rodriguez, Emilio; Hill, Ewan; Hill, John; Hiller, Karl Heinz; Hillert, Sonja; Hillier, Stephen; Hinchliffe, Ian; Hines, Elizabeth; Hirose, Minoru; Hirschbuehl, Dominic; Hobbs, John; Hod, Noam; Hodgkinson, Mark; Hodgson, Paul; Hoecker, Andreas; Hoeferkamp, Martin; Hoffman, Julia; Hoffmann, Dirk; Hofmann, Julia Isabell; Hohlfeld, Marc; Holmes, Tova Ray; Hong, Tae Min; Hooft van Huysduynen, Loek; Hostachy, Jean-Yves; Hou, Suen; Hoummada, Abdeslam; Howard, Jacob; Howarth, James; Hrabovsky, Miroslav; Hristova, Ivana; Hrivnac, Julius; Hryn'ova, Tetiana; Hsu, Catherine; Hsu, Pai-hsien Jennifer; Hsu, Shih-Chieh; Hu, Diedi; Hu, Xueye; Huang, Yanping; Hubacek, Zdenek; Hubaut, Fabrice; Huegging, Fabian; Huffman, Todd Brian; Hughes, Emlyn; Hughes, Gareth; Huhtinen, Mika; Hülsing, Tobias Alexander; Hurwitz, Martina; Huseynov, Nazim; Huston, Joey; Huth, John; Iacobucci, Giuseppe; Iakovidis, Georgios; Ibragimov, Iskander; Iconomidou-Fayard, Lydia; Ideal, Emma; Iengo, Paolo; Igonkina, Olga; Iizawa, Tomoya; Ikegami, Yoichi; Ikematsu, Katsumasa; Ikeno, Masahiro; Ilchenko, Iurii; Iliadis, Dimitrios; Ilic, Nikolina; Inamaru, Yuki; Ince, Tayfun; Ioannou, Pavlos; Iodice, Mauro; Iordanidou, Kalliopi; Ippolito, Valerio; Irles Quiles, Adrian; Isaksson, Charlie; Ishino, Masaya; Ishitsuka, Masaki; Ishmukhametov, Renat; Issever, Cigdem; Istin, Serhat; Iturbe Ponce, Julia Mariana; Iuppa, Roberto; Ivarsson, Jenny; Iwanski, Wieslaw; Iwasaki, Hiroyuki; Izen, Joseph; Izzo, Vincenzo; Jackson, Brett; Jackson, Matthew; Jackson, Paul; Jaekel, Martin; Jain, Vivek; Jakobs, Karl; Jakobsen, Sune; Jakoubek, Tomas; Jakubek, Jan; Jamin, David Olivier; Jana, Dilip; Jansen, Eric; Jansen, Hendrik; Janssen, Jens; Janus, Michel; Jarlskog, Göran; Javadov, Namig; Javůrek, Tomáš; Jeanty, Laura; Jejelava, Juansher; Jeng, Geng-yuan; Jennens, David; Jenni, Peter; Jentzsch, Jennifer; Jeske, Carl; Jézéquel, Stéphane; Ji, Haoshuang; Ji, Weina; Jia, Jiangyong; Jiang, Yi; Jimenez Belenguer, Marcos; Jin, Shan; Jinaru, Adam; Jinnouchi, Osamu; Joergensen, Morten Dam; Johansson, Erik; Johansson, Per; Johns, Kenneth; Jon-And, Kerstin; Jones, Graham; Jones, Roger; Jones, Tim; Jongmanns, Jan; Jorge, Pedro; Joshi, Kiran Daniel; Jovicevic, Jelena; Ju, Xiangyang; Jung, Christian; Jungst, Ralph Markus; Jussel, Patrick; Juste Rozas, Aurelio; Kaci, Mohammed; Kaczmarska, Anna; Kado, Marumi; Kagan, Harris; Kagan, Michael; Kajomovitz, Enrique; Kalderon, Charles William; Kama, Sami; Kamenshchikov, Andrey; Kanaya, Naoko; Kaneda, Michiru; Kaneti, Steven; Kantserov, Vadim; Kanzaki, Junichi; Kaplan, Benjamin; Kapliy, Anton; Kar, Deepak; Karakostas, Konstantinos; Karastathis, Nikolaos; Karnevskiy, Mikhail; Karpov, Sergey; Karpova, Zoya; Karthik, Krishnaiyengar; Kartvelishvili, Vakhtang; Karyukhin, Andrey; Kashif, Lashkar; Kasieczka, Gregor; Kass, Richard; Kastanas, Alex; Kataoka, Yousuke; Katre, Akshay; Katzy, Judith; Kaushik, Venkatesh; Kawagoe, Kiyotomo; Kawamoto, Tatsuo; Kawamura, Gen; Kazama, Shingo; Kazanin, Vassili; Kazarinov, Makhail; Keeler, Richard; Kehoe, Robert; Keil, Markus; Keller, John; Kempster, Jacob Julian; Keoshkerian, Houry; Kepka, Oldrich; Kerševan, Borut Paul; Kersten, Susanne; Kessoku, Kohei; Keung, Justin; Khalil-zada, Farkhad; Khandanyan, Hovhannes; Khanov, Alexander; Khodinov, Alexander; Khomich, Andrei; Khoo, Teng Jian; Khoriauli, Gia; Khoroshilov, Andrey; Khovanskiy, Valery; Khramov, Evgeniy; Khubua, Jemal; Kim, Hee Yeun; Kim, Hyeon Jin; Kim, Shinhong; Kimura, Naoki; Kind, Oliver; King, Barry; King, Matthew; King, Robert Steven Beaufoy; King, Samuel Burton; Kirk, Julie; Kiryunin, Andrey; Kishimoto, Tomoe; Kisielewska, Danuta; Kiss, Florian; Kittelmann, Thomas; Kiuchi, Kenji; Kladiva, Eduard; Klein, Max; Klein, Uta; Kleinknecht, Konrad; Klimek, Pawel; Klimentov, Alexei; Klingenberg, Reiner; Klinger, Joel Alexander; Klioutchnikova, Tatiana; Klok, Peter; Kluge, Eike-Erik; Kluit, Peter; Kluth, Stefan; Kneringer, Emmerich; Knoops, Edith; Knue, Andrea; Kobayashi, Dai; Kobayashi, Tomio; Kobel, Michael; Kocian, Martin; Kodys, Peter; Koevesarki, Peter; Koffas, Thomas; Koffeman, Els; Kogan, Lucy Anne; Kohlmann, Simon; Kohout, Zdenek; Kohriki, Takashi; Koi, Tatsumi; Kolanoski, Hermann; Koletsou, Iro; Koll, James; Komar, Aston; Komori, Yuto; Kondo, Takahiko; Kondrashova, Nataliia; Köneke, Karsten; König, Adriaan; König, Sebastian; Kono, Takanori; Konoplich, Rostislav; Konstantinidis, Nikolaos; Kopeliansky, Revital; Koperny, Stefan; Köpke, Lutz; Kopp, Anna Katharina; Korcyl, Krzysztof; Kordas, Kostantinos; Korn, Andreas; Korol, Aleksandr; Korolkov, Ilya; Korolkova, Elena; Korotkov, Vladislav; Kortner, Oliver; Kortner, Sandra; Kostyukhin, Vadim; Kotov, Vladislav; Kotwal, Ashutosh; Kourkoumelis, Christine; Kouskoura, Vasiliki; Koutsman, Alex; Kowalewski, Robert Victor; Kowalski, Tadeusz; Kozanecki, Witold; Kozhin, Anatoly; Kral, Vlastimil; Kramarenko, Viktor; Kramberger, Gregor; Krasnopevtsev, Dimitriy; Krasny, Mieczyslaw Witold; Krasznahorkay, Attila; Kraus, Jana; Kravchenko, Anton; Kreiss, Sven; Kretz, Moritz; Kretzschmar, Jan; Kreutzfeldt, Kristof; Krieger, Peter; Kroeninger, Kevin; Kroha, Hubert; Kroll, Joe; Kroseberg, Juergen; Krstic, Jelena; Kruchonak, Uladzimir; Krüger, Hans; Kruker, Tobias; Krumnack, Nils; Krumshteyn, Zinovii; Kruse, Amanda; Kruse, Mark; Kruskal, Michael; Kubota, Takashi; Kuday, Sinan; Kuehn, Susanne; Kugel, Andreas; Kuhl, Andrew; Kuhl, Thorsten; Kukhtin, Victor; Kulchitsky, Yuri; Kuleshov, Sergey; Kuna, Marine; Kunkle, Joshua; Kupco, Alexander; Kurashige, Hisaya; Kurochkin, Yurii; Kurumida, Rie; Kus, Vlastimil; Kuwertz, Emma Sian; Kuze, Masahiro; Kvita, Jiri; La Rosa, Alessandro; La Rotonda, Laura; Lacasta, Carlos; Lacava, Francesco; Lacey, James; Lacker, Heiko; Lacour, Didier; Lacuesta, Vicente Ramón; Ladygin, Evgueni; Lafaye, Remi; Laforge, Bertrand; Lagouri, Theodota; Lai, Stanley; Laier, Heiko; Lambourne, Luke; Lammers, Sabine; Lampen, Caleb; Lampl, Walter; Lançon, Eric; Landgraf, Ulrich; Landon, Murrough; Lang, Valerie Susanne; Lankford, Andrew; Lanni, Francesco; Lantzsch, Kerstin; Laplace, Sandrine; Lapoire, Cecile; Laporte, Jean-Francois; Lari, Tommaso; Lassnig, Mario; Laurelli, Paolo; Lavrijsen, Wim; Law, Alexander; Laycock, Paul; Le, Bao Tran; Le Dortz, Olivier; Le Guirriec, Emmanuel; Le Menedeu, Eve; LeCompte, Thomas; Ledroit-Guillon, Fabienne Agnes Marie; Lee, Claire Alexandra; Lee, Hurng-Chun; Lee, Jason; Lee, Shih-Chang; Lee, Lawrence; Lefebvre, Guillaume; Lefebvre, Michel; Legger, Federica; Leggett, Charles; Lehan, Allan; Lehmacher, Marc; Lehmann