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Sample records for neural representation suggest

  1. Moral transgressions corrupt neural representations of value.

    Science.gov (United States)

    Crockett, Molly J; Siegel, Jenifer Z; Kurth-Nelson, Zeb; Dayan, Peter; Dolan, Raymond J

    2017-06-01

    Moral systems universally prohibit harming others for personal gain. However, we know little about how such principles guide moral behavior. Using a task that assesses the financial cost participants ascribe to harming others versus themselves, we probed the relationship between moral behavior and neural representations of profit and pain. Most participants displayed moral preferences, placing a higher cost on harming others than themselves. Moral preferences correlated with neural responses to profit, where participants with stronger moral preferences had lower dorsal striatal responses to profit gained from harming others. Lateral prefrontal cortex encoded profit gained from harming others, but not self, and tracked the blameworthiness of harmful choices. Moral decisions also modulated functional connectivity between lateral prefrontal cortex and the profit-sensitive region of dorsal striatum. The findings suggest moral behavior in our task is linked to a neural devaluation of reward realized by a prefrontal modulation of striatal value representations.

  2. Atypical Neural Self-Representation in Autism

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    Lombardo, Michael V.; Chakrabarti, Bhismadev; Bullmore, Edward T.; Sadek, Susan A.; Pasco, Greg; Wheelwright, Sally J.; Suckling, John; Baron-Cohen, Simon

    2010-01-01

    The "self" is a complex multidimensional construct deeply embedded and in many ways defined by our relations with the social world. Individuals with autism are impaired in both self-referential and other-referential social cognitive processing. Atypical neural representation of the self may be a key to understanding the nature of such impairments.…

  3. Matrix representation of a Neural Network

    DEFF Research Database (Denmark)

    Christensen, Bjørn Klint

    Processing, by David Rummelhart (Rummelhart 1986) for an easy-to-read introduction. What the paper does explain is how a matrix representation of a neural net allows for a very simple implementation. The matrix representation is introduced in (Rummelhart 1986, chapter 9), but only for a two-layer linear...... network and the feedforward algorithm. This paper develops the idea further to three-layer non-linear networks and the backpropagation algorithm. Figure 1 shows the layout of a three-layer network. There are I input nodes, J hidden nodes and K output nodes all indexed from 0. Bias-node for the hidden...

  4. Identifying bilingual semantic neural representations across languages

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    Buchweitz, Augusto; Shinkareva, Svetlana V.; Mason, Robert A.; Mitchell, Tom M.; Just, Marcel Adam

    2015-01-01

    The goal of the study was to identify the neural representation of a noun's meaning in one language based on the neural representation of that same noun in another language. Machine learning methods were used to train classifiers to identify which individual noun bilingual participants were thinking about in one language based solely on their brain activation in the other language. The study shows reliable (p languages. It also shows that the stable voxels used to classify the brain activation were located in areas associated with encoding information about semantic dimensions of the words in the study. The identification of the semantic trace of individual nouns from the pattern of cortical activity demonstrates the existence of a multi-voxel pattern of activation across the cortex for a single noun common to both languages in bilinguals. PMID:21978845

  5. Modular representation of layered neural networks.

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    Watanabe, Chihiro; Hiramatsu, Kaoru; Kashino, Kunio

    2018-01-01

    Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its internal representation has many nonlinear and complex parameters embedded in hierarchical layers. Therefore, it becomes important to establish a new methodology by which layered neural networks can be understood. In this paper, we propose a new method for extracting a global and simplified structure from a layered neural network. Based on network analysis, the proposed method detects communities or clusters of units with similar connection patterns. We show its effectiveness by applying it to three use cases. (1) Network decomposition: it can decompose a trained neural network into multiple small independent networks thus dividing the problem and reducing the computation time. (2) Training assessment: the appropriateness of a trained result with a given hyperparameter or randomly chosen initial parameters can be evaluated by using a modularity index. And (3) data analysis: in practical data it reveals the community structure in the input, hidden, and output layers, which serves as a clue for discovering knowledge from a trained neural network. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Representations in neural network based empirical potentials

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    Cubuk, Ekin D.; Malone, Brad D.; Onat, Berk; Waterland, Amos; Kaxiras, Efthimios

    2017-07-01

    Many structural and mechanical properties of crystals, glasses, and biological macromolecules can be modeled from the local interactions between atoms. These interactions ultimately derive from the quantum nature of electrons, which can be prohibitively expensive to simulate. Machine learning has the potential to revolutionize materials modeling due to its ability to efficiently approximate complex functions. For example, neural networks can be trained to reproduce results of density functional theory calculations at a much lower cost. However, how neural networks reach their predictions is not well understood, which has led to them being used as a "black box" tool. This lack of understanding is not desirable especially for applications of neural networks in scientific inquiry. We argue that machine learning models trained on physical systems can be used as more than just approximations since they had to "learn" physical concepts in order to reproduce the labels they were trained on. We use dimensionality reduction techniques to study in detail the representation of silicon atoms at different stages in a neural network, which provides insight into how a neural network learns to model atomic interactions.

  7. Neural representation of probabilities for Bayesian inference.

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    Rich, Dylan; Cazettes, Fanny; Wang, Yunyan; Peña, José Luis; Fischer, Brian J

    2015-04-01

    Bayesian models are often successful in describing perception and behavior, but the neural representation of probabilities remains in question. There are several distinct proposals for the neural representation of probabilities, but they have not been directly compared in an example system. Here we consider three models: a non-uniform population code where the stimulus-driven activity and distribution of preferred stimuli in the population represent a likelihood function and a prior, respectively; the sampling hypothesis which proposes that the stimulus-driven activity over time represents a posterior probability and that the spontaneous activity represents a prior; and the class of models which propose that a population of neurons represents a posterior probability in a distributed code. It has been shown that the non-uniform population code model matches the representation of auditory space generated in the owl's external nucleus of the inferior colliculus (ICx). However, the alternative models have not been tested, nor have the three models been directly compared in any system. Here we tested the three models in the owl's ICx. We found that spontaneous firing rate and the average stimulus-driven response of these neurons were not consistent with predictions of the sampling hypothesis. We also found that neural activity in ICx under varying levels of sensory noise did not reflect a posterior probability. On the other hand, the responses of ICx neurons were consistent with the non-uniform population code model. We further show that Bayesian inference can be implemented in the non-uniform population code model using one spike per neuron when the population is large and is thus able to support the rapid inference that is necessary for sound localization.

  8. Linking neural and symbolic representation and processing of conceptual structures

    NARCIS (Netherlands)

    van der Velde, Frank; Forth, Jamie; Nazareth, Deniece S.; Wiggins, Geraint A.

    2017-01-01

    We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual

  9. Neural Representations of Emotion Are Organized around Abstract Event Features

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    Skerry, Amy E.; Saxe, Rebecca

    2016-01-01

    Summary Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. PMID:26212878

  10. How learning to abstract shapes neural sound representations

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    Anke eLey

    2014-06-01

    Full Text Available The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound features, adequate sound identification and categorization require neural sound representations that are invariant to irrelevant stimulus parameters. Crucially, what is relevant and irrelevant is not necessarily intrinsic to the physical stimulus structure but needs to be learned over time, often through integration of information from other senses. This review discusses the main principles underlying categorical sound perception with a special focus on the role of learning and neural plasticity. We examine the role of different neural structures along the auditory processing pathway in the formation of abstract sound representations with respect to hierarchical as well as dynamic and distributed processing models. Whereas most fMRI studies on categorical sound processing employed speech sounds, the emphasis of the current review lies on the contribution of empirical studies using natural or artificial sounds that enable separating acoustic and perceptual processing levels and avoid interference with existing category representations. Finally, we discuss the opportunities of modern analyses techniques (such as multivariate pattern analysis in studying categorical sound representations. With their increased sensitivity to distributed activation changes - even in absence of changes in overall signal level - these analyses techniques provide a promising tool to reveal the neural underpinnings of perceptually invariant sound representations.

  11. Linking Neural and Symbolic Representation and Processing of Conceptual Structures

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    Frank van der Velde

    2017-08-01

    Full Text Available We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like structures. First is the Neural Blackboard Architecture (NBA, which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking, which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures.

  12. Invariant recognition drives neural representations of action sequences.

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    Andrea Tacchetti

    2017-12-01

    Full Text Available Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs, that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences.

  13. Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations

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    Holca-Lamarre, Raphaël; Lücke, Jörg; Obermayer, Klaus

    2017-01-01

    Biological and artificial neural networks (ANNs) represent input signals as patterns of neural activity. In biology, neuromodulators can trigger important reorganizations of these neural representations. For instance, pairing a stimulus with the release of either acetylcholine (ACh) or dopamine (DA) evokes long lasting increases in the responses of neurons to the paired stimulus. The functional roles of ACh and DA in rearranging representations remain largely unknown. Here, we address this question using a Hebbian-learning neural network model. Our aim is both to gain a functional understanding of ACh and DA transmission in shaping biological representations and to explore neuromodulator-inspired learning rules for ANNs. We model the effects of ACh and DA on synaptic plasticity and confirm that stimuli coinciding with greater neuromodulator activation are over represented in the network. We then simulate the physiological release schedules of ACh and DA. We measure the impact of neuromodulator release on the network's representation and on its performance on a classification task. We find that ACh and DA trigger distinct changes in neural representations that both improve performance. The putative ACh signal redistributes neural preferences so that more neurons encode stimulus classes that are challenging for the network. The putative DA signal adapts synaptic weights so that they better match the classes of the task at hand. Our model thus offers a functional explanation for the effects of ACh and DA on cortical representations. Additionally, our learning algorithm yields performances comparable to those of state-of-the-art optimisation methods in multi-layer perceptrons while requiring weaker supervision signals and interacting with synaptically-local weight updates. PMID:28690509

  14. Neural Representations of Location Outside the Hippocampus

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    Knierim, James J.

    2006-01-01

    Place cells of the rat hippocampus are a dominant model system for understanding the role of the hippocampus in learning and memory at the level of single-unit and neural ensemble responses. A complete understanding of the information processing and computations performed by the hippocampus requires detailed knowledge about the properties of the…

  15. Neural representation of face familiarity in an awake chimpanzee

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    Hirokata Fukushima

    2013-12-01

    Full Text Available Evaluating the familiarity of faces is critical for social animals as it is the basis of individual recognition. In the present study, we examined how face familiarity is reflected in neural activities in our closest living relative, the chimpanzee. Skin-surface event-related brain potentials (ERPs were measured while a fully awake chimpanzee observed photographs of familiar and unfamiliar chimpanzee faces (Experiment 1 and human faces (Experiment 2. The ERPs evoked by chimpanzee faces differentiated unfamiliar individuals from familiar ones around midline areas centered on vertex sites at approximately 200 ms after the stimulus onset. In addition, the ERP response to the image of the subject’s own face did not significantly diverge from those evoked by familiar chimpanzees, suggesting that the subject’s brain at a minimum remembered the image of her own face. The ERPs evoked by human faces were not influenced by the familiarity of target individuals. These results indicate that chimpanzee neural representations are more sensitive to the familiarity of conspecific than allospecific faces.

  16. How learning to abstract shapes neural sound representations

    NARCIS (Netherlands)

    Ley, A.; Vroomen, J.; Formisano, E.

    2014-01-01

    The transformation of acoustic signals into abstract perceptual representations is the essence of the efficient and goal-directed neural processing of sounds in complex natural environments. While the human and animal auditory system is perfectly equipped to process the spectrotemporal sound

  17. Neural Dynamics and Information Representation in Microcircuits of Motor Cortex

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    Yasuhiro eTsubo

    2013-05-01

    Full Text Available The brain has to analyze and respond to external events that can change rapidly from time to time, suggesting that information processing by the brain may be essentially dynamic rather than static. The dynamical features of neural computation are of significant importance in motor cortex that governs the process of movement generation and learning. In this paper, we discuss these features based primarily on our recent findings on neural dynamics and information coding in the microcircuit of rat motor cortex. In fact, cortical neurons show a variety of dynamical behavior from rhythmic activity in various frequency bands to highly irregular spike firing. Of particular interest are the similarity and dissimilarity of the neuronal response properties in different layers of motor cortex. By conducting electrophysiological recordings in slice preparation, we report the phase response curves of neurons in different cortical layers to demonstrate their layer-dependent synchronization properties. We then study how motor cortex recruits task-related neurons in different layers for voluntary arm movements by simultaneous juxtacellular and multiunit recordings from behaving rats. The results suggest an interesting difference in the spectrum of functional activity between the superficial and deep layers. Furthermore, the task-related activities recorded from various layers exhibited power law distributions of inter-spike intervals (ISIs, in contrast to a general belief that ISIs obey Poisson or Gamma distributions in cortical neurons. We present a theoretical argument that this power law of in vivo neurons may represent the maximization of the entropy of firing rate with limited energy consumption of spike generation. Though further studies are required to fully clarify the functional implications of this coding principle, it may shed new light on information representations by neurons and circuits in motor cortex.

  18. Sex Discrimination: 2D Hand Representations Suggest Pan-Stimulus Effects

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    Anna Rayner Brooks

    2011-05-01

    Full Text Available Whether buying fruit or negotiating a peace deal, the sexes of the people involved affect the style of their interactions with each other. Indeed, even such an “objective” act as measuring blood pressure has been found to be influenced by an interaction between patient and observer sex (Millar & Accioly, 1996. As such, understanding the perceptual and neural correlates of the ability is important. Here we tested observer sensitivity to sex cues using a new partial body stimulus set: Static two-dimensional representations of human hands. Our data show that whilst availability of cues including absolute size, colour and texture enhances discrimination, those cues are not required for reliable performance on the task. Moreover, patterns of sensitivity arising in relation to hand stimuli show marked similarities with those associated with other stimulus sets—suggesting the existence of pan-stimulus effects. Implications of those findings for models of the perceptual and neural correlates of sex discrimination are discussed.

  19. Inferring low-dimensional microstructure representations using convolutional neural networks

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    Lubbers, Nicholas; Lookman, Turab; Barros, Kipton

    2017-11-01

    We apply recent advances in machine learning and computer vision to a central problem in materials informatics: the statistical representation of microstructural images. We use activations in a pretrained convolutional neural network to provide a high-dimensional characterization of a set of synthetic microstructural images. Next, we use manifold learning to obtain a low-dimensional embedding of this statistical characterization. We show that the low-dimensional embedding extracts the parameters used to generate the images. According to a variety of metrics, the convolutional neural network method yields dramatically better embeddings than the analogous method derived from two-point correlations alone.

  20. Marketing actions can modulate neural representations of experienced pleasantness.

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    Plassmann, Hilke; O'Doherty, John; Shiv, Baba; Rangel, Antonio

    2008-01-22

    Despite the importance and pervasiveness of marketing, almost nothing is known about the neural mechanisms through which it affects decisions made by individuals. We propose that marketing actions, such as changes in the price of a product, can affect neural representations of experienced pleasantness. We tested this hypothesis by scanning human subjects using functional MRI while they tasted wines that, contrary to reality, they believed to be different and sold at different prices. Our results show that increasing the price of a wine increases subjective reports of flavor pleasantness as well as blood-oxygen-level-dependent activity in medial orbitofrontal cortex, an area that is widely thought to encode for experienced pleasantness during experiential tasks. The paper provides evidence for the ability of marketing actions to modulate neural correlates of experienced pleasantness and for the mechanisms through which the effect operates.

  1. Neural Schematics as a unified formal graphical representation of large-scale Neural Network Structures

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    Matthias eEhrlich

    2013-10-01

    Full Text Available One of the major outcomes of neuroscientific research are models of Neural Network Structures. Descriptions of these models usually consist of a non-standardized mixture of text, figures, and other means of visual information communication in print media. However, as neuroscience is an interdisciplinary domain by nature, a standardized way of consistently representing models of Neural Network Structures is required. While generic descriptions of such models in textual form have recently been developed, a formalized way of schematically expressing them does not exist to date. Hence, in this paper we present Neural Schematics as a concept inspired by similar approaches from other disciplines for a generic two dimensional representation of said structures. After introducing Neural Network Structures in general, a set of current visualizations of models of Neural Network Structures is reviewed and analyzed for what information they convey and how their elements are rendered. This analysis then allows for the definition of general items and symbols to consistently represent these models as Neural Schematics on a two dimensional plane. We will illustrate the possibilities an agreed upon standard can yield on sampled diagrams transformed into Neural Schematics and an example application for the design and modeling of large-scale Neural Network Structures.

