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  1. Multistability in bidirectional associative memory neural networks

    International Nuclear Information System (INIS)

    Huang Gan; Cao Jinde

    2008-01-01

    In this Letter, the multistability issue is studied for Bidirectional Associative Memory (BAM) neural networks. Based on the existence and stability analysis of the neural networks with or without delay, it is found that the 2n-dimensional networks can have 3 n equilibria and 2 n equilibria of them are locally exponentially stable, where each layer of the BAM network has n neurons. Furthermore, the results has been extended to (n+m)-dimensional BAM neural networks, where there are n and m neurons on the two layers respectively. Finally, two numerical examples are presented to illustrate the validity of our results

  2. Multistability in bidirectional associative memory neural networks

    Science.gov (United States)

    Huang, Gan; Cao, Jinde

    2008-04-01

    In this Letter, the multistability issue is studied for Bidirectional Associative Memory (BAM) neural networks. Based on the existence and stability analysis of the neural networks with or without delay, it is found that the 2 n-dimensional networks can have 3 equilibria and 2 equilibria of them are locally exponentially stable, where each layer of the BAM network has n neurons. Furthermore, the results has been extended to (n+m)-dimensional BAM neural networks, where there are n and m neurons on the two layers respectively. Finally, two numerical examples are presented to illustrate the validity of our results.

  3. Associative memory model with spontaneous neural activity

    Science.gov (United States)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2012-05-01

    We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

  4. 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.

  5. Neural activity associated with self-reflection.

    Science.gov (United States)

    Herwig, Uwe; Kaffenberger, Tina; Schell, Caroline; Jäncke, Lutz; Brühl, Annette B

    2012-05-24

    Self-referential cognitions are important for self-monitoring and self-regulation. Previous studies have addressed the neural correlates of self-referential processes in response to or related to external stimuli. We here investigated brain activity associated with a short, exclusively mental process of self-reflection in the absence of external stimuli or behavioural requirements. Healthy subjects reflected either on themselves, a personally known or an unknown person during functional magnetic resonance imaging (fMRI). The reflection period was initialized by a cue and followed by photographs of the respective persons (perception of pictures of oneself or the other person). Self-reflection, compared with reflecting on the other persons and to a major part also compared with perceiving photographs of one-self, was associated with more prominent dorsomedial and lateral prefrontal, insular, anterior and posterior cingulate activations. Whereas some of these areas showed activity in the "other"-conditions as well, self-selective characteristics were revealed in right dorsolateral prefrontal and posterior cingulate cortex for self-reflection; in anterior cingulate cortex for self-perception and in the left inferior parietal lobe for self-reflection and -perception. Altogether, cingulate, medial and lateral prefrontal, insular and inferior parietal regions show relevance for self-related cognitions, with in part self-specificity in terms of comparison with the known-, unknown- and perception-conditions. Notably, the results are obtained here without behavioural response supporting the reliability of this methodological approach of applying a solely mental intervention. We suggest considering the reported structures when investigating psychopathologically affected self-related processing.

  6. ABOUT HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH DISCRETE DELAYS

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In this paper, hybrid bidirectional associative memory neural networks with discrete delays is considered. By ingeniously importing real parameters di > 0(i = 1,2,···,n) which can be adjusted, we establish some new sufficient conditions for the dynamical characteristics of hybrid bidirectional associative memory neural networks with discrete delays by the method of variation of parameters and some analysis techniques. Our results generalize and improve the related results in [10,11]. Our work is significant...

  7. Topology influences performance in the associative memory neural networks

    International Nuclear Information System (INIS)

    Lu Jianquan; He Juan; Cao Jinde; Gao Zhiqiang

    2006-01-01

    To explore how topology affects performance within Hopfield-type associative memory neural networks (AMNNs), we studied the computational performance of the neural networks with regular lattice, random, small-world, and scale-free structures. In this Letter, we found that the memory performance of neural networks obtained through asynchronous updating from 'larger' nodes to 'smaller' nodes are better than asynchronous updating in random order, especially for the scale-free topology. The computational performance of associative memory neural networks linked by the above-mentioned network topologies with the same amounts of nodes (neurons) and edges (synapses) were studied respectively. Along with topologies becoming more random and less locally disordered, we will see that the performance of associative memory neural network is quite improved. By comparing, we show that the regular lattice and random network form two extremes in terms of patterns stability and retrievability. For a network, its patterns stability and retrievability can be largely enhanced by adding a random component or some shortcuts to its structured component. According to the conclusions of this Letter, we can design the associative memory neural networks with high performance and minimal interconnect requirements

  8. Distorted Character Recognition Via An Associative Neural Network

    Science.gov (United States)

    Messner, Richard A.; Szu, Harold H.

    1987-03-01

    The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

  9. Neural coding in graphs of bidirectional associative memories.

    Science.gov (United States)

    Bouchain, A David; Palm, Günther

    2012-01-24

    In the last years we have developed large neural network models for the realization of complex cognitive tasks in a neural network architecture that resembles the network of the cerebral cortex. We have used networks of several cortical modules that contain two populations of neurons (one excitatory, one inhibitory). The excitatory populations in these so-called "cortical networks" are organized as a graph of Bidirectional Associative Memories (BAMs), where edges of the graph correspond to BAMs connecting two neural modules and nodes of the graph correspond to excitatory populations with associative feedback connections (and inhibitory interneurons). The neural code in each of these modules consists essentially of the firing pattern of the excitatory population, where mainly it is the subset of active neurons that codes the contents to be represented. The overall activity can be used to distinguish different properties of the patterns that are represented which we need to distinguish and control when performing complex tasks like language understanding with these cortical networks. The most important pattern properties or situations are: exactly fitting or matching input, incomplete information or partially matching pattern, superposition of several patterns, conflicting information, and new information that is to be learned. We show simple simulations of these situations in one area or module and discuss how to distinguish these situations based on the overall internal activation of the module. This article is part of a Special Issue entitled "Neural Coding". Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Multi-Valued Associative Memory Neural Network

    Institute of Scientific and Technical Information of China (English)

    修春波; 刘向东; 张宇河

    2003-01-01

    A novel learning method for multi-valued associative memory network is introduced, which is based on Hebb rule, but utilizes more information. According to the current probe vector, the connection weights matrix could be chosen dynamically. Double-valued and multi-valued associative memory are all realized in our simulation experiment. The experimental results show that the method could enhance the associative success rate.

  11. Periodic bidirectional associative memory neural networks with distributed delays

    Science.gov (United States)

    Chen, Anping; Huang, Lihong; Liu, Zhigang; Cao, Jinde

    2006-05-01

    Some sufficient conditions are obtained for the existence and global exponential stability of a periodic solution to the general bidirectional associative memory (BAM) neural networks with distributed delays by using the continuation theorem of Mawhin's coincidence degree theory and the Lyapunov functional method and the Young's inequality technique. These results are helpful for designing a globally exponentially stable and periodic oscillatory BAM neural network, and the conditions can be easily verified and be applied in practice. An example is also given to illustrate our results.

  12. Neural Inductive Matrix Completion for Predicting Disease-Gene Associations

    KAUST Repository

    Hou, Siqing

    2018-05-21

    In silico prioritization of undiscovered associations can help find causal genes of newly discovered diseases. Some existing methods are based on known associations, and side information of diseases and genes. We exploit the possibility of using a neural network model, Neural inductive matrix completion (NIMC), in disease-gene prediction. Comparing to the state-of-the-art inductive matrix completion method, using neural networks allows us to learn latent features from non-linear functions of input features. Previous methods use disease features only from mining text. Comparing to text mining, disease ontology is a more informative way of discovering correlation of dis- eases, from which we can calculate the similarities between diseases and help increase the performance of predicting disease-gene associations. We compare the proposed method with other state-of-the-art methods for pre- dicting associated genes for diseases from the Online Mendelian Inheritance in Man (OMIM) database. Results show that both new features and the proposed NIMC model can improve the chance of recovering an unknown associated gene in the top 100 predicted genes. Best results are obtained by using both the new features and the new model. Results also show the proposed method does better in predicting associated genes for newly discovered diseases.

  13. Accelerated DNA Methylation Age: Associations with PTSD and Neural Integrity

    Science.gov (United States)

    Wolf, Erika J.; Logue, Mark W.; Hayes, Jasmeet P.; Sadeh, Naomi; Schichman, Steven A.; Stone, Annjanette; Salat, David H.; Milberg, William; McGlinchey, Regina; Miller, Mark W.

    2015-01-01

    Background Accumulating evidence suggests that post traumatic stress disorder (PTSD) may accelerate cellular aging and lead to premature morbidity and neurocognitive decline. Methods This study evaluated associations between PTSD and DNA methylation (DNAm) age using recently developed algorithms of cellular age by Horvath (2013) and Hannum et al. (2013). These estimates reflect accelerated aging when they exceed chronological age. We also examined if accelerated cellular age manifested in degraded neural integrity, indexed via diffusion tensor imaging. Results Among 281 male and female veterans of the conflicts in Iraq and Afghanistan, DNAm age was strongly related to chronological age (rs ~.88). Lifetime PTSD severity was associated with Hannum DNAm age estimates residualized for chronological age (β = .13, p= .032). Advanced DNAm age was associated with reduced integrity in the genu of the corpus callosum (β = −.17, p= .009) and indirectly linked to poorer working memory performance via this region (indirect β = − .05, p= .029). Horvath DNAm age estimates were not associated with PTSD or neural integrity. Conclusions Results provide novel support for PTSD-related accelerated aging in DNAm and extend the evidence base of known DNAm age correlates to the domains of neural integrity and cognition. PMID:26447678

  14. Associative memory in an analog iterated-map neural network

    Science.gov (United States)

    Marcus, C. M.; Waugh, F. R.; Westervelt, R. M.

    1990-03-01

    The behavior of an analog neural network with parallel dynamics is studied analytically and numerically for two associative-memory learning algorithms, the Hebb rule and the pseudoinverse rule. Phase diagrams in the parameter space of analog gain β and storage ratio α are presented. For both learning rules, the networks have large ``recall'' phases in which retrieval states exist and convergence to a fixed point is guaranteed by a global stability criterion. We also demonstrate numerically that using a reduced analog gain increases the probability of recall starting from a random initial state. This phenomenon is comparable to thermal annealing used to escape local minima but has the advantage of being deterministic, and therefore easily implemented in electronic hardware. Similarities and differences between analog neural networks and networks with two-state neurons at finite temperature are also discussed.

  15. Chromosomal Abnormalities Associated with Neural Tube Defects (I: Full Aneuploidy

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2007-12-01

    Full Text Available Fetuses with neural tube defects (NTDs carry a risk of chromosomal abnormalities. The risk varies with maternal age, gestational age at diagnosis, association with other structural abnormalities, and family history of chromosome aberrations. This article provides an overview of chromosomal abnormalities associated with NTDs in embryos, fetuses, and newborn patients, and a comprehensive review of numerical chromosomal abnormalities associated with NTDs, such as trisomy 18, trisomy 13, triploidy, trisomy 9, trisomy 2, trisomy 21, trisomy 7, trisomy 8, trisomy 14, trisomy 15, trisomy 16, trisomy 5 mosaicism, trisomy 11 mosaicism, trisomy 20 mosaicism, monosomy X, and tetraploidy. NTDs may be associated with aneuploidy. Perinatal identification of NTDs should alert one to the possibility of chromosomal abnormalities and prompt a thorough cytogenetic investigation and genetic counseling.

  16. Neural network modeling of associative memory: Beyond the Hopfield model

    Science.gov (United States)

    Dasgupta, Chandan

    1992-07-01

    A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

  17. 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.

  18. [Neural representations of facial identity and its associative meaning].

    Science.gov (United States)

    Eifuku, Satoshi

    2012-07-01

    Since the discovery of "face cells" in the early 1980s, single-cell recording experiments in non-human primates have made significant contributions toward the elucidation of neural mechanisms underlying face perception and recognition. In this paper, we review the recent progress in face cell studies, including the recent remarkable findings of the face patches that are scattered around the anterior temporal cortical areas of monkeys. In particular, we focus on the neural representations of facial identity within these areas. The identification of faces requires both discrimination of facial identities and generalization across facial views. It has been indicated by some laboratories that the population of face cells found in the anterior ventral inferior temporal cortex of monkeys represent facial identity in a manner which is facial view-invariant. These findings suggest a relatively distributed representation that operates for facial identification. It has also been shown that certain individual neurons in the medial temporal lobe of humans represent view-invariant facial identity. This finding suggests a relatively sparse representation that may be employed for memory formation. Finally, we summarize our recent study, showing that the population of face cells in the anterior ventral inferior temporal cortex of monkeys that represent view-invariant facial identity, can also represent learned paired associations between an abstract picture and a particular facial identity, extending our understanding of the function of the anterior ventral inferior temporal cortex in the recognition of associative meanings of faces.

  19. Neural Signaling of Food Healthiness Associated with Emotion Processing.

    Science.gov (United States)

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake.

  20. Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress.

    Science.gov (United States)

    Sadeh, Naomi; Spielberg, Jeffrey M; Warren, Stacie L; Miller, Gregory A; Heller, Wendy

    2014-11-01

    Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing.

  1. Neural dynamics of learning sound-action associations.

    Directory of Open Access Journals (Sweden)

    Adam McNamara

    Full Text Available A motor component is pre-requisite to any communicative act as one must inherently move to communicate. To learn to make a communicative act, the brain must be able to dynamically associate arbitrary percepts to the neural substrate underlying the pre-requisite motor activity. We aimed to investigate whether brain regions involved in complex gestures (ventral pre-motor cortex, Brodmann Area 44 were involved in mediating association between novel abstract auditory stimuli and novel gestural movements. In a functional resonance imaging (fMRI study we asked participants to learn associations between previously unrelated novel sounds and meaningless gestures inside the scanner. We use functional connectivity analysis to eliminate the often present confound of 'strategic covert naming' when dealing with BA44 and to rule out effects of non-specific reductions in signal. Brodmann Area 44, a region incorporating Broca's region showed strong, bilateral, negative correlation of BOLD (blood oxygen level dependent response with learning of sound-action associations during data acquisition. Left-inferior-parietal-lobule (l-IPL and bilateral loci in and around visual area V5, right-orbital-frontal-gyrus, right-hippocampus, left-para-hippocampus, right-head-of-caudate, right-insula and left-lingual-gyrus also showed decreases in BOLD response with learning. Concurrent with these decreases in BOLD response, an increasing connectivity between areas of the imaged network as well as the right-middle-frontal-gyrus with rising learning performance was revealed by a psychophysiological interaction (PPI analysis. The increasing connectivity therefore occurs within an increasingly energy efficient network as learning proceeds. Strongest learning related connectivity between regions was found when analysing BA44 and l-IPL seeds. The results clearly show that BA44 and l-IPL is dynamically involved in linking gesture and sound and therefore provides evidence that one of

  2. Trait motivation moderates neural activation associated with goal pursuit.

    Science.gov (United States)

    Spielberg, Jeffrey M; Miller, Gregory A; Warren, Stacie L; Engels, Anna S; Crocker, Laura D; Sutton, Bradley P; Heller, Wendy

    2012-06-01

    Research has indicated that regions of left and right dorsolateral prefrontal cortex (DLPFC) are involved in integrating the motivational and executive function processes related to, respectively, approach and avoidance goals. Given that sensitivity to pleasant and unpleasant stimuli is an important feature of conceptualizations of approach and avoidance motivation, it is possible that these regions of DLPFC are preferentially activated by valenced stimuli. The present study tested this hypothesis by using a task in which goal pursuit was threatened by distraction from valenced stimuli while functional magnetic resonance imaging data were collected. The analyses examined whether the impact of trait approach and avoidance motivation on the neural processes associated with executive function differed depending on the valence or arousal level of the distractor stimuli. The present findings support the hypothesis that the regions of DLPFC under investigation are involved in integrating motivational and executive function processes, and they also indicate the involvement of a number of other brain areas in maintaining goal pursuit. However, DLPFC did not display differential sensitivity to valence.

  3. Neural representations of novel objects associated with olfactory experience.

    Science.gov (United States)

    Ghio, Marta; Schulze, Patrick; Suchan, Boris; Bellebaum, Christian

    2016-07-15

    Object conceptual knowledge comprises information related to several motor and sensory modalities (e.g. for tools, how they look like, how to manipulate them). Whether and to which extent conceptual object knowledge is represented in the same sensory and motor systems recruited during object-specific learning experience is still a controversial question. A direct approach to assess the experience-dependence of conceptual object representations is based on training with novel objects. The present study extended previous research, which focused mainly on the role of manipulation experience for tool-like stimuli, by considering sensory experience only. Specifically, we examined the impact of experience in the non-dominant olfactory modality on the neural representation of novel objects. Sixteen healthy participants visually explored a set of novel objects during the training phase while for each object an odor (e.g., peppermint) was presented (olfactory-visual training). As control conditions, a second set of objects was only visually explored (visual-only training), and a third set was not part of the training. In a post-training fMRI session, participants performed an old/new task with pictures of objects associated with olfactory-visual and visual-only training (old) and no training objects (new). Although we did not find any evidence of activations in primary olfactory areas, the processing of olfactory-visual versus visual-only training objects elicited greater activation in the right anterior hippocampus, a region included in the extended olfactory network. This finding is discussed in terms of different functional roles of the hippocampus in olfactory processes. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Finite-Time Stability for Fractional-Order Bidirectional Associative Memory Neural Networks with Time Delays

    International Nuclear Information System (INIS)

    Xu Chang-Jin; Li Pei-Luan; Pang Yi-Cheng

    2017-01-01

    This paper is concerned with fractional-order bidirectional associative memory (BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag–Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results. (paper)

  5. Altered Neural Activity Associated with Mindfulness during Nociception: A Systematic Review of Functional MRI.

    Science.gov (United States)

    Bilevicius, Elena; Kolesar, Tiffany A; Kornelsen, Jennifer

    2016-04-19

    To assess the neural activity associated with mindfulness-based alterations of pain perception. The Cochrane Central, EMBASE, Ovid Medline, PsycINFO, Scopus, and Web of Science databases were searched on 2 February 2016. Titles, abstracts, and full-text articles were independently screened by two reviewers. Data were independently extracted from records that included topics of functional neuroimaging, pain, and mindfulness interventions. The literature search produced 946 total records, of which five met the inclusion criteria. Records reported pain in terms of anticipation (n = 2), unpleasantness (n = 5), and intensity (n = 5), and how mindfulness conditions altered the neural activity during noxious stimulation accordingly. Although the studies were inconsistent in relating pain components to neural activity, in general, mindfulness was able to reduce pain anticipation and unpleasantness ratings, as well as alter the corresponding neural activity. The major neural underpinnings of mindfulness-based pain reduction consisted of altered activity in the anterior cingulate cortex, insula, and dorsolateral prefrontal cortex.

  6. Neural associative memories for the integration of language, vision and action in an autonomous agent.

    Science.gov (United States)

    Markert, H; Kaufmann, U; Kara Kayikci, Z; Palm, G

    2009-03-01

    Language understanding is a long-standing problem in computer science. However, the human brain is capable of processing complex languages with seemingly no difficulties. This paper shows a model for language understanding using biologically plausible neural networks composed of associative memories. The model is able to deal with ambiguities on the single word and grammatical level. The language system is embedded into a robot in order to demonstrate the correct semantical understanding of the input sentences by letting the robot perform corresponding actions. For that purpose, a simple neural action planning system has been combined with neural networks for visual object recognition and visual attention control mechanisms.

  7. Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

    Science.gov (United States)

    Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

    2018-04-01

    Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

  8. Dynamic analysis of stochastic bidirectional associative memory neural networks with delays

    International Nuclear Information System (INIS)

    Zhao Hongyong; Ding Nan

    2007-01-01

    In this paper, stochastic bidirectional associative memory neural networks model with delays is considered. By constructing Lyapunov functionals, and using stochastic analysis method and inequality technique, we give some sufficient criteria ensuring almost sure exponential stability, pth exponential stability and mean value exponential stability. The obtained criteria can be used as theoretic guidance to stabilize neural networks in practical applications when stochastic noise is taken into consideration

  9. Global asymptotic stability of hybrid bidirectional associative memory neural networks with time delays

    International Nuclear Information System (INIS)

    Arik, Sabri

    2006-01-01

    This Letter presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. The results are also compared with the previous results derived in the literature

  10. Global robust stability of bidirectional associative memory neural networks with multiple time delays.

    Science.gov (United States)

    Senan, Sibel; Arik, Sabri

    2007-10-01

    This correspondence presents a sufficient condition for the existence, uniqueness, and global robust asymptotic stability of the equilibrium point for bidirectional associative memory neural networks with discrete time delays. The results impose constraint conditions on the network parameters of the neural system independently of the delay parameter, and they are applicable to all bounded continuous nonmonotonic neuron activation functions. Some numerical examples are given to compare our results with the previous robust stability results derived in the literature.

  11. Global asymptotic stability of hybrid bidirectional associative memory neural networks with time delays

    Science.gov (United States)

    Arik, Sabri

    2006-02-01

    This Letter presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. The results are also compared with the previous results derived in the literature.

  12. Two-Layer Feedback Neural Networks with Associative Memories

    International Nuclear Information System (INIS)

    Gui-Kun, Wu; Hong, Zhao

    2008-01-01

    We construct a two-layer feedback neural network by a Monte Carlo based algorithm to store memories as fixed-point attractors or as limit-cycle attractors. Special attention is focused on comparing the dynamics of the network with limit-cycle attractors and with fixed-point attractors. It is found that the former has better retrieval property than the latter. Particularly, spurious memories may be suppressed completely when the memories are stored as a long-limit cycle. Potential application of limit-cycle-attractor networks is discussed briefly. (general)

  13. Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

    Science.gov (United States)

    Gros, Claudius

    2007-02-01

    The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

  14. 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.

  15. Cutaneous vascular anomalies associated with neural tube defects: nomenclature and pathology revisited.

    Science.gov (United States)

    Maugans, Todd; Sheridan, Rachel M; Adams, Denise; Gupta, Anita

    2011-07-01

    Lumbosacral cutaneous vascular anomalies associated with neural tube defects are frequently described in the literature as "hemangiomas." The classification system for pediatric vascular anomalies developed by the International Society for the Study of Vascular Anomalies provides a framework to accurately diagnose these lesions. To apply this classification to vascular cutaneous anomalies overlying myelodysplasias. A retrospective analysis of patients with neural tube defects and lumbosacral cutaneous vascular lesions was performed. All eligible patients had detailed histopathologic analysis of skin and spinal cord/placode lesions. Clinical and radiologic features were analyzed. Conventional histology and GLUT-1 immunostaining were performed to differentiate infantile capillary hemangiomas from capillary vascular malformations. Ten cases with cutaneous lesions associated with neural tube defects were reviewed. Five lesions were diagnosed as infantile capillary hemangiomas based upon histology and positive GLUT-1 endothelial reactivity. These lesions had a strong association with dermal sinus tracts. No reoperations were required for residual intraspinal vascular lesions, and overlying cutaneous vascular anomalies involuted with time. The remaining 5 lesions were diagnosed as capillary malformations. These occurred with both open and closed neural tube defects, did not involute, and demonstrated enlargement and darkening due to vascular congestion. The International Society for the Study of Vascular Anomalies scheme should be used to describe the cutaneous vascular lesions associated with neural tube defects: infantile capillary hemangiomas and capillary malformations. We advocate that these lesions be described as "vascular anomalies" or "stains" pending accurate diagnosis by clinical, histological, and immunohistochemical evaluations.

  16. Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

    Science.gov (United States)

    Qu, Jing; Qian, Liu; Chen, Chuansheng; Xue, Gui; Li, Huiling; Xie, Peng; Mei, Leilei

    2017-01-01

    Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO) and fusiform gyrus (FG) before training was negatively associated with reaction time (RT) in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory. PMID:28878640

  17. Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

    Directory of Open Access Journals (Sweden)

    Jing Qu

    2017-08-01

    Full Text Available Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO and fusiform gyrus (FG before training was negatively associated with reaction time (RT in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory.

  18. Stationary oscillation for nonautonomous bidirectional associative memory neural networks with impulse

    International Nuclear Information System (INIS)

    Zhang Yinping

    2009-01-01

    In this paper, we study the existence, uniqueness and global stability of periodic solution (i.e. stationary oscillation) for general bidirectional associative memory neural networks with impulses. Some sufficient conditions are obtained for stationary oscillation of the nonautonomous bidirectional associative memory neural networks with impulses. It is derived by using a new method which is different from those of previous literatures, and a assumption in previous results does not required. The model considered is more general and some previous results are extended and improved. An illustrative example is given to demonstrate the effectiveness and less conservativeness of the obtained results.

  19. Neural activity associated with metaphor comprehension: spatial analysis.

    Science.gov (United States)

    Sotillo, María; Carretié, Luis; Hinojosa, José A; Tapia, Manuel; Mercado, Francisco; López-Martín, Sara; Albert, Jacobo

    2005-01-03

    Though neuropsychological data indicate that the right hemisphere (RH) plays a major role in metaphor processing, other studies suggest that, at least during some phases of this processing, a RH advantage may not exist. The present study explores, through a temporally agile neural signal--the event-related potentials (ERPs)--, and through source-localization algorithms applied to ERP recordings, whether the crucial phase of metaphor comprehension presents or not a RH advantage. Participants (n=24) were submitted to a S1-S2 experimental paradigm. S1 consisted of visually presented metaphoric sentences (e.g., "Green lung of the city"), followed by S2, which consisted of words that could (i.e., "Park") or could not (i.e., "Semaphore") be defined by S1. ERPs elicited by S2 were analyzed using temporal principal component analysis (tPCA) and source-localization algorithms. These analyses revealed that metaphorically related S2 words showed significantly higher N400 amplitudes than non-related S2 words. Source-localization algorithms showed differential activity between the two S2 conditions in the right middle/superior temporal areas. These results support the existence of an important RH contribution to (at least) one phase of metaphor processing and, furthermore, implicate the temporal cortex with respect to that contribution.

  20. Peripheral neuropathies associated with antibodies directed to intracellular neural antigens.

    Science.gov (United States)

    Antoine, J-C

    2014-10-01

    Antibodies directed to intracellular neural antigens have been mainly described in paraneoplastic peripheral neuropathies and mostly includes anti-Hu and anti-CV2/CRMP5 antibodies. These antibodies occur with different patterns of neuropathy. With anti-Hu antibody, the most frequent manifestation is sensory neuronopathy with frequent autonomic involvement. With anti-CV2/CRMP5 the neuropathy is more frequently sensory and motor with an axonal or mixed demyelinating and axonal electrophysiological pattern. The clinical pattern of these neuropathies is in keeping with the cellular distribution of HuD and CRMP5 in the peripheral nervous system. Although present in high titer, these antibodies are probably not directly responsible for the neuropathy. Pathological and experimental studies indicate that cytotoxic T-cells are probably the main effectors of the immune response. These disorders contrast with those in which antibodies recognize a cell surface antigen and are probably responsible for the disease. The neuronal cell death and axonal degeneration which result from T-cell mediated immunity explains why treating these disorders remains challenging. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

  1. Hopf bifurcation of an (n + 1) -neuron bidirectional associative memory neural network model with delays.

    Science.gov (United States)

    Xiao, Min; Zheng, Wei Xing; Cao, Jinde

    2013-01-01

    Recent studies on Hopf bifurcations of neural networks with delays are confined to simplified neural network models consisting of only two, three, four, five, or six neurons. It is well known that neural networks are complex and large-scale nonlinear dynamical systems, so the dynamics of the delayed neural networks are very rich and complicated. Although discussing the dynamics of networks with a few neurons may help us to understand large-scale networks, there are inevitably some complicated problems that may be overlooked if simplified networks are carried over to large-scale networks. In this paper, a general delayed bidirectional associative memory neural network model with n + 1 neurons is considered. By analyzing the associated characteristic equation, the local stability of the trivial steady state is examined, and then the existence of the Hopf bifurcation at the trivial steady state is established. By applying the normal form theory and the center manifold reduction, explicit formulae are derived to determine the direction and stability of the bifurcating periodic solution. Furthermore, the paper highlights situations where the Hopf bifurcations are particularly critical, in the sense that the amplitude and the period of oscillations are very sensitive to errors due to tolerances in the implementation of neuron interconnections. It is shown that the sensitivity is crucially dependent on the delay and also significantly influenced by the feature of the number of neurons. Numerical simulations are carried out to illustrate the main results.

  2. Convergence analysis of stochastic hybrid bidirectional associative memory neural networks with delays

    International Nuclear Information System (INIS)

    Wan Li; Zhou Qinghua

    2007-01-01

    The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem

  3. Application of associative emulator neural network for power control of nuclear reactor

    International Nuclear Information System (INIS)

    Datta, A.K.; Bandyopadhyay, Somnath

    1993-01-01

    This paper addresses the question of how to perform on-line training of emulator neural network for power control in a nuclear reactor. The computation and convergence problem can be reduced by judicious choice of bidirectional associative recall. (author). 10 refs., 2 figs

  4. Robust stability of bidirectional associative memory neural networks with time delays

    Science.gov (United States)

    Park, Ju H.

    2006-01-01

    Based on the Lyapunov Krasovskii functionals combined with linear matrix inequality approach, a novel stability criterion is proposed for asymptotic stability of bidirectional associative memory neural networks with time delays. A novel delay-dependent stability criterion is given in terms of linear matrix inequalities, which can be solved easily by various optimization algorithms.

  5. Robust stability of bidirectional associative memory neural networks with time delays

    International Nuclear Information System (INIS)

    Park, Ju H.

    2006-01-01

    Based on the Lyapunov-Krasovskii functionals combined with linear matrix inequality approach, a novel stability criterion is proposed for asymptotic stability of bidirectional associative memory neural networks with time delays. A novel delay-dependent stability criterion is given in terms of linear matrix inequalities, which can be solved easily by various optimization algorithms

  6. Convergence analysis of stochastic hybrid bidirectional associative memory neural networks with delays

    Science.gov (United States)

    Wan, Li; Zhou, Qinghua

    2007-10-01

    The stability property of stochastic hybrid bidirectional associate memory (BAM) neural networks with discrete delays is considered. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the delay-independent sufficient conditions to guarantee the exponential stability of the equilibrium solution for such networks are given by using the nonnegative semimartingale convergence theorem.

  7. Discrete-time bidirectional associative memory neural networks with variable delays

    International Nuclear Information System (INIS)

    Liang Jinling; Cao Jinde; Ho, Daniel W.C.

    2005-01-01

    Based on the linear matrix inequality (LMI), some sufficient conditions are presented in this Letter for the existence, uniqueness and global exponential stability of the equilibrium point of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Some of the stability criteria obtained in this Letter are delay-dependent, and some of them are delay-independent, they are less conservative than the ones reported so far in the literature. Furthermore, the results provide one more set of easily verified criteria for determining the exponential stability of discrete-time BAM neural networks

  8. Global asymptotic stability analysis of bidirectional associative memory neural networks with time delays.

    Science.gov (United States)

    Arik, Sabri

    2005-05-01

    This paper presents a sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with distributed time delays. The results impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all continuous nonmonotonic neuron activation functions. It is shown that in some special cases of the results, the stability criteria can be easily checked. Some examples are also given to compare the results with the previous results derived in the literature.

  9. Global asymptotic stability analysis of bidirectional associative memory neural networks with distributed delays and impulse

    International Nuclear Information System (INIS)

    Huang Zaitang; Luo Xiaoshu; Yang Qigui

    2007-01-01

    Many systems existing in physics, chemistry, biology, engineering and information science can be characterized by impulsive dynamics caused by abrupt jumps at certain instants during the process. These complex dynamical behaviors can be model by impulsive differential system or impulsive neural networks. This paper formulates and studies a new model of impulsive bidirectional associative memory (BAM) networks with finite distributed delays. Several fundamental issues, such as global asymptotic stability and existence and uniqueness of such BAM neural networks with impulse and distributed delays, are established

  10. Periodic oscillation of higher-order bidirectional associative memory neural networks with periodic coefficients and delays

    Science.gov (United States)

    Ren, Fengli; Cao, Jinde

    2007-03-01

    In this paper, several sufficient conditions are obtained ensuring existence, global attractivity and global asymptotic stability of the periodic solution for the higher-order bidirectional associative memory neural networks with periodic coefficients and delays by using the continuation theorem of Mawhin's coincidence degree theory, the Lyapunov functional and the non-singular M-matrix. Two examples are exploited to illustrate the effectiveness of the proposed criteria. These results are more effective than the ones in the literature for some neural networks, and can be applied to the design of globally attractive or globally asymptotically stable networks and thus have important significance in both theory and applications.

  11. Discrete-time bidirectional associative memory neural networks with variable delays

    Science.gov (United States)

    Liang, variable delays [rapid communication] J.; Cao, J.; Ho, D. W. C.

    2005-02-01

    Based on the linear matrix inequality (LMI), some sufficient conditions are presented in this Letter for the existence, uniqueness and global exponential stability of the equilibrium point of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Some of the stability criteria obtained in this Letter are delay-dependent, and some of them are delay-independent, they are less conservative than the ones reported so far in the literature. Furthermore, the results provide one more set of easily verified criteria for determining the exponential stability of discrete-time BAM neural networks.

  12. New results for global robust stability of bidirectional associative memory neural networks with multiple time delays

    International Nuclear Information System (INIS)

    Senan, Sibel; Arik, Sabri

    2009-01-01

    This paper presents some new sufficient conditions for the global robust asymptotic stability of the equilibrium point for bidirectional associative memory (BAM) neural networks with multiple time delays. The results we obtain impose constraint conditions on the network parameters of neural system independently of the delay parameter, and they are applicable to all bounded continuous non-monotonic neuron activation functions. We also give some numerical examples to demonstrate the applicability and effectiveness of our results, and compare the results with the previous robust stability results derived in the literature.

  13. Association of contextual cues with morphine reward increases neural and synaptic plasticity in the ventral hippocampus of rats

    NARCIS (Netherlands)

    Alvandi, M.S.; Bourmpoula, M.; Homberg, J.R.; Fathollahi, Y.

    2017-01-01

    Drug addiction is associated with aberrant memory and permanent functional changes in neural circuits. It is known that exposure to drugs like morphine is associated with positive emotional states and reward-related memory. However, the underlying mechanisms in terms of neural plasticity in the

  14. Altered Neural Activity Associated with Mindfulness during Nociception: A Systematic Review of Functional MRI

    Directory of Open Access Journals (Sweden)

    Elena Bilevicius

    2016-04-01

    Full Text Available Objective: To assess the neural activity associated with mindfulness-based alterations of pain perception. Methods: The Cochrane Central, EMBASE, Ovid Medline, PsycINFO, Scopus, and Web of Science databases were searched on 2 February 2016. Titles, abstracts, and full-text articles were independently screened by two reviewers. Data were independently extracted from records that included topics of functional neuroimaging, pain, and mindfulness interventions. Results: The literature search produced 946 total records, of which five met the inclusion criteria. Records reported pain in terms of anticipation (n = 2, unpleasantness (n = 5, and intensity (n = 5, and how mindfulness conditions altered the neural activity during noxious stimulation accordingly. Conclusions: Although the studies were inconsistent in relating pain components to neural activity, in general, mindfulness was able to reduce pain anticipation and unpleasantness ratings, as well as alter the corresponding neural activity. The major neural underpinnings of mindfulness-based pain reduction consisted of altered activity in the anterior cingulate cortex, insula, and dorsolateral prefrontal cortex.

  15. Explaining neural signals in human visual cortex with an associative learning model.

    Science.gov (United States)

    Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

    2012-08-01

    "Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals.

  16. Neural and behavioral associations of manipulated determination facial expressions

    NARCIS (Netherlands)

    Price, Tom F.; Hortensius, R.; Harmon-Jones, Eddie

    Past research associated relative left frontal cortical activity with positive affect and approach motivation, or the urge to move toward a stimulus. Less work has examined relative left frontal activity and positive emotions ranging from low to high approach motivation, to test whether positive

  17. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (IV)

    OpenAIRE

    Chen, Chih-Ping

    2008-01-01

    Fetuses with neural tube defects (NTDs) may be associated with maternal and fetal risk factors. This article provides a comprehensive review of maternal and fetal risk factors associated with NTDs, such as infertility, periconceptional clomiphene use and assisted reproductive technology, periconceptional folic acid deficiency and effects offolic acid supplementation and fortification on NTD rates, periconceptional vitamin B1 2 deficiency, single nucleotide polymorphisms and polymorphisms in g...

  18. Neural activation to monetary reward is associated with amphetamine reward sensitivity.

    Science.gov (United States)

    Crane, Natania A; Gorka, Stephanie M; Weafer, Jessica; Langenecker, Scott A; de Wit, Harriet; Phan, K Luan

    2018-03-14

    One known risk factor for drug use and abuse is sensitivity to rewarding effects of drugs. It is not known whether this risk factor extends to sensitivity to non-drug rewards. In this study with healthy young adults, we examined the association between sensitivity to the subjective rewarding effects of amphetamine and a neural indicator of anticipation of monetary reward. We hypothesized that greater euphorigenic response to amphetamine would be associated with greater neural activation to anticipation of monetary reward (Win > Loss). Healthy participants (N = 61) completed four laboratory sessions in which they received d-amphetamine (20 mg) and placebo in alternating order, providing self-report measures of euphoria and stimulation at regular intervals. At a separate visit 1-3 weeks later, participants completed the guessing reward task (GRT) during fMRI in a drug-free state. Participants reporting greater euphoria after amphetamine also exhibited greater neural activation during monetary reward anticipation in mesolimbic reward regions, including the bilateral caudate and putamen. This is the first study to show a relationship between neural correlates of monetary reward and sensitivity to the subjective rewarding effects of amphetamine in humans. These findings support growing evidence that sensitivity to reward in general is a risk factor for drug use and abuse, and suggest that sensitivity of drug-induced euphoria may reflect a general sensitivity to rewards. This may be an index of vulnerability for drug use or abuse.

  19. Body mass is positively associated with neural response to sweet taste, but not alcohol, among drinkers.

    Science.gov (United States)

    Gardiner, Casey K; YorkWilliams, Sophie L; Bryan, Angela D; Hutchison, Kent E

    2017-07-28

    Obesity is a large and growing public health concern, presenting enormous economic and health costs to individuals and society. A burgeoning literature demonstrates that overweight and obese individuals display different neural processing of rewarding stimuli, including caloric substances, as compared to healthy weight individuals. However, much extant research on the neurobiology of obesity has focused on addiction models, without highlighting potentially separable neural underpinnings of caloric intake versus substance use. The present research explores these differences by examining neural response to alcoholic beverages and a sweet non-alcoholic beverage, among a sample of individuals with varying weight status and patterns of alcohol use and misuse. Participants received tastes of a sweet beverage (litchi juice) and alcoholic beverages during fMRI scanning. When controlling for alcohol use, elevated weight status was associated with increased activation in response to sweet taste in regions including the cingulate cortex, hippocampus, precuneus, and fusiform gyrus. However, weight status was not associated with neural response to alcoholic beverages. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Neural Correlates Associated with Successful Working Memory Performance in Older Adults as Revealed by Spatial ICA

    Science.gov (United States)

    Saliasi, Emi; Geerligs, Linda; Lorist, Monicque M.; Maurits, Natasha M.

    2014-01-01

    To investigate which neural correlates are associated with successful working memory performance, fMRI was recorded in healthy younger and older adults during performance on an n-back task with varying task demands. To identify functional networks supporting working memory processes, we used independent component analysis (ICA) decomposition of the fMRI data. Compared to younger adults, older adults showed a larger neural (BOLD) response in the more complex (2-back) than in the baseline (0-back) task condition, in the ventral lateral prefrontal cortex (VLPFC) and in the right fronto-parietal network (FPN). Our results indicated that a higher BOLD response in the VLPFC was associated with increased performance accuracy in older adults, in both the baseline and the more complex task condition. This ‘BOLD-performance’ relationship suggests that the neural correlates linked with successful performance in the older adults are not uniquely related to specific working memory processes present in the complex but not in the baseline task condition. Furthermore, the selective presence of this relationship in older but not in younger adults suggests that increased neural activity in the VLPFC serves a compensatory role in the aging brain which benefits task performance in the elderly. PMID:24911016

  1. Neural and behavioral associations of manipulated determination facial expressions.

    Science.gov (United States)

    Price, Tom F; Hortensius, Ruud; Harmon-Jones, Eddie

    2013-09-01

    Past research associated relative left frontal cortical activity with positive affect and approach motivation, or the urge to move toward a stimulus. Less work has examined relative left frontal activity and positive emotions ranging from low to high approach motivation, to test whether positive affects that differ in approach motivational intensity influence relative left frontal cortical activity. Participants in the present experiment adopted determination (high approach positive), satisfaction (low approach positive), or neutral facial expressions while electroencephalographic (EEG) activity was recorded. Next, participants completed a task measuring motivational persistence behavior and then they completed self-report emotion questionnaires. Determination compared to satisfaction and neutral facial expressions caused greater relative left frontal activity relative to baseline EEG recordings. Facial expressions did not directly influence task persistence. However, relative left frontal activity correlated positively with persistence on insolvable tasks in the determination condition. These results extend embodiment theories and motivational interpretations of relative left frontal activity. Published by Elsevier B.V.

  2. Neural processing associated with cognitive and affective Theory of Mind in adolescents and adults.

    Science.gov (United States)

    Sebastian, Catherine L; Fontaine, Nathalie M G; Bird, Geoffrey; Blakemore, Sarah-Jayne; Brito, Stephane A De; McCrory, Eamon J P; Viding, Essi

    2012-01-01

    Theory of Mind (ToM) is the ability to attribute thoughts, intentions and beliefs to others. This involves component processes, including cognitive perspective taking (cognitive ToM) and understanding emotions (affective ToM). This study assessed the distinction and overlap of neural processes involved in these respective components, and also investigated their development between adolescence and adulthood. While data suggest that ToM develops between adolescence and adulthood, these populations have not been compared on cognitive and affective ToM domains. Using fMRI with 15 adolescent (aged 11-16 years) and 15 adult (aged 24-40 years) males, we assessed neural responses during cartoon vignettes requiring cognitive ToM, affective ToM or physical causality comprehension (control). An additional aim was to explore relationships between fMRI data and self-reported empathy. Both cognitive and affective ToM conditions were associated with neural responses in the classic ToM network across both groups, although only affective ToM recruited medial/ventromedial PFC (mPFC/vmPFC). Adolescents additionally activated vmPFC more than did adults during affective ToM. The specificity of the mPFC/vmPFC response during affective ToM supports evidence from lesion studies suggesting that vmPFC may integrate affective information during ToM. Furthermore, the differential neural response in vmPFC between adult and adolescent groups indicates developmental changes in affective ToM processing.

  3. Dynamics of continuous-time bidirectional associative memory neural networks with impulses and their discrete counterparts

    International Nuclear Information System (INIS)

    Huo Haifeng; Li Wantong

    2009-01-01

    This paper is concerned with the global stability characteristics of a system of equations modelling the dynamics of continuous-time bidirectional associative memory neural networks with impulses. Sufficient conditions which guarantee the existence of a unique equilibrium and its exponential stability of the networks are obtained. For the goal of computation, discrete-time analogues of the corresponding continuous-time bidirectional associative memory neural networks with impulses are also formulated and studied. Our results show that the above continuous-time and discrete-time systems with impulses preserve the dynamics of the networks without impulses when we make some modifications and impose some additional conditions on the systems, the convergence characteristics dynamics of the networks are preserved by both continuous-time and discrete-time systems with some restriction imposed on the impulse effect.

  4. Finite-Time Stability for Fractional-Order Bidirectional Associative Memory Neural Networks with Time Delays

    Science.gov (United States)

    Xu, Chang-Jin; Li, Pei-Luan; Pang, Yi-Cheng

    2017-02-01

    This paper is concerned with fractional-order bidirectional associative memory (BAM) neural networks with time delays. Applying Laplace transform, the generalized Gronwall inequality and estimates of Mittag-Leffler functions, some sufficient conditions which ensure the finite-time stability of fractional-order bidirectional associative memory neural networks with time delays are obtained. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results. Supported by National Natural Science Foundation of China under Grant Nos.~61673008, 11261010, 11101126, Project of High-Level Innovative Talents of Guizhou Province ([2016]5651), Natural Science and Technology Foundation of Guizhou Province (J[2015]2025 and J[2015]2026), 125 Special Major Science and Technology of Department of Education of Guizhou Province ([2012]011) and Natural Science Foundation of the Education Department of Guizhou Province (KY[2015]482)

  5. NEURAL AND CARDIAC TOXICITIES ASSOCIATED WITH 3,4-METHYLENEDIOXYMETHAMPHETAMINE (MDMA)

    OpenAIRE

    Baumann, Michael H.; Rothman, Richard B.

    2009-01-01

    (±)-3,4-Methylenedioxymethamphetamine (MDMA) is a commonly abused illicit drug which affects multiple organ systems. In animals, high-dose administration of MDMA produces deficits in serotonin (5-HT) neurons (e.g., depletion of forebrain 5-HT) that have been viewed as neurotoxicity. Recent data implicate MDMA in the development of valvular heart disease (VHD). The present paper reviews several issues related to MDMA-associated neural and cardiac toxicities. The hypothesis of MDMA neurotoxicit...

  6. On exponential stability of bidirectional associative memory neural networks with time-varying delays

    International Nuclear Information System (INIS)

    Park, Ju H.; Lee, S.M.; Kwon, O.M.

    2009-01-01

    For bidirectional associate memory neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov functional method and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. A numerical example is given to demonstrate the effectiveness of the obtained results.

  7. Associations between maternal negative affect and adolescent's neural response to peer evaluation

    Science.gov (United States)

    Tan, Patricia Z.; Lee, Kyung Hwa; Dahl, Ronald E.; Nelson, Eric E.; Stroud, Laura J.; Siegle, Greg J.; Morgan, Judith K.; Silk, Jennifer S.

    2016-01-01

    Parenting is often implicated as a potential source of individual differences in youths’ emotional information processing. The present study examined whether parental affect is related to an important aspect of adolescent emotional development, response to peer evaluation. Specifically, we examined relations between maternal negative affect, observed during parent–adolescent discussion of an adolescent-nominated concern with which s/he wants parental support, and adolescent neural responses to peer evaluation in 40 emotionally healthy and depressed adolescents. We focused on a network of ventral brain regions involved in affective processing of social information: the amygdala, anterior insula, nucleus accumbens, and subgenual anterior cingulate, as well as the ventrolateral prefrontal cortex. Maternal negative affect was not associated with adolescent neural response to peer rejection. However, longer durations of maternal negative affect were associated with decreased responsivity to peer acceptance in the amygdala, left anterior insula, subgenual anterior cingulate, and left nucleus accumbens. These findings provide some of the first evidence that maternal negative affect is associated with adolescents’ neural processing of social rewards. Findings also suggest that maternal negative affect could contribute to alterations in affective processing, specifically, dampening the saliency and/or reward of peer interactions during adolescence. PMID:24613174

  8. Associations between maternal negative affect and adolescent's neural response to peer evaluation

    Directory of Open Access Journals (Sweden)

    Patricia Z. Tan

    2014-04-01

    Full Text Available Parenting is often implicated as a potential source of individual differences in youths’ emotional information processing. The present study examined whether parental affect is related to an important aspect of adolescent emotional development, response to peer evaluation. Specifically, we examined relations between maternal negative affect, observed during parent–adolescent discussion of an adolescent-nominated concern with which s/he wants parental support, and adolescent neural responses to peer evaluation in 40 emotionally healthy and depressed adolescents. We focused on a network of ventral brain regions involved in affective processing of social information: the amygdala, anterior insula, nucleus accumbens, and subgenual anterior cingulate, as well as the ventrolateral prefrontal cortex. Maternal negative affect was not associated with adolescent neural response to peer rejection. However, longer durations of maternal negative affect were associated with decreased responsivity to peer acceptance in the amygdala, left anterior insula, subgenual anterior cingulate, and left nucleus accumbens. These findings provide some of the first evidence that maternal negative affect is associated with adolescents’ neural processing of social rewards. Findings also suggest that maternal negative affect could contribute to alterations in affective processing, specifically, dampening the saliency and/or reward of peer interactions during adolescence.

  9. Lack of association between folate-receptor autoantibodies and neural-tube defects.

    LENUS (Irish Health Repository)

    Molloy, Anne M

    2009-07-09

    BACKGROUND: A previous report described the presence of autoantibodies against folate receptors in 75% of serum samples from women with a history of pregnancy complicated by a neural-tube defect, as compared with 10% of controls. We sought to confirm this finding in an Irish population, which traditionally has had a high prevalence of neural-tube defects. METHODS: We performed two studies. Study 1 consisted of analysis of stored frozen blood samples collected from 1993 through 1994 from 103 mothers with a history of pregnancy complicated by a neural-tube defect (case mothers), 103 mothers with a history of pregnancy but no complication by a neural-tube defect (matched with regard to number of pregnancies and sampling dates), 58 women who had never been pregnant, and 36 men. Study 2, conducted to confirm that the storage of samples did not influence the folate-receptor autoantibodies, included fresh samples from 37 case mothers, 22 control mothers, 10 women who had never been pregnant, and 9 men. All samples were assayed for blocking and binding autoantibodies against folate receptors. RESULTS: In Study 1, blocking autoantibodies were found in 17% of case mothers, as compared with 13% of control mothers (odds ratio, 1.54; 95% confidence interval [CI], 0.70 to 3.39), and binding autoantibodies in 29%, as compared with 32%, respectively (odds ratio, 0.82; 95% CI, 0.44 to 1.50). Study 2 showed similar results, indicating that sample degradation was unlikely. CONCLUSIONS: The presence and titer of maternal folate-receptor autoantibodies were not significantly associated with a neural-tube defect-affected pregnancy in this Irish population.

  10. Social anhedonia is associated with neural abnormalities during face emotion processing.

    Science.gov (United States)

    Germine, Laura T; Garrido, Lucia; Bruce, Lori; Hooker, Christine

    2011-10-01

    Human beings are social organisms with an intrinsic desire to seek and participate in social interactions. Social anhedonia is a personality trait characterized by a reduced desire for social affiliation and reduced pleasure derived from interpersonal interactions. Abnormally high levels of social anhedonia prospectively predict the development of schizophrenia and contribute to poorer outcomes for schizophrenia patients. Despite the strong association between social anhedonia and schizophrenia, the neural mechanisms that underlie individual differences in social anhedonia have not been studied and are thus poorly understood. Deficits in face emotion recognition are related to poorer social outcomes in schizophrenia, and it has been suggested that face emotion recognition deficits may be a behavioral marker for schizophrenia liability. In the current study, we used functional magnetic resonance imaging (fMRI) to see whether there are differences in the brain networks underlying basic face emotion processing in a community sample of individuals low vs. high in social anhedonia. We isolated the neural mechanisms related to face emotion processing by comparing face emotion discrimination with four other baseline conditions (identity discrimination of emotional faces, identity discrimination of neutral faces, object discrimination, and pattern discrimination). Results showed a group (high/low social anhedonia) × condition (emotion discrimination/control condition) interaction in the anterior portion of the rostral medial prefrontal cortex, right superior temporal gyrus, and left somatosensory cortex. As predicted, high (relative to low) social anhedonia participants showed less neural activity in face emotion processing regions during emotion discrimination as compared to each control condition. The findings suggest that social anhedonia is associated with abnormalities in networks responsible for basic processes associated with social cognition, and provide a

  11. Clique-Based Neural Associative Memories with Local Coding and Precoding.

    Science.gov (United States)

    Mofrad, Asieh Abolpour; Parker, Matthew G; Ferdosi, Zahra; Tadayon, Mohammad H

    2016-08-01

    Techniques from coding theory are able to improve the efficiency of neuroinspired and neural associative memories by forcing some construction and constraints on the network. In this letter, the approach is to embed coding techniques into neural associative memory in order to increase their performance in the presence of partial erasures. The motivation comes from recent work by Gripon, Berrou, and coauthors, which revisited Willshaw networks and presented a neural network with interacting neurons that partitioned into clusters. The model introduced stores patterns as small-size cliques that can be retrieved in spite of partial error. We focus on improving the success of retrieval by applying two techniques: doing a local coding in each cluster and then applying a precoding step. We use a slightly different decoding scheme, which is appropriate for partial erasures and converges faster. Although the ideas of local coding and precoding are not new, the way we apply them is different. Simulations show an increase in the pattern retrieval capacity for both techniques. Moreover, we use self-dual additive codes over field [Formula: see text], which have very interesting properties and a simple-graph representation.