Miotto, Giovanna; Lei, Xiaowen; Leight, William Axel; Leisos, Antonios; Leister, Andrew Gerard; Leite, Marco Aurelio Lisboa; Leitner, Rupert; Lellouch, Daniel; Lemmer, Boris; Leney, Katharine; Lenz, Tatjana; Lenzen, Georg; Lenzi, Bruno; Leone, Robert; Leone, Sandra; Leonhardt, Kathrin; Leonidopoulos, Christos; Leontsinis, Stefanos; Leroy, Claude; Lester, Christopher; Lester, Christopher Michael; Levchenko, Mikhail; Levêque, Jessica; Levin, Daniel; Levinson, Lorne; Levy, Mark; Lewis, Adrian; Lewis, George; Leyko, Agnieszka; Leyton, Michael; Li, Bing; Li, Bo; Li, Haifeng; Li, Ho Ling; Li, Lei; Li, Liang; Li, Shu; Li, Yichen; Liang, Zhijun; Liao, Hongbo; Liberti, Barbara; Lichard, Peter; Lie, Ki; Liebal, Jessica; Liebig, Wolfgang; Limbach, Christian; Limosani, Antonio; Lin, Simon; Lin, Tai-Hua; Linde, Frank; Lindquist, Brian Edward; Linnemann, James; Lipeles, Elliot; Lipniacka, Anna; Lisovyi, Mykhailo; Liss, Tony; Lissauer, David; Lister, Alison; Litke, Alan; Liu, Bo; Liu, Dong; Liu, Jianbei; Liu, Kun; Liu, Lulu; Liu, Miaoyuan; Liu, Minghui; Liu, Yanwen; Livan, Michele; Livermore, Sarah; Lleres, Annick; Llorente Merino, Javier; Lloyd, Stephen; Lo Sterzo, Francesco; Lobodzinska, Ewelina; Loch, Peter; Lockman, William; Loddenkoetter, Thomas; Loebinger, Fred; Loevschall-Jensen, Ask Emil; Loginov, Andrey; Loh, Chang Wei; Lohse, Thomas; Lohwasser, Kristin; Lokajicek, Milos; Lombardo, Vincenzo Paolo; Long, Brian Alexander; Long, Jonathan; Long, Robin Eamonn; Lopes, Lourenco; Lopez Mateos, David; Lopez Paredes, Brais; Lopez Paz, Ivan; Lorenz, Jeanette; Lorenzo Martinez, Narei; Losada, Marta; Loscutoff, Peter; Lou, XinChou; Lounis, Abdenour; Love, Jeremy; Love, Peter; Lowe, Andrew; Lu, Feng; Lubatti, Henry; Luci, Claudio; Lucotte, Arnaud; Luehring, Frederick; Lukas, Wolfgang; Luminari, Lamberto; Lundberg, Olof; Lund-Jensen, Bengt; Lungwitz, Matthias; Lynn, David; Lysak, Roman; Lytken, Else; Ma, Hong; Ma, Lian Liang; Maccarrone, Giovanni; Macchiolo, Anna; Machado Miguens, Joana; Macina, Daniela; Madaffari, Daniele; Madar, Romain; Maddocks, Harvey Jonathan; Mader, Wolfgang; Madsen, Alexander; Maeno, Mayuko; Maeno, Tadashi; Magradze, Erekle; Mahboubi, Kambiz; Mahlstedt, Joern; Mahmoud, Sara; Maiani, Camilla; Maidantchik, Carmen; Maier, Andreas Alexander; Maio, Amélia; Majewski, Stephanie; Makida, Yasuhiro; Makovec, Nikola; Mal, Prolay; Malaescu, Bogdan; Malecki, Pawel; Maleev, Victor; Malek, Fairouz; Mallik, Usha; Malon, David; Malone, Caitlin; Maltezos, Stavros; Malyshev, Vladimir; Malyukov, Sergei; Mamuzic, Judita; Mandelli, Beatrice; Mandelli, Luciano; Mandić, Igor; Mandrysch, Rocco; Maneira, José; Manfredini, Alessandro; Manhaes de Andrade Filho, Luciano; Manjarres Ramos, Joany Andreina; Mann, Alexander; Manning, Peter; Manousakis-Katsikakis, Arkadios; Mansoulie, Bruno; Mantifel, Rodger; Mapelli, Livio; March, Luis; Marchand, Jean-Francois; Marchiori, Giovanni; Marcisovsky, Michal; Marino, Christopher; Marjanovic, Marija; Marques, Carlos; Marroquim, Fernando; Marsden, Stephen Philip; Marshall, Zach; Marti, Lukas Fritz; Marti-Garcia, Salvador; Martin, Brian; Martin, Brian Thomas; Martin, Tim; Martin, Victoria Jane; Martin dit Latour, Bertrand; Martinez, Homero; Martinez, Mario; Martin-Haugh, Stewart; Martyniuk, Alex; Marx, Marilyn; Marzano, Francesco; Marzin, Antoine; Masetti, Lucia; Mashimo, Tetsuro; Mashinistov, Ruslan; Masik, Jiri; Maslennikov, Alexey; Massa, Ignazio; Massol, Nicolas; Mastrandrea, Paolo; Mastroberardino, Anna; Masubuchi, Tatsuya; Mättig, Peter; Mattmann, Johannes; Maurer, Julien; Maxfield, Stephen; Maximov, Dmitriy; Mazini, Rachid; Mazzaferro, Luca; Mc Goldrick, Garrin; Mc Kee, Shawn Patrick; McCarn, Allison; McCarthy, Robert; McCarthy, Tom; McCubbin, Norman; McFarlane, Kenneth; Mcfayden, Josh; Mchedlidze, Gvantsa; McMahon, Steve; McPherson, Robert; Meade, Andrew; Mechnich, Joerg; Medinnis, Michael; Meehan, Samuel; Mehlhase, Sascha; Mehta, Andrew; Meier, Karlheinz; Meineck, Christian; Meirose, Bernhard; Melachrinos, Constantinos; Mellado Garcia, Bruce Rafael; Meloni, Federico; Mengarelli, Alberto; Menke, Sven; Meoni, Evelin; Mercurio, Kevin Michael; Mergelmeyer, Sebastian; Meric, Nicolas; Mermod, Philippe; Merola, Leonardo; Meroni, Chiara; Merritt, Frank; Merritt, Hayes; Messina, Andrea; Metcalfe, Jessica; Mete, Alaettin Serhan; Meyer, Carsten; Meyer, Christopher; Meyer, Jean-Pierre; Meyer, Jochen; Middleton, Robin; Migas, Sylwia; Mijović, Liza; Mikenberg, Giora; Mikestikova, Marcela; Mikuž, Marko; Milic, Adriana; Miller, David; Mills, Corrinne; Milov, Alexander; Milstead, David; Milstein, Dmitry; Minaenko, Andrey; Minashvili, Irakli; Mincer, Allen; Mindur, Bartosz; Mineev, Mikhail; Ming, Yao; Mir, Lluisa-Maria; Mirabelli, Giovanni; Mitani, Takashi; Mitrevski, Jovan; Mitsou, Vasiliki A; Mitsui, Shingo; Miucci, Antonio; Miyagawa, Paul; Mjörnmark, Jan-Ulf; Moa, Torbjoern; Mochizuki, Kazuya; Mohapatra, Soumya; Mohr, Wolfgang; Molander, Simon; Moles-Valls, Regina; Mönig, Klaus; Monini, Caterina; Monk, James; Monnier, Emmanuel; Montejo Berlingen, Javier; Monticelli, Fernando; Monzani, Simone; Moore, Roger; Moraes, Arthur; Morange, Nicolas; Moreno, Deywis; Moreno Llácer, María; Morettini, Paolo; Morgenstern, Marcus; Morii, Masahiro; Moritz, Sebastian; Morley, Anthony Keith; Mornacchi, Giuseppe; Morris, John; Morvaj, Ljiljana; Moser, Hans-Guenther; Mosidze, Maia; Moss, Josh; Motohashi, Kazuki; Mount, Richard; Mountricha, Eleni; Mouraviev, Sergei; Moyse, Edward; Muanza, Steve; Mudd, Richard; Mueller, Felix; Mueller, James; Mueller, Klemens; Mueller, Thibaut; Mueller, Timo; Muenstermann, Daniel; Munwes, Yonathan; Murillo Quijada, Javier Alberto; Murray, Bill; Musheghyan, Haykuhi; Musto, Elisa; Myagkov, Alexey; Myska, Miroslav; Nackenhorst, Olaf; Nadal, Jordi; Nagai, Koichi; Nagai, Ryo; Nagai, Yoshikazu; Nagano, Kunihiro; Nagarkar, Advait; Nagasaka, Yasushi; Nagel, Martin; Nairz, Armin Michael; Nakahama, Yu; Nakamura, Koji; Nakamura, Tomoaki; Nakano, Itsuo; Namasivayam, Harisankar; Nanava, Gizo; Narayan, Rohin; Nattermann, Till; Naumann, Thomas; Navarro, Gabriela; Nayyar, Ruchika; Neal, Homer; Nechaeva, Polina; Neep, Thomas James; Nef, Pascal Daniel; Negri, Andrea; Negri, Guido; Negrini, Matteo; Nektarijevic, Snezana; Nelson, Andrew; Nelson, Timothy Knight; Nemecek, Stanislav; Nemethy, Peter; Nepomuceno, Andre Asevedo; Nessi, Marzio; Neubauer, Mark; Neumann, Manuel; Neves, Ricardo; Nevski, Pavel; Newman, Paul; Nguyen, Duong