  2. Neural Representation of Concurrent Vowels in Macaque Primary Auditory Cortex.

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    Fishman, Yonatan I; Micheyl, Christophe; Steinschneider, Mitchell

    2016-01-01

    Successful speech perception in real-world environments requires that the auditory system segregate competing voices that overlap in frequency and time into separate streams. Vowels are major constituents of speech and are comprised of frequencies (harmonics) that are integer multiples of a common fundamental frequency (F0). The pitch and identity of a vowel are determined by its F0 and spectral envelope (formant structure), respectively. When two spectrally overlapping vowels differing in F0 are presented concurrently, they can be readily perceived as two separate "auditory objects" with pitches at their respective F0s. A difference in pitch between two simultaneous vowels provides a powerful cue for their segregation, which in turn, facilitates their individual identification. The neural mechanisms underlying the segregation of concurrent vowels based on pitch differences are poorly understood. Here, we examine neural population responses in macaque primary auditory cortex (A1) to single and double concurrent vowels (/a/ and /i/) that differ in F0 such that they are heard as two separate auditory objects with distinct pitches. We find that neural population responses in A1 can resolve, via a rate-place code, lower harmonics of both single and double concurrent vowels. Furthermore, we show that the formant structures, and hence the identities, of single vowels can be reliably recovered from the neural representation of double concurrent vowels. We conclude that A1 contains sufficient spectral information to enable concurrent vowel segregation and identification by downstream cortical areas.

  3. Social behaviour shapes hypothalamic neural ensemble representations of conspecific sex

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    Remedios, Ryan; Kennedy, Ann; Zelikowsky, Moriel; Grewe, Benjamin F.; Schnitzer, Mark J.; Anderson, David J.

    2017-10-01

    All animals possess a repertoire of innate (or instinctive) behaviours, which can be performed without training. Whether such behaviours are mediated by anatomically distinct and/or genetically specified neural pathways remains unknown. Here we report that neural representations within the mouse hypothalamus, that underlie innate social behaviours, are shaped by social experience. Oestrogen receptor 1-expressing (Esr1+) neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) control mating and fighting in rodents. We used microendoscopy to image Esr1+ neuronal activity in the VMHvl of male mice engaged in these social behaviours. In sexually and socially experienced adult males, divergent and characteristic neural ensembles represented male versus female conspecifics. However, in inexperienced adult males, male and female intruders activated overlapping neuronal populations. Sex-specific neuronal ensembles gradually separated as the mice acquired social and sexual experience. In mice permitted to investigate but not to mount or attack conspecifics, ensemble divergence did not occur. However, 30 minutes of sexual experience with a female was sufficient to promote the separation of male and female ensembles and to induce an attack response 24 h later. These observations uncover an unexpected social experience-dependent component to the formation of hypothalamic neural assemblies controlling innate social behaviours. More generally, they reveal plasticity and dynamic coding in an evolutionarily ancient deep subcortical structure that is traditionally viewed as a ‘hard-wired’ system.

  4. Owl's behavior and neural representation predicted by Bayesian inference.

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    Fischer, Brian J; Peña, José Luis

    2011-07-03

    The owl captures prey using sound localization. In the classical model, the owl infers sound direction from the position of greatest activity in a brain map of auditory space. However, this model fails to describe the actual behavior. Although owls accurately localize sources near the center of gaze, they systematically underestimate peripheral source directions. We found that this behavior is predicted by statistical inference, formulated as a Bayesian model that emphasizes central directions. We propose that there is a bias in the neural coding of auditory space, which, at the expense of inducing errors in the periphery, achieves high behavioral accuracy at the ethologically relevant range. We found that the owl's map of auditory space decoded by a population vector is consistent with the behavioral model. Thus, a probabilistic model describes both how the map of auditory space supports behavior and why this representation is optimal.

  5. Neural Representation of Working Memory Content Is Modulated by Visual Attentional Demand.

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    Kiyonaga, Anastasia; Dowd, Emma Wu; Egner, Tobias

    2017-12-01

    Recent theories assert that visual working memory (WM) relies on the same attentional resources and sensory substrates as visual attention to external stimuli. Behavioral studies have observed competitive tradeoffs between internal (i.e., WM) and external (i.e., visual) attentional demands, and neuroimaging studies have revealed representations of WM content as distributed patterns of activity within the same cortical regions engaged by perception of that content. Although a key function of WM is to protect memoranda from competing input, it remains unknown how neural representations of WM content are impacted by incoming sensory stimuli and concurrent attentional demands. Here, we investigated how neural evidence for WM information is affected when attention is occupied by visual search-at varying levels of difficulty-during the delay interval of a WM match-to-sample task. Behavioral and fMRI analyses suggested that WM maintenance was impacted by the difficulty of a concurrent visual task. Critically, multivariate classification analyses of category-specific ventral visual areas revealed a reduction in decodable WM-related information when attention was diverted to a visual search task, especially when the search was more difficult. This study suggests that the amount of available attention during WM maintenance influences the detection of sensory WM representations.

  6. A stranger in my brain: Neural representation for unfamiliar persons using fMRI repetition suppression.

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    Heleven, Elien; Boukhlal, Siham; Van Overwalle, Frank

    2017-08-02

    Prior neuroimaging research demonstrated that the ventromedial prefrontal cortex (vmPFC) houses neural representations for traits and familiar persons that possess these traits. But do such neural representations also exist for people we do not know? We hypothesized that knowledge about unknown persons is encoded in "generic" mentalizing representations as opposed to "specific" representations for well-known individuals. Neural representations for unfamiliar persons were investigated by fMRI repetition suppression, which is a rapid suppression of fMRI responses upon repeated presentation of the same stimulus signaling the neural representation of this stimulus. Participants had to infer an unfamiliar person's traits from brief behavioral descriptions. In each trial, a critical sentence was preceded by another sentence in which we manipulated whether or not the person or trait was repeated. The results revealed suppression for unfamiliar others in the vmPFC extending earlier research, as well as in novel areas including the inferior parietal lobule and dorsal posterior cingulate. We also found trait suppression in the vmPFC. This indicates that the vmPFC houses neural populations of "generic" representations of unknown persons and their traits. We speculate that the other brain areas showing suppression might reflect embodied representations at a somatomotor level.

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

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    Liddell, Belinda J; Jobson, Laura

    2016-01-01

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

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

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    Belinda J. Liddell

    2016-06-01

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

  9. Expression patterns of neural genes in Euperipatoides kanangrensis suggest divergent evolution of onychophoran and euarthropod neurogenesis.

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    Eriksson, Bo Joakim; Stollewerk, Angelika

    2010-12-28

    One of the controversial debates on euarthropod relationships centers on the question as to whether insects, crustaceans, and myriapods (Mandibulata) share a common ancestor or whether myriapods group with the chelicerates (Myriochelata). The debate was stimulated recently by studies in chelicerates and myriapods that show that neural precursor groups (NPGs) segregate from the neuroectoderm generating the nervous system, whereas in insects and crustaceans the nervous tissue is produced by stem cells. Do the shared neural characters of myriapods and chelicerates represent derived characters that support the Myriochelata grouping? Or do they rather reflect the ancestral pattern? Analyses of neurogenesis in a group closely related to euarthropods, the onychophorans, show that, similar to insects and crustaceans, single neural precursors are formed in the neuroectoderm, potentially supporting the Myriochelata hypothesis. Here we show that the nature and the selection of onychophoran neural precursors are distinct from euarthropods. The onychophoran nervous system is generated by the massive irregular segregation of single neural precursors, contrasting with the limited number and stereotyped arrangement of NPGs/stem cells in euarthropods. Furthermore, neural genes do not show the spatiotemporal pattern that sets up the precise position of neural precursors as in euarthropods. We conclude that neurogenesis in onychophorans largely does not reflect the ancestral pattern of euarthropod neurogenesis, but shows a mixture of derived characters and ancestral characters that have been modified in the euarthropod lineage. Based on these data and additional evidence, we suggest an evolutionary sequence of arthropod neurogenesis that is in line with the Mandibulata hypothesis.

  10. Action Potential Modulation of Neural Spin Networks Suggests Possible Role of Spin

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    Hu, H P

    2004-01-01

    In this paper we show that nuclear spin networks in neural membranes are modulated by action potentials through J-coupling, dipolar coupling and chemical shielding tensors and perturbed by microscopically strong and fluctuating internal magnetic fields produced largely by paramagnetic oxygen. We suggest that these spin networks could be involved in brain functions since said modulation inputs information carried by the neural spike trains into them, said perturbation activates various dynamics within them and the combination of the two likely produce stochastic resonance thus synchronizing said dynamics to the neural firings. Although quantum coherence is desirable and may indeed exist, it is not required for these spin networks to serve as the subatomic components for the conventional neural networks.

  11. Aging affects hemispheric asymmetry in the neural representation of speech sounds.

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    Bellis, T J; Nicol, T; Kraus, N

    2000-01-15

    Hemispheric asymmetries in the processing of elemental speech sounds appear to be critical for normal speech perception. This study investigated the effects of age on hemispheric asymmetry observed in the neurophysiological responses to speech stimuli in three groups of normal hearing, right-handed subjects: children (ages, 8-11 years), young adults (ages, 20-25 years), and older adults (ages > 55 years). Peak-to-peak response amplitudes of the auditory cortical P1-N1 complex obtained over right and left temporal lobes were examined to determine the degree of left/right asymmetry in the neurophysiological responses elicited by synthetic speech syllables in each of the three subject groups. In addition, mismatch negativity (MMN) responses, which are elicited by acoustic change, were obtained. Whereas children and young adults demonstrated larger P1-N1-evoked response amplitudes over the left temporal lobe than over the right, responses from elderly subjects were symmetrical. In contrast, MMN responses, which reflect an echoic memory process, were symmetrical in all subject groups. The differences observed in the neurophysiological responses were accompanied by a finding of significantly poorer ability to discriminate speech syllables involving rapid spectrotemporal changes in the older adult group. This study demonstrates a biological, age-related change in the neural representation of basic speech sounds and suggests one possible underlying mechanism for the speech perception difficulties exhibited by aging adults. Furthermore, results of this study support previous findings suggesting a dissociation between neural mechanisms underlying those processes that reflect the basic representation of sound structure and those that represent auditory echoic memory and stimulus change.

  12. Distributed neural representation of saliency controlled value and category during anticipation of rewards and punishments.

    Science.gov (United States)

    Zhang, Zhihao; Fanning, Jennifer; Ehrlich, Daniel B; Chen, Wenting; Lee, Daeyeol; Levy, Ifat

    2017-12-04

    An extensive literature from cognitive neuroscience examines the neural representation of value, but interpretations of these existing results are often complicated by the potential confound of saliency. At the same time, recent attempts to dissociate neural signals of value and saliency have not addressed their relationship with category information. Using a multi-category valuation task that incorporates rewards and punishments of different nature, we identify distributed neural representation of value, saliency, and category during outcome anticipation. Moreover, we reveal category encoding in multi-voxel blood-oxygen-level-dependent activity patterns of the vmPFC and the striatum that coexist with value signals. These results help clarify ambiguities regarding value and saliency encoding in the human brain and their category independence, lending strong support to the neural "common currency" hypothesis. Our results also point to potential novel mechanisms of integrating multiple aspects of decision-related information.

  13. Examining overlap in behavioral and neural representations of morals, facts, and preferences.

    Science.gov (United States)

    Theriault, Jordan; Waytz, Adam; Heiphetz, Larisa; Young, Liane

    2017-11-01

    Metaethical judgments refer to judgments about the information expressed by moral claims. Moral objectivists generally believe that moral claims are akin to facts, whereas moral subjectivists generally believe that moral claims are more akin to preferences. Evidence from developmental and social psychology has generally favored an objectivist view; however, this work has typically relied on few examples, and analyses have disallowed statistical generalizations beyond these few stimuli. The present work addresses whether morals are represented as fact-like or preference-like, using behavioral and neuroimaging methods, in combination with statistical techniques that can (a) generalize beyond our sample stimuli, and (b) test whether particular item features are associated with neural activity. Behaviorally, and contrary to prior work, morals were perceived as more preference-like than fact-like. Neurally, morals and preferences elicited common magnitudes and spatial patterns of activity, particularly within the dorsal-medial prefrontal cortex (DMPFC), a critical region for social cognition. This common DMPFC activity for morals and preferences was present across whole-brain conjunctions, and in individually localized functional regions of interest (targeting the theory of mind network). By contrast, morals and facts did not elicit any neural activity in common. Follow-up item analyses suggested that the activity elicited in common by morals and preferences was explained by their shared tendency to evoke representations of mental states. We conclude that morals are represented as far more subjective than prior work has suggested. This conclusion is consistent with recent theoretical research, which has argued that morality is fundamentally about regulating social relationships. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  14. Neural aspects of second language representation and language control.

    Science.gov (United States)

    Abutalebi, Jubin

    2008-07-01

    A basic issue in the neurosciences of language is whether an L2 can be processed through the same neural mechanism underlying L1 acquisition and processing. In the present paper I review data from functional neuroimaging studies focusing on grammatical and lexico-semantic processing in bilinguals. The available evidence indicates that the L2 seems to be acquired through the same neural structures responsible for L1 acquisition. This fact is also observed for grammar acquisition in late L2 learners contrary to what one may expect from critical period accounts. However, neural differences for an L2 may be observed, in terms of more extended activity of the neural system mediating L1 processing. These differences may disappear once a more 'native-like' proficiency is established, reflecting a change in language processing mechanisms: from controlled processing for a weak L2 system (i.e., a less proficient L2) to more automatic processing. The neuroimaging data reviewed in this paper also support the notion that language control is a crucial aspect specific to the bilingual language system. The activity of brain areas related to cognitive control during the processing of a 'weak' L2 may reflect competition and conflict between languages which may be resolved with the intervention of these areas.

  15. Implicit race bias decreases the similarity of neural representations of black and white faces.

    Science.gov (United States)

    Brosch, Tobias; Bar-David, Eyal; Phelps, Elizabeth A

    2013-02-01

    Implicit race bias has been shown to affect decisions and behaviors. It may also change perceptual experience by increasing perceived differences between social groups. We investigated how this phenomenon may be expressed at the neural level by testing whether the distributed blood-oxygenation-level-dependent (BOLD) patterns representing Black and White faces are more dissimilar in participants with higher implicit race bias. We used multivoxel pattern analysis to predict the race of faces participants were viewing. We successfully predicted the race of the faces on the basis of BOLD activation patterns in early occipital visual cortex, occipital face area, and fusiform face area (FFA). Whereas BOLD activation patterns in early visual regions, likely reflecting different perceptual features, allowed successful prediction for all participants, successful prediction on the basis of BOLD activation patterns in FFA, a high-level face-processing region, was restricted to participants with high pro-White bias. These findings suggest that stronger implicit pro-White bias decreases the similarity of neural representations of Black and White faces.

  16. A View of the Neural Representation of Second Language Syntax through Artificial Language Learning under Implicit Contexts of Exposure

    Science.gov (United States)

    Morgan-Short, Kara; Deng, ZhiZhou; Brill-Schuetz, Katherine A.; Faretta- Stutenberg, Mandy; Wong, Patrick C. M.; Wong, Francis C. K.

    2015-01-01

    The current study aims to make an initial neuroimaging contribution to central implicit-explicit issues in second language (L2) acquisition by considering how implicit and explicit contexts mediate the neural representation of L2. Focusing on implicit contexts, the study employs a longitudinal design to examine the neural representation of L2…

  17. Cross-linguistic differences in the neural representation of human language: evidence from users of signed languages.

    Science.gov (United States)

    Corina, David P; Lawyer, Laurel A; Cates, Deborah

    2012-01-01

    Studies of deaf individuals who are users of signed languages have provided profound insight into the neural representation of human language. Case studies of deaf signers who have incurred left- and right-hemisphere damage have shown that left-hemisphere resources are a necessary component of sign language processing. These data suggest that, despite frank differences in the input and output modality of language, core left perisylvian regions universally serve linguistic function. Neuroimaging studies of deaf signers have generally provided support for this claim. However, more fine-tuned studies of linguistic processing in deaf signers are beginning to show evidence of important differences in the representation of signed and spoken languages. In this paper, we provide a critical review of this literature and present compelling evidence for language-specific cortical representations in deaf signers. These data lend support to the claim that the neural representation of language may show substantive cross-linguistic differences. We discuss the theoretical implications of these findings with respect to an emerging understanding of the neurobiology of language.

  18. Cross-linguistic differences in the neural representation of human language: evidence from users of signed languages.

    Directory of Open Access Journals (Sweden)

    David eCorina

    2013-01-01

    Full Text Available Studies of deaf individuals who are users of signed languages have provided profound insight into the neural representation of human language. Case studies of deaf signers who have incurred left- and right-hemisphere damage have shown that left-hemisphere resources are a necessary component of sign language processing. These data suggest that, despite frank differences in the input and output modality of language,; core left perisylvian regions universally serve linguistic function. Neuroimaging studies of deaf signers have generally provided support for this claim. However, more fine-tuned studies of linguistic processing in deaf signers are beginning to show evidence of important differences in the representation of signed and spoken languages. In this paper, we provide a critical review of this literature and present compelling evidence for language-specific cortical representations in deaf signers. These data lend support to the claim that the neural representation of language may show substantive cross-linguistic differences. We discuss the theoretical implications of these findings with respect to an emerging understanding of the neurobiology of language.