  12. Neural markers of neuropathic pain associated with maladaptive plasticity in spinal cord injury.

    Science.gov (United States)

    Pascoal-Faria, Paula; Yalcin, Nilufer; Fregni, Felipe

    2015-04-01

    Given the potential use of neural markers for the development of novel treatments in spinal cord pain, we aimed to characterize the most effective neural markers of neuropathic pain following spinal cord injury (SCI). A systematic PubMed review was conducted, compiling studies that were published prior to April, 2014 that examined neural markers associated with neuropathic pain after SCI using electrophysiological and neuroimaging techniques. We identified 6 studies: Four using electroencephalogram (EEG); 1 using magnetic resonance imaging (MRI) and FDG-PET (positron emission tomography); and 1 using MR spectroscopy. The EEG recordings suggested a reduction in alpha EEG peak frequency activity in the frontal regions of SCI patients with neuropathic pain. The MRI scans showed volume loss, primarily in the gray matter of the left dorsolateral prefrontal cortex, and by FDG-PET, hypometabolism in the medial prefrontal cortex was observed in SCI patients with neuropathic pain compared with healthy subjects. In the MR spectroscopy findings, the presence of pain was associated with changes in the prefrontal cortex and anterior cingulate cortex. When analyzed together, the results of these studies seem to point out to a common marker of pain in SCI characterized by decreased cortical activity in frontal areas and possibly increased subcortical activity. These results may contribute to planning further mechanistic studies as to better understand the mechanisms by which neuropathic pain is modulated in patients with SCI as well as clinical studies investigating best responders of treatment. © 2014 World Institute of Pain.

  13. Syndromes, disorders and maternal risk factors associated with neural tube defects (I).

    Science.gov (United States)

    Chen, Chih-Ping

    2008-03-01

    Fetuses with neural tube defects (NTDs) may be associated with syndromes, disorders, and maternal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal risk factors associated with NTDs, such as acrocallosal syndrome, autosomal dominant brachydactyly-clinodactyly syndrome, Manouvrier syndrome, short rib-polydactyly syndrome, Disorganization ( Ds )-like human malformations, isolated hemihyperplasia, X-linked NTDs, meroanencephaly, schisis association, diprosopus, fetal valproate syndrome, DiGeorge syndrome/velocardiofacial syndrome, Waardenburg syndrome, folic acid antagonists, diabetes mellitus, and obesity. NTDs associated with syndromes, disorders, and maternal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders, and maternal risk factors may be different from those of non-syndromic multifactorial NTDs. Perinatal identification of NTDs should alert one to the syndromes, disorders, and maternal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling.

  14. Robust stability of interval bidirectional associative memory neural network with time delays.

    Science.gov (United States)

    Liao, Xiaofeng; Wong, Kwok-wo

    2004-04-01

    In this paper, the conventional bidirectional associative memory (BAM) neural network with signal transmission delay is intervalized in order to study the bounded effect of deviations in network parameters and external perturbations. The resultant model is referred to as a novel interval dynamic BAM (IDBAM) model. By combining a number of different Lyapunov functionals with the Razumikhin technique, some sufficient conditions for the existence of unique equilibrium and robust stability are derived. These results are fairly general and can be verified easily. To go further, we extend our investigation to the time-varying delay case. Some robust stability criteria for BAM with perturbations of time-varying delays are derived. Besides, our approach for the analysis allows us to consider several different types of activation functions, including piecewise linear sigmoids with bounded activations as well as the usual C1-smooth sigmoids. We believe that the results obtained have leading significance in the design and application of BAM neural networks.

  15. Robust stability for stochastic bidirectional associative memory neural networks with time delays

    Science.gov (United States)

    Shu, H. S.; Lv, Z. W.; Wei, G. L.

    2008-02-01

    In this paper, the asymptotic stability is considered for a class of uncertain stochastic bidirectional associative memory neural networks with time delays and parameter uncertainties. The delays are time-invariant and the uncertainties are norm-bounded that enter into all network parameters. The aim of this paper is to establish easily verifiable conditions under which the delayed neural network is robustly asymptotically stable in the mean square for all admissible parameter uncertainties. By employing a Lyapunov-Krasovskii functional and conducting the stochastic analysis, a linear matrix inequality matrix inequality (LMI) approach is developed to derive the stability criteria. The proposed criteria can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed criteria.

  16. Convergence dynamics of hybrid bidirectional associative memory neural networks with distributed delays

    International Nuclear Information System (INIS)

    Liao Xiaofeng; Wong, K.-W.; Yang Shizhong

    2003-01-01

    In this Letter, the characteristics of the convergence dynamics of hybrid bidirectional associative memory neural networks with distributed transmission delays are studied. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the Lyapunov functionals are constructed and the generalized Halanay-type inequalities are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Some examples are given to illustrate the correctness of our results

  17. Distinct Neural Activity Associated with Focused-Attention Meditation and Loving-Kindness Meditation

    Science.gov (United States)

    Lee, Tatia M. C.; Leung, Mei-Kei; Hou, Wai-Kai; Tang, Joey C. Y.; Yin, Jing; So, Kwok-Fai; Lee, Chack-Fan; Chan, Chetwyn C. H.

    2012-01-01

    This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (loving-kindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotion-processing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing. PMID:22905090

  18. Identifying temporal and causal contributions of neural processes underlying the Implicit Association Test (IAT

    Directory of Open Access Journals (Sweden)

    Chad Edward Forbes

    2012-11-01

    Full Text Available The Implicit Association Test (IAT is a popular behavioral measure that assesses the associative strength between outgroup members and stereotypical and counterstereotypical traits. Less is known, however, about the degree to which the IAT reflects automatic processing. Two studies examined automatic processing contributions to a gender-IAT using a data driven, social neuroscience approach. Performance on congruent (e.g., categorizing male names with synonyms of strength and incongruent (e.g., categorizing female names with synonyms of strength IAT blocks were separately analyzed using EEG (event-related potentials, or ERPs, and coherence; Study 1 and lesion (Study 2 methodologies. Compared to incongruent blocks, performance on congruent IAT blocks was associated with more positive ERPs that manifested in frontal and occipital regions at automatic processing speeds, occipital regions at more controlled processing speeds and was compromised by volume loss in the anterior temporal lobe, insula and medial PFC. Performance on incongruent blocks was associated with volume loss in supplementary motor areas, cingulate gyrus and a region in medial PFC similar to that found for congruent blocks. Greater coherence was found between frontal and occipital regions to the extent individuals exhibited more bias. This suggests there are separable neural contributions to congruent and incongruent blocks of the IAT but there is also a surprising amount of overlap. Given the temporal and regional neural distinctions, these results provide converging evidence that stereotypic associative strength assessed by the IAT indexes automatic processing to a degree.

  19. Syndromes, Disorders and Maternal Risk Factors Associated With Neural Tube Defects (VI

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-09-01

    Full Text Available Neural tube defects (NTDs may be associated with syndromes, disorders, and maternal and fetal risk factors. This article provides a comprehensive review of the syndromes, disorders, and maternal and fetal risk factors associated with NTDs, including maternal fumonisin consumption, periconceptional zinc deficiency, parental occupational exposure and residential proximity to pesticides, lower socioeconomic status, fetal alcohol syndrome, mutations in the VANGL1 gene, human athymic Nude/SCID fetus, and single nucleotide polymorphism in the NOS3 gene. NTDs associated with these syndromes, disorders, and maternal and fetal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders and maternal risk factors may be different from those of nonsyndromic multifactorial NTDs. Perinatal diagnosis of NTDs should alert doctors to the syndromes, disorders, and maternal and fetal risk factors associated with NTDs, and prompt thorough etiologic investigation and genetic counseling.

  20. Adolescents' emotional competence is associated with parents' neural sensitivity to emotions.

    Science.gov (United States)

    Telzer, Eva H; Qu, Yang; Goldenberg, Diane; Fuligni, Andrew J; Galván, Adriana; Lieberman, Matthew D

    2014-01-01

    An essential component of youths' successful development is learning to appropriately respond to emotions, including the ability to recognize, identify, and describe one's feelings. Such emotional competence is thought to arise through the parent-child relationship. Yet, the mechanisms by which parents transmit emotional competence to their children are difficult to measure because they are often implicit, idiosyncratic, and not easily articulated by parents or children. In the current study, we used a multifaceted approach that went beyond self-report measures and examined whether parental neural sensitivity to emotions predicted their child's emotional competence. Twenty-two adolescent-parent dyads completed an fMRI scan during which they labeled the emotional expressions of negatively valenced faces. Results indicate that parents who recruited the amygdala, VLPFC, and brain regions involved in mentalizing (i.e., inferring others' emotional states) had adolescent children with greater emotional competence. These results held after controlling for parents' self-reports of emotional expressivity and adolescents' self-reports of the warmth and support of their parent relationships. In addition, adolescents recruited neural regions involved in mentalizing during affect labeling, which significantly mediated the associated between parental neural sensitivity and adolescents' emotional competence, suggesting that youth are modeling or referencing their parents' emotional profiles, thereby contributing to better emotional competence.

  1. Neural activation associated with the cognitive emotion regulation of sadness in healthy children

    Directory of Open Access Journals (Sweden)

    Andy C. Belden

    2014-07-01

    Full Text Available When used effectively, cognitive reappraisal of distressing events is a highly adaptive cognitive emotion regulation (CER strategy, with impairments in cognitive reappraisal associated with greater risk for psychopathology. Despite extensive literature examining the neural correlates of cognitive reappraisal in healthy and psychiatrically ill adults, there is a dearth of data to inform the neural bases of CER in children, a key gap in the literature necessary to map the developmental trajectory of cognitive reappraisal. In this fMRI study, psychiatrically healthy schoolchildren were instructed to use cognitive reappraisal to modulate their emotional reactions and responses of negative affect after viewing sad photos. Consistent with the adult literature, when actively engaged in reappraisal compared to passively viewing sad photos, children showed increased activation in the vlPFC, dlPFC, and dmPFC as well as in parietal and temporal lobe regions. When children used cognitive reappraisal to minimize their experience of negative affect after viewing sad stimuli they exhibited dampened amygdala responses. Results are discussed in relation to the importance of identifying and characterizing neural processes underlying adaptive CER strategies in typically developing children in order to understand how these systems go awry and relate to the risk and occurrence of affective disorders.

  2. Adolescents’ emotional competence is associated with parents’ neural sensitivity to emotions

    Directory of Open Access Journals (Sweden)

    Eva H Telzer

    2014-07-01

    Full Text Available An essential component of youths’ successful development is learning to appropriately respond to emotions, including the ability to recognize, identify, and describe one’s feelings. Such emotional competence is thought to arise through the parent-child relationship. Yet, the mechanisms by which parents transmit emotional competence to their children are difficult to measure because they are often implicit, idiosyncratic, and not easily articulated by parents or children. In the current study, we used a multifaceted approach that went beyond self-report measures and examined whether parental neural sensitivity to emotions predicted their child’s emotional competence. Twenty-two adolescent-parent dyads completed an fMRI scan during which they labeled the emotional expressions of negatively valenced faces. Results indicate that parents who recruited the amygdala, VLPFC, and brain regions involved in mentalizing (i.e., inferring others’ emotional states had adolescent children with greater emotional competence. These results held after controlling for parents’ self-reports of emotional expressivity and adolescents’ self-reports of the warmth and support of their parent relationships. In addition, adolescents recruited neural regions involved in mentalizing during affect labeling, which significantly mediated the associated between parental neural sensitivity and adolescents’ emotional competence, suggesting that youth are modeling or referencing their parents’ emotional profiles, thereby contributing to better emotional competence.

  3. Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

    Science.gov (United States)

    Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

    2017-09-01

    We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. Trait approach and avoidance motivation: lateralized neural activity associated with executive function.

    Science.gov (United States)

    Spielberg, Jeffrey M; Miller, Gregory A; Engels, Anna S; Herrington, John D; Sutton, Bradley P; Banich, Marie T; Heller, Wendy

    2011-01-01

    Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals. Copyright © 2010 Elsevier Inc. All rights reserved.

  5. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (IV

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-06-01

    Full Text Available Fetuses with neural tube defects (NTDs may be associated with maternal and fetal risk factors. This article provides a comprehensive review of maternal and fetal risk factors associated with NTDs, such as infertility, periconceptional clomiphene use and assisted reproductive technology, periconceptional folic acid deficiency and effects offolic acid supplementation and fortification on NTD rates, periconceptional vitamin B1 2 deficiency, single nucleotide polymorphisms and polymorphisms in genes of folate metabolism, and maternal autoantibodies to folate receptors. NTDs associated with maternal and fetal risk factors are an important cause of NTDs. Perinatal identification of NTDs should alert the clinician to the maternal and fetal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling. [Taiwan J Obstet Cynecol 2008;47(2:141-1 50

  6. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (II

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-03-01

    Full Text Available Fetuses with neural tube defects (NTDs maybe associated with syndromes, disorders, and maternal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal risk factors associated with NTDs, such as Currarino syndrome, sacral defect with anterior meningocele, Jarcho-Levin syndrome (spondylo-costal dysostosis, lateral meningocele syndrome, neurofibromatosis type I, Marfan syndrome, and hyperthermia. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders, and maternal risk factors may be different from those of non-syndromic multifactorial NTDs. Perinatal identification of NTDs should alert one to the syndromes, disorders, and maternal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling.

  7. Adolescent development of context-dependent stimulus-reward association memory and its neural correlates.

    Science.gov (United States)

    Voss, Joel L; O'Neil, Jonathan T; Kharitonova, Maria; Briggs-Gowan, Margaret J; Wakschlag, Lauren S

    2015-01-01

    Expression of learned stimulus-reward associations based on context is essential for regulation of behavior to meet situational demands. Contextual regulation improves during development, although the developmental progression of relevant neural and cognitive processes is not fully specified. We therefore measured neural correlates of flexible, contextual expression of stimulus-reward associations in pre/early-adolescent children (ages 9-13 years) and young adults (ages 19-22 years). After reinforcement learning using standard parameters, a contextual reversal manipulation was used whereby contextual cues indicated that stimulus-reward associations were the same as previously reinforced for some trials (consistent trials) or were reversed on other trials (inconsistent trials). Subjects were thus required to respond according to original stimulus-reward associations vs. reversed associations based on trial-specific contextual cues. Children and young adults did not differ in reinforcement learning or in relevant functional magnetic resonance imaging (fMRI) correlates. In contrast, adults outperformed children during contextual reversal, with better performance specifically for inconsistent trials. fMRI signals corresponding to this selective advantage included greater activity in lateral prefrontal cortex (LPFC), hippocampus, and dorsal striatum for young adults relative to children. Flexible expression of stimulus-reward associations based on context thus improves via adolescent development, as does recruitment of brain regions involved in reward learning and contextual expression of memory. HighlightsEarly-adolescent children and young adults were equivalent in reinforcement learning.Adults outperformed children in contextual expression of stimulus-reward associations.Adult advantages correlated with increased activity of relevant brain regions.Specific neurocognitive developmental changes support better contextual regulation.

  8. 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.

  9. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

    OpenAIRE

    Wei Feng; Simon X. Yang; Haixia Wu

    2014-01-01

    The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties. The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only. Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported ...

  10. Age associations with neural processing of reward anticipation in adolescents with bipolar disorders

    Science.gov (United States)

    Urošević, Snežana; Luciana, Monica; Jensen, Jonathan B.; Youngstrom, Eric A.; Thomas, Kathleen M.

    2016-01-01

    Reward/behavioral approach system hypersensitivity is implicated in bipolar disorders (BD) and in normative development during adolescence. Pediatric onset of BD is associated with a more severe illness course. However, little is known about neural processing of rewards in adolescents with BD or developmental (i.e., age) associations with activation of these neural systems. The present study aims to address this knowledge gap. The present sample included 21 adolescents with BD and 26 healthy adolescents, ages 13 to 19. Participants completed a functional magnetic resonance imaging (fMRI) protocol using the Monetary Incentive Delay (MID) task. Behavioral performance was similar between groups. Group differences in BOLD activation during target anticipation and feedback anticipation periods of the task were examined using whole-brain analyses, as were group differences in age effects. During both target anticipation and feedback anticipation, adolescents with BD, compared to adolescents without psychopathology, exhibited decreased engagement of frontal regions involved in cognitive control (i.e., dorsolateral prefrontal cortex). Healthy adolescents exhibited age-related decreases, while adolescents with BD exhibited age-related increases, in activity of other cognitive control frontal areas (i.e., right inferior frontal gyrus), suggesting altered development in the BD group. Longitudinal research is needed to examine potentially abnormal development of cognitive control during reward pursuit in adolescent BD and whether early therapeutic interventions can prevent these potential deviations from normative development. PMID:27114896

  11. Age associations with neural processing of reward anticipation in adolescents with bipolar disorders

    Directory of Open Access Journals (Sweden)

    Snežana Urošević

    2016-01-01

    Full Text Available Reward/behavioral approach system hypersensitivity is implicated in bipolar disorders (BD and in normative development during adolescence. Pediatric onset of BD is associated with a more severe illness course. However, little is known about neural processing of rewards in adolescents with BD or developmental (i.e., age associations with activation of these neural systems. The present study aims to address this knowledge gap. The present sample included 21 adolescents with BD and 26 healthy adolescents, ages 13 to 19. Participants completed a functional magnetic resonance imaging (fMRI protocol using the Monetary Incentive Delay (MID task. Behavioral performance was similar between groups. Group differences in BOLD activation during target anticipation and feedback anticipation periods of the task were examined using whole-brain analyses, as were group differences in age effects. During both target anticipation and feedback anticipation, adolescents with BD, compared to adolescents without psychopathology, exhibited decreased engagement of frontal regions involved in cognitive control (i.e., dorsolateral prefrontal cortex. Healthy adolescents exhibited age-related decreases, while adolescents with BD exhibited age-related increases, in activity of other cognitive control frontal areas (i.e., right inferior frontal gyrus, suggesting altered development in the BD group. Longitudinal research is needed to examine potentially abnormal development of cognitive control during reward pursuit in adolescent BD and whether early therapeutic interventions can prevent these potential deviations from normative development.

  12. Temporal and Spatial Patterns of Neural Activity Associated with Information Selection in Open-ended Creativity.

    Science.gov (United States)

    Zhou, Siyuan; Chen, Shi; Wang, Shuang; Zhao, Qingbai; Zhou, Zhijin; Lu, Chunming

    2018-02-10

    Novel information selection is a crucial process in creativity and was found to be associated with frontal-temporal functional connectivity in the right brain in closed-ended creativity. Since it has distinct cognitive processing from closed-ended creativity, the information selection in open-ended creativity might be underlain by different neural activity. To address this issue, a creative generation task of Chinese two-part allegorical sayings was adopted, and the trials were classified into novel and normal solutions according to participants' self-ratings. The results showed that (1) novel solutions induced a higher lower alpha power in the temporal area, which might be associated with the automatic, unconscious mental process of retrieving extensive semantic information, and (2) upper alpha power in both frontal and temporal areas and frontal-temporal alpha coherence were higher in novel solutions than in normal solutions, which might reflect the selective inhibition of semantic information. Furthermore, lower alpha power in the temporal area showed a reduction with time, while the frontal-temporal and temporal-temporal coherence in the upper alpha band appeared to increase from the early to the middle phase. These dynamic changes in neural activity might reflect the transformation from divergent thinking to convergent thinking in the creative progress. The advantage of the right brain in frontal-temporal connectivity was not found in the present work, which might result from the diversity of solutions in open-ended creativity. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  13. Neural correlates of associative face memory in the anterior inferior temporal cortex of monkeys.

    Science.gov (United States)

    Eifuku, Satoshi; Nakata, Ryuzaburo; Sugimori, Michiya; Ono, Taketoshi; Tamura, Ryoi

    2010-11-10

    To investigate the neural basis of the associative aspects of facial identification, we recorded neuronal activity from the ventral, anterior inferior temporal cortex (AITv) of macaque monkeys during the performance of an asymmetrical paired-association (APA) task that required associative pairing between an abstract pattern and five different facial views of a single person. In the APA task, after one element of a pair (either an abstract pattern or a face) was presented as a sample cue, the reward-seeking monkey correctly identified the other element of the pair among various repeatedly presented test stimuli (faces or patterns) that were temporally separated by interstimulus delays. The results revealed that a substantial number of AITv neurons responded both to faces and abstract patterns, and the majority of these neurons responded selectively to a particular associative pair. It was demonstrated that in addition to the view-invariant identity of faces used in the APA task, the population of AITv neurons was also able to represent the associative pairing between faces and abstract patterns, which was acquired by training in the APA task. It also appeared that the effect of associative pairing was not so strong that the abstract pattern could be treated in a manner similar to a series of faces belonging to a unique identity. Together, these findings indicate that the AITv plays a crucial role in both facial identification and semantic associations with facial identities.

  14. Multidimensional analysis of the abnormal neural oscillations associated with lexical processing in schizophrenia.

    Science.gov (United States)

    Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

    2013-04-01

    The neural mechanisms of language abnormalities, the core symptoms in schizophrenia, remain unclear. In this study, a new experimental paradigm, combining magnetoencephalography (MEG) techniques and machine intelligence methodologies, was designed to gain knowledge about the frequency, brain location, and time of occurrence of the neural oscillations that are associated with lexical processing in schizophrenia. The 248-channel MEG recordings were obtained from 12 patients with schizophrenia and 10 healthy controls, during a lexical processing task, where the patients discriminated correct from incorrect lexical stimuli that were visually presented. Event-related desynchronization/synchronization (ERD/ERS) was computed along the frequency, time, and space dimensions combined, that resulted in a large spectral-spatial-temporal ERD/ERS feature set. Machine intelligence techniques were then applied to select a small subset of oscillation patterns that are abnormal in patients with schizophrenia, according to their discriminating power in patient and control classification. Patients with schizophrenia showed abnormal ERD/ERS patterns during both lexical encoding and post-encoding periods. The top-ranked features were located at the occipital and left frontal-temporal areas, and covered a wide frequency range, including δ (1-4 Hz), α (8-12 Hz), β (12-32 Hz), and γ (32-48 Hz) bands. These top features could discriminate the patient group from the control group with 90.91% high accuracy, which demonstrates significant brain oscillation abnormalities in patients with schizophrenia at the specific frequency, time, and brain location indicated by these top features. As neural oscillation abnormality may be due to the mechanisms of the disease, the spectral, spatial, and temporal content of the discriminating features can offer useful information for helping understand the physiological basis of the language disorder in schizophrenia, as well as the pathology of the

  15. An Incremental Time-delay Neural Network for Dynamical Recurrent Associative Memory

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An incremental time-delay neural network based on synapse growth, which is suitable for dynamic control and learning of autonomous robots, is proposed to improve the learning and retrieving performance of dynamical recurrent associative memory architecture. The model allows steady and continuous establishment of associative memory for spatio-temporal regularities and time series in discrete sequence of inputs. The inserted hidden units can be taken as the long-term memories that expand the capacity of network and sometimes may fade away under certain condition. Preliminary experiment has shown that this incremental network may be a promising approach to endow autonomous robots with the ability of adapting to new data without destroying the learned patterns. The system also benefits from its potential chaos character for emergence.

  16. pth moment exponential stability of stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays.

    Science.gov (United States)

    Wang, Fen; Chen, Yuanlong; Liu, Meichun

    2018-02-01

    Stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays play an increasingly important role in the design and implementation of neural network systems. Under the framework of Filippov solutions, the issues of the pth moment exponential stability of stochastic memristor-based BAM neural networks are investigated. By using the stochastic stability theory, Itô's differential formula and Young inequality, the criteria are derived. Meanwhile, with Lyapunov approach and Cauchy-Schwarz inequality, we derive some sufficient conditions for the mean square exponential stability of the above systems. The obtained results improve and extend previous works on memristor-based or usual neural networks dynamical systems. Four numerical examples are provided to illustrate the effectiveness of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (I

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-03-01

    Full Text Available Fetuses with neural tube defects (NTDs maybe associated with syndromes, disorders, and maternal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal risk factors associated with NTDs, such as acrocallosal syndrome, autosomal dominant brachydactyly-clinodactyly syndrome, Manouvrier syndrome, short rib-polydactyly syndrome, Disorganization (Ds-like human malformations, isolated hemihyper-plasia, X-linked NTDs, meroanencephaly, schisis association, diprosopus, fetal valproate syndrome, DiGeorge syndrome/velocardiofacial syndrome, Waardenburg syndrome, folic acid antagonists, diabetes mellitus, and obesity. NTDs associated with syndromes, disorders, and maternal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders, and maternal risk factors may be different from those of non-syndromic multifactorial NTDs. Perinatal identification of NTDs should alert one to the syndromes, disorders, and maternal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling.

  18. Chronic Childhood Peer Rejection is Associated with Heightened Neural Responses to Social Exclusion During Adolescence.

    Science.gov (United States)

    Will, Geert-Jan; van Lier, Pol A C; Crone, Eveline A; Güroğlu, Berna

    2016-01-01

    This functional Magnetic Resonance Imaging (fMRI) study examined subjective and neural responses to social exclusion in adolescents (age 12-15) who either had a stable accepted (n = 27; 14 males) or a chronic rejected (n = 19; 12 males) status among peers from age 6 to 12. Both groups of adolescents reported similar increases in distress after being excluded in a virtual ball-tossing game (Cyberball), but adolescents with a history of chronic peer rejection showed higher activity in brain regions previously linked to the detection of, and the distress caused by, social exclusion. Specifically, compared with stably accepted adolescents, chronically rejected adolescents displayed: 1) higher activity in the dorsal anterior cingulate cortex (dACC) during social exclusion and 2) higher activity in the dACC and anterior prefrontal cortex when they were incidentally excluded in a social interaction in which they were overall included. These findings demonstrate that chronic childhood peer rejection is associated with heightened neural responses to social exclusion during adolescence, which has implications for understanding the processes through which peer rejection may lead to adverse effects on mental health over time.

  19. Co-speech gestures influence neural activity in brain regions associated with processing semantic information.

    Science.gov (United States)

    Dick, Anthony Steven; Goldin-Meadow, Susan; Hasson, Uri; Skipper, Jeremy I; Small, Steven L

    2009-11-01

    Everyday communication is accompanied by visual information from several sources, including co-speech gestures, which provide semantic information listeners use to help disambiguate the speaker's message. Using fMRI, we examined how gestures influence neural activity in brain regions associated with processing semantic information. The BOLD response was recorded while participants listened to stories under three audiovisual conditions and one auditory-only (speech alone) condition. In the first audiovisual condition, the storyteller produced gestures that naturally accompany speech. In the second, the storyteller made semantically unrelated hand movements. In the third, the storyteller kept her hands still. In addition to inferior parietal and posterior superior and middle temporal regions, bilateral posterior superior temporal sulcus and left anterior inferior frontal gyrus responded more strongly to speech when it was further accompanied by gesture, regardless of the semantic relation to speech. However, the right inferior frontal gyrus was sensitive to the semantic import of the hand movements, demonstrating more activity when hand movements were semantically unrelated to the accompanying speech. These findings show that perceiving hand movements during speech modulates the distributed pattern of neural activation involved in both biological motion perception and discourse comprehension, suggesting listeners attempt to find meaning, not only in the words speakers produce, but also in the hand movements that accompany speech.

  20. Estimating the geoeffectiveness of halo CMEs from associated solar and IP parameters using neural networks

    Directory of Open Access Journals (Sweden)

    J. Uwamahoro

    2012-06-01

    Full Text Available Estimating the geoeffectiveness of solar events is of significant importance for space weather modelling and prediction. This paper describes the development of a neural network-based model for estimating the probability occurrence of geomagnetic storms following halo coronal mass ejection (CME and related interplanetary (IP events. This model incorporates both solar and IP variable inputs that characterize geoeffective halo CMEs. Solar inputs include numeric values of the halo CME angular width (AW, the CME speed (Vcme, and the comprehensive flare index (cfi, which represents the flaring activity associated with halo CMEs. IP parameters used as inputs are the numeric peak values of the solar wind speed (Vsw and the southward Z-component of the interplanetary magnetic field (IMF or Bs. IP inputs were considered within a 5-day time window after a halo CME eruption. The neural network (NN model training and testing data sets were constructed based on 1202 halo CMEs (both full and partial halo and their properties observed between 1997 and 2006. The performance of the developed NN model was tested using a validation data set (not part of the training data set covering the years 2000 and 2005. Under the condition of halo CME occurrence, this model could capture 100% of the subsequent intense geomagnetic storms (Dst ≤ −100 nT. For moderate storms (−100 < Dst ≤ −50, the model is successful up to 75%. This model's estimate of the storm occurrence rate from halo CMEs is estimated at a probability of 86%.

  1. Perceived social isolation is associated with altered functional connectivity in neural networks associated with tonic alertness and executive control.

    Science.gov (United States)

    Layden, Elliot A; Cacioppo, John T; Cacioppo, Stephanie; Cappa, Stefano F; Dodich, Alessandra; Falini, Andrea; Canessa, Nicola

    2017-01-15

    Perceived social isolation (PSI), colloquially known as loneliness, is associated with selectively altered attentional, cognitive, and affective processes in humans, but the neural mechanisms underlying these adjustments remain largely unexplored. Behavioral, eye tracking, and neuroimaging research has identified associations between PSI and implicit hypervigilance for social threats. Additionally, selective executive dysfunction has been evidenced by reduced prepotent response inhibition in social Stroop and dichotic listening tasks. Given that PSI is associated with pre-attentional processes, PSI may also be related to altered resting-state functional connectivity (FC) in the brain. Therefore, we conducted the first resting-state fMRI FC study of PSI in healthy young adults. Five-minute resting-state scans were obtained from 55 participants (31 females). Analyses revealed robust associations between PSI and increased brain-wide FC in areas encompassing the right central operculum and right supramarginal gyrus, and these associations were not explained by depressive symptomatology, objective isolation, or demographics. Further analyses revealed that PSI was associated with increased FC between several nodes of the cingulo-opercular network, a network known to underlie the maintenance of tonic alertness. These regions encompassed the bilateral insula/frontoparietal opercula and ACC/pre-SMA. In contrast, FC between the cingulo-opercular network and right middle/superior frontal gyrus was reduced, a finding associated with diminished executive function in prior literature. We suggest that, in PSI, increased within-network cingulo-opercular FC may be associated with hypervigilance to social threat, whereas reduced right middle/superior frontal gyrus FC to the cingulo-opercular network may be associated with diminished impulse control. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Syndromes, Disorders and Maternal Risk Factors Associated with Neural Tube Defects (III

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-06-01

    Full Text Available Fetuses with neural tube defects (NTDs may be associated with syndromes, disorders, and maternal and fetal risk factors. This article provides a comprehensive review of syndromes, disorders, and maternal and fetal risk factors associated with NTDs, such as omphalocele, OEIS (omphalocele-exstrophy-imperforate anus-spinal defects complex, pentalogy of Cantrell, amniotic band sequence, limb-body wall complex, Meckel syndrome, Joubert syndrome, skeletal dysplasia, diabetic embryopathy, and single nucleotide polymorphisms in genes of glucose metabolism. NTDs associated with syndromes, disorders, and maternal and fetal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders and maternal risk factors may be different from those of nonsyndromic multi facto rial NTDs. Perinatal identification of NTDs should alert the clinician to the syndromes, disorders, and maternal and fetal risk factors associated with NTDs, and prompt a thorough etiologic investigation and genetic counseling. [Taiwan J Obstet Cynecol 2008;47(2:131-140

  3. Syndromes, Disorders and Maternal Risk Factors Associated With Neural Tube Defects (VII

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2008-09-01

    Full Text Available Neural tube defects (NTDs may be associated with syndromes, disorders and maternal risk factors. This article provides a comprehensive review of the syndromes, disorders and maternal risk factors associated with NTDs, including DK phocomelia syndrome (von Voss-Cherstvoy syndrome, Siegel-Bartlet syndrome, fetal warfarin syndrome, craniotelencephalic dysplasia, Czeizel-Losonci syndrome, maternal cocaine abuse, Weissenbacher-Zweymüller syndrome, parietal foramina (cranium bifidum, Apert syndrome, craniomicromelic syndrome, XX-agonadism with multiple dysraphic lesions including omphalocele and NTDs, Fryns microphthalmia syndrome, Gershoni-Baruch syndrome, PHAVER syndrome, periconceptional vitamin B6 deficiency, and autosomal dominant Dandy-Walker malformation with occipital cephalocele. NTDs associated with these syndromes, disorders and maternal risk factors are a rare but important cause of NTDs. The recurrence risk and the preventive effect of maternal folic acid intake in NTDs associated with syndromes, disorders and maternal risk factors may be different from those of nonsyndromic multifactorial NTDs. Perinatal diagnosis of NTDs should alert doctors to the syndromes, disorders and maternal risk factors associated with NTDs, and prompt thorough etiologic investigation and genetic counseling.

  4. The association between reconstructed phase space and Artificial Neural Networks for vectorcardiographic recognition of myocardial infarction.

    Science.gov (United States)

    Costa, Cecília M; Silva, Ittalo S; de Sousa, Rafael D; Hortegal, Renato A; Regis, Carlos Danilo M

    Myocardial infarction is one of the leading causes of death worldwide. As it is life threatening, it requires an immediate and precise treatment. Due to this, a growing number of research and innovations in the field of biomedical signal processing is in high demand. This paper proposes the association of Reconstructed Phase Space and Artificial Neural Networks for Vectorcardiography Myocardial Infarction Recognition. The algorithm promotes better results for the box size 10 × 10 and the combination of four parameters: box counting (Vx), box counting (Vz), self-similarity method (Vx) and self-similarity method (Vy) with sensitivity = 92%, specificity = 96% and accuracy = 94%. The topographic diagnosis presented different performances for different types of infarctions with better results for anterior wall infarctions and less accurate results for inferior infarctions. Copyright © 2018 Elsevier Inc. All rights reserved.

  5. Stability in Cohen Grossberg-type bidirectional associative memory neural networks with time-varying delays

    Science.gov (United States)

    Cao, Jinde; Song, Qiankun

    2006-07-01

    In this paper, the exponential stability problem is investigated for a class of Cohen-Grossberg-type bidirectional associative memory neural networks with time-varying delays. By using the analysis method, inequality technique and the properties of an M-matrix, several novel sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are derived. Moreover, the exponential convergence rate is estimated. The obtained results are less restrictive than those given in the earlier literature, and the boundedness and differentiability of the activation functions and differentiability of the time-varying delays are removed. Two examples with their simulations are given to show the effectiveness of the obtained results.

  6. Global exponential stability of bidirectional associative memory neural networks with distributed delays

    Science.gov (United States)

    Song, Qiankun; Cao, Jinde

    2007-05-01

    A bidirectional associative memory neural network model with distributed delays is considered. By constructing a new Lyapunov functional, employing the homeomorphism theory, M-matrix theory and the inequality (a[greater-or-equal, slanted]0,bk[greater-or-equal, slanted]0,qk>0 with , and r>1), a sufficient condition is obtained to ensure the existence, uniqueness and global exponential stability of the equilibrium point for the model. Moreover, the exponential converging velocity index is estimated, which depends on the delay kernel functions and the system parameters. The results generalize and improve the earlier publications, and remove the usual assumption that the activation functions are bounded . Two numerical examples are given to show the effectiveness of the obtained results.

  7. AUTOMATIC SEGMENTATION OF BROADCAST AUDIO SIGNALS USING AUTO ASSOCIATIVE NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    P. Dhanalakshmi

    2010-12-01

    Full Text Available In this paper, we describe automatic segmentation methods for audio broadcast data. Today, digital audio applications are part of our everyday lives. Since there are more and more digital audio databases in place these days, the importance of effective management for audio databases have become prominent. Broadcast audio data is recorded from the Television which comprises of various categories of audio signals. Efficient algorithms for segmenting the audio broadcast data into predefined categories are proposed. Audio features namely Linear prediction coefficients (LPC, Linear prediction cepstral coefficients, and Mel frequency cepstral coefficients (MFCC are extracted to characterize the audio data. Auto Associative Neural Networks are used to segment the audio data into predefined categories using the extracted features. Experimental results indicate that the proposed algorithms can produce satisfactory results.

  8. 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.

  9. CHD8 regulates neurodevelopmental pathways associated with autism spectrum disorder in neural progenitors

    Science.gov (United States)

    Sugathan, Aarathi; Biagioli, Marta; Golzio, Christelle; Erdin, Serkan; Blumenthal, Ian; Manavalan, Poornima; Ragavendran, Ashok; Brand, Harrison; Lucente, Diane; Miles, Judith; Sheridan, Steven D.; Stortchevoi, Alexei; Kellis, Manolis; Haggarty, Stephen J.; Katsanis, Nicholas; Gusella, James F.; Talkowski, Michael E.

    2014-01-01

    Truncating mutations of chromodomain helicase DNA-binding protein 8 (CHD8), and of many other genes with diverse functions, are strong-effect risk factors for autism spectrum disorder (ASD), suggesting multiple mechanisms of pathogenesis. We explored the transcriptional networks that CHD8 regulates in neural progenitor cells (NPCs) by reducing its expression and then integrating transcriptome sequencing (RNA sequencing) with genome-wide CHD8 binding (ChIP sequencing). Suppressing CHD8 to levels comparable with the loss of a single allele caused altered expression of 1,756 genes, 64.9% of which were up-regulated. CHD8 showed widespread binding to chromatin, with 7,324 replicated sites that marked 5,658 genes. Integration of these data suggests that a limited array of direct regulatory effects of CHD8 produced a much larger network of secondary expression changes. Genes indirectly down-regulated (i.e., without CHD8-binding sites) reflect pathways involved in brain development, including synapse formation, neuron differentiation, cell adhesion, and axon guidance, whereas CHD8-bound genes are strongly associated with chromatin modification and transcriptional regulation. Genes associated with ASD were strongly enriched among indirectly down-regulated loci (P neurodevelopmental pathways in which many ASD-associated genes may converge on shared mechanisms of pathogenesis. PMID:25294932

  10. Are concentrations of alkaline earth elements in maternal hair associated with risk of neural tube defects?

    Science.gov (United States)

    Li, Zhenjiang; Wang, Bin; Huo, Wenhua; Liu, Yingying; Zhu, Yibing; Xie, Jing; Li, Zhiwen; Ren, Aiguo

    2017-12-31

    The relationship between maternal intake of alkaline earth elements (AEEs) during the period of neural tube closure and the risk of neural tube defects (NTDs) is still unclear. We propose that AEE deficiency during the early period of pregnancy is associated with an elevated risk of NTDs in the offspring. In this study, we recruited 191 women with NTD-affected pregnancies (cases) and 261 women who delivered healthy infants (controls). The concentrations of four AEEs (Ca, Mg, Sr, Ba) in maternal hair sections that grew during early pregnancy were analyzed. Information on the dietary habits of the mothers was also collected by questionnaire. Higher concentrations of the four AEEs in hair had protective effects against the risk of total NTDs, with odds ratios with 95% confidence interval (comparing groups separated by each median level) of 0.44 (0.28-0.68) for Mg, 0.56 (0.36-0.87) for Ca, 0.45 (0.28-0.70) for Sr, and 0.41 (0.26-0.65) for Ba. Significant negative dose-response trends were identified for the relationships between the four AEE concentrations in maternal hair and the risks of anencephaly and spina bifida, but not for encephalocele. The frequencies of maternal consumption of fresh green vegetables, fresh fruit, and meat or fish were positively correlated with the concentrations of AEEs in hair. We concluded that the maternal intake of AEEs may play an important role in preventing NTD formation in offspring, and that this intake is related to maternal dietary habits of consuming fresh green vegetables, fresh fruit, and fish or meat. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. A regulating element essential for PDGFRA transcription is recognized by neural tube defect-associated PRX homeobox transcription factors

    NARCIS (Netherlands)

    Joosten, Paul H. L. J.; Toepoel, Mascha; van Oosterhout, Dirk; Afink, Gijs B.; van Zoelen, Everardus J. J.

    2002-01-01

    We have previously shown that deregulated expression of the platelet-derived growth factor alpha-receptor (PDGFRA) can be associated with neural tube defects (NTDs) in both men and mice. In the present study, we have investigated the transcription factors that control the up-regulation of PDGFRA

  12. Altered Immune Function Associated with Disordered Neural Connectivity and Executive Dysfunctions: A Neurophysiological Study on Children with Autism Spectrum Disorders

    Science.gov (United States)

    Han, Yvonne M. Y.; Chan, Agnes S.; Sze, Sophia L.; Cheung, Mei-Chun; Wong, Chun-kwok; Lam, Joseph M. K.; Poon, Priscilla M. K.

    2013-01-01

    Previous studies have shown that children with autism spectrum disorders (ASDs) have impaired executive function, disordered neural connectivity, and abnormal immunologic function. The present study examined whether these abnormalities were associated. Seventeen high-functioning (HFA) and 17 low-functioning (LFA) children with ASD, aged 8-17…

  13. Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

    Directory of Open Access Journals (Sweden)

    Wei Feng

    2014-01-01

    Full Text Available The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties. The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only. Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported literature results. Two numerical examples are illustrated to verify our results.

  14. Functional neural changes associated with acquired amusia across different stages of recovery after stroke.

    Science.gov (United States)

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

    2017-09-12

    Brain damage causing acquired amusia disrupts the functional music processing system, creating a unique opportunity to investigate the critical neural architectures of musical processing in the brain. In this longitudinal fMRI study of stroke patients (N = 41) with a 6-month follow-up, we used natural vocal music (sung with lyrics) and instrumental music stimuli to uncover brain activation and functional network connectivity changes associated with acquired amusia and its recovery. In the acute stage, amusic patients exhibited decreased activation in right superior temporal areas compared to non-amusic patients during instrumental music listening. During the follow-up, the activation deficits expanded to comprise a wide-spread bilateral frontal, temporal, and parietal network. The amusics showed less activation deficits to vocal music, suggesting preserved processing of singing in the amusic brain. Compared to non-recovered amusics, recovered amusics showed increased activation to instrumental music in bilateral frontoparietal areas at 3 months and in right middle and inferior frontal areas at 6 months. Amusia recovery was also associated with increased functional connectivity in right and left frontoparietal attention networks to instrumental music. Overall, our findings reveal the dynamic nature of deficient activation and connectivity patterns in acquired amusia and highlight the role of dorsal networks in amusia recovery.

  15. Light evokes melanopsin-dependent vocalization and neural activation associated with aversive experience in neonatal mice.

    Directory of Open Access Journals (Sweden)

    Anton Delwig

    Full Text Available Melanopsin-expressing intrinsically photosensitive retinal ganglion cells (ipRGCs are the only functional photoreceptive cells in the eye of newborn mice. Through postnatal day 9, in the absence of functional rods and cones, these ipRGCs mediate a robust avoidance behavior to a light source, termed negative phototaxis. To determine whether this behavior is associated with an aversive experience in neonatal mice, we characterized light-induced vocalizations and patterns of neuronal activation in regions of the brain involved in the processing of aversive and painful stimuli. Light evoked distinct melanopsin-dependent ultrasonic vocalizations identical to those emitted under stressful conditions, such as isolation from the litter. In contrast, light did not evoke the broad-spectrum calls elicited by acute mechanical pain. Using markers of neuronal activation, we found that light induced the immediate-early gene product Fos in the posterior thalamus, a brain region associated with the enhancement of responses to mechanical stimulation of the dura by light, and thought to be the basis for migrainous photophobia. Additionally, light induced the phosphorylation of extracellular-related kinase (pERK in neurons of the central amygdala, an intracellular signal associated with the processing of the aversive aspects of pain. However, light did not activate Fos expression in the spinal trigeminal nucleus caudalis, the primary receptive field for painful stimulation to the head. We conclude that these light-evoked vocalizations and the distinct pattern of brain activation in neonatal mice are consistent with a melanopsin-dependent neural pathway involved in processing light as an aversive but not acutely painful stimulus.

  16. Drinking water treatment is not associated with an observed increase in neural tube defects in mice

    Science.gov (United States)

    Melin, Vanessa E.; Johnstone, David W.; Etzkorn, Felicia A.

    2018-01-01

    Disinfection by-products (DBPs) arise when natural organic matter in source water reacts with disinfectants used in the water treatment process. Studies have suggested an association between DBPs and birth defects. Neural tube defects (NTDs) in embryos of untreated control mice were first observed in-house in May 2006 and have continued to date. The source of the NTD-inducing agent was previously determined to be a component of drinking water. Tap water samples from a variety of sources were analyzed for trihalomethanes (THMs) to determine if they were causing the malformations. NTDs were observed in CD-1 mice provided with treated and untreated surface water. Occurrence of NTDs varied by water source and treatment regimens. THMs were detected in tap water derived from surface water but not detected in tap water derived from a groundwater source. THMs were absent in untreated river water and laboratory purified waters, yet the percentage of NTDs in untreated river water were similar to the treated water counterpart. These findings indicate that THMs were not the primary cause of NTDs in the mice since the occurrence of NTDs was unrelated to drinking water disinfection. PMID:24497082

  17. Linear stability analysis of retrieval state in associative memory neural networks of spiking neurons

    International Nuclear Information System (INIS)

    Yoshioka, Masahiko

    2002-01-01

    We study associative memory neural networks of the Hodgkin-Huxley type of spiking neurons in which multiple periodic spatiotemporal patterns of spike timing are memorized as limit-cycle-type attractors. In encoding the spatiotemporal patterns, we assume the spike-timing-dependent synaptic plasticity with the asymmetric time window. Analysis for periodic solution of retrieval state reveals that if the area of the negative part of the time window is equivalent to the positive part, then crosstalk among encoded patterns vanishes. Phase transition due to the loss of the stability of periodic solution is observed when we assume fast α function for direct interaction among neurons. In order to evaluate the critical point of this phase transition, we employ Floquet theory in which the stability problem of the infinite number of spiking neurons interacting with α function is reduced to the eigenvalue problem with the finite size of matrix. Numerical integration of the single-body dynamics yields the explicit value of the matrix, which enables us to determine the critical point of the phase transition with a high degree of precision

  18. Associations between parental ideology and neural sensitivity to cognitive conflict in children.

    Science.gov (United States)

    Dennis, Tracy A; Amodio, David M; O'Toole, Laura J

    2015-04-01

    Processes through which parental ideology is transmitted to children-especially at a young age prior to the formation of political beliefs-remain poorly understood. Given recent evidence that political ideology is associated with neural responses to cognitive conflict in adults, we tested the exploratory hypothesis that children's neurocognitive responses to conflict may also differ depending on their parents' ideology. We assessed relations between parental political ideology and children's neurocognitive responses to conflict, as measured by the N2 component of the event-related potential. Children aged 5-7 completed an age-appropriate flanker task while electroencephalography was recorded, and the N2 was scored to incongruent versus congruent flankers to index conflict processing. Because previous research documents heightened liberal-conservative differences in threat-relevant contexts, each trial of the task was preceded by an angry face (threat-relevant) or comparison face (happy or neutral). An effect of parental ideology on the conflict-related N2 emerged in the threat condition, such that the N2 was larger among children of liberals compared with children of moderates and conservatives. These findings suggest that individual differences in neurocognitive responses to conflict, heightened in the context of threat, may reflect a more general pattern of individual differences that, in adults, relates to political ideology.

  19. Boys with conduct problems and callous-unemotional traits: Neural response to reward and punishment and associations with treatment response

    Directory of Open Access Journals (Sweden)

    Amy L. Byrd

    2018-04-01

    Full Text Available Abnormalities in reward and punishment processing are implicated in the development of conduct problems (CP, particularly among youth with callous-unemotional (CU traits. However, no studies have examined whether CP children with high versus low CU traits exhibit differences in the neural response to reward and punishment. A clinic-referred sample of CP boys with high versus low CU traits (ages 8–11; n = 37 and healthy controls (HC; n = 27 completed a fMRI task assessing reward and punishment processing. CP boys also completed a randomized control trial examining the effectiveness of an empirically-supported intervention (i.e., Stop-Now-And-Plan; SNAP. Primary analyses examined pre-treatment differences in neural activation to reward and punishment, and exploratory analyses assessed whether these differences predicted treatment outcome. Results demonstrated associations between CP and reduced amygdala activation to punishment independent of age, race, IQ and co-occurring ADHD and internalizing symptoms. CU traits were not associated with reward or punishment processing after accounting for covariates and no differences were found between CP boys with high versus low CU traits. While boys assigned to SNAP showed a greater reduction in CP, differences in neural activation were not associated with treatment response. Findings suggest that reduced sensitivity to punishment is associated with early-onset CP in boys regardless of the level of CU traits. Keywords: Conduct problems, Callous-unemotional (CU traits, Reward, Punishment, fMRI

  20. Application of artificial neural network to search for gravitational-wave signals associated with short gamma-ray bursts

    International Nuclear Information System (INIS)

    Kim, Kyungmin; Lee, Hyun Kyu; Harry, Ian W; Hodge, Kari A; Kim, Young-Min; Lee, Chang-Hwan; Oh, John J; Oh, Sang Hoon; Son, Edwin J

    2015-01-01

    We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts (GRBs). The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability (FAP) is improved by the artificial neural network in comparison to the conventional detection statistic. Specifically, the distance at 50% detection probability at a fixed false positive rate is increased about 8%–14% for the considered waveform models. We also evaluate a few seconds of the gravitational-wave data segment using the trained networks and obtain the FAP. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short GRBs. (paper)

  1. A Self-Reconstructing Algorithm for Single and Multiple-Sensor Fault Isolation Based on Auto-Associative Neural Networks

    Directory of Open Access Journals (Sweden)

    Hamidreza Mousavi

    2017-01-01

    Full Text Available Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN. In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple fault conditions. The algorithm uses a calibration model based on AANN. AANN can reconstruct the faulty sensor using non-faulty sensors due to correlation between the process variables, and mean of the difference between reconstructed and original data determines which sensors are faulty. The algorithms are tested on a Dimerization process. The simulation results show that the S-AANN can isolate multiple faulty sensors with low computational time that make the algorithm appropriate candidate for online applications.

  2. Association of contextual cues with morphine reward increases neural and synaptic plasticity in the ventral hippocampus of rats.

    Science.gov (United States)

    Alvandi, Mina Sadighi; Bourmpoula, Maria; Homberg, Judith R; Fathollahi, Yaghoub

    2017-11-01

    Drug addiction is associated with aberrant memory and permanent functional changes in neural circuits. It is known that exposure to drugs like morphine is associated with positive emotional states and reward-related memory. However, the underlying mechanisms in terms of neural plasticity in the ventral hippocampus, a region involved in associative memory and emotional behaviors, are not fully understood. Therefore, we measured adult neurogenesis, dendritic spine density and brain-derived neurotrophic factor (BDNF) and TrkB mRNA expression as parameters for synaptic plasticity in the ventral hippocampus. Male Sprague Dawley rats were subjected to the CPP (conditioned place preference) paradigm and received 10 mg/kg morphine. Half of the rats were used to evaluate neurogenesis by immunohistochemical markers Ki67 and doublecortin (DCX). The other half was used for Golgi staining to measure spine density and real-time quantitative reverse transcription-polymerase chain reaction to assess BDNF/TrkB expression levels. We found that morphine-treated rats exhibited more place conditioning as compared with saline-treated rats and animals that were exposed to the CPP without any injections. Locomotor activity did not change significantly. Morphine-induced CPP significantly increased the number of Ki67 and DCX-labeled cells in the ventral dentate gyrus. Additionally, we found increased dendritic spine density in both CA1 and dentate gyrus and an enhancement of BDNF/TrkB mRNA levels in the whole ventral hippocampus. Ki67, DCX and spine density were significantly correlated with CPP scores. In conclusion, we show that morphine-induced reward-related memory is associated with neural and synaptic plasticity changes in the ventral hippocampus. Such neural changes could underlie context-induced drug relapse. © 2017 Society for the Study of Addiction.

  3. Mature teratoma in association with neural tube defect (occipital encephalocele): series of four cases and review of the literature.

    Science.gov (United States)

    Goyal, Nishant; Singh, Pankaj Kumar; Kakkar, Aanchal; Sharma, Meher Chand; Mahapatra, Ashok Kumar

    2012-01-01

    Both occipital encephalocele and teratomas are midline congenital malformations. Encephalocele is a form of neural tube defect in which there is a congenital defect of the cranium through which occurs a protrusion of brain matter or meninges, while teratoma is a tumor derived from all three germ layers. The association between occipital encephalocele and teratoma has not been reported to date. In the present study, the authors present a series of four such cases. Copyright © 2012 S. Karger AG, Basel.

  4. Delay-Dependent Stability Criterion for Bidirectional Associative Memory Neural Networks with Interval Time-Varying Delays

    Science.gov (United States)

    Park, Ju H.; Kwon, O. M.

    In the letter, the global asymptotic stability of bidirectional associative memory (BAM) neural networks with delays is investigated. The delay is assumed to be time-varying and belongs to a given interval. A novel stability criterion for the stability is presented based on the Lyapunov method. The criterion is represented in terms of linear matrix inequality (LMI), which can be solved easily by various optimization algorithms. Two numerical examples are illustrated to show the effectiveness of our new result.