Hai; Nickerson, Richard; Nicolaidou, Rosy; Nicquevert, Bertrand; Nielsen, Jason; Nikiforou, Nikiforos; Nikiforov, Andriy; Nikolaenko, Vladimir; Nikolic-Audit, Irena; Nikolics, Katalin; Nikolopoulos, Konstantinos; Nilsson, Paul; Ninomiya, Yoichi; Nisati, Aleandro; Nisius, Richard; Nobe, Takuya; Nodulman, Lawrence; Nomachi, Masaharu; Nomidis, Ioannis; Norberg, Scarlet; Nordberg, Markus; Novgorodova, Olga; Nowak, Sebastian; Nozaki, Mitsuaki; Nozka, Libor; Ntekas, Konstantinos; Nunes Hanninger, Guilherme; Nunnemann, Thomas; Nurse, Emily; Nuti, Francesco; O'Brien, Brendan Joseph; O'grady, Fionnbarr; O'Neil, Dugan; O'Shea, Val; Oakham, Gerald; Oberlack, Horst; Obermann, Theresa; Ocariz, Jose; Ochi, Atsuhiko; Ochoa, Ines; Oda, Susumu; Odaka, Shigeru; Ogren, Harold; Oh, Alexander; Oh, Seog; Ohm, Christian; Ohman, Henrik; Ohshima, Takayoshi; Okamura, Wataru; Okawa, Hideki; Okumura, Yasuyuki; Okuyama, Toyonobu; Olariu, Albert; Olchevski, Alexander; Olivares Pino, Sebastian Andres; Oliveira Damazio, Denis; Oliver Garcia, Elena; Olszewski, Andrzej; Olszowska, Jolanta; Onofre, António; Onyisi, Peter; Oram, Christopher; Oreglia, Mark; Oren, Yona; Orestano, Domizia; Orlando, Nicola; Oropeza Barrera, Cristina; Orr, Robert; Osculati, Bianca; Ospanov, Rustem; Otero y Garzon, Gustavo; Otono, Hidetoshi; Ouchrif, Mohamed; Ouellette, Eric; Ould-Saada, Farid; Ouraou, Ahmimed; Oussoren, Koen Pieter; Ouyang, Qun; Ovcharova, Ana; Owen, Mark; Ozcan, Veysi Erkcan; Ozturk, Nurcan; Pachal, Katherine; Pacheco Pages, Andres; Padilla Aranda, Cristobal; Pagáčová, Martina; Pagan Griso, Simone; Paganis, Efstathios; Pahl, Christoph; Paige, Frank; Pais, Preema; Pajchel, Katarina; Palacino, Gabriel; Palestini, Sandro; Palka, Marek; Pallin, Dominique; Palma, Alberto; Palmer, Jody; Pan, Yibin; Panagiotopoulou, Evgenia; Panduro Vazquez, William; Pani, Priscilla; Panikashvili, Natalia; Panitkin, Sergey; Pantea, Dan; Paolozzi, Lorenzo; Papadopoulou, Theodora; Papageorgiou, Konstantinos; Paramonov, Alexander; Paredes Hernandez, Daniela; Parker, Michael Andrew; Parodi, Fabrizio; Parsons, John; Parzefall, Ulrich; Pasqualucci, Enrico; Passaggio, Stefano; Passeri, Antonio; Pastore, Fernanda; Pastore, Francesca; Pásztor, Gabriella; Pataraia, Sophio; Patel, Nikhul; Pater, Joleen; Patricelli, Sergio; Pauly, Thilo; Pearce, James; Pedersen, Maiken; Pedraza Lopez, Sebastian; Pedro, Rute; Peleganchuk, Sergey; Pelikan, Daniel; Peng, Haiping; Penning, Bjoern; Penwell, John; Perepelitsa, Dennis; Perez Codina, Estel; Pérez García-Estañ, María Teresa; Perez Reale, Valeria; Perini, Laura; Pernegger, Heinz; Perrino, Roberto; Peschke, Richard; Peshekhonov, Vladimir; Peters, Krisztian; Peters, Yvonne; Petersen, Brian; Petersen, Troels; Petit, Elisabeth; Petridis, Andreas; Petridou, Chariclia; Petrolo, Emilio; Petrucci, Fabrizio; Pettersson, Nora Emilia; Pezoa, Raquel; Phillips, Peter William; Piacquadio, Giacinto; Pianori, Elisabetta; Picazio, Attilio; Piccaro, Elisa; Piccinini, Maurizio; Piegaia, Ricardo; Pignotti, David; Pilcher, James; Pilkington, Andrew; Pina, João Antonio; Pinamonti, Michele; Pinder, Alex; Pinfold, James; Pingel, Almut; Pinto, Belmiro; Pires, Sylvestre; Pitt, Michael; Pizio, Caterina; Plazak, Lukas; Pleier, Marc-Andre; Pleskot, Vojtech; Plotnikova, Elena; Plucinski, Pawel; Poddar, Sahill; Podlyski, Fabrice; Poettgen, Ruth; Poggioli, Luc; Pohl, David-leon; Pohl, Martin; Polesello, Giacomo; Policicchio, Antonio; Polifka, Richard; Polini, Alessandro; Pollard, Christopher Samuel; Polychronakos, Venetios; Pommès, Kathy; Pontecorvo, Ludovico; Pope, Bernard; Popeneciu, Gabriel Alexandru; Popovic, Dragan; Poppleton, Alan; Portell Bueso, Xavier; Pospisil, Stanislav; Potamianos, Karolos; Potrap, Igor; Potter, Christina; Potter, Christopher; Poulard, Gilbert; Poveda, Joaquin; Pozdnyakov, Valery; Pralavorio, Pascal; Pranko, Aliaksandr; Prasad, Srivas; Pravahan, Rishiraj; Prell, Soeren; Price, Darren; Price, Joe; Price, Lawrence; Prieur, Damien; Primavera, Margherita; Proissl, Manuel; Prokofiev, Kirill; Prokoshin, Fedor; Protopapadaki, Eftychia-sofia; Protopopescu, Serban; Proudfoot, James; Przybycien, Mariusz; Przysiezniak, Helenka; Ptacek, Elizabeth; Puddu, Daniele; Pueschel, Elisa; Puldon, David; Purohit, Milind; Puzo, Patrick; Qian, Jianming; Qin, Gang; Qin, Yang; Quadt, Arnulf; Quarrie, David; Quayle, William; Queitsch-Maitland, Michaela; Quilty, Donnchadha; Qureshi, Anum; Radeka, Veljko; Radescu, Voica; Radhakrishnan, Sooraj Krishnan; Radloff, Peter; Rados, Pere; Ragusa, Francesco; Rahal, Ghita; Rajagopalan, Srinivasan; Rammensee, Michael; Randle-Conde, Aidan Sean; Rangel-Smith, Camila; Rao, Kanury; Rauscher, Felix; Rave, Tobias Christian; Ravenscroft, Thomas; Raymond, Michel; Read, Alexander Lincoln; Readioff, Nathan Peter; Rebuzzi, Daniela; Redelbach, Andreas; Redlinger, George; Reece, Ryan; Reeves, Kendall; Rehnisch, Laura; Reisin, Hernan; Relich, Matthew; Rembser, Christoph; Ren, Huan; Ren, Zhongliang; Renaud, Adrien; Rescigno, Marco; Resconi, Silvia; Rezanova, Olga; Reznicek, Pavel; Rezvani, Reyhaneh; Richter, Robert; Ridel, Melissa; Rieck, Patrick; Rieger, Julia; Rijssenbeek, Michael; Rimoldi, Adele; Rinaldi, Lorenzo; Ritsch, Elmar; Riu, Imma; Rizatdinova, Flera; Rizvi, Eram; Robertson, Steven; Robichaud-Veronneau, Andree; Robinson, Dave; Robinson, James; Robson, Aidan; Roda, Chiara; Rodrigues, Luis; Roe, Shaun; Røhne, Ole; Rolli, Simona; Romaniouk, Anatoli; Romano, Marino; Romero Adam, Elena; Rompotis, Nikolaos; Roos, Lydia; Ros, Eduardo; Rosati, Stefano; Rosbach, Kilian; Rose, Matthew; Rosendahl, Peter Lundgaard; Rosenthal, Oliver; Rossetti, Valerio; Rossi, Elvira; Rossi, Leonardo Paolo; Rosten, Rachel; Rotaru, Marina; Roth, Itamar; Rothberg, Joseph; Rousseau, David; Royon, Christophe; Rozanov, Alexandre; Rozen, Yoram; Ruan, Xifeng; Rubbo, Francesco; Rubinskiy, Igor; Rud, Viacheslav; Rudolph, Christian; Rudolph, Matthew Scott; Rühr, Frederik; Ruiz-Martinez, Aranzazu; Rurikova, Zuzana; Rusakovich, Nikolai; Ruschke, Alexander; Rutherfoord, John; Ruthmann, Nils; Ryabov, Yury; Rybar, Martin; Rybkin, Grigori; Ryder, Nick; Saavedra, Aldo; Sacerdoti, Sabrina; Saddique, Asif; Sadeh, Iftach; Sadrozinski, Hartmut; Sadykov, Renat; Safai Tehrani, Francesco; Sakamoto, Hiroshi; Sakurai, Yuki; Salamanna, Giuseppe; Salamon, Andrea; Saleem, Muhammad; Salek, David; Sales De Bruin, Pedro Henrique; Salihagic, Denis; Salnikov, Andrei; Salt, José; Salvachua