  19. Cross-Linguistic Differences in the Neural Representation of Human Language: Evidence from Users of Signed Languages

    Science.gov (United States)

    Corina, David P.; Lawyer, Laurel A.; Cates, Deborah

    2013-01-01

    Studies of deaf individuals who are users of signed languages have provided profound insight into the neural representation of human language. Case studies of deaf signers who have incurred left- and right-hemisphere damage have shown that left-hemisphere resources are a necessary component of sign language processing. These data suggest that, despite frank differences in the input and output modality of language, core left perisylvian regions universally serve linguistic function. Neuroimaging studies of deaf signers have generally provided support for this claim. However, more fine-tuned studies of linguistic processing in deaf signers are beginning to show evidence of important differences in the representation of signed and spoken languages. In this paper, we provide a critical review of this literature and present compelling evidence for language-specific cortical representations in deaf signers. These data lend support to the claim that the neural representation of language may show substantive cross-linguistic differences. We discuss the theoretical implications of these findings with respect to an emerging understanding of the neurobiology of language. PMID:23293624

  20. Reliable prediction of T-cell epitopes using neural networks with novel sequence representations

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Worning, Peder

    2003-01-01

    In this paper we describe an improved neural network method to predict T-cell class I epitopes. A novel input representation has been developed consisting of a combination of sparse encoding, Blosum encoding, and input derived from hidden Markov models. We demonstrate that the combination...

  1. Spatiotemporal dynamics of similarity-based neural representations of facial identity.

    Science.gov (United States)

    Vida, Mark D; Nestor, Adrian; Plaut, David C; Behrmann, Marlene

    2017-01-10

    Humans' remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level "image-based" and higher level "identity-based" model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise.

  2. Contributions of feature shapes and surface cues to the recognition and neural representation of facial identity.

    Science.gov (United States)

    Andrews, Timothy J; Baseler, Heidi; Jenkins, Rob; Burton, A Mike; Young, Andrew W

    2016-10-01

    A full understanding of face recognition will involve identifying the visual information that is used to discriminate different identities and how this is represented in the brain. The aim of this study was to explore the importance of shape and surface properties in the recognition and neural representation of familiar faces. We used image morphing techniques to generate hybrid faces that mixed shape properties (more specifically, second order spatial configural information as defined by feature positions in the 2D-image) from one identity and surface properties from a different identity. Behavioural responses showed that recognition and matching of these hybrid faces was primarily based on their surface properties. These behavioural findings contrasted with neural responses recorded using a block design fMRI adaptation paradigm to test the sensitivity of Haxby et al.'s (2000) core face-selective regions in the human brain to the shape or surface properties of the face. The fusiform face area (FFA) and occipital face area (OFA) showed a lower response (adaptation) to repeated images of the same face (same shape, same surface) compared to different faces (different shapes, different surfaces). From the behavioural data indicating the critical contribution of surface properties to the recognition of identity, we predicted that brain regions responsible for familiar face recognition should continue to adapt to faces that vary in shape but not surface properties, but show a release from adaptation to faces that vary in surface properties but not shape. However, we found that the FFA and OFA showed an equivalent release from adaptation to changes in both shape and surface properties. The dissociation between the neural and perceptual responses suggests that, although they may play a role in the process, these core face regions are not solely responsible for the recognition of facial identity. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Predicting behavior change from persuasive messages using neural representational similarity and social network analyses.

    Science.gov (United States)

    Pegors, Teresa K; Tompson, Steven; O'Donnell, Matthew Brook; Falk, Emily B

    2017-08-15

    Neural activity in medial prefrontal cortex (MPFC), identified as engaging in self-related processing, predicts later health behavior change. However, it is unknown to what extent individual differences in neural representation of content and lived experience influence this brain-behavior relationship. We examined whether the strength of content-specific representations during persuasive messaging relates to later behavior change, and whether these relationships change as a function of individuals' social network composition. In our study, smokers viewed anti-smoking messages while undergoing fMRI and we measured changes in their smoking behavior one month later. Using representational similarity analyses, we found that the degree to which message content (i.e. health, social, or valence information) was represented in a self-related processing MPFC region was associated with later smoking behavior, with increased representations of negatively valenced (risk) information corresponding to greater message-consistent behavior change. Furthermore, the relationship between representations and behavior change depended on social network composition: smokers who had proportionally fewer smokers in their network showed increases in smoking behavior when social or health content was strongly represented in MPFC, whereas message-consistent behavior (i.e., less smoking) was more likely for those with proportionally more smokers in their social network who represented social or health consequences more strongly. These results highlight the dynamic relationship between representations in MPFC and key outcomes such as health behavior change; a complete understanding of the role of MPFC in motivation and action should take into account individual differences in neural representation of stimulus attributes and social context variables such as social network composition. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. An auditory neural correlate suggests a mechanism underlying holistic pitch perception.

    Directory of Open Access Journals (Sweden)

    Daryl Wile

    Full Text Available Current theories of auditory pitch perception propose that cochlear place (spectral and activity timing pattern (temporal information are somehow combined within the brain to produce holistic pitch percepts, yet the neural mechanisms for integrating these two kinds of information remain obscure. To examine this process in more detail, stimuli made up of three pure tones whose components are individually resolved by the peripheral auditory system, but that nonetheless elicit a holistic, "missing fundamental" pitch percept, were played to human listeners. A technique was used to separate neural timing activity related to individual components of the tone complexes from timing activity related to an emergent feature of the complex (the envelope, and the region of the tonotopic map where information could originate from was simultaneously restricted by masking noise. Pitch percepts were mirrored to a very high degree by a simple combination of component-related and envelope-related neural responses with similar timing that originate within higher-frequency regions of the tonotopic map where stimulus components interact. These results suggest a coding scheme for holistic pitches whereby limited regions of the tonotopic map (spectral places carrying envelope- and component-related activity with similar timing patterns selectively provide a key source of neural pitch information. A similar mechanism of integration between local and emergent object properties may contribute to holistic percepts in a variety of sensory systems.

  5. Crystal Structure Representation for Neural Networks using Topological Approach.

    Science.gov (United States)

    Fedorov, Aleksandr V; Shamanaev, Ivan V

    2017-08-01

    In the present work we describe a new approach, which uses topology of crystals for physicochemical properties prediction using artificial neural networks (ANN). The topologies of 268 crystal structures were determined using ToposPro software. Quotient graphs were used to identify topological centers and their neighbors. The topological approach was illustrated by training ANN to predict molar heat capacity, standard molar entropy and lattice energy of 268 crystals with different compositions and structures (metals, inorganic salts, oxides, etc.). ANN was trained using Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Mean absolute percentage error of predicted properties was ≤8 %. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Neural representation of reward probability: evidence from the illusion of control.

    Science.gov (United States)

    Kool, Wouter; Getz, Sarah J; Botvinick, Matthew M

    2013-06-01

    To support reward-based decision-making, the brain must encode potential outcomes both in terms of their incentive value and their probability of occurrence. Recent research has made it clear that the brain bears multiple representations of reward magnitude, meaning that a single choice option may be represented differently-and even inconsistently-in different brain areas. There are some hints that the same may be true for reward probability. Preliminary evidence hints that, even as systematic distortions of probability are expressed in behavior, these may not always be uniformly reflected at the neural level: Some neural representations of probability may be immune from such distortions. This study provides new evidence consistent with this possibility. Participants in a behavioral experiment displayed a classic "illusion of control," providing higher estimates of reward probability for gambles they had chosen than for identical gambles that were imposed on them. However, an fMRI study of the same task revealed that neural prediction error signals, arising when gamble outcomes were revealed, were unaffected by the illusion of control. The resulting behavioral-neural dissociation reinforces the case for multiple, inconsistent internal representations of reward probability, while also prompting a reinterpretation of the illusion of control effect itself.

  7. Social Categories Shape the Neural Representation of Emotion: Evidence from a Visual Face Adaptation Task.

    Directory of Open Access Journals (Sweden)

    Marte eOtten

    2012-02-01

    Full Text Available A number of recent behavioral studies have shown that emotional expressions are differently perceived depending on the race of a face, and that that perception of race cues is influenced by emotional expressions. However, neural processes related to the perception of invariant cues that indicate the identity of a face (such as race are often described to proceed independently of processes related to the perception of cues that can vary over time (such as emotion. Using a visual face adaptation paradigm, we tested whether these behavioral interactions between emotion and race also reflect interdependent neural representation of emotion and race. We compared visual emotion aftereffects when the adapting face and ambiguous test face differed in race or not. Emotion aftereffects were much smaller in different race trials than same race trials, indicating that the neural representation of a facial expression is significantly different depending on whether the emotional face is black or white. It thus seems that invariable cues such as race interact with variable face cues such as emotion not just at a response level, but also at the level of perception and neural representation.

  8. Reduced Fidelity of Neural Representation Underlies Episodic Memory Decline in Normal Aging.

    Science.gov (United States)

    Zheng, Li; Gao, Zhiyao; Xiao, Xiaoqian; Ye, Zhifang; Chen, Chuansheng; Xue, Gui

    2017-06-07

    Emerging studies have emphasized the importance of the fidelity of cortical representation in forming enduring episodic memory. No study, however, has examined whether there are age-related reductions in representation fidelity that can explain memory declines in normal aging. Using functional MRI and multivariate pattern analysis, we found that older adults showed reduced representation fidelity in the visual cortex, which accounted for their decreased memory performance even after controlling for the contribution of reduced activation level. This reduced fidelity was specifically due to older adults' poorer item-specific representation, not due to their lower activation level and variance, greater variability in neuro-vascular coupling, or decreased selectivity of categorical representation (i.e., dedifferentiation). Older adults also showed an enhanced subsequent memory effect in the prefrontal cortex based on activation level, and their prefrontal activation was associated with greater fidelity of representation in the visual cortex and better memory performance. The fidelity of cortical representation thus may serve as a promising neural index for better mechanistic understanding of the memory declines and its compensation in normal aging. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

    Science.gov (United States)

    Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.

    2016-10-01

    Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

  10. Emotional complexity and the neural representation of emotion in motion.

    Science.gov (United States)

    Tavares, Paula; Barnard, Philip J; Lawrence, Andrew D

    2011-01-01

    According to theories of emotional complexity, individuals low in emotional complexity encode and represent emotions in visceral or action-oriented terms, whereas individuals high in emotional complexity encode and represent emotions in a differentiated way, using multiple emotion concepts. During functional magnetic resonance imaging, participants viewed valenced animated scenarios of simple ball-like figures attending either to social or spatial aspects of the interactions. Participant's emotional complexity was assessed using the Levels of Emotional Awareness Scale. We found a distributed set of brain regions previously implicated in processing emotion from facial, vocal and bodily cues, in processing social intentions, and in emotional response, were sensitive to emotion conveyed by motion alone. Attention to social meaning amplified the influence of emotion in a subset of these regions. Critically, increased emotional complexity correlated with enhanced processing in a left temporal polar region implicated in detailed semantic knowledge; with a diminished effect of social attention; and with increased differentiation of brain activity between films of differing valence. Decreased emotional complexity was associated with increased activity in regions of pre-motor cortex. Thus, neural coding of emotion in semantic vs action systems varies as a function of emotional complexity, helping reconcile puzzling inconsistencies in neuropsychological investigations of emotion recognition.

  11. Neural representation of the sensorimotor speech-action-repository

    Directory of Open Access Journals (Sweden)

    Cornelia eEckers

    2013-04-01

    Full Text Available A speech-action-repository (SAR or mental syllabary has been proposed as a central module for sensorimotor processing of syllables. In this approach, syllables occurring frequently within language are assumed to be stored as holistic sensorimotor patterns, while non-frequent syllables need to be assembled from sub-syllabic units. Thus, frequent syllables are processed efficiently and quickly during production or perception by a direct activation of their sensorimotor patterns. Whereas several behavioral psycholinguistic studies provided evidence in support of the existence of a syllabary, fMRI studies have failed to demonstrate its neural reality. In the present fMRI study a reaction paradigm using homogeneous vs. heterogeneous syllable blocks are used during overt vs. covert speech production and auditory vs. visual presentation modes. Two complementary data analyses were performed: (1 in a logical conjunction, activation for syllable processing independent of input modality and response mode was assessed, in order to support the assumption of existence of a supramodal hub within a SAR. (2 In addition priming effects in the BOLD response in homogeneous vs. heterogeneous blocks were measured in order to identify brain regions, which indicate reduced activity during multiple production/perception repetitions of a specific syllable in order to determine state maps. Auditory-visual conjunction analysis revealed an activation network comprising bilateral precentral gyrus and left inferior frontal gyrus (area 44. These results are compatible with the notion of a supramodal hub within the SAR. The main effect of homogeneity priming revealed an activation pattern of areas within frontal, temporal, and parietal lobe. These findings are taken to represent sensorimotor state maps of the SAR. In conclusion, the present study provided preliminary evidence for a SAR.

  12. What recent research on diagrams suggests about learning with rather than learning from visual representations in science

    Science.gov (United States)

    Tippett, Christine D.

    2016-03-01

    The move from learning science from representations to learning science with representations has many potential and undocumented complexities. This thematic analysis partially explores the trends of representational uses in science instruction, examining 80 research studies on diagram use in science. These studies, published during 2000-2014, were located through searches of journal databases and books. Open coding of the studies identified 13 themes, 6 of which were identified in at least 10% of the studies: eliciting mental models, classroom-based research, multimedia principles, teaching and learning strategies, representational competence, and student agency. A shift in emphasis on learning with rather than learning from representations was evident across the three 5-year intervals considered, mirroring a pedagogical shift from science instruction as transmission of information to constructivist approaches in which learners actively negotiate understanding and construct knowledge. The themes and topics in recent research highlight areas of active interest and reveal gaps that may prove fruitful for further research, including classroom-based studies, the role of prior knowledge, and the use of eye-tracking. The results of the research included in this thematic review of the 2000-2014 literature suggest that both interpreting and constructing representations can lead to better understanding of science concepts.

  13. Deep neural networks rival the representation of primate IT cortex for core visual object recognition.

    Directory of Open Access Journals (Sweden)

    Charles F Cadieu

    2014-12-01

    Full Text Available The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition. This remarkable performance is mediated by the representation formed in inferior temporal (IT cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs. It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of "kernel analysis" that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds.

  14. Neural representation of the self-heard biosonar click in bottlenose dolphins (Tursiops truncatus).

    Science.gov (United States)

    Finneran, James J; Mulsow, Jason; Houser, Dorian S; Schlundt, Carolyn E

    2017-05-01

    The neural representation of the dolphin broadband biosonar click was investigated by measuring auditory brainstem responses (ABRs) to "self-heard" clicks masked with noise bursts having various high-pass cutoff frequencies. Narrowband ABRs were obtained by sequentially subtracting responses obtained with noise having lower high-pass cutoff frequencies from those obtained with noise having higher cutoff frequencies. For comparison to the biosonar data, ABRs were also measured in a passive listening experiment, where external clicks and masking noise were presented to the dolphins and narrowband ABRs were again derived using the subtractive high-pass noise technique. The results showed little change in the peak latencies of the ABR to the self-heard click from 28 to 113 kHz; i.e., the high-frequency neural responses to the self-heard click were delayed relative to those of an external, spectrally "pink" click. The neural representation of the self-heard click is thus highly synchronous across the echolocation frequencies and does not strongly resemble that of a frequency modulated downsweep (i.e., decreasing-frequency chirp). Longer ABR latencies at higher frequencies are hypothesized to arise from spectral differences between self-heard clicks and external clicks, forward masking from previously emitted biosonar clicks, or neural inhibition accompanying the emission of clicks.

  15. Standard representation and unified stability analysis for dynamic artificial neural network models.

    Science.gov (United States)

    Kim, Kwang-Ki K; Patrón, Ernesto Ríos; Braatz, Richard D

    2017-12-02

    An overview is provided of dynamic artificial neural network models (DANNs) for nonlinear dynamical system identification and control problems, and convex stability conditions are proposed that are less conservative than past results. The three most popular classes of dynamic artificial neural network models are described, with their mathematical representations and architectures followed by transformations based on their block diagrams that are convenient for stability and performance analyses. Classes of nonlinear dynamical systems that are universally approximated by such models are characterized, which include rigorous upper bounds on the approximation errors. A unified framework and linear matrix inequality-based stability conditions are described for different classes of dynamic artificial neural network models that take additional information into account such as local slope restrictions and whether the nonlinearities within the DANNs are odd. A theoretical example shows reduced conservatism obtained by the conditions. Copyright © 2017. Published by Elsevier Ltd.