  5. Detection of copy number variants reveals association of cilia genes with neural tube defects.

    Directory of Open Access Journals (Sweden)

    Xiaoli Chen

    Full Text Available BACKGROUND: Neural tube defects (NTDs are one of the most common birth defects caused by a combination of genetic and environmental factors. Currently, little is known about the genetic basis of NTDs although up to 70% of human NTDs were reported to be attributed to genetic factors. Here we performed genome-wide copy number variants (CNVs detection in a cohort of Chinese NTD patients in order to exam the potential role of CNVs in the pathogenesis of NTDs. METHODS: The genomic DNA from eighty-five NTD cases and seventy-five matched normal controls were subjected for whole genome CNVs analysis. Non-DGV (the Database of Genomic Variants CNVs from each group were further analyzed for their associations with NTDs. Gene content in non-DGV CNVs as well as participating pathways were examined. RESULTS: Fifty-five and twenty-six non-DGV CNVs were detected in cases and controls respectively. Among them, forty and nineteen CNVs involve genes (genic CNV. Significantly more non-DGV CNVs and non-DGV genic CNVs were detected in NTD patients than in control (41.2% vs. 25.3%, p<0.05 and 37.6% vs. 20%, p<0.05. Non-DGV genic CNVs are associated with a 2.65-fold increased risk for NTDs (95% CI: 1.24-5.87. Interestingly, there are 41 cilia genes involved in non-DGV CNVs from NTD patients which is significantly enriched in cases compared with that in controls (24.7% vs. 9.3%, p<0.05, corresponding with a 3.19-fold increased risk for NTDs (95% CI: 1.27-8.01. Pathway analyses further suggested that two ciliogenesis pathways, tight junction and protein kinase A signaling, are top canonical pathways implicated in NTD-specific CNVs, and these two novel pathways interact with known NTD pathways. CONCLUSIONS: Evidence from the genome-wide CNV study suggests that genic CNVs, particularly ciliogenic CNVs are associated with NTDs and two ciliogenesis pathways, tight junction and protein kinase A signaling, are potential pathways involved in NTD pathogenesis.

  6. 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

  7. Changes in cholinergic parameters associated with failure of conotruncal septation in embryonic chick hearts after neural crest ablation

    International Nuclear Information System (INIS)

    Kirby, M.L.; Aronstam, R.S.; Buccafusco, J.J.

    1985-01-01

    Cells from the neural crest over occipital somites migrate to the heart, where they give rise to parasympathetic postganglionic neurons as well as ectomesenchymal elements which contribute to conotruncal septation. With a microcautery needle, the neural crest over occipital somites was ablated bilaterally in chicken embryos at an early stage of development. Histological examination on incubation day 15 revealed conotruncal malformations, involving malformation or absence of the conotruncal septum in all embryos. Two peaks of embryo mortality were observed. One peak (incubation days 6-8) occurred at the same time as conotruncal septal closure; the second peak (incubation days 11-13) was concurrent with the onset of functional parasympathetic innervation. A disruption of parasympathetic innervation was indicated by: (1) a decrease in acetylcholinesterase staining, (2) a decrease (27%) in the number of ganglion cells in the conotruncus, (3) decreases in the acetylcholine content of atrium (31%) and ventricle (39%), and (4) a decrease (21%) in muscarinic acetylcholine receptor density on incubation day 15. Radiolabeled ligand-binding studies revealed no change in the affinity of cardiac muscarinic receptors for [ 3 H]methylscopolamine (K/sub D/ . 0.17-0.21 nM). Agonist-binding affinity and sensitivity to guanine nucleotides were similarly unaffected. The reasons for the limited extent of the parasympathetic lesion are unclear, but may involve recruitment of precursor cells from other regions of the neural crest, partial regeneration of the neural crest following surgical removal, or an alteration in the contribution of incoming sympathetic or preganglionic parasympathetic elements. No such plasticity was associated with neural crest contributions to the structural development of the conotruncus. Malformations were observed in all lesioned embryos

  8. Lymphotropic Virions Affect Chemokine Receptor-Mediated Neural Signaling and Apoptosis: Implications for Human Immunodeficiency Virus Type 1-Associated Dementia

    Science.gov (United States)

    Zheng, Jialin; Ghorpade, Anuja; Niemann, Douglas; Cotter, Robin L.; Thylin, Michael R.; Epstein, Leon; Swartz, Jennifer M.; Shepard, Robin B.; Liu, Xiaojuan; Nukuna, Adeline; Gendelman, Howard E.

    1999-01-01

    Chemokine receptors pivotal for human immunodeficiency virus type 1 (HIV-1) infection in lymphocytes and macrophages (CCR3, CCR5, and CXCR4) are expressed on neural cells (microglia, astrocytes, and/or neurons). It is these cells which are damaged during progressive HIV-1 infection of the central nervous system. We theorize that viral coreceptors could effect neural cell damage during HIV-1-associated dementia (HAD) without simultaneously affecting viral replication. To these ends, we studied the ability of diverse viral strains to affect intracellular signaling and apoptosis of neurons, astrocytes, and monocyte-derived macrophages. Inhibition of cyclic AMP, activation of inositol 1,4,5-trisphosphate, and apoptosis were induced by diverse HIV-1 strains, principally in neurons. Virions from T-cell-tropic (T-tropic) strains (MN, IIIB, and Lai) produced the most significant alterations in signaling of neurons and astrocytes. The HIV-1 envelope glycoprotein, gp120, induced markedly less neural damage than purified virions. Macrophage-tropic (M-tropic) strains (ADA, JR-FL, Bal, MS-CSF, and DJV) produced the least neural damage, while 89.6, a dual-tropic HIV-1 strain, elicited intermediate neural cell damage. All T-tropic strain-mediated neuronal impairments were blocked by the CXCR4 antibody, 12G5. In contrast, the M-tropic strains were only partially blocked by 12G5. CXCR4-mediated neuronal apoptosis was confirmed in pure populations of rat cerebellar granule neurons and was blocked by HA1004, an inhibitor of calcium/calmodulin-dependent protein kinase II, protein kinase A, and protein kinase C. Taken together, these results suggest that progeny HIV-1 virions can influence neuronal signal transduction and apoptosis. This process occurs, in part, through CXCR4 and is independent of CD4 binding. T-tropic viruses that traffic in and out of the brain during progressive HIV-1 disease may play an important role in HAD neuropathogenesis. PMID:10482576

  9. Validation of artificial neural network models for predicting biochemical markers associated with male infertility.

    Science.gov (United States)

    Vickram, A S; Kamini, A Rao; Das, Raja; Pathy, M Ramesh; Parameswari, R; Archana, K; Sridharan, T B

    2016-08-01

    Seminal fluid is the secretion from many glands comprised of several organic and inorganic compounds including free amino acids, proteins, fructose, glucosidase, zinc, and other scavenging elements like Mg(2+), Ca(2+), K(+), and Na(+). Therefore, in the view of development of novel approaches and proper diagnosis to male infertility, overall understanding of the biochemical and molecular composition and its role in regulation of sperm quality is highly desirable. Perhaps this can be achieved through artificial intelligence. This study was aimed to elucidate and predict various biochemical markers present in human seminal plasma with three different neural network models. A total of 177 semen samples were collected for this research (both fertile and infertile samples) and immediately processed to prepare a semen analysis report, based on the protocol of the World Health Organization (WHO [2010]). The semen samples were then categorized into oligoasthenospermia (n=35), asthenospermia (n=35), azoospermia (n=22), normospermia (n=34), oligospermia (n=34), and control (n=17). The major biochemical parameters like total protein content, fructose, glucosidase, and zinc content were elucidated by standard protocols. All the biochemical markers were predicted by using three different artificial neural network (ANN) models with semen parameters as inputs. Of the three models, the back propagation neural network model (BPNN) yielded the best results with mean absolute error 0.025, -0.080, 0.166, and -0.057 for protein, fructose, glucosidase, and zinc, respectively. This suggests that BPNN can be used to predict biochemical parameters for the proper diagnosis of male infertility in assisted reproductive technology (ART) centres. AAS: absorption spectroscopy; AI: artificial intelligence; ANN: artificial neural networks; ART: assisted reproductive technology; BPNN: back propagation neural network model; DT: decision tress; MLP: multilayer perceptron; PESA: percutaneous

  10. Delay-dependent exponential stability analysis of bi-directional associative memory neural networks with time delay: an LMI approach

    International Nuclear Information System (INIS)

    Li Chuandong; Liao Xiaofeng; Zhang Rong

    2005-01-01

    For bi-directional associative memory (BAM) neural networks (NNs) with different constant or time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated in this paper. An approach combining the Lyapunov-Krasovskii functional with the linear matrix inequality (LMI) is taken to study the problems, which provide bounds on the interconnection matrix and the activation functions, so as to guarantee the system's exponential stability. Some criteria for the exponential stability, which give information on the delay-dependent property, are derived. The results obtained in this paper provide one more set of easily verified guidelines for determining the exponential stability of delayed BAM (DBAM) neural networks, which are less conservative and less restrictive than the ones reported so far in the literature. Some typical examples are presented to show the application of the criteria obtained in this paper

  11. Chronic childhood peer rejection is associated with heightened neural responses to social exclusion during adolescence.

    NARCIS (Netherlands)

    Will, G.J.; Van, Lier P.A.; Crone, E.A.; Guroglu, B.

    2016-01-01

    This functional Magnetic Resonance Imaging (fMRI) study examined subjective and neural responses to social exclusion in adolescents (age 12-15) who either had a stable accepted (n = 27; 14 males) or a chronic rejected (n = 19; 12 males) status among peers from age 6 to 12. Both groups of adolescents

  12. Neural Dynamics Associated with Semantic and Episodic Memory for Faces: Evidence from Multiple Frequency Bands

    Science.gov (United States)

    Zion-Golumbic, Elana; Kutas, Marta; Bentin, Shlomo

    2010-01-01

    Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident…

  13. Diminished behavioral and neural sensitivity to sound modulation is associated with moderate developmental hearing loss.

    Directory of Open Access Journals (Sweden)

    Merri J Rosen

    Full Text Available The acoustic rearing environment can alter central auditory coding properties, yet altered neural coding is seldom linked with specific deficits to adult perceptual skills. To test whether developmental hearing loss resulted in comparable changes to perception and sensory coding, we examined behavioral and neural detection thresholds for sinusoidally amplitude modulated (sAM stimuli. Behavioral sAM detection thresholds for slow (5 Hz modulations were significantly worse for animals reared with bilateral conductive hearing loss (CHL, as compared to controls. This difference could not be attributed to hearing thresholds, proficiency at the task, or proxies for attention. Detection thresholds across the groups did not differ for fast (100 Hz modulations, a result paralleling that seen in humans. Neural responses to sAM stimuli were recorded in single auditory cortex neurons from separate groups of awake animals. Neurometric analyses indicated equivalent thresholds for the most sensitive neurons, but a significantly poorer detection threshold for slow modulations across the population of CHL neurons as compared to controls. The magnitude of the neural deficit matched that of the behavioral differences, suggesting that a reduction of sensory information can account for limitations to perceptual skills.

  14. Neural reuse leads to associative connections between concrete (physical) and abstract (social) concepts and motives.

    Science.gov (United States)

    Wang, Yimeng; Bargh, John A

    2016-01-01

    Consistent with neural reuse theory, empirical tests of the related "scaffolding" principle of abstract concept development show that higher-level concepts "reuse" and are built upon fundamental motives such as survival, safety, and consumption. This produces mutual influence between the two levels, with far-ranging impacts from consumer behavior to political attitudes.

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

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Eun Jin; Cho, Sang Soo; Kim, Hee Jung; Bang, Seong Ae; Park, Hyun Soo; Kim, Yu Kyeong; Kim, Sang Eun [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of)

    2007-07-01

    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<0.05 uncorrected). For path analysis, seven brain regions (bilateral middle frontal gyri and putamen, left fusiform gyrus, anterior cingulate and right parahippocampal gyri) were selected based on the results of the correlation analysis. Model construction and path analysis processing were done by AMOS 5.0. The elderly had significantly lower total hit rates than the young (P<0.005). In the correlation analysis, both groups showed similar metabolic correlation in frontal and striatal area. But correlation in the medial temporal lobe (MTL) was found differently by group. In path analysis, the functional networks for the constructed model was accepted (X(2) =0.80, P=0.67) and it proved to be significantly different between groups (X{sub 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.

  16. Neural changes associated to procedural learning and automatization process in Developmental Coordination Disorder and/or Developmental Dyslexia.

    Science.gov (United States)

    Biotteau, Maëlle; Péran, Patrice; Vayssière, Nathalie; Tallet, Jessica; Albaret, Jean-Michel; Chaix, Yves

    2017-03-01

    Recent theories hypothesize that procedural learning may support the frequent overlap between neurodevelopmental disorders. The neural circuitry supporting procedural learning includes, among others, cortico-cerebellar and cortico-striatal loops. Alteration of these loops may account for the frequent comorbidity between Developmental Coordination Disorder (DCD) and Developmental Dyslexia (DD). The aim of our study was to investigate cerebral changes due to the learning and automatization of a sequence learning task in children with DD, or DCD, or both disorders. fMRI on 48 children (aged 8-12) with DD, DCD or DD + DCD was used to explore their brain activity during procedural tasks, performed either after two weeks of training or in the early stage of learning. Firstly, our results indicate that all children were able to perform the task with the same level of automaticity, but recruit different brain processes to achieve the same performance. Secondly, our fMRI results do not appear to confirm Nicolson and Fawcett's model. The neural correlates recruited for procedural learning by the DD and the comorbid groups are very close, while the DCD group presents distinct characteristics. This provide a promising direction on the neural mechanisms associated with procedural learning in neurodevelopmental disorders and for understanding comorbidity. Published by Elsevier Ltd.

  17. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    information [2]. Each one of these cells acts as a simple processor. When individual cells interact with one another, the complex abilities of the brain are made possible. In neural networks, the input or data are processed by a propagation function that adds up the values of all the incoming data. The ending value is then compared with a threshold or specific value. The resulting value must exceed the activation function value in order to become output. The activation function is a mathematical function that a neuron uses to produce an output referring to its input value. [8] Figure 1 depicts this process. Neural networks usually have three components an input, a hidden, and an output. These layers create the end result of the neural network. A real world example is a child associating the word dog with a picture. The child says dog and simultaneously looks a picture of a dog. The input is the spoken word ''dog'', the hidden is the brain processing, and the output will be the category of the word dog based on the picture. This illustration describes how a neural network functions

  18. Callous-unemotional traits modulate the neural response associated with punishing another individual during social exchange: a preliminary investigation.

    Science.gov (United States)

    White, Stuart F; Brislin, Sarah J; Meffert, Harma; Sinclair, Stephen; Blair, R James R

    2013-02-01

    The current study examined whether Callous-Unemotional (CU) traits, a core component of psychopathy, modulate neural responses of participants engaged in a social exchange game. In this task, participants were offered an allocation of money and then given the chance to punish the offerer. Twenty youth participated and responses to both offers and the participant's punishment (or not) of these offers were examined. Increasingly unfair offers were associated with increased dorsal anterior cingulate cortex (dACC) activity but this responsiveness was not modulated by CU traits. Increasing punishment of unfair offers was associated with increased dACC and anterior insula activity and this activity was modulated by CU traits. Higher CU trait participants showed a weaker association between activity and punishment level. These data suggest that CU traits are associated with appropriate expectations of other individual's normative behavior but weaker representations of such information when guiding behavior of the self.

  19. A case of junctional neural tube defect associated with a lipoma of the filum terminale: a new subtype of junctional neural tube defect?

    Science.gov (United States)

    Florea, Simona Mihaela; Faure, Alice; Brunel, Hervé; Girard, Nadine; Scavarda, Didier

    2018-06-01

    The embryological development of the central nervous system takes place during the neurulation process, which includes primary and secondary neurulation. A new form of dysraphism, named junctional neural tube defect (JNTD), was recently reported, with only 4 cases described in the literature. The authors report a fifth case of JNTD. This 5-year-old boy, who had been operated on during his 1st month of life for a uretero-rectal fistula, was referred for evaluation of possible spinal dysraphism. He had urinary incontinence, clubfeet, and a history of delayed walking ability. MRI showed a spinal cord divided in two, with an upper segment ending at the T-11 level and a lower segment at the L5-S1 level, with a thickened filum terminale. The JNTDs represent a recently classified dysraphism caused by an error during junctional neurulation. The authors suggest that their patient should be included in this category as the fifth case reported in the literature and note that this would be the first reported case of JNTD in association with a lipomatous filum terminale.

  20. Differentiation defect in neural crest-derived smooth muscle cells in patients with aortopathy associated with bicuspid aortic valves

    Directory of Open Access Journals (Sweden)

    Jiao Jiao

    2016-08-01

    Full Text Available Individuals with bicuspid aortic valves (BAV are at a higher risk of developing thoracic aortic aneurysms (TAA than patients with trileaflet aortic valves (TAV. The aneurysms associated with BAV most commonly involve the ascending aorta and spare the descending aorta. Smooth muscle cells (SMCs in the ascending and descending aorta arise from neural crest (NC and paraxial mesoderm (PM, respectively. We hypothesized defective differentiation of the neural crest stem cells (NCSCs-derived SMCs but not paraxial mesoderm cells (PMCs-derived SMCs contributes to the aortopathy associated with BAV. When induced pluripotent stem cells (iPSCs from BAV/TAA patients were differentiated into NCSC-derived SMCs, these cells demonstrated significantly decreased expression of marker of SMC differentiation (MYH11 and impaired contraction compared to normal control. In contrast, the PMC-derived SMCs were similar to control cells in these aspects. The NCSC-SMCs from the BAV/TAA also showed decreased TGF-β signaling based on phosphorylation of SMAD2, and increased mTOR signaling. Inhibition of mTOR pathway using rapamycin rescued the aberrant differentiation. Our data demonstrates that decreased differentiation and contraction of patient's NCSC-derived SMCs may contribute to that aortopathy associated with BAV.

  1. Cocaine self-administration abolishes associative neural encoding in the nucleus accumbens necessary for higher-order learning.

    Science.gov (United States)

    Saddoris, Michael P; Carelli, Regina M

    2014-01-15

    Cocaine use is often associated with diminished cognitive function, persisting even after abstinence from the drug. Likely targets for these changes are the core and shell of the nucleus accumbens (NAc), which are critical for mediating the rewarding aspects of drugs of abuse as well as supporting associative learning. To understand this deficit, we recorded neural activity in the NAc of rats with a history of cocaine self-administration or control subjects while they learned Pavlovian first- and second-order associations. Rats were trained for 2 weeks to self-administer intravenous cocaine or water. Later, rats learned a first-order Pavlovian discrimination where a conditioned stimulus (CS)+ predicted food, and a control (CS-) did not. Rats then learned a second-order association where, absent any food reinforcement, a novel cued (SOC+) predicted the CS+ and another (SOC-) predicted the CS-. Electrophysiological recordings were taken during performance of these tasks in the NAc core and shell. Both control subjects and cocaine-experienced rats learned the first-order association, but only control subjects learned the second-order association. Neural recordings indicated that core and shell neurons encoded task-relevant information that correlated with behavioral performance, whereas this type of encoding was abolished in cocaine-experienced rats. The NAc core and shell perform complementary roles in supporting normal associative learning, functions that are impaired after cocaine experience. This impoverished encoding of motivational behavior, even after abstinence from the drug, might provide a key mechanism to understand why addiction remains a chronically relapsing disorder despite repeated attempts at sobriety. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  2. Neural and sympathetic activity associated with exploration in decision-making: Further evidence for involvement of insula

    Directory of Open Access Journals (Sweden)

    Hideki eOhira

    2014-11-01

    Full Text Available We previously reported that sympathetic activity was associated with exploration in decision-making indexed by entropy, which is a concept in information theory and indexes randomness of choices or the degree of deviation from sticking to recent experiences of gains and losses, and that activation of the anterior insula mediated this association. The current study aims to replicate and to expand these findings in a situation where contingency between options and outcomes is manipulated. Sixteen participants performed a stochastic decision-making task in which we manipulated a condition with low uncertainty of gain/loss (contingent-reward condition and a condition with high uncertainty of gain/loss (random-reward condition. Regional cerebral blood flow was measured by 15O-water positron emission tomography (PET, and cardiovascular parameters and catecholamine in the peripheral blood were measured, during the task. In the contingent-reward condition, norepinephrine as an index of sympathetic activity was positively correlated with entropy indicating exploration in decision-making. Norepinephrine was negatively correlated with neural activity in the right posterior insula, rostral anterior cingulate cortex, and dorsal pons, suggesting neural bases for detecting changes of bodily states. Furthermore, right anterior insular activity was negatively correlated with entropy, suggesting influences on exploration in decision-making. By contrast, in the random-reward condition, entropy correlated with activity in the dorsolateral prefrontal and parietal cortices but not with sympathetic activity. These findings suggest that influences of sympathetic activity on exploration in decision-making and its underlying neural mechanisms might be dependent on the degree of uncertainty of situations.

  3. Endogenous testosterone levels are associated with neural activity in men with schizophrenia during facial emotion processing.

    Science.gov (United States)

    Ji, Ellen; Weickert, Cynthia Shannon; Lenroot, Rhoshel; Catts, Stanley V; Vercammen, Ans; White, Christopher; Gur, Raquel E; Weickert, Thomas W

    2015-06-01

    Growing evidence suggests that testosterone may play a role in the pathophysiology of schizophrenia given that testosterone has been linked to cognition and negative symptoms in schizophrenia. Here, we determine the extent to which serum testosterone levels are related to neural activity in affective processing circuitry in men with schizophrenia. Functional magnetic resonance imaging was used to measure blood-oxygen-level-dependent signal changes as 32 healthy controls and 26 people with schizophrenia performed a facial emotion identification task. Whole brain analyses were performed to determine regions of differential activity between groups during processing of angry versus non-threatening faces. A follow-up ROI analysis using a regression model in a subset of 16 healthy men and 16 men with schizophrenia was used to determine the extent to which serum testosterone levels were related to neural activity. Healthy controls displayed significantly greater activation than people with schizophrenia in the left inferior frontal gyrus (IFG). There was no significant difference in circulating testosterone levels between healthy men and men with schizophrenia. Regression analyses between activation in the IFG and circulating testosterone levels revealed a significant positive correlation in men with schizophrenia (r=.63, p=.01) and no significant relationship in healthy men. This study provides the first evidence that circulating serum testosterone levels are related to IFG activation during emotion face processing in men with schizophrenia but not in healthy men, which suggests that testosterone levels modulate neural processes relevant to facial emotion processing that may interfere with social functioning in men with schizophrenia. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

  4. Syndromes and Disorders Associated with Omphalocele (III: Single Gene Disorders, Neural Tube Defects, Diaphragmatic Defects and Others

    Directory of Open Access Journals (Sweden)

    Chih-Ping Chen

    2007-06-01

    Full Text Available Omphalocele can be associated with single gene disorders, neural tube defects, diaphragmatic defects, fetal valproate syndrome, and syndromes of unknown etiology. This article provides a comprehensive review of omphalocele-related disorders: otopalatodigital syndrome type II; Melnick–Needles syndrome; Rieger syndrome; neural tube defects; Meckel syndrome; Shprintzen–Goldberg omphalocele syndrome; lethal omphalocele-cleft palate syndrome; cerebro-costo-mandibular syndrome; fetal valproate syndrome; Marshall–Smith syndrome; fibrochondrogenesis; hydrolethalus syndrome; Fryns syndrome; omphalocele, diaphragmatic defects, radial anomalies and various internal malformations; diaphragmatic defects, limb deficiencies and ossification defects of skull; Donnai–Barrow syndrome; CHARGE syndrome; Goltz syndrome; Carpenter syndrome; Toriello–Carey syndrome; familial omphalocele; Cornelia de Lange syndrome; C syndrome; Elejalde syndrome; Malpuech syndrome; cervical ribs, Sprengel anomaly, anal atresia and urethral obstruction; hydrocephalus with associated malformations; Kennerknecht syndrome; lymphedema, atrial septal defect and facial changes; and craniosynostosis- mental retardation syndrome of Lin and Gettig. Perinatal identification of omphalocele should alert one to the possibility of omphalocele-related disorders and familial inheritance and prompt a thorough genetic counseling for these disorders.

  5. Inca: a novel p21-activated kinase-associated protein required for cranial neural crest development.

    Science.gov (United States)

    Luo, Ting; Xu, Yanhua; Hoffman, Trevor L; Zhang, Tailin; Schilling, Thomas; Sargent, Thomas D

    2007-04-01

    Inca (induced in neural crest by AP2) is a novel protein discovered in a microarray screen for genes that are upregulated in Xenopus embryos by the transcriptional activator protein Tfap2a. It has no significant similarity to any known protein, but is conserved among vertebrates. In Xenopus, zebrafish and mouse embryos, Inca is expressed predominantly in the premigratory and migrating neural crest (NC). Knockdown experiments in frog and fish using antisense morpholinos reveal essential functions for Inca in a subset of NC cells that form craniofacial cartilage. Cells lacking Inca migrate successfully but fail to condense into skeletal primordia. Overexpression of Inca disrupts cortical actin and prevents formation of actin "purse strings", which are required for wound healing in Xenopus embryos. We show that Inca physically interacts with p21-activated kinase 5 (PAK5), a known regulator of the actin cytoskeleton that is co-expressed with Inca in embryonic ectoderm, including in the NC. These results suggest that Inca and PAK5 cooperate in restructuring cytoskeletal organization and in the regulation of cell adhesion in the early embryo and in NC cells during craniofacial development.

  6. Fetal Alcohol Spectrum Disorder (FASD) Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets.

    Science.gov (United States)

    Muralidharan, Pooja; Sarmah, Swapnalee; Zhou, Feng C; Marrs, James A

    2013-06-19

    Fetal alcohol spectrum disorder (FASD), caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection.

  7. Fetal Alcohol Spectrum Disorder (FASD Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets

    Directory of Open Access Journals (Sweden)

    James A. Marrs

    2013-06-01

    Full Text Available Fetal alcohol spectrum disorder (FASD, caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection.

  8. Dynamic neural network reorganization associated with second language vocabulary acquisition: a multimodal imaging study.

    Science.gov (United States)

    Hosoda, Chihiro; Tanaka, Kanji; Nariai, Tadashi; Honda, Manabu; Hanakawa, Takashi

    2013-08-21

    It remains unsettled whether human language relies exclusively on innately privileged brain structure in the left hemisphere or is more flexibly shaped through experiences, which induce neuroplastic changes in potentially relevant neural circuits. Here we show that learning of second language (L2) vocabulary and its cessation can induce bidirectional changes in the mirror-reverse of the traditional language areas. A cross-sectional study identified that gray matter volume in the inferior frontal gyrus pars opercularis (IFGop) and connectivity of the IFGop with the caudate nucleus and the superior temporal gyrus/supramarginal (STG/SMG), predominantly in the right hemisphere, were positively correlated with L2 vocabulary competence. We then implemented a cohort study involving 16 weeks of L2 training in university students. Brain structure before training did not predict the later gain in L2 ability. However, training intervention did increase IFGop volume and reorganization of white matter including the IFGop-caudate and IFGop-STG/SMG pathways in the right hemisphere. These "positive" plastic changes were correlated with the gain in L2 ability in the trained group but were not observed in the control group. We propose that the right hemispheric network can be reorganized into language-related areas through use-dependent plasticity in young adults, reflecting a repertoire of flexible reorganization of the neural substrates responding to linguistic experiences.

  9. Risk factors, organ weight deviation and associated anomalies in neural tube defects: A prospective fetal and perinatal autopsy series

    Directory of Open Access Journals (Sweden)

    Asaranti Kar

    2015-01-01

    Full Text Available Introduction: Neural tube defects (NTD are a group of serious birth defects occurring due to defective closure of neural tube during embryonic development. It comprises of anencephaly, encephalocele and spina bifida. We conducted this prospective fetal autopsy series to study the rate and distribution of NTD, analyze the reproductive factors and risk factors, note any associated anomalies and evaluate the organ weights and their deviation from normal. Materials and Methods: This was a prospective study done over a period of 6 years from August, 2007 to July, 2013. All cases of NTDs delivered as abortion, still born and live born were included. The reproductive and risk factors like age, parity, multiple births, previous miscarriage, obesity, diabetes mellitus, socioeconomic status and use of folic acid during pregnancy were collected.Autopsy was performed according to Virchow′s technique. Detail external and internal examination were carried out to detect any associated anomalies. Gross and microscopic examination of organs were done. Results: Out of 210 cases of fetal and perinatal autopsy done, 72 (34.28% had NTD constituting 49 cases of anencephaly, 16 spina bifida and 7 cases of encephalocele. The mothers in these cases predominantly were within 25-29 years (P = 0.02 and primy (P = 0.01. Female sex was more commonly affected than males (M:F = 25:47, P = 0.0005 There was no history of folate use in majority of cases. Organ weight deviations were >2 standard deviation low in most of the cases. Most common associated anomalies were adrenal hypoplasia and thymic hyperplasia. Conclusion: The authors have made an attempt to study NTD cases in respect to maternal reproductive and risk factors and their association with NTD along with the organ weight deviation and associated anomalies. This so far in our knowledge is an innovative study which was not found in literature even after extensive search.

  10. Use of neural network based auto-associative memory as a data compressor for pre-processing optical emission spectra in gas thermometry with the help of neural network

    International Nuclear Information System (INIS)

    Dolenko, S.A.; Filippov, A.V.; Pal, A.F.; Persiantsev, I.G.; Serov, A.O.

    2003-01-01

    Determination of temperature from optical emission spectra is an inverse problem that is often very difficult to solve, especially when substantial noise is present. One of the means that can be used to solve such a problem is a neural network trained on the results of modeling of spectra at different temperatures (Dolenko, et al., in: I.C. Parmee (Ed.), Adaptive Computing in Design and Manufacture, Springer, London, 1998, p. 345). Reducing the dimensionality of the input data prior to application of neural network can increase the accuracy and stability of temperature determination. In this study, such pre-processing is performed with another neural network working as an auto-associative memory with a narrow bottleneck in the hidden layer. The improvement in the accuracy and stability of temperature determination in presence of noise is demonstrated on model spectra similar to those recorded in a DC-discharge CVD reactor

  11. Understanding the neural control of ingestive behaviors: helping to separate cause from effect with dehydration-associated anorexia.

    Science.gov (United States)

    Watts, A G

    2000-06-01

    Eating and drinking are motivated behaviors that are made up of coordinated sets of neuroendocrine, autonomic, and behavioral motor events. Although the spinal cord, hindbrain, and hypothalamus contain the motor neurons and circuitry sufficient to maintain the reflex parts of these motor events, inputs from the telencephalon are required to furnish the behavioral components with a motivated (goal-directed) character. Each of these motor events derives from the complex interaction of a variety of sensory inputs with groups of neural networks whose components are distributed throughout the brain and collectively support motor expression and coordination. At a first approximation based on a variety of data, these networks can be divided into three groups: networks that stimulate, those that inhibit, and those that disinhibit motor functions. A fourth contributor is the circadian timing signal that originates in the hypothalamic suprachiasmatic nucleus and provides the temporal anchor for the expression of all behaviors. This article discusses the nature of these networks using neuroanatomical (tract-tracing and neuropeptide in situ hybridization), endocrine, and behavioral evidence from a variety of experimental models. A persistent problem when studying the control of food intake from a neural systems perspective has been the difficulty in separating those neuronal changes that result in hunger from those that are as a consequence of eating. To address this problem, dehydration-associated anorexia is presented as a particularly useful experimental model because it can be used to distinguish between neural mechanisms underlying anorexia and those changes that occur as a consequence of anorexia. The article concludes by highlighting the potential role of neuropeptidergic action in the operation of these networks, using forebrain neuropeptidergic innervation of the parabrachial nucleus as an example. Copyright 2000 Academic Press.

  12. Neural changes associated with semantic processing in healthy aging despite intact behavioral performance.

    Science.gov (United States)

    Lacombe, Jacinthe; Jolicoeur, Pierre; Grimault, Stephan; Pineault, Jessica; Joubert, Sven

    2015-10-01

    Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. 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.

  14. Associating a product with a luxury brand label modulates neural reward processing and favors choices in materialistic individuals.

    Science.gov (United States)

    Audrin, Catherine; Ceravolo, Leonardo; Chanal, Julien; Brosch, Tobias; Sander, David

    2017-11-23

    The present study investigated the extent to which luxury vs. non-luxury brand labels (i.e., extrinsic cues) randomly assigned to items and preferences for these items impact choice, and how this impact may be moderated by materialistic tendencies (i.e., individual characteristics). The main objective was to investigate the neural correlates of abovementioned effects using functional magnetic resonance imaging. Behavioural results showed that the more materialistic people are, the more they choose and like items labelled with luxury brands. Neuroimaging results revealed the implication of a neural network including the dorsolateral and ventromedial prefrontal cortex and the orbitofrontal cortex that was modulated by the brand label and also by the participants' preference. Most importantly, items with randomly assigned luxurious brand labels were preferentially chosen by participants and triggered enhanced signal in the caudate nucleus. This effect increased linearly with materialistic tendencies. Our results highlight the impact of brand-item association, although random in our study, and materialism on preference, relying on subparts of the brain valuation system for the integration of extrinsic cues, preferences and individual characteristics.

  15. Damage detection in carbon composite material typical of wind turbine blades using auto-associative neural networks

    Science.gov (United States)

    Dervilis, N.; Barthorpe, R. J.; Antoniadou, I.; Staszewski, W. J.; Worden, K.

    2012-04-01

    The structure of a wind turbine blade plays a vital role in the mechanical and structural operation of the turbine. As new generations of offshore wind turbines are trying to achieve a leading role in the energy market, key challenges such as a reliable Structural Health Monitoring (SHM) of the blades is significant for the economic and structural efficiency of the wind energy. Fault diagnosis of wind turbine blades is a "grand challenge" due to their composite nature, weight and length. The damage detection procedure involves additional difficulties focused on aerodynamic loads, environmental conditions and gravitational loads. It will be shown that vibration dynamic response data combined with AANNs is a robust and powerful tool, offering on-line and real time damage prediction. In this study the features used for SHM are Frequency Response Functions (FRFs) acquired via experimental methods based on an LMS system by which identification of mode shapes and natural frequencies is accomplished. The methods used are statistical outlier analysis which allows a diagnosis of deviation from normality and an Auto-Associative Neural Network (AANN). Both of these techniques are trained by adopting the FRF data for normal and damage condition. The AANN is a method which has not yet been widely used in the condition monitoring of composite materials of blades. This paper is trying to introduce a new scheme for damage detection, localisation and severity assessment by adopting simple measurements such as FRFs and exploiting multilayer neural networks and outlier novelty detection.

  16. An fMRI comparison of neural activity associated with recognition of familiar melodies in younger and older adults.

    Science.gov (United States)

    Sikka, Ritu; Cuddy, Lola L; Johnsrude, Ingrid S; Vanstone, Ashley D

    2015-01-01

    Several studies of semantic memory in non-musical domains involving recognition of items from long-term memory have shown an age-related shift from the medial temporal lobe structures to the frontal lobe. However, the effects of aging on musical semantic memory remain unexamined. We compared activation associated with recognition of familiar melodies in younger and older adults. Recognition follows successful retrieval from the musical lexicon that comprises a lifetime of learned musical phrases. We used the sparse-sampling technique in fMRI to determine the neural correlates of melody recognition by comparing activation when listening to familiar vs. unfamiliar melodies, and to identify age differences. Recognition-related cortical activation was detected in the right superior temporal, bilateral inferior and superior frontal, left middle orbitofrontal, bilateral precentral, and left supramarginal gyri. Region-of-interest analysis showed greater activation for younger adults in the left superior temporal gyrus and for older adults in the left superior frontal, left angular, and bilateral superior parietal regions. Our study provides powerful evidence for these musical memory networks due to a large sample (N = 40) that includes older adults. This study is the first to investigate the neural basis of melody recognition in older adults and to compare the findings to younger adults.

  17. An fMRI comparison of neural activity associated with recognition of familiar melodies in younger and older adults

    Directory of Open Access Journals (Sweden)

    Ritu eSikka

    2015-10-01

    Full Text Available Several studies of semantic memory in non-musical domains involving recognition of items from long-term memory have shown an age-related shift from the medial temporal lobe structures to the frontal lobe. However, the effects of aging on musical semantic memory remain unexamined. We compared activation associated with recognition of familiar melodies in younger and older adults. Recognition follows successful retrieval from the musical lexicon that comprises a lifetime of learned musical phrases. We used the sparse-sampling technique in fMRI to determine the neural correlates of melody recognition by comparing activation when listening to familiar versus unfamiliar melodies, and to identify age differences. Recognition-related cortical activation was detected in the right superior temporal, bilateral inferior and superior frontal, left middle orbitofrontal, bilateral precentral, and left supramarginal gyri. Region-of-interest analysis showed greater activation for younger adults in the left superior temporal gyrus and for older adults in the left superior frontal, left angular, and bilateral superior parietal regions. Our study provides powerful evidence for these musical memory networks due to a large sample (N = 40 that includes older adults. This study is the first to investigate the neural basis of melody recognition in older adults and to compare the findings to younger adults.

  18. Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

    Science.gov (United States)

    Mathar, David; Neumann, Jane; Villringer, Arno; Horstmann, Annette

    2017-10-01

    Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Exponential lag function projective synchronization of memristor-based multidirectional associative memory neural networks via hybrid control

    Science.gov (United States)

    Yuan, Manman; Wang, Weiping; Luo, Xiong; Li, Lixiang; Kurths, Jürgen; Wang, Xiao

    2018-03-01

    This paper is concerned with the exponential lag function projective synchronization of memristive multidirectional associative memory neural networks (MMAMNNs). First, we propose a new model of MMAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying discrete delays and distributed time delays. Second, we design two kinds of hybrid controllers. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the controllers are carefully designed to confirm the process of different types of synchronization in the MMAMNNs. Third, sufficient criteria guaranteeing the synchronization of system are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.

  20. The spatial decision-supporting system combination of RBR & CBR based on artificial neural network and association rules

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

    The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.

  1. Underlying neural alpha frequency patterns associated with intra-hemispheric inhibition during an interhemispheric transfer task.

    Science.gov (United States)

    Simon-Dack, Stephanie L; Kraus, Brian; Walter, Zachary; Smith, Shelby; Cadle, Chelsea

    2018-05-18

    Interhemispheric transfer measured via differences in right- or left-handed motoric responses to lateralized visual stimuli, known as the crossed-uncrossed difference (CUD), is one way of identifying patterns of processing that are vital for understanding the transfer of neural signals. Examination of interhemispheric transfer by means of the CUD is not entirely explained by simple measures of response time. Multiple processes contribute to wide variability observed in CUD reaction times. Prior research has suggested that intra-hemispheric inhibitory processes may be involved in regulation of speed of transfer. Our study examined electroencephalography recordings and time-locked alpha frequency activity while 18 participants responded to lateralized targets during performance of the Poffenberger Paradigm. Our results suggest that there are alpha frequency differences at fronto-central lateral electrodes based on target, hand-of-response, and receiving hemisphere. These findings suggest that early motoric inhibitory mechanisms may help explain the wide range of variability typically seen with the CUD. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. 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.

  3. Associative memory for online learning in noisy environments using self-organizing incremental neural network.

    Science.gov (United States)

    Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

    2009-06-01

    Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

  4. Arbitrary associations in animals: what can paired associate recall in rats tell us about the neural basis of episodic memory? Theoretical comment on Kesner, Hunsaker, & Warthen (2008).

    Science.gov (United States)

    Langston, Rosamund F; Wood, Emma R

    2008-12-01

    Detailed memories for unique episodes from an individual's past can be triggered, often effortlessly, when that individual is exposed to a stimulus that was present during the original event. The aim of Kesner et al. is to understand the neural basis of memory encoding that supports this cued recall of episodic memories. Kesner and colleagues make novel use of an object-place paired-associate task for rats to provide evidence for a critical role of dorsal CA3 in certain aspects of episodic memory encoding. Using one-trial cued recall versions of the task they show that when rats are cued with an object stimulus, they can be trained to revisit the location in which the object appeared previously. Conversely, when rats are cued with a location, they can learn to choose the object with which it was associated. Rats with dorsal CA3 lesions are severely impaired at these tasks. These data are consistent with the theory that the autoassociative network in CA3 supports the rapid formation of novel associations and may allow pattern completion--the phenomenom whereby a subset of the cues present at an encoding event triggers recall of the whole event. Although flexible recall of arbitrary associations is not fully demonstrated, the study contributes 2 novel behavioral tasks to the previously limited repertoire for studying paired associate recall in rats. It also builds on previous data to specify the role of the hippocampal CA3 subregion in cued recall--a critical aspect of episodic memory.

  5. 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

  6. Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development

    Science.gov (United States)

    Thomas, Michael S. C.; Forrester, Neil A.; Ronald, Angelica

    2016-01-01

    In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such…

  7. Neural network modelling and dynamical system theory: are they relevant to study the governing dynamics of association football players?

    Science.gov (United States)

    Dutt-Mazumder, Aviroop; Button, Chris; Robins, Anthony; Bartlett, Roger

    2011-12-01

    Recent studies have explored the organization of player movements in team sports using a range of statistical tools. However, the factors that best explain the performance of association football teams remain elusive. Arguably, this is due to the high-dimensional behavioural outputs that illustrate the complex, evolving configurations typical of team games. According to dynamical system analysts, movement patterns in team sports exhibit nonlinear self-organizing features. Nonlinear processing tools (i.e. Artificial Neural Networks; ANNs) are becoming increasingly popular to investigate the coordination of participants in sports competitions. ANNs are well suited to describing high-dimensional data sets with nonlinear attributes, however, limited information concerning the processes required to apply ANNs exists. This review investigates the relative value of various ANN learning approaches used in sports performance analysis of team sports focusing on potential applications for association football. Sixty-two research sources were summarized and reviewed from electronic literature search engines such as SPORTDiscus, Google Scholar, IEEE Xplore, Scirus, ScienceDirect and Elsevier. Typical ANN learning algorithms can be adapted to perform pattern recognition and pattern classification. Particularly, dimensionality reduction by a Kohonen feature map (KFM) can compress chaotic high-dimensional datasets into low-dimensional relevant information. Such information would be useful for developing effective training drills that should enhance self-organizing coordination among players. We conclude that ANN-based qualitative analysis is a promising approach to understand the dynamical attributes of association football players.

  8. Neural correlates of verbal creativity: Differences in resting-state functional connectivity associated with expertise in creative writing

    Directory of Open Access Journals (Sweden)

    Martin eLotze

    2014-07-01

    Full Text Available Neural characteristics of verbal creativity as assessed by word generation tasks have been recently identified, but differences in resting-state functional connectivity (rFC between experts and non-experts in creative writing have not been reported yet. Previous electroencephalography (EEG coherence measures during rest demonstrated a decreased cooperation between brain areas in association with creative thinking ability. Here, we used resting-state functional magnetic resonance imaging to compare 20 experts in creative writing and 23 age-matched non-experts with respect to rFC strengths within a brain network previously found to be associated with creative writing. Decreased rFC for experts was found between areas 44 of both hemispheres. Increased rFC for experts was observed between right hemispheric caudate and intraparietal sulcus. Correlation analysis of verbal creativity indices with rFC values in the expert group revealed predominantly negative associations, particularly of rFC between left area 44 and left temporal pole. Overall, our data support previous findings on reduced connectivity between interhemispheric areas and increased right-hemispheric connectivity during rest in highly verbally creative individuals.

  9. The COMT Val/Met polymorphism is associated with reading related skills and consistent patterns of functional neural activation

    Science.gov (United States)

    Landi, Nicole; Frost, Stephen J.; Mencl, W. Einar; Preston, Jonathan L.; Jacobsen, Leslie K.; Lee, Maria; Yrigollen, Carolyn; Pugh, Kenneth R.; Grigorenko, Elena L.

    2013-01-01

    In both children and adults there is large variability in reading skill, with approximately 5–10% of individuals characterized as having reading disability; these individuals struggle to learn to read despite adequate intelligence and opportunity. Although it is well established that a substantial portion of this variability is attributed to the genetic differences between individuals, specifics of the connections between reading and the genome are not understood. This article presents data that suggest that variation in the COMT gene, which has previously been associated with variation in higher-order cognition, is associated with reading and reading-related skills, both at the level of brain and behavior. In particular, we found that the COMT Val/Met polymorphism at rs4680, which results in the substitution of the ancestral Valine (Val) by Methionine (Met), was associated with better performance on a number of critical reading measures and with patterns of functional neural activation that have been linked to better readers. We argue that this polymorphism, known for its broad effects on cognition, may modulate (likely through frontal lobe function) reading skill. PMID:23278923

  10. The COMT Val/Met polymorphism is associated with reading-related skills and consistent patterns of functional neural activation.

    Science.gov (United States)

    Landi, Nicole; Frost, Stephen J; Mencl, W Einar; Preston, Jonathan L; Jacobsen, Leslie K; Lee, Maria; Yrigollen, Carolyn; Pugh, Kenneth R; Grigorenko, Elena L

    2013-01-01

    In both children and adults there is large variability in reading skill, with approximately 5-10% of individuals characterized as having reading disability; these individuals struggle to learn to read despite adequate intelligence and opportunity. Although it is well established that a substantial portion of this variability is attributed to the genetic differences between individuals, specifics of the connections between reading and the genome are not understood. This article presents data that suggest that variation in the COMT gene, which has previously been associated with variation in higher-order cognition, is associated with reading and reading-related skills, at the level of both brain and behavior. In particular, we found that the COMT Val/Met polymorphism at rs4680, which results in the substitution of the ancestral Valine (Val) by Methionine (Met), was associated with better performance on a number of critical reading measures and with patterns of functional neural activation that have been linked to better readers. We argue that this polymorphism, known for its broad effects on cognition, may modulate (likely through frontal lobe function) reading skill. © 2012 Blackwell Publishing Ltd.

  11. Working Memory Load and Negative Picture Processing: Neural and Behavioral Associations With Panic, Social Anxiety, and Positive Affect.

    Science.gov (United States)

    MacNamara, Annmarie; Jackson, T Bryan; Fitzgerald, Jacklynn M; Hajcak, Greg; Phan, K Luan

    2018-04-22

    Internalizing disorders such as anxiety may be characterized by an imbalance between bottom-up (stimulus-driven) and top-down (goal-directed) attention. The late positive potential (LPP) can be used to assess these processes when task-irrelevant negative and neutral pictures are presented within a working memory paradigm. Prior work using this paradigm has found that working memory load reduces the picture-elicited LPP across participants; however, anxious individuals showed a reduced effect of working memory load on the LPP, suggesting increased distractibility. The current study assessed transdiagnostic associations between specific symptom dimensions of anxiety, the LPP, and behavior in a clinically representative, heterogeneous group of 76 treatment-seeking patients with internalizing disorders, who performed a working memory task interspersed with negative and neutral pictures. As expected, negative pictures enhanced the LPP, and working memory load reduced the LPP. Participants with higher social anxiety showed increased LPPs to negative stimuli during early and late portions of picture presentation. Panic symptoms were associated with reduced LPPs to negative pictures compared with neutral pictures as well as a reduced effect of working memory load on the LPP during the late time window. Reduced positive affect was associated with greater behavioral interference from negative pictures. Hypervigilance for negative stimuli was uniquely explained by social anxiety symptoms, whereas panic symptoms were associated with the opposing effect-blunted processing/avoidance of these stimuli. Panic symptoms were uniquely associated with reduced top-down control. Results reveal distinct associations between neural reactivity and anxiety symptom dimensions that transcend traditional diagnostic boundaries. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  12. Dance type and flight parameters are associated with different mushroom body neural activities in worker honeybee brains.

    Directory of Open Access Journals (Sweden)

    Taketoshi Kiya

    Full Text Available BACKGROUND: Honeybee foragers can transmit the information concerning the location of food sources to their nestmates using dance communication. We previously used a novel immediate early gene, termed kakusei, to demonstrate that the neural activity of a specific mushroom body (MB neuron subtype is preferentially enhanced in the forager brain. The sensory information related to this MB neuron activity, however, remained unclear. METHODOLOGY/PRINCIPAL FINDINGS: Here, we used kakusei to analyze the relationship between MB neuron activity and types of foraging behavior. The number of kakusei-positive MB neurons was higher in the round dancers that had flown a short distance than in the waggle dancers that had flown a long distance. Furthermore, the amount of kakusei transcript in the MBs inversely related to the waggle-phase duration of the waggle dance, which correlates with the flight distance. Using a narrow tunnel whose inside was vertically or axially lined, we manipulated the pattern of visual input, which is received by the foragers during flight, and analysed kakusei expression. The amount of kakusei transcript in the MBs was related to the foraging frequency but not to the tunnel pattern. In contrast, the number of kakusei-positive MB neurons was affected by the tunnel patterns, but not related to foraging frequency. CONCLUSIONS/SIGNIFICANCE: These results suggest that the MB neuron activity depends on the foraging frequency, whereas the number of active MB neurons is related to the pattern of visual input received during foraging flight. Our results suggest that the foraging frequency and visual experience during foraging are associated with different MB neural activities.

  13. Training spiking neural networks to associate spatio-temporal input-output spike patterns

    OpenAIRE

    Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

    2013-01-01

    In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

  14. Mittag-Leffler synchronization of delayed fractional-order bidirectional associative memory neural networks with discontinuous activations: state feedback control and impulsive control schemes.

    Science.gov (United States)

    Ding, Xiaoshuai; Cao, Jinde; Zhao, Xuan; Alsaadi, Fuad E

    2017-08-01

    This paper is concerned with the drive-response synchronization for a class of fractional-order bidirectional associative memory neural networks with time delays, as well as in the presence of discontinuous activation functions. The global existence of solution under the framework of Filippov for such networks is firstly obtained based on the fixed-point theorem for condensing map. Then the state feedback and impulsive controllers are, respectively, designed to ensure the Mittag-Leffler synchronization of these neural networks and two new synchronization criteria are obtained, which are expressed in terms of a fractional comparison principle and Razumikhin techniques. Numerical simulations are presented to validate the proposed methodologies.

  15. Neural Correlates of Biased Responses: The Negative Method Effect in the Rosenberg Self-Esteem Scale Is Associated with Right Amygdala Volume.

    Science.gov (United States)

    Wang, Yinan; Kong, Feng; Huang, Lijie; Liu, Jia

    2016-10-01

    Self-esteem is a widely studied construct in psychology that is typically measured by the Rosenberg Self-Esteem Scale (RSES). However, a series of cross-sectional and longitudinal studies have suggested that a simple and widely used unidimensional factor model does not provide an adequate explanation of RSES responses due to method effects. To identify the neural correlates of the method effect, we sought to determine whether and how method effects were associated with the RSES and investigate the neural basis of these effects. Two hundred and eighty Chinese college students (130 males; mean age = 22.64 years) completed the RSES and underwent magnetic resonance imaging (MRI). Behaviorally, method effects were linked to both positively and negatively worded items in the RSES. Neurally, the right amygdala volume negatively correlated with the negative method factor, while the hippocampal volume positively correlated with the general self-esteem factor in the RSES. The neural dissociation between the general self-esteem factor and negative method factor suggests that there are different neural mechanisms underlying them. The amygdala is involved in modulating negative affectivity; therefore, the current study sheds light on the nature of method effects that are related to self-report with a mix of positively and negatively worded items. © 2015 Wiley Periodicals, Inc.

  16. Why Social Pain Can Live on: Different Neural Mechanisms Are Associated with Reliving Social and Physical Pain.

    Science.gov (United States)

    Meyer, Meghan L; Williams, Kipling D; Eisenberger, Naomi I

    2015-01-01

    Although social and physical pain recruit overlapping neural activity in regions associated with the affective component of pain, the two pains can diverge in their phenomenology. Most notably, feelings of social pain can be re-experienced or "relived," even when the painful episode has long passed, whereas feelings of physical pain cannot be easily relived once the painful episode subsides. Here, we observed that reliving social (vs. physical) pain led to greater self-reported re-experienced pain and greater activity in affective pain regions (dorsal anterior cingulate cortex and anterior insula). Moreover, the degree of relived pain correlated positively with affective pain system activity. In contrast, reliving physical (vs. social) pain led to greater activity in the sensory-discriminative pain system (primary and secondary somatosensory cortex and posterior insula), which did not correlate with relived pain. Preferential engagement of these different pain mechanisms may reflect the use of different top-down neurocognitive pathways to elicit the pain. Social pain reliving recruited dorsomedial prefrontal cortex, often associated with mental state processing, which functionally correlated with affective pain system responses. In contrast, physical pain reliving recruited inferior frontal gyrus, known to be involved in body state processing, which functionally correlated with activation in the sensory pain system. These results update the physical-social pain overlap hypothesis: while overlapping mechanisms support live social and physical pain, distinct mechanisms guide internally-generated pain.

  17. Transcription-associated processes cause DNA double-strand breaks and translocations in neural stem/progenitor cells.