Ferrando, Belén; Salvatore, Daniela; Salvatore, Pasquale Fabrizio; Salvucci, Antonio; Salzburger, Andreas; Sampsonidis, Dimitrios; Sanchez, Arturo; Sánchez, Javier; Sanchez Martinez, Victoria; Sandaker, Heidi; Sandbach, Ruth Laura; Sander, Heinz Georg; Sanders, Michiel; Sandhoff, Marisa; Sandoval, Tanya; Sandoval, Carlos; Sandstroem, Rikard; Sankey, Dave; Sansoni, Andrea; Santoni, Claudio; Santonico, Rinaldo; Santos, Helena; Santoyo Castillo, Itzebelt; Sapp, Kevin; Sapronov, Andrey; Saraiva, João; Sarrazin, Bjorn; Sartisohn, Georg; Sasaki, Osamu; Sasaki, Yuichi; Sauvage, Gilles; Sauvan, Emmanuel; Savard, Pierre; Savu, Dan Octavian; Sawyer, Craig; Sawyer, Lee; Saxon, David; Saxon, James; Sbarra, Carla; Sbrizzi, Antonio; Scanlon, Tim; Scannicchio, Diana; Scarcella, Mark; Scarfone, Valerio; Schaarschmidt, Jana; Schacht, Peter; Schaefer, Douglas; Schaefer, Ralph; Schaepe, Steffen; Schaetzel, Sebastian; Schäfer, Uli; Schaffer, Arthur; Schaile, Dorothee; Schamberger, R. Dean; Scharf, Veit; Schegelsky, Valery; Scheirich, Daniel; Schernau, Michael; Scherzer, Max; Schiavi, Carlo; Schieck, Jochen; Schillo, Christian; Schioppa, Marco; Schlenker, Stefan; Schmidt, Evelyn; Schmieden, Kristof; Schmitt, Christian; Schmitt, Christopher; Schmitt, Sebastian; Schneider, Basil; Schnellbach, Yan Jie; Schnoor, Ulrike; Schoeffel, Laurent; Schoening, Andre; Schoenrock, Bradley Daniel; Schorlemmer, Andre Lukas; Schott, Matthias; Schouten, Doug; Schovancova, Jaroslava; Schramm, Steven; Schreyer, Manuel; Schroeder, Christian; Schuh, Natascha; Schultens, Martin Johannes; Schultz-Coulon, Hans-Christian; Schulz, Holger; Schumacher, Markus; Schumm, Bruce; Schune, Philippe; Schwanenberger, Christian; Schwartzman, Ariel; Schwegler, Philipp; Schwemling, Philippe; Schwienhorst, Reinhard; Schwindling, Jerome; Schwindt, Thomas; Schwoerer, Maud; Sciacca, Gianfranco; Scifo, Estelle; Sciolla, Gabriella; Scott, Bill; Scuri, Fabrizio; Scutti, Federico; Searcy, Jacob; Sedov, George; Sedykh, Evgeny; Seidel, Sally; Seiden, Abraham; Seifert, Frank; Seixas, José; Sekhniaidze, Givi; Sekula, Stephen; Selbach, Karoline Elfriede; Seliverstov, Dmitry; Sellers, Graham; Semprini-Cesari, Nicola; Serfon, Cedric; Serin, Laurent; Serkin, Leonid; Serre, Thomas; Seuster, Rolf; Severini, Horst; Sfiligoj, Tina; Sforza, Federico; Sfyrla, Anna; Shabalina, Elizaveta; Shamim, Mansoora; Shan, Lianyou; Shang, Ruo-yu; Shank, James; Shapiro, Marjorie; Shatalov, Pavel; Shaw, Kate; Shehu, Ciwake Yusufu; Sherwood, Peter; Shi, Liaoshan; Shimizu, Shima; Shimmin, Chase Owen; Shimojima, Makoto; Shiyakova, Mariya; Shmeleva, Alevtina; Shochet, Mel; Short, Daniel; Shrestha, Suyog; Shulga, Evgeny; Shupe, Michael; Shushkevich, Stanislav; Sicho, Petr; Sidiropoulou, Ourania; Sidorov, Dmitri; Sidoti, Antonio; Siegert, Frank; Sijacki, Djordje; Silva, José; Silver, Yiftah; Silverstein, Daniel; Silverstein, Samuel; Simak, Vladislav; Simard, Olivier; Simic, Ljiljana; Simion, Stefan; Simioni, Eduard; Simmons, Brinick; Simoniello, Rosa; Simonyan, Margar; Sinervo, Pekka; Sinev, Nikolai; Sipica, Valentin; Siragusa, Giovanni; Sircar, Anirvan; Sisakyan, Alexei; Sivoklokov, Serguei; Sjölin, Jörgen; Sjursen, Therese; Skottowe, Hugh Philip; Skovpen, Kirill; Skubic, Patrick; Slater, Mark; Slavicek, Tomas; Sliwa, Krzysztof; Smakhtin, Vladimir; Smart, Ben; Smestad, Lillian; Smirnov, Sergei; Smirnov, Yury; Smirnova, Lidia; Smirnova, Oxana; Smith, Kenway; Smizanska, Maria; Smolek, Karel; Snesarev, Andrei; Snidero, Giacomo; Snyder, Scott; Sobie, Randall; Socher, Felix; Soffer, Abner; Soh, Dart-yin; Solans, Carlos; Solar, Michael; Solc, Jaroslav; Soldatov, Evgeny; Soldevila, Urmila; Solfaroli Camillocci, Elena; Solodkov, Alexander; Soloshenko, Alexei; Solovyanov, Oleg; Solovyev, Victor; Sommer, Philip; Song, Hong Ye; Soni, Nitesh; Sood, Alexander; Sopczak, Andre; Sopko, Bruno; Sopko, Vit; Sorin, Veronica; Sosebee, Mark; Soualah, Rachik; Soueid, Paul; Soukharev, Andrey; South, David; Spagnolo, Stefania; Spanò, Francesco; Spearman, William Robert; Spettel, Fabian; Spighi, Roberto; Spigo, Giancarlo; Spousta, Martin; Spreitzer, Teresa; Spurlock, Barry; St Denis, Richard Dante; Staerz, Steffen; Stahlman, Jonathan; Stamen, Rainer; Stanecka, Ewa; Stanek, Robert; Stanescu, Cristian; Stanescu-Bellu, Madalina; Stanitzki, Marcel Michael; Stapnes, Steinar; Starchenko, Evgeny; Stark, Jan; Staroba, Pavel; Starovoitov, Pavel; Staszewski, Rafal; Stavina, Pavel; Steinberg, Peter; Stelzer, Bernd; Stelzer, Harald Joerg; Stelzer-Chilton, Oliver; Stenzel, Hasko; Stern, Sebastian; Stewart, Graeme; Stillings, Jan Andre; Stockton, Mark; Stoebe, Michael; Stoicea, Gabriel; Stolte, Philipp; Stonjek, Stefan; Stradling, Alden; Straessner, Arno; Stramaglia, Maria Elena; Strandberg, Jonas; Strandberg, Sara; Strandlie, Are; Strauss, Emanuel; Strauss, Michael; Strizenec, Pavol; Ströhmer, Raimund; Strom, David; Stroynowski, Ryszard; Stucci, Stefania Antonia; Stugu, Bjarne; Styles, Nicholas Adam; Su, Dong; Su, Jun; Subramania, Halasya Siva; Subramaniam, Rajivalochan; Succurro, Antonella; Sugaya, Yorihito; Suhr, Chad; Suk, Michal; Sulin, Vladimir; Sultansoy, Saleh; Sumida, Toshi; Sun, Xiaohu; Sundermann, Jan Erik; Suruliz, Kerim; Susinno, Giancarlo; Sutton, Mark; Suzuki, Yu; Svatos, Michal; Swedish, Stephen; Swiatlowski, Maximilian; Sykora, Ivan; Sykora, Tomas; Ta, Duc; Taccini, Cecilia; Tackmann, Kerstin; Taenzer, Joe; Taffard, Anyes; Tafirout, Reda; Taiblum, Nimrod; Takahashi, Yuta; Takai, Helio; Takashima, Ryuichi; Takeda, Hiroshi; Takeshita, Tohru; Takubo, Yosuke; Talby, Mossadek; Talyshev, Alexey; Tam, Jason; Tan, Kong Guan; Tanaka, Junichi; Tanaka, Reisaburo; Tanaka, Satoshi; Tanaka, Shuji; Tanasijczuk, Andres Jorge; Tannenwald, Benjamin Bordy; Tannoury, Nancy; Tapprogge, Stefan; Tarem, Shlomit; Tarrade, Fabien; Tartarelli, Giuseppe Francesco; Tas, Petr; Tasevsky, Marek; Tashiro, Takuya; Tassi, Enrico; Tavares Delgado, Ademar; Tayalati, Yahya; Taylor, Frank; Taylor, Geoffrey; Taylor, Wendy; Teischinger, Florian Alfred; Teixeira Dias Castanheira, Matilde; Teixeira-Dias, Pedro; Temming, Kim Katrin; Ten Kate, Herman; Teng, Ping-Kun; Teoh, Jia Jian; Terada, Susumu; Terashi, Koji; Terron, Juan; Terzo, Stefano; Testa, Marianna; Teuscher, Richard; Therhaag, Jan; Theveneaux-Pelzer, Timothée; Thomas, Juergen; Thomas-Wilsker, Joshuha; Thompson, Emily; Thompson, Paul; Thompson, Peter; Thompson, Stan; Thomsen, Lotte Ansgaard; Thomson, Evelyn; Thomson, Mark; Thong, Wai Meng; Thun, Rudolf; Tian, Feng; Tibbetts, Mark