  16. Neuroeconomics: in search of the neural representation of brands.

    Science.gov (United States)

    Schaefer, Michael

    2009-01-01

    In modern economy the customer is confronted with a huge amount of consumer goods. In this situation, culturally based brands seem to play an important role in establishing strong emotional bonds between customers and goods and to guide people's economic behavior by biasing selections and preference decisions based on affect. Recently, neuroscientific approaches have demonstrated that cultural objects like brands or brand-related behavior may successfully be investigated with neuroimaging tools like fMRI. First studies suggested that structures associated with the reward circuit (striatum) and the dorsolateral part of the prefrontal cortex may be involved when perceiving a favorite brand. Hence, brands that have been associated with appetitive stimuli due to marketing efforts or cultural factors seem to engage similar brain networks than artificially associated reward stimuli. However, brands have different and complex meanings in our life far beyond representing objects of desire. For example, the possession of goods from certain kinds of brands often is used to mark the social state of the owner and to distinguish him or her from other groups. In particular, luxury goods often seem to have this function. Recent neuroimaging results support this observation by showing that viewing logos of luxury brands is associated with brain activity in the anterior medial prefrontal cortex, a region known to be associated with self-centered cognitions. Thus, it seems that brands of luxury goods improve self-relevant thoughts, pointing to the role of luxury brands to mark the superior position of the owner in society. These results demonstrate that cultural symbols like brands can successfully be examined with neuroimaging approaches. Thus, along with advanced cultural theories, neuroeconomics may provide important contributions to the understanding of brand-related or economic behavior.

  17. Image decomposition fusion method based on sparse representation and neural network.

    Science.gov (United States)

    Chang, Lihong; Feng, Xiangchu; Zhang, Rui; Huang, Hua; Wang, Weiwei; Xu, Chen

    2017-10-01

    For noisy images, in most existing sparse representation-based models, fusion and denoising proceed simultaneously using the coefficients of a universal dictionary. This paper proposes an image fusion method based on a cartoon + texture dictionary pair combined with a deep neural network combination (DNNC). In our model, denoising and fusion are carried out alternately. The proposed method is divided into three main steps: denoising + fusion + network denoising. More specifically, (1) denoise the source images using external/internal methods separately; (2) fuse these preliminary denoised results with external/internal cartoon and texture dictionary pair to obtain the external cartoon + texture sparse representation result (E-CTSR) and internal cartoon + texture sparse representation result (I-CTSR); and (3) combine E-CTSR and I-CTSR using DNNC (EI-CTSR) to obtain the final result. Experimental results demonstrate that EI-CTSR outperforms not only the stand-alone E-CTSR and I-CTSR methods but also state-of-the-art methods such as sparse representation (SR) and adaptive sparse representation (ASR) for isomorphic images, and E-CTSR outperforms SR and ASR for heterogeneous multi-mode images.

  18. Perceptual Competition Promotes Suppression of Reward Salience in Behavioral Selection and Neural Representation.

    Science.gov (United States)

    Gong, Mengyuan; Jia, Ke; Li, Sheng

    2017-06-28

    Visual attentional selection is influenced by the value of objects. Previous studies have demonstrated that reward-associated items lead to rapid distraction and associated behavioral costs, which are difficult to override with top-down control. However, it has not been determined whether a perceptually competitive environment could render the reward-driven distraction more susceptible to top-down suppression. Here, we trained both genders of human subjects to associate two orientations with high and low magnitudes of reward. After training, we collected fMRI data while the subjects performed a categorical visual search task. The item in the reward-associated orientation served as the distractor, and the relative physical salience between the target and distractor was carefully controlled to modulate the degree of perceptual competition. The behavioral results showed faster searches in the presence of high, relative to low, reward-associated distractors. However, this effect was evident only if the physical salience of the distractor was higher than that of the target, indicating a context-dependent suppression effect of reward salience that relied on high perceptual competition. By analyzing the fMRI data in primary visual cortex, we found that the behavioral pattern of results could be predicted by the suppressed channel responses tuned to the reward-associated orientation in the distractor location, accompanied by increased responses in the midbrain dopaminergic region. Our results suggest that the learned salience of a reward plays a flexible role in solving perceptual competition, enabling the neural system to adaptively modulate the perceptual representation for behavioral optimization.SIGNIFICANCE STATEMENT The predictiveness principle in learning theory suggests that the stimulus with high predictability of reward receives priority in attentional selection. This selection bias leads to difficulties in changing approach behaviors, and thus becomes an

  19. Concept hierarchy memory model: a neural architecture for conceptual knowledge representation, learning, and commonsense reasoning.

    Science.gov (United States)

    Tan, A H; Soon, H S

    1996-07-01

    This article introduces a neural network based cognitive architecture termed Concept Hierarchy Memory Model (CHMM) for conceptual knowledge representation and commonsense reasoning. CHMM is composed of two subnetworks: a Concept Formation Network (CFN), that acquires concepts based on their sensory representations; and a Concept Hierarchy Network (CHN), that encodes hierarchical relationships between concepts. Based on Adaptive Resonance Associative Map (ARAM), a supervised Adaptive Resonance Theory (ART) model, CHMM provides a systematic treatment for concept formation and organization of a concept hierarchy. Specifically, a concept can be learned by sampling activities across multiple sensory fields. By chunking relations between concepts as cognitive codes, a concept hierarchy can be learned/modified through experience. Also, fuzzy relations between concepts can now be represented in terms of the weights on the links connecting them. Using a unified inferencing mechanism based on code firing, CHMM performs an important class of commonsense reasoning, including concept recognition and property inheritance.

  20. Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts.

    Science.gov (United States)

    Gómez-Adorno, Helena; Markov, Ilia; Sidorov, Grigori; Posadas-Durán, Juan-Pablo; Sanchez-Perez, Miguel A; Chanona-Hernandez, Liliana

    2016-01-01

    We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available.

  1. Generalized neural-network representation of high-dimensional potential-energy surfaces.

    Science.gov (United States)

    Behler, Jörg; Parrinello, Michele

    2007-04-06

    The accurate description of chemical processes often requires the use of computationally demanding methods like density-functional theory (DFT), making long simulations of large systems unfeasible. In this Letter we introduce a new kind of neural-network representation of DFT potential-energy surfaces, which provides the energy and forces as a function of all atomic positions in systems of arbitrary size and is several orders of magnitude faster than DFT. The high accuracy of the method is demonstrated for bulk silicon and compared with empirical potentials and DFT. The method is general and can be applied to all types of periodic and nonperiodic systems.

  2. Neural Representation of Concurrent Vowels in Macaque Primary Auditory Cortex123

    Science.gov (United States)

    Micheyl, Christophe; Steinschneider, Mitchell

    2016-01-01

    Abstract Successful speech perception in real-world environments requires that the auditory system segregate competing voices that overlap in frequency and time into separate streams. Vowels are major constituents of speech and are comprised of frequencies (harmonics) that are integer multiples of a common fundamental frequency (F0). The pitch and identity of a vowel are determined by its F0 and spectral envelope (formant structure), respectively. When two spectrally overlapping vowels differing in F0 are presented concurrently, they can be readily perceived as two separate “auditory objects” with pitches at their respective F0s. A difference in pitch between two simultaneous vowels provides a powerful cue for their segregation, which in turn, facilitates their individual identification. The neural mechanisms underlying the segregation of concurrent vowels based on pitch differences are poorly understood. Here, we examine neural population responses in macaque primary auditory cortex (A1) to single and double concurrent vowels (/a/ and /i/) that differ in F0 such that they are heard as two separate auditory objects with distinct pitches. We find that neural population responses in A1 can resolve, via a rate-place code, lower harmonics of both single and double concurrent vowels. Furthermore, we show that the formant structures, and hence the identities, of single vowels can be reliably recovered from the neural representation of double concurrent vowels. We conclude that A1 contains sufficient spectral information to enable concurrent vowel segregation and identification by downstream cortical areas. PMID:27294198

  3. Multivariate Cross-Classification: Applying machine learning techniques to characterize abstraction in neural representations

    Directory of Open Access Journals (Sweden)

    Jonas eKaplan

    2015-03-01

    Full Text Available Here we highlight an emerging trend in the use of machine learning classifiers to test for abstraction across patterns of neural activity. When a classifier algorithm is trained on data from one cognitive context, and tested on data from another, conclusions can be drawn about the role of a given brain region in representing information that abstracts across those cognitive contexts. We call this kind of analysis Multivariate Cross-Classification (MVCC, and review several domains where it has recently made an impact. MVCC has been important in establishing correspondences among neural patterns across cognitive domains, including motor-perception matching and cross-sensory matching. It has been used to test for similarity between neural patterns evoked by perception and those generated from memory. Other work has used MVCC to investigate the similarity of representations for semantic categories across different kinds of stimulus presentation, and in the presence of different cognitive demands. We use these examples to demonstrate the power of MVCC as a tool for investigating neural abstraction and discuss some important methodological issues related to its application.

  4. Discriminative feature representation for image classification via multimodal multitask deep neural networks

    Science.gov (United States)

    Mei, Shuang; Yang, Hua; Yin, Zhouping

    2017-01-01

    A good image feature representation is crucial for image classification tasks. Many traditional applications have attempted to design single-modal features for image classification; however, these may have difficulty extracting sufficient information, resulting in misjudgments for various categories. Recently, researchers have focused on designing multimodal features, which have been successfully employed in many situations. However, there are still some problems in this research area, including selecting efficient features for each modality, transforming them to the subspace feature domain, and removing the heterogeneities among different modalities. We propose an end-to-end multimodal deep neural network (MDNN) framework to automate the feature selection and transformation procedures for image classification. Furthermore, inspired by Fisher's theory of linear discriminant analysis, we improve the proposed MDNN by further proposing a multimodal multitask deep neural network (M2DNN) model. The motivation behind M2DNN is to improve the classification performance by incorporating an auxiliary discriminative constraint to the subspace representation. Experimental results on five representative datasets (NUS-WIDE, Scene-15, Texture-25, Indoor-67, and Caltech-101) demonstrate the effectiveness of the proposed MDNN and M2DNN models. In addition, experimental comparisons of the Fisher score criterion exhibit that M2DNN is more robust and has better discriminative power than other approaches.

  5. A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning.

    Science.gov (United States)

    Loonis, Roman F; Brincat, Scott L; Antzoulatos, Evan G; Miller, Earl K

    2017-10-11

    A meta-analysis of non-human primates performing three different tasks (Object-Match, Category-Match, and Category-Saccade associations) revealed signatures of explicit and implicit learning. Performance improved equally following correct and error trials in the Match (explicit) tasks, but it improved more after correct trials in the Saccade (implicit) task, a signature of explicit versus implicit learning. Likewise, error-related negativity, a marker for error processing, was greater in the Match (explicit) tasks. All tasks showed an increase in alpha/beta (10-30 Hz) synchrony after correct choices. However, only the implicit task showed an increase in theta (3-7 Hz) synchrony after correct choices that decreased with learning. In contrast, in the explicit tasks, alpha/beta synchrony increased with learning and decreased thereafter. Our results suggest that explicit versus implicit learning engages different neural mechanisms that rely on different patterns of oscillatory synchrony. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Neural representations and mechanisms for the performance of simple speech sequences.

    Science.gov (United States)

    Bohland, Jason W; Bullock, Daniel; Guenther, Frank H

    2010-07-01

    Speakers plan the phonological content of their utterances before their release as speech motor acts. Using a finite alphabet of learned phonemes and a relatively small number of syllable structures, speakers are able to rapidly plan and produce arbitrary syllable sequences that fall within the rules of their language. The class of computational models of sequence planning and performance termed competitive queuing models have followed K. S. Lashley [The problem of serial order in behavior. In L. A. Jeffress (Ed.), Cerebral mechanisms in behavior (pp. 112-136). New York: Wiley, 1951] in assuming that inherently parallel neural representations underlie serial action, and this idea is increasingly supported by experimental evidence. In this article, we developed a neural model that extends the existing DIVA model of speech production in two complementary ways. The new model includes paired structure and content subsystems [cf. MacNeilage, P. F. The frame/content theory of evolution of speech production. Behavioral and Brain Sciences, 21, 499-511, 1998 ] that provide parallel representations of a forthcoming speech plan as well as mechanisms for interfacing these phonological planning representations with learned sensorimotor programs to enable stepping through multisyllabic speech plans. On the basis of previous reports, the model's components are hypothesized to be localized to specific cortical and subcortical structures, including the left inferior frontal sulcus, the medial premotor cortex, the basal ganglia, and the thalamus. The new model, called gradient order DIVA, thus fills a void in current speech research by providing formal mechanistic hypotheses about both phonological and phonetic processes that are grounded by neuroanatomy and physiology. This framework also generates predictions that can be tested in future neuroimaging and clinical case studies.

  7. Emotions in ‘black or white’ or shades of gray? How we think about emotion shapes our perception and neural representation of emotion

    Science.gov (United States)

    Satpute, Ajay B.; Nook, Erik C.; Narayanan, Sandhya; Shu, Jocelyn; Weber, Jochen; Ochsner, Kevin N.

    2016-01-01

    The demands of social life often require categorically judging whether someone's continuously varying facial movements express “calm” or “fear”, or whether our fluctuating internal states mean we feel “good” or “bad”. In two neuroimaging studies, we ask whether this kind of categorical, ‘black and white’, thinking can shape the perception and neural representation of emotion. Using psychometric and neuroimaging methods, we found that (1) across participants, judging emotions using a ‘black and white’ scale vs. a ‘shades of gray’ scale shifted subjective emotion perception thresholds, (2) these shifts corresponded with activity in regions associated with affective responding including the amygdala and ventral anterior insula, and (3) connectivity of these regions with the medial prefrontal cortex correlated with the magnitude of categorization-related shifts. These findings suggest that categorical thinking about emotion may actively shape the perception and neural representation of the emotions in question. PMID:27670663

  8. Emotions in "Black and White" or Shades of Gray? How We Think About Emotion Shapes Our Perception and Neural Representation of Emotion.

    Science.gov (United States)

    Satpute, Ajay B; Nook, Erik C; Narayanan, Sandhya; Shu, Jocelyn; Weber, Jochen; Ochsner, Kevin N

    2016-11-01

    The demands of social life often require categorically judging whether someone's continuously varying facial movements express "calm" or "fear," or whether one's fluctuating internal states mean one feels "good" or "bad." In two studies, we asked whether this kind of categorical, "black and white," thinking can shape the perception and neural representation of emotion. Using psychometric and neuroimaging methods, we found that (a) across participants, judging emotions using a categorical, "black and white" scale relative to judging emotions using a continuous, "shades of gray," scale shifted subjective emotion perception thresholds; (b) these shifts corresponded with activity in brain regions previously associated with affective responding (i.e., the amygdala and ventral anterior insula); and (c) connectivity of these regions with the medial prefrontal cortex correlated with the magnitude of categorization-related shifts. These findings suggest that categorical thinking about emotions may actively shape the perception and neural representation of the emotions in question. © The Author(s) 2016.

  9. Unaware Processing of Tools in the Neural System for Object-Directed Action Representation.

    Science.gov (United States)

    Tettamanti, Marco; Conca, Francesca; Falini, Andrea; Perani, Daniela

    2017-11-01

    The hypothesis that the brain constitutively encodes observed manipulable objects for the actions they afford is still debated. Yet, crucial evidence demonstrating that, even in the absence of perceptual awareness, the mere visual appearance of a manipulable object triggers a visuomotor coding in the action representation system including the premotor cortex, has hitherto not been provided. In this fMRI study, we instantiated reliable unaware visual perception conditions by means of continuous flash suppression, and we tested in 24 healthy human participants (13 females) whether the visuomotor object-directed action representation system that includes left-hemispheric premotor, parietal, and posterior temporal cortices is activated even under subliminal perceptual conditions. We found consistent activation in the target visuomotor cortices, both with and without perceptual awareness, specifically for pictures of manipulable versus non-manipulable objects. By means of a multivariate searchlight analysis, we also found that the brain activation patterns in this visuomotor network enabled the decoding of manipulable versus non-manipulable object picture processing, both with and without awareness. These findings demonstrate the intimate neural coupling between visual perception and motor representation that underlies manipulable object processing: manipulable object stimuli specifically engage the visuomotor object-directed action representation system, in a constitutive manner that is independent from perceptual awareness. This perceptuo-motor coupling endows the brain with an efficient mechanism for monitoring and planning reactions to external stimuli in the absence of awareness. SIGNIFICANCE STATEMENT Our brain constantly encodes the visual information that hits the retina, leading to a stimulus-specific activation of sensory and semantic representations, even for objects that we do not consciously perceive. Do these unconscious representations encompass the motor

  10. A study on neural network representation of reactor power control procedures 2

    Energy Technology Data Exchange (ETDEWEB)

    Moon, Byung Soo; Park, Jea Chang; Kim, Young Taek; Lee, Hee Cho; Yang, Sung Uoon; Hwang, Hee Sun; Hwang, In Ah

    1998-12-01

    The major results of this study are as follows; the first is the algorithm developed through this study for computing the spline interpolation coefficients without solving the matrix equation involved. This is expected to be used in various numerical analysis problems. If this algorithm can be extended to functions of two independent variables in the future, then it could be a big help for the finite element method used in solving various boundary value problems. The second is the method developed to reduce systematically the number of output fuzzy sets for fuzzy systems representing functions of two variables. this may be considered as an indication that the neural network representation of functions has advantages over other conventional methods. The third result is an artificial neural network system developed for automating the manual procedures being used to change the reactor power level by adding boric acid or water to the reactor coolant. This along with the neural networks developed earlier can be used in nuclear power plants as an operator aid after a verification process. (author). 8 refs., 13 tabs., 5 figs.