    Science.gov (United States)

    Schwer, Bjoern; Wei, Pei-Chi; Chang, Amelia N; Kao, Jennifer; Du, Zhou; Meyers, Robin M; Alt, Frederick W

    2016-02-23

    High-throughput, genome-wide translocation sequencing (HTGTS) studies of activated B cells have revealed that DNA double-strand breaks (DSBs) capable of translocating to defined bait DSBs are enriched around the transcription start sites (TSSs) of active genes. We used the HTGTS approach to investigate whether a similar phenomenon occurs in primary neural stem/progenitor cells (NSPCs). We report that breakpoint junctions indeed are enriched around TSSs that were determined to be active by global run-on sequencing analyses of NSPCs. Comparative analyses of transcription profiles in NSPCs and B cells revealed that the great majority of TSS-proximal junctions occurred in genes commonly expressed in both cell types, possibly because this common set has higher transcription levels on average than genes transcribed in only one or the other cell type. In the latter context, among all actively transcribed genes containing translocation junctions in NSPCs, those with junctions located within 2 kb of the TSS show a significantly higher transcription rate on average than genes with junctions in the gene body located at distances greater than 2 kb from the TSS. Finally, analysis of repair junction signatures of TSS-associated translocations in wild-type versus classical nonhomologous end-joining (C-NHEJ)-deficient NSPCs reveals that both C-NHEJ and alternative end-joining pathways can generate translocations by joining TSS-proximal DSBs to DSBs on other chromosomes. Our studies show that the generation of transcription-associated DSBs is conserved across divergent cell types.

  18. Neural correlates of relational memory: successful encoding and retrieval of semantic and perceptual associations

    NARCIS (Netherlands)

    Prince, S.E.; Daselaar, S.M.; Cabeza, R.

    2005-01-01

    Using event-related functional magnetic resonance imaging, we identified brain regions involved in successful relational memory (RM) during encoding and retrieval for semantic and perceptual associations or in general, independent of phase and content. Participants were scanned while encoding and

  19. Defeitos de fechamento do tubo neural e fatores associados em recém-nascidos vivos e natimortos Neural tube defects and associated factors among liveborn and stillborn infants

    Directory of Open Access Journals (Sweden)

    Marcos J.B. Aguiar

    2003-04-01

    evaluate the prevalence and factors associated to neural tube defects in liveborn and stillborn infants delivered at the Hospital das Clínicas, UFMG, from January 8, 1999 to July 31, 2000. METHODS: this is a descriptive study, based on a database, according to the Latin-American Collaborative Study of Congenital Malformation (ECLAMC rules. Reports on liveborn and stillborn infants with congenital anomalies were prepared including information about morphological description, necropsy results, complementary exams, family, social and pregnancy histories and other clinical data. Each malformed liveborn infant originated a control of the same sex, without malformations. The liveborn and stillborn infants with neural tube defects delivered during that period were classified according to their defect and the presence or absence of associated defects. The liveborn and stillborn infants with neural tube defects were compared to newborns without neural tube defects according to their weight and sex and their mother's age and parity. Epi-Info 6.0 Program was used for the statistical analysis of the results. RESULTS: the prevalence of neural tube defects was 4.73 to 1,000 deliveries (89:18,807; it was significantly higher among stillborn infants (23.7:1,000 than among liveborn infants (4.16:1,000, p < 0.001. Neural tube defects were more often found among low weight liveborn infants (< 2,500 g, p < 0.001 and less frequently among women who had had more than three gestations, p = 0.007. No association was found regarding newborn's sex or maternal age. There was no association with newborn's sex and weight, maternal parity or age among stillborn infants. The most common neural tube defects were myelomeningocele (47.2%, anencephaly (26.9% and encephalocele (16.9%. The defects were found as isolated anomalies in 71.1% of the liveborn and 38.5% of the stillborn infants; they were part of a syndrome in 9.2% (liveborn and 7.7% (stillborn. CONCLUSIONS: the neural tube defect prevalence found

  20. Association of main folate metabolic pathway gene polymorphisms with neural tube defects in Han population of Northern China.

    Science.gov (United States)

    Fang, Yulian; Zhang, Ruiping; Zhi, Xiufang; Zhao, Linsheng; Cao, Lirong; Wang, Yizheng; Cai, Chunquan

    2018-04-01

    Neural tube defects (NTDs) are one of the most prevalent and the most severe congenital malformations worldwide. Studies have confirmed that folic acid supplementation could effectively reduce NTDs risk, but the genetic mechanism remains unclear. In this study, we explored association of single nucleotide polymorphisms (SNP) within folate metabolic pathway genes with NTDs in Han population of Northern China. We performed a case-control study to compare genotype and allele distributions of SNPs in 152 patients with NTDs and 169 controls. A total of 16 SNPs within five genes were genotyped by the Sequenom MassARRAY assay. Our results indicated that three SNPs associated significantly with NTDs (P<0.05). For rs2236225 within MTHFD1, children with allele A or genotype AA had a high NTDs risk (OR=1.500, 95%CI=1.061~2.120; OR=2.862, 95%CI=1.022~8.015, respectively). For rs1801133 within MTHFR, NTDs risk markedly increased in patients with allele T or genotype TT (OR=1.552, 95%CI=1.130~2.131; OR=2.344, 95%CI=1.233~4.457, respectively). For rs1801394 within MTRR, children carrying allele G and genotype GG had a higher NTDs risk (OR=1.533, 95%CI=1.102~2.188; OR=2.355, 95%CI=1.044~5.312, respectively). Our results suggest that rs2236225 of MTHFD1 gene, rs1801133 of MTHFR gene and rs1801394 of MTRR gene were associated with NTDs in Han population of Northern China.

  1. Associations Between Neural Reward Processing and Binge Eating Among Adolescent Girls.

    Science.gov (United States)

    Bodell, Lindsay P; Wildes, Jennifer E; Goldschmidt, Andrea B; Lepage, Rachel; Keenan, Kate E; Guyer, Amanda E; Hipwell, Alison E; Stepp, Stephanie D; Forbes, Erika E

    2018-01-01

    Neuroimaging studies suggest that altered brain responses to food-related cues in reward-sensitive regions characterize individuals who experience binge-eating episodes. However, the absence of longitudinal data limits the understanding of whether reward-system alterations increase vulnerability to binge eating, as theorized in models of the development of this behavior. Adolescent girls (N = 122) completed a functional magnetic resonance imaging monetary reward task at age 16 years as part of an ongoing longitudinal study. Self-report of binge eating was assessed using the Eating Attitudes Test at ages 16 and 18 years. Regression analyses examined concurrent and longitudinal associations between the blood-oxygenation-level-dependent response to anticipating and winning monetary rewards and the severity of binge eating while controlling for age 16 depressive symptoms and socioeconomic status. Greater ventromedial prefrontal cortex and caudate responses to winning money were correlated with greater severity of binge eating concurrently but not prospectively. This study is the first to examine longitudinal associations between reward responding and binge eating in community-based, mostly low-socioeconomic status adolescent girls. Ventromedial prefrontal cortex response to reward outcome-possibly reflecting an enhanced subjective reward value-appears to be a state marker of binge-eating severity rather than a predictor of future severity. Copyright © 2017 The Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  2. Disostose espôndilo-costal associada a defeitos de fechamento do tubo neural Spondylocostal dysostosis associated with neural tube defects

    Directory of Open Access Journals (Sweden)

    Rafael Fabiano M. Rosa

    2009-09-01

    Full Text Available OBJETIVO: Salientar a relação dos defeitos de fechamento do tubo neural com a disostose espôndilo-costal (DEC por meio da descrição de três pacientes. DESCRIÇÃO DOS CASOS: Paciente 1: menina branca, 22 meses, nascida com mielomeningocele lombar. Na avaliação, apresentava hipotonia, baixa estatura, dolicocefalia, fendas palpebrais oblíquas para cima, pregas epicânticas e tronco curto com tórax assimétrico. A avaliação radiográfica revelou hemivértebras múltiplas, vértebras em borboleta e fusão e ausência de algumas costelas. Paciente 2: menina branca, 22 meses, com moderado atraso do desenvolvimento neuropsicomotor, baixa estatura, olhos profundos, pregas epicânticas, pescoço e tronco curtos com assimetria do tórax, abdome protruso, hemangioma plano na altura da transição lombossacra e fosseta sacral profunda no dorso. A avaliação radiográfica identificou hemivértebras, fusão incompleta de vértebras e vértebras em borboleta, malformações de costelas e espinha bífida oculta em L5/S1. Paciente 3: menina branca, 9 dias de vida, com fendas palpebrais oblíquas para cima, ponte nasal alargada, orelhas baixo implantadas e rotadas posteriormente, tronco curto, tórax assimétrico e meningocele tóraco-lombar. A avaliação radiográfica evidenciou hemivértebras, malformação e ausência de algumas costelas e agenesia diafragmática à esquerda. A tomografia computadorizada de encéfalo mostrou estenose de aqueduto. COMENTÁRIOS: Vários defeitos de fechamento do tubo neural, de espinha bífida oculta a grandes mielomeningoceles, são observados em pacientes com DEC, indicando que tais pacientes devem ser cuidadosamente avaliados quanto à possível presença desses defeitos.OBJECTIVE: To highlight the relationship between neural tube defects and spondylocostal dysostosis (SCD through the description of three patients. CASES DESCRIPTION: Patient 1: white girl, 22 months old, born with a lumbar meningomyelocele. At

  3. Spike frequency adaptation is a possible mechanism for control of attractor preference in auto-associative neural networks

    Science.gov (United States)

    Roach, James; Sander, Leonard; Zochowski, Michal

    Auto-associative memory is the ability to retrieve a pattern from a small fraction of the pattern and is an important function of neural networks. Within this context, memories that are stored within the synaptic strengths of networks act as dynamical attractors for network firing patterns. In networks with many encoded memories, some attractors will be stronger than others. This presents the problem of how networks switch between attractors depending on the situation. We suggest that regulation of neuronal spike-frequency adaptation (SFA) provides a universal mechanism for network-wide attractor selectivity. Here we demonstrate in a Hopfield type attractor network that neurons minimal SFA will reliably activate in the pattern corresponding to a local attractor and that a moderate increase in SFA leads to the network to converge to the strongest attractor state. Furthermore, we show that on long time scales SFA allows for temporal sequences of activation to emerge. Finally, using a model of cholinergic modulation within the cortex we argue that dynamic regulation of attractor preference by SFA could be critical for the role of acetylcholine in attention or for arousal states in general. This work was supported by: NSF Graduate Research Fellowship Program under Grant No. DGE 1256260 (JPR), NSF CMMI 1029388 (MRZ) and NSF PoLS 1058034 (MRZ & LMS).

  4. Associations between proprioceptive neural pathway structural connectivity and balance in people with multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Brett W Fling

    2014-10-01

    Full Text Available Mobility and balance impairments are a hallmark of multiple sclerosis (MS, affecting nearly half of patients at presentation and resulting in decreased activity and participation, falls, injuries, and reduced quality of life. A growing body of work suggests that balance impairments in people with mild MS are primarily the result of deficits in proprioception, the ability to determine body position in space in the absence of vision. A better understanding of the pathophysiology of balance disturbances in MS is needed to develop evidence-based rehabilitation approaches. The purpose of the current study was to 1 map the cortical proprioceptive pathway in-vivo using diffusion weighted imaging and 2 assess associations between proprioceptive pathway white matter microstructural integrity and performance on clinical and behavioral balance tasks. We hypothesized that people with MS (PwMS would have reduced integrity of cerebral proprioceptive pathways, and that reduced white matter microstructure within these tracts would be strongly related to proprioceptive-based balance deficits. We found poorer balance control on proprioceptive-based tasks and reduced white matter microstructural integrity of the cortical proprioceptive tracts in PwMS compared with age-matched healthy controls. Microstructural integrity of this pathway in the right hemisphere was also strongly associated with proprioceptive-based balance control in PwMS and controls. Conversely, while white matter integrity of the right hemisphere’s proprioceptive pathway was significantly correlated with overall balance performance in healthy controls, there was no such relationship in PwMS. These results augment existing literature suggesting that balance control in PwMS may become more dependent upon 1 cerebellar-regulated proprioceptive control, 2 the vestibular system, and/or 3 the visual system.

  5. Lesser Neural Pattern Similarity across Repeated Tests Is Associated with Better Long-Term Memory Retention.

    Science.gov (United States)

    Karlsson Wirebring, Linnea; Wiklund-Hörnqvist, Carola; Eriksson, Johan; Andersson, Micael; Jonsson, Bert; Nyberg, Lars

    2015-07-01

    Encoding and retrieval processes enhance long-term memory performance. The efficiency of encoding processes has recently been linked to representational consistency: the reactivation of a representation that gets more specific each time an item is further studied. Here we examined the complementary hypothesis of whether the efficiency of retrieval processes also is linked to representational consistency. Alternatively, recurrent retrieval might foster representational variability--the altering or adding of underlying memory representations. Human participants studied 60 Swahili-Swedish word pairs before being scanned with fMRI the same day and 1 week later. On Day 1, participants were tested three times on each word pair, and on Day 7 each pair was tested once. A BOLD signal change in right superior parietal cortex was associated with subsequent memory on Day 1 and with successful long-term retention on Day 7. A representational similarity analysis in this parietal region revealed that beneficial recurrent retrieval was associated with representational variability, such that the pattern similarity on Day 1 was lower for retrieved words subsequently remembered compared with those subsequently forgotten. This was mirrored by a monotonically decreased BOLD signal change in dorsolateral prefrontal cortex on Day 1 as a function of repeated successful retrieval for words subsequently remembered, but not for words subsequently forgotten. This reduction in prefrontal response could reflect reduced demands on cognitive control. Collectively, the results offer novel insights into why memory retention benefits from repeated retrieval, and they suggest fundamental differences between repeated study and repeated testing. Repeated testing is known to produce superior long-term retention of the to-be-learned material compared with repeated encoding and other learning techniques, much because it fosters repeated memory retrieval. This study demonstrates that repeated memory

  6. Rumination in major depressive disorder is associated with impaired neural activation during conflict monitoring

    Directory of Open Access Journals (Sweden)

    Brandon L Alderman

    2015-05-01

    Full Text Available Individuals with major depressive disorder (MDD often ruminate about past experiences, especially those with negative content. These repetitive thoughts may interfere with cognitive processes related to attention and conflict monitoring. However, the temporal nature of these processes as reflected in event-related potentials (ERPs has not been well described. We examined behavioral and ERP indices of conflict monitoring during a modified flanker task and the allocation of attention during an attentional blink (AB task in 33 individuals with MDD and 36 healthy controls, and whether their behavioral performance and ERPs varied with level of rumination. N2 amplitude elicited by the flanker task was significantly reduced in participants with MDD compared to healthy controls. Level of self-reported rumination was also correlated with N2 amplitude. In contrast, P3 amplitude during the AB task was not significantly different between groups, nor was it correlated with rumination. No significant differences were found in behavioral task performance measures between groups or by rumination levels. These findings suggest that rumination in MDD is associated with select deficits in cognitive control, particularly related to conflict monitoring.

  7. Neural effects of the CSMD1 genome-wide associated schizophrenia risk variant rs10503253.

    LENUS (Irish Health Repository)

    Rose, Emma J

    2013-09-01

    The single nucleotide polymorphism rs10503253 within the CUB and Sushi multiple domains-1 (CSMD1) gene on 8p23.2 has been identified as genome-wide significant for schizophrenia (SZ). This gene is of unknown function but has been implicated in multiple neurodevelopmental disorders that impact upon cognition, leading us to hypothesize that an effect on brain structure and function underlying cognitive processes may be part of the mechanism by which CMSD1 increases illness risk. To test this hypothesis, we investigated this CSMD1 variant in vivo in healthy participants in a magnetic resonance imaging (MRI) study comprised of both fMRI of spatial working memory (N = 50) and a voxel-based morphometry investigation of grey and white matter (WM) volume (N = 150). Analyses of these data indicated that the risk "A" allele was associated with comparatively reduced cortical activations in BA18, that is, middle occipital gyrus and cuneus; posterior brain regions that support maintenance processes during performance of a spatial working memory task. Conversely, there was an absence of significant structural differences in brain volume (i.e., grey or WM). In accordance with previous evidence, these data suggest that CSMD1 may mediate brain function related to cognitive processes (i.e., executive function); with the relatively deleterious effects of the identified "A" risk allele on brain activity possibly constituting part of the mechanism by which CSMD1 increases schizophrenia risk.

  8. Early Parenting Moderates the Association between Parental Depression and Neural Reactivity to Rewards and Losses in Offspring

    OpenAIRE

    Kujawa, Autumn; Proudfit, Greg H.; Laptook, Rebecca; Klein, Daniel N.

    2014-01-01

    Children of parents with depression exhibit neural abnormalities in reward processing. Examining contributions of parenting could provide insight into the development of these abnormalities and to the etiology of depression. We evaluated whether early parenting moderates the effects of parental depression on a neural measure of reward and loss processing in mid-late childhood. Parenting was assessed when children were preschoolers. At age nine, children completed an event-related potential as...

  9. Molecular profiling of aged neural progenitors identifies Dbx2 as a candidate regulator of age-associated neurogenic decline.

    Science.gov (United States)

    Lupo, Giuseppe; Nisi, Paola S; Esteve, Pilar; Paul, Yu-Lee; Novo, Clara Lopes; Sidders, Ben; Khan, Muhammad A; Biagioni, Stefano; Liu, Hai-Kun; Bovolenta, Paola; Cacci, Emanuele; Rugg-Gunn, Peter J

    2018-06-01

    Adult neurogenesis declines with aging due to the depletion and functional impairment of neural stem/progenitor cells (NSPCs). An improved understanding of the underlying mechanisms that drive age-associated neurogenic deficiency could lead to the development of strategies to alleviate cognitive impairment and facilitate neuroregeneration. An essential step towards this aim is to investigate the molecular changes that occur in NSPC aging on a genomewide scale. In this study, we compare the transcriptional, histone methylation and DNA methylation signatures of NSPCs derived from the subventricular zone (SVZ) of young adult (3 months old) and aged (18 months old) mice. Surprisingly, the transcriptional and epigenomic profiles of SVZ-derived NSPCs are largely unchanged in aged cells. Despite the global similarities, we detect robust age-dependent changes at several hundred genes and regulatory elements, thereby identifying putative regulators of neurogenic decline. Within this list, the homeobox gene Dbx2 is upregulated in vitro and in vivo, and its promoter region has altered histone and DNA methylation levels, in aged NSPCs. Using functional in vitro assays, we show that elevated Dbx2 expression in young adult NSPCs promotes age-related phenotypes, including the reduced proliferation of NSPC cultures and the altered transcript levels of age-associated regulators of NSPC proliferation and differentiation. Depleting Dbx2 in aged NSPCs caused the reverse gene expression changes. Taken together, these results provide new insights into the molecular programmes that are affected during mouse NSPC aging, and uncover a new functional role for Dbx2 in promoting age-related neurogenic decline. © 2018 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

  10. Neural intrinsic connectivity networks associated with risk aversion in old age.

    Science.gov (United States)

    Han, S Duke; Boyle, Patricia A; Arfanakis, Konstantinos; Fleischman, Debra A; Yu, Lei; Edmonds, Emily C; Bennett, David A

    2012-02-01

    Risk aversion is associated with several important real world outcomes. Although the neurobiological correlates of risk aversion have been studied in young persons, little is known of the neurobiological correlates of risk aversion among older persons. Resting-state functional MRI data were collected on 134 non-demented participants of the Rush Memory and Aging Project, a community-based cohort study of aging. Risk aversion was measured using a series of standard questions in which participants were asked to choose between a certain monetary payment ($15) versus a gamble in which they could gain more than $15 or gain nothing, with potential gains varied across questions. Participants determined to be "high" (n=27) and "low" (n=27) in risk aversion were grouped accordingly. Using a spherical seed region of interest in the anterior cingulate cortex, voxel-wise functional connectivity network similarities were observed in bilateral frontal, anterior and posterior cingulate, insula, basal ganglia, temporal, parietal, and thalamic regions. Differences in functional connectivity were observed such that those low in risk aversion had greater connectivity to clusters in the superior, middle, and medial frontal regions, as well as cerebellar, parietal, occipital, and inferior temporal regions. Those high in risk aversion had greater connectivity to clusters in the inferior and orbital frontal, parahippocampal, and insula regions, as well as thalamic, parietal, precentral gyrus, postcentral gyrus, and middle temporal regions. Similarities and differences in functional connectivity patterns may reflect the historical recruitment of specific brain regions as a network in the active processing of risk in older adults. Copyright © 2011 Elsevier B.V. All rights reserved.

  11. Neural Control of Startle-Induced Locomotion by the Mushroom Bodies and Associated Neurons in Drosophila

    Directory of Open Access Journals (Sweden)

    Jun Sun

    2018-03-01

    Full Text Available Startle-induced locomotion is commonly used in Drosophila research to monitor locomotor reactivity and its progressive decline with age or under various neuropathological conditions. A widely used paradigm is startle-induced negative geotaxis (SING, in which flies entrapped in a narrow column react to a gentle mechanical shock by climbing rapidly upwards. Here we combined in vivo manipulation of neuronal activity and splitGFP reconstitution across cells to search for brain neurons and putative circuits that regulate this behavior. We show that the activity of specific clusters of dopaminergic neurons (DANs afferent to the mushroom bodies (MBs modulates SING, and that DAN-mediated SING regulation requires expression of the DA receptor Dop1R1/Dumb, but not Dop1R2/Damb, in intrinsic MB Kenyon cells (KCs. We confirmed our previous observation that activating the MB α'β', but not αβ, KCs decreased the SING response, and we identified further MB neurons implicated in SING control, including KCs of the γ lobe and two subtypes of MB output neurons (MBONs. We also observed that co-activating the αβ KCs antagonizes α'β' and γ KC-mediated SING modulation, suggesting the existence of subtle regulation mechanisms between the different MB lobes in locomotion control. Overall, this study contributes to an emerging picture of the brain circuits modulating locomotor reactivity in Drosophila that appear both to overlap and differ from those underlying associative learning and memory, sleep/wake state and stress-induced hyperactivity.

  12. BDNF Overexpression Exhibited Bilateral Effect on Neural Behavior in SCT Mice Associated with AKT Signal Pathway.

    Science.gov (United States)

    Chen, Mei-Rong; Dai, Ping; Wang, Shu-Fen; Song, Shu-Hua; Wang, Hang-Ping; Zhao, Ya; Wang, Ting-Hua; Liu, Jia

    2016-10-01

    Spinal cord injury (SCI), a severe health problem in worldwide, was commonly associated with functional disability and reduced quality of life. As the expression of brain-derived neurotrophic factor (BDNF) was substantial event in injured spinal cord, we hypothesized whether BDNF-overexpression could be in favor of the recovery of both sensory function and hindlimb function after SCI. By using BDNF-overexpression transgene mice [CMV-BDNF 26 (CB26) mice] we assessed the role of BDNF on the recovery of neurological behavior in spinal cord transection (SCT) model. BMS score and tail-flick test was performed to evaluate locomotor function and sensory function, respectively. Immunohistochemistry was employed to detect the location and the expression of BDNF, NeuN, 5-HT, GAP-43, GFAP as well as CGRP, and the level of p-AKT and AKT were examined through western blot analysis. BDNF overexpressing resulted in significant locomotor functional recovery from 21 to 28 days after SCT, compared with wild type (WT)+SCT group. Meanwhile, the NeuN, 5-HT and GAP-43 positive cells were markedly increased in ventral horn in BDNF overexpression animals, compared with WT mice with SCT. Moreover, the crucial molecular signal, p-AKT/AKT has been largely up-regulated, which is consistent with the improvement of locomotor function. However, in this study, thermal hyperpathia encountered in sham (CB26) group and WT+SCT mice and further aggravated in CB26 mice after SCT. Also, following SCT, the significant augment of positive-GFAP astrocytes and CGRP fibers were found in WT+SCT mice, and further increase was seen in BDNF over-expression transgene mice. BDNF-overexpression may not only facilitate the recovery of locomotor function via AKT pathway, but also contributed simultaneously to thermal hyperalgesia after SCT.

  13. Attentional states influence early neural responses associated with motivational processes: local vs. global attentional scope and N1 amplitude to appetitive stimuli.

    Science.gov (United States)

    Gable, Philip A; Harmon-Jones, Eddie

    2011-05-01

    Positive affects vary in the degree with which they are associated with approach motivation, the drive to approach an object or a goal. High approach-motivated positive affects cause a narrowing of attention, whereas low approach-motivated positive affects causes a broadening of attention. The current study was designed to extend this work by examining whether the relationship between motivation and attentional bias was bi-directional. Specifically, the experiment investigated whether a manipulated local attentional scope would cause greater approach motivational processing than a global attentional scope as measured by neural processes as early as 100 ms. As compared to a global attentional scope, a local attentional scope caused greater neural processing associated with approach motivation as measured by the N1 to appetitive pictures. Copyright © 2011 Elsevier B.V. All rights reserved.

  14. Behavioral Performance and Neural Areas Associated with Memory Processes Contribute to Math and Reading Achievement in 6-year-old Children.

    Science.gov (United States)

    Blankenship, Tashauna L; Keith, Kayla; Calkins, Susan D; Bell, Martha Ann

    2018-01-01

    Associations between working memory and academic achievement (math and reading) are well documented. Surprisingly, little is known of the contributions of episodic memory, segmented into temporal memory (recollection proxy) and item recognition (familiarity proxy), to academic achievement. This is the first study to observe these associations in typically developing 6-year old children. Overlap in neural correlates exists between working memory, episodic memory, and math and reading achievement. We attempted to tease apart the neural contributions of working memory, temporal memory, and item recognition to math and reading achievement. Results suggest that working memory and temporal memory, but not item recognition, are important contributors to both math and reading achievement, and that EEG power during a working memory task contributes to performance on tests of academic achievement.

  15. Acute opioid withdrawal is associated with increased neural activity in reward-processing centers in healthy men: A functional magnetic resonance imaging study.

    Science.gov (United States)

    Chu, Larry F; Lin, Joanne C; Clemenson, Anna; Encisco, Ellen; Sun, John; Hoang, Dan; Alva, Heather; Erlendson, Matthew; Clark, J David; Younger, Jarred W

    2015-08-01

    Opioid analgesics are frequently prescribed for chronic pain. One expected consequence of long-term opioid use is the development of physical dependence. Although previous resting state functional magnetic resonance imaging (fMRI) studies have demonstrated signal changes in reward-associated areas following morphine administration, the effects of acute withdrawal on the human brain have been less well-investigated. In an earlier study by our laboratory, ondansetron was shown to be effective in preventing symptoms associated with opioid withdrawal. The purpose of this current study was to characterize neural activity associated with acute opioid withdrawal and examine whether these changes are modified by ondansetron. Ten participants were enrolled in this placebo-controlled, randomized, double-blind, crossover study and attended three acute opioid withdrawal sessions. Participants received either placebo or ondansetron (8Ymg IV) before morphine administration (10Ymg/70Ykg IV). Participants then underwent acute naloxone-precipitated withdrawal during a resting state fMRI scan. Objective and subjective opioid withdrawal symptoms were assessed. Imaging results showed that naloxone-precipitated opioid withdrawal was associated with increased neural activity in several reward processing regions, including the right pregenual cingulate, putamen, and bilateral caudate, and decreased neural activity in networks involved in sensorimotor integration. Ondansetron pretreatment did not have a significant effect on the imaging correlates of opioid withdrawal. This study presents a preliminary investigation of the regional changes in neural activity during acute opioid withdrawal. The fMRI acute opioid withdrawal model may serve as a tool for studying opioid dependence and withdrawal in human participants. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  16. Neural correlates of stress- and food cue-induced food craving in obesity: association with insulin levels.

    Science.gov (United States)

    Jastreboff, Ania M; Sinha, Rajita; Lacadie, Cheryl; Small, Dana M; Sherwin, Robert S; Potenza, Marc N

    2013-02-01

    Obesity is associated with alterations in corticolimbic-striatal brain regions involved in food motivation and reward. Stress and the presence of food cues may each motivate eating and engage corticolimibic-striatal neurocircuitry. It is unknown how these factors interact to influence brain responses and whether these interactions are influenced by obesity, insulin levels, and insulin sensitivity. We hypothesized that obese individuals would show greater responses in corticolimbic-striatal neurocircuitry after exposure to stress and food cues and that brain activations would correlate with subjective food craving, insulin levels, and HOMA-IR. Fasting insulin levels were assessed in obese and lean subjects who were exposed to individualized stress and favorite-food cues during functional MRI. Obese, but not lean, individuals exhibited increased activation in striatal, insular, and hypothalamic regions during exposure to favorite-food and stress cues. In obese but not lean individuals, food craving, insulin, and HOMA-IR levels correlated positively with neural activity in corticolimbic-striatal brain regions during favorite-food and stress cues. The relationship between insulin resistance and food craving in obese individuals was mediated by activity in motivation-reward regions including the striatum, insula, and thalamus. These findings demonstrate that obese, but not lean, individuals exhibit increased corticolimbic-striatal activation in response to favorite-food and stress cues and that these brain responses mediate the relationship between HOMA-IR and food craving. Improving insulin sensitivity and in turn reducing corticolimbic-striatal reactivity to food cues and stress may diminish food craving and affect eating behavior in obesity.

  17. Early Parenting Moderates the Association between Parental Depression and Neural Reactivity to Rewards and Losses in Offspring.

    Science.gov (United States)

    Kujawa, Autumn; Proudfit, Greg H; Laptook, Rebecca; Klein, Daniel N

    2015-07-01

    Children of parents with depression exhibit neural abnormalities in reward processing. Examining contributions of parenting could provide insight into the development of these abnormalities and to the etiology of depression. We evaluated whether early parenting moderates the effects of parental depression on a neural measure of reward and loss processing in mid-late childhood. Parenting was assessed when children were preschoolers. At age nine, children completed an event-related potential assessment and the feedback negativity (FN) was measured following rewards and losses ( N =344). Maternal authoritative parenting moderated the effect of maternal depression; among offspring of mothers with histories of depression, low authoritative parenting predicted a blunted FN. Observed maternal positive parenting interacted with paternal depression in a comparable manner, indicating that maternal parenting may buffer the effects of paternal depression. Early parenting may be important in shaping the neural systems involved in reward processing among children at high risk for depression.

  18. Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility.

    Science.gov (United States)

    Saggar, Manish; Shelly, Elizabeth Walter; Lepage, Jean-Francois; Hoeft, Fumiko; Reiss, Allan L

    2014-01-01

    Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks was found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus was found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) was partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom. © 2013.

  19. Revealing the neural networks associated with processing of natural social interaction and the related effects of actor-orientation and face-visibility

    Science.gov (United States)

    Saggar, Manish; Shelly, Elizabeth Walter; Lepage, Jean-Francois; Hoeft, Fumiko; Reiss, Allan L.

    2013-01-01

    Understanding the intentions and desires of those around us is vital for adapting to a dynamic social environment. In this paper, a novel event-related functional Magnetic Resonance Imaging (fMRI) paradigm with dynamic and natural stimuli (2s video clips) was developed to directly examine the neural networks associated with processing of gestures with social intent as compared to nonsocial intent. When comparing social to nonsocial gestures, increased activation in both the mentalizing (or theory of mind) and amygdala networks were found. As a secondary aim, a factor of actor-orientation was included in the paradigm to examine how the neural mechanisms differ with respect to personal engagement during a social interaction versus passively observing an interaction. Activity in the lateral occipital cortex and precentral gyrus were found sensitive to actor-orientation during social interactions. Lastly, by manipulating face-visibility we tested whether facial information alone is the primary driver of neural activation differences observed between social and nonsocial gestures. We discovered that activity in the posterior superior temporal sulcus (pSTS) and fusiform gyrus (FFG) were partially driven by observing facial expressions during social gestures. Altogether, using multiple factors associated with processing of natural social interaction, we conceptually advance our understanding of how social stimuli is processed in the brain and discuss the application of this paradigm to clinical populations where atypical social cognition is manifested as a key symptom. PMID:24084068

  20. Impaired neurogenesis, learning and memory and low seizure threshold associated with loss of neural precursor cell survivin

    Directory of Open Access Journals (Sweden)

    Eisch Amelia

    2010-01-01

    Full Text Available Abstract Background Survivin is a unique member of the inhibitor of apoptosis protein (IAP family in that it exhibits antiapoptotic properties and also promotes the cell cycle and mediates mitosis as a chromosome passenger protein. Survivin is highly expressed in neural precursor cells in the brain, yet its function there has not been elucidated. Results To examine the role of neural precursor cell survivin, we first showed that survivin is normally expressed in periventricular neurogenic regions in the embryo, becoming restricted postnatally to proliferating and migrating NPCs in the key neurogenic sites, the subventricular zone (SVZ and the subgranular zone (SGZ. We then used a conditional gene inactivation strategy to delete the survivin gene prenatally in those neurogenic regions. Lack of embryonic NPC survivin results in viable, fertile mice (SurvivinCamcre with reduced numbers of SVZ NPCs, absent rostral migratory stream, and olfactory bulb hypoplasia. The phenotype can be partially rescued, as intracerebroventricular gene delivery of survivin during embryonic development increases olfactory bulb neurogenesis, detected postnatally. SurvivinCamcre brains have fewer cortical inhibitory interneurons, contributing to enhanced sensitivity to seizures, and profound deficits in memory and learning. Conclusions The findings highlight the critical role that survivin plays during neural development, deficiencies of which dramatically impact on postnatal neural function.

  1. Cell Junction Pathology of Neural Stem Cells Is Associated With Ventricular Zone Disruption, Hydrocephalus, and Abnormal Neurogenesis

    NARCIS (Netherlands)

    Montserrat Guerra, Maria; Henzi, Roberto; Ortloff, Alexander; Lichtin, Nicole; Vio, Karin; Jimenez, Antonio J.; Dolores Dominguez-Pinos, Maria; Gonzalez, Cesar; Clara Jara, Maria; Hinostroza, Fernando; Rodriguez, Sara; Jara, Maryoris; Ortega, Eduardo; Guerra, Francisco; Sival, Deborah A.; den Dunnen, Wilfred F. A.; Perez-Figares, Jose M.; McAllister, James P.; Johanson, Conrad E.; Rodriguez, Esteban M.

    Fetal-onset hydrocephalus affects 1 to 3 per 1,000 live births. It is not only a disorder of cerebrospinal fluid dynamics but also a brain disorder that corrective surgery does not ameliorate. We hypothesized that cell junction abnormalities of neural stem cells (NSCs) lead to the inseparable

  2. Genome-wide association mapping in dogs enables identification of the homeobox gene, NKX2-8, as a genetic component of neural tube defects in humans.

    Directory of Open Access Journals (Sweden)

    Noa Safra

    Full Text Available Neural tube defects (NTDs is a general term for central nervous system malformations secondary to a failure of closure or development of the neural tube. The resulting pathologies may involve the brain, spinal cord and/or vertebral column, in addition to associated structures such as soft tissue or skin. The condition is reported among the more common birth defects in humans, leading to significant infant morbidity and mortality. The etiology remains poorly understood but genetic, nutritional, environmental factors, or a combination of these, are known to play a role in the development of NTDs. The variable conditions associated with NTDs occur naturally in dogs, and have been previously reported in the Weimaraner breed. Taking advantage of the strong linkage-disequilibrium within dog breeds we performed genome-wide association analysis and mapped a genomic region for spinal dysraphism, a presumed NTD, using 4 affected and 96 unaffected Weimaraners. The associated region on canine chromosome 8 (pgenome  =3.0 × 10(-5, after 100,000 permutations, encodes 18 genes, including NKX2-8, a homeobox gene which is expressed in the developing neural tube. Sequencing NKX2-8 in affected Weimaraners revealed a G to AA frameshift mutation within exon 2 of the gene, resulting in a premature stop codon that is predicted to produce a truncated protein. The exons of NKX2-8 were sequenced in human patients with spina bifida and rare variants (rs61755040 and rs10135525 were found to be significantly over-represented (p=0.036. This is the first documentation of a potential role for NKX2-8 in the etiology of NTDs, made possible by investigating the molecular basis of naturally occurring mutations in dogs.

  3. 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

  4. Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns.

    Directory of Open Access Journals (Sweden)

    Hiroyuki Akama

    Full Text Available In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF. This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk and co-occurrence adjustment (degree balance and distribution. We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

  5. Fatigue sensation induced by the sounds associated with mental fatigue and its related neural activities: revealed by magnetoencephalography

    OpenAIRE

    Ishii, Akira; Tanaka, Masaaki; Iwamae, Masayoshi; Kim, Chongsoo; Yamano, Emi; Watanabe, Yasuyoshi

    2013-01-01

    Background It has been proposed that an inappropriately conditioned fatigue sensation could be one cause of chronic fatigue. Although classical conditioning of the fatigue sensation has been reported in rats, there have been no reports in humans. Our aim was to examine whether classical conditioning of the mental fatigue sensation can take place in humans and to clarify the neural mechanisms of fatigue sensation using magnetoencephalography (MEG). Methods Ten and 9 healthy volunteers particip...

  6. Associating a product with a luxury brand label modulates neural reward processing and favors choices in materialistic individuals

    OpenAIRE

    Audrin, Catherine; Ceravolo, Leonardo; Chanal, Julien; Brosch, Tobias; Sander, David

    2017-01-01

    The present study investigated the extent to which luxury vs. non-luxury brand labels (i.e., extrinsic cues) randomly assigned to items and preferences for these items impact choice, and how this impact may be moderated by materialistic tendencies (i.e., individual characteristics). The main objective was to investigate the neural correlates of abovementioned effects using functional magnetic resonance imaging. Behavioural results showed that the more materialistic people are, the more they c...

  7. A negative modulatory role for rho and rho-associated kinase signaling in delamination of neural crest cells

    Directory of Open Access Journals (Sweden)

    Kalcheim Chaya

    2008-10-01

    Full Text Available Abstract Background Neural crest progenitors arise as epithelial cells and then undergo a process of epithelial to mesenchymal transition that precedes the generation of cellular motility and subsequent migration. We aim at understanding the underlying molecular network. Along this line, possible roles of Rho GTPases that act as molecular switches to control a variety of signal transduction pathways remain virtually unexplored, as are putative interactions between Rho proteins and additional known components of this cascade. Results We investigated the role of Rho/Rock signaling in neural crest delamination. Active RhoA and RhoB are expressed in the membrane of epithelial progenitors and are downregulated upon delamination. In vivo loss-of-function of RhoA or RhoB or of overall Rho signaling by C3 transferase enhanced and/or triggered premature crest delamination yet had no effect on cell specification. Consistently, treatment of explanted neural primordia with membrane-permeable C3 or with the Rock inhibitor Y27632 both accelerated and enhanced crest emigration without affecting cell proliferation. These treatments altered neural crest morphology by reducing stress fibers, focal adhesions and downregulating membrane-bound N-cadherin. Reciprocally, activation of endogenous Rho by lysophosphatidic acid inhibited emigration while enhancing the above. Since delamination is triggered by BMP and requires G1/S transition, we examined their relationship with Rho. Blocking Rho/Rock function rescued crest emigration upon treatment with noggin or with the G1/S inhibitor mimosine. In the latter condition, cells emigrated while arrested at G1. Conversely, BMP4 was unable to rescue cell emigration when endogenous Rho activity was enhanced by lysophosphatidic acid. Conclusion Rho-GTPases, through Rock, act downstream of BMP and of G1/S transition to negatively regulate crest delamination by modifying cytoskeleton assembly and intercellular adhesion.

  8. Fatigue sensation induced by the sounds associated with mental fatigue and its related neural activities: revealed by magnetoencephalography.

    Science.gov (United States)

    Ishii, Akira; Tanaka, Masaaki; Iwamae, Masayoshi; Kim, Chongsoo; Yamano, Emi; Watanabe, Yasuyoshi

    2013-06-13

    It has been proposed that an inappropriately conditioned fatigue sensation could be one cause of chronic fatigue. Although classical conditioning of the fatigue sensation has been reported in rats, there have been no reports in humans. Our aim was to examine whether classical conditioning of the mental fatigue sensation can take place in humans and to clarify the neural mechanisms of fatigue sensation using magnetoencephalography (MEG). Ten and 9 healthy volunteers participated in a conditioning and a control experiment, respectively. In the conditioning experiment, we used metronome sounds as conditioned stimuli and two-back task trials as unconditioned stimuli to cause fatigue sensation. Participants underwent MEG measurement while listening to the metronome sounds for 6 min. Thereafter, fatigue-inducing mental task trials (two-back task trials), which are demanding working-memory task trials, were performed for 60 min; metronome sounds were started 30 min after the start of the task trials (conditioning session). The next day, neural activities while listening to the metronome for 6 min were measured. Levels of fatigue sensation were also assessed using a visual analogue scale. In the control experiment, participants listened to the metronome on the first and second days, but they did not perform conditioning session. MEG was not recorded in the control experiment. The level of fatigue sensation caused by listening to the metronome on the second day was significantly higher relative to that on the first day only when participants performed the conditioning session on the first day. Equivalent current dipoles (ECDs) in the insular cortex, with mean latencies of approximately 190 ms, were observed in six of eight participants after the conditioning session, although ECDs were not identified in any participant before the conditioning session. We demonstrated that the metronome sounds can cause mental fatigue sensation as a result of repeated pairings of the sounds

  9. Association of Irritability and Anxiety With the Neural Mechanisms of Implicit Face Emotion Processing in Youths With Psychopathology.

    Science.gov (United States)

    Stoddard, Joel; Tseng, Wan-Ling; Kim, Pilyoung; Chen, Gang; Yi, Jennifer; Donahue, Laura; Brotman, Melissa A; Towbin, Kenneth E; Pine, Daniel S; Leibenluft, Ellen

    2017-01-01

    Psychiatric comorbidity complicates clinical care and confounds efforts to elucidate the pathophysiology of commonly occurring symptoms in youths. To our knowledge, few studies have simultaneously assessed the effect of 2 continuously distributed traits on brain-behavior relationships in children with psychopathology. To determine shared and unique effects of 2 major dimensions of child psychopathology, irritability and anxiety, on neural responses to facial emotions during functional magnetic resonance imaging. Cross-sectional functional magnetic resonance imaging study in a large, well-characterized clinical sample at a research clinic at the National Institute of Mental Health. The referred sample included youths ages 8 to 17 years, 93 youths with anxiety, disruptive mood dysregulation, and/or attention-deficit/hyperactivity disorders and 22 healthy youths. The child's irritability and anxiety were rated by both parent and child on the Affective Reactivity Index and Screen for Child Anxiety Related Disorders, respectively. Using functional magnetic resonance imaging, neural response was measured across the brain during gender labeling of varying intensities of angry, happy, or fearful face emotions. In mixed-effects analyses, the shared and unique effects of irritability and anxiety were tested on amygdala functional connectivity and activation to face emotions. The mean (SD) age of participants was 13.2 (2.6) years; of the 115 included, 64 were male. Irritability and/or anxiety influenced amygdala connectivity to the prefrontal and temporal cortex. Specifically, irritability and anxiety jointly influenced left amygdala to left medial prefrontal cortex connectivity during face emotion viewing (F4,888 = 9.20; P differences in neural response to face emotions in several areas (F2, 888 ≥ 13.45; all P emotion dysregulation when very anxious and irritable youth process threat-related faces. Activation in the ventral visual circuitry suggests a mechanism

  10. Improved Exercise Tolerance with Caffeine Is Associated with Modulation of both Peripheral and Central Neural Processes in Human Participants

    DEFF Research Database (Denmark)

    Bowtell, Joanna L; Mohr, Magni; Fulford, Jonathan

    2018-01-01

    calcium handling and extracellular potassium regulation. Our aims were to investigate how caffeine (i) affects knee extensor PCr kinetics and pH during repeated sets of single-leg knee extensor exercise to task failure and (ii) modulates the interplay between central and peripheral neural processes. We...... hypothesized that the caffeine-induced extension of exercise capacity during repeated sets of exercise would occur despite greater disturbance of the muscle milieu due to enhanced peripheral and corticospinal excitatory output, central motor drive, and muscle contractility. Methods: Nine healthy active young...

  11. Neural processing of gendered information is more robustly associated with mothers' gendered communication with children than mothers' implicit and explicit gender stereotypes.

    Science.gov (United States)

    Endendijk, Joyce J; Spencer, Hannah; Bos, Peter A; Derks, Belle

    2018-04-26

    Processes like gender socialization (the ways in which parents convey information to their children about how girls and boys should behave) often happen unconsciously and might therefore be studied best with neuroscientific measures. We examined whether neural processing of gender-stereotype-congruent and incongruent information is more robustly related to mothers' gendered socialization of their child than mothers' implicit and explicit gender stereotypes. To this end, we examined event-related potentials (ERPs) of mothers (N = 35) completing an implicit gender-stereotype task and mothers' gender stereotypes in relation to observed gendered communication with their child (2-6 years old) in a naturalistic picture-book-reading setting. Increased N2 activity (previously related to attentional processes) to gender stimuli in the implicit gender-stereotype task was associated with mothers' positive evaluation of similar gendered behaviors and activities in the picture book they read with their child. Increased P300 activity (previously related to attention to unexpected events) to incongruent trials in the gender-stereotype task was associated with a more positive evaluation of congruent versus incongruent pictures. Compared to mothers' gender stereotypes, neural processing of gendered information was more robustly related to how mothers talk to their children about boys' and girls' stereotype-congruent and incongruent behavior, and masculine and feminine activities.

  12. Neural reactivity to monetary rewards and losses in childhood: longitudinal and concurrent associations with observed and self-reported positive emotionality.

    Science.gov (United States)

    Kujawa, Autumn; Proudfit, Greg Hajcak; Kessel, Ellen M; Dyson, Margaret; Olino, Thomas; Klein, Daniel N

    2015-01-01

    Reward reactivity and positive emotion are key components of a theoretical, early-emerging approach motivational system, yet few studies have examined associations between positive emotion and neural reactivity to reward across development. In this multi-method prospective study, we examined the association of laboratory observations of positive emotionality (PE) at age 3 and self-reported positive affect (PA) at age 9 with an event-related potential component sensitive to the relative response to winning vs. losing money, the feedback negativity (ΔFN), at age 9 (N=381). Males had a larger ΔFN than females, and both greater observed PE at age 3 and self-reported PA at age 9 significantly, but modestly, predicted an enhanced ΔFN at age 9. Negative emotionality and behavioral inhibition did not predict ΔFN. Results contribute to understanding the neural correlates of PE and suggest that the FN and PE may be related to the same biobehavioral approach system. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Neural processing of emotional facial and semantic expressions in euthymic bipolar disorder (BD and its association with theory of mind (ToM.

    Directory of Open Access Journals (Sweden)

    Agustin Ibanez

    Full Text Available BACKGROUND: Adults with bipolar disorder (BD have cognitive impairments that affect face processing and social cognition. However, it remains unknown whether these deficits in euthymic BD have impaired brain markers of emotional processing. METHODOLOGY/PRINCIPAL FINDINGS: We recruited twenty six participants, 13 controls subjects with an equal number of euthymic BD participants. We used an event-related potential (ERP assessment of a dual valence task (DVT, in which faces (angry and happy, words (pleasant and unpleasant, and face-word simultaneous combinations are presented to test the effects of the stimulus type (face vs word and valence (positive vs. negative. All participants received clinical, neuropsychological and social cognition evaluations. ERP analysis revealed that both groups showed N170 modulation of stimulus type effects (face > word. BD patients exhibited reduced and enhanced N170 to facial and semantic valence, respectively. The neural source estimation of N170 was a posterior section of the fusiform gyrus (FG, including the face fusiform area (FFA. Neural generators of N170 for faces (FG and FFA were reduced in BD. In these patients, N170 modulation was associated with social cognition (theory of mind. CONCLUSIONS/SIGNIFICANCE: This is the first report of euthymic BD exhibiting abnormal N170 emotional discrimination associated with theory of mind impairments.

  14. Neural processing of emotional facial and semantic expressions in euthymic bipolar disorder (BD) and its association with theory of mind (ToM).

    Science.gov (United States)

    Ibanez, Agustin; Urquina, Hugo; Petroni, Agustín; Baez, Sandra; Lopez, Vladimir; do Nascimento, Micaela; Herrera, Eduar; Guex, Raphael; Hurtado, Esteban; Blenkmann, Alejandro; Beltrachini, Leandro; Gelormini, Carlos; Sigman, Mariano; Lischinsky, Alicia; Torralva, Teresa; Torrente, Fernando; Cetkovich, Marcelo; Manes, Facundo

    2012-01-01

    Adults with bipolar disorder (BD) have cognitive impairments that affect face processing and social cognition. However, it remains unknown whether these deficits in euthymic BD have impaired brain markers of emotional processing. We recruited twenty six participants, 13 controls subjects with an equal number of euthymic BD participants. We used an event-related potential (ERP) assessment of a dual valence task (DVT), in which faces (angry and happy), words (pleasant and unpleasant), and face-word simultaneous combinations are presented to test the effects of the stimulus type (face vs word) and valence (positive vs. negative). All participants received clinical, neuropsychological and social cognition evaluations. ERP analysis revealed that both groups showed N170 modulation of stimulus type effects (face > word). BD patients exhibited reduced and enhanced N170 to facial and semantic valence, respectively. The neural source estimation of N170 was a posterior section of the fusiform gyrus (FG), including the face fusiform area (FFA). Neural generators of N170 for faces (FG and FFA) were reduced in BD. In these patients, N170 modulation was associated with social cognition (theory of mind). This is the first report of euthymic BD exhibiting abnormal N170 emotional discrimination associated with theory of mind impairments.

  15. Clinically oriented device programming in bradycardia patients: part 2 (atrioventricular blocks and neurally mediated syncope). Proposals from AIAC (Italian Association of Arrhythmology and Cardiac Pacing).

    Science.gov (United States)

    Palmisano, Pietro; Ziacchi, Matteo; Biffi, Mauro; Ricci, Renato P; Landolina, Maurizio; Zoni-Berisso, Massimo; Occhetta, Eraldo; Maglia, Giampiero; Botto, Gianluca; Padeletti, Luigi; Boriani, Giuseppe

    2018-04-01

    : The purpose of this two-part consensus document is to provide specific suggestions (based on an extensive literature review) on appropriate pacemaker setting in relation to patients' clinical features. In part 2, criteria for pacemaker choice and programming in atrioventricular blocks and neurally mediate syncope are proposed. The atrioventricular blocks can be paroxysmal or persistent, isolated or associated with sinus node disease. Neurally mediated syncope can be related to carotid sinus syndrome or cardioinhibitory vasovagal syncope. In sinus rhythm, with persistent atrioventricular block, we considered appropriate the activation of mode-switch algorithms, and algorithms for auto-adaptive management of the ventricular pacing output. If the atrioventricular block is paroxysmal, in addition to algorithms mentioned above, algorithms to maximize intrinsic atrioventricular conduction should be activated. When sinus node disease is associated with atrioventricular block, the activation of rate-responsive function in patients with chronotropic incompetence is appropriate. In permanent atrial fibrillation with atrioventricular block, algorithms for auto-adaptive management of the ventricular pacing output should be activated. If the atrioventricular block is persistent, the activation of rate-responsive function is appropriate. In carotid sinus syndrome, adequate rate hysteresis should be programmed. In vasovagal syncope, specialized sensing and pacing algorithms designed for reflex syncope prevention should be activated.

  16. Recognition of abstract objects via neural oscillators: interaction among topological organization, associative memory and gamma band synchronization.

    Science.gov (United States)

    Ursino, Mauro; Magosso, Elisa; Cuppini, Cristiano

    2009-02-01

    Synchronization of neural activity in the gamma band is assumed to play a significant role not only in perceptual processing, but also in higher cognitive functions. Here, we propose a neural network of Wilson-Cowan oscillators to simulate recognition of abstract objects, each represented as a collection of four features. Features are ordered in topological maps of oscillators connected via excitatory lateral synapses, to implement a similarity principle. Experience on previous objects is stored in long-range synapses connecting the different topological maps, and trained via timing dependent Hebbian learning (previous knowledge principle). Finally, a downstream decision network detects the presence of a reliable object representation, when all features are oscillating in synchrony. Simulations performed giving various simultaneous objects to the network (from 1 to 4), with some missing and/or modified properties suggest that the network can reconstruct objects, and segment them from the other simultaneously present objects, even in case of deteriorated information, noise, and moderate correlation among the inputs (one common feature). The balance between sensitivity and specificity depends on the strength of the Hebbian learning. Achieving a correct reconstruction in all cases, however, requires ad hoc selection of the oscillation frequency. The model represents an attempt to investigate the interactions among topological maps, autoassociative memory, and gamma-band synchronization, for recognition of abstract objects.

  17. Auto-Associative Recurrent Neural Networks and Long Term Dependencies in Novelty Detection for Audio Surveillance Applications

    Science.gov (United States)

    Rossi, A.; Montefoschi, F.; Rizzo, A.; Diligenti, M.; Festucci, C.

    2017-10-01

    Machine Learning applied to Automatic Audio Surveillance has been attracting increasing attention in recent years. In spite of several investigations based on a large number of different approaches, little attention had been paid to the environmental temporal evolution of the input signal. In this work, we propose an exploration in this direction comparing the temporal correlations extracted at the feature level with the one learned by a representational structure. To this aim we analysed the prediction performances of a Recurrent Neural Network architecture varying the length of the processed input sequence and the size of the time window used in the feature extraction. Results corroborated the hypothesis that sequential models work better when dealing with data characterized by temporal order. However, so far the optimization of the temporal dimension remains an open issue.