James; Tikhomirov, Vladimir; Tikhonov, Yury; Timoshenko, Sergey; Tiouchichine, Elodie; Tipton, Paul; Tisserant, Sylvain; Todorov, Theodore; Todorova-Nova, Sharka; Toggerson, Brokk; Tojo, Junji; Tokár, Stanislav; Tokushuku, Katsuo; Tollefson, Kirsten; Tomlinson, Lee; Tomoto, Makoto; Tompkins, Lauren; Toms, Konstantin; Topilin, Nikolai; Torrence, Eric; Torres, Heberth; Torró Pastor, Emma; Toth, Jozsef; Touchard, Francois; Tovey, Daniel; Tran, Huong Lan; Trefzger, Thomas; Tremblet, Louis; Tricoli, Alessandro; Trigger, Isabel Marian; Trincaz-Duvoid, Sophie; Tripiana, Martin; Triplett, Nathan; Trischuk, William; Trocmé, Benjamin; Troncon, Clara; Trottier-McDonald, Michel; Trovatelli, Monica; True, Patrick; Trzebinski, Maciej; Trzupek, Adam; Tsarouchas, Charilaos; Tseng, Jeffrey; Tsiareshka, Pavel; Tsionou, Dimitra; Tsipolitis, Georgios; Tsirintanis, Nikolaos; Tsiskaridze, Shota; Tsiskaridze, Vakhtang; Tskhadadze, Edisher; Tsukerman, Ilya; Tsulaia, Vakhtang; Tsuno, Soshi; Tsybychev, Dmitri; Tudorache, Alexandra; Tudorache, Valentina; Tuna, Alexander Naip; Tupputi, Salvatore; Turchikhin, Semen; Turecek, Daniel; Turk Cakir, Ilkay; Turra, Ruggero; Tuts, Michael; Tykhonov, Andrii; Tylmad, Maja; Tyndel, Mike; Uchida, Kirika; Ueda, Ikuo; Ueno, Ryuichi; Ughetto, Michael; Ugland, Maren; Uhlenbrock, Mathias; Ukegawa, Fumihiko; Unal, Guillaume; Undrus, Alexander; Unel, Gokhan; Ungaro, Francesca; Unno, Yoshinobu; Urbaniec, Dustin; Urquijo, Phillip; Usai, Giulio; Usanova, Anna; Vacavant, Laurent; Vacek, Vaclav; Vachon, Brigitte; Valencic, Nika; Valentinetti, Sara; Valero, Alberto; Valery, Loic; Valkar, Stefan; Valladolid Gallego, Eva; Vallecorsa, Sofia; Valls Ferrer, Juan Antonio; Van Den Wollenberg, Wouter; Van Der Deijl, Pieter; van der Geer, Rogier; van der Graaf, Harry; Van Der Leeuw, Robin; van der Ster, Daniel; van Eldik, Niels; van Gemmeren, Peter; Van Nieuwkoop, Jacobus; van Vulpen, Ivo; van Woerden, Marius Cornelis; Vanadia, Marco; Vandelli, Wainer; Vanguri, Rami; Vaniachine, Alexandre; Vankov, Peter; Vannucci, Francois; Vardanyan, Gagik; Vari, Riccardo; Varnes, Erich; Varol, Tulin; Varouchas, Dimitris; Vartapetian, Armen; Varvell, Kevin; Vazeille, Francois; Vazquez Schroeder, Tamara; Veatch, Jason; Veloso, Filipe; Veneziano, Stefano; Ventura, Andrea; Ventura, Daniel; Venturi, Manuela; Venturi, Nicola; Venturini, Alessio; Vercesi, Valerio; Verducci, Monica; Verkerke, Wouter; Vermeulen, Jos; Vest, Anja; Vetterli, Michel; Viazlo, Oleksandr; Vichou, Irene; Vickey, Trevor; Vickey Boeriu, Oana Elena; Viehhauser, Georg; Viel, Simon; Vigne, Ralph; Villa, Mauro; Villaplana Perez, Miguel; Vilucchi, Elisabetta; Vincter, Manuella; Vinogradov, Vladimir; Virzi, Joseph; Vivarelli, Iacopo; Vives Vaque, Francesc; Vlachos, Sotirios; Vladoiu, Dan; Vlasak, Michal; Vogel, Adrian; Vogel, Marcelo; Vokac, Petr; Volpi, Guido; Volpi, Matteo; von der Schmitt, Hans; von Radziewski, Holger; von Toerne, Eckhard; Vorobel, Vit; Vorobev, Konstantin; Vos, Marcel; Voss, Rudiger; Vossebeld, Joost; Vranjes, Nenad; Vranjes Milosavljevic, Marija; Vrba, Vaclav; Vreeswijk, Marcel; Vu Anh, Tuan; Vuillermet, Raphael; Vukotic, Ilija; Vykydal, Zdenek; Wagner, Peter; Wagner, Wolfgang; Wahlberg, Hernan; Wahrmund, Sebastian; Wakabayashi, Jun; Walder, James; Walker, Rodney; Walkowiak, Wolfgang; Wall, Richard; Waller, Peter; Walsh, Brian; Wang, Chao; Wang, Chiho; Wang, Fuquan; Wang, Haichen; Wang, Hulin; Wang, Jike; Wang, Jin; Wang, Kuhan; Wang, Rui; Wang, Song-Ming; Wang, Tan; Wang, Xiaoxiao; Wanotayaroj, Chaowaroj; Warburton, Andreas; Ward, Patricia; Wardrope, David Robert; Warsinsky, Markus; Washbrook, Andrew; Wasicki, Christoph; Watkins, Peter; Watson, Alan; Watson, Ian; Watson, Miriam; Watts, Gordon; Watts, Stephen; Waugh, Ben; Webb, Samuel; Weber, Michele; Weber, Stefan Wolf; Webster, Jordan S; Weidberg, Anthony; Weigell, Philipp; Weinert, Benjamin; Weingarten, Jens; Weiser, Christian; Weits, Hartger; Wells, Phillippa; Wenaus, Torre; Wendland, Dennis; Weng, Zhili; Wengler, Thorsten; Wenig, Siegfried; Wermes, Norbert; Werner, Matthias; Werner, Per; Wessels, Martin; Wetter, Jeffrey; Whalen, Kathleen; White, Andrew; White, Martin; White, Ryan; White, Sebastian; Whiteson, Daniel; Wicke, Daniel; Wickens, Fred; Wiedenmann, Werner; Wielers, Monika; Wienemann, Peter; Wiglesworth, Craig; Wiik-Fuchs, Liv Antje Mari; Wijeratne, Peter Alexander; Wildauer, Andreas; Wildt, Martin Andre; Wilkens, Henric George; Will, Jonas Zacharias; Williams, Hugh; Williams, Sarah; Willis, Christopher; Willocq, Stephane; Wilson, Alan; Wilson, John; Wingerter-Seez, Isabelle; Winklmeier, Frank; Winter, Benedict Tobias; Wittgen, Matthias; Wittig, Tobias; Wittkowski, Josephine; Wollstadt, Simon Jakob; Wolter, Marcin Wladyslaw; Wolters, Helmut; Wosiek, Barbara; Wotschack, Jorg; Woudstra, Martin; Wozniak, Krzysztof; Wright, Michael; Wu, Mengqing; Wu, Sau Lan; Wu, Xin; Wu, Yusheng; Wulf, Evan; Wyatt, Terry Richard; Wynne, Benjamin; Xella, Stefania; Xiao, Meng; Xu, Da; Xu, Lailin; Yabsley, Bruce; Yacoob, Sahal; Yamada, Miho; Yamaguchi, Hiroshi; Yamaguchi, Yohei; Yamamoto, Akira; Yamamoto, Kyoko; Yamamoto, Shimpei; Yamamura, Taiki; Yamanaka, Takashi; Yamauchi, Katsuya; Yamazaki, Yuji; Yan, Zhen; Yang, Haijun; Yang, Hongtao; Yang, Un-Ki; Yang, Yi; Yanush, Serguei; Yao, Liwen; Yao, Weiming; Yasu, Yoshiji; Yatsenko, Elena; Yau Wong, Kaven Henry; Ye, Jingbo; Ye, Shuwei; Yen, Andy L; Yildirim, Eda; Yilmaz, Metin; Yoosoofmiya, Reza; Yorita, Kohei; Yoshida, Rikutaro; Yoshihara, Keisuke; Young, Charles; Young, Christopher John; Youssef, Saul; Yu, David Ren-Hwa; Yu, Jaehoon; Yu, Jiaming; Yu, Jie; Yuan, Li; Yurkewicz, Adam; Yusuff, Imran; Zabinski, Bartlomiej; Zaidan, Remi; Zaitsev, Alexander; Zaman, Aungshuman; Zambito, Stefano; Zanello, Lucia; Zanzi, Daniele; Zeitnitz, Christian; Zeman, Martin; Zemla, Andrzej; Zengel, Keith; Zenin, Oleg; Ženiš, Tibor; Zerwas, Dirk; Zevi della Porta, Giovanni; Zhang, Dongliang; Zhang, Fangzhou; Zhang, Huaqiao; Zhang, Jinlong; Zhang, Lei; Zhang, Xueyao; Zhang, Zhiqing; Zhao, Zhengguo; Zhemchugov, Alexey; Zhong, Jiahang; Zhou, Bing; Zhou, Lei; Zhou, Ning; Zhu, Cheng Guang; Zhu, Hongbo; Zhu, Junjie; Zhu, Yingchun; Zhuang, Xuai; Zhukov, Konstantin; Zibell, Andre; Zieminska, Daria; Zimine, Nikolai; Zimmermann, Christoph; Zimmermann, Robert; Zimmermann, Simone; Zimmermann, Stephanie; Zinonos, Zinonas; Ziolkowski, Michael; Zobernig, Georg; Zoccoli, Antonio; zur Nedden, Martin; Zurzolo, Giovanni; Zutshi, Vishnu; Zwalinski, Lukasz