  11. Deep neural networks reveal a gradient in the complexity of neural representations across the ventral stream

    NARCIS (Netherlands)

    Güçlü, U.; Gerven, M.A.J. van

    2015-01-01

    Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping

  12. The neural representation of emotionally neutral faces and places in patients with panic disorder with agoraphobia.

    Science.gov (United States)

    Petrowski, Katja; Wintermann, Gloria; Smolka, Michael N; Huebner, Thomas; Donix, Markus

    2014-01-01

    Panic disorder with agoraphobia (PD-A) has been associated with abnormal neural activity for threat-related stimuli (faces, places). Recent findings suggest a disturbed neural processing of emotionally neutral stimuli at a more general level. Using functional magnetic resonance imaging (fMRI) we investigated the neural processing of emotionally neutral faces and places in PD-A. Fifteen patients with PD-A and fifteen healthy subjects participated in the study. When they perceived neutral faces and places, the patients with PD-A showed significantly less brain activity in the fusiform gyrus, the inferior occipital gyrus, the calcarine gyrus, the cerebellum, and the cuneus compared with the healthy controls. However, the patients with PD-A showed significantly more brain activity in the precuneus compared with controls subjects. It was not possible to distinguish the agoraphobia-associated effects from possible contributions due to general anxiety induced by fMRI. For future investigations, an additional clinical control group with patients suffering from panic disorder without agoraphobia would be of interest. In addition, the psychopathology concerning the agoraphobic symptoms needs to be investigated in more detail. The findings suggest altered neural processing of emotionally neutral faces and places in patients with PD-A. Reduced neural activity in different brain regions may indicate difficulties in recognizing the emotional content in face and place stimuli due to anxiety-related hyper-arousal. © 2013 Published by Elsevier B.V.

  13. Neural competition for conscious representation across time: an fMRI study.

    Directory of Open Access Journals (Sweden)

    Heleen A Slagter

    2010-05-01

    Full Text Available The information processing capacity of the human mind is limited, as is evidenced by the attentional blink (AB--a deficit in identifying the second of two temporally-close targets (T1 and T2 embedded in a rapid stream of distracters. Theories of the AB generally agree that it results from competition between stimuli for conscious representation. However, they disagree in the specific mechanisms, in particular about how attentional processing of T1 determines the AB to T2.The present study used the high spatial resolution of functional magnetic resonance imaging (fMRI to examine the neural mechanisms underlying the AB. Our research approach was to design T1 and T2 stimuli that activate distinguishable brain areas involved in visual categorization and representation. ROI and functional connectivity analyses were then used to examine how attentional processing of T1, as indexed by activity in the T1 representation area, affected T2 processing. Our main finding was that attentional processing of T1 at the level of the visual cortex predicted T2 detection rates Those individuals who activated the T1 encoding area more strongly in blink versus no-blink trials generally detected T2 on a lower percentage of trials. The coupling of activity between T1 and T2 representation areas did not vary as a function of conscious T2 perception.These data are consistent with the notion that the AB is related to attentional demands of T1 for selection, and indicate that these demands are reflected at the level of visual cortex. They also highlight the importance of individual differences in attentional settings in explaining AB task performance.

  14. Getting a grip on reality: Grasping movements directed to real objects and images rely on dissociable neural representations.

    Science.gov (United States)

    Freud, Erez; Macdonald, Scott N; Chen, Juan; Quinlan, Derek J; Goodale, Melvyn A; Culham, Jody C

    2018-01-01

    In the current era of touchscreen technology, humans commonly execute visually guided actions directed to two-dimensional (2D) images of objects. Although real, three-dimensional (3D), objects and images of the same objects share high degree of visual similarity, they differ fundamentally in the actions that can be performed on them. Indeed, previous behavioral studies have suggested that simulated grasping of images relies on different representations than actual grasping of real 3D objects. Yet the neural underpinnings of this phenomena have not been investigated. Here we used functional magnetic resonance imaging (fMRI) to investigate how brain activation patterns differed for grasping and reaching actions directed toward real 3D objects compared to images. Multivoxel Pattern Analysis (MVPA) revealed that the left anterior intraparietal sulcus (aIPS), a key region for visually guided grasping, discriminates between both the format in which objects were presented (real/image) and the motor task performed on them (grasping/reaching). Interestingly, during action planning, the representations of real 3D objects versus images differed more for grasping movements than reaching movements, likely because grasping real 3D objects involves fine-grained planning and anticipation of the consequences of a real interaction. Importantly, this dissociation was evident in the planning phase, before movement initiation, and was not found in any other regions, including motor and somatosensory cortices. This suggests that the dissociable representations in the left aIPS were not based on haptic, motor or proprioceptive feedback. Together, these findings provide novel evidence that actions, particularly grasping, are affected by the realness of the target objects during planning, perhaps because real targets require a more elaborate forward model based on visual cues to predict the consequences of real manipulation. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Reward Selectively Modulates the Lingering Neural Representation of Recently Attended Objects in Natural Scenes.

    Science.gov (United States)

    Hickey, Clayton; Peelen, Marius V

    2017-08-02

    Theories of reinforcement learning and approach behavior suggest that reward can increase the perceptual salience of environmental stimuli, ensuring that potential predictors of outcome are noticed in the future. However, outcome commonly follows visual processing of the environment, occurring even when potential reward cues have long disappeared. How can reward feedback retroactively cause now-absent stimuli to become attention-drawing in the future? One possibility is that reward and attention interact to prime lingering visual representations of attended stimuli that sustain through the interval separating stimulus and outcome. Here, we test this idea using multivariate pattern analysis of fMRI data collected from male and female humans. While in the scanner, participants searched for examples of target categories in briefly presented pictures of cityscapes and landscapes. Correct task performance was followed by reward feedback that could randomly have either high or low magnitude. Analysis showed that high-magnitude reward feedback boosted the lingering representation of target categories while reducing the representation of nontarget categories. The magnitude of this effect in each participant predicted the behavioral impact of reward on search performance in subsequent trials. Other analyses show that sensitivity to reward-as expressed in a personality questionnaire and in reactivity to reward feedback in the dopaminergic midbrain-predicted reward-elicited variance in lingering target and nontarget representations. Credit for rewarding outcome thus appears to be assigned to the target representation, causing the visual system to become sensitized for similar objects in the future. SIGNIFICANCE STATEMENT How do reward-predictive visual stimuli become salient and attention-drawing? In the real world, reward cues precede outcome and reward is commonly received long after potential predictors have disappeared. How can the representation of environmental stimuli

  16. Impact of the virtual reality on the neural representation of an environment.

    Science.gov (United States)

    Mellet, Emmanuel; Laou, Laetitia; Petit, Laurent; Zago, Laure; Mazoyer, Bernard; Tzourio-Mazoyer, Nathalie

    2010-07-01

    Despite the increasing use of virtual reality, the impact on cerebral representation of topographical knowledge of learning by virtual reality rather than by actual locomotion has never been investigated. To tackle this challenging issue, we conducted an experiment wherein participants learned an immersive virtual environment using a joystick. The following day, participants' brain activity was monitored by functional magnetic resonance imaging while they mentally estimated distances in this environment. Results were compared with that of participants performing the same task but having learned the real version of the environment by actual walking. We detected a large set of areas shared by both groups including the parieto-frontal areas and the parahippocampal gyrus. More importantly, although participants of both groups performed the same mental task and exhibited similar behavioral performances, they differed at the brain activity level. Unlike real learners, virtual learners activated a left-lateralized network associated with tool manipulation and action semantics. This demonstrated that a neural fingerprint distinguishing virtual from real learning persists when subjects use a mental representation of the learnt environment with equivalent performances. (c) 2009 Wiley-Liss, Inc.

  17. Differential representation of liver proteins in obese human subjects suggests novel biomarkers and promising targets for drug development in obesity.

    Science.gov (United States)

    Caira, Simonetta; Iannelli, Antonio; Sciarrillo, Rosaria; Picariello, Gianluca; Renzone, Giovanni; Scaloni, Andrea; Addeo, Pietro

    2017-12-01

    The proteome of liver biopsies from human obese (O) subjects has been compared to those of nonobese (NO) subjects using two-dimensional gel electrophoresis (2-DE). Differentially represented proteins were identified by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)-based peptide mass fingerprinting (PMF) and nanoflow-liquid chromatography coupled to electrospray-tandem mass spectrometry (nLC-ESI-MS/MS). Overall, 61 gene products common to all of the liver biopsies were identified within 65 spots, among which 25 ones were differently represented between O and NO subjects. In particular, over-representation of short-chain acyl-CoA dehydrogenase, Δ(3,5)-Δ(2,4)dienoyl-CoA isomerase, acetyl-CoA acetyltransferase, glyoxylate reductase/hydroxypyruvate reductase, fructose-biphosphate aldolase B, peroxiredoxin I, protein DJ-1, catalase, α- and β-hemoglobin subunits, 3-mercaptopyruvate S-transferase, calreticulin, aminoacylase 1, phenazine biosynthesis-like domain-containing protein and a form of fatty acid-binding protein, together with downrepresentation of glutamate dehydrogenase, glutathione S-transferase A1, S-adenosylmethionine synthase 1A and a form of apolipoprotein A-I, was associated with the obesity condition. Some of these metabolic enzymes and antioxidant proteins have already been identified as putative diagnostic markers of liver dysfunction in animal models of steatosis or obesity, suggesting additional investigations on their role in these syndromes. Their differential representation in human liver was suggestive of their consideration as obesity human biomarkers and for the development of novel antiobesity drugs.

  18. Contralateral delay activity provides a neural measure of the number of representations in visual working memory.

    Science.gov (United States)

    Ikkai, Akiko; McCollough, Andrew W; Vogel, Edward K

    2010-04-01

    Visual working memory (VWM) helps to temporarily represent information from the visual environment and is severely limited in capacity. Recent work has linked various forms of neural activity to the ongoing representations in VWM. One piece of evidence comes from human event-related potential studies, which find a sustained contralateral negativity during the retention period of VWM tasks. This contralateral delay activity (CDA) has previously been shown to increase in amplitude as the number of memory items increases, up to the individual's working memory capacity limit. However, significant alternative hypotheses remain regarding the true nature of this activity. Here we test whether the CDA is modulated by the perceptual requirements of the memory items as well as whether it is determined by the number of locations that are being attended within the display. Our results provide evidence against these two alternative accounts and instead strongly support the interpretation that this activity reflects the current number of objects that are being represented in VWM.

  19. Neural representation of swallowing is retained with age. A functional neuroimaging study validated by classical and Bayesian inference.

    Science.gov (United States)

    Windel, Anne-Sophie; Mihai, Paul Glad; Lotze, Martin

    2015-06-01

    We investigated the neural representation of swallowing in two age groups for a total of 51 healthy participants (seniors: average age 64 years; young adults: average age 24 years) using high spatial resolution functional magnetic resonance imaging (fMRI). Two statistical comparisons (classical and Bayesian inference) revealed no significant differences between subject groups, apart from higher cortical activation for the seniors in the frontal pole 1 of Brodmann's Area 10 using Bayesian inference. Seniors vs. young participants showed longer reaction times and higher skin conductance response (SCR) during swallowing. We found a positive association of SCR and fMRI-activation only among seniors in areas processing sensorimotor performance, arousal and emotional perception. The results indicate that the highly automated swallowing network retains its functionality with age. However, seniors with higher SCR during swallowing appear to also engage areas involved in attention control and emotional regulation, possibly suggesting increased attention and emotional demands during task performance. Copyright © 2015 Elsevier B.V. All rights reserved.

  20. Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

    Science.gov (United States)

    Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

    2001-03-01

    This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

  1. Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.

    Science.gov (United States)

    Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

    2008-01-01

    The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to differences both in the features most effective for automatic recognition and in the featural codes recruited by neural processing. Our study appeals to a computational framework characterizing the features representing object categories as sets of overlapping image fragments. Within this framework, we assess the extent to which task-relevant information differs across image fragments. Based on objective differences we find among task-specific representations, we test the sensitivity of the human visual system to these different face descriptions independently of one another. Both behavior and functional magnetic resonance imaging reveal effects elicited by objective task-specific levels of information. Behaviorally, recognition performance with image fragments improves with increasing task-specific information carried by different face fragments. Neurally, this sensitivity to the two tasks manifests as differential localization of neural responses across the ventral visual pathway. Fragments diagnostic for detection evoke larger neural responses than non-diagnostic ones in the right posterior fusiform gyrus and bilaterally in the inferior occipital gyrus. In contrast, fragments diagnostic for individuation evoke larger responses than non-diagnostic ones in the anterior inferior temporal gyrus. Finally, for individuation only, pattern analysis reveals sensitivity to task-specific information within the right "fusiform face area". OUR RESULTS DEMONSTRATE: 1) information diagnostic for face detection and individuation is roughly separable; 2) the human visual system is independently sensitive to both types of information; 3) neural responses differ according to the type of task-relevant information

  2. Multiple neural states of representation in short-term memory? It's a matter of attention

    Directory of Open Access Journals (Sweden)

    Joshua J Larocque

    2014-01-01

    Full Text Available Short-term memory (STM refers to the capacity-limited retention of information over a brief period of time, and working memory (WM refers to the manipulation and use of that information to guide behavior. In recent years it has become apparent that STM and WM interact and overlap with other cognitive processes, including attention (the selection of a subset of information for further processing and long-term memory (LTM – the encoding and retention of an effectively unlimited amount of information for a much longer period of time. Broadly speaking, there have been two classes of memory models: systems models, which posit distinct stores for STM and LTM (Atkinson & Shiffrin, 1968; Baddeley & Hitch, 1974; and state-based models, which posit a common store with different activation states corresponding to STM and LTM (Cowan, 1995; McElree, 1996; Oberauer, 2002. In this paper, we will focus on state-based accounts of STM. First, we will consider several theoretical models that postulate, based on considerable behavioral evidence, that information in STM can exist in multiple representational states. We will then consider how neural data from recent studies of STM can inform and constrain these theoretical models. In the process we will highlight the inferential advantage of multivariate, information-based analyses of neuroimaging data (fMRI and EEG over conventional activation-based analysis approaches (Postle, in press. We will conclude by addressing lingering questions regarding the fractionation of STM, highlighting differences between the attention to information vs. the retention of information during brief memory delays.

  3. Multiple neural states of representation in short-term memory? It's a matter of attention.

    Science.gov (United States)

    Larocque, Joshua J; Lewis-Peacock, Jarrod A; Postle, Bradley R

    2014-01-01

    Short-term memory (STM) refers to the capacity-limited retention of information over a brief period of time, and working memory (WM) refers to the manipulation and use of that information to guide behavior. In recent years it has become apparent that STM and WM interact and overlap with other cognitive processes, including attention (the selection of a subset of information for further processing) and long-term memory (LTM-the encoding and retention of an effectively unlimited amount of information for a much longer period of time). Broadly speaking, there have been two classes of memory models: systems models, which posit distinct stores for STM and LTM (Atkinson and Shiffrin, 1968; Baddeley and Hitch, 1974); and state-based models, which posit a common store with different activation states corresponding to STM and LTM (Cowan, 1995; McElree, 1996; Oberauer, 2002). In this paper, we will focus on state-based accounts of STM. First, we will consider several theoretical models that postulate, based on considerable behavioral evidence, that information in STM can exist in multiple representational states. We will then consider how neural data from recent studies of STM can inform and constrain these theoretical models. In the process we will highlight the inferential advantage of multivariate, information-based analyses of neuroimaging data (fMRI and electroencephalography (EEG)) over conventional activation-based analysis approaches (Postle, in press). We will conclude by addressing lingering questions regarding the fractionation of STM, highlighting differences between the attention to information vs. the retention of information during brief memory delays.

  4. Love flows downstream: mothers' and children's neural representation similarity in perceiving distress of self and family.

    Science.gov (United States)

    Lee, Tae-Ho; Qu, Yang; Telzer, Eva H

    2017-12-01

    The current study aimed to capture empathy processing in an interpersonal context. Mother-adolescent dyads (N = 22) each completed an empathy task during fMRI, in which they imagined the target person in distressing scenes as either themselves or their family (i.e. child for the mother, mother for the child). Using multi-voxel pattern approach, we compared neural pattern similarity for the self and family conditions and found that mothers showed greater perceptual similarity between self and child in the fusiform face area (FFA), representing high self-child overlap, whereas adolescents showed significantly less self-mother overlap. Adolescents' pattern similarity was dependent upon family relationship quality, such that they showed greater self-mother overlap with higher relationship quality, whereas mothers' pattern similarity was independent of relationship quality. Furthermore, adolescents' perceptual similarity in the FFA was associated with increased social brain activation (e.g. temporal parietal junction). Mediation analyses indicated that high relationship quality was associated with greater social brain activation, which was mediated by greater self-mother overlap in the FFA. Our findings suggest that adolescents show more distinct neural patterns in perceiving their own vs their mother's distress, and such distinction is sensitive to mother-child relationship quality. In contrast, mothers' perception for their own and child's distress is highly similar and unconditional. © The Author (2017). Published by Oxford University Press.