  18. Improved Exercise Tolerance with Caffeine Is Associated with Modulation of both Peripheral and Central Neural Processes in Human Participants

    DEFF Research Database (Denmark)

    Bowtell, Joanna L; Mohr, Magni; Fulford, Jonathan

    2018-01-01

    Background: Caffeine has been shown to enhance exercise performance and capacity. The mechanisms remain unclear but are suggested to relate to adenosine receptor antagonism, resulting in increased central motor drive, reduced perception of effort, and altered peripheral processes such as enhanced...... men performed five sets of intense single-leg knee extensor exercise to task failure on four separate occasions: for two visits (6 mg·kg-1 caffeine vs placebo), quadriceps 31P-magnetic resonance spectroscopy scans were performed to quantify phosphocreatine kinetics and pH, and for the remaining two...... calcium handling and extracellular potassium regulation. Our aims were to investigate how caffeine (i) affects knee extensor PCr kinetics and pH during repeated sets of single-leg knee extensor exercise to task failure and (ii) modulates the interplay between central and peripheral neural processes. We...

  19. 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.

  20. Recycling signals in the neural crest

    OpenAIRE

    Taneyhill, Lisa A.; Bronner-Fraser, Marianne E.

    2006-01-01

    Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

  1. Recycling signals in the neural crest.

    Science.gov (United States)

    Taneyhill, Lisa A; Bronner-Fraser, Marianne

    2005-01-01

    Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

  2. Frontolimbic neural circuit changes in emotional processing and inhibitory control associated with clinical improvement following transference-focused psychotherapy in borderline personality disorder.

    Science.gov (United States)

    Perez, David L; Vago, David R; Pan, Hong; Root, James; Tuescher, Oliver; Fuchs, Benjamin H; Leung, Lorene; Epstein, Jane; Cain, Nicole M; Clarkin, John F; Lenzenweger, Mark F; Kernberg, Otto F; Levy, Kenneth N; Silbersweig, David A; Stern, Emily

    2016-01-01

    Borderline personality disorder (BPD) is characterized by self-regulation deficits, including impulsivity and affective lability. Transference-focused psychotherapy (TFP) is an evidence-based treatment proven to reduce symptoms across multiple cognitive-emotional domains in BPD. This pilot study aimed to investigate neural activation associated with, and predictive of, clinical improvement in emotional and behavioral regulation in BPD following TFP. BPD subjects (n = 10) were scanned pre- and post-TFP treatment using a within-subjects design. A disorder-specific emotional-linguistic go/no-go functional magnetic resonance imaging paradigm was used to probe the interaction between negative emotional processing and inhibitory control. Analyses demonstrated significant treatment-related effects with relative increased dorsal prefrontal (dorsal anterior cingulate, dorsolateral prefrontal, and frontopolar cortices) activation, and relative decreased ventrolateral prefrontal cortex and hippocampal activation following treatment. Clinical improvement in constraint correlated positively with relative increased left dorsal anterior cingulate cortex activation. Clinical improvement in affective lability correlated positively with left posterior-medial orbitofrontal cortex/ventral striatum activation, and negatively with right amygdala/parahippocampal activation. Post-treatment improvements in constraint were predicted by pre-treatment right dorsal anterior cingulate cortex hypoactivation, and pre-treatment left posterior-medial orbitofrontal cortex/ventral striatum hypoactivation predicted improvements in affective lability. These preliminary findings demonstrate potential TFP-associated alterations in frontolimbic circuitry and begin to identify neural mechanisms associated with a psychodynamically oriented psychotherapy. © 2015 The Authors. Psychiatry and Clinical Neurosciences © 2015 Japanese Society of Psychiatry and Neurology.

  3. Neural correlates of memory encoding and recognition for own-race and other-race faces in an associative-memory task.

    Science.gov (United States)

    Herzmann, Grit; Minor, Greta; Adkins, Makenzie

    2017-01-15

    The ability to recognize faces of family members, friends, and acquaintances plays an important role in our daily interactions. The other-race effect is the reduced ability to recognize other-race faces as compared to own-race faces. Previous studies showed different patterns of event-related potentials (ERPs) associated with recollection and familiarity during memory encoding (i.e., Dm) and recognition (i.e., parietal old/new effect) for own-race and other-race faces in a subjective-recollection task (remember-know judgments). The present study investigated the same neural correlates of the other-race effect in an associative-memory task, in which Caucasian and East Asian participants learned and recognized own-race and other-race faces along with background colors. Participants made more false alarms for other-race faces indicating lower memory performance. During the study phase, subsequently recognized other-race faces (with and without correct background information) elicited more positive mean amplitudes than own-race faces, suggesting increased neural activation during encoding of other-race faces. During the test phase, recollection-related old/new effects dissociated between own-race and other-race faces. Old/new effects were significant only for own-race but not for other-race faces, indicating that recognition only of own-race faces was supported by recollection and led to more detailed memory retrieval. Most of these results replicated previous studies that used a subjective-recollection task. Our study also showed that the increased demand on memory encoding during an associative-memory task led to Dm patterns that indicated similarly deep memory encoding for own-race and other-race faces. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Exploring geological and socio-demographic factors associated with under-five mortality in the Wenchuan earthquake using neural network model.

    Science.gov (United States)

    Hu, Yi; Wang, Jinfeng; Li, Xiaohong; Ren, Dan; Driskell, Luke; Zhu, Jun

    2012-01-01

    On 12 May 2008, a devastating earthquake occurred in Sichuan Province, China, taking tens of thousands of lives and destroying the homes of millions of people. Among the large number of dead or missing were children, particularly children aged less than five years old, a fact which drew significant media attention. To obtain relevant information specifically to aid further studies and future preventative measures, a neural network model was proposed to explore some geological and socio-demographic factors associated with earthquake-related child mortality. Sensitivity analysis showed that topographic slope (mean 35.76%), geomorphology (mean 24.18%), earthquake intensity (mean 13.68%), and average income (mean 11%) had great contributions to child mortality. These findings could provide some clues to researchers for further studies and to policy makers in deciding how and where preventive measures and corresponding policies should be implemented in the reconstruction of communities.

  5. Synchronization of a Class of Memristive Stochastic Bidirectional Associative Memory Neural Networks with Mixed Time-Varying Delays via Sampled-Data Control

    Directory of Open Access Journals (Sweden)

    Manman Yuan

    2018-01-01

    Full Text Available The paper addresses the issue of synchronization of memristive bidirectional associative memory neural networks (MBAMNNs with mixed time-varying delays and stochastic perturbation via a sampled-data controller. First, we propose a new model of MBAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying distributed delays and discrete delays. Second, we design a new method of sampled-data control for the stochastic MBAMNNs. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the methods are carefully designed to confirm the synchronization processes are suitable for the feather of the memristor. Third, sufficient criteria guaranteeing the synchronization of the systems are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.

  6. Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

    Science.gov (United States)

    Oustimov, Andrew; Gastounioti, Aimilia; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

    2017-03-01

    We assess the feasibility of a parenchymal texture feature fusion approach, utilizing a convolutional neural network (ConvNet) architecture, to benefit breast cancer risk assessment. Hypothesizing that by capturing sparse, subtle interactions between localized motifs present in two-dimensional texture feature maps derived from mammographic images, a multitude of texture feature descriptors can be optimally reduced to five meta-features capable of serving as a basis on which a linear classifier, such as logistic regression, can efficiently assess breast cancer risk. We combine this methodology with our previously validated lattice-based strategy for parenchymal texture analysis and we evaluate the feasibility of this approach in a case-control study with 424 digital mammograms. In a randomized split-sample setting, we optimize our framework in training/validation sets (N=300) and evaluate its descriminatory performance in an independent test set (N=124). The discriminatory capacity is assessed in terms of the the area under the curve (AUC) of the receiver operator characteristic (ROC). The resulting meta-features exhibited strong classification capability in the test dataset (AUC = 0.90), outperforming conventional, non-fused, texture analysis which previously resulted in an AUC=0.85 on the same case-control dataset. Our results suggest that informative interactions between localized motifs exist and can be extracted and summarized via a fairly simple ConvNet architecture.

  7. Patterns of congenital bony spinal deformity and associated neural anomalies on X-ray and magnetic resonance imaging.

    Science.gov (United States)

    Trenga, Anthony P; Singla, Anuj; Feger, Mark A; Abel, Mark F

    2016-08-01

    Congenital malformations of the bony vertebral column are often accompanied by spinal cord anomalies; these observations have been reinforced with the use of magnetic resonance imaging (MRI). We hypothesized that the incidence of cord anomalies will increase as the number and complexity of bony vertebral abnormalities increases. All patients aged ≤13 years (n = 75) presenting to the pediatric spine clinic from 2003-2013 with congenital bony spinal deformity and both radiographs and MRI were analyzed retrospectively for bone and neural pathology. Chi-squared analysis was used to compare groups for categorical dependent variables. Independent t tests were used for continuous dependent variables. Significance was set at p formation had a higher incidence of cord anomalies (73 %) than failures of formation (50 %) or segmentation (45 %) alone (p = 0.065). Deformities in the sacrococcygeal area had the highest rate of spinal cord anomalies (13 of 15 patients, 87 %). In 35 cases (47 %), MRI revealed additional bony anomalies that were not seen on the radiographs. As the number of bony malformations increased, we found a higher incidence of cord anomalies. Clinicians should have increased suspicion of spinal cord pathology in the presence of mixed failures of segmentation and formation.

  8. Changes in neural circuitry associated with depression at pre-clinical, pre-motor and early motor phases of Parkinson's disease.

    Science.gov (United States)

    Borgonovo, Janina; Allende-Castro, Camilo; Laliena, Almudena; Guerrero, Néstor; Silva, Hernán; Concha, Miguel L

    2017-02-01

    Although Parkinson's Disease (PD) is mostly considered a motor disorder, it can present at early stages as a non-motor pathology. Among the non-motor clinical manifestations, depression shows a high prevalence and can be one of the first clinical signs to appear, even a decade before the onset of motor symptoms. Here, we review the evidence of early dysfunction in neural circuitry associated with depression in the context of PD, focusing on pre-clinical, pre-motor and early motor phases of the disease. In the pre-clinical phase, structural and functional changes in the substantia nigra, basal ganglia and limbic structures are already observed. Some of these changes are linked to motor compensation mechanisms while others correspond to pathological processes common to PD and depression and thus could underlie the appearance of depressive symptoms during the pre-motor phase. Studies of the early motor phase (less than five years post diagnosis) reveal an association between the extent of damage in different monoaminergic systems and the appearance of emotional disorders. We propose that the limbic loop of the basal ganglia and the lateral habenula play key roles in the early genesis of depression in PD. Alterations in the neural circuitry linked with emotional control might be sensitive markers of the ongoing neurodegenerative process and thus may serve to facilitate an early diagnosis of this disease. To take advantage of this, we need to improve the clinical criteria and develop biomarkers to identify depression, which could be used to determine individuals at risk to develop PD. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Can early-life growth disruptions predict longevity? Testing the association between vertebral neural canal (VNC) size and age-at-death.

    Science.gov (United States)

    Amoroso, Alexandra; Garcia, Susana J

    2018-04-04

    This study tests the association of vertebral neural canal (VNC) size and age-at-death in a Portuguese skeletal collection from the 19 th -20th century. If the plasticity and constraint model best explains this association, VNC size would be negatively related to mortality risk. If the predictive adaptive response (PAR) model is a better fit, no association can be inferred between VNC size and age-at-death. Ninety individuals were used in this study. The anteroposterior and transverse diameters of all vertebrae were measured. A Cox regression analysis was performed by sex to assess the effect of VNC size on age-at-death, after adjusting for the effects of year of birth and cause of death. Several measurements of VNC diameters have a statistically significant effect on age-at-death, but when the covariates were considered, this association became non-significant. The PAR model seems the best fit to explain the relation between VNC and age-at-death. Individuals who went through stressful events early in life were prepared to face a stressful environment later in life, allowing them to cope with adversity without affecting longevity. However, developmental plasticity may be buffered by maternal capital accumulated over several generations, and health hazards encountered throughout life can contribute to health outcomes and longevity. Copyright © 2018 Elsevier Inc. All rights reserved.

  10. Cadmium-induced neural tube defects and fetal growth restriction: Association with disturbance of placental folate transport

    International Nuclear Information System (INIS)

    Zhang, Gui-Bin; Wang, Hua; Hu, Jun; Guo, Min-Yin; Wang, Ying; Zhou, Yan; Yu, Zhen; Fu, Lin; Chen, Yuan-Hua; Xu, De-Xiang

    2016-01-01

    Previous studies found that maternal Cd exposure on gestational day (GD)9 caused forelimb ectrodactyly and tail deformity, the characteristic malformations. The aim of the present study was to investigate whether maternal Cd exposure on GD8 induces fetal neural tube defects (NTDs). Pregnant mice were intraperitoneally injected with CdCl 2 (2.5 or 5.0 mg/kg) on GD8. Neither forelimb ectrodactyly nor tail deformity was observed in mice injected with CdCl 2 on GD8. Instead, maternal Cd exposure on GD8 resulted in the incidence of NTDs. Moreover, maternal Cd exposure on GD8 resulted in fetal growth restriction. In addition, maternal Cd exposure on GD8 reduced placental weight and diameter. The internal space of maternal and fetal blood vessels in the labyrinth layer was decreased in the placentas of mice treated with CdCl 2 . Additional experiment showed that placental PCFT protein and mRNA, a critical folate transporter, was persistently decreased when dams were injected with CdCl 2 on GD8. Correspondingly, embryonic folate content was markedly decreased in mice injected with CdCl 2 on GD8, whereas Cd had little effect on folate content in maternal serum. Taken together, these results suggest that maternal Cd exposure during organogenesis disturbs transport of folate from maternal circulation to the fetuses through down-regulating placental folate transporters. - Highlights: • Maternal Cd exposure during organogenesis causes NTDs and FGR. • Maternal Cd exposure during organogenesis impairs placental development. • Cd disturbs transport of folate by down-regulating placental folate transporters.

  11. Cadmium-induced neural tube defects and fetal growth restriction: Association with disturbance of placental folate transport

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Gui-Bin; Wang, Hua, E-mail: wanghuadev@126.com; Hu, Jun; Guo, Min-Yin; Wang, Ying; Zhou, Yan; Yu, Zhen; Fu, Lin; Chen, Yuan-Hua; Xu, De-Xiang, E-mail: xudex@126.com

    2016-09-01

    Previous studies found that maternal Cd exposure on gestational day (GD)9 caused forelimb ectrodactyly and tail deformity, the characteristic malformations. The aim of the present study was to investigate whether maternal Cd exposure on GD8 induces fetal neural tube defects (NTDs). Pregnant mice were intraperitoneally injected with CdCl{sub 2} (2.5 or 5.0 mg/kg) on GD8. Neither forelimb ectrodactyly nor tail deformity was observed in mice injected with CdCl{sub 2} on GD8. Instead, maternal Cd exposure on GD8 resulted in the incidence of NTDs. Moreover, maternal Cd exposure on GD8 resulted in fetal growth restriction. In addition, maternal Cd exposure on GD8 reduced placental weight and diameter. The internal space of maternal and fetal blood vessels in the labyrinth layer was decreased in the placentas of mice treated with CdCl{sub 2}. Additional experiment showed that placental PCFT protein and mRNA, a critical folate transporter, was persistently decreased when dams were injected with CdCl{sub 2} on GD8. Correspondingly, embryonic folate content was markedly decreased in mice injected with CdCl{sub 2} on GD8, whereas Cd had little effect on folate content in maternal serum. Taken together, these results suggest that maternal Cd exposure during organogenesis disturbs transport of folate from maternal circulation to the fetuses through down-regulating placental folate transporters. - Highlights: • Maternal Cd exposure during organogenesis causes NTDs and FGR. • Maternal Cd exposure during organogenesis impairs placental development. • Cd disturbs transport of folate by down-regulating placental folate transporters.

  12. Magnitude of Neural Tube Defects and Associated Risk Factors at Three Teaching Hospitals in Addis Ababa, Ethiopia

    Directory of Open Access Journals (Sweden)

    Abel Gedefaw

    2018-01-01

    Full Text Available There is scarcity of data on prevalence of neural tube defects (NTDs in lower-income countries. Local data are important to understand the real burden of the problem and explore risk factors to design and implement preventive approaches. This study aimed to determine prevalence and risk factors of NTDs. A hospital-based cross-sectional and unmatched case-control study was conducted at three teaching hospitals of Addis Ababa University. NTDs were defined as cases of anencephaly, spina bifida, and encephalocele based on ICD-10 criteria. The prevalence of NTDs was calculated per 10,000 births for both birth and total prevalence. During seven months, we observed 55 cases of NTDs out of 8677 births after 28 weeks of gestation—birth prevalence of 63.4 per 10,000 births (95% confidence interval (CI, 51–77. A total of 115 cases were medically terminated after 12 weeks of gestation. Fifty-six of these terminations (48.7% were due to NTDs. Thus, total prevalence of NTDs after 12 weeks’ gestation is 126 per 10,000 births (95% CI, 100–150. Planned pregnancy (adjusted odds ratio (aOR, 0.47; 95% CI, 0.24–0.92, male sex (aOR, 0.56; 95% CI, 0.33–0.94, normal or underweight body mass index (aOR, 0.49; 95%, 0.29–0.95, and taking folic acid or multivitamins during first trimester (aOR, 0.47; 95%, 0.23–0.95 were protective of NTDs. However, annual cash family income less than $1,300 USD (aOR, 2.5; 95%, 1.2–5.5, $1,300–1,800 USD (aOR, 2.8; 95%, 1.3–5.8, and $1,801–2,700 USD (aOR, 2.6; 95%, 1.2–5.8 was found to be risk factors compared to income greater than $2,700 USD. The prevalence of NTDs was found to be high in this setting. Comprehensive preventive strategies focused on identified risk factors should be urgently established. More studies on prevention strategies, including folic acid supplementations, should be conducted in the setting.

  13. Magnitude of Neural Tube Defects and Associated Risk Factors at Three Teaching Hospitals in Addis Ababa, Ethiopia.

    Science.gov (United States)

    Gedefaw, Abel; Teklu, Sisay; Tadesse, Birkneh Tilahun

    2018-01-01

    There is scarcity of data on prevalence of neural tube defects (NTDs) in lower-income countries. Local data are important to understand the real burden of the problem and explore risk factors to design and implement preventive approaches. This study aimed to determine prevalence and risk factors of NTDs. A hospital-based cross-sectional and unmatched case-control study was conducted at three teaching hospitals of Addis Ababa University. NTDs were defined as cases of anencephaly, spina bifida, and encephalocele based on ICD-10 criteria. The prevalence of NTDs was calculated per 10,000 births for both birth and total prevalence. During seven months, we observed 55 cases of NTDs out of 8677 births after 28 weeks of gestation-birth prevalence of 63.4 per 10,000 births (95% confidence interval (CI), 51-77). A total of 115 cases were medically terminated after 12 weeks of gestation. Fifty-six of these terminations (48.7%) were due to NTDs. Thus, total prevalence of NTDs after 12 weeks' gestation is 126 per 10,000 births (95% CI, 100-150). Planned pregnancy (adjusted odds ratio (aOR), 0.47; 95% CI, 0.24-0.92), male sex (aOR, 0.56; 95% CI, 0.33-0.94), normal or underweight body mass index (aOR, 0.49; 95%, 0.29-0.95), and taking folic acid or multivitamins during first trimester (aOR, 0.47; 95%, 0.23-0.95) were protective of NTDs. However, annual cash family income less than $1,300 USD (aOR, 2.5; 95%, 1.2-5.5), $1,300-1,800 USD (aOR, 2.8; 95%, 1.3-5.8), and $1,801-2,700 USD (aOR, 2.6; 95%, 1.2-5.8) was found to be risk factors compared to income greater than $2,700 USD. The prevalence of NTDs was found to be high in this setting. Comprehensive preventive strategies focused on identified risk factors should be urgently established. More studies on prevention strategies, including folic acid supplementations, should be conducted in the setting.

  14. Associations between neural injury markers of intrauterine growth-restricted infants and neurodevelopment at 2 years of age.

    Science.gov (United States)

    Mazarico, E; Llurba, E; Cabero, L; Sánchez, O; Valls, A; Martín-Ancel, A; Cardenas, D; Gómez Roig, M D

    2018-04-18

    The aim of this study was to evaluate the relationships between brain injury biomarkers in intrauterine growth-restricted (IUGR) infants (S100B and neuron-specific enolase (NSE)) and neurodevelopment at 2 years of age. This prospective case-control study was a cooperative effort among Spanish Maternal and Child Health Network (Retic SAMID) hospitals. At inclusion, biometry for estimated fetal weight and feto-placental Doppler variables were measured for each infant. Maternal venous blood and fetal umbilical arterial blood samples were collected at the time of delivery and neural injury markers S100B and NSE concentrations were measured. Neurodevelopment was evaluated at 2 years of age using the Bayley Scales of Infant and Toddler Development, third edition (Bayley-III). Fifty six pregnancies were included. Thirty-one infants were classified as IUGR and 25 as non-IUGR. Neurodevelopmental evaluation at 2 years of age indicated that there were no between-group differences for any of the tests. For all patients in both groups, we found statistically significant inverse relationships between the concentrations of NSE in the cord blood and the results of the cognitive test (r = -271, p = .042), fine motor subtest (r = -280, p = .036), and social-emotional test (r = -349, p = .015). We also found statistically significant differences between the concentrations of S100B in the cord blood and the results of the cognitive test (r = -306, p = .022) and expressive communication subtest (r = -304, p = .023). For the IUGR group, we found a significant inverse relationship between the concentrations of S100B in the maternal serum and the results of adaptive behavior test (p < .05). In the non-IUGR group, we found statistically significant inverse relationships between the concentration of NSE in the cord blood and the results of the fine motor subtest (r = -446, p = .025) and social-emotional test (r = -489, p = .021

  15. Chondroitin sulfate effects on neural stem cell differentiation.

    Science.gov (United States)

    Canning, David R; Brelsford, Natalie R; Lovett, Neil W

    2016-01-01

    We have investigated the role chondroitin sulfate has on cell interactions during neural plate formation in the early chick embryo. Using tissue culture isolates from the prospective neural plate, we have measured neural gene expression profiles associated with neural stem cell differentiation. Removal of chondroitin sulfate from stage 4 neural plate tissue leads to altered associations of N-cadherin-positive neural progenitors and causes changes in the normal sequence of neural marker gene expression. Absence of chondroitin sulfate in the neural plate leads to reduced Sox2 expression and is accompanied by an increase in the expression of anterior markers of neural regionalization. Results obtained in this study suggest that the presence of chondroitin sulfate in the anterior chick embryo is instrumental in maintaining cells in the neural precursor state.

  16. Improved Exercise Tolerance with Caffeine Is Associated with Modulation of both Peripheral and Central Neural Processes in Human Participants

    Directory of Open Access Journals (Sweden)

    Joanna L. Bowtell

    2018-02-01

    Full Text Available BackgroundCaffeine has been shown to enhance exercise performance and capacity. The mechanisms remain unclear but are suggested to relate to adenosine receptor antagonism, resulting in increased central motor drive, reduced perception of effort, and altered peripheral processes such as enhanced calcium handling and extracellular potassium regulation. Our aims were to investigate how caffeine (i affects knee extensor PCr kinetics and pH during repeated sets of single-leg knee extensor exercise to task failure and (ii modulates the interplay between central and peripheral neural processes. We hypothesized that the caffeine-induced extension of exercise capacity during repeated sets of exercise would occur despite greater disturbance of the muscle milieu due to enhanced peripheral and corticospinal excitatory output, central motor drive, and muscle contractility.MethodsNine healthy active young men performed five sets of intense single-leg knee extensor exercise to task failure on four separate occasions: for two visits (6 mg·kg−1 caffeine vs placebo, quadriceps 31P-magnetic resonance spectroscopy scans were performed to quantify phosphocreatine kinetics and pH, and for the remaining two visits (6 mg·kg−1 caffeine vs placebo, femoral nerve electrical and transcranial magnetic stimulation of the quadriceps cortical motor area were applied pre- and post exercise.ResultsThe total exercise time was 17.9 ± 6.0% longer in the caffeine (1,225 ± 86 s than in the placebo trial (1,049 ± 73 s, p = 0.016, and muscle phosphocreatine concentration and pH (p < 0.05 were significantly lower in the latter sets of exercise after caffeine ingestion. Voluntary activation (VA (peripheral, p = 0.007; but not supraspinal, p = 0.074, motor-evoked potential (MEP amplitude (p = 0.007, and contractility (contraction time, p = 0.009; and relaxation rate, p = 0.003 were significantly higher after caffeine consumption, but at

  17. Neural Activity Associated with Visual Search for Line Drawings on AAC Displays: An Exploration of the Use of fMRI.

    Science.gov (United States)

    Wilkinson, Krista M; Dennis, Nancy A; Webb, Christina E; Therrien, Mari; Stradtman, Megan; Farmer, Jacquelyn; Leach, Raevynn; Warrenfeltz, Megan; Zeuner, Courtney

    2015-01-01

    Visual aided augmentative and alternative communication (AAC) consists of books or technologies that contain visual symbols to supplement spoken language. A common observation concerning some forms of aided AAC is that message preparation can be frustratingly slow. We explored the uses of fMRI to examine the neural correlates of visual search for line drawings on AAC displays in 18 college students under two experimental conditions. Under one condition, the location of the icons remained stable and participants were able to learn the spatial layout of the display. Under the other condition, constant shuffling of the locations of the icons prevented participants from learning the layout, impeding rapid search. Brain activation was contrasted under these conditions. Rapid search in the stable display was associated with greater activation of cortical and subcortical regions associated with memory, motor learning, and dorsal visual pathways compared to the search in the unpredictable display. Rapid search for line drawings on stable AAC displays involves not just the conceptual knowledge of the symbol meaning but also the integration of motor, memory, and visual-spatial knowledge about the display layout. Further research must study individuals who use AAC, as well as the functional effect of interventions that promote knowledge about array layout.

  18. Correction: Neural Correlates Associated with Successful Working Memory Performance in Older Adults as Revealed by Spatial ICA

    NARCIS (Netherlands)

    Saliasi, Emi; Geerligs, Linda; Lorist, Monicque M.; Maurits, Natasha M.

    2016-01-01

    There are errors in the fourth and fifth sentences of the Abstract. The correct sentences are: Our results indicated that a higher BOLD response in the VLPFC was associated with increased performance accuracy in older adults, in the more complex task condition. This ‘BOLD-performance’ relationship

  19. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  20. Introduction to neural networks

    International Nuclear Information System (INIS)

    Pavlopoulos, P.

    1996-01-01

    This lecture is a presentation of today's research in neural computation. Neural computation is inspired by knowledge from neuro-science. It draws its methods in large degree from statistical physics and its potential applications lie mainly in computer science and engineering. Neural networks models are algorithms for cognitive tasks, such as learning and optimization, which are based on concepts derived from research into the nature of the brain. The lecture first gives an historical presentation of neural networks development and interest in performing complex tasks. Then, an exhaustive overview of data management and networks computation methods is given: the supervised learning and the associative memory problem, the capacity of networks, the Perceptron networks, the functional link networks, the Madaline (Multiple Adalines) networks, the back-propagation networks, the reduced coulomb energy (RCE) networks, the unsupervised learning and the competitive learning and vector quantization. An example of application in high energy physics is given with the trigger systems and track recognition system (track parametrization, event selection and particle identification) developed for the CPLEAR experiment detectors from the LEAR at CERN. (J.S.). 56 refs., 20 figs., 1 tab., 1 appendix

  1. The Winding Road to Relapse: Forging a New Understanding of Cue-Induced Reinstatement Models and Their Associated Neural Mechanisms.

    Science.gov (United States)

    Namba, Mark D; Tomek, Seven E; Olive, M Foster; Beckmann, Joshua S; Gipson, Cassandra D

    2018-01-01

    In drug addiction, cues previously associated with drug use can produce craving and frequently trigger the resumption of drug taking in individuals vulnerable to relapse. Environmental stimuli associated with drugs or natural reinforcers can become reliably conditioned to increase behavior that was previously reinforced. In preclinical models of addiction, these cues enhance both drug self-administration and reinstatement of drug seeking. In this review, we will dissociate the roles of conditioned stimuli as reinforcers from their modulatory or discriminative functions in producing drug-seeking behavior. As well, we will examine possible differences in neurobiological encoding underlying these functional differences. Specifically, we will discuss how models of drug addiction and relapse should more systematically evaluate these different types of stimuli to better understand the neurobiology underlying craving and relapse. In this way, behavioral and pharmacotherapeutic interventions may be better tailored to promote drug use cessation outcomes and long-term abstinence.

  2. Distinct neural correlates of associative working memory and long-term memory encoding in the medial temporal lobe.

    Science.gov (United States)

    Bergmann, Heiko C; Rijpkema, Mark; Fernández, Guillén; Kessels, Roy P C

    2012-11-01

    Increasing evidence suggests a role for the hippocampus not only in long-term memory (LTM) but also in relational working memory (WM) processes, challenging the view of the hippocampus as being solely involved in episodic LTM. However, hippocampal involvement reported in some neuroimaging studies using "classical" WM tasks may at least partly reflect incidental LTM encoding. To disentangle WM processing and LTM formation we administered a delayed-match-to-sample associative WM task in an event-related fMRI study design. Each trial of the WM task consisted of four pairs of faces and houses, which had to be maintained during a delay of 10 s. This was followed by a probe phase consisting of three consecutively presented pairs; for each pair participants were to indicate whether it matched one of the pairs of the encoding phase. After scanning, an unexpected recognition-memory (LTM) task was administered. Brain activity during encoding was analyzed based on WM and LTM performance. Hence, encoding-related activity predicting WM success in the absence of successful LTM formation could be isolated. Furthermore, regions critical for successful LTM formation for pairs previously correctly processed in WM were analyzed. Results showed that the left parahippocampal gyrus including the fusiform gyrus predicted subsequent accuracy on WM decisions. The right anterior hippocampus and left inferior frontal gyrus, in contrast, predicted successful LTM for pairs that were previously correctly classified in the WM task. Our results suggest that brain regions associated with higher-level visuo-perceptual processing are involved in successful associative WM encoding, whereas the anterior hippocampus and left inferior frontal gyrus are involved in successful LTM formation during incidental encoding. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. Disease-associated prion protein in neural and lymphoid tissues of mink (Mustela vison) inoculated with transmissible mink encephalopathy.

    Science.gov (United States)

    Schneider, D A; Harrington, R D; Zhuang, D; Yan, H; Truscott, T C; Dassanayake, R P; O'Rourke, K I

    2012-11-01

    Transmissible spongiform encephalopathies (TSEs) are diagnosed by immunodetection of disease-associated prion protein (PrP(d)). The distribution of PrP(d) within the body varies with the time-course of infection and between species, during interspecies transmission, as well as with prion strain. Mink are susceptible to a form of TSE known as transmissible mink encephalopathy (TME), presumed to arise due to consumption of feed contaminated with a single prion strain of ruminant origin. After extended passage of TME isolates in hamsters, two strains emerge, HY and DY, each of which is associated with unique structural isoforms of PrP(TME) and of which only the HY strain is associated with accumulation of PrP(TME) in lymphoid tissues. Information on the structural nature and lymphoid accumulation of PrP(TME) in mink is limited. In this study, 13 mink were challenged by intracerebral inoculation using late passage TME inoculum, after which brain and lymphoid tissues were collected at preclinical and clinical time points. The distribution and molecular nature of PrP(TME) was investigated by techniques including blotting of paraffin wax-embedded tissue and epitope mapping by western blotting. PrP(TME) was detected readily in the brain and retropharyngeal lymph node during preclinical infection, with delayed progression of accumulation within other lymphoid tissues. For comparison, three mink were inoculated by the oral route and examined during clinical disease. Accumulation of PrP(TME) in these mink was greater and more widespread, including follicles of rectoanal mucosa-associated lymphoid tissue. Western blot analyses revealed that PrP(TME) accumulating in the brain of mink is structurally most similar to that accumulating in the brain of hamsters infected with the DY strain. Collectively, the results of extended passage in mink are consistent with the presence of only a single strain of TME, the DY strain, capable of inducing accumulation of PrP(TME) in the lymphoid

  4. Plasma folate levels and associated factors in women planning to become pregnant in a population with high prevalence of neural tube defects.

    Science.gov (United States)

    Ma, Rui; Wang, Linlin; Jin, Lei; Li, Zhiwen; Ren, Aiguo

    2017-07-17

    Optimal blood folate levels of women before pregnancy are critical to the prevention of neural tube defects (NTDs). However, few studies have focused on blood folate levels of women planning to become pregnant. The aims of this study were to assess plasma folate levels in women who planned to become pregnant in a population with high prevalence of NTDs, to identify factors associated with plasma folate levels, and to evaluate the risk of NTDs at the population level. A total of 2065 women were enrolled at the time of premarital health check-up in two rural counties in northern China from November 2009 to December 2012. Fasting venous blood samples were collected and plasma folate concentrations were measured by microbiological method. The overall median of plasma folate was 10.5 nmol/L. 50% of the women had a plasma folate level below 10.5 nmol/L, a cutoff for megaloblastic anemia, and 88% below 18 nmol/L, a proposed optimal plasma folate level for the prevention of NTDs. Folic acid supplementation was the only factor to be associated with plasma folate concentrations, but only 1.9% of the women reported having taken folic acid supplements. A population risk of 29.3 NTD cases per 10,000 births was predicted. Women who planned to become pregnant had very low plasma folate in the population. Folic acid supplementation was the only factor to be associated with a high plasma folate concentration. High NTD risk would remain if women would get pregnant without having taken folic acid supplements. Birth Defects Research 109:1039-1047, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  5. Status epilepticus after prolonged umbilical cord occlusion is associated with greater neural injury in [corrected] fetal sheep at term-equivalent.

    Directory of Open Access Journals (Sweden)

    Paul P Drury

    Full Text Available The majority of pre-clinical studies of hypoxic-ischemic encephalopathy at term-equivalent have focused on either relatively mild insults, or on functional paradigms of cerebral ischemia or hypoxia-ischemia/hypotension. There is surprisingly little information on the responses to single, severe 'physiological' insults. In this study we examined the evolution and pattern of neural injury after prolonged umbilical cord occlusion (UCO. 36 chronically instrumented fetal sheep at 125-129 days gestational age (term = 147 days were subjected to either UCO until mean arterial pressure was < = 8 mmHg (n = 29, or sham occlusion (n = 7. Surviving fetuses were killed after 72 hours for histopathologic assessment with acid-fuchsin thionine. After UCO, 11 fetuses died with intractable hypotension and 5 ewes entered labor and were euthanized. The remaining 13 fetuses showed marked EEG suppression followed by evolving seizures starting at 5.8 (6.8 hours (median (interquartile range. 6 of 13 developed status epilepticus, which was associated with a transient secondary increase in cortical impedance (a measure of cytotoxic edema, p<0.05. All fetuses showed moderate to severe neuronal loss in the hippocampus and the basal ganglia but mild cortical cell loss (p<0.05 vs sham occlusion. Status epilepticus was associated with more severe terminal hypotension (p<0.05 and subsequently, greater neuronal loss (p<0.05. In conclusion, profound UCO in term-equivalent fetal sheep was associated with delayed seizures, secondary cytotoxic edema, and subcortical injury, consistent with the predominant pattern after peripartum sentinel events at term. It is unclear whether status epilepticus exacerbated cortical injury or was simply a reflection of a longer duration of asphyxia.

  6. The AutoAssociative Neural Network in signal analysis: II. Application to on-line monitoring of a simulated BWR component

    International Nuclear Information System (INIS)

    Marseguerra, M.; Zoia, A.

    2005-01-01

    In this paper, Robust AutoAssociative Neural Networks (RAANN) are applied to a series of signals produced by the Halden simulator of the 1200MWe BWR Forsmark-3 plant in Sweden. The applications concern: - correction of drifts and gross errors in sensors, for diagnostic and control purposes, - cluster analysis, to individuate a failed component and the intensity of the failure, - forecasting system signals, for safety or economic purposes, - reconstruction of unmeasured signals (virtual sensors). In the attainment of the above results, the geometric interpretation of the mapping performed by the network, propounded in Part I of this work, has provided a reasoned choice of the most critical free parameter, i.e., the number f of nodes of the bottleneck layer, thus allowing a deep understanding of the network functioning and also avoiding the traditional and troubling procedure of selection by trial-and-error. The theoretical basis of this analysis, discussed in details in the companion paper, is founded on the idea of dimension and in particular of fractal dimension, which has been used as a numerical estimator of f

  7. Neural plasticity of development and learning.

    Science.gov (United States)

    Galván, Adriana

    2010-06-01

    Development and learning are powerful agents of change across the lifespan that induce robust structural and functional plasticity in neural systems. An unresolved question in developmental cognitive neuroscience is whether development and learning share the same neural mechanisms associated with experience-related neural plasticity. In this article, I outline the conceptual and practical challenges of this question, review insights gleaned from adult studies, and describe recent strides toward examining this topic across development using neuroimaging methods. I suggest that development and learning are not two completely separate constructs and instead, that they exist on a continuum. While progressive and regressive changes are central to both, the behavioral consequences associated with these changes are closely tied to the existing neural architecture of maturity of the system. Eventually, a deeper, more mechanistic understanding of neural plasticity will shed light on behavioral changes across development and, more broadly, about the underlying neural basis of cognition. (c) 2010 Wiley-Liss, Inc.

  8. Changes in expression of the long noncoding RNA FMR4 associate with altered gene expression during differentiation of human neural precursor cells

    Directory of Open Access Journals (Sweden)

    Veronica Julia Peschansky

    2015-08-01

    Full Text Available CGG repeat expansions in the Fragile X mental retardation 1 (FMR1 gene are responsible for a family of associated disorders characterized by either intellectual disability and autism (Fragile X Syndrome, FXS, or adult-onset neurodegeneration (Fragile X-associated Tremor/Ataxia Syndrome, FXTAS. However, the FMR1 locus is complex and encodes several long noncoding RNAs (lncRNAs, whose expression is altered by repeat expansion mutations.The role of these lncRNAs is thus far unknown; therefore we investigated the functionality of FMR4, which we previously identified. Full-length expansions of the FMR1 triplet repeat cause silencing of both FMR1 and FMR4, thus we are interested in potential loss-of-function that may add to phenotypic manifestation of FXS. Since the two transcripts do not exhibit cis-regulation of one another, we examined the potential for FMR4 to regulate target genes at distal genomic loci using gene expression microarrays. We identified FMR4-responsive genes, including the methyl-CpG-binding domain protein 4 (MBD4. Furthermore, we found that in differentiating human neural precursor cells (hNPCs, FMR4 expression is developmentally regulated in opposition to expression of both FMR1 (which is expected to share a bidirectional promoter with FMR4 and MBD4.We therefore propose that FMR4’s function is as a gene-regulatory lncRNA and that this transcript may function in normal development. Closer examination of FMR4 increases our understanding of the role of regulatory lncRNA and the consequences of FMR1 repeat expansions.

  9. "I Know that You Know that I Know": Neural Substrates Associated with Social Cognition Deficits in DM1 Patients.

    Directory of Open Access Journals (Sweden)

    Laura Serra

    Full Text Available Myotonic dystrophy type-1 (DM1 is a genetic multi-systemic disorder involving several organs including the brain. Despite the heterogeneity of this condition, some patients with non-congenital DM1 can present with minimal cognitive impairment on formal testing but with severe difficulties in daily-living activities including social interactions. One explanation for this paradoxical mismatch can be found in patients' dysfunctional social cognition, which can be assessed in the framework of the Theory of Mind (ToM. We hypothesize here that specific disease driven abnormalities in DM1 brains may result in ToM impairments. We recruited 20 DM1 patients who underwent the "Reading the Mind in the Eyes" and the ToM-story tests. These patients, together with 18 healthy controls, also underwent resting-state functional MRI. A composite Theory of Mind score was computed for all recruited patients and correlated with their brain functional connectivity. This analysis provided the patients' "Theory of Mind-network", which was compared, for its topological properties, with that of healthy controls. We found that DM1 patients showed deficits in both tests assessing ToM. These deficits were associated with specific patterns of abnormal connectivity between the left inferior temporal and fronto-cerebellar nodes in DM1 brains. The results confirm the previous suggestions of ToM dysfunctions in patients with DM1 and support the hypothesis that difficulties in social interactions and personal relationships are a direct consequence of brain abnormalities, and not a reaction symptom. This is relevant not only for a better pathophysiological comprehension of DM1, but also for non-pharmacological interventions to improve clinical aspects and impact on patients' success in life.

  10. Low concentrations of methylmercury inhibit neural progenitor cell proliferation associated with up-regulation of glycogen synthase kinase 3β and subsequent degradation of cyclin E in rats

    Energy Technology Data Exchange (ETDEWEB)

    Fujimura, Masatake, E-mail: fujimura@nimd.go.jp [Department of Basic Medical Science, National Institute for Minamata Disease, Kumamoto (Japan); Usuki, Fusako [Department of Clinical Medicine, National Institute for Minamata Disease, Kumamoto (Japan)

    2015-10-01

    Methylmercury (MeHg) is an environmental neurotoxicant. The developing nervous system is susceptible to low concentrations of MeHg; however, the effect of MeHg on neural progenitor cell (NPC) proliferation, a key stage of neurogenesis during development, remains to be clarified. In this study, we investigated the effect of low concentrations of MeHg on NPCs by using a primary culture system developed using the embryonic rat cerebral cortex. NPC proliferation was suppressed 48 h after exposure to 10 nM MeHg, but cell death was not observed. Western blot analyses for cyclins A, B, D1, and E demonstrated that MeHg down-regulated cyclin E, a promoter of the G1/S cell cycle transition. Cyclin E has been shown to be degraded following the phosphorylation by glycogen synthase kinase 3β (GSK-3β). The time course study showed that GSK-3β was up-regulated 3 h after exposure to 10 nM MeHg, and cyclin E degradation 48 h after MeHg exposure. We further demonstrated that GSK-3β inhibitors, lithium and SB-415286, suppressed MeHg-induced inhibition of NPC proliferation by preventing cyclin E degradation. These results suggest that the inhibition of NPC proliferation induced by low concentration of MeHg was associated with up-regulation of GSK-3β at the early stage and subsequent degeneration of cyclin E. - Highlights: • NPC proliferation was suppressed by 10 nM MeHg, but cell death was not observed. • MeHg induced down-regulation of cyclin E, a promoter of cell cycle progression. • GSK-3β was up-regulated by 10 nM MeHg, leading to cyclin E degradation. • GSK-3β inhibitors suppressed MeHg-induced degradation of cyclin E.

  11. Kidins220/ARMS depletion is associated with the neural-to Schwann-like transition in a human neuroblastoma cell line model.

    Science.gov (United States)

    Rogers, Danny A; Schor, Nina F

    2013-03-10

    Peripheral neuroblastic tumors exist as a heterogeneous mixture of neuroblastic (N-type) cells and Schwannian stromal (S-type) cells. These stromal cells not only represent a differentiated and less aggressive fraction of the tumor, but also have properties that can influence the further differentiation of nearby malignant cells. In vitro neuroblastoma cultures exhibit similar heterogeneity with N-type and S-type cells representing the neuroblastic and stromal portions of the tumor, respectively, in behavior, morphology, and molecular expression patterns. In this study, we deplete kinase D-interacting substrate of 220kD (Kidins220) with an shRNA construct and thereby cause morphologic transition of the human SH-SY5Y neuroblastoma cell line from N-type to S-type. The resulting cells have similar morphology and expression profile to SH-EP1 cells, a native S-type cell line from the same parent cell line, and to SH-SY5Y cells treated with BrdU, a treatment that induces S-type morphology. Specifically, both Kidins220-deficient SH-SY5Y cells and native SH-EP1 cells demonstrate down-regulation of the genes DCX and STMN2, markers for the neuronal lineage. We further show that Kidins220, DCX and STMN2 are co-down-regulated in cells of S-type morphology generated by methods other than Kidins220 depletion. Finally, we report that the association of low Kidins220 expression with S-type morphology and low DCX and STMN2 expression is demonstrated in spontaneously occurring human peripheral neuroblastic tumors. We propose that Kidins220 is critical in N- to S-type transition of neural crest tumor cells. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Boolean Factor Analysis by Attractor Neural Network

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

    2007-01-01

    Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

  13. ADM1-based modeling of methane production from acidified sweet sorghum extractin a two stage process

    DEFF Research Database (Denmark)

    Antonopoulou, Georgia; Gavala, Hariklia N.; Skiadas, Ioannis

    2012-01-01

    estimated through fitting of the model equations to the data obtained from batch experiments. The simulation of the continuous reactor performance at all HRTs tested (20, 15 and 10d) was very satisfactory. Specifically, the largest deviation of the theoretical predictions against the experimental data...... was 12% for the methane production rate at the HRT of 20d while the deviation values for the 15 and 10 d HRT were 1.9% and 1.1%, respectively. The model predictions regarding pH, methane percentage in the gas phase and COD removal were in very good agreement with the experimental data with a deviation...

  14. The DNA glycosylases OGG1 and NEIL3 influence differentiation potential, proliferation, and senescence-associated signs in neural stem cells

    International Nuclear Information System (INIS)

    Reis, Amilcar; Hermanson, Ola

    2012-01-01

    Highlights: ► DNA glycosylases OGG1 and NEIL3 are required for neural stem cell state. ► No effect on cell viability by OGG1 or NEIL3 knockdown in neural stem cells. ► OGG1 or NEIL3 RNA knockdown result in decreased proliferation and differentiation. ► Increased HP1γ immunoreactivity after NEIL3 knockdown suggests premature senescence. -- Abstract: Embryonic neural stem cells (NSCs) exhibit self-renewal and multipotency as intrinsic characteristics that are key parameters for proper brain development. When cells are challenged by oxidative stress agents the resulting DNA lesions are repaired by DNA glycosylases through the base excision repair (BER) pathway as a means to maintain the fidelity of the genome, and thus, proper cellular characteristics. The functional roles for DNA glycosylases in NSCs have however remained largely unexplored. Here we demonstrate that RNA knockdown of the DNA glycosylases OGG1 and NEIL3 decreased NSC differentiation ability and resulted in decreased expression of both neuronal and astrocytic genes after mitogen withdrawal, as well as the stem cell marker Musashi-1. Furthermore, while cell survival remained unaffected, NEIL3 deficient cells displayed decreased cell proliferation rates along with an increase in HP1γ immunoreactivity, a sign of premature senescence. Our results suggest that DNA glycosylases play multiple roles in governing essential neural stem cell characteristics.

  15. The DNA glycosylases OGG1 and NEIL3 influence differentiation potential, proliferation, and senescence-associated signs in neural stem cells

    Energy Technology Data Exchange (ETDEWEB)

    Reis, Amilcar [Linnaeus Center in Developmental Biology for Regenerative Medicine (DBRM), Department of Neuroscience, Karolinska Institutet, SE 17177 Stockholm (Sweden); Hermanson, Ola, E-mail: ola.hermanson@ki.se [Linnaeus Center in Developmental Biology for Regenerative Medicine (DBRM), Department of Neuroscience, Karolinska Institutet, SE 17177 Stockholm (Sweden)

    2012-07-13

    Highlights: Black-Right-Pointing-Pointer DNA glycosylases OGG1 and NEIL3 are required for neural stem cell state. Black-Right-Pointing-Pointer No effect on cell viability by OGG1 or NEIL3 knockdown in neural stem cells. Black-Right-Pointing-Pointer OGG1 or NEIL3 RNA knockdown result in decreased proliferation and differentiation. Black-Right-Pointing-Pointer Increased HP1{gamma} immunoreactivity after NEIL3 knockdown suggests premature senescence. -- Abstract: Embryonic neural stem cells (NSCs) exhibit self-renewal and multipotency as intrinsic characteristics that are key parameters for proper brain development. When cells are challenged by oxidative stress agents the resulting DNA lesions are repaired by DNA glycosylases through the base excision repair (BER) pathway as a means to maintain the fidelity of the genome, and thus, proper cellular characteristics. The functional roles for DNA glycosylases in NSCs have however remained largely unexplored. Here we demonstrate that RNA knockdown of the DNA glycosylases OGG1 and NEIL3 decreased NSC differentiation ability and resulted in decreased expression of both neuronal and astrocytic genes after mitogen withdrawal, as well as the stem cell marker Musashi-1. Furthermore, while cell survival remained unaffected, NEIL3 deficient cells displayed decreased cell proliferation rates along with an increase in HP1{gamma} immunoreactivity, a sign of premature senescence. Our results suggest that DNA glycosylases play multiple roles in governing essential neural stem cell characteristics.

  16. Spin glasses and neural networks

    International Nuclear Information System (INIS)

    Parga, N.; Universidad Nacional de Cuyo, San Carlos de Bariloche

    1989-01-01

    The mean-field theory of spin glass models has been used as a prototype of systems with frustration and disorder. One of the most interesting related systems are models of associative memories. In these lectures we review the main concepts developed to solve the Sherrington-Kirkpatrick model and its application to neural networks. (orig.)

  17. Neural networks and statistical learning

    CERN Document Server

    Du, Ke-Lin

    2014-01-01

    Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...

  18. Experimental Demonstrations of Optical Neural Computers

    OpenAIRE

    Hsu, Ken; Brady, David; Psaltis, Demetri

    1988-01-01

    We describe two experiments in optical neural computing. In the first a closed optical feedback loop is used to implement auto-associative image recall. In the second a perceptron-like learning algorithm is implemented with photorefractive holography.

  19. 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.

  20. 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 ...

  1. 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...

  2. Spontaneous neural activity in the right superior temporal gyrus and left middle temporal gyrus is associated with insight level in obsessive-compulsive disorder.

    Science.gov (United States)

    Fan, Jie; Zhong, Mingtian; Gan, Jun; Liu, Wanting; Niu, Chaoyang; Liao, Haiyan; Zhang, Hongchun; Tan, Changlian; Yi, Jinyao; Zhu, Xiongzhao

    2017-01-01

    Insight into illness is an important issue for psychiatry disorder. Although the existence of a poor insight subtype of obsessive-compulsive disorder (OCD) was recognized in the DSM-IV, and the insight level in OCD was specified further in DSM-V, the neural underpinnings of insight in OCD have been rarely explored. The present study was designed to bridge this research gap by using resting-state functional magnetic resonance imaging (fMRI). Spontaneous neural activity were examined in 19 OCD patients with good insight (OCD-GI), 18 OCD patients with poor insight (OCD-PI), and 25 healthy controls (HC) by analyzing the amplitude of low-frequency fluctuation (ALFF) in the resting state. Pearson correlation analysis was performed between regional ALFFs and insight levels among OCD patients. OCD-GI and OCD-PI demonstrated overlapping and distinct brain alterations. Notably, compared with OCD-GI, tOCD-PI had reduced ALFF in left middle temporal gyrus (MTG) and right superior temporal gyrus (STG), as well as increased ALFF in right middle occipital gyrus. Further analysis revealed that ALFF values for the left MTG and right STG were correlated negatively with insight level in patients with OCD. Relatively small sample size and not all patients were un-medicated are our major limitations. Spontaneous brain activity in left MTG and right STG may be neural underpinnings of insight in OCD. Our results suggest the great role of human temporal brain regions in understanding insight, and further underscore the importance of considering insight presentation in understanding the clinical heterogeneity of OCD. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. 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.

  4. Nonequilibrium landscape theory of neural networks.

    Science.gov (United States)

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-11-05

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

  5. Nonequilibrium landscape theory of neural networks

    Science.gov (United States)

    Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

    2013-01-01

    The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

  6. Neural Darwinism and consciousness.

    Science.gov (United States)

    Seth, Anil K; Baars, Bernard J

    2005-03-01

    Neural Darwinism (ND) is a large scale selectionist theory of brain development and function that has been hypothesized to relate to consciousness. According to ND, consciousness is entailed by reentrant interactions among neuronal populations in the thalamocortical system (the 'dynamic core'). These interactions, which permit high-order discriminations among possible core states, confer selective advantages on organisms possessing them by linking current perceptual events to a past history of value-dependent learning. Here, we assess the consistency of ND with 16 widely recognized properties of consciousness, both physiological (for example, consciousness is associated with widespread, relatively fast, low amplitude interactions in the thalamocortical system), and phenomenal (for example, consciousness involves the existence of a private flow of events available only to the experiencing subject). While no theory accounts fully for all of these properties at present, we find that ND and its recent extensions fare well.

  7. 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)

  8. Neural activation in stress-related exhaustion

    DEFF Research Database (Denmark)

    Gavelin, Hanna Malmberg; Neely, Anna Stigsdotter; Andersson, Micael

    2017-01-01

    The primary purpose of this study was to investigate the association between burnout and neural activation during working memory processing in patients with stress-related exhaustion. Additionally, we investigated the neural effects of cognitive training as part of stress rehabilitation. Fifty...... association between burnout level and working memory performance was found, however, our findings indicate that frontostriatal neural responses related to working memory were modulated by burnout severity. We suggest that patients with high levels of burnout need to recruit additional cognitive resources...... to uphold task performance. Following cognitive training, increased neural activation was observed during 3-back in working memory-related regions, including the striatum, however, low sample size limits any firm conclusions....