2014-09-15

A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from highly energetic objects, such as jets. Neural networks are trained using Monte Carlo samples produced with a detailed detector simulation. This technique replaces the former clustering approach based on a connected component analysis and charge interpolation. The performance of the neural network splitting technique is quantified using data from proton-proton collisions at the LHC collected by the ATLAS detector in 2011 and from Monte Carlo simulations. This technique reduces the number of clusters shared between tracks in highly energetic jets by up to a factor of three. It also provides more precise position and error estimates of the clusters in both the transverse and longitudinal impact parameter resolution.

Acclimatization and growth of ornamental pineapple seedlings under organic substrates

Directory of Open Access Journals (Sweden)

Ronan Carlos Colombo

2017-09-01

Full Text Available The in vitro propagation techniques are commonly used to produce ornamental pineapple seedlings in commercial scale, aiming to attend the growers with genetic and sanitary quality seedlings. However, the choice of the ideal substrate is essential for the acclimatization and growth stage of the seedlings propagated by this technique, since some substrates can increase the seedling mortality and/or limit the seedling growth due to its physical and chemical characteristics. Thus, the aim of this study was to evaluate the acclimatization of ornamental pineapple [Ananas comosus (L. Merr. var. ananassoides (Baker Coppens & Leal] on different substrates. Seedlings with approximately seven centimeters, obtained from in vitro culture, were transplanted into styrofoam trays filled with the following substrates: sphagnum; semi-composed pine bark; carbonized rice husk; sphagnum + semicomposed pine bark; sphagnum + carbonized rice husk; and semi-composed pine bark + carbonized rice husk. Each treatment was replicated five times using 10 plants. At 180 days, there were evaluated the following variables: survival percentage, plant height, number of leaves, leaf area, largest root length, and shoot and root dry matter. The substrate semi-composed pine bark + carbonized rice husk presented the lowest mean (62% for survival percentage. The semi-composed pine bark and semi-composed pine bark + carbonized rice husk treatments presented significant increments in some evaluated biometric characteristics. The semi-composed pine bark is the most favorable substrate for the A. comosus var. ananassoids acclimatization.

Neural Tube Defect in Alive Neonates: Incidence Rate and Predisposing Factors

Directory of Open Access Journals (Sweden)

F Haghollahi

2008-06-01

Full Text Available Background: Neural Tube Defect (NTD characterized by failure of neural tube to close properly be the second most common born defect after congenital heart disease. The most prevalent forms of NTD are Anencephaly and Spinal-bifida. Many factors are involved in this anomaly. New researches suggest environmental factors like radiation, hyperthermia, Vitamin A and acid folic deficiency, anti epileptic drug like Carbamazepine, Phenobarbital, phenytoin, Folic acid antagonist like Sulfasalazine, Triametherine and systemic disease like diabet mellitus, obesity, genetic factors, the most schance 40 to 70 percentages.Methods: In this survey cross sectional study was conducted in five hospitals depend to Tehran university during three years. Study subject identified through review of admission and discharge at major hospital through regular contact with newborn nurseries and birth hospital.Results: In 38473 reported cases, 143 cases have neural tube defect. Among NTD cases, 11.9% of mothers had medical diseases in their previous history such as diabetes mellitus, epilepsy-psychiatric, and disorder-heart diseases. In this study group, 5.6% have preclampsia during pregnancy period. The most common NTD anomaly in this study was anencephaly and meningomyelocele that was different from studies in literature.Conclusion: NTD result from failure of neural tube close threats fetus health up to 28 days after conception. When is often prior to the recognition of pregnancy since many pregnancy are unplanned NTD prevention is best achieve by adequate daily folic acid intake thought of reproductive ages .educational effort to promote daily intake of folic acid supplemental by women of reproductive age and NTD risk factor should be done. Early diagnostic procedure for high risk pregnancy advised.

Argon plasma sintering of inkjet printed silver tracks on polymer substrates

NARCIS (Netherlands)

Reinhold, I.; Hendriks, C.E.; Eckardt, R.; Kranenburg, J.M.; Perelaer, J.; Baumann, R.; Schubert, U.S.

2009-01-01

An alternative and selective sintering method for the fabrication of conductive silver tracks on common polymer substrates is presented, by exposure to low-pressure argon plasma. Inkjet printing has been used to pattern a silver nanoparticle ink. This resulted in conductive features with a

Autoshaped choice in artificial neural networks: implications for behavioral economics and neuroeconomics.

Science.gov (United States)

Burgos, José E; García-Leal, Óscar

2015-05-01

An existing neural network model of conditioning was used to simulate autoshaped choice. In this phenomenon, pigeons first receive an autoshaping procedure with two keylight stimuli X and Y separately paired with food in a forward-delay manner, intermittently for X and continuously for Y. Then pigeons receive unreinforced choice test trials of X and Y concurrently present. Most pigeons choose Y. This preference for a more valuable response alternative is a form of economic behavior that makes the phenomenon relevant to behavioral economics. The phenomenon also suggests a role for Pavlovian contingencies in economic behavior. The model used, in contrast to others, predicts autoshaping and automaintenance, so it is uniquely positioned to predict autoshaped choice. The model also contemplates neural substrates of economic behavior in neuroeconomics, such as dopaminergic and hippocampal systems. A feedforward neural network architecture was designed to simulate a neuroanatomical differentiation between two environment-behavior relations X-R1 and Y-R2, [corrected] where R1 and R2 denote two different emitted responses (not unconditionally elicited by the reward). Networks with this architecture received a training protocol that simulated an autoshaped-choice procedure. Most networks simulated the phenomenon. Implications for behavioral economics and neuroeconomics, limitations, and the issue of model appraisal are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.

Dolomitic lime amendment affects pine bark substrate pH, nutrient availability, and plant growth: A review

Science.gov (United States)

Dolomitic lime (DL) is one of the most commonly used fertilizer amendments in nursery container substrates. It is used to adjust pH of pine bark substrates from their native pH, 4.1 to 5.1, up to about pH 6. Additions of DL have been shown to be beneficial, inconsequential, or detrimental dependin...

Substrate system for spray forming

Energy Technology Data Exchange (ETDEWEB)

Chu, Men G. (Export, PA); Chernicoff, William P. (Harrisburg, PA)

2002-01-01

A substrate system for receiving a deposit of sprayed metal droplets including a movable outer substrate on which the sprayed metal droplets are deposited. The substrate system also includes an inner substrate disposed adjacent the outer substrate where the sprayed metal droplets are deposited on the outer substrate. The inner substrate includes zones of differing thermal conductivity to resist substrate layer porosity and to resist formation of large grains and coarse constituent particles in a bulk layer of the metal droplets which have accumulated on the outer substrate. A spray forming apparatus and associated method of spray forming a molten metal to form a metal product using the substrate system of the invention is also provided.

Epigenetics and Neural developmental disorders: Washington DC, September 18 and 19, 2006.

Science.gov (United States)

Zhao, Xinyu; Pak, ChangHui; Smrt, Richard D; Jin, Peng

2007-01-01

Neural developmental disorders, such as autism, Rett Syndrome, Fragile X syndrome, and Angelman syndrome manifest during early postnatal neural development. Although the genes responsible for some of these disorders have been identified, how the mutations of these genes affect neural development is currently unclear. Emerging evidence suggest that these disorders share common underlying defects in neuronal morphology, synaptic connectivity and brain plasticity. In particular, alterations in dendritic branching and spine morphology play a central role in the pathophysiology of most mental retardation disorders, suggesting that common pathways regulating neuronal function may be affected. Epigenetic modulations, mediated by DNA methylation, RNA-associated silencing, and histone modification, can serve as an intermediate process that imprints dynamic environmental experiences on the "fixed" genome, resulting in stable alterations in phenotypes. Disturbance in epigenetic regulations can lead to inappropriate expression or silencing of genes, causing an array of multi-system disorders and neoplasias. Rett syndrome, the most common form of mental retardation in young girls, is due to l mutation of MECP2, encoding a methylated DNA binding protein that translates DNA methylation into gene repression. Angelman syndrome is due to faulty genomic imprinting or maternal mutations in UBE3A. Fragile X Syndrome, in most cases, results from the hypermethylation of FMR1 promoter, hence the loss of expression of functional FMRP protein. Autism, with its complex etiology, may have strong epigenetic link. Together, these observations strongly suggest that epigenetic mechanisms may play a critical role in brain development and etiology of related disorders. This report summarizes the scientific discussions and major conclusions from a recent conference that aimed to gain insight into the common molecular pathways affected among these disorders and discover potential therapeutic targets

Lifetimes of carbon foils deposited on etched substrates

International Nuclear Information System (INIS)

Stoner, J.O. Jr.; Bashkin, S.; Hartog, P.D.; Thomas, G.; Yntema, J.L.

1981-01-01

The methods currently in use for producing long-lived carbon foils are listed. The possible common factors which are important in making long lasting foils are a) making a strong, coherent, continuous layer, b) making a foil slack, loose, or baggy, and c) making a foil whose molecular structure minimizes shrinkage. The behavior of foils deposited on etched substrates is compared with foils deposited upon conventional microscope slides

Neural network classification of quark and gluon jets

International Nuclear Information System (INIS)

Graham, M.A.; Jones, L.M.; Herbin, S.