  5. Neural representation and clinically relevant moderators of individualised self-criticism in healthy subjects

    Science.gov (United States)

    Schlumpf, Yolanda; Spinelli, Simona; Späti, Jakub; Brakowski, Janis; Quednow, Boris B.; Seifritz, Erich; Grosse Holtforth, Martin

    2014-01-01

    Many people routinely criticise themselves. While self-criticism is largely unproblematic for most individuals, depressed patients exhibit excessive self-critical thinking, which leads to strong negative affects. We used functional magnetic resonance imaging in healthy subjects (N = 20) to investigate neural correlates and possible psychological moderators of self-critical processing. Stimuli consisted of individually selected adjectives of personally negative content and were contrasted with neutral and negative non-self-referential adjectives. We found that confrontation with self-critical material yielded neural activity in regions involved in emotions (anterior insula/hippocampus–amygdala formation) and in anterior and posterior cortical midline structures, which are associated with self-referential and autobiographical memory processing. Furthermore, contrasts revealed an extended network of bilateral frontal brain areas. We suggest that the co-activation of superior and inferior lateral frontal brain regions reflects the recruitment of a frontal top–down pathway, representing cognitive reappraisal strategies for dealing with evoked negative affects. In addition, activation of right superior frontal areas was positively associated with neuroticism and negatively associated with cognitive reappraisal. Although these findings may not be specific to negative stimuli, they support a role for clinically relevant personality traits in successful regulation of emotion during confrontation with self-critical material. PMID:23887820

  6. Exploring the Neural Representation of Novel Words Learned through Enactment in a Word Recognition Task.

    Science.gov (United States)

    Macedonia, Manuela; Mueller, Karsten

    2016-01-01

    Vocabulary learning in a second language is enhanced if learners enrich the learning experience with self-performed iconic gestures. This learning strategy is called enactment. Here we explore how enacted words are functionally represented in the brain and which brain regions contribute to enhance retention. After an enactment training lasting 4 days, participants performed a word recognition task in the functional Magnetic Resonance Imaging (fMRI) scanner. Data analysis suggests the participation of different and partially intertwined networks that are engaged in higher cognitive processes, i.e., enhanced attention and word recognition. Also, an experience-related network seems to map word representation. Besides core language regions, this latter network includes sensory and motor cortices, the basal ganglia, and the cerebellum. On the basis of its complexity and the involvement of the motor system, this sensorimotor network might explain superior retention for enactment.

  7. The Neural Representation of Goal-Directed Actions and Outcomes in the Ventral Striatum's Olfactory Tubercle

    Science.gov (United States)

    Gadziola, Marie A.

    2016-01-01

    The ventral striatum is critical for evaluating reward information and the initiation of goal-directed behaviors. The many cellular, afferent, and efferent similarities between the ventral striatum's nucleus accumbens and olfactory tubercle (OT) suggests the distributed involvement of neurons within the ventral striatopallidal complex in motivated behaviors. Although the nucleus accumbens has an established role in representing goal-directed actions and their outcomes, it is not known whether this function is localized within the nucleus accumbens or distributed also within the OT. Answering such a fundamental question will expand our understanding of the neural mechanisms underlying motivated behaviors. Here we address whether the OT encodes natural reinforcers and serves as a substrate for motivational information processing. In recordings from mice engaged in a novel water-motivated instrumental task, we report that OT neurons modulate their firing rate during initiation and progression of the instrumental licking behavior, with some activity being internally generated and preceding the first lick. We further found that as motivational drive decreases throughout a session, the activity of OT neurons is enhanced earlier relative to the behavioral action. Additionally, OT neurons discriminate the types and magnitudes of fluid reinforcers. Together, these data suggest that the processing of reward information and the orchestration of goal-directed behaviors is a global principle of the ventral striatum and have important implications for understanding the neural systems subserving addiction and mood disorders. SIGNIFICANCE STATEMENT Goal-directed behaviors are widespread among animals and underlie complex behaviors ranging from food intake, social behavior, and even pathological conditions, such as gambling and drug addiction. The ventral striatum is a neural system critical for evaluating reward information and the initiation of goal-directed behaviors. Here we

  8. Dissociable neural representations of grammatical gender in Broca's area investigated by the combination of satiation and TMS.

    Science.gov (United States)

    Cattaneo, Zaira; Devlin, Joseph T; Vecchi, Tomaso; Silvanto, Juha

    2009-08-15

    Along with meaning and form, words can be described on the basis of their grammatical properties. Grammatical gender is often used to investigate the latter as it is a grammatical property that is independent of meaning. The left inferior frontal gyrus (IFG) has been implicated in the encoding of grammatical gender, but its causal role in this process in neurologically normal observers has not been demonstrated. Here we combined verbal satiation with transcranial magnetic stimulation (TMS) to demonstrate that subpopulations of neurons within Broca's area respond preferentially to different classes of grammatical gender. Subjects were asked to classify Italian nouns into living and nonliving categories; half of these words were of masculine and the other half of feminine grammatical gender. Prior to each test block, a satiation paradigm (a phenomenon in which verbal repetition of a category name leads to a reduced access to that category) was used to modulate the initial state of the representations of either masculine or feminine noun categories. In the No TMS condition, subjects were slower in responding to exemplars to the satiated category relative to exemplars of the nonsatiated category, implying that the neural representations for different classes of grammatical gender are partly dissociable. The application of TMS over Broca's area removed the behavioral impact of verbal (grammatical) satiation, demonstrating the causal role of this region in the encoding of grammatical gender. These results show that the neural representations for different cases of a grammatical property within Broca's area are dissociable.

  9. Neural representation of self-concept in sighted and congenitally blind adults.

    Science.gov (United States)

    Ma, Yina; Han, Shihui

    2011-01-01

    The functional organization of human primary visual and auditory cortices is influenced by sensory experience and exhibits cross-modal plasticity in the absence of input from one modality. However, it remains debated whether the functional architecture of the prefrontal cortex, when engaged in social cognitive processes, is shaped by sensory experience. The present study investigated whether activity in the medial prefrontal cortex underlying self-reflective thinking of one's own traits is modality-specific and whether it undergoes cross-modal plasticity in the absence of visual input. We scanned 47 sighted participants and 21 congenitally blind individuals using functional magnetic resonance imaging during trait judgements of the self and a familiar other. Sighted participants showed medial prefrontal activation and enhanced functional connectivity between the medial prefrontal and visual cortices during self-judgements compared to other-judgements on visually but not aurally presented trait words, indicating that medial prefrontal activity underlying self-representation is visual modality-specific in sighted people. In contrast, blind individuals showed medial prefrontal activation and enhanced functional connectivity between the medial prefrontal and occipital cortices during self-judgements relative to other-judgements on aurally presented stimuli, suggesting that visual deprivation leads to functional reorganization of the medial prefrontal cortex so as to be tuned by auditory inputs during self-referential processing. The medial prefrontal activity predicted memory performances on trait words used for self-judgements in both subject groups, implicating a similar functional role of the medial prefrontal cortex in self-referential processing in sighted and blind individuals. Together, our findings indicate that self-representation in the medial prefrontal cortex is strongly shaped by sensory experience.

  10. Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris.

    Directory of Open Access Journals (Sweden)

    Martin F Strube-Bloss

    Full Text Available To trigger innate behavior, sensory neural networks are pre-tuned to extract biologically relevant stimuli. Many male-female or insect-plant interactions depend on this phenomenon. Especially communication among individuals within social groups depends on innate behaviors. One example is the efficient recruitment of nest mates by successful bumblebee foragers. Returning foragers release a recruitment pheromone in the nest while they perform a 'dance' behavior to activate unemployed nest mates. A major component of this pheromone is the sesquiterpenoid farnesol. How farnesol is processed and perceived by the olfactory system, has not yet been identified. It is much likely that processing farnesol involves an innate mechanism for the extraction of relevant information to trigger a fast and reliable behavioral response. To test this hypothesis, we used population response analyses of 100 antennal lobe (AL neurons recorded in alive bumblebee workers under repeated stimulation with four behaviorally different, but chemically related odorants (geraniol, citronellol, citronellal and farnesol. The analysis identified a unique neural representation of the recruitment pheromone component compared to the other odorants that are predominantly emitted by flowers. The farnesol induced population activity in the AL allowed a reliable separation of farnesol from all other chemically related odor stimuli we tested. We conclude that the farnesol induced population activity may reflect a predetermined representation within the AL-neural network allowing efficient and fast extraction of a behaviorally relevant stimulus. Furthermore, the results show that population response analyses of multiple single AL-units may provide a powerful tool to identify distinct representations of behaviorally relevant odors.

  11. Extracting the Behaviorally Relevant Stimulus: Unique Neural Representation of Farnesol, a Component of the Recruitment Pheromone of Bombus terrestris.

    Science.gov (United States)

    Strube-Bloss, Martin F; Brown, Austin; Spaethe, Johannes; Schmitt, Thomas; Rössler, Wolfgang

    2015-01-01

    To trigger innate behavior, sensory neural networks are pre-tuned to extract biologically relevant stimuli. Many male-female or insect-plant interactions depend on this phenomenon. Especially communication among individuals within social groups depends on innate behaviors. One example is the efficient recruitment of nest mates by successful bumblebee foragers. Returning foragers release a recruitment pheromone in the nest while they perform a 'dance' behavior to activate unemployed nest mates. A major component of this pheromone is the sesquiterpenoid farnesol. How farnesol is processed and perceived by the olfactory system, has not yet been identified. It is much likely that processing farnesol involves an innate mechanism for the extraction of relevant information to trigger a fast and reliable behavioral response. To test this hypothesis, we used population response analyses of 100 antennal lobe (AL) neurons recorded in alive bumblebee workers under repeated stimulation with four behaviorally different, but chemically related odorants (geraniol, citronellol, citronellal and farnesol). The analysis identified a unique neural representation of the recruitment pheromone component compared to the other odorants that are predominantly emitted by flowers. The farnesol induced population activity in the AL allowed a reliable separation of farnesol from all other chemically related odor stimuli we tested. We conclude that the farnesol induced population activity may reflect a predetermined representation within the AL-neural network allowing efficient and fast extraction of a behaviorally relevant stimulus. Furthermore, the results show that population response analyses of multiple single AL-units may provide a powerful tool to identify distinct representations of behaviorally relevant odors.

  12. Neural Correlates of Visual Short-term Memory Dissociate between Fragile and Working Memory Representations.

    Science.gov (United States)

    Vandenbroucke, Annelinde R E; Sligte, Ilja G; de Vries, Jade G; Cohen, Michael X; Lamme, Victor A F

    2015-12-01

    Evidence is accumulating that the classic two-stage model of visual STM (VSTM), comprising iconic memory (IM) and visual working memory (WM), is incomplete. A third memory stage, termed fragile VSTM (FM), seems to exist in between IM and WM [Vandenbroucke, A. R. E., Sligte, I. G., & Lamme, V. A. F. Manipulations of attention dissociate fragile visual STM from visual working memory. Neuropsychologia, 49, 1559-1568, 2011; Sligte, I. G., Scholte, H. S., & Lamme, V. A. F. Are there multiple visual STM stores? PLoS One, 3, e1699, 2008]. Although FM can be distinguished from IM using behavioral and fMRI methods, the question remains whether FM is a weak expression of WM or a separate form of memory with its own neural signature. Here, we tested whether FM and WM in humans are supported by dissociable time-frequency features of EEG recordings. Participants performed a partial-report change detection task, from which individual differences in FM and WM capacity were estimated. These individual FM and WM capacities were correlated with time-frequency characteristics of the EEG signal before and during encoding and maintenance of the memory display. FM capacity showed negative alpha correlations over peri-occipital electrodes, whereas WM capacity was positively related, suggesting increased visual processing (lower alpha) to be related to FM capacity. Furthermore, FM capacity correlated with an increase in theta power over central electrodes during preparation and processing of the memory display, whereas WM did not. In addition to a difference in visual processing characteristics, a positive relation between gamma power and FM capacity was observed during both preparation and maintenance periods of the task. On the other hand, we observed that theta-gamma coupling was negatively correlated with FM capacity, whereas it was slightly positively correlated with WM. These data show clear differences in the neural substrates of FM versus WM and suggest that FM depends more on

  13. Multivariate Neural Representations of Value during Reward Anticipation and Consummation in the Human Orbitofrontal Cortex

    Science.gov (United States)

    Yan, Chao; Su, Li; Wang, Yi; Xu, Ting; Yin, Da-zhi; Fan, Ming-xia; Deng, Ci-ping; Hu, Yang; Wang, Zhao-xin; Cheung, Eric F. C.; Lim, Kelvin O.; Chan, Raymond C. K.

    2016-01-01

    The role of the orbitofrontal cortex (OFC) in value processing is a focus of research. Conventional imaging analysis, where smoothing and averaging are employed, may not be sufficiently sensitive in studying the OFC, which has heterogeneous anatomical structures and functions. In this study, we employed representational similarity analysis (RSA) to reveal the multi-voxel fMRI patterns in the OFC associated with value processing during the anticipatory and the consummatory phases. We found that multi-voxel activation patterns in the OFC encoded magnitude and partial valence information (win vs. loss) but not outcome (favourable vs. unfavourable) during reward consummation. Furthermore, the lateral OFC rather than the medial OFC encoded loss information. Also, we found that OFC encoded values in a similar way to the ventral striatum (VS) or the anterior insula (AI) during reward anticipation regardless of motivated response and to the medial prefrontal cortex (MPFC) and the VS in reward consummation. In contrast, univariate analysis did not show changes of activation in the OFC. These findings suggest an important role of the OFC in value processing during reward anticipation and consummation. PMID:27378417

  14. The neural substrates of complex argument structure representations: Processing 'alternating transitivity' verbs.

    Science.gov (United States)

    Meltzer-Asscher, Aya; Schuchard, Julia; den Ouden, Dirk-Bart; Thompson, Cynthia K

    This study examines the neural correlates of processing verbal entries with multiple argument structures using fMRI. We compared brain activation in response to 'alternating transitivity' verbs, corresponding to two different verbal alternates - one transitive and one intransitive - and simple verbs, with only one, intransitive, thematic grid. Fourteen young healthy participants performed a lexical decision task with the two verb types. Results showed significantly greater activation in the angular and supramarginal gyri (BAs 39 and 40) extending to the posterior superior and middle temporal gyri bilaterally, for alternating compared to simple verbs. Additional activation was detected in bilateral middle and superior frontal gyri (BAs 8 and 9). The opposite contrast, simple compared to alternating verbs, showed no significant differential activation in any regions of the brain. These findings are consistent with previous studies implicating a posterior network including the superior temporal, supramarginal and angular gyri for processing verbs with multiple thematic roles, as well as with those suggesting involvement of the middle and superior frontal gyri in lexical ambiguity processing. However, because 'alternating transitivity' verbs differ from simple intransitives with regard to both the number of thematic grids (two vs. one) and the number of thematic roles (two vs. one), our findings do not distinguish between activations associated with these two differences.

  15. The neural substrates of complex argument structure representations: Processing ‘alternating transitivity’ verbs

    Science.gov (United States)

    Meltzer-Asscher, Aya; Schuchard, Julia; den Ouden, Dirk-Bart; Thompson, Cynthia K.

    2015-01-01

    This study examines the neural correlates of processing verbal entries with multiple argument structures using fMRI. We compared brain activation in response to ‘alternating transitivity’ verbs, corresponding to two different verbal alternates – one transitive and one intransitive - and simple verbs, with only one, intransitive, thematic grid. Fourteen young healthy participants performed a lexical decision task with the two verb types. Results showed significantly greater activation in the angular and supramarginal gyri (BAs 39 and 40) extending to the posterior superior and middle temporal gyri bilaterally, for alternating compared to simple verbs. Additional activation was detected in bilateral middle and superior frontal gyri (BAs 8 and 9). The opposite contrast, simple compared to alternating verbs, showed no significant differential activation in any regions of the brain. These findings are consistent with previous studies implicating a posterior network including the superior temporal, supramarginal and angular gyri for processing verbs with multiple thematic roles, as well as with those suggesting involvement of the middle and superior frontal gyri in lexical ambiguity processing. However, because ‘alternating transitivity’ verbs differ from simple intransitives with regard to both the number of thematic grids (two vs. one) and the number of thematic roles (two vs. one), our findings do not distinguish between activations associated with these two differences. PMID:26139954

  16. Using modular neural networks to model self-consciousness and self-representation for artificial entities

    OpenAIRE

    Martínez Luaces, Milton; Gayoso Rocha, Celina; Pazos Sierra, Juan; Rodríguez-Patón Aradas, Alfonso

    2008-01-01

    Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this pa...