  9. Serotonin, neural markers and memory

    Directory of Open Access Journals (Sweden)

    Alfredo eMeneses

    2015-07-01

    Full Text Available Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The interactions among behavioral tasks, control groups and molecular changes and/or pharmacological effects are mentioned. Neurotransmitter receptors and signaling pathways, during normal and abnormally functioning memory with an emphasis on the behavioral aspects of memory are revised. With focus on serotonin, since as it is a well characterized neurotransmitter, with multiple pharmacological tools, and well characterized downstream signaling in mammals’ species. 5-HT1A, 5-HT4, 5-HT5, 5-HT6 and 5-HT7 receptors as well as SERT (serotonin transporter seem to be useful neural markers and/or therapeutic targets. Certainly, if the mentioned evidence is replicated, then the translatability from preclinical and clinical studies to neural changes might be confirmed. Hypothesis and theories might provide appropriate limits and perspectives of evidence

  10. 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.

  11. Neural networks, D0, and the SSC

    International Nuclear Information System (INIS)

    Barter, C.; Cutts, D.; Hoftun, J.S.; Partridge, R.A.; Sornborger, A.T.; Johnson, C.T.; Zeller, R.T.

    1989-01-01

    We outline several exploratory studies involving neural network simulations applied to pattern recognition in high energy physics. We describe the D0 data acquisition system and a natual means by which algorithms derived from neural networks techniques may be incorporated into recently developed hardware associated with the D0 MicroVAX farm nodes. Such applications to the event filtering needed by SSC detectors look interesting. 10 refs., 11 figs

  12. Neural codes of seeing architectural styles

    OpenAIRE

    Choo, Heeyoung; Nasar, Jack L.; Nikrahei, Bardia; Walther, Dirk B.

    2017-01-01

    Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people′s visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding sugges...

  13. Transfer Effects to a Multimodal Dual-Task after Working Memory Training and Associated Neural Correlates in Older Adults - A Pilot Study.

    Science.gov (United States)

    Heinzel, Stephan; Rimpel, Jérôme; Stelzel, Christine; Rapp, Michael A

    2017-01-01

    Working memory (WM) performance declines with age. However, several studies have shown that WM training may lead to performance increases not only in the trained task, but also in untrained cognitive transfer tasks. It has been suggested that transfer effects occur if training task and transfer task share specific processing components that are supposedly processed in the same brain areas. In the current study, we investigated whether single-task WM training and training-related alterations in neural activity might support performance in a dual-task setting, thus assessing transfer effects to higher-order control processes in the context of dual-task coordination. A sample of older adults (age 60-72) was assigned to either a training or control group. The training group participated in 12 sessions of an adaptive n-back training. At pre and post-measurement, a multimodal dual-task was performed in all participants to assess transfer effects. This task consisted of two simultaneous delayed match to sample WM tasks using two different stimulus modalities (visual and auditory) that were performed either in isolation (single-task) or in conjunction (dual-task). A subgroup also participated in functional magnetic resonance imaging (fMRI) during the performance of the n-back task before and after training. While no transfer to single-task performance was found, dual-task costs in both the visual modality ( p task costs, while neural activity changes in right DLPFC during three-back predicted visual dual-task costs. Results might indicate an improvement in central executive processing that could facilitate both WM and dual-task coordination.

  14. Envisaging the Regulation of Alkaloid Biosynthesis and Associated Growth Kinetics in Hairy Roots of Vinca minor Through the Function of Artificial Neural Network.

    Science.gov (United States)

    Verma, Priyanka; Anjum, Shahin; Khan, Shamshad Ahmad; Roy, Sudeep; Odstrcilik, Jan; Mathur, Ajay Kumar

    2016-03-01

    Artificial neural network based modeling is a generic approach to understand and correlate different complex parameters of biological systems for improving the desired output. In addition, some new inferences can also be predicted in a shorter time with less cost and labor. As terpenoid indole alkaloid pathway in Vinca minor is very less investigated or elucidated, a strategy of elicitation with hydroxylase and acetyltransferase along with incorporation of various precursors from primary shikimate and secoiridoid pools via simultaneous employment of cyclooxygenase inhibitor was performed in the hairy roots of V. minor. This led to the increment in biomass accumulation, total alkaloid concentration, and vincamine production in selected treatments. The resultant experimental values were correlated with algorithm approaches of artificial neural network that assisted in finding the yield of vincamine, alkaloids, and growth kinetics using number of elicits. The inputs were the hydroxylase/acetyltransferase elicitors and cyclooxygenase inhibitor along with various precursors from shikimate and secoiridoid pools and the outputs were growth index (GI), alkaloids, and vincamine. The approach incorporates two MATLAB codes; GRNN and FFBPNN. Growth kinetic studies revealed that shikimate and tryptophan supplementation triggers biomass accumulation (GI = 440.2 to 540.5); while maximum alkaloid (3.7 % dry wt.) and vincamine production (0.017 ± 0.001 % dry wt.) was obtained on supplementation of secologanin along with tryptophan, naproxen, hydrogen peroxide, and acetic anhydride. The study shows that experimental and predicted values strongly correlate each other. The correlation coefficient for growth index (GI), alkaloids, and vincamine was found to be 0.9997, 0.9980, 0.9511 in GRNN and 0.9725, 0.9444, 0.9422 in FFBPNN, respectively. GRNN provided greater similarity between the target and predicted dataset in comparison to FFBPNN. The findings can provide future

  15. Higher serum cholesterol is associated with intensified age-related neural network decoupling and cognitive decline in early- to mid-life.

    Science.gov (United States)

    Spielberg, Jeffrey M; Sadeh, Naomi; Leritz, Elizabeth C; McGlinchey, Regina E; Milberg, William P; Hayes, Jasmeet P; Salat, David H

    2017-06-01

    Mounting evidence indicates that serum cholesterol and other risk factors for cardiovascular disease intensify normative trajectories of age-related cognitive decline. However, the neural mechanisms by which this occurs remain largely unknown. To understand the impact of cholesterol on brain networks, we applied graph theory to resting-state fMRI in a large sample of early- to mid-life Veterans (N = 206, Mean age  = 32). A network emerged (centered on the banks of the superior temporal sulcus) that evidenced age-related decoupling (i.e., decreased network connectivity with age), but only in participants with clinically-elevated total cholesterol (≥180 mg/dL). Crucially, decoupling in this network corresponded to greater day-to-day disability and mediated age-related declines in psychomotor speed. Finally, examination of network organization revealed a pattern of age-related dedifferentiation for the banks of the superior temporal sulcus, again present only with higher cholesterol. More specifically, age was related to decreasing within-module communication (indexed by Within-Module Degree Z-Score) and increasing between-module communication (indexed by Participation Coefficient), but only in participants with clinically-elevated cholesterol. Follow-up analyses indicated that all findings were driven by low-density lipoprotein (LDL) levels, rather than high-density lipoprotein (HDL) or triglycerides, which is interesting as LDL levels have been linked to increased risk for cardiovascular disease, whereas HDL levels appear inversely related to such disease. These findings provide novel insight into the deleterious effects of cholesterol on brain health and suggest that cholesterol accelerates the impact of age on neural trajectories by disrupting connectivity in circuits implicated in integrative processes and behavioral control. Hum Brain Mapp 38:3249-3261, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  16. Neural networks and applications tutorial

    Science.gov (United States)

    Guyon, I.

    1991-09-01

    The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

  17. A neural flow estimator

    DEFF Research Database (Denmark)

    Jørgensen, Ivan Harald Holger; Bogason, Gudmundur; Bruun, Erik

    1995-01-01

    This paper proposes a new way to estimate the flow in a micromechanical flow channel. A neural network is used to estimate the delay of random temperature fluctuations induced in a fluid. The design and implementation of a hardware efficient neural flow estimator is described. The system...... is implemented using switched-current technique and is capable of estimating flow in the μl/s range. The neural estimator is built around a multiplierless neural network, containing 96 synaptic weights which are updated using the LMS1-algorithm. An experimental chip has been designed that operates at 5 V...

  18. Neural Systems Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — As part of the Electrical and Computer Engineering Department and The Institute for System Research, the Neural Systems Laboratory studies the functionality of the...

  19. Deciphering Neural Codes of Memory during Sleep

    Science.gov (United States)

    Chen, Zhe; Wilson, Matthew A.

    2017-01-01

    Memories of experiences are stored in the cerebral cortex. Sleep is critical for consolidating hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms on memory consolidation, and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here, we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches for analyzing sleep-associated neural codes (SANC). We focus on two analysis paradigms for sleep-associated memory, and propose a new unsupervised learning framework (“memory first, meaning later”) for unbiased assessment of SANC. PMID:28390699

  20. Neural Networks: Implementations and Applications

    OpenAIRE

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  1. Optical resonators and neural networks

    Science.gov (United States)

    Anderson, Dana Z.

    1986-08-01

    It may be possible to implement neural network models using continuous field optical architectures. These devices offer the inherent parallelism of propagating waves and an information density in principle dictated by the wavelength of light and the quality of the bulk optical elements. Few components are needed to construct a relatively large equivalent network. Various associative memories based on optical resonators have been demonstrated in the literature, a ring resonator design is discussed in detail here. Information is stored in a holographic medium and recalled through a competitive processes in the gain medium supplying energy to the ring rsonator. The resonator memory is the first realized example of a neural network function implemented with this kind of architecture.

  2. Association of neural tube defects in children of mothers with MTHFR 677TT genotype and abnormal carbohydrate metabolism risk: a case-control study.

    Science.gov (United States)

    Cadenas-Benitez, N M; Yanes-Sosa, F; Gonzalez-Meneses, A; Cerrillos, L; Acosta, D; Praena-Fernandez, J M; Neth, O; Gomez de Terreros, I; Ybot-González, P

    2014-03-26

    Abnormalities in maternal folate and carbohydrate metabolism have both been shown to induce neural tube defects (NTD) in humans and animal models. However, the relationship between these two factors in the development of NTDs remains unclear. Data from mothers of children with spina bifida seen at the Unidad de Espina Bífida del Hospital Infantil Virgen del Rocío (case group) were compared to mothers of healthy children with no NTD (control group) who were randomly selected from patients seen at the outpatient ward in the same hospital. There were 25 individuals in the case group and 41 in the control group. Analysis of genotypes for the methylenetetrahydrofolate reductase (MTHFR) 677CT polymorphism in women with or without risk factors for abnormal carbohydrate metabolism revealed that mothers who were homozygous for the MTHFR 677TT polymorphism and at risk of abnormal carbohydrate metabolism were more likely to have offspring with spina bifida and high levels of homocysteine, compared to the control group. The increased incidence of NTDs in mothers homozygous for the MTHFR 677TT polymorphism and at risk of abnormal carbohydrate metabolism stresses the need for careful metabolic screening in pregnant women, and, if necessary, determination of the MTHFR 677CT genotype in those mothers at risk of developing abnormal carbohydrate metabolism.

  3. Critical Branching Neural Networks

    Science.gov (United States)

    Kello, Christopher T.

    2013-01-01

    It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

  4. Consciousness and neural plasticity

    DEFF Research Database (Denmark)

    changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is...

  5. Stress-altered synaptic plasticity and DAMP signaling in the hippocampus-PFC axis; elucidating the significance of IGF-1/IGF-1R/CaMKIIα expression in neural changes associated with a prolonged exposure therapy.

    Science.gov (United States)

    Ogundele, Olalekan M; Ebenezer, Philip J; Lee, Charles C; Francis, Joseph

    2017-06-14

    Traumatic stress patients showed significant improvement in behavior after a prolonged exposure to an unrelated stimulus. This treatment method attempts to promote extinction of the fear memory associated with the initial traumatic experience. However, the subsequent prolonged exposure to such stimulus creates an additional layer of neural stress. Although the mechanism remains unclear, prolonged exposure therapy (PET) likely involves changes in synaptic plasticity, neurotransmitter function and inflammation; especially in parts of the brain concerned with the formation and retrieval of fear memory (Hippocampus and Prefrontal Cortex: PFC). Since certain synaptic proteins are also involved in danger-associated molecular pattern signaling (DAMP), we identified the significance of IGF-1/IGF-1R/CaMKIIα expression as a potential link between the concurrent progression of synaptic and inflammatory changes in stress. Thus, a comparison between IGF-1/IGF-1R/CaMKIIα, synaptic and DAMP proteins in stress and PET may highlight the significance of PET on synaptic morphology and neuronal inflammatory response. In behaviorally characterized Sprague-Dawley rats, there was a significant decline in neural IGF-1 (pIGF-1R expression. These animals showed a significant loss of presynaptic markers (synaptophysin; pIGF-1 (pIGF-1R was recorded in the Stress-PET group (pIGF-1/IGF-1R, an increase in activated hippocampal and cortical microglia was seen in stress (pIGF1/IGF-1R/CaMKIIα. Firstly, we showed a direct relationship between IGF-1/IGF-1R expression, presynaptic function (synaptophysin) and neurotransmitter activity in stress and PET. Secondly, we identified the possible role of CaMKIIα in post-synaptic function and regulation of small ion conductance channels. Lastly, we highlighted some of the possible links between IGF1/IGF-1R/CaMKIIα, the expression of DAMP proteins, Microglia activation, and its implication on synaptic plasticity during stress and PET. Copyright © 2017

  6. Dynamics of neural cryptography.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  7. Dynamics of neural cryptography

    International Nuclear Information System (INIS)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-01-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible

  8. Dynamics of neural cryptography

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Kanter, Ido

    2007-05-01

    Synchronization of neural networks has been used for public channel protocols in cryptography. In the case of tree parity machines the dynamics of both bidirectional synchronization and unidirectional learning is driven by attractive and repulsive stochastic forces. Thus it can be described well by a random walk model for the overlap between participating neural networks. For that purpose transition probabilities and scaling laws for the step sizes are derived analytically. Both these calculations as well as numerical simulations show that bidirectional interaction leads to full synchronization on average. In contrast, successful learning is only possible by means of fluctuations. Consequently, synchronization is much faster than learning, which is essential for the security of the neural key-exchange protocol. However, this qualitative difference between bidirectional and unidirectional interaction vanishes if tree parity machines with more than three hidden units are used, so that those neural networks are not suitable for neural cryptography. In addition, the effective number of keys which can be generated by the neural key-exchange protocol is calculated using the entropy of the weight distribution. As this quantity increases exponentially with the system size, brute-force attacks on neural cryptography can easily be made unfeasible.

  9. Photon spectrometry utilizing neural networks

    International Nuclear Information System (INIS)

    Silveira, R.; Benevides, C.; Lima, F.; Vilela, E.

    2015-01-01

    Having in mind the time spent on the uneventful work of characterization of the radiation beams used in a ionizing radiation metrology laboratory, the Metrology Service of the Centro Regional de Ciencias Nucleares do Nordeste - CRCN-NE verified the applicability of artificial intelligence (artificial neural networks) to perform the spectrometry in photon fields. For this, was developed a multilayer neural network, as an application for the classification of patterns in energy, associated with a thermoluminescent dosimetric system (TLD-700 and TLD-600). A set of dosimeters was initially exposed to various well known medium energies, between 40 keV and 1.2 MeV, coinciding with the beams determined by ISO 4037 standard, for the dose of 10 mSv in the quantity Hp(10), on a chest phantom (ISO slab phantom) with the purpose of generating a set of training data for the neural network. Subsequently, a new set of dosimeters irradiated in unknown energies was presented to the network with the purpose to test the method. The methodology used in this work was suitable for application in the classification of energy beams, having obtained 100% of the classification performed. (authors)

  10. Towards a magnetoresistive platform for neural signal recording

    Science.gov (United States)

    Sharma, P. P.; Gervasoni, G.; Albisetti, E.; D'Ercoli, F.; Monticelli, M.; Moretti, D.; Forte, N.; Rocchi, A.; Ferrari, G.; Baldelli, P.; Sampietro, M.; Benfenati, F.; Bertacco, R.; Petti, D.

    2017-05-01

    A promising strategy to get deeper insight on brain functionalities relies on the investigation of neural activities at the cellular and sub-cellular level. In this framework, methods for recording neuron electrical activity have gained interest over the years. Main technological challenges are associated to finding highly sensitive detection schemes, providing considerable spatial and temporal resolution. Moreover, the possibility to perform non-invasive assays would constitute a noteworthy benefit. In this work, we present a magnetoresistive platform for the detection of the action potential propagation in neural cells. Such platform allows, in perspective, the in vitro recording of neural signals arising from single neurons, neural networks and brain slices.

  11. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  12. ANT Advanced Neural Tool

    International Nuclear Information System (INIS)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-01-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs

  13. Evolutionary Algorithms For Neural Networks Binary And Real Data Classification

    Directory of Open Access Journals (Sweden)

    Dr. Hanan A.R. Akkar

    2015-08-01

    Full Text Available Artificial neural networks are complex networks emulating the way human rational neurons process data. They have been widely used generally in prediction clustering classification and association. The training algorithms that used to determine the network weights are almost the most important factor that influence the neural networks performance. Recently many meta-heuristic and Evolutionary algorithms are employed to optimize neural networks weights to achieve better neural performance. This paper aims to use recently proposed algorithms for optimizing neural networks weights comparing these algorithms performance with other classical meta-heuristic algorithms used for the same purpose. However to evaluate the performance of such algorithms for training neural networks we examine such algorithms to classify four opposite binary XOR clusters and classification of continuous real data sets such as Iris and Ecoli.

  14. Methodology of Neural Design: Applications in Microwave Engineering

    Directory of Open Access Journals (Sweden)

    Z. Raida

    2006-06-01

    Full Text Available In the paper, an original methodology for the automatic creation of neural models of microwave structures is proposed and verified. Following the methodology, neural models of the prescribed accuracy are built within the minimum CPU time. Validity of the proposed methodology is verified by developing neural models of selected microwave structures. Functionality of neural models is verified in a design - a neural model is joined with a genetic algorithm to find a global minimum of a formulated objective function. The objective function is minimized using different versions of genetic algorithms, and their mutual combinations. The verified methodology of the automated creation of accurate neural models of microwave structures, and their association with global optimization routines are the most important original features of the paper.

  15. Hidden neural networks

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose; Riis, Søren Kamaric

    1999-01-01

    A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

  16. 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.

  17. Active Neural Localization

    OpenAIRE

    Chaplot, Devendra Singh; Parisotto, Emilio; Salakhutdinov, Ruslan

    2018-01-01

    Localization is the problem of estimating the location of an autonomous agent from an observation and a map of the environment. Traditional methods of localization, which filter the belief based on the observations, are sub-optimal in the number of steps required, as they do not decide the actions taken by the agent. We propose "Active Neural Localizer", a fully differentiable neural network that learns to localize accurately and efficiently. The proposed model incorporates ideas of tradition...

  18. Neural cryptography with feedback.

    Science.gov (United States)

    Ruttor, Andreas; Kinzel, Wolfgang; Shacham, Lanir; Kanter, Ido

    2004-04-01

    Neural cryptography is based on a competition between attractive and repulsive stochastic forces. A feedback mechanism is added to neural cryptography which increases the repulsive forces. Using numerical simulations and an analytic approach, the probability of a successful attack is calculated for different model parameters. Scaling laws are derived which show that feedback improves the security of the system. In addition, a network with feedback generates a pseudorandom bit sequence which can be used to encrypt and decrypt a secret message.

  19. Low maternal folate concentrations and maternal MTHFR C677T polymorphism are associated with an increased risk for neural tube defects in offspring: a case-control study among Pakistani case and control mothers.

    Science.gov (United States)

    Nauman, Nuzhat; Jalali, Samina; Shami, Sajjad; Rafiq, Shireen; Große, Greta; Hilger, Alina C; Zhang, Rhong; Mansoor, Saira; Ludwig, Michael; Reutter, Heiko

    2018-01-01

    There is considerable evidence that periconceptional maternal folate deficiency and coding variants in maternal genes coding for critical enzymes in the folate pathway are associated with neural tube defects (NTDs) in offspring. In a case-control study we investigated C677T polymorphism in the 5,10- methylenetetrahydrofolate reductase (MTHFR) gene in case and control mothers of Pakistani origin, and compared these with the respective maternal folate concentrations measured at the time of delivery. A case-control study was conducted among 109 case and 100 control mothers identified through the Holy Family Hospital Rawalpindi, Quaid-i-Azam University, Islamabad, Pakistan. Red blood cell (RBC) and serum folate concentrations and MTHFRC677T polymorphism were compared between case and control mothers. Mean RBC folate and serum folate concentrations were significantly lower in cases compared with control mothers (pcases compared with control mothers (CC vs TT pcases compared with control mothers (C vs T pCase mothers with 677CT or 677TT genotypes had significantly lower serum (pstudy provides further evidence that maternal folate deficiency and MTHFRC677T polymorphism might be associated with an increased risk for NTDs in offspring. Our results are limited by the fact that maternal folate concentrations were not obtained during the periconceptional period, but at delivery. Further analyses, including maternal folate levels during the periconceptional period, are warranted.

  20. Linear matrix inequality approach to exponential synchronization of a class of chaotic neural networks with time-varying delays

    Science.gov (United States)

    Wu, Wei; Cui, Bao-Tong

    2007-07-01

    In this paper, a synchronization scheme for a class of chaotic neural networks with time-varying delays is presented. This class of chaotic neural networks covers several well-known neural networks, such as Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks. The obtained criteria are expressed in terms of linear matrix inequalities, thus they can be efficiently verified. A comparison between our results and the previous results shows that our results are less restrictive.

  1. Correction: Neural Correlates Associated with Successful Working Memory Performance in Older Adults as Revealed by Spatial ICA (vol 9, e99250, 2014)

    NARCIS (Netherlands)

    Saliasi, Emi; Geerligs, Linda; Lorist, Monicque M.; Maurits, Natasha M.

    2016-01-01

    There are errors in the fourth and fifth sentences of the Abstract. The correct sentences are: Our results indicated that a higher BOLD response in the VLPFC was associated with increased performance accuracy in older adults, in the more complex task condition. This ‘BOLD-performance’ relationship

  2. Recurrent Neural Network Based Boolean Factor Analysis and its Application to Word Clustering

    Czech Academy of Sciences Publication Activity Database

    Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.

    2009-01-01

    Roč. 20, č. 7 (2009), s. 1073-1086 ISSN 1045-9227 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.889, year: 2009

  3. Neural Entrainment to Speech Modulates Speech Intelligibility

    NARCIS (Netherlands)

    Riecke, Lars; Formisano, Elia; Sorger, Bettina; Baskent, Deniz; Gaudrain, Etienne

    2018-01-01

    Speech is crucial for communication in everyday life. Speech-brain entrainment, the alignment of neural activity to the slow temporal fluctuations (envelope) of acoustic speech input, is a ubiquitous element of current theories of speech processing. Associations between speech-brain entrainment and

  4. Estimating Conditional Distributions by Neural Networks

    DEFF Research Database (Denmark)

    Kulczycki, P.; Schiøler, Henrik

    1998-01-01

    Neural Networks for estimating conditionaldistributions and their associated quantiles are investigated in this paper. A basic network structure is developed on the basis of kernel estimation theory, and consistency property is considered from a mild set of assumptions. A number of applications...

  5. Artificial Neural Networks and Instructional Technology.

    Science.gov (United States)

    Carlson, Patricia A.

    1991-01-01

    Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

  6. Application of neural networks in experimental physics

    International Nuclear Information System (INIS)

    Kisel', I.V.; Neskromnyj, V.N.; Ososkov, G.A.

    1993-01-01

    The theoretical foundations of numerous models of artificial neural networks (ANN) and their applications to the actual problems of associative memory, optimization and pattern recognition are given. This review contains also numerous using of ANN in the experimental physics both as the hardware realization of fast triggering systems for even selection and for the following software implementation of the trajectory data recognition

  7. Pax7 lineage contributions to the mammalian neural crest.

    Directory of Open Access Journals (Sweden)

    Barbara Murdoch

    Full Text Available Neural crest cells are vertebrate-specific multipotent cells that contribute to a variety of tissues including the peripheral nervous system, melanocytes, and craniofacial bones and cartilage. Abnormal development of the neural crest is associated with several human maladies including cleft/lip palate, aggressive cancers such as melanoma and neuroblastoma, and rare syndromes, like Waardenburg syndrome, a complex disorder involving hearing loss and pigment defects. We previously identified the transcription factor Pax7 as an early marker, and required component for neural crest development in chick embryos. In mammals, Pax7 is also thought to play a role in neural crest development, yet the precise contribution of Pax7 progenitors to the neural crest lineage has not been determined.Here we use Cre/loxP technology in double transgenic mice to fate map the Pax7 lineage in neural crest derivates. We find that Pax7 descendants contribute to multiple tissues including the cranial, cardiac and trunk neural crest, which in the cranial cartilage form a distinct regional pattern. The Pax7 lineage, like the Pax3 lineage, is additionally detected in some non-neural crest tissues, including a subset of the epithelial cells in specific organs.These results demonstrate a previously unappreciated widespread distribution of Pax7 descendants within and beyond the neural crest. They shed light regarding the regionally distinct phenotypes observed in Pax3 and Pax7 mutants, and provide a unique perspective into the potential roles of Pax7 during disease and development.

  8. Requirement of mouse BCCIP for neural development and progenitor proliferation.

    Directory of Open Access Journals (Sweden)

    Yi-Yuan Huang

    Full Text Available Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors.

  9. Cognitive deficits caused by prefrontal cortical and hippocampal neural disinhibition.

    Science.gov (United States)

    Bast, Tobias; Pezze, Marie; McGarrity, Stephanie

    2017-10-01

    We review recent evidence concerning the significance of inhibitory GABA transmission and of neural disinhibition, that is, deficient GABA transmission, within the prefrontal cortex and the hippocampus, for clinically relevant cognitive functions. Both regions support important cognitive functions, including attention and memory, and their dysfunction has been implicated in cognitive deficits characterizing neuropsychiatric disorders. GABAergic inhibition shapes cortico-hippocampal neural activity, and, recently, prefrontal and hippocampal neural disinhibition has emerged as a pathophysiological feature of major neuropsychiatric disorders, especially schizophrenia and age-related cognitive decline. Regional neural disinhibition, disrupting spatio-temporal control of neural activity and causing aberrant drive of projections, may disrupt processing within the disinhibited region and efferent regions. Recent studies in rats showed that prefrontal and hippocampal neural disinhibition (by local GABA antagonist microinfusion) dysregulates burst firing, which has been associated with important aspects of neural information processing. Using translational tests of clinically relevant cognitive functions, these studies showed that prefrontal and hippocampal neural disinhibition disrupts regional cognitive functions (including prefrontal attention and hippocampal memory function). Moreover, hippocampal neural disinhibition disrupted attentional performance, which does not require the hippocampus but requires prefrontal-striatal circuits modulated by the hippocampus. However, some prefrontal and hippocampal functions (including inhibitory response control) are spared by regional disinhibition. We consider conceptual implications of these findings, regarding the distinct relationships of distinct cognitive functions to prefrontal and hippocampal GABA tone and neural activity. Moreover, the findings support the proposition that prefrontal and hippocampal neural disinhibition

  10. Correction of Hirschsprung-Associated Mutations in Human Induced Pluripotent Stem Cells Via Clustered Regularly Interspaced Short Palindromic Repeats/Cas9, Restores Neural Crest Cell Function.

    Science.gov (United States)

    Lai, Frank Pui-Ling; Lau, Sin-Ting; Wong, John Kwong-Leong; Gui, Hongsheng; Wang, Reeson Xu; Zhou, Tingwen; Lai, Wing Hon; Tse, Hung-Fat; Tam, Paul Kwong-Hang; Garcia-Barcelo, Maria-Mercedes; Ngan, Elly Sau-Wai

    2017-07-01

    Hirschsprung disease is caused by failure of enteric neural crest cells (ENCCs) to fully colonize the bowel, leading to bowel obstruction and megacolon. Heterozygous mutations in the coding region of the RET gene cause a severe form of Hirschsprung disease (total colonic aganglionosis). However, 80% of HSCR patients have short-segment Hirschsprung disease (S-HSCR), which has not been associated with genetic factors. We sought to identify mutations associated with S-HSCR, and used the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing system to determine how mutations affect ENCC function. We created induced pluripotent stem cell (iPSC) lines from 1 patient with total colonic aganglionosis (with the G731del mutation in RET) and from 2 patients with S-HSCR (without a RET mutation), as well as RET +/- and RET -/- iPSCs. IMR90-iPSC cells were used as the control cell line. Migration and differentiation capacities of iPSC-derived ENCCs were analyzed in differentiation and migration assays. We searched for mutation(s) associated with S-HSCR by combining genetic and transcriptome data from patient blood- and iPSC-derived ENCCs, respectively. Mutations in the iPSCs were corrected using the CRISPR/Cas9 system. ENCCs derived from all iPSC lines, but not control iPSCs, had defects in migration and neuronal lineage differentiation. RET mutations were associated with differentiation and migration defects of ENCCs in vitro. Genetic and transcriptome analyses associated a mutation in the vinculin gene (VCL M209L) with S-HSCR. CRISPR/Cas9 correction of the RET G731del and VCL M209L mutations in iPSCs restored the differentiation and migration capacities of ENCCs. We identified mutations in VCL associated with S-HSCR. Correction of this mutation in iPSC using CRISPR/Cas9 editing, as well as the RET G731del mutation that causes Hirschsprung disease with total colonic aganglionosis, restored ENCC function. Our study demonstrates how human iPSCs can

  11. Malformation/dysplasia syndrome (neural tube defect, hypospadias neuroblastoma) associated with an extra dicentric marker chromosome 15 ({open_quotes}inversion duplication 15{close_quotes})

    Energy Technology Data Exchange (ETDEWEB)

    Reitnauer, P.J.; Rao, K.W.; Tepperberg, J.H. [Univ. of North Carolina, Chapel Hill, NC (United States)

    1994-09-01

    Extra dicentric 15 marker chromosomes are associated with variable degrees of mental retardation but not major structural birth defects. We have studied a unique patient, a male infant who was prenatally diagnosed with lumbar meningomyelocele and an extra pseudodicentric marker chromosome: 47,XY,+psu dic(15)t(15;15)(?q12,?q12)mat. Hairy ears and a coronal hypospadias were noted at birth. At three months of age, a stage I thoracic neuroblastoma was primarily resected. Tumor cells, skin fibroblasts and peripheral blood lymphocytes contained the dicentric 15. The mother is mosaic for the marker chromosome. Fluorescence in situ hybridization (FISH) studies using a classic 15 satellite probe (D15Z1 [Oncor]) confirmed the presence of 2 number 15 centromeres in the marker. The marker is felt to be the result of a translocation rather than an inverted duplication because the G-band morphology of the short arm/satellite complexes differ from one another, implying that the arms originate from 2 different number 15s. FISH analysis using cosmid probes for the Prader-Willi/Angelman critical region (D15S11 and GABRB3 [Oncor]) revealed 2 copies of this region, indicating that these loci are duplicated in the marker. Although some features of the patient`s phenotype such as developmental delay and hypotonia have been associated with dicentric chromosome 15 markers, this is the first malformation/dysplasia syndrome or neuroblastoma reported to our knowledge. The association of neuroblastoma with chromosome 15 aberrations in this case provides speculation as to the role of chromosome 15 loci in cell division control.

  12. The neural signatures of distinct psychopathic traits.

    Science.gov (United States)

    Carré, Justin M; Hyde, Luke W; Neumann, Craig S; Viding, Essi; Hariri, Ahmad R

    2013-01-01

    Recent studies suggest that psychopathy may be associated with dysfunction in the neural circuitry supporting both threat- and reward-related processes. However, these studies have involved small samples and often focused on extreme groups. Thus, it is unclear to what extent current findings may generalize to psychopathic traits in the general population. Furthermore, no studies have systematically and simultaneously assessed associations between distinct psychopathy facets and both threat- and reward-related brain function in the same sample of participants. Here, we examined the relationship between threat-related amygdala reactivity and reward-related ventral striatum (VS) reactivity and variation in four facets of self-reported psychopathy in a sample of 200 young adults. Path models indicated that amygdala reactivity to fearful facial expressions is negatively associated with the interpersonal facet of psychopathy, whereas amygdala reactivity to angry facial expressions is positively associated with the lifestyle facet. Furthermore, these models revealed that differential VS reactivity to positive versus negative feedback is negatively associated with the lifestyle facet. There was suggestive evidence for gender-specific patterns of association between brain function and psychopathy facets. Our findings are the first to document differential associations between both threat- and reward-related neural processes and distinct facets of psychopathy and thus provide a more comprehensive picture of the pattern of neural vulnerabilities that may predispose to maladaptive outcomes associated with psychopathy.

  13. Fructose:Glucose Ratios—A Study of Sugar Self-Administration and Associated Neural and Physiological Responses in the Rat

    Directory of Open Access Journals (Sweden)

    AnneMarie Levy

    2015-05-01

    Full Text Available This study explored whether different ratios of fructose (F and glucose (G in sugar can engender significant differences in self-administration and associated neurobiological and physiological responses in male Sprague-Dawley rats. In Experiment 1, animals self-administered pellets containing 55% F + 45% G or 30% F + 70% G, and Fos immunoreactivity was assessed in hypothalamic regions regulating food intake and reward. In Experiment 2, rats self-administered solutions of 55% F + 42% G (high fructose corn syrup (HFCS, 50% F + 50% G (sucrose or saccharin, and mRNA of the dopamine 2 (D2R and mu-opioid (MOR receptor genes were assessed in striatal regions involved in addictive behaviors. Finally, in Experiment 3, rats self-administered HFCS and sucrose in their home cages, and hepatic fatty acids were quantified. It was found that higher fructose ratios engendered lower self-administration, lower Fos expression in the lateral hypothalamus/arcuate nucleus, reduced D2R and increased MOR mRNA in the dorsal striatum and nucleus accumbens core, respectively, as well as elevated omega-6 polyunsaturated fatty acids in the liver. These data indicate that a higher ratio of fructose may enhance the reinforcing effects of sugar and possibly lead to neurobiological and physiological alterations associated with addictive and metabolic disorders.

  14. Fructose:glucose ratios--a study of sugar self-administration and associated neural and physiological responses in the rat.

    Science.gov (United States)

    Levy, AnneMarie; Marshall, Paul; Zhou, Yan; Kreek, Mary Jeanne; Kent, Katrina; Daniels, Stephen; Shore, Ari; Downs, Tiana; Fernandes, Maria Fernanda; Mutch, David M; Leri, Francesco

    2015-05-22

    This study explored whether different ratios of fructose (F) and glucose (G) in sugar can engender significant differences in self-administration and associated neurobiological and physiological responses in male Sprague-Dawley rats. In Experiment 1, animals self-administered pellets containing 55% F + 45% G or 30% F + 70% G, and Fos immunoreactivity was assessed in hypothalamic regions regulating food intake and reward. In Experiment 2, rats self-administered solutions of 55% F + 42% G (high fructose corn syrup (HFCS)), 50% F + 50% G (sucrose) or saccharin, and mRNA of the dopamine 2 (D2R) and mu-opioid (MOR) receptor genes were assessed in striatal regions involved in addictive behaviors. Finally, in Experiment 3, rats self-administered HFCS and sucrose in their home cages, and hepatic fatty acids were quantified. It was found that higher fructose ratios engendered lower self-administration, lower Fos expression in the lateral hypothalamus/arcuate nucleus, reduced D2R and increased MOR mRNA in the dorsal striatum and nucleus accumbens core, respectively, as well as elevated omega-6 polyunsaturated fatty acids in the liver. These data indicate that a higher ratio of fructose may enhance the reinforcing effects of sugar and possibly lead to neurobiological and physiological alterations associated with addictive and metabolic disorders.

  15. Parallel consensual neural networks.

    Science.gov (United States)

    Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

    1997-01-01

    A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

  16. Dysfunction of Rapid Neural Adaptation in Dyslexia.

    Science.gov (United States)

    Perrachione, Tyler K; Del Tufo, Stephanie N; Winter, Rebecca; Murtagh, Jack; Cyr, Abigail; Chang, Patricia; Halverson, Kelly; Ghosh, Satrajit S; Christodoulou, Joanna A; Gabrieli, John D E

    2016-12-21

    Identification of specific neurophysiological dysfunctions resulting in selective reading difficulty (dyslexia) has remained elusive. In addition to impaired reading development, individuals with dyslexia frequently exhibit behavioral deficits in perceptual adaptation. Here, we assessed neurophysiological adaptation to stimulus repetition in adults and children with dyslexia for a wide variety of stimuli, spoken words, written words, visual objects, and faces. For every stimulus type, individuals with dyslexia exhibited significantly diminished neural adaptation compared to controls in stimulus-specific cortical areas. Better reading skills in adults and children with dyslexia were associated with greater repetition-induced neural adaptation. These results highlight a dysfunction of rapid neural adaptation as a core neurophysiological difference in dyslexia that may underlie impaired reading development. Reduced neurophysiological adaptation may relate to prior reports of reduced behavioral adaptation in dyslexia and may reveal a difference in brain functions that ultimately results in a specific reading impairment. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. Open quantum generalisation of Hopfield neural networks

    Science.gov (United States)

    Rotondo, P.; Marcuzzi, M.; Garrahan, J. P.; Lesanovsky, I.; Müller, M.

    2018-03-01

    We propose a new framework to understand how quantum effects may impact on the dynamics of neural networks. We implement the dynamics of neural networks in terms of Markovian open quantum systems, which allows us to treat thermal and quantum coherent effects on the same footing. In particular, we propose an open quantum generalisation of the Hopfield neural network, the simplest toy model of associative memory. We determine its phase diagram and show that quantum fluctuations give rise to a qualitatively new non-equilibrium phase. This novel phase is characterised by limit cycles corresponding to high-dimensional stationary manifolds that may be regarded as a generalisation of storage patterns to the quantum domain.

  18. Metabolic neural mapping in neonatal rats

    International Nuclear Information System (INIS)

    DiRocco, R.J.; Hall, W.G.

    1981-01-01

    Functional neural mapping by 14 C-deoxyglucose autoradiography in adult rats has shown that increases in neural metabolic rate that are coupled to increased neurophysiological activity are more evident in axon terminals and dendrites than neuron cell bodies. Regions containing architectonically well-defined concentrations of terminals and dendrites (neuropil) have high metabolic rates when the neuropil is physiologically active. In neonatal rats, however, we find that regions containing well-defined groupings of neuron cell bodies have high metabolic rates in 14 C-deoxyglucose autoradiograms. The striking difference between the morphological appearance of 14 C-deoxyglucose autoradiograms obtained from neonatal and adult rats is probably related to developmental changes in morphometric features of differentiating neurons, as well as associated changes in type and locus of neural work performed

  19. Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station.

    Science.gov (United States)

    Moustris, Konstantinos; Tsiros, Ioannis X; Tseliou, Areti; Nastos, Panagiotis

    2018-04-11

    The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

  20. Neural Plasticity Associated with Hippocampal PKA-CREB and NMDA Signaling Is Involved in the Antidepressant Effect of Repeated Low Dose of Yueju Pill on Chronic Mouse Model of Learned Helplessness

    Directory of Open Access Journals (Sweden)

    Zhilu Zou

    2017-01-01

    Full Text Available Yueju pill is a traditional Chinese medicine formulated to treat syndromes of mood disorders. Here, we investigated the therapeutic effect of repeated low dose of Yueju in the animal model mimicking clinical long-term depression condition and the role of neural plasticity associated with PKA- (protein kinase A- CREB (cAMP response element binding protein and NMDA (N-methyl-D-aspartate signaling. We showed that a single low dose of Yueju demonstrated antidepressant effects in tests of tail suspension, forced swim, and novelty-suppressed feeding. A chronic learned helplessness (LH protocol resulted in a long-term depressive-like condition. Repeated administration of Yueju following chronic LH remarkably alleviated all of depressive-like symptoms measured, whereas conventional antidepressant fluoxetine only showed a minor improvement. In the hippocampus, Yueju and fluoxetine both normalized brain-derived neurotrophic factor (BDNF and PKA level. Only Yueju, not fluoxetine, rescued the deficits in CREB signaling. The chronic LH upregulated the expression of NMDA receptor subunits NR1, NR2A, and NR2B, which were all attenuated by Yueju. Furthermore, intracerebraventricular administration of NMDA blunted the antidepressant effect of Yueju. These findings supported the antidepressant efficacy of repeated routine low dose of Yueju in a long-term depression model and the critical role of CREB and NMDA signaling.

  1. Neural Plasticity Associated with Hippocampal PKA-CREB and NMDA Signaling Is Involved in the Antidepressant Effect of Repeated Low Dose of Yueju Pill on Chronic Mouse Model of Learned Helplessness.

    Science.gov (United States)

    Zou, Zhilu; Chen, Yin; Shen, Qinqin; Guo, Xiaoyan; Zhang, Yuxuan; Chen, Gang

    2017-01-01

    Yueju pill is a traditional Chinese medicine formulated to treat syndromes of mood disorders. Here, we investigated the therapeutic effect of repeated low dose of Yueju in the animal model mimicking clinical long-term depression condition and the role of neural plasticity associated with PKA- (protein kinase A-) CREB (cAMP response element binding protein) and NMDA (N-methyl-D-aspartate) signaling. We showed that a single low dose of Yueju demonstrated antidepressant effects in tests of tail suspension, forced swim, and novelty-suppressed feeding. A chronic learned helplessness (LH) protocol resulted in a long-term depressive-like condition. Repeated administration of Yueju following chronic LH remarkably alleviated all of depressive-like symptoms measured, whereas conventional antidepressant fluoxetine only showed a minor improvement. In the hippocampus, Yueju and fluoxetine both normalized brain-derived neurotrophic factor (BDNF) and PKA level. Only Yueju, not fluoxetine, rescued the deficits in CREB signaling. The chronic LH upregulated the expression of NMDA receptor subunits NR1, NR2A, and NR2B, which were all attenuated by Yueju. Furthermore, intracerebraventricular administration of NMDA blunted the antidepressant effect of Yueju. These findings supported the antidepressant efficacy of repeated routine low dose of Yueju in a long-term depression model and the critical role of CREB and NMDA signaling.

  2. Development and application of artificial neural network models to estimate values of a complex human thermal comfort index associated with urban heat and cool island patterns using air temperature data from a standard meteorological station

    Science.gov (United States)

    Moustris, Konstantinos; Tsiros, Ioannis X.; Tseliou, Areti; Nastos, Panagiotis

    2018-04-01

    The present study deals with the development and application of artificial neural network models (ANNs) to estimate the values of a complex human thermal comfort-discomfort index associated with urban heat and cool island conditions inside various urban clusters using as only inputs air temperature data from a standard meteorological station. The index used in the study is the Physiologically Equivalent Temperature (PET) index which requires as inputs, among others, air temperature, relative humidity, wind speed, and radiation (short- and long-wave components). For the estimation of PET hourly values, ANN models were developed, appropriately trained, and tested. Model results are compared to values calculated by the PET index based on field monitoring data for various urban clusters (street, square, park, courtyard, and gallery) in the city of Athens (Greece) during an extreme hot weather summer period. For the evaluation of the predictive ability of the developed ANN models, several statistical evaluation indices were applied: the mean bias error, the root mean square error, the index of agreement, the coefficient of determination, the true predictive rate, the false alarm rate, and the Success Index. According to the results, it seems that ANNs present a remarkable ability to estimate hourly PET values within various urban clusters using only hourly values of air temperature. This is very important in cases where the human thermal comfort-discomfort conditions have to be analyzed and the only available parameter is air temperature.

  3. Prototype-Incorporated Emotional Neural Network.

    Science.gov (United States)

    Oyedotun, Oyebade K; Khashman, Adnan

    2017-08-15

    Artificial neural networks (ANNs) aim to simulate the biological neural activities. Interestingly, many ''engineering'' prospects in ANN have relied on motivations from cognition and psychology studies. So far, two important learning theories that have been subject of active research are the prototype and adaptive learning theories. The learning rules employed for ANNs can be related to adaptive learning theory, where several examples of the different classes in a task are supplied to the network for adjusting internal parameters. Conversely, the prototype-learning theory uses prototypes (representative examples); usually, one prototype per class of the different classes contained in the task. These prototypes are supplied for systematic matching with new examples so that class association can be achieved. In this paper, we propose and implement a novel neural network algorithm based on modifying the emotional neural network (EmNN) model to unify the prototype- and adaptive-learning theories. We refer to our new model as ``prototype-incorporated EmNN''. Furthermore, we apply the proposed model to two real-life challenging tasks, namely, static hand-gesture recognition and face recognition, and compare the result to those obtained using the popular back-propagation neural network (BPNN), emotional BPNN (EmNN), deep networks, an exemplar classification model, and k-nearest neighbor.

  4. Neural codes of seeing architectural styles.

    Science.gov (United States)

    Choo, Heeyoung; Nasar, Jack L; Nikrahei, Bardia; Walther, Dirk B

    2017-01-10

    Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people's visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture.

  5. The different effects of high-frequency stimulation of the nucleus accumbens shell and core on food consumption are possibly associated with different neural responses in the lateral hypothalamic area.

    Science.gov (United States)

    Wei, N; Wang, Y; Wang, X; He, Z; Zhang, M; Zhang, X; Pan, Y; Zhang, J; Qin, Z; Zhang, K

    2015-08-20

    Obesity may result from dysfunction of the reward system, especially in the nucleus accumbens (Acb). Based on this hypothesis, many researchers have tested the effect of high-frequency stimulation (HFS) of the Acb shell (Acb-Sh) and/or core (Acb-Co) on ingestive behaviors, but few studies have explored the possible mechanisms involved in the differences between the Acb-Sh and Acb-Co. The present study tested effects of HFS of the Acb-Sh and Acb-Co on high-fat food (HFF) consumption in rats after 24h of food deprivation. Microdialysis and electrophysiological experiments were carried out in awake rats to explore potential mechanisms. The results showed that the Acb-Sh decreased HFF consumption after food deprivation both during and post-HFS. However, HFS of the Acb-Co did not induce similar changes in food consumption. HFS of the Acb-Sh (Sh-HFS) induced an increase in GABA level in the lateral hypothalamic area (LHA) during both phases, whereas HFS of the Acb-Co (Co-HFS) did not exhibit similar effects. The electrophysiological experiment showed that nearly all the LHA neurons were inhibited by Sh-HFS, and the mean firing rate decreased significantly both during and post-HFS. In contrast, the mean firing rate of the LHA neurons did not exhibit clear changes during Co-HFS, although some individual neurons appeared to exhibit responses to Co-HFS. Considering all the data, we postulated that Sh-HFS, rather than Co-HFS, might inhibit palatable food consumption after food deprivation by decreasing the reward value of that food, which suggested that it might also disturb the process of developing obesity. The mechanisms involved in the different effects of Sh-HFS and Co-HFS on food consumption may be associated with different neural responses in the LHA. The Acb-Sh has abundant GABAergic projections to the LHA, whereas the Acb-Co has few or no GABAergic innervations to the LHA. Thus, neural activity in the LHA exhibits different responses to Sh-HFS and Co-HFS. Copyright

  6. Feature to prototype transition in neural networks

    Science.gov (United States)

    Krotov, Dmitry; Hopfield, John

    Models of associative memory with higher order (higher than quadratic) interactions, and their relationship to neural networks used in deep learning are discussed. Associative memory is conventionally described by recurrent neural networks with dynamical convergence to stable points. Deep learning typically uses feedforward neural nets without dynamics. However, a simple duality relates these two different views when applied to problems of pattern classification. From the perspective of associative memory such models deserve attention because they make it possible to store a much larger number of memories, compared to the quadratic case. In the dual description, these models correspond to feedforward neural networks with one hidden layer and unusual activation functions transmitting the activities of the visible neurons to the hidden layer. These activation functions are rectified polynomials of a higher degree rather than the rectified linear functions used in deep learning. The network learns representations of the data in terms of features for rectified linear functions, but as the power in the activation function is increased there is a gradual shift to a prototype-based representation, the two extreme regimes of pattern recognition known in cognitive psychology. Simons Center for Systems Biology.

  7. Cotton genotypes selection through artificial neural networks.

    Science.gov (United States)

    Júnior, E G Silva; Cardoso, D B O; Reis, M C; Nascimento, A F O; Bortolin, D I; Martins, M R; Sousa, L B

    2017-09-27

    Breeding programs currently use statistical analysis to assist in the identification of superior genotypes at various stages of a cultivar's development. Differently from these analyses, the computational intelligence approach has been little explored in genetic improvement of cotton. Thus, this study was carried out with the objective of presenting the use of artificial neural networks as auxiliary tools in the improvement of the cotton to improve fiber quality. To demonstrate the applicability of this approach, this research was carried out using the evaluation data of 40 genotypes. In order to classify the genotypes for fiber quality, the artificial neural networks were trained with replicate data of 20 genotypes of cotton evaluated in the harvests of 2013/14 and 2014/15, regarding fiber length, uniformity of length, fiber strength, micronaire index, elongation, short fiber index, maturity index, reflectance degree, and fiber quality index. This quality index was estimated by means of a weighted average on the determined score (1 to 5) of each characteristic of the HVI evaluated, according to its industry standards. The artificial neural networks presented a high capacity of correct classification of the 20 selected genotypes based on the fiber quality index, so that when using fiber length associated with the short fiber index, fiber maturation, and micronaire index, the artificial neural networks presented better results than using only fiber length and previous associations. It was also observed that to submit data of means of new genotypes to the neural networks trained with data of repetition, provides better results of classification of the genotypes. When observing the results obtained in the present study, it was verified that the artificial neural networks present great potential to be used in the different stages of a genetic improvement program of the cotton, aiming at the improvement of the fiber quality of the future cultivars.

  8. Neural Architectures for Control

    Science.gov (United States)

    Peterson, James K.

    1991-01-01

    The cerebellar model articulated controller (CMAC) neural architectures are shown to be viable for the purposes of real-time learning and control. Software tools for the exploration of CMAC performance are developed for three hardware platforms, the MacIntosh, the IBM PC, and the SUN workstation. All algorithm development was done using the C programming language. These software tools were then used to implement an adaptive critic neuro-control design that learns in real-time how to back up a trailer truck. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neuro-controllers on-line in real-time on a MS-DOS PC 386. CMAC neural architectures are also used in conjunction with a hierarchical planning approach to find collision-free paths over 2-D analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The CMAC architectures are trained in real-time for each obstacle field presented. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array. These results are a very good indication of the potential power of the neural architectures in control design. In order to reach as wide an audience as possible, we have run a seminar on neuro-control that has met once per week since 20 May 1991. This seminar has thoroughly discussed the CMAC architecture, relevant portions of classical control, back propagation through time, and adaptive critic designs.

  9. Sacred or Neural?

    DEFF Research Database (Denmark)

    Runehov, Anne Leona Cesarine

    Are religious spiritual experiences merely the product of the human nervous system? Anne L.C. Runehov investigates the potential of contemporary neuroscience to explain religious experiences. Following the footsteps of Michael Persinger, Andrew Newberg and Eugene d'Aquili she defines...... the terminological bounderies of "religious experiences" and explores the relevant criteria for the proper evaluation of scientific research, with a particular focus on the validity of reductionist models. Runehov's theis is that the perspectives looked at do not necessarily exclude each other but can be merged....... The question "sacred or neural?" becomes a statement "sacred and neural". The synergies thus produced provide manifold opportunities for interdisciplinary dialogue and research....

  10. Deconvolution using a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, S.K.

    1990-11-15

    Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

  11. Introduction to Artificial Neural Networks

    DEFF Research Database (Denmark)

    Larsen, Jan

    1999-01-01

    The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks.......The note addresses introduction to signal analysis and classification based on artificial feed-forward neural networks....

  12. Combination of counterpropagation artificial neural networks and antioxidant activities for comprehensive evaluation of associated-extraction efficiency of various cyclodextrins in the traditional Chinese formula Xue-Zhi-Ning.

    Science.gov (United States)

    Sun, Lili; Yang, Jianwen; Wang, Meng; Zhang, Huijie; Liu, Yanan; Ren, Xiaoliang; Qi, Aidi

    2015-11-10

    Xue-Zhi-Ning (XZN) is a widely used traditional Chinese medicine formula to treat hyperlipidemia. Recently, cyclodextrins (CDs) have been extensively used to minimize problems relative to medicine bioavailability, such as low solubility and poor stability. The objective of this study was to determine the associated-extraction efficiency of various CDs in XZN. Three various type CDs were evaluated, including native CDs (α-CD, β-CD), hydrophilic CD derivatives (HP-β-CD and Me-β-CD), and ionic CD derivatives (SBE-β-CD and CM-β-CD). An ultra high-performance liquid chromatography (UHPLC) fingerprint was applied to determine the components in CD extracts and original aqueous extract (OAE). A counterpropagation artificial neural network (CP-ANN) was used to analyze the components in different extracts and compare the selective extraction of various CDs. Extraction efficiencies of the various CDs in terms of extracted components follow the ranking, ionic CD derivatives>hydrophilic CD derivatives>native CDs>OAE. Besides, different types of CDs have their own selective extraction and ionic CD derivatives present the strongest associated-extraction efficiency. Antioxidant potentials of various extracts were evaluated by determining the inhibition of spontaneous, H2O2-induced, CCl4-induced and Fe(2+)/ascorbic acid-induced lipid peroxidation (LPO) and analyzing the scavenging capacity for DPPH and hydroxyl radicals. The order of extraction efficiencies of the various CDs relative to antioxidant activities is as follows: SBE-β-CD>CM-β-CD>HP-β-CD>Me-β-CD>β-CD>α-CD. It can be demonstrated that all of the CDs studied increase the extraction efficiency and that ionic CD derivatives (SBE-β-CD and CM-β-CD) present the highest extraction capability in terms of amount extracted and antioxidant activities of extracts. Copyright © 2015 Elsevier B.V. All rights reserved.