1995-01-01

We demonstrate that there are characteristics common to quark jets and to gluon jets regardless of the interaction that produced them. The classification technique we use depends on the mass of the jet as well as the center-of-mass energy of the hard subprocess that produces the jet. In addition, we present the quark-gluon separability results of an artificial neural network trained on three-jet e + e - events at the Z 0 mass, using a back-propagation algorithm. The inputs to the network are the longitudinal momenta of the leading hadrons in the jet. We tested the network with quark and gluon jets from both e + e - →3 jets and bar pp→2 jets. Finally, we compare the performance of the artificial neural network with the results of making well chosen physical cuts

Computational Approach for Epitaxial Polymorph Stabilization through Substrate Selection

Energy Technology Data Exchange (ETDEWEB)

Ding, Hong; Dwaraknath, Shyam S.; Garten, Lauren; Ndione, Paul; Ginley, David; Persson, Kristin A.

2016-05-25

With the ultimate goal of finding new polymorphs through targeted synthesis conditions and techniques, we outline a computational framework to select optimal substrates for epitaxial growth using first principle calculations of formation energies, elastic strain energy, and topological information. To demonstrate the approach, we study the stabilization of metastable VO2 compounds which provides a rich chemical and structural polymorph space. We find that common polymorph statistics, lattice matching, and energy above hull considerations recommends homostructural growth on TiO2 substrates, where the VO2 brookite phase would be preferentially grown on the a-c TiO2 brookite plane while the columbite and anatase structures favor the a-b plane on the respective TiO2 phases. Overall, we find that a model which incorporates a geometric unit cell area matching between the substrate and the target film as well as the resulting strain energy density of the film provide qualitative agreement with experimental observations for the heterostructural growth of known VO2 polymorphs: rutile, A and B phases. The minimal interfacial geometry matching and estimated strain energy criteria provide several suggestions for substrates and substrate-film orientations for the heterostructural growth of the hitherto hypothetical anatase, brookite, and columbite polymorphs. These criteria serve as a preliminary guidance for the experimental efforts stabilizing new materials and/or polymorphs through epitaxy. The current screening algorithm is being integrated within the Materials Project online framework and data and hence publicly available.

Layers and Multilayers of Self-Assembled Polymers: Tunable Engineered Extracellular Matrix Coatings for Neural Cell Growth.

Science.gov (United States)

Landry, Michael J; Rollet, Frédéric-Guillaume; Kennedy, Timothy E; Barrett, Christopher J

2018-03-12

Growing primary cells and tissue in long-term cultures, such as primary neural cell culture, presents many challenges. A critical component of any environment that supports neural cell growth in vivo is an appropriate 2-D surface or 3-D scaffold, typically in the form of a thin polymer layer that coats an underlying plastic or glass substrate and aims to mimic critical aspects of the extracellular matrix. A fundamental challenge to mimicking a hydrophilic, soft natural cell environment is that materials with these properties are typically fragile and are difficult to adhere to and stabilize on an underlying plastic or glass cell culture substrate. In this review, we highlight the current state of the art and overview recent developments of new artificial extracellular matrix (ECM) surfaces for in vitro neural cell culture. Notably, these materials aim to strike a balance between being hydrophilic and soft while also being thick, stable, robust, and bound well to the underlying surface to provide an effective surface to support long-term cell growth. We focus on improved surface and scaffold coating systems that can mimic the natural physicochemical properties that enhance neuronal survival and growth, applied as soft hydrophilic polymer coatings for both in vitro cell culture and for implantable neural probes and 3-D matrixes that aim to enhance stability and longevity to promote neural biocompatibility in vivo. With respect to future developments, we outline four emerging principles that serve to guide the development of polymer assemblies that function well as artificial ECMs: (a) design inspired by biological systems and (b) the employment of principles of aqueous soft bonding and self-assembly to achieve (c) a high-water-content gel-like coating that is stable over time in a biological environment and possesses (d) a low modulus to more closely mimic soft, compliant real biological tissue. We then highlight two emerging classes of thick material coatings that

Neural network-based run-to-run controller using exposure and resist thickness adjustment

Science.gov (United States)

Geary, Shane; Barry, Ronan

2003-06-01

This paper describes the development of a run-to-run control algorithm using a feedforward neural network, trained using the backpropagation training method. The algorithm is used to predict the critical dimension of the next lot using previous lot information. It is compared to a common prediction algorithm - the exponentially weighted moving average (EWMA) and is shown to give superior prediction performance in simulations. The manufacturing implementation of the final neural network showed significantly improved process capability when compared to the case where no run-to-run control was utilised.

Bacterial protease uses distinct thermodynamic signatures for substrate recognition.

OpenAIRE

Bezerra, GA; Ohara-Nemoto, Y; Cornaciu, I; Fedosyuk, S; Hoffmann, G; Round, A; Márquez, JA; Nemoto, TK; Djinović-Carugo, K

2017-01-01

Porphyromonas gingivalis and Porphyromonas endodontalis are important bacteria related to periodontitis, the most common chronic inflammatory disease in humans worldwide. Its comorbidity with systemic diseases, such as type 2 diabetes, oral cancers and cardiovascular diseases, continues to generate considerable interest. Surprisingly, these two microorganisms do not ferment carbohydrates; rather they use proteinaceous substrates as carbon and energy sources. However, the underlying biochemica...

Time to connect: bringing social context into addiction neuroscience.

Science.gov (United States)

Heilig, Markus; Epstein, David H; Nader, Michael A; Shaham, Yavin

2016-09-01

Research on the neural substrates of drug reward, withdrawal and relapse has yet to be translated into significant advances in the treatment of addiction. One potential reason is that this research has not captured a common feature of human addiction: progressive social exclusion and marginalization. We propose that research aimed at understanding the neural mechanisms that link these processes to drug seeking and drug taking would help to make addiction neuroscience research more clinically relevant.

Neural networks for genetic epidemiology: past, present, and future

Directory of Open Access Journals (Sweden)

Motsinger-Reif Alison A

2008-07-01

Full Text Available Abstract During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes. In the current review, we consider how NN have been used for both linkage and association analyses in genetic epidemiology. We discuss both the successes of these initial NN applications, and the questions that arose during the previous studies. Finally, we introduce evolutionary computing strategies, Genetic Programming Neural Networks (GPNN and Grammatical Evolution Neural Networks (GENN, for using NN in association studies of complex human diseases that address some of the caveats illuminated by previous work.

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

Science.gov (United States)

Decker, Arthur J.; Krasowski, Michael J.; Weiland, Kenneth E.

1993-01-01

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

Neural networks for aircraft control

Science.gov (United States)

Linse, Dennis

1990-01-01

Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

Science.gov (United States)

Waheeb, Waddah; Ghazali, Rozaida; Herawan, Tutut

2016-01-01

Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF) that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN) and the Dynamic Ridge Polynomial Neural Network (DRPNN). Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE) with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

Efficient decoding with steady-state Kalman filter in neural interface systems.

Science.gov (United States)

Malik, Wasim Q; Truccolo, Wilson; Brown, Emery N; Hochberg, Leigh R

2011-02-01

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5±0.5 s (mean ±s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25±3 single units by a factor of 7.0±0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems.

Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting.

Directory of Open Access Journals (Sweden)

Waddah Waheeb

Full Text Available Time series forecasting has gained much attention due to its many practical applications. Higher-order neural network with recurrent feedback is a powerful technique that has been used successfully for time series forecasting. It maintains fast learning and the ability to learn the dynamics of the time series over time. Network output feedback is the most common recurrent feedback for many recurrent neural network models. However, not much attention has been paid to the use of network error feedback instead of network output feedback. In this study, we propose a novel model, called Ridge Polynomial Neural Network with Error Feedback (RPNN-EF that incorporates higher order terms, recurrence and error feedback. To evaluate the performance of RPNN-EF, we used four univariate time series with different forecasting horizons, namely star brightness, monthly smoothed sunspot numbers, daily Euro/Dollar exchange rate, and Mackey-Glass time-delay differential equation. We compared the forecasting performance of RPNN-EF with the ordinary Ridge Polynomial Neural Network (RPNN and the Dynamic Ridge Polynomial Neural Network (DRPNN. Simulation results showed an average 23.34% improvement in Root Mean Square Error (RMSE with respect to RPNN and an average 10.74% improvement with respect to DRPNN. That means that using network errors during training helps enhance the overall forecasting performance for the network.

Neural correlates of attentional and mnemonic processing in event-based prospective memory.

Science.gov (United States)

Knight, Justin B; Ethridge, Lauren E; Marsh, Richard L; Clementz, Brett A

2010-01-01

Prospective memory (PM), or memory for realizing delayed intentions, was examined with an event-based paradigm while simultaneously measuring neural activity with high-density EEG recordings. Specifically, the neural substrates of monitoring for an event-based cue were examined, as well as those perhaps associated with the cognitive processes supporting detection of cues and fulfillment of intentions. Participants engaged in a baseline lexical decision task (LDT), followed by a LDT with an embedded PM component. Event-based cues were constituted by color and lexicality (red words). Behavioral data provided evidence that monitoring, or preparatory attentional processes, were used to detect cues. Analysis of the event-related potentials (ERP) revealed visual attentional modulations at 140 and 220 ms post-stimulus associated with preparatory attentional processes. In addition, ERP components at 220, 350, and 400 ms post-stimulus were enhanced for intention-related items. Our results suggest preparatory attention may operate by selectively modulating processing of features related to a previously formed event-based intention, as well as provide further evidence for the proposal that dissociable component processes support the fulfillment of delayed intentions.