  17. Internal representation of task rules by recurrent dynamics: the importance of the diversity of neural responses

    Directory of Open Access Journals (Sweden)

    Mattia Rigotti

    2010-10-01

    Full Text Available Neural activity of behaving animals, especially in the prefrontal cortex, is highly heterogeneous, with selective responses to diverse aspects of the executed task. We propose a general model of recurrent neural networks that perform complex rule-based tasks, and we show that the diversity of neuronal responses plays a fundamental role when the behavioral responses are context dependent. Specifically, we found that when the inner mental states encoding the task rules are represented by stable patterns of neural activity (attractors of the neural dynamics, the neurons must be selective for combinations of sensory stimuli and inner mental states. Such mixed selectivity is easily obtained by neurons that connect with random synaptic strengths both to the recurrent network and to neurons encoding sensory inputs. The number of randomly connected neurons needed to solve a task is on average only three times as large as the number of neurons needed in a network designed ad hoc. Moreover, the number of needed neurons grows only linearly with the number of task-relevant events and mental states, provided that each neuron responds to a large proportion of events (dense/distributed coding. A biologically realistic implementation of the model captures several aspects of the activity recorded from monkeys performing context dependent tasks. Our findings explain the importance of the diversity of neural responses and provide us with simple and general principles for designing attractor neural networks that perform complex computation.

  18. SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.

    Science.gov (United States)

    Ahmad, Jamil; Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

    2017-01-01

    Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN) pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC) descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches.

  19. SiNC: Saliency-injected neural codes for representation and efficient retrieval of medical radiographs.

    Directory of Open Access Journals (Sweden)

    Jamil Ahmad

    Full Text Available Medical image collections contain a wealth of information which can assist radiologists and medical experts in diagnosis and disease detection for making well-informed decisions. However, this objective can only be realized if efficient access is provided to semantically relevant cases from the ever-growing medical image repositories. In this paper, we present an efficient method for representing medical images by incorporating visual saliency and deep features obtained from a fine-tuned convolutional neural network (CNN pre-trained on natural images. Saliency detector is employed to automatically identify regions of interest like tumors, fractures, and calcified spots in images prior to feature extraction. Neuronal activation features termed as neural codes from different CNN layers are comprehensively studied to identify most appropriate features for representing radiographs. This study revealed that neural codes from the last fully connected layer of the fine-tuned CNN are found to be the most suitable for representing medical images. The neural codes extracted from the entire image and salient part of the image are fused to obtain the saliency-injected neural codes (SiNC descriptor which is used for indexing and retrieval. Finally, locality sensitive hashing techniques are applied on the SiNC descriptor to acquire short binary codes for allowing efficient retrieval in large scale image collections. Comprehensive experimental evaluations on the radiology images dataset reveal that the proposed framework achieves high retrieval accuracy and efficiency for scalable image retrieval applications and compares favorably with existing approaches.

  20. Mining e-cigarette adverse events in social media using Bi-LSTM recurrent neural network with word embedding representation.

    Science.gov (United States)

    Xie, Jiaheng; Liu, Xiao; Dajun Zeng, Daniel

    2018-01-01

    Recent years have seen increased worldwide popularity of e-cigarette use. However, the risks of e-cigarettes are underexamined. Most e-cigarette adverse event studies have achieved low detection rates due to limited subject sample sizes in the experiments and surveys. Social media provides a large data repository of consumers' e-cigarette feedback and experiences, which are useful for e-cigarette safety surveillance. However, it is difficult to automatically interpret the informal and nontechnical consumer vocabulary about e-cigarettes in social media. This issue hinders the use of social media content for e-cigarette safety surveillance. Recent developments in deep neural network methods have shown promise for named entity extraction from noisy text. Motivated by these observations, we aimed to design a deep neural network approach to extract e-cigarette safety information in social media. Our deep neural language model utilizes word embedding as the representation of text input and recognizes named entity types with the state-of-the-art Bidirectional Long Short-Term Memory (Bi-LSTM) Recurrent Neural Network. Our Bi-LSTM model achieved the best performance compared to 3 baseline models, with a precision of 94.10%, a recall of 91.80%, and an F-measure of 92.94%. We identified 1591 unique adverse events and 9930 unique e-cigarette components (ie, chemicals, flavors, and devices) from our research testbed. Although the conditional random field baseline model had slightly better precision than our approach, our Bi-LSTM model achieved much higher recall, resulting in the best F-measure. Our method can be generalized to extract medical concepts from social media for other medical applications.

  1. Training data representation in a neural based robot position estimation system

    Energy Technology Data Exchange (ETDEWEB)

    Taraglio, S. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Innovazione; Di Fonzo, F. [Rome Univ. `La Sapienza` (Italy). Dipt. Ingegneria; Burrascano, P. [Rome Univ. `La Sapienza` (Italy). Ist. di Elettronica

    1997-03-01

    The vision subsystem of an autonomous vehicle is studies. It is based on a multi layer perceptron that uses TV images to estimate the position of the vehicle. A comparative study of the effects of output data representation and input data processing is presented and discussed.

  2. Scene statistics: neural representation of real-world structure in rapid visual perception

    NARCIS (Netherlands)

    Groen, I.I.A.

    2014-01-01

    How does the brain represent our visual environment? Research has revealed brain areas that respond to specific information such as faces and objects, but how a representation of an entire visual scene is formed is still unclear. This thesis explores the idea that scene statistics play an important

  3. Image Classification System Based on Cortical Representations and Unsupervised Neural Network Learning

    NARCIS (Netherlands)

    Petkov, Nikolay

    1995-01-01

    A preprocessor based on a computational model of simple cells in the mammalian primary visual cortex is combined with a self-organising artificial neural network classifier. After learning with a sequence of input images, the output units of the system turn out to correspond to classes of input

  4. Social categories shape the neural representation of emotion: evidence from a visual face adaptation task

    NARCIS (Netherlands)

    Otten, M.; Banaji, M.R.

    2012-01-01

    A number of recent behavioral studies have shown that emotional expressions are differently perceived depending on the race of a face, and that perception of race cues is influenced by emotional expressions. However, neural processes related to the perception of invariant cues that indicate the

  5. Animal-to-Animal Variation in Odor Preference and Neural Representation of Odors

    Science.gov (United States)

    Honegger, Kyle; Smith, Matthew; Turner, Glenn; de Bivort, Benjamin

    Across any population of animals, individuals exhibit diverse behaviors and reactions to sensory stimuli like tastes and odors. While idiosyncratic behavior is ubiquitous, its biological basis is poorly understood. In this talk, I will present evidence that individual fruit flies (Drosophila melanogaster) display idiosyncratic olfactory behaviors and discuss our ongoing efforts to map these behavioral differences to variation in neural circuits. Using a high-throughput, single-fly assay for odor preference, we have demonstrated that highly inbred flies display substantial animal-to-animal variability, beyond that expected from experimental error, and that these preferences persist over days. Using in vivo two-photon calcium imaging, we are beginning to examine the idiosyncrasy of neural coding in the fly olfactory pathway and find that the odor responses of individual processing channels in the antennal lobe can vary substantially from fly to fly. These results imply that individual differences in neural coding may be used to predict the idiosyncratic behavior of an individual - a hypothesis we are currently testing by imaging neural activity from flies after measuring their odor preferences.

  6. Specific and Nonspecific Neural Activity during Selective Processing of Visual Representations in Working Memory

    Science.gov (United States)

    Oh, Hwamee; Leung, Hoi-Chung

    2010-01-01

    In this fMRI study, we investigated prefrontal cortex (PFC) and visual association regions during selective information processing. We recorded behavioral responses and neural activity during a delayed recognition task with a cue presented during the delay period. A specific cue ("Face" or "Scene") was used to indicate which one of the two…

  7. Neural representation of object orientation: A dissociation between MVPA and Repetition Suppression.

    Science.gov (United States)

    Hatfield, Miles; McCloskey, Michael; Park, Soojin

    2016-10-01

    How is object orientation represented in the brain? Behavioral error patterns reveal systematic tendencies to confuse certain orientations with one another. Using fMRI, we asked whether more confusable orientations are represented more similarly in object selective cortex (LOC). We compared two widely-used measures of neural similarity: multi-voxel pattern similarity (MVP-similarity) and Repetition Suppression. In LO, we found that multi-voxel pattern similarity was predicted by the confusability of two orientations. By contrast, Repetition Suppression effects in LO were unrelated to the confusability of orientations. To account for these differences between MVP-similarity and Repetition Suppression, we propose that MVP-similarity reflects the topographical distribution of neural populations, whereas Repetition Suppression depends on repeated activation of particular groups of neurons. This hypothesis leads to a unified interpretation of our results and may explain other dissociations between MVPA and Repetition Suppression observed in the literature. Copyright © 2016. Published by Elsevier Inc.

  8. A multiple distributed representation method based on neural network for biomedical event extraction.

    Science.gov (United States)

    Wang, Anran; Wang, Jian; Lin, Hongfei; Zhang, Jianhai; Yang, Zhihao; Xu, Kan

    2017-12-20

    Biomedical event extraction is one of the most frontier domains in biomedical research. The two main subtasks of biomedical event extraction are trigger identification and arguments detection which can both be considered as classification problems. However, traditional state-of-the-art methods are based on support vector machine (SVM) with massive manually designed one-hot represented features, which require enormous work but lack semantic relation among words. In this paper, we propose a multiple distributed representation method for biomedical event extraction. The method combines context consisting of dependency-based word embedding, and task-based features represented in a distributed way as the input of deep learning models to train deep learning models. Finally, we used softmax classifier to label the example candidates. The experimental results on Multi-Level Event Extraction (MLEE) corpus show higher F-scores of 77.97% in trigger identification and 58.31% in overall compared to the state-of-the-art SVM method. Our distributed representation method for biomedical event extraction avoids the problems of semantic gap and dimension disaster from traditional one-hot representation methods. The promising results demonstrate that our proposed method is effective for biomedical event extraction.

  9. Learning representations for the early detection of sepsis with deep neural networks.

    Science.gov (United States)

    Kam, Hye Jin; Kim, Ha Young

    2017-10-01

    Sepsis is one of the leading causes of death in intensive care unit patients. Early detection of sepsis is vital because mortality increases as the sepsis stage worsens. This study aimed to develop detection models for the early stage of sepsis using deep learning methodologies, and to compare the feasibility and performance of the new deep learning methodology with those of the regression method with conventional temporal feature extraction. Study group selection adhered to the InSight model. The results of the deep learning-based models and the InSight model were compared. With deep feedforward networks, the area under the ROC curve (AUC) of the models were 0.887 and 0.915 for the InSight and the new feature sets, respectively. For the model with the combined feature set, the AUC was the same as that of the basic feature set (0.915). For the long short-term memory model, only the basic feature set was applied and the AUC improved to 0.929 compared with the existing 0.887 of the InSight model. The contributions of this paper can be summarized in three ways: (i) improved performance without feature extraction using domain knowledge, (ii) verification of feature extraction capability of deep neural networks through comparison with reference features, and (iii) improved performance with feedforward neural networks using long short-term memory, a neural network architecture that can learn sequential patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Stimulus information contaminates summation tests of independent neural representations of features

    Science.gov (United States)

    Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

    2002-01-01

    Many models of visual processing assume that visual information is analyzed into separable and independent neural codes, or features. A common psychophysical test of independent features is known as a summation study, which measures performance in a detection, discrimination, or visual search task as the number of proposed features increases. Improvement in human performance with increasing number of available features is typically attributed to the summation, or combination, of information across independent neural coding of the features. In many instances, however, increasing the number of available features also increases the stimulus information in the task, as assessed by an optimal observer that does not include the independent neural codes. In a visual search task with spatial frequency and orientation as the component features, a particular set of stimuli were chosen so that all searches had equivalent stimulus information, regardless of the number of features. In this case, human performance did not improve with increasing number of features, implying that the improvement observed with additional features may be due to stimulus information and not the combination across independent features.

  11. Distinct representations of subtraction and multiplication in the neural systems for numerosity and language

    Science.gov (United States)

    Prado, Jérôme; Mutreja, Rachna; Zhang, Hongchuan; Mehta, Rucha; Desroches, Amy S.; Minas, Jennifer E.; Booth, James R.

    2010-01-01

    It has been proposed that recent cultural inventions such as symbolic arithmetic recycle evolutionary older neural mechanisms. A central assumption of this hypothesis is that the degree to which a pre-existing mechanism is recycled depends upon the degree of similarity between its initial function and the novel task. To test this assumption, we investigated whether the brain region involved in magnitude comparison in the intraparietal sulcus (IPS), localized by a numerosity comparison task, is recruited to a greater degree by arithmetic problems that involve number comparison (single-digit subtractions) than by problems that involve retrieving facts from memory (single-digit multiplications). Our results confirmed that subtractions are associated with greater activity in the IPS than multiplications, whereas multiplications elicit greater activity than subtractions in regions involved in verbal processing including the middle temporal gyrus and inferior frontal gyrus that were localized by a phonological processing task. Pattern analyses further indicated that the neural mechanisms more active for subtraction than multiplication in the IPS overlap with those involved in numerosity comparison, and that the strength of this overlap predicts inter-individual performance in the subtraction task. These findings provide novel evidence that elementary arithmetic relies on the co-option of evolutionary older neural circuits. PMID:21246667

  12. Energy-based stochastic control of neural mass models suggests time-varying effective connectivity in the resting state.

    Science.gov (United States)

    Sotero, Roberto C; Shmuel, Amir

    2012-06-01

    Several studies posit energy as a constraint on the coding and processing of information in the brain due to the high cost of resting and evoked cortical activity. This suggestion has been addressed theoretically with models of a single neuron and two coupled neurons. Neural mass models (NMMs) address mean-field based modeling of the activity and interactions between populations of neurons rather than a few neurons. NMMs have been widely employed for studying the generation of EEG rhythms, and more recently as frameworks for integrated models of neurophysiology and functional MRI (fMRI) responses. To date, the consequences of energy constraints on the activity and interactions of ensembles of neurons have not been addressed. Here we aim to study the impact of constraining energy consumption during the resting-state on NMM parameters. To this end, we first linearized the model, then used stochastic control theory by introducing a quadratic cost function, which transforms the NMM into a stochastic linear quadratic regulator (LQR). Solving the LQR problem introduces a regime in which the NMM parameters, specifically the effective connectivities between neuronal populations, must vary with time. This is in contrast to current NMMs, which assume a constant parameter set for a given condition or task. We further simulated energy-constrained stochastic control of a specific NMM, the Wilson and Cowan model of two coupled neuronal populations, one of which is excitatory and the other inhibitory. These simulations demonstrate that with varying weights of the energy-cost function, the NMM parameters show different time-varying behavior. We conclude that constraining NMMs according to energy consumption may create more realistic models. We further propose to employ linear NMMs with time-varying parameters as an alternative to traditional nonlinear NMMs with constant parameters.

  13. Evaluation of hierarchical structured representations for QSPR studies of small molecules and polymers by recursive neural networks.

    Science.gov (United States)

    Bertinetto, Carlo; Duce, Celia; Micheli, Alessio; Solaro, Roberto; Starita, Antonina; Tiné, Maria Rosaria

    2009-04-01

    This paper reports some recent results from the empirical evaluation of different types of structured molecular representations used in QSPR analysis through a recursive neural network (RNN) model, which allows for their direct use without the need for measuring or computing molecular descriptors. This RNN methodology has been applied to the prediction of the properties of small molecules and polymers. In particular, three different descriptions of cyclic moieties, namely group, template and cyclebreak have been proposed. The effectiveness of the proposed method in dealing with different representations of chemical structures, either specifically designed or of more general use, has been demonstrated by its application to data sets encompassing various types of cyclic structures. For each class of experiments a test set with data that were not used for the development of the model was used for validation, and the comparisons have been based on the test results. The reported results highlight the flexibility of the RNN in directly treating different classes of structured input data without using input descriptors.