  13. Suppression of immunodeficiency virus-associated neural damage by the p75 neurotrophin receptor ligand, LM11A-31, in an in vitro feline model.

    Science.gov (United States)

    Meeker, Rick B; Poulton, Winona; Feng, Wen-hai; Hudson, Lola; Longo, Frank M

    2012-06-01

    Feline immunodeficiency virus (FIV) infection like human immunodeficiency virus (HIV), produces systemic and central nervous system disease in its natural host, the domestic cat, that parallels the pathogenesis seen in HIV-infected humans. The ability to culture feline nervous system tissue affords the unique opportunity to directly examine interactions of infectious virus with CNS cells for the development of models and treatments that can then be translated to a natural infectious model. To explore the therapeutic potential of a new p75 neurotrophin receptor ligand, LM11A-31, we evaluated neuronal survival, neuronal damage and calcium homeostasis in cultured feline neurons following inoculation with FIV. FIV resulted in the gradual appearance of dendritic beading, pruning of processes and shrinkage of neuronal perikarya in the neurons. Astrocytes developed a more activated appearance and there was an enhanced accumulation of microglia, particularly at longer times post-inoculation. Addition of 10 nM LM11A-31, to the cultures greatly reduced or eliminated the neuronal pathology as well as the FIV effects on astrocytes and microglia. LM11A-31 also, prevented the development of delayed calcium deregulation in feline neurons exposed to conditioned medium from FIV treated macrophages. The suppression of calcium accumulation prevented the development of foci of calcium accumulation and beading in the dendrites. FIV replication was unaffected by LM11A-31. The strong neuroprotection afforded by LM11A-31 in an infectious in vitro model indicates that LM11A-31 may have excellent potential for the treatment of HIV-associated neurodegeneration.

  14. A Possible Neural Representation of Mathematical Group Structures.

    Science.gov (United States)

    Pomi, Andrés

    2016-09-01

    Every cognitive activity has a neural representation in the brain. When humans deal with abstract mathematical structures, for instance finite groups, certain patterns of activity are occurring in the brain that constitute their neural representation. A formal neurocognitive theory must account for all the activities developed by our brain and provide a possible neural representation for them. Associative memories are neural network models that have a good chance of achieving a universal representation of cognitive phenomena. In this work, we present a possible neural representation of mathematical group structures based on associative memory models that store finite groups through their Cayley graphs. A context-dependent associative memory stores the transitions between elements of the group when multiplied by each generator of a given presentation of the group. Under a convenient election of the vector basis mapping the elements of the group in the neural activity, the input of a vector corresponding to a generator of the group collapses the context-dependent rectangular matrix into a virtual square permutation matrix that is the matrix representation of the generator. This neural representation corresponds to the regular representation of the group, in which to each element is assigned a permutation matrix. This action of the generator on the memory matrix can also be seen as the dissection of the corresponding monochromatic subgraph of the Cayley graph of the group, and the adjacency matrix of this subgraph is the permutation matrix corresponding to the generator.

  15. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  16. Neural correlates of consciousness

    African Journals Online (AJOL)

    neural cells.1 Under this approach, consciousness is believed to be a product of the ... possible only when the 40 Hz electrical hum is sustained among the brain circuits, ... expect the brain stem ascending reticular activating system. (ARAS) and the ... related synchrony of cortical neurons.11 Indeed, stimulation of brainstem ...

  17. Neural Networks and Micromechanics

    Science.gov (United States)

    Kussul, Ernst; Baidyk, Tatiana; Wunsch, Donald C.

    The title of the book, "Neural Networks and Micromechanics," seems artificial. However, the scientific and technological developments in recent decades demonstrate a very close connection between the two different areas of neural networks and micromechanics. The purpose of this book is to demonstrate this connection. Some artificial intelligence (AI) methods, including neural networks, could be used to improve automation system performance in manufacturing processes. However, the implementation of these AI methods within industry is rather slow because of the high cost of conducting experiments using conventional manufacturing and AI systems. To lower the cost, we have developed special micromechanical equipment that is similar to conventional mechanical equipment but of much smaller size and therefore of lower cost. This equipment could be used to evaluate different AI methods in an easy and inexpensive way. The proved methods could be transferred to industry through appropriate scaling. In this book, we describe the prototypes of low cost microequipment for manufacturing processes and the implementation of some AI methods to increase precision, such as computer vision systems based on neural networks for microdevice assembly and genetic algorithms for microequipment characterization and the increase of microequipment precision.

  18. Learning from neural control.

    Science.gov (United States)

    Wang, Cong; Hill, David J

    2006-01-01

    One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.

  19. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  20. Neural underpinnings of music

    DEFF Research Database (Denmark)

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

    2014-01-01

    . According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Fourth, empirical studies of neural and behavioral effects of syncopation, polyrhythm and groove will be reported, and we...

  1. Improvement of the detection response time of gas sensors using the association of artificial neural networks with pattern recognition technique; Amelioration de la reponse temporelle de capteurs de gaz par reconnaissance de forme a l'aide de reseaux de neurones

    Energy Technology Data Exchange (ETDEWEB)

    Bordieu, Ch.; Rebiere, D. [Bordeaux-1 Univ., Lab. IXL, UMR CNRS 5818, 33 (France); Pistre, J.; Planata, R. [Centre d' Etudes du Bouchet, 91 - Vert-le-Petit (France)

    1999-07-01

    The association of artificial neural networks (multilayer perceptrons) with a real time pattern recognition technique (shifting windows) allowed the development of systems for the detection and the quantification of gases. Shifting window technique is presented and offers an interesting way to improve the detection response time. The partial detector characterization with regard to its parameters was realized. Applications dealing with the detection of gas compounds using surface acoustic sensors permit to show the shifting window technique feasibility. (author)

  2. Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networks

    Science.gov (United States)

    Saghafi, Behrouz; Murugesan, Gowtham; Davenport, Elizabeth; Wagner, Ben; Urban, Jillian; Kelley, Mireille; Jones, Derek; Powers, Alexander; Whitlow, Christopher; Stitzel, Joel; Maldjian, Joseph; Montillo, Albert

    2018-02-01

    The effect of subconcussive head impact exposure during contact sports, including American football, on brain health is poorly understood particularly in young and adolescent players, who may be more vulnerable to brain injury during periods of rapid brain maturation. This study aims to quantify the association between cumulative effects of head impact exposure from a single season of football on white matter (WM) integrity as measured with diffusion MRI. The study targets football players aged 9-18 years old. All players were imaged pre- and post-season with structural MRI and diffusion tensor MRI (DTI). Fractional Anisotropy (FA) maps, shown to be closely correlated with WM integrity, were computed for each subject, co-registered and subtracted to compute the change in FA per subject. Biomechanical metrics were collected at every practice and game using helmet mounted accelerometers. Each head impact was converted into a risk of concussion, and the risk of concussion-weighted cumulative exposure (RWE) was computed for each player for the season. Athletes with high and low RWE were selected for a two-category classification task. This task was addressed by developing a 3D Convolutional Neural Network (CNN) to automatically classify players into high and low impact exposure groups from the change in FA maps. Using the proposed model, high classification performance, including ROC Area Under Curve score of 85.71% and F1 score of 83.33% was achieved. This work adds to the growing body of evidence for the presence of detectable neuroimaging brain changes in white matter integrity from a single season of contact sports play, even in the absence of a clinically diagnosed concussion.

  3. Bioprinting for Neural Tissue Engineering.

    Science.gov (United States)

    Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

    2018-01-01

    Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Neural networks: a biased overview

    International Nuclear Information System (INIS)

    Domany, E.

    1988-01-01

    An overview of recent activity in the field of neural networks is presented. The long-range aim of this research is to understand how the brain works. First some of the problems are stated and terminology defined; then an attempt is made to explain why physicists are drawn to the field, and their main potential contribution. In particular, in recent years some interesting models have been introduced by physicists. A small subset of these models is described, with particular emphasis on those that are analytically soluble. Finally a brief review of the history and recent developments of single- and multilayer perceptrons is given, bringing the situation up to date regarding the central immediate problem of the field: search for a learning algorithm that has an associated convergence theorem

  5. Discrete-time BAM neural networks with variable delays

    Science.gov (United States)

    Liu, Xin-Ge; Tang, Mei-Lan; Martin, Ralph; Liu, Xin-Bi

    2007-07-01

    This Letter deals with the global exponential stability of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Using a Lyapunov functional, and linear matrix inequality techniques (LMI), we derive a new delay-dependent exponential stability criterion for BAM neural networks with variable delays. As this criterion has no extra constraints on the variable delay functions, it can be applied to quite general BAM neural networks with a broad range of time delay functions. It is also easy to use in practice. An example is provided to illustrate the theoretical development.

  6. Discrete-time BAM neural networks with variable delays

    International Nuclear Information System (INIS)

    Liu Xinge; Tang Meilan; Martin, Ralph; Liu Xinbi

    2007-01-01

    This Letter deals with the global exponential stability of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Using a Lyapunov functional, and linear matrix inequality techniques (LMI), we derive a new delay-dependent exponential stability criterion for BAM neural networks with variable delays. As this criterion has no extra constraints on the variable delay functions, it can be applied to quite general BAM neural networks with a broad range of time delay functions. It is also easy to use in practice. An example is provided to illustrate the theoretical development

  7. 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.

  8. 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.

  9. Deep Neural Yodelling

    OpenAIRE

    Pfäffli, Daniel (Autor/in)

    2018-01-01

    Yodel music differs from most other genres by exercising the transition from chest voice to falsetto with an audible glottal stop which is recognised even by laymen. Yodel often consists of a yodeller with a choir accompaniment. In Switzerland, it is differentiated between the natural yodel and yodel songs. Today's approaches to music generation with machine learning algorithms are based on neural networks, which are best described by stacked layers of neurons which are connected with neurons...

  10. Neural networks for triggering

    International Nuclear Information System (INIS)

    Denby, B.; Campbell, M.; Bedeschi, F.; Chriss, N.; Bowers, C.; Nesti, F.

    1990-01-01

    Two types of neural network beauty trigger architectures, based on identification of electrons in jets and recognition of secondary vertices, have been simulated in the environment of the Fermilab CDF experiment. The efficiencies for B's and rejection of background obtained are encouraging. If hardware tests are successful, the electron identification architecture will be tested in the 1991 run of CDF. 10 refs., 5 figs., 1 tab

  11. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  12. Rotation Invariance Neural Network

    OpenAIRE

    Li, Shiyuan

    2017-01-01

    Rotation invariance and translation invariance have great values in image recognition tasks. In this paper, we bring a new architecture in convolutional neural network (CNN) named cyclic convolutional layer to achieve rotation invariance in 2-D symbol recognition. We can also get the position and orientation of the 2-D symbol by the network to achieve detection purpose for multiple non-overlap target. Last but not least, this architecture can achieve one-shot learning in some cases using thos...

  13. Neural Mechanisms of Foraging

    OpenAIRE

    Kolling, Nils; Behrens, Timothy EJ; Mars, Rogier B; Rushworth, Matthew FS

    2012-01-01

    Behavioural economic studies, involving limited numbers of choices, have provided key insights into neural decision-making mechanisms. By contrast, animals’ foraging choices arise in the context of sequences of encounters with prey/food. On each encounter the animal chooses to engage or whether the environment is sufficiently rich that searching elsewhere is merited. The cost of foraging is also critical. We demonstrate humans can alternate between two modes of choice, comparative decision-ma...

  14. Artificial neural networks in neutron dosimetry

    Energy Technology Data Exchange (ETDEWEB)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Mercado, G.A.; Perales M, W.A.; Robles R, J.A. [Unidades Academicas de Estudios Nucleares, UAZ, A.P. 336, 98000 Zacatecas (Mexico); Gallego, E.; Lorente, A. [Depto. de Ingenieria Nuclear, Universidad Politecnica de Madrid, (Spain)

    2005-07-01

    An artificial neural network has been designed to obtain the neutron doses using only the Bonner spheres spectrometer's count rates. Ambient, personal and effective neutron doses were included. 187 neutron spectra were utilized to calculate the Bonner count rates and the neutron doses. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. Re-binned spectra, UTA4 response matrix and fluence-to-dose coefficients were used to calculate the count rates in Bonner spheres spectrometer and the doses. Count rates were used as input and the respective doses were used as output during neural network training. Training and testing was carried out in Mat lab environment. The artificial neural network performance was evaluated using the {chi}{sup 2}- test, where the original and calculated doses were compared. The use of Artificial Neural Networks in neutron dosimetry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

  15. Neural networks in continuous optical media

    International Nuclear Information System (INIS)

    Anderson, D.Z.

    1987-01-01

    The authors' interest is to see to what extent neural models can be implemented using continuous optical elements. Thus these optical networks represent a continuous distribution of neuronlike processors rather than a discrete collection. Most neural models have three characteristic features: interconnections; adaptivity; and nonlinearity. In their optical representation the interconnections are implemented with linear one- and two-port optical elements such as lenses and holograms. Real-time holographic media allow these interconnections to become adaptive. The nonlinearity is achieved with gain, for example, from two-beam coupling in photorefractive media or a pumped dye medium. Using these basic optical elements one can in principle construct continuous representations of a number of neural network models. The authors demonstrated two devices based on continuous optical elements: an associative memory which recalls an entire object when addressed with a partial object and a tracking novelty filter which identifies time-dependent features in an optical scene. These devices demonstrate the potential of distributed optical elements to implement more formal models of neural networks

  16. Neutron spectrometry with artificial neural networks

    International Nuclear Information System (INIS)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Rodriguez, J.M.; Mercado S, G.A.; Iniguez de la Torre Bayo, M.P.; Barquero, R.; Arteaga A, T.

    2005-01-01

    An artificial neural network has been designed to obtain the neutron spectra from the Bonner spheres spectrometer's count rates. The neural network was trained using 129 neutron spectra. These include isotopic neutron sources; reference and operational spectra from accelerators and nuclear reactors, spectra from mathematical functions as well as few energy groups and monoenergetic spectra. The spectra were transformed from lethargy to energy distribution and were re-bin ned to 31 energy groups using the MCNP 4C code. Re-binned spectra and UTA4 response matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and the respective spectrum was used as output during neural network training. After training the network was tested with the Bonner spheres count rates produced by a set of neutron spectra. This set contains data used during network training as well as data not used. Training and testing was carried out in the Mat lab program. To verify the network unfolding performance the original and unfolded spectra were compared using the χ 2 -test and the total fluence ratios. The use of Artificial Neural Networks to unfold neutron spectra in neutron spectrometry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

  17. Artificial neural networks in neutron dosimetry

    International Nuclear Information System (INIS)

    Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.; Mercado, G.A.; Perales M, W.A.; Robles R, J.A.; Gallego, E.; Lorente, A.

    2005-01-01

    An artificial neural network has been designed to obtain the neutron doses using only the Bonner spheres spectrometer's count rates. Ambient, personal and effective neutron doses were included. 187 neutron spectra were utilized to calculate the Bonner count rates and the neutron doses. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. Re-binned spectra, UTA4 response matrix and fluence-to-dose coefficients were used to calculate the count rates in Bonner spheres spectrometer and the doses. Count rates were used as input and the respective doses were used as output during neural network training. Training and testing was carried out in Mat lab environment. The artificial neural network performance was evaluated using the χ 2 - test, where the original and calculated doses were compared. The use of Artificial Neural Networks in neutron dosimetry is an alternative procedure that overcomes the drawbacks associated in this ill-conditioned problem. (Author)

  18. Neutron spectrometry using artificial neural networks

    International Nuclear Information System (INIS)

    Vega-Carrillo, Hector Rene; Martin Hernandez-Davila, Victor; Manzanares-Acuna, Eduardo; Mercado Sanchez, Gema A.; Pilar Iniguez de la Torre, Maria; Barquero, Raquel; Palacios, Francisco; Mendez Villafane, Roberto; Arteaga Arteaga, Tarcicio; Manuel Ortiz Rodriguez, Jose

    2006-01-01

    An artificial neural network has been designed to obtain neutron spectra from Bonner spheres spectrometer count rates. The neural network was trained using 129 neutron spectra. These include spectra from isotopic neutron sources; reference and operational spectra from accelerators and nuclear reactors, spectra based on mathematical functions as well as few energy groups and monoenergetic spectra. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. The re-binned spectra and the UTA4 response matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and their respective spectra were used as output during the neural network training. After training, the network was tested with the Bonner spheres count rates produced by folding a set of neutron spectra with the response matrix. This set contains data used during network training as well as data not used. Training and testing was carried out using the Matlab ( R) program. To verify the network unfolding performance, the original and unfolded spectra were compared using the root mean square error. The use of artificial neural networks to unfold neutron spectra in neutron spectrometry is an alternative procedure that overcomes the drawbacks associated with this ill-conditioned problem

  19. 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

  20. Modulated error diffusion CGHs for neural nets

    Science.gov (United States)

    Vermeulen, Pieter J. E.; Casasent, David P.

    1990-05-01

    New modulated error diffusion CGHs (computer generated holograms) for optical computing are considered. Specific attention is given to their use in optical matrix-vector, associative processor, neural net and optical interconnection architectures. We consider lensless CGH systems (many CGHs use an external Fourier transform (FT) lens), the Fresnel sampling requirements, the effects of finite CGH apertures (sample and hold inputs), dot size correction (for laser recorders), and new applications for this novel encoding method (that devotes attention to quantization noise effects).

  1. Neural correlates of continuous causal word generation.

    Science.gov (United States)

    Wende, Kim C; Straube, Benjamin; Stratmann, Mirjam; Sommer, Jens; Kircher, Tilo; Nagels, Arne

    2012-09-01

    Causality provides a natural structure for organizing our experience and language. Causal reasoning during speech production is a distinct aspect of verbal communication, whose related brain processes are yet unknown. The aim of the current study was to investigate the neural mechanisms underlying the continuous generation of cause-and-effect coherences during overt word production. During fMRI data acquisition participants performed three verbal fluency tasks on identical cue words: A novel causal verbal fluency task (CVF), requiring the production of multiple reasons to a given cue word (e.g. reasons for heat are fire, sun etc.), a semantic (free association, FA, e.g. associations with heat are sweat, shower etc.) and a phonological control task (phonological verbal fluency, PVF, e.g. rhymes with heat are meat, wheat etc.). We found that, in contrast to PVF, both CVF and FA activated a left lateralized network encompassing inferior frontal, inferior parietal and angular regions, with further bilateral activation in middle and inferior as well as superior temporal gyri and the cerebellum. For CVF contrasted against FA, we found greater bold responses only in the left middle frontal cortex. Large overlaps in the neural activations during free association and causal verbal fluency indicate that the access to causal relationships between verbal concepts is at least partly based on the semantic neural network. The selective activation in the left middle frontal cortex for causal verbal fluency suggests that distinct neural processes related to cause-and-effect-relations are associated with the recruitment of middle frontal brain areas. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Trimaran Resistance Artificial Neural Network

    Science.gov (United States)

    2011-01-01

    11th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 Trimaran Resistance Artificial Neural Network Richard...Trimaran Resistance Artificial Neural Network 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e... Artificial Neural Network and is restricted to the center and side-hull configurations tested. The value in the parametric model is that it is able to

  3. Quantum neural networks: Current status and prospects for development

    Science.gov (United States)

    Altaisky, M. V.; Kaputkina, N. E.; Krylov, V. A.

    2014-11-01

    The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

  4. The application of artificial neural networks to TLD dose algorithm

    International Nuclear Information System (INIS)

    Moscovitch, M.

    1997-01-01

    We review the application of feed forward neural networks to multi element thermoluminescence dosimetry (TLD) dose algorithm development. A Neural Network is an information processing method inspired by the biological nervous system. A dose algorithm based on a neural network is a fundamentally different approach from conventional algorithms, as it has the capability to learn from its own experience. The neural network algorithm is shown the expected dose values (output) associated with a given response of a multi-element dosimeter (input) many times.The algorithm, being trained that way, eventually is able to produce its own unique solution to similar (but not exactly the same) dose calculation problems. For personnel dosimetry, the output consists of the desired dose components: deep dose, shallow dose, and eye dose. The input consists of the TL data obtained from the readout of a multi-element dosimeter. For this application, a neural network architecture was developed based on the concept of functional links network (FLN). The FLN concept allowed an increase in the dimensionality of the input space and construction of a neural network without any hidden layers. This simplifies the problem and results in a relatively simple and reliable dose calculation algorithm. Overall, the neural network dose algorithm approach has been shown to significantly improve the precision and accuracy of dose calculations. (authors)

  5. Neural plasticity and its initiating conditions in tinnitus.

    Science.gov (United States)

    Roberts, L E

    2018-03-01

    Deafferentation caused by cochlear pathology (which can be hidden from the audiogram) activates forms of neural plasticity in auditory pathways, generating tinnitus and its associated conditions including hyperacusis. This article discusses tinnitus mechanisms and suggests how these mechanisms may relate to those involved in normal auditory information processing. Research findings from animal models of tinnitus and from electromagnetic imaging of tinnitus patients are reviewed which pertain to the role of deafferentation and neural plasticity in tinnitus and hyperacusis. Auditory neurons compensate for deafferentation by increasing their input/output functions (gain) at multiple levels of the auditory system. Forms of homeostatic plasticity are believed to be responsible for this neural change, which increases the spontaneous and driven activity of neurons in central auditory structures in animals expressing behavioral evidence of tinnitus. Another tinnitus correlate, increased neural synchrony among the affected neurons, is forged by spike-timing-dependent neural plasticity in auditory pathways. Slow oscillations generated by bursting thalamic neurons verified in tinnitus animals appear to modulate neural plasticity in the cortex, integrating tinnitus neural activity with information in brain regions supporting memory, emotion, and consciousness which exhibit increased metabolic activity in tinnitus patients. The latter process may be induced by transient auditory events in normal processing but it persists in tinnitus, driven by phantom signals from the auditory pathway. Several tinnitus therapies attempt to suppress tinnitus through plasticity, but repeated sessions will likely be needed to prevent tinnitus activity from returning owing to deafferentation as its initiating condition.

  6. A wirelessly powered microspectrometer for neural probe-pin device

    Science.gov (United States)

    Choi, Sang H.; Kim, Min H.; Song, Kyo D.; Yoon, Hargsoon; Lee, Uhn

    2015-12-01

    Treatment of neurological anomalies, whether done invasively or not, places stringent demands on device functionality and size. We have developed a micro-spectrometer for use as an implantable neural probe to monitor neuro-chemistry in synapses. The micro-spectrometer, based on a NASA-invented miniature Fresnel grating, is capable of differentiating the emission spectra from various brain tissues. The micro-spectrometer meets the size requirements, and is able to probe the neuro-chemistry and suppression voltage typically associated with a neural anomaly. This neural probe-pin device (PPD) is equipped with wireless power technology (WPT) to enable operation in a continuous manner without requiring an implanted battery. The implanted neural PPD, together with a neural electronics interface and WPT, enable real-time measurement and control/feedback for remediation of neural anomalies. The design and performance of the combined PPD/WPT device for monitoring dopamine in a rat brain will be presented to demonstrate the current level of development. Future work on this device will involve the addition of an embedded expert system capable of performing semi-autonomous management of neural functions through a routine of sensing, processing, and control.

  7. Optics in neural computation

    Science.gov (United States)

    Levene, Michael John

    In all attempts to emulate the considerable powers of the brain, one is struck by both its immense size, parallelism, and complexity. While the fields of neural networks, artificial intelligence, and neuromorphic engineering have all attempted oversimplifications on the considerable complexity, all three can benefit from the inherent scalability and parallelism of optics. This thesis looks at specific aspects of three modes in which optics, and particularly volume holography, can play a part in neural computation. First, holography serves as the basis of highly-parallel correlators, which are the foundation of optical neural networks. The huge input capability of optical neural networks make them most useful for image processing and image recognition and tracking. These tasks benefit from the shift invariance of optical correlators. In this thesis, I analyze the capacity of correlators, and then present several techniques for controlling the amount of shift invariance. Of particular interest is the Fresnel correlator, in which the hologram is displaced from the Fourier plane. In this case, the amount of shift invariance is limited not just by the thickness of the hologram, but by the distance of the hologram from the Fourier plane. Second, volume holography can provide the huge storage capacity and high speed, parallel read-out necessary to support large artificial intelligence systems. However, previous methods for storing data in volume holograms have relied on awkward beam-steering or on as-yet non- existent cheap, wide-bandwidth, tunable laser sources. This thesis presents a new technique, shift multiplexing, which is capable of very high densities, but which has the advantage of a very simple implementation. In shift multiplexing, the reference wave consists of a focused spot a few millimeters in front of the hologram. Multiplexing is achieved by simply translating the hologram a few tens of microns or less. This thesis describes the theory for how shift

  8. Embedding responses in spontaneous neural activity shaped through sequential learning.

    Directory of Open Access Journals (Sweden)

    Tomoki Kurikawa

    Full Text Available Recent experimental measurements have demonstrated that spontaneous neural activity in the absence of explicit external stimuli has remarkable spatiotemporal structure. This spontaneous activity has also been shown to play a key role in the response to external stimuli. To better understand this role, we proposed a viewpoint, "memories-as-bifurcations," that differs from the traditional "memories-as-attractors" viewpoint. Memory recall from the memories-as-bifurcations viewpoint occurs when the spontaneous neural activity is changed to an appropriate output activity upon application of an input, known as a bifurcation in dynamical systems theory, wherein the input modifies the flow structure of the neural dynamics. Learning, then, is a process that helps create neural dynamical systems such that a target output pattern is generated as an attractor upon a given input. Based on this novel viewpoint, we introduce in this paper an associative memory model with a sequential learning process. Using a simple hebbian-type learning, the model is able to memorize a large number of input/output mappings. The neural dynamics shaped through the learning exhibit different bifurcations to make the requested targets stable upon an increase in the input, and the neural activity in the absence of input shows chaotic dynamics with occasional approaches to the memorized target patterns. These results suggest that these dynamics facilitate the bifurcations to each target attractor upon application of the corresponding input, which thus increases the capacity for learning. This theoretical finding about the behavior of the spontaneous neural activity is consistent with recent experimental observations in which the neural activity without stimuli wanders among patterns evoked by previously applied signals. In addition, the neural networks shaped by learning properly reflect the correlations of input and target-output patterns in a similar manner to those designed in

  9. 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.

  10. Neural responses to exclusion predict susceptibility to social influence.

    Science.gov (United States)

    Falk, Emily B; Cascio, Christopher N; O'Donnell, Matthew Brook; Carp, Joshua; Tinney, Francis J; Bingham, C Raymond; Shope, Jean T; Ouimet, Marie Claude; Pradhan, Anuj K; Simons-Morton, Bruce G

    2014-05-01

    Social influence is prominent across the lifespan, but sensitivity to influence is especially high during adolescence and is often associated with increased risk taking. Such risk taking can have dire consequences. For example, in American adolescents, traffic-related crashes are leading causes of nonfatal injury and death. Neural measures may be especially useful in understanding the basic mechanisms of adolescents' vulnerability to peer influence. We examined neural responses to social exclusion as potential predictors of risk taking in the presence of peers in recently licensed adolescent drivers. Risk taking was assessed in a driving simulator session occurring approximately 1 week after the neuroimaging session. Increased activity in neural systems associated with the distress of social exclusion and mentalizing during an exclusion episode predicted increased risk taking in the presence of a peer (controlling for solo risk behavior) during a driving simulator session outside the neuroimaging laboratory 1 week later. These neural measures predicted risky driving behavior above and beyond self-reports of susceptibility to peer pressure and distress during exclusion. These results address the neural bases of social influence and risk taking; contribute to our understanding of social and emotional function in the adolescent brain; and link neural activity in specific, hypothesized, regions to risk-relevant outcomes beyond the neuroimaging laboratory. Results of this investigation are discussed in terms of the mechanisms underlying risk taking in adolescents and the public health implications for adolescent driving. Copyright © 2014 Society for Adolescent Health and Medicine. All rights reserved.

  11. Discriminating lysosomal membrane protein types using dynamic neural network.

    Science.gov (United States)

    Tripathi, Vijay; Gupta, Dwijendra Kumar

    2014-01-01

    This work presents a dynamic artificial neural network methodology, which classifies the proteins into their classes from their sequences alone: the lysosomal membrane protein classes and the various other membranes protein classes. In this paper, neural networks-based lysosomal-associated membrane protein type prediction system is proposed. Different protein sequence representations are fused to extract the features of a protein sequence, which includes seven feature sets; amino acid (AA) composition, sequence length, hydrophobic group, electronic group, sum of hydrophobicity, R-group, and dipeptide composition. To reduce the dimensionality of the large feature vector, we applied the principal component analysis. The probabilistic neural network, generalized regression neural network, and Elman regression neural network (RNN) are used as classifiers and compared with layer recurrent network (LRN), a dynamic network. The dynamic networks have memory, i.e. its output depends not only on the input but the previous outputs also. Thus, the accuracy of LRN classifier among all other artificial neural networks comes out to be the highest. The overall accuracy of jackknife cross-validation is 93.2% for the data-set. These predicted results suggest that the method can be effectively applied to discriminate lysosomal associated membrane proteins from other membrane proteins (Type-I, Outer membrane proteins, GPI-Anchored) and Globular proteins, and it also indicates that the protein sequence representation can better reflect the core feature of membrane proteins than the classical AA composition.

  12. Neural substrates of sublexical processing for spelling.

    Science.gov (United States)

    DeMarco, Andrew T; Wilson, Stephen M; Rising, Kindle; Rapcsak, Steven Z; Beeson, Pélagie M

    2017-01-01

    We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Artificial neural network detects human uncertainty

    Science.gov (United States)

    Hramov, Alexander E.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Makarov, Vladimir V.; Koronovskii, Alexey A.; Garcia-Prieto, Juan; Antón-Toro, Luis Fernando; Maestú, Fernando; Pisarchik, Alexander N.

    2018-03-01

    Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.

  14. Evidence for a neural law of effect.

    Science.gov (United States)

    Athalye, Vivek R; Santos, Fernando J; Carmena, Jose M; Costa, Rui M

    2018-03-02

    Thorndike's law of effect states that actions that lead to reinforcements tend to be repeated more often. Accordingly, neural activity patterns leading to reinforcement are also reentered more frequently. Reinforcement relies on dopaminergic activity in the ventral tegmental area (VTA), and animals shape their behavior to receive dopaminergic stimulation. Seeking evidence for a neural law of effect, we found that mice learn to reenter more frequently motor cortical activity patterns that trigger optogenetic VTA self-stimulation. Learning was accompanied by gradual shaping of these patterns, with participating neurons progressively increasing and aligning their covariance to that of the target pattern. Motor cortex patterns that lead to phasic dopaminergic VTA activity are progressively reinforced and shaped, suggesting a mechanism by which animals select and shape actions to reliably achieve reinforcement. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  15. Analysis of neural networks

    CERN Document Server

    Heiden, Uwe

    1980-01-01

    The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica­ ted throughout the text. However, they are not explored in de­ tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev­ els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be­ havior of neurons or neuron pools. In this respect the essay is writt...

  16. Neural Synchronization and Cryptography

    Science.gov (United States)

    Ruttor, Andreas

    2007-11-01

    Neural networks can synchronize by learning from each other. In the case of discrete weights full synchronization is achieved in a finite number of steps. Additional networks can be trained by using the inputs and outputs generated during this process as examples. Several learning rules for both tasks are presented and analyzed. In the case of Tree Parity Machines synchronization is much faster than learning. Scaling laws for the number of steps needed for full synchronization and successful learning are derived using analytical models. They indicate that the difference between both processes can be controlled by changing the synaptic depth. In the case of bidirectional interaction the synchronization time increases proportional to the square of this parameter, but it grows exponentially, if information is transmitted in one direction only. Because of this effect neural synchronization can be used to construct a cryptographic key-exchange protocol. Here the partners benefit from mutual interaction, so that a passive attacker is usually unable to learn the generated key in time. The success probabilities of different attack methods are determined by numerical simulations and scaling laws are derived from the data. They show that the partners can reach any desired level of security by just increasing the synaptic depth. Then the complexity of a successful attack grows exponentially, but there is only a polynomial increase of the effort needed to generate a key. Further improvements of security are possible by replacing the random inputs with queries generated by the partners.

  17. Neural Networks for Optimal Control

    DEFF Research Database (Denmark)

    Sørensen, O.

    1995-01-01

    Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

  18. Neural networks at the Tevatron

    International Nuclear Information System (INIS)

    Badgett, W.; Burkett, K.; Campbell, M.K.; Wu, D.Y.; Bianchin, S.; DeNardi, M.; Pauletta, G.; Santi, L.; Caner, A.; Denby, B.; Haggerty, H.; Lindsey, C.S.; Wainer, N.; Dall'Agata, M.; Johns, K.; Dickson, M.; Stanco, L.; Wyss, J.L.

    1992-10-01

    This paper summarizes neural network applications at the Fermilab Tevatron, including the first online hardware application in high energy physics (muon tracking): the CDF and DO neural network triggers; offline quark/gluon discrimination at CDF; ND a new tool for top to multijets recognition at CDF

  19. Neural Networks for the Beginner.

    Science.gov (United States)

    Snyder, Robin M.

    Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…

  20. Neural fields theory and applications

    CERN Document Server

    Graben, Peter; Potthast, Roland; Wright, James

    2014-01-01

    With this book, the editors present the first comprehensive collection in neural field studies, authored by leading scientists in the field - among them are two of the founding-fathers of neural field theory. Up to now, research results in the field have been disseminated across a number of distinct journals from mathematics, computational neuroscience, biophysics, cognitive science and others. Starting with a tutorial for novices in neural field studies, the book comprises chapters on emergent patterns, their phase transitions and evolution, on stochastic approaches, cortical development, cognition, robotics and computation, large-scale numerical simulations, the coupling of neural fields to the electroencephalogram and phase transitions in anesthesia. The intended readership are students and scientists in applied mathematics, theoretical physics, theoretical biology, and computational neuroscience. Neural field theory and its applications have a long-standing tradition in the mathematical and computational ...

  1. Artificial neural networks in NDT

    International Nuclear Information System (INIS)

    Abdul Aziz Mohamed

    2001-01-01

    Artificial neural networks, simply known as neural networks, have attracted considerable interest in recent years largely because of a growing recognition of the potential of these computational paradigms as powerful alternative models to conventional pattern recognition or function approximation techniques. The neural networks approach is having a profound effect on almost all fields, and has been utilised in fields Where experimental inter-disciplinary work is being carried out. Being a multidisciplinary subject with a broad knowledge base, Nondestructive Testing (NDT) or Nondestructive Evaluation (NDE) is no exception. This paper explains typical applications of neural networks in NDT/NDE. Three promising types of neural networks are highlighted, namely, back-propagation, binary Hopfield and Kohonen's self-organising maps. (Author)

  2. Maternal Antenatal Bereavement and Neural Tube Defect in Live-Born Offspring

    DEFF Research Database (Denmark)

    Ingstrup, Katja Glejsted; Wu, Chun Sen; Olsen, Jørn

    2016-01-01

    BACKGROUND: Maternal emotional stress during pregnancy has previously been associated with congenital neural malformations, but most studies are based on data collected retrospectively. The objective of our study was to investigate associations between antenatal maternal bereavement due to death...

  3. Longitudinal links between childhood peer acceptance and the neural correlates of sharing

    NARCIS (Netherlands)

    Will, G.-J. (Geert-Jan); E.A. Crone (Eveline); P.A.C. van Lier (Pol); Güroğlu, B. (Berna)

    2016-01-01

    textabstractChildhood peer acceptance is associated with high levels of prosocial behavior and advanced perspective taking skills. Yet, the neurobiological mechanisms underlying these associations have not been studied. This functional magnetic resonance imaging study examined the neural correlates

  4. Implementation of a kinematic fit of single top-quark production in association with a W boson and its application in a neural-network-based analysis in ATLAS

    International Nuclear Information System (INIS)

    Loddenkoetter, Thomas

    2012-08-01

    In order to provide discrimination between the Wt-channel signal and its backgrounds for analyses that try to measure single top-quark production in the Wt-channel, a kinematic fit to the lepton+jets decay mode of the Wt-channel has been implemented using the KLFitter package. The fit has been validated by studying its performance in terms of the efficiency of the fit to correctly assign the final-state quarks of the fit model to the measured jets as a function of various parameters, as well as the improvement of the energy resolutions of the fitted particles due to the fit. By combining the output variables of the kinematic fitter using neural networks, it has been shown that the fit results are suitable to identify the decay mode of the top quark in Wt events and to identify whether the kinematic fit succeeded in correctly assigning the final-state quarks to the measured jets. In order to demonstrate the value of the kinematic fit for analysis, another neural network - again using strictly results of the kinematic fit as input - has been trained to separate to the Wt-channel signal from its backgrounds. A separation power comparable to a conventional neural-network-based Wt-channel analysis has been achieved.

  5. Implementation of a kinematic fit of single top-quark production in association with a W boson and its application in a neural-network-based analysis in ATLAS

    Energy Technology Data Exchange (ETDEWEB)

    Loddenkoetter, Thomas

    2012-08-15

    In order to provide discrimination between the Wt-channel signal and its backgrounds for analyses that try to measure single top-quark production in the Wt-channel, a kinematic fit to the lepton+jets decay mode of the Wt-channel has been implemented using the KLFitter package. The fit has been validated by studying its performance in terms of the efficiency of the fit to correctly assign the final-state quarks of the fit model to the measured jets as a function of various parameters, as well as the improvement of the energy resolutions of the fitted particles due to the fit. By combining the output variables of the kinematic fitter using neural networks, it has been shown that the fit results are suitable to identify the decay mode of the top quark in Wt events and to identify whether the kinematic fit succeeded in correctly assigning the final-state quarks to the measured jets. In order to demonstrate the value of the kinematic fit for analysis, another neural network - again using strictly results of the kinematic fit as input - has been trained to separate to the Wt-channel signal from its backgrounds. A separation power comparable to a conventional neural-network-based Wt-channel analysis has been achieved.

  6. Stability analysis for stochastic BAM nonlinear neural network with delays

    Science.gov (United States)

    Lv, Z. W.; Shu, H. S.; Wei, G. L.

    2008-02-01

    In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associative memory neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities(LMIs). Hence, the global asymptotic stability of the stochastic bidirectional associative memory neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global asymptotic stability criteria.

  7. Stability analysis for stochastic BAM nonlinear neural network with delays

    International Nuclear Information System (INIS)

    Lv, Z W; Shu, H S; Wei, G L

    2008-01-01

    In this paper, stochastic bidirectional associative memory neural networks with constant or time-varying delays is considered. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, we derive several sufficient conditions in order to guarantee the global asymptotically stable in the mean square. Our investigation shows that the stochastic bidirectional associative memory neural networks are globally asymptotically stable in the mean square if there are solutions to some linear matrix inequalities(LMIs). Hence, the global asymptotic stability of the stochastic bidirectional associative memory neural networks can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed global asymptotic stability criteria

  8. Interacting neural networks

    Science.gov (United States)

    Metzler, R.; Kinzel, W.; Kanter, I.

    2000-08-01

    Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbor. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated. Two competitive perceptrons trained on mutually exclusive learning aims and a perceptron which is trained on the opposite of its own output are examined analytically. An ensemble of competitive perceptrons is used as decision-making algorithms in a model of a closed market (El Farol Bar problem or the Minority Game. In this game, a set of agents who have to make a binary decision is considered.); each network is trained on the history of minority decisions. This ensemble of perceptrons relaxes to a stationary state whose performance can be better than random.

  9. Neural circuitry and immunity

    Science.gov (United States)

    Pavlov, Valentin A.; Tracey, Kevin J.

    2015-01-01

    Research during the last decade has significantly advanced our understanding of the molecular mechanisms at the interface between the nervous system and the immune system. Insight into bidirectional neuroimmune communication has characterized the nervous system as an important partner of the immune system in the regulation of inflammation. Neuronal pathways, including the vagus nerve-based inflammatory reflex are physiological regulators of immune function and inflammation. In parallel, neuronal function is altered in conditions characterized by immune dysregulation and inflammation. Here, we review these regulatory mechanisms and describe the neural circuitry modulating immunity. Understanding these mechanisms reveals possibilities to use targeted neuromodulation as a therapeutic approach for inflammatory and autoimmune disorders. These findings and current clinical exploration of neuromodulation in the treatment of inflammatory diseases defines the emerging field of Bioelectronic Medicine. PMID:26512000

  10. 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.

  11. Neural crest stem cell multipotency requires Foxd3 to maintain neural potential and repress mesenchymal fates.

    Science.gov (United States)

    Mundell, Nathan A; Labosky, Patricia A

    2011-02-01

    Neural crest (NC) progenitors generate a wide array of cell types, yet molecules controlling NC multipotency and self-renewal and factors mediating cell-intrinsic distinctions between multipotent versus fate-restricted progenitors are poorly understood. Our earlier work demonstrated that Foxd3 is required for maintenance of NC progenitors in the embryo. Here, we show that Foxd3 mediates a fate restriction choice for multipotent NC progenitors with loss of Foxd3 biasing NC toward a mesenchymal fate. Neural derivatives of NC were lost in Foxd3 mutant mouse embryos, whereas abnormally fated NC-derived vascular smooth muscle cells were ectopically located in the aorta. Cranial NC defects were associated with precocious differentiation towards osteoblast and chondrocyte cell fates, and individual mutant NC from different anteroposterior regions underwent fate changes, losing neural and increasing myofibroblast potential. Our results demonstrate that neural potential can be separated from NC multipotency by the action of a single gene, and establish novel parallels between NC and other progenitor populations that depend on this functionally conserved stem cell protein to regulate self-renewal and multipotency.

  12. A TLD dose algorithm using artificial neural networks

    International Nuclear Information System (INIS)

    Moscovitch, M.; Rotunda, J.E.; Tawil, R.A.; Rathbone, B.A.

    1995-01-01

    An artificial neural network was designed and used to develop a dose algorithm for a multi-element thermoluminescence dosimeter (TLD). The neural network architecture is based on the concept of functional links network (FLN). Neural network is an information processing method inspired by the biological nervous system. A dose algorithm based on neural networks is fundamentally different as compared to conventional algorithms, as it has the capability to learn from its own experience. The neural network algorithm is shown the expected dose values (output) associated with given responses of a multi-element dosimeter (input) many times. The algorithm, being trained that way, eventually is capable to produce its own unique solution to similar (but not exactly the same) dose calculation problems. For personal dosimetry, the output consists of the desired dose components: deep dose, shallow dose and eye dose. The input consists of the TL data obtained from the readout of a multi-element dosimeter. The neural network approach was applied to the Harshaw Type 8825 TLD, and was shown to significantly improve the performance of this dosimeter, well within the U.S. accreditation requirements for personnel dosimeters

  13. High level cognitive information processing in neural networks

    Science.gov (United States)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

    Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

  14. [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.

  15. Controlling the dynamics of multi-state neural networks

    International Nuclear Information System (INIS)

    Jin, Tao; Zhao, Hong

    2008-01-01

    In this paper, we first analyze the distribution of local fields (DLF) which is induced by the memory patterns in the Q-Ising model. It is found that the structure of the DLF is closely correlated with the network dynamics and the system performance. However, the design rule adopted in the Q-Ising model, like the other rules adopted for multi-state neural networks with associative memories, cannot be applied to directly control the DLF for a given set of memory patterns, and thus cannot be applied to further study the relationships between the structure of the DLF and the dynamics of the network. We then extend a design rule, which was presented recently for designing binary-state neural networks, to make it suitable for designing general multi-state neural networks. This rule is able to control the structure of the DLF as expected. We show that controlling the DLF not only can affect the dynamic behaviors of the multi-state neural networks for a given set of memory patterns, but also can improve the storage capacity. With the change of the DLF, the network shows very rich dynamic behaviors, such as the 'chaos phase', the 'memory phase', and the 'mixture phase'. These dynamic behaviors are also observed in the binary-state neural networks; therefore, our results imply that they may be the universal behaviors of feedback neural networks

  16. Oscillator Neural Network Retrieving Sparsely Coded Phase Patterns

    Science.gov (United States)

    Aoyagi, Toshio; Nomura, Masaki

    1999-08-01

    Little is known theoretically about the associative memory capabilities of neural networks in which information is encoded not only in the mean firing rate but also in the timing of firings. Particularly, in the case of sparsely coded patterns, it is biologically important to consider the timings of firings and to study how such consideration influences storage capacities and quality of recalled patterns. For this purpose, we propose a simple extended model of oscillator neural networks to allow for expression of a nonfiring state. Analyzing both equilibrium states and dynamical properties in recalling processes, we find that the system possesses good associative memory.

  17. Neural basis of social status hierarchy across species.

    Science.gov (United States)

    Chiao, Joan Y

    2010-12-01

    Social status hierarchy is a ubiquitous principle of social organization across the animal kingdom. Recent findings in social neuroscience reveal distinct neural networks associated with the recognition and experience of social hierarchy in humans, as well as modulation of these networks by personality and culture. Additionally, allelic variation in the serotonin transporter gene is associated with prevalence of social hierarchy across species and cultures, suggesting the importance of the study of genetic factors underlying social hierarchy. Future studies are needed to determine how genetic and environmental factors shape neural systems involved in the production and maintenance of social hierarchy across ontogeny and phylogeny. Copyright © 2010 Elsevier Ltd. All rights reserved.

  18. Discrete Neural Signatures of Basic Emotions.

    Science.gov (United States)

    Saarimäki, Heini; Gotsopoulos, Athanasios; Jääskeläinen, Iiro P; Lampinen, Jouko; Vuilleumier, Patrik; Hari, Riitta; Sams, Mikko; Nummenmaa, Lauri

    2016-06-01

    Categorical models of emotions posit neurally and physiologically distinct human basic emotions. We tested this assumption by using multivariate pattern analysis (MVPA) to classify brain activity patterns of 6 basic emotions (disgust, fear, happiness, sadness, anger, and surprise) in 3 experiments. Emotions were induced with short movies or mental imagery during functional magnetic resonance imaging. MVPA accurately classified emotions induced by both methods, and the classification generalized from one induction condition to another and across individuals. Brain regions contributing most to the classification accuracy included medial and inferior lateral prefrontal cortices, frontal pole, precentral and postcentral gyri, precuneus, and posterior cingulate cortex. Thus, specific neural signatures across these regions hold representations of different emotional states in multimodal fashion, independently of how the emotions are induced. Similarity of subjective experiences between emotions was associated with similarity of neural patterns for the same emotions, suggesting a direct link between activity in these brain regions and the subjective emotional experience. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  19. Functional model of biological neural networks.

    Science.gov (United States)

    Lo, James Ting-Ho

    2010-12-01

    A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

  20. Neural correlates of affective influence on choice.

    Science.gov (United States)

    Piech, Richard M; Lewis, Jade; Parkinson, Caroline H; Owen, Adrian M; Roberts, Angela C; Downing, Paul E; Parkinson, John A

    2010-03-01

    Making the right choice depends crucially on the accurate valuation of the available options in the light of current needs and goals of an individual. Thus, the valuation of identical options can vary considerably with motivational context. The present study investigated the neural structures underlying context dependent evaluation. We instructed participants to choose from food menu items based on different criteria: on their anticipated taste or on ease of preparation. The aim of the manipulation was to assess which neural sites were activated during choice guided by incentive value, and which during choice based on a value-irrelevant criterion. To assess the impact of increased motivation, affect-guided choice and cognition-guided choice was compared during the sated and hungry states. During affective choice, we identified increased activity in structures representing primarily valuation and taste (medial prefrontal cortex, insula). During cognitive choice, structures showing increased activity included those implicated in suppression and conflict monitoring (lateral orbitofrontal cortex, anterior cingulate). Hunger influenced choice-related activity in the ventrolateral prefrontal cortex. Our results show that choice is associated with the use of distinct neural structures for the pursuit of different goals. Published by Elsevier Inc.

  1. Neural Mechanisms Underlying Risk and Ambiguity Attitudes.

    Science.gov (United States)

    Blankenstein, Neeltje E; Peper, Jiska S; Crone, Eveline A; van Duijvenvoorde, Anna C K

    2017-11-01

    Individual differences in attitudes to risk (a taste for risk, known probabilities) and ambiguity (a tolerance for uncertainty, unknown probabilities) differentially influence risky decision-making. However, it is not well understood whether risk and ambiguity are coded differently within individuals. Here, we tested whether individual differences in risk and ambiguity attitudes were reflected in distinct neural correlates during choice and outcome processing of risky and ambiguous gambles. To these ends, we developed a neuroimaging task in which participants ( n = 50) chose between a sure gain and a gamble, which was either risky or ambiguous, and presented decision outcomes (gains, no gains). From a separate task in which the amount, probability, and ambiguity level were varied, we estimated individuals' risk and ambiguity attitudes. Although there was pronounced neural overlap between risky and ambiguous gambling in a network typically related to decision-making under uncertainty, relatively more risk-seeking attitudes were associated with increased activation in valuation regions of the brain (medial and lateral OFC), whereas relatively more ambiguity-seeking attitudes were related to temporal cortex activation. In addition, although striatum activation was observed during reward processing irrespective of a prior risky or ambiguous gamble, reward processing after an ambiguous gamble resulted in enhanced dorsomedial PFC activation, possibly functioning as a general signal of uncertainty coding. These findings suggest that different neural mechanisms reflect individual differences in risk and ambiguity attitudes and that risk and ambiguity may impact overt risk-taking behavior in different ways.

  2. Memory Consolidation and Neural Substrate of Reward

    Directory of Open Access Journals (Sweden)

    Redolar-Ripoll, Diego

    2012-08-01

    Full Text Available The aim of this report is to analyze the relationships between reward and learning and memory processes. Different studies have described how information about rewards influences behavior and how the brain uses this reward information to control learning and memory processes. Reward nature seems to be processed in different ways by neurons in different brain structures, ranging from the detection and perception of rewards to the use of information about predicted rewards for the control of goal-directed behavior. The neural substrate underling this processing of reward information is a reliable way of improving learning and memory processes. Evidence from several studies indicates that this neural system can facilitate memory consolidation in a wide variety of learning tasks. From a molecular perspective, certain cardinal features of reward have been described as forms of memory. Studies of human addicts and studies in animal models of addiction show that chronic drug exposure produces stable changes in the brain at the cellular and molecular levels that underlie the long-lasting behavioral plasticity associated with addiction. These molecular and cellular adaptations involved in addiction are also implicated in learning and memory processes. Dopamine seems to be a critical common signal to activate different genetic mechanisms that ultimately remodel synapses and circuits. Despite memory is an active and complex process mediated by different brain areas, the neural substrate of reward is able to improve memory consolidation in a several paradigms. We believe that there are many equivalent traits between reward and learning and memory processes.

  3. 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

  4. A study of reactor monitoring method with neural network

    Energy Technology Data Exchange (ETDEWEB)

    Nabeshima, Kunihiko [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    2001-03-01

    The purpose of this study is to investigate the methodology of Nuclear Power Plant (NPP) monitoring with neural networks, which create the plant models by the learning of the past normal operation patterns. The concept of this method is to detect the symptom of small anomalies by monitoring the deviations between the process signals measured from an actual plant and corresponding output signals from the neural network model, which might not be equal if the abnormal operational patterns are presented to the input of the neural network. Auto-associative network, which has same output as inputs, can detect an kind of anomaly condition by using normal operation data only. The monitoring tests of the feedforward neural network with adaptive learning were performed using the PWR plant simulator by which many kinds of anomaly conditions can be easily simulated. The adaptively trained feedforward network could follow the actual plant dynamics and the changes of plant condition, and then find most of the anomalies much earlier than the conventional alarm system during steady state and transient operations. Then the off-line and on-line test results during one year operation at the actual NPP (PWR) showed that the neural network could detect several small anomalies which the operators or the conventional alarm system didn't noticed. Furthermore, the sensitivity analysis suggests that the plant models by neural networks are appropriate. Finally, the simulation results show that the recurrent neural network with feedback connections could successfully model the slow behavior of the reactor dynamics without adaptive learning. Therefore, the recurrent neural network with adaptive learning will be the best choice for the actual reactor monitoring system. (author)

  5. Determining the confidence levels of sensor outputs using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Broten, G S; Wood, H C [Saskatchewan Univ., Saskatoon, SK (Canada). Dept. of Electrical Engineering

    1996-12-31

    This paper describes an approach for determining the confidence level of a sensor output using multi-sensor arrays, sensor fusion and artificial neural networks. The authors have shown in previous work that sensor fusion and artificial neural networks can be used to learn the relationships between the outputs of an array of simulated partially selective sensors and the individual analyte concentrations in a mixture of analyses. Other researchers have shown that an array of partially selective sensors can be used to determine the individual gas concentrations in a gaseous mixture. The research reported in this paper shows that it is possible to extract confidence level information from an array of partially selective sensors using artificial neural networks. The confidence level of a sensor output is defined as a numeric value, ranging from 0% to 100%, that indicates the confidence associated with a output of a given sensor. A three layer back-propagation neural network was trained on a subset of the sensor confidence level space, and was tested for its ability to generalize, where the confidence level space is defined as all possible deviations from the correct sensor output. A learning rate of 0.1 was used and no momentum terms were used in the neural network. This research has shown that an artificial neural network can accurately estimate the confidence level of individual sensors in an array of partially selective sensors. This research has also shown that the neural network`s ability to determine the confidence level is influenced by the complexity of the sensor`s response and that the neural network is able to estimate the confidence levels even if more than one sensor is in error. The fundamentals behind this research could be applied to other configurations besides arrays of partially selective sensors, such as an array of sensors separated spatially. An example of such a configuration could be an array of temperature sensors in a tank that is not in

  6. Anti-synchronization control of BAM memristive neural networks with multiple proportional delays and stochastic perturbations

    Science.gov (United States)

    Wang, Weiping; Yuan, Manman; Luo, Xiong; Liu, Linlin; Zhang, Yao

    2018-01-01

    Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.