Random noise effects in pulse-mode digital multilayer neural networks.

Science.gov (United States)

Kim, Y C; Shanblatt, M A

1995-01-01

A pulse-mode digital multilayer neural network (DMNN) based on stochastic computing techniques is implemented with simple logic gates as basic computing elements. The pulse-mode signal representation and the use of simple logic gates for neural operations lead to a massively parallel yet compact and flexible network architecture, well suited for VLSI implementation. Algebraic neural operations are replaced by stochastic processes using pseudorandom pulse sequences. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. Synaptic weights and neuron states are represented as probabilities and estimated as average pulse occurrence rates in corresponding pulse sequences. A statistical model of the noise (error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Computational differences are then explained by comparison to deterministic neural computations. DMNN feedforward architectures are modeled in VHDL using character recognition problems as testbeds. Computational accuracy is analyzed, and the results of the statistical model are compared with the actual simulation results. Experiments show that the calculations performed in the DMNN are more accurate than those anticipated when Bernoulli sequences are assumed, as is common in the literature. Furthermore, the statistical model successfully predicts the accuracy of the operations performed in the DMNN.

3D Polygon Mesh Compression with Multi Layer Feed Forward Neural Networks

Directory of Open Access Journals (Sweden)

Emmanouil Piperakis

2003-06-01

Full Text Available In this paper, an experiment is conducted which proves that multi layer feed forward neural networks are capable of compressing 3D polygon meshes. Our compression method not only preserves the initial accuracy of the represented object but also enhances it. The neural network employed includes the vertex coordinates, the connectivity and normal information in one compact form, converting the discrete and surface polygon representation into an analytic, solid colloquial. Furthermore, the 3D object in its compressed neural form can be directly - without decompression - used for rendering. The neural compression - representation is viable to 3D transformations without the need of any anti-aliasing techniques - transformations do not disrupt the accuracy of the geometry. Our method does not su.er any scaling problem and was tested with objects of 300 to 107 polygons - such as the David of Michelangelo - achieving in all cases an order of O(b3 less bits for the representation than any other commonly known compression method. The simplicity of our algorithm and the established mathematical background of neural networks combined with their aptness for hardware implementation can establish this method as a good solution for polygon compression and if further investigated, a novel approach for 3D collision, animation and morphing.

Modelling substrate specificity and enantioselectivity for lipases and esterases by substrate-imprinted docking

Directory of Open Access Journals (Sweden)

Tyagi Sadhna

2009-06-01

Full Text Available Abstract Background Previously, ways to adapt docking programs that were developed for modelling inhibitor-receptor interaction have been explored. Two main issues were discussed. First, when trying to model catalysis a reaction intermediate of the substrate is expected to provide more valid information than the ground state of the substrate. Second, the incorporation of protein flexibility is essential for reliable predictions. Results Here we present a predictive and robust method to model substrate specificity and enantioselectivity of lipases and esterases that uses reaction intermediates and incorporates protein flexibility. Substrate-imprinted docking starts with covalent docking of reaction intermediates, followed by geometry optimisation of the resulting enzyme-substrate complex. After a second round of docking the same substrate into the geometry-optimised structures, productive poses are identified by geometric filter criteria and ranked by their docking scores. Substrate-imprinted docking was applied in order to model (i enantioselectivity of Candida antarctica lipase B and a W104A mutant, (ii enantioselectivity and substrate specificity of Candida rugosa lipase and Burkholderia cepacia lipase, and (iii substrate specificity of an acetyl- and a butyrylcholine esterase toward the substrates acetyl- and butyrylcholine. Conclusion The experimentally observed differences in selectivity and specificity of the enzymes were reproduced with an accuracy of 81%. The method was robust toward small differences in initial structures (different crystallisation conditions or a co-crystallised ligand, although large displacements of catalytic residues often resulted in substrate poses that did not pass the geometric filter criteria.

A common signal detection model accounts for both perception and discrimination of the watercolor effect.

Science.gov (United States)

Devinck, Frédéric; Knoblauch, Kenneth

2012-03-21

Establishing the relation between perception and discrimination is a fundamental objective in psychophysics, with the goal of characterizing the neural mechanisms mediating perception. Here, we show that a procedure for estimating a perceptual scale based on a signal detection model also predicts discrimination performance. We use a recently developed procedure, Maximum Likelihood Difference Scaling (MLDS), to measure the perceptual strength of a long-range, color, filling-in phenomenon, the Watercolor Effect (WCE), as a function of the luminance ratio between the two components of its generating contour. MLDS is based on an equal-variance, gaussian, signal detection model and yields a perceptual scale with interval properties. The strength of the fill-in percept increased 10-15 times the estimate of the internal noise level for a 3-fold increase in the luminance ratio. Each observer's estimated scale predicted discrimination performance in a subsequent paired-comparison task. A common signal detection model accounts for both the appearance and discrimination data. Since signal detection theory provides a common metric for relating discrimination performance and neural response, the results have implications for comparing perceptual and neural response functions.

Selective light sintering of Aerosol-Jet printed silver nanoparticle inks on polymer substrates

International Nuclear Information System (INIS)

Schuetz, K.; Hoerber, J.; Franke, J.

2014-01-01

Printing silver nanoparticle inks to generate conductive structures for electronics on polymer substrates has gained increasing relevance in recent years. In this context, the Aerosol-Jet Technology is well suited to print silver ink on 3D-Molded Interconnect Devices (MID). The deposited ink requires thermal post-treatment to obtain sufficient electrical conductivity and adhesion. However, commonly used oven sintering cannot be applied for many thermoplastic substrates due to low melting temperatures. In this study a new sintering technology, selective light sintering, is presented, based on the focused, continuous light beam of a xenon lamp. Sintering experiments were conducted with Aerosol-Jet printed structures on various polycarbonate (PC) substrates. Especially on neat, light transparent PC, silver tracks were evenly sintered with marginal impact to the substrate. Electrical conductivities significantly exceed the values obtained with conventional oven sintering. Adhesive strength is sufficient for conductive tracks. Experiments with non-transparent PC substrates led to substrate damage due to increased light absorption. Therefore a concept for a variation of light sintering was developed, using optical filters. First experiments showed significant reduction of substrate damage and good sintering qualities. The highly promising results of the conducted experiments provide a base for further investigations to increase adhesion and qualifying the technology for MID applications and a broad spectrum of thermoplastic substrates

PREFACE: Cell-substrate interactions Cell-substrate interactions

Science.gov (United States)

Gardel, Margaret; Schwarz, Ulrich

2010-05-01

One of the most striking achievements of evolution is the ability to build cellular systems that are both robust and dynamic. Taken by themselves, both properties are obvious requirements: robustness reflects the fact that cells are there to survive, and dynamics is required to adapt to changing environments. However, it is by no means trivial to understand how these two requirements can be implemented simultaneously in a physical system. The long and difficult quest to build adaptive materials is testimony to the inherent difficulty of this goal. Here materials science can learn a lot from nature, because cellular systems show that robustness and dynamics can be achieved in a synergetic fashion. For example, the capabilities of tissues to repair and regenerate are still unsurpassed in the world of synthetic materials. One of the most important aspects of the way biological cells adapt to their environment is their adhesive interaction with the substrate. Numerous aspects of the physiology of metazoan cells, including survival, proliferation, differentiation and migration, require the formation of adhesions to the cell substrate, typically an extracellular matrix protein. Adhesions guide these diverse processes both by mediating force transmission from the cell to the substrate and by controlling biochemical signaling pathways. While the study of cell-substrate adhesions is a mature field in cell biology, a quantitative biophysical understanding of how the interactions of the individual molecular components give rise to the rich dynamics and mechanical behaviors observed for cell-substrate adhesions has started to emerge only over the last decade or so. The recent growth of research activities on cell-substrate interactions was strongly driven by the introduction of new physical techniques for surface engineering into traditional cell biological work with cell culture. For example, microcontact printing of adhesive patterns was used to show that cell fate depends

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

Science.gov (United States)

Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

A review on mechanical considerations for chronically-implanted neural probes

Science.gov (United States)

Lecomte, Aziliz; Descamps, Emeline; Bergaud, Christian

2018-06-01

This review intends to present a comprehensive analysis of the mechanical considerations for chronically-implanted neural probes. Failure of neural electrical recordings or stimulation over time has shown to arise from foreign body reaction and device material stability. It seems that devices that match most closely with the mechanical properties of the brain would be more likely to reduce the mechanical stress at the probe/tissue interface, thus improving body acceptance. The use of low Young’s modulus polymers instead of hard substrates is one way to enhance this mechanical mimetism, though compliance can be achieved through a variety of means. The reduction of probe width and thickness in comparison to a designated length, the use of soft hydrogel coatings and the release in device tethering to the skull, can also improve device compliance. Paradoxically, the more compliant the device, the more likely it will fail during the insertion process in the brain. Strategies have multiplied this past decade to offer partial or temporary stiffness to the device to overcome this buckling effect. A detailed description of the probe insertion mechanisms is provided to analyze potential sources of implantation failure and the need for a mechanically-enhancing structure. This leads us to present an overview of the strategies that have been put in place over the last ten years to overcome buckling issues. Particularly, great emphasis is put on bioresorbable polymers and their assessment for neural applications. Finally, a discussion is provided on some of the key features for the design of mechanically-reliable, polymer-based next generation of chronic neuroprosthetic devices.

The neural basis of task switching changes with skill acquisition

Directory of Open Access Journals (Sweden)

Koji eJimura

2014-05-01

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

A modular architecture for transparent computation in recurrent neural networks.