  7. Program Helps Simulate Neural Networks

    Science.gov (United States)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  8. Artificial Neural Network Analysis System

    Science.gov (United States)

    2001-02-27

    Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis

  9. Cooperating attackers in neural cryptography.

    Science.gov (United States)

    Shacham, Lanir N; Klein, Einat; Mislovaty, Rachel; Kanter, Ido; Kinzel, Wolfgang

    2004-06-01

    A successful attack strategy in neural cryptography is presented. The neural cryptosystem, based on synchronization of neural networks by mutual learning, has been recently shown to be secure under different attack strategies. The success of the advanced attacker presented here, called the "majority-flipping attacker," does not decay with the parameters of the model. This attacker's outstanding success is due to its using a group of attackers which cooperate throughout the synchronization process, unlike any other attack strategy known. An analytical description of this attack is also presented, and fits the results of simulations.

  10. Preserving information in neural transmission.

    Science.gov (United States)

    Sincich, Lawrence C; Horton, Jonathan C; Sharpee, Tatyana O

    2009-05-13

    Along most neural pathways, the spike trains transmitted from one neuron to the next are altered. In the process, neurons can either achieve a more efficient stimulus representation, or extract some biologically important stimulus parameter, or succeed at both. We recorded the inputs from single retinal ganglion cells and the outputs from connected lateral geniculate neurons in the macaque to examine how visual signals are relayed from retina to cortex. We found that geniculate neurons re-encoded multiple temporal stimulus features to yield output spikes that carried more information about stimuli than was available in each input spike. The coding transformation of some relay neurons occurred with no decrement in information rate, despite output spike rates that averaged half the input spike rates. This preservation of transmitted information was achieved by the short-term summation of inputs that geniculate neurons require to spike. A reduced model of the retinal and geniculate visual responses, based on two stimulus features and their associated nonlinearities, could account for >85% of the total information available in the spike trains and the preserved information transmission. These results apply to neurons operating on a single time-varying input, suggesting that synaptic temporal integration can alter the temporal receptive field properties to create a more efficient representation of visual signals in the thalamus than the retina.

  11. Neural correlates of pediatric obesity.

    Science.gov (United States)

    Bruce, Amanda S; Martin, Laura E; Savage, Cary R

    2011-06-01

    Childhood obesity rates have increased over the last 40 years and have a detrimental impact on public health. While the causes of the obesity epidemic are complex, obesity ultimately arises from chronic imbalances between energy intake and expenditure. An emerging area of research in obesity has focused on the role of the brain in evaluating the rewarding properties of food and making decisions about what and how much to eat. This article reviews recent scientific literature regarding the brain's role in pediatric food motivation and childhood obesity. The article will begin by reviewing some of the recent literature discussing challenges associated with neuroimaging in children and the relevant developmental brain changes that occur in childhood and adolescence. The article will then review studies regarding neural mechanisms of food motivation and the ability to delay gratification in children and how these responses differ in obese compared to healthy weight children. Increasing our understanding about how brain function and behavior may differ in children will inform future research, obesity prevention, and interventions targeting childhood obesity. Copyright © 2011. Published by Elsevier Inc.

  12. 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.

  13. Creative-Dynamics Approach To Neural Intelligence

    Science.gov (United States)

    Zak, Michail A.

    1992-01-01

    Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

  14. Parameter extraction with neural networks

    Science.gov (United States)

    Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

    1998-06-01

    In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs

  15. Existence and exponential stability of almost periodic solution for Hopfield-type neural networks with impulse

    International Nuclear Information System (INIS)

    Zhang Huiying; Xia Yonghui

    2008-01-01

    In this paper, some sufficient conditions are obtained for checking the existence and exponential stability of almost periodic solution for bidirectional associative memory Hopfield-type neural networks with impulse. The approaches are based on contraction principle and Gronwall-Bellman's inequality. This paper is considering the almost periodic solution for impulsive Hopfield-type neural networks

  16. A Decline in Response Variability Improves Neural Signal Detection during Auditory Task Performance.

    Science.gov (United States)

    von Trapp, Gardiner; Buran, Bradley N; Sen, Kamal; Semple, Malcolm N; Sanes, Dan H

    2016-10-26

    The detection of a sensory stimulus arises from a significant change in neural activity, but a sensory neuron's response is rarely identical to successive presentations of the same stimulus. Large trial-to-trial variability would limit the central nervous system's ability to reliably detect a stimulus, presumably affecting perceptual performance. However, if response variability were to decrease while firing rate remained constant, then neural sensitivity could improve. Here, we asked whether engagement in an auditory detection task can modulate response variability, thereby increasing neural sensitivity. We recorded telemetrically from the core auditory cortex of gerbils, both while they engaged in an amplitude-modulation detection task and while they sat quietly listening to the identical stimuli. Using a signal detection theory framework, we found that neural sensitivity was improved during task performance, and this improvement was closely associated with a decrease in response variability. Moreover, units with the greatest change in response variability had absolute neural thresholds most closely aligned with simultaneously measured perceptual thresholds. Our findings suggest that the limitations imposed by response variability diminish during task performance, thereby improving the sensitivity of neural encoding and potentially leading to better perceptual sensitivity. The detection of a sensory stimulus arises from a significant change in neural activity. However, trial-to-trial variability of the neural response may limit perceptual performance. If the neural response to a stimulus is quite variable, then the response on a given trial could be confused with the pattern of neural activity generated when the stimulus is absent. Therefore, a neural mechanism that served to reduce response variability would allow for better stimulus detection. By recording from the cortex of freely moving animals engaged in an auditory detection task, we found that variability

  17. EDITORIAL: Why we need a new journal in neural engineering

    Science.gov (United States)

    Durand, Dominique M.

    2004-03-01

    revolutionary change in the quality of life of persons with sensory and/or motor deficits. Microelectrode technology represents the initial step towards this goal and has already improved the quality of life of many patients, as is evident from the success of auditory prostheses. The cost to society of neurological disorders such as stroke, Parkinson's disease, Alzheimer's disease and epilepsy is staggering. Stroke, which is the third leading cause of death in North America, runs up costs of 40 billion to society per year for its treatment. Costs associated with brain disorders are estimated at 285 billion. Breakthroughs in this field will have a significant impact on the market for enabling technologies. The market for neurological medical devices totaled 2 billion in 1999 and is projected to grow at a rate of 20 to 30% in the next ten years, far outpacing the market for cardiac devices. Although we have all recognized the importance of interdisciplinary research (see the NIH Road map at http://nihroadmap.nih.gov/), the fields of neuroscience and engineering have remained compartmentalized. Collaboration is still difficult since the language of these disciplines is different. Moreover, the scientific journals in these fields are also clearly separate. Researchers involved in neural engineering have a choice of publishing their research in either neuroscience-oriented journals such as Journal of Neuroscience, Journal of Neurophysiology and Brain Research or in engineering journals such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation and Annals of Biomedical Engineering. There is no journal currently available focusing on the interdisciplinary field of neural engineering. In order to capitalize on the potential of neural engineering to investigate neural function and to solve problems related to neural disorders, it is necessary to break down the traditional barriers between neuroscientists and engineers not just in the

  18. The Neural Correlates of Humor Creativity.

    Science.gov (United States)

    Amir, Ori; Biederman, Irving

    2016-01-01

    Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product's quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur "improv" comedians and controls viewed New Yorker cartoon drawings while being scanned. For each drawing, they were instructed to generate either a humorous or a mundane caption. Greater comedic experience was associated with decreased activation in the striatum and medial prefrontal cortex (mPFC), but increased activation in temporal association regions (TMP). Less experienced comedians manifested greater activation of mPFC, reflecting their deliberate search through TMP association space. Professionals, by contrast, tend to reap the fruits of their spontaneous associations with reduced reliance on top-down guided search.

  19. The Neural Correlates of Humor Creativity

    Directory of Open Access Journals (Sweden)

    Ori Amir

    2016-11-01

    Full Text Available Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product’s quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur improv comedians and controls viewed New Yorker cartoon drawings while being scanned. For each drawing, they were instructed to generate either a humorous or a mundane caption. Greater comedic experience was associated with decreased activation in the striatum and medial prefrontal cortex (mPFC, but increased activation in temporal association regions (TMP. Less experienced comedians manifested greater activation of mPFC, reflecting their deliberate search through TMP association space. Professionals, by contrast, tend to reap the fruits of their spontaneous associations with reduced reliance on top-down guided search.

  20. The Neural Correlates of Humor Creativity

    Science.gov (United States)

    Amir, Ori; Biederman, Irving

    2016-01-01

    Unlike passive humor appreciation, the neural correlates of real-time humor creation have been unexplored. As a case study for creativity, humor generation uniquely affords a reliable assessment of a creative product’s quality with a clear and relatively rapid beginning and end, rendering it amenable to neuroimaging that has the potential for reflecting individual differences in expertise. Professional and amateur “improv” comedians and controls viewed New Yorker cartoon drawings while being scanned. For each drawing, they were instructed to generate either a humorous or a mundane caption. Greater comedic experience was associated with decreased activation in the striatum and medial prefrontal cortex (mPFC), but increased activation in temporal association regions (TMP). Less experienced comedians manifested greater activation of mPFC, reflecting their deliberate search through TMP association space. Professionals, by contrast, tend to reap the fruits of their spontaneous associations with reduced reliance on top-down guided search. PMID:27932965

  1. 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.

  2. Functional neural networks underlying response inhibition in adolescents and adults.

    Science.gov (United States)

    Stevens, Michael C; Kiehl, Kent A; Pearlson, Godfrey D; Calhoun, Vince D

    2007-07-19

    This study provides the first description of neural network dynamics associated with response inhibition in healthy adolescents and adults. Functional and effective connectivity analyses of whole brain hemodynamic activity elicited during performance of a Go/No-Go task were used to identify functionally integrated neural networks and characterize their causal interactions. Three response inhibition circuits formed a hierarchical, inter-dependent system wherein thalamic modulation of input to premotor cortex by fronto-striatal regions led to response suppression. Adolescents differed from adults in the degree of network engagement, regional fronto-striatal-thalamic connectivity, and network dynamics. We identify and characterize several age-related differences in the function of neural circuits that are associated with behavioral performance changes across adolescent development.

  3. Racial bias in neural empathic responses to pain.

    Directory of Open Access Journals (Sweden)

    Luis Sebastian Contreras-Huerta

    Full Text Available Recent studies have shown that perceiving the pain of others activates brain regions in the observer associated with both somatosensory and affective-motivational aspects of pain, principally involving regions of the anterior cingulate and anterior insula cortex. The degree of these empathic neural responses is modulated by racial bias, such that stronger neural activation is elicited by observing pain in people of the same racial group compared with people of another racial group. The aim of the present study was to examine whether a more general social group category, other than race, could similarly modulate neural empathic responses and perhaps account for the apparent racial bias reported in previous studies. Using a minimal group paradigm, we assigned participants to one of two mixed-race teams. We use the term race to refer to the Chinese or Caucasian appearance of faces and whether the ethnic group represented was the same or different from the appearance of the participant' own face. Using fMRI, we measured neural empathic responses as participants observed members of their own group or other group, and members of their own race or other race, receiving either painful or non-painful touch. Participants showed clear group biases, with no significant effect of race, on behavioral measures of implicit (affective priming and explicit group identification. Neural responses to observed pain in the anterior cingulate cortex, insula cortex, and somatosensory areas showed significantly greater activation when observing pain in own-race compared with other-race individuals, with no significant effect of minimal groups. These results suggest that racial bias in neural empathic responses is not influenced by minimal forms of group categorization, despite the clear association participants showed with in-group more than out-group members. We suggest that race may be an automatic and unconscious mechanism that drives the initial neural responses to

  4. Racial Bias in Neural Empathic Responses to Pain

    Science.gov (United States)

    Contreras-Huerta, Luis Sebastian; Baker, Katharine S.; Reynolds, Katherine J.; Batalha, Luisa; Cunnington, Ross

    2013-01-01

    Recent studies have shown that perceiving the pain of others activates brain regions in the observer associated with both somatosensory and affective-motivational aspects of pain, principally involving regions of the anterior cingulate and anterior insula cortex. The degree of these empathic neural responses is modulated by racial bias, such that stronger neural activation is elicited by observing pain in people of the same racial group compared with people of another racial group. The aim of the present study was to examine whether a more general social group category, other than race, could similarly modulate neural empathic responses and perhaps account for the apparent racial bias reported in previous studies. Using a minimal group paradigm, we assigned participants to one of two mixed-race teams. We use the term race to refer to the Chinese or Caucasian appearance of faces and whether the ethnic group represented was the same or different from the appearance of the participant' own face. Using fMRI, we measured neural empathic responses as participants observed members of their own group or other group, and members of their own race or other race, receiving either painful or non-painful touch. Participants showed clear group biases, with no significant effect of race, on behavioral measures of implicit (affective priming) and explicit group identification. Neural responses to observed pain in the anterior cingulate cortex, insula cortex, and somatosensory areas showed significantly greater activation when observing pain in own-race compared with other-race individuals, with no significant effect of minimal groups. These results suggest that racial bias in neural empathic responses is not influenced by minimal forms of group categorization, despite the clear association participants showed with in-group more than out-group members. We suggest that race may be an automatic and unconscious mechanism that drives the initial neural responses to observed pain in

  5. Neural components of altruistic punishment

    Directory of Open Access Journals (Sweden)

    Emily eDu

    2015-02-01

    Full Text Available Altruistic punishment, which occurs when an individual incurs a cost to punish in response to unfairness or a norm violation, may play a role in perpetuating cooperation. The neural correlates underlying costly punishment have only recently begun to be explored. Here we review the current state of research on the neural basis of altruism from the perspectives of costly punishment, emphasizing the importance of characterizing elementary neural processes underlying a decision to punish. In particular, we emphasize three cognitive processes that contribute to the decision to altruistically punish in most scenarios: inequity aversion, cost-benefit calculation, and social reference frame to distinguish self from others. Overall, we argue for the importance of understanding the neural correlates of altruistic punishment with respect to the core computations necessary to achieve a decision to punish.

  6. Neural complexity, dissociation, and schizophrenia

    Czech Academy of Sciences Publication Activity Database

    Bob, P.; Šusta, M.; Chládek, Jan; Glaslová, K.; Fedor-Ferybergh, P.

    2007-01-01

    Roč. 13, č. 10 (2007), HY1-5 ISSN 1234-1010 Institutional research plan: CEZ:AV0Z20650511 Keywords : neural complexity * dissociation * schizophrenia Subject RIV: FH - Neurology Impact factor: 1.607, year: 2007

  7. Neural Networks in Control Applications

    DEFF Research Database (Denmark)

    Sørensen, O.

    The intention of this report is to make a systematic examination of the possibilities of applying neural networks in those technical areas, which are familiar to a control engineer. In other words, the potential of neural networks in control applications is given higher priority than a detailed...... study of the networks themselves. With this end in view the following restrictions have been made: - Amongst numerous neural network structures, only the Multi Layer Perceptron (a feed-forward network) is applied. - Amongst numerous training algorithms, only four algorithms are examined, all...... in a recursive form (sample updating). The simplest is the Back Probagation Error Algorithm, and the most complex is the recursive Prediction Error Method using a Gauss-Newton search direction. - Over-fitting is often considered to be a serious problem when training neural networks. This problem is specifically...

  8. Complex-Valued Neural Networks

    CERN Document Server

    Hirose, Akira

    2012-01-01

    This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...

  9. Artificial intelligence: Deep neural reasoning

    Science.gov (United States)

    Jaeger, Herbert

    2016-10-01

    The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471

  10. Optical Neural Network Classifier Architectures

    National Research Council Canada - National Science Library

    Getbehead, Mark

    1998-01-01

    We present an adaptive opto-electronic neural network hardware architecture capable of exploiting parallel optics to realize real-time processing and classification of high-dimensional data for Air...

  11. Memristor-based neural networks

    International Nuclear Information System (INIS)

    Thomas, Andy

    2013-01-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them. (topical review)

  12. Review of the Neural Oscillations Underlying Meditation

    Directory of Open Access Journals (Sweden)

    Darrin J. Lee

    2018-03-01

    Full Text Available Objective: Meditation is one type of mental training that has been shown to produce many cognitive benefits. Meditation practice is associated with improvement in concentration and reduction of stress, depression, and anxiety symptoms. Furthermore, different forms of meditation training are now being used as interventions for a variety of psychological and somatic illnesses. These benefits are thought to occur as a result of neurophysiologic changes. The most commonly studied specific meditation practices are focused attention (FA, open-monitoring (OM, as well as transcendental meditation (TM, and loving-kindness (LK meditation. In this review, we compare the neural oscillatory patterns during these forms of meditation.Method: We performed a systematic review of neural oscillations during FA, OM, TM, and LK meditation practices, comparing meditators to meditation-naïve adults.Results: FA, OM, TM, and LK meditation are associated with global increases in oscillatory activity in meditators compared to meditation-naïve adults, with larger changes occurring as the length of meditation training increases. While FA and OM are related to increases in anterior theta activity, only FA is associated with changes in posterior theta oscillations. Alpha activity increases in posterior brain regions during both FA and OM. In anterior regions, FA shows a bilateral increase in alpha power, while OM shows a decrease only in left-sided power. Gamma activity in these meditation practices is similar in frontal regions, but increases are variable in parietal and occipital regions.Conclusions: The current literature suggests distinct differences in neural oscillatory activity among FA, OM, TM, and LK meditation practices. Further characterizing these oscillatory changes may better elucidate the cognitive and therapeutic effects of specific meditation practices, and potentially lead to the development of novel neuromodulation targets to take advantage of their

  13. Sequential neural models with stochastic layers

    DEFF Research Database (Denmark)

    Fraccaro, Marco; Sønderby, Søren Kaae; Paquet, Ulrich

    2016-01-01

    How can we efficiently propagate uncertainty in a latent state representation with recurrent neural networks? This paper introduces stochastic recurrent neural networks which glue a deterministic recurrent neural network and a state space model together to form a stochastic and sequential neural...... generative model. The clear separation of deterministic and stochastic layers allows a structured variational inference network to track the factorization of the model's posterior distribution. By retaining both the nonlinear recursive structure of a recurrent neural network and averaging over...

  14. Implantable Neural Interfaces for Sharks

    Science.gov (United States)

    2007-05-01

    technology for recording and stimulating from the auditory and olfactory sensory nervous systems of the awake, swimming nurse shark , G. cirratum (Figures...overlay of the central nervous system of the nurse shark on a horizontal MR image. Implantable Neural Interfaces for Sharks ...Neural Interfaces for Characterizing Population Responses to Odorants and Electrical Stimuli in the Nurse Shark , Ginglymostoma cirratum.” AChemS Abs

  15. What are artificial neural networks?

    DEFF Research Database (Denmark)

    Krogh, Anders

    2008-01-01

    Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb......Artificial neural networks have been applied to problems ranging from speech recognition to prediction of protein secondary structure, classification of cancers and gene prediction. How do they work and what might they be good for? Udgivelsesdato: 2008-Feb...

  16. Neurally mediated syncope in electroconvulsive therapy maintenance.

    Science.gov (United States)

    Arbaizar, Beatriz; Llorca, Javier

    2012-03-01

    Electroconvulsive therapy (ECT) is especially necessary to revert some types of depressive disease; nevertheless, it has some widely recognized adverse effects, such as short-term memory loss. Moreover, some articles have reported its potential association with falls; this literature is, however, scanty and mainly consists of case reports. We present the case of a man who has a diagnosis of neurally mediated syncope at the age of 79 years, during the maintenance ECT. The patient had a significant increase in syncope frequency in the period he was treated with ECT, followed by a dramatic decrease when ECT was discontinued.

  17. Realistic thermodynamic and statistical-mechanical measures for neural synchronization.

    Science.gov (United States)

    Kim, Sang-Yoon; Lim, Woochang

    2014-04-15

    Synchronized brain rhythms, associated with diverse cognitive functions, have been observed in electrical recordings of brain activity. Neural synchronization may be well described by using the population-averaged global potential VG in computational neuroscience. The time-averaged fluctuation of VG plays the role of a "thermodynamic" order parameter O used for describing the synchrony-asynchrony transition in neural systems. Population spike synchronization may be well visualized in the raster plot of neural spikes. The degree of neural synchronization seen in the raster plot is well measured in terms of a "statistical-mechanical" spike-based measure Ms introduced by considering the occupation and the pacing patterns of spikes. The global potential VG is also used to give a reference global cycle for the calculation of Ms. Hence, VG becomes an important collective quantity because it is associated with calculation of both O and Ms. However, it is practically difficult to directly get VG in real experiments. To overcome this difficulty, instead of VG, we employ the instantaneous population spike rate (IPSR) which can be obtained in experiments, and develop realistic thermodynamic and statistical-mechanical measures, based on IPSR, to make practical characterization of the neural synchronization in both computational and experimental neuroscience. Particularly, more accurate characterization of weak sparse spike synchronization can be achieved in terms of realistic statistical-mechanical IPSR-based measure, in comparison with the conventional measure based on VG. Copyright © 2014. Published by Elsevier B.V.

  18. Neural correlates of hate.

    Directory of Open Access Journals (Sweden)

    Semir Zeki

    Full Text Available In this work, we address an important but unexplored topic, namely the neural correlates of hate. In a block-design fMRI study, we scanned 17 normal human subjects while they viewed the face of a person they hated and also faces of acquaintances for whom they had neutral feelings. A hate score was obtained for the object of hate for each subject and this was used as a covariate in a between-subject random effects analysis. Viewing a hated face resulted in increased activity in the medial frontal gyrus, right putamen, bilaterally in premotor cortex, in the frontal pole and bilaterally in the medial insula. We also found three areas where activation correlated linearly with the declared level of hatred, the right insula, right premotor cortex and the right fronto-medial gyrus. One area of deactivation was found in the right superior frontal gyrus. The study thus shows that there is a unique pattern of activity in the brain in the context of hate. Though distinct from the pattern of activity that correlates with romantic love, this pattern nevertheless shares two areas with the latter, namely the putamen and the insula.

  19. neural control system

    International Nuclear Information System (INIS)

    Elshazly, A.A.E.

    2002-01-01

    Automatic power stabilization control is the desired objective for any reactor operation , especially, nuclear power plants. A major problem in this area is inevitable gap between a real plant ant the theory of conventional analysis and the synthesis of linear time invariant systems. in particular, the trajectory tracking control of a nonlinear plant is a class of problems in which the classical linear transfer function methods break down because no transfer function can represent the system over the entire operating region . there is a considerable amount of research on the model-inverse approach using feedback linearization technique. however, this method requires a prices plant model to implement the exact linearizing feedback, for nuclear reactor systems, this approach is not an easy task because of the uncertainty in the plant parameters and un-measurable state variables . therefore, artificial neural network (ANN) is used either in self-tuning control or in improving the conventional rule-based exper system.the main objective of this thesis is to suggest an ANN, based self-learning controller structure . this method is capable of on-line reinforcement learning and control for a nuclear reactor with a totally unknown dynamics model. previously, researches are based on back- propagation algorithm . back -propagation (BP), fast back -propagation (FBP), and levenberg-marquardt (LM), algorithms are discussed and compared for reinforcement learning. it is found that, LM algorithm is quite superior

  20. The Neural Baroreflex Pathway in Subjects With Metabolic Syndrome

    OpenAIRE

    Zanoli, Luca; Empana, Jean-Philippe; Estrugo, Nicolas; Escriou, Guillaume; Ketthab, Hakim; Pruny, Jean-Francois; Castellino, Pietro; Laude, Dominique; Thomas, Frederique; Pannier, Bruno; Jouven, Xavier; Boutouyrie, Pierre; Laurent, Stephane

    2016-01-01

    Abstract The mechanisms that link metabolic syndrome (MetS) to increased cardiovascular risk are incompletely understood. We examined whether MetS is associated with the neural baroreflex pathway (NBP) and whether any such associations are independent of blood pressure values. This study involved the cross-sectional analysis of data on 2835 subjects aged 50 to 75 years from the Paris Prospective Study 3. The prevalence of MetS was defined according to the American Heart Association/National H...

  1. Neural basis for generalized quantifier comprehension.

    Science.gov (United States)

    McMillan, Corey T; Clark, Robin; Moore, Peachie; Devita, Christian; Grossman, Murray

    2005-01-01

    Generalized quantifiers like "all cars" are semantically well understood, yet we know little about their neural representation. Our model of quantifier processing includes a numerosity device, operations that combine number elements and working memory. Semantic theory posits two types of quantifiers: first-order quantifiers identify a number state (e.g. "at least 3") and higher-order quantifiers additionally require maintaining a number state actively in working memory for comparison with another state (e.g. "less than half"). We used BOLD fMRI to test the hypothesis that all quantifiers recruit inferior parietal cortex associated with numerosity, while only higher-order quantifiers recruit prefrontal cortex associated with executive resources like working memory. Our findings showed that first-order and higher-order quantifiers both recruit right inferior parietal cortex, suggesting that a numerosity component contributes to quantifier comprehension. Moreover, only probes of higher-order quantifiers recruited right dorsolateral prefrontal cortex, suggesting involvement of executive resources like working memory. We also observed activation of thalamus and anterior cingulate that may be associated with selective attention. Our findings are consistent with a large-scale neural network centered in frontal and parietal cortex that supports comprehension of generalized quantifiers.

  2. 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.

  3. Leader emergence through interpersonal neural synchronization.

    Science.gov (United States)

    Jiang, Jing; Chen, Chuansheng; Dai, Bohan; Shi, Guang; Ding, Guosheng; Liu, Li; Lu, Chunming

    2015-04-07

    The neural mechanism of leader emergence is not well understood. This study investigated (i) whether interpersonal neural synchronization (INS) plays an important role in leader emergence, and (ii) whether INS and leader emergence are associated with the frequency or the quality of communications. Eleven three-member groups were asked to perform a leaderless group discussion (LGD) task, and their brain activities were recorded via functional near infrared spectroscopy (fNIRS)-based hyperscanning. Video recordings of the discussions were coded for leadership and communication. Results showed that the INS for the leader-follower (LF) pairs was higher than that for the follower-follower (FF) pairs in the left temporo-parietal junction (TPJ), an area important for social mentalizing. Although communication frequency was higher for the LF pairs than for the FF pairs, the frequency of leader-initiated and follower-initiated communication did not differ significantly. Moreover, INS for the LF pairs was significantly higher during leader-initiated communication than during follower-initiated communications. In addition, INS for the LF pairs during leader-initiated communication was significantly correlated with the leaders' communication skills and competence, but not their communication frequency. Finally, leadership could be successfully predicted based on INS as well as communication frequency early during the LGD (before half a minute into the task). In sum, this study found that leader emergence was characterized by high-level neural synchronization between the leader and followers and that the quality, rather than the frequency, of communications was associated with synchronization. These results suggest that leaders emerge because they are able to say the right things at the right time.

  4. 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.

  5. 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.

  6. 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.

  7. A novel neural-wavelet approach for process diagnostics and complex system modeling

    Science.gov (United States)

    Gao, Rong

    Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

  8. Neural networks prove effective at NO{sub x} reduction

    Energy Technology Data Exchange (ETDEWEB)

    Radl, B.J. [Pegasus Technologies, Mentor, OH (United States)

    2000-05-01

    The virtues of the Pegasus NeuSIGHT combustion optimisation software are extolled. It has been installed at more than 25 power plants and operates mostly in closed loop control. The software uses the leading neural network technology from Computer associates. The system is said to reduce emissions of nitrogen oxides, increase plant efficiency and has the potential for saving millions of dollars in capital and operating costs. The value of the system is illustrated by case studies from three coal-fired power plants. The meaning of 'neural network' is explained.

  9. 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.

  10. Exponential stability of neural networks with asymmetric connection weights

    International Nuclear Information System (INIS)

    Yang Jinxiang; Zhong Shouming

    2007-01-01

    This paper investigates the exponential stability of a class of neural networks with asymmetric connection weights. By dividing the network state variables into various parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Lyapunov function and using the method of the variation of constant. The new conditions are associated with the initial values and are described by some blocks of the interconnection matrix, and do not depend on other blocks. Examples are given to further illustrate the theory

  11. Inhibition delay increases neural network capacity through Stirling transform

    Science.gov (United States)

    Nogaret, Alain; King, Alastair

    2018-03-01

    Inhibitory neural networks are found to encode high volumes of information through delayed inhibition. We show that inhibition delay increases storage capacity through a Stirling transform of the minimum capacity which stabilizes locally coherent oscillations. We obtain both the exact and asymptotic formulas for the total number of dynamic attractors. Our results predict a (ln2) -N-fold increase in capacity for an N -neuron network and demonstrate high-density associative memories which host a maximum number of oscillations in analog neural devices.

  12. Neural network regulation driven by autonomous neural firings

    Science.gov (United States)

    Cho, Myoung Won

    2016-07-01

    Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

  13. Inactivity-induced phrenic and hypoglossal motor facilitation are differentially expressed following intermittent vs. sustained neural apnea

    Science.gov (United States)

    Baertsch, N. A.

    2013-01-01

    Reduced respiratory neural activity elicits a rebound increase in phrenic and hypoglossal motor output known as inactivity-induced phrenic and hypoglossal motor facilitation (iPMF and iHMF, respectively). We hypothesized that, similar to other forms of respiratory plasticity, iPMF and iHMF are pattern sensitive. Central respiratory neural activity was reversibly reduced in ventilated rats by hyperventilating below the CO2 apneic threshold to create brief intermittent neural apneas (5, ∼1.5 min each, separated by 5 min), a single brief massed neural apnea (7.5 min), or a single prolonged neural apnea (30 min). Upon restoration of respiratory neural activity, long-lasting (>60 min) iPMF was apparent following brief intermittent and prolonged, but not brief massed, neural apnea. Further, brief intermittent and prolonged neural apnea elicited an increase in the maximum phrenic response to high CO2, suggesting that iPMF is associated with an increase in phrenic dynamic range. By contrast, only prolonged neural apnea elicited iHMF, which was transient in duration (<15 min). Intermittent, massed, and prolonged neural apnea all elicited a modest transient facilitation of respiratory frequency. These results indicate that iPMF, but not iHMF, is pattern sensitive, and that the response to respiratory neural inactivity is motor pool specific. PMID:23493368

  14. Neural correlates of eating disorders: translational potential

    Directory of Open Access Journals (Sweden)

    McAdams CJ

    2015-09-01

    Full Text Available Carrie J McAdams,1,2 Whitney Smith1 1University of Texas at Southwestern Medical Center, 2Department of Psychiatry, Texas Health Presbyterian Hospital of Dallas, Dallas, TX, USA Abstract: Eating disorders are complex and serious psychiatric illnesses whose etiology includes psychological, biological, and social factors. Treatment of eating disorders is challenging as there are few evidence-based treatments and limited understanding of the mechanisms that result in sustained recovery. In the last 20 years, we have begun to identify neural pathways that are altered in eating disorders. Consideration of how these pathways may contribute to an eating disorder can provide an understanding of expected responses to treatments. Eating disorder behaviors include restrictive eating, compulsive overeating, and purging behaviors after eating. Eating disorders are associated with changes in many neural systems. In this targeted review, we focus on three cognitive processes associated with neurocircuitry differences in subjects with eating disorders such as reward, decision-making, and social behavior. We briefly examine how each of these systems function in healthy people, using Neurosynth meta-analysis to identify key regions commonly implicated in these circuits. We review the evidence for disruptions of these regions and systems in eating disorders. Finally, we describe psychiatric and psychological treatments that are likely to function by impacting these regions. Keywords: anorexia nervosa, bulimia nervosa, social cognition, reward processing, decision-making

  15. Noise-enhanced categorization in a recurrently reconnected neural network

    International Nuclear Information System (INIS)

    Monterola, Christopher; Zapotocky, Martin

    2005-01-01

    We investigate the interplay of recurrence and noise in neural networks trained to categorize spatial patterns of neural activity. We develop the following procedure to demonstrate how, in the presence of noise, the introduction of recurrence permits to significantly extend and homogenize the operating range of a feed-forward neural network. We first train a two-level perceptron in the absence of noise. Following training, we identify the input and output units of the feed-forward network, and thus convert it into a two-layer recurrent network. We show that the performance of the reconnected network has features reminiscent of nondynamic stochastic resonance: the addition of noise enables the network to correctly categorize stimuli of subthreshold strength, with optimal noise magnitude significantly exceeding the stimulus strength. We characterize the dynamics leading to this effect and contrast it to the behavior of a more simple associative memory network in which noise-mediated categorization fails

  16. Noise-enhanced categorization in a recurrently reconnected neural network

    Science.gov (United States)

    Monterola, Christopher; Zapotocky, Martin

    2005-03-01

    We investigate the interplay of recurrence and noise in neural networks trained to categorize spatial patterns of neural activity. We develop the following procedure to demonstrate how, in the presence of noise, the introduction of recurrence permits to significantly extend and homogenize the operating range of a feed-forward neural network. We first train a two-level perceptron in the absence of noise. Following training, we identify the input and output units of the feed-forward network, and thus convert it into a two-layer recurrent network. We show that the performance of the reconnected network has features reminiscent of nondynamic stochastic resonance: the addition of noise enables the network to correctly categorize stimuli of subthreshold strength, with optimal noise magnitude significantly exceeding the stimulus strength. We characterize the dynamics leading to this effect and contrast it to the behavior of a more simple associative memory network in which noise-mediated categorization fails.

  17. 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.

  18. 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.

  19. 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.

  20. Unfolding code for neutron spectrometry based on neural nets technology

    International Nuclear Information System (INIS)

    Ortiz R, J. M.; Vega C, H. R.

    2012-10-01

    The most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral information is not simple because the unknown is not given directly as a result of the measurements. The drawbacks associated with traditional unfolding procedures have motivated the need of complementary approaches. Novel methods based on Artificial Neural Networks have been widely investigated. In this work, a neutron spectrum unfolding code based on neural nets technology is presented. This unfolding code called Neutron Spectrometry and Dosimetry by means of Artificial Neural Networks was designed in a graphical interface under LabVIEW programming environment. The core of the code is an embedded neural network architecture, previously optimized by the R obust Design of Artificial Neural Networks Methodology . The main features of the code are: is easy to use, friendly and intuitive to the user. This code was designed for a Bonner Sphere System based on a 6 Lil(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. The main feature of the code is that as entrance data, only seven rate counts measurement with a Bonner spheres spectrometer are required for simultaneously unfold the 60 energy bins of the neutron spectrum and to calculate 15 dosimetric quantities, for radiation protection porpoises. This code generates a full report in html format with all relevant information. (Author)

  1. Unfolding code for neutron spectrometry based on neural nets technology

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz R, J. M.; Vega C, H. R., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Unidad Academica de Ingenieria Electrica, Apdo. Postal 336, 98000 Zacatecas (Mexico)

    2012-10-15

    The most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral information is not simple because the unknown is not given directly as a result of the measurements. The drawbacks associated with traditional unfolding procedures have motivated the need of complementary approaches. Novel methods based on Artificial Neural Networks have been widely investigated. In this work, a neutron spectrum unfolding code based on neural nets technology is presented. This unfolding code called Neutron Spectrometry and Dosimetry by means of Artificial Neural Networks was designed in a graphical interface under LabVIEW programming environment. The core of the code is an embedded neural network architecture, previously optimized by the {sup R}obust Design of Artificial Neural Networks Methodology{sup .} The main features of the code are: is easy to use, friendly and intuitive to the user. This code was designed for a Bonner Sphere System based on a {sup 6}Lil(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. The main feature of the code is that as entrance data, only seven rate counts measurement with a Bonner spheres spectrometer are required for simultaneously unfold the 60 energy bins of the neutron spectrum and to calculate 15 dosimetric quantities, for radiation protection porpoises. This code generates a full report in html format with all relevant information. (Author)

  2. 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.

  3. Learning-induced neural plasticity of speech processing before birth.

    Science.gov (United States)

    Partanen, Eino; Kujala, Teija; Näätänen, Risto; Liitola, Auli; Sambeth, Anke; Huotilainen, Minna

    2013-09-10

    Learning, the foundation of adaptive and intelligent behavior, is based on plastic changes in neural assemblies, reflected by the modulation of electric brain responses. In infancy, auditory learning implicates the formation and strengthening of neural long-term memory traces, improving discrimination skills, in particular those forming the prerequisites for speech perception and understanding. Although previous behavioral observations show that newborns react differentially to unfamiliar sounds vs. familiar sound material that they were exposed to as fetuses, the neural basis of fetal learning has not thus far been investigated. Here we demonstrate direct neural correlates of human fetal learning of speech-like auditory stimuli. We presented variants of words to fetuses; unlike infants with no exposure to these stimuli, the exposed fetuses showed enhanced brain activity (mismatch responses) in response to pitch changes for the trained variants after birth. Furthermore, a significant correlation existed between the amount of prenatal exposure and brain activity, with greater activity being associated with a higher amount of prenatal speech exposure. Moreover, the learning effect was generalized to other types of similar speech sounds not included in the training material. Consequently, our results indicate neural commitment specifically tuned to the speech features heard before birth and their memory representations.

  4. 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.

  5. Neural networks in signal processing

    International Nuclear Information System (INIS)

    Govil, R.

    2000-01-01

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  6. Principles of neural information processing

    CERN Document Server

    Seelen, Werner v

    2016-01-01

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

  7. 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.

  8. Neural correlates of executive functions in patients with obesity.

    Science.gov (United States)

    Ho, Ming-Chou; Chen, Vincent Chin-Hung; Chao, Seh-Huang; Fang, Ching-Tzu; Liu, Yi-Chun; Weng, Jun-Cheng

    2018-01-01

    Obesity is one of the most challenging problems in human health and is recognized as an important risk factor for many chronic diseases. It remains unclear how the neural systems (e.g., the mesolimbic "reward" and the prefrontal "control" neural systems) are correlated with patients' executive function (EF), conceptualized as the integration of "cool" EF and "hot" EF. "Cool" EF refers to relatively abstract, non-affective operations such as inhibitory control and mental flexibility. "Hot" EF refers to motivationally significant affective operations such as affective decision-making. We tried to find the correlation between structural and functional neuroimaging indices and EF in obese patients. The study population comprised seventeen patients with obesity (seven males and 10 females, BMI = 37.99 ± 5.40, age = 31.82 ± 8.75 year-old) preparing to undergo bariatric surgery. We used noninvasive diffusion tensor imaging, generalized q-sampling imaging, and resting-state functional magnetic resonance imaging to examine the neural correlations between structural and functional neuroimaging indices and EF performances in patients with obesity. We reported that many brain areas are correlated to the patients' EF performances. More interestingly, some correlations may implicate the possible associations of EF and the incentive motivational effects of food. The neural correlation between the left precuneus and middle occipital gyrus and inhibitory control may suggest that patients with a better ability to detect appetitive food may have worse inhibitory control. Also, the neural correlation between the superior frontal blade and affective decision-making may suggest that patients' affective decision-making may be associated with the incentive motivational effects of food. Our results provide evidence suggesting neural correlates of EF in patients with obesity.

  9. Neural Decoder for Topological Codes

    Science.gov (United States)

    Torlai, Giacomo; Melko, Roger G.

    2017-07-01

    We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.

  10. Entropy Learning in Neural Network

    Directory of Open Access Journals (Sweden)

    Geok See Ng

    2017-12-01

    Full Text Available In this paper, entropy term is used in the learning phase of a neural network.  As learning progresses, more hidden nodes get into saturation.  The early creation of such hidden nodes may impair generalisation.  Hence entropy approach is proposed to dampen the early creation of such nodes.  The entropy learning also helps to increase the importance of relevant nodes while dampening the less important nodes.  At the end of learning, the less important nodes can then be eliminated to reduce the memory requirements of the neural network.

  11. The neural cell adhesion molecule

    DEFF Research Database (Denmark)

    Berezin, V; Bock, E; Poulsen, F M

    2000-01-01

    During the past year, the understanding of the structure and function of neural cell adhesion has advanced considerably. The three-dimensional structures of several of the individual modules of the neural cell adhesion molecule (NCAM) have been determined, as well as the structure of the complex...... between two identical fragments of the NCAM. Also during the past year, a link between homophilic cell adhesion and several signal transduction pathways has been proposed, connecting the event of cell surface adhesion to cellular responses such as neurite outgrowth. Finally, the stimulation of neurite...

  12. Antenna analysis using neural networks

    Science.gov (United States)

    Smith, William T.

    1992-01-01

    Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

  13. Arabic Handwriting Recognition Using Neural Network Classifier

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... an OCR using Neural Network classifier preceded by a set of preprocessing .... Artificial Neural Networks (ANNs), which we adopt in this research, consist of ... advantage and disadvantages of each technique. In [9],. Khemiri ...

  14. Neural overlap in processing music and speech.

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

    2015-03-19

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  15. Application of neural networks in coastal engineering

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.

    the neural network attractive. A neural network is an information processing system modeled on the structure of the dynamic process. It can solve the complex/nonlinear problems quickly once trained by operating on problems using an interconnected number...

  16. Ocean wave forecasting using recurrent neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    , merchant vessel routing, nearshore construction, etc. more efficiently and safely. This paper describes an artificial neural network, namely recurrent neural network with rprop update algorithm and is applied for wave forecasting. Measured ocean waves off...

  17. Neural overlap in processing music and speech

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.

    2015-01-01

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513

  18. Molecular parallels between neural and vascular development.

    Science.gov (United States)

    Eichmann, Anne; Thomas, Jean-Léon

    2013-01-01

    The human central nervous system (CNS) features a network of ~400 miles of blood vessels that receives >20% of the body's cardiac output and uses most of its blood glucose. Many human diseases, including stroke, retinopathy, and cancer, are associated with the biology of CNS blood vessels. These vessels originate from extrinsic cell populations, including endothelial cells and pericytes that colonize the CNS and interact with glia and neurons to establish the blood-brain barrier and control cerebrovascular exchanges. Neurovascular interactions also play important roles in adult neurogenic niches, which harbor a unique population of neural stem cells that are intimately associated with blood vessels. We here review the cellular and molecular mechanisms required to establish the CNS vascular network, with a special focus on neurovascular interactions and the functions of vascular endothelial growth factors.

  19. The neural bases of orthographic working memory

    Directory of Open Access Journals (Sweden)

    Jeremy Purcell

    2014-04-01

    First, these results reveal a neurotopography of OWM lesion sites that is well-aligned with results from neuroimaging of orthographic working memory in neurally intact participants (Rapp & Dufor, 2011. Second, the dorsal neurotopography of the OWM lesion overlap is clearly distinct from what has been reported for lesions associated with either lexical or sublexical deficits (e.g., Henry, Beeson, Stark, & Rapcsak, 2007; Rapcsak & Beeson, 2004; these have, respectively, been identified with the inferior occipital/temporal and superior temporal/inferior parietal regions. These neurotopographic distinctions support the claims of the computational distinctiveness of long-term vs. working memory operations. The specific lesion loci raise a number of questions to be discussed regarding: (a the selectivity of these regions and associated deficits to orthographic working memory vs. working memory more generally (b the possibility that different lesion sub-regions may correspond to different components of the OWM system.

  20. Neural and Behavioral Correlates of PTSD and Alcohol Use

    Science.gov (United States)

    2014-12-01

    Rezayof A, Hosseini SS, Zarrindast MR (2009) Effects of Morphine on Rat Behaviour in the Elevated Plus Maze: The Role of Central Amygdala Dopamine...The current research takes a multi-level approach to study the psychological , behavioral, cognitive and neural relationships between PTSD and alcohol...presented with combat-associated stimuli, an effect mediated by the anterior cingulate cortex. PTSD was associated with heightened anterior cingulate

  1. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Artur Popko

    2013-06-01

    Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

  2. Neural network to diagnose lining condition

    Science.gov (United States)

    Yemelyanov, V. A.; Yemelyanova, N. Y.; Nedelkin, A. A.; Zarudnaya, M. V.

    2018-03-01

    The paper presents data on the problem of diagnosing the lining condition at the iron and steel works. The authors describe the neural network structure and software that are designed and developed to determine the lining burnout zones. The simulation results of the proposed neural networks are presented. The authors note the low learning and classification errors of the proposed neural networks. To realize the proposed neural network, the specialized software has been developed.

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

    Directory of Open Access Journals (Sweden)

    Jay Waldron

    2010-11-01

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

  4. Determination of fat, moisture, and protein in meat and meat products by using the FOSS FoodScan Near-Infrared Spectrophotometer with FOSS Artificial Neural Network Calibration Model and Associated Database: collaborative study.

    Science.gov (United States)

    Anderson, Shirley

    2007-01-01

    A collaborative study was conducted to evaluate the repeatability and reproducibility of the FOSS FoodScan near-infrared spectrophotometer with artificial neural network calibration model and database for the determination of fat, moisture, and protein in meat and meat products. Representative samples were homogenized by grinding according to AOAC Official Method 983.18. Approximately 180 g ground sample was placed in a 140 mm round sample dish, and the dish was placed in the FoodScan. The operator ID was entered, the meat product profile within the software was selected, and the scanning process was initiated by pressing the "start" button. Results were displayed for percent (g/100 g) fat, moisture, and protein. Ten blind duplicate samples were sent to 15 collaborators in the United States. The within-laboratory (repeatability) relative standard deviation (RSD(r)) ranged from 0.22 to 2.67% for fat, 0.23 to 0.92% for moisture, and 0.35 to 2.13% for protein. The between-laboratories (reproducibility) relative standard deviation (RSD(R)) ranged from 0.52 to 6.89% for fat, 0.39 to 1.55% for moisture, and 0.54 to 5.23% for protein. The method is recommended for Official First Action.

  5. Nuclear power plant monitoring method by neural network and its application to actual nuclear reactor

    International Nuclear Information System (INIS)

    Nabeshima, Kunihiko; Suzuki, Katsuo; Shinohara, Yoshikuni; Tuerkcan, E.

    1995-11-01

    In this paper, the anomaly detection method for nuclear power plant monitoring and its program are described by using a neural network approach, which is based on the deviation between measured signals and output signals of neural network model. The neural network used in this study has three layered auto-associative network with 12 input/output, and backpropagation algorithm is adopted for learning. Furthermore, to obtain better dynamical model of the reactor plant, a new learning technique was developed in which the learning process of the present neural network is divided into initial and adaptive learning modes. The test results at the actual nuclear reactor shows that the neural network plant monitoring system is successfull in detecting in real-time the symptom of small anomaly over a wide power range including reactor start-up, shut-down and stationary operation. (author)

  6. Simplified LQG Control with Neural Networks

    DEFF Research Database (Denmark)

    Sørensen, O.

    1997-01-01

    A new neural network application for non-linear state control is described. One neural network is modelled to form a Kalmann predictor and trained to act as an optimal state observer for a non-linear process. Another neural network is modelled to form a state controller and trained to produce...

  7. Analysis of neural networks through base functions

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  8. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    NJD

    Improvements in neural network calibration models by a novel approach using neural network ensemble (NNE) for the simultaneous ... process by training a number of neural networks. .... Matlab® version 6.1 was employed for building principal component ... provide a fair simulation of calibration data set with some degree.

  9. 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

  10. Medical Imaging with Neural Networks

    International Nuclear Information System (INIS)

    Pattichis, C.; Cnstantinides, A.

    1994-01-01

    The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors)

  11. Optoelectronic Implementation of Neural Networks

    Indian Academy of Sciences (India)

    neural networks, such as learning, adapting and copying by means of parallel ... to provide robust recognition of hand-printed English text. Engine idle and misfiring .... and s represents the bounded activation function of a neuron. It is typically ...

  12. Aphasia Classification Using Neural Networks

    DEFF Research Database (Denmark)

    Axer, H.; Jantzen, Jan; Berks, G.

    2000-01-01

    A web-based software model (http://fuzzy.iau.dtu.dk/aphasia.nsf) was developed as an example for classification of aphasia using neural networks. Two multilayer perceptrons were used to classify the type of aphasia (Broca, Wernicke, anomic, global) according to the results in some subtests...

  13. 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.

  14. Medical Imaging with Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Pattichis, C [Department of Computer Science, University of Cyprus, Kallipoleos 75, P.O.Box 537, Nicosia (Cyprus); Cnstantinides, A [Department of Electrical Engineering, Imperial College of Science, Technology and Medicine, London SW7 2BT (United Kingdom)

    1994-12-31

    The objective of this paper is to provide an overview of the recent developments in the use of artificial neural networks in medical imaging. The areas of medical imaging that are covered include : ultrasound, magnetic resonance, nuclear medicine and radiological (including computerized tomography). (authors). 61 refs, 4 tabs.

  15. Numerical experiments with neural networks

    International Nuclear Information System (INIS)

    Miranda, Enrique.

    1990-01-01

    Neural networks are highly idealized models which, in spite of their simplicity, reproduce some key features of the real brain. In this paper, they are introduced at a level adequate for an undergraduate computational physics course. Some relevant magnitudes are defined and evaluated numerically for the Hopfield model and a short term memory model. (Author)

  16. Neural correlates of viewing paintings

    DEFF Research Database (Denmark)

    Vartanian, Oshin; Skov, Martin

    2014-01-01

    Many studies involving functional magnetic resonance imaging (fMRI) have exposed participants to paintings under varying task demands. To isolate neural systems that are activated reliably across fMRI studies in response to viewing paintings regardless of variation in task demands, a quantitative...

  17. Neural Basis of Visual Distraction

    Science.gov (United States)

    Kim, So-Yeon; Hopfinger, Joseph B.

    2010-01-01

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

  18. Vestibular hearing and neural synchronization.

    Science.gov (United States)

    Emami, Seyede Faranak; Daneshi, Ahmad

    2012-01-01

    Objectives. Vestibular hearing as an auditory sensitivity of the saccule in the human ear is revealed by cervical vestibular evoked myogenic potentials (cVEMPs). The range of the vestibular hearing lies in the low frequency. Also, the amplitude of an auditory brainstem response component depends on the amount of synchronized neural activity, and the auditory nerve fibers' responses have the best synchronization with the low frequency. Thus, the aim of this study was to investigate correlation between vestibular hearing using cVEMPs and neural synchronization via slow wave Auditory Brainstem Responses (sABR). Study Design. This case-control survey was consisted of twenty-two dizzy patients, compared to twenty healthy controls. Methods. Intervention comprised of Pure Tone Audiometry (PTA), Impedance acoustic metry (IA), Videonystagmography (VNG), fast wave ABR (fABR), sABR, and cVEMPs. Results. The affected ears of the dizzy patients had the abnormal findings of cVEMPs (insecure vestibular hearing) and the abnormal findings of sABR (decreased neural synchronization). Comparison of the cVEMPs at affected ears versus unaffected ears and the normal persons revealed significant differences (P < 0.05). Conclusion. Safe vestibular hearing was effective in the improvement of the neural synchronization.

  19. 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.

  20. Neural and psychological underpinnings of gambling disorder

    DEFF Research Database (Denmark)

    Grant, Jon E; Odlaug, Brian L; Chamberlain, Samuel R

    2016-01-01

    Gambling disorder affects 0.4 to 1.6% of adults worldwide, and is highly comorbid with other mental health disorders. This article provides a concise primer on the neural and psychological underpinnings of gambling disorder based on a selective review of the literature. Gambling disorder is assoc......Gambling disorder affects 0.4 to 1.6% of adults worldwide, and is highly comorbid with other mental health disorders. This article provides a concise primer on the neural and psychological underpinnings of gambling disorder based on a selective review of the literature. Gambling disorder...... is associated with dysfunction across multiple cognitive domains which can be considered in terms of impulsivity and compulsivity. Neuroimaging data suggest structural and functional abnormalities of networks involved in reward processing and top-down control. Gambling disorder shows 50-60% heritability...... is required to evaluate whether cognitive dysfunction and personality aspects influence the longitudinal course and treatment outcome for gambling disorder. It is hoped that improved understanding of the biological and psychological components of gambling disorder, and their interactions, may lead to improved...