  14. Neural Representation of Concurrent Harmonic Sounds in Monkey Primary Auditory Cortex: Implications for Models of Auditory Scene Analysis

    Science.gov (United States)

    Steinschneider, Mitchell; Micheyl, Christophe

    2014-01-01

    The ability to attend to a particular sound in a noisy environment is an essential aspect of hearing. To accomplish this feat, the auditory system must segregate sounds that overlap in frequency and time. Many natural sounds, such as human voices, consist of harmonics of a common fundamental frequency (F0). Such harmonic complex tones (HCTs) evoke a pitch corresponding to their F0. A difference in pitch between simultaneous HCTs provides a powerful cue for their segregation. The neural mechanisms underlying concurrent sound segregation based on pitch differences are poorly understood. Here, we examined neural responses in monkey primary auditory cortex (A1) to two concurrent HCTs that differed in F0 such that they are heard as two separate “auditory objects” with distinct pitches. We found that A1 can resolve, via a rate-place code, the lower harmonics of both HCTs, a prerequisite for deriving their pitches and for their perceptual segregation. Onset asynchrony between the HCTs enhanced the neural representation of their harmonics, paralleling their improved perceptual segregation in humans. Pitches of the concurrent HCTs could also be temporally represented by neuronal phase-locking at their respective F0s. Furthermore, a model of A1 responses using harmonic templates could qualitatively reproduce psychophysical data on concurrent sound segregation in humans. Finally, we identified a possible intracortical homolog of the “object-related negativity” recorded noninvasively in humans, which correlates with the perceptual segregation of concurrent sounds. Findings indicate that A1 contains sufficient spectral and temporal information for segregating concurrent sounds based on differences in pitch. PMID:25209282

  15. [Neural representation of human body schema and corporeal self-consciousness].

    Science.gov (United States)

    Naito, Eiichi; Morita, Tomoyo

    2014-04-01

    The human brain processes every sensation evoked by altered posture and builds up a constantly changing postural model of the body. This is called a body schema, and somatic signals originating from skeletal muscles and joints, i.e. proprioceptive signals, largely contribute its formation. Recent neuroimaging techniques have revealed neuronal substrates for human body schema. A dynamic limb position model seems to be computed in the central motor network (represented by the primary motor cortex). Here, proprioceptive (kinesthetic) signals from muscle spindles are transformed into motor commands, which may underlie somatic perception of limb movement and facilitate its efficient motor control. Somatic signals originating from different body parts are integrated in the course of hierarchical somatosensory processing, and activity in higher-order somatosensory parietal cortices is capable of representing a postural model of the entire body. The left fronto-parietal network associates internal motor representation with external object representation, allowing the embodiment of external objects. In contrast, the right fronto-parietal regions connected by the most inferior branch of superior longitudinal fasciculus fibers seem to have the functions of monitoring bodily states and updating body schema. We hypothesize that activity in these right-sided fronto-parietal regions is deeply involved in corporeal self-consciousness.

  16. Computational Modelling of the Neural Representation of Object Shape in the Primate Ventral Visual System

    Directory of Open Access Journals (Sweden)

    Akihiro eEguchi

    2015-08-01

    Full Text Available Neurons in successive stages of the primate ventral visual pathway encode the spatial structure of visual objects. In this paper, we investigate through computer simulation how these cell firing properties may develop through unsupervised visually-guided learning. Individual neurons in the model are shown to exploit statistical regularity and temporal continuity of the visual inputs during training to learn firing properties that are similar to neurons in V4 and TEO. Neurons in V4 encode the conformation of boundary contour elements at a particular position within an object regardless of the location of the object on the retina, while neurons in TEO integrate information from multiple boundary contour elements. This representation goes beyond mere object recognition, in which neurons simply respond to the presence of a whole object, but provides an essential foundation from which the brain is subsequently able to recognise the whole object.

  17. The neural representation of personally familiar and unfamiliar faces in the distributed system for face perception.

    Science.gov (United States)

    Visconti di Oleggio Castello, Matteo; Halchenko, Yaroslav O; Guntupalli, J Swaroop; Gors, Jason D; Gobbini, M Ida

    2017-09-25

    Personally familiar faces are processed more robustly and efficiently than unfamiliar faces. The human face processing system comprises a core system that analyzes the visual appearance of faces and an extended system for the retrieval of person-knowledge and other nonvisual information. We applied multivariate pattern analysis to fMRI data to investigate aspects of familiarity that are shared by all familiar identities and information that distinguishes specific face identities from each other. Both identity-independent familiarity information and face identity could be decoded in an overlapping set of areas in the core and extended systems. Representational similarity analysis revealed a clear distinction between the two systems and a subdivision of the core system into ventral, dorsal and anterior components. This study provides evidence that activity in the extended system carries information about both individual identities and personal familiarity, while clarifying and extending the organization of the core system for face perception.

  18. Neural Representations of Hierarchical Rule Sets: the Human Control System Represents Rules Irrespective of the Hierarchical Level They Belong to.

    Science.gov (United States)

    Pischedda, Doris; Görgen, Kai; Haynes, John-Dylan; Reverberi, Carlo

    2017-11-07

    Humans use rules to organize their actions to achieve specific goals. While simple rules that link a sensory stimulus to one response may suffice in some situations, often the application of multiple, hierarchically-organized rules is required. Recent theories suggest that progressively higher level rules are encoded along an anterior-to-posterior gradient within PFC. While some work supports the existence of such a functional gradient, other studies argue for a lesser degree of specialization within PFC.We used fMRI to investigate whether rules at different hierarchical levels are represented at distinct locations in the brain or encoded by a single system. Thirty-seven male and female participants represented and applied hierarchical rule sets containing one lower-level stimulus-response rule and one higher-level selection rule. We used multivariate pattern analysis to directly investigate the representation of rules at each hierarchical level in absence of information about rules from other levels or other task-related information, thus providing a clear identification of low- and high-level rule representations.We could decode low- and high-level rules from local patterns of brain activity within a wide frontoparietal network. However, no significant difference existed between regions encoding representations of rules from both levels, except for precentral gyrus that represented only low-level rule information. Our findings show that the brain represents conditional rules irrespective of their level in the explored hierarchy, and thus that the human control system did not organize task representation according to this dimension. Our paradigm represents a promising approach to identify critical principles that shape this control system.SIGNIFICANCE STATEMENTSeveral recent studies investigating the organization of the human control system propose that rules at different control levels are organized along an anterior-to-posterior gradient within PFC. In this

  19. Learning expectation in insects: a recurrent spiking neural model for spatio-temporal representation.

    Science.gov (United States)

    Arena, Paolo; Patané, Luca; Termini, Pietro Savio

    2012-08-01

    Insects are becoming a reference point in Neuroscience for the study of biological aspects at the basis of cognitive processes. These animals have much simpler brains with respect to higher animals, showing, at the same time, impressive capability to adaptively react and take decisions in front of complex environmental situations. In this paper we propose a neural model inspired by the insect olfactory system, with particular attention to the fruit fly Drosophila melanogaster. This architecture is a multilayer spiking network, where each layer is inspired by the structures of the insect brain mainly involved in olfactory information processing, namely the Mushroom Bodies, the Lateral Horns and the Antennal Lobes. In the Antennal Lobes layer olfactory signals lead to a competition among sets of neurons, resulting in a pattern which is projected to the Mushroom Bodies layer. Here a competitive reaction-diffusion process leads to a spontaneous emerging of clusters. The Lateral Horns have been modeled as a delayed input-triggered resetting system. Using plastic recurrent connections, with the addition of simple learning mechanisms, the structure is able to realize a top-down modulation at the input level. This leads to the emergence of an attentional loop as well as to the arousal of basic expectation behaviors in case of subsequently presented stimuli. Simulation results and analysis on the biological plausibility of the architecture are provided and the role of noise in the network is reported. Copyright © 2012 Elsevier Ltd. All rights reserved.

  20. Neural Representation of Harmonic Complex Tones in Primary Auditory Cortex of the Awake Monkey

    Science.gov (United States)

    Micheyl, Christophe; Steinschneider, Mitchell

    2013-01-01

    Many natural sounds are periodic and consist of frequencies (harmonics) that are integer multiples of a common fundamental frequency (F0). Such harmonic complex tones (HCTs) evoke a pitch corresponding to their F0, which plays a key role in the perception of speech and music. “Pitch-selective” neurons have been identified in non-primary auditory cortex of marmoset monkeys. Noninvasive studies point to a putative “pitch center” located in a homologous cortical region in humans. It remains unclear whether there is sufficient spectral and temporal information available at the level of primary auditory cortex (A1) to enable reliable pitch extraction in non-primary auditory cortex. Here we evaluated multiunit responses to HCTs in A1 of awake macaques using a stimulus design employed in auditory nerve studies of pitch encoding. The F0 of the HCTs was varied in small increments, such that harmonics of the HCTs fell either on the peak or on the sides of the neuronal pure tone tuning functions. Resultant response-amplitude-versus-harmonic-number functions (“rate-place profiles”) displayed a periodic pattern reflecting the neuronal representation of individual HCT harmonics. Consistent with psychoacoustic findings in humans, lower harmonics were better resolved in rate-place profiles than higher harmonics. Lower F0s were also temporally represented by neuronal phase-locking to the periodic waveform of the HCTs. Findings indicate that population responses in A1 contain sufficient spectral and temporal information for extracting the pitch of HCTs by neurons in downstream cortical areas that receive their input from A1. PMID:23785145

  1. Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network

    Science.gov (United States)

    Laloy, Eric; Hérault, Romain; Lee, John; Jacques, Diederik; Linde, Niklas

    2017-12-01

    Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational autoencoder type to construct a parametric low-dimensional base model parameterization of complex binary geological media. For inversion purposes, it has the attractive feature that random draws from an uncorrelated standard normal distribution yield model realizations with spatial characteristics that are in agreement with the training set. In comparison with the most commonly used parametric representations in probabilistic inversion, we find that our dimensionality reduction (DR) approach outperforms principle component analysis (PCA), optimization-PCA (OPCA) and discrete cosine transform (DCT) DR techniques for unconditional geostatistical simulation of a channelized prior model. For the considered examples, important compression ratios (200-500) are achieved. Given that the construction of our parameterization requires a training set of several tens of thousands of prior model realizations, our DR approach is more suited for probabilistic (or deterministic) inversion than for unconditional (or point-conditioned) geostatistical simulation. Probabilistic inversions of 2D steady-state and 3D transient hydraulic tomography data are used to demonstrate the DR-based inversion. For the 2D case study, the performance is superior compared to current state-of-the-art multiple-point statistics inversion by sequential geostatistical resampling (SGR). Inversion results for the 3D application are also encouraging.

  2. Cardiac modulation of startle is altered in depersonalization-/derealization disorder: Evidence for impaired brainstem representation of baro-afferent neural traffic.

    Science.gov (United States)

    Schulz, André; Matthey, Jan Hendrik; Vögele, Claus; Schaan, Violetta; Schächinger, Hartmut; Adler, Julia; Beutel, Manfred E; Michal, Matthias

    2016-06-30

    Patients with depersonalization-/derealization disorder (DPD) show altered heartbeat-evoked brain potentials, which are considered psychophysiological indicators of cortical representation of visceral-afferent neural signals. The aim of the current investigation was to clarify whether the impaired CNS representation of visceral-afferent neural signals in DPD is restricted to the cortical level or is also present in sub-cortical structures. We used cardiac modulation of startle (CMS) to assess baro-afferent signal transmission at brainstem level in 22 DPD and 23 healthy control individuals. The CMS paradigm involved acoustic startle stimuli (105dB(A), 50ms) elicited 0, 100, 200, 300, 400 and 500ms after a cardiac R-wave. In healthy control individuals, we observed lower startle responses at 100 and 300ms than at 0 and 400ms after an R-wave. In DPD patients, no effect of the cardiac cycle on startle response magnitude was found. We conclude that the representation of visceral-afferent neural signals at brainstem level may be deficient in DPD. This effect may be due to increased peripheral sympathetic tone or to dysregulated signal processing at brainstem level. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. Analysis of the internal representations developed by neural networks for structures applied to quantitative structure--activity relationship studies of benzodiazepines.

    Science.gov (United States)

    Micheli, A; Sperduti, A; Starita, A; Bianucci, A M

    2001-01-01

    An application of recursive cascade correlation (CC) neural networks to quantitative structure-activity relationship (QSAR) studies is presented, with emphasis on the study of the internal representations developed by the neural networks. Recursive CC is a neural network model recently proposed for the processing of structured data. It allows the direct handling of chemical compounds as labeled ordered directed graphs, and constitutes a novel approach to QSAR. The adopted representation of molecular structure captures, in a quite general and flexible way, significant topological aspects and chemical functionalities for each specific class of molecules showing a particular chemical reactivity or biological activity. A class of 1,4-benzodiazepin-2-ones is analyzed by the proposed approach. It compares favorably versus the traditional QSAR treatment based on equations. To show the ability of the model in capturing most of the structural features that account for the biological activity, the internal representations developed by the networks are analyzed by principal component analysis. This analysis shows that the networks are able to discover relevant structural features just on the basis of the association between the molecular morphology and the target property (affinity).

  4. Neural Activity during Voluntary Movements in Each Body Representation of the Intracortical Microstimulation-Derived Map in the Macaque Motor Cortex.

    Science.gov (United States)

    Higo, Noriyuki; Kunori, Nobuo; Murata, Yumi

    2016-01-01

    In order to accurately interpret experimental data using the topographic body map identified by conventional intracortical microstimulation (ICMS), it is important to know how neurons in each division of the map respond during voluntary movements. Here we systematically investigated neuronal responses in each body representation of the ICMS map during a reach-grasp-retrieval task that involves the movements of multiple body parts. The topographic body map in the primary motor cortex (M1) generally corresponds to functional divisions of voluntary movements; neurons at the recording sites in each body representation with movement thresholds of 10 μA or less were differentially activated during the task, and the timing of responses was consistent with the movements of the body part represented. Moreover, neurons in the digit representation responded differently for the different types of grasping. In addition, the present study showed that neural activity depends on the ICMS current threshold required to elicit body movements and the location of the recording on the cortical surface. In the ventral premotor cortex (PMv), no correlation was found between the response properties of neurons and the body representation in the ICMS map. Neural responses specific to forelimb movements were often observed in the rostral part of PMv, including the lateral bank of the lower arcuate limb, in which ICMS up to 100 μA evoked no detectable movement. These results indicate that the physiological significance of the ICMS-derived maps is different between, and even within, areas M1 and PMv.

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

    Science.gov (United States)

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

    2017-02-01

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

  6. Neural development in Onychophora (velvet worms) suggests a step-wise evolution of segmentation in the nervous system of Panarthropoda.

    Science.gov (United States)

    Mayer, Georg; Whitington, Paul M

    2009-11-01

    A fundamental question in biology is how animal segmentation arose during evolution. One particular challenge is to clarify whether segmental ganglia of the nervous system evolved once, twice, or several times within the Bilateria. As close relatives of arthropods, Onychophora play an important role in this debate since their nervous system displays a mixture of both segmental and non-segmental features. We present evidence that the onychophoran "ventral organs," previously interpreted as segmental anlagen of the nervous system, do not contribute to nerve cord formation and therefore cannot be regarded as vestiges of segmental ganglia. The early axonal pathways in the central nervous system arise by an anterior-to-posterior cascade of axonogenesis from neuronal cell bodies, which are distributed irregularly along each presumptive ventral cord. This pattern contrasts with the strictly segmental neuromeres present in arthropod embryos and makes the assumption of a secondary loss of segmentation in the nervous system during the evolution of the Onychophora less plausible. We discuss the implications of these findings for the evolution of neural segmentation in the Panarthropoda (Arthropoda+Onychophora+Tardigrada). Our data best support the hypothesis that the ancestral panarthropod had only a partially segmented nervous system, which evolved progressively into the segmental chain of ganglia seen in extant tardigrades and arthropods.

  7. FPGA implementation of a modified FitzHugh-Nagumo neuron based causal neural network for compact internal representation of dynamic environments

    Science.gov (United States)

    Salas-Paracuellos, L.; Alba, Luis; Villacorta-Atienza, Jose A.; Makarov, Valeri A.

    2011-05-01

    Animals for surviving have developed cognitive abilities allowing them an abstract representation of the environment. This internal representation (IR) may contain a huge amount of information concerning the evolution and interactions of the animal and its surroundings. The temporal information is needed for IRs of dynamic environments and is one of the most subtle points in its implementation as the information needed to generate the IR may eventually increase dramatically. Some recent studies have proposed the compaction of the spatiotemporal information into only space, leading to a stable structure suitable to be the base for complex cognitive processes in what has been called Compact Internal Representation (CIR). The Compact Internal Representation is especially suited to be implemented in autonomous robots as it provides global strategies for the interaction with real environments. This paper describes an FPGA implementation of a Causal Neural Network based on a modified FitzHugh-Nagumo neuron to generate a Compact Internal Representation of dynamic environments for roving robots, developed under the framework of SPARK and SPARK II European project, to avoid dynamic and static obstacles.

  8. The morphology of the sella turcica in velocardiofacial syndrome suggests involvement of a neural crest developmental field

    DEFF Research Database (Denmark)

    Mølsted, Kirsten; Boers, Maria; Kjaer, Inger

    2010-01-01

    was to measure the cranial base angles in individuals with VCFS and, if possible, to discover the developmental field that may be involved in the condition. The study included 33 patients with VCFS from the Copenhagen Cleft Palate Center, Denmark. The genotype was confirmed by fluorescence in situ hybridization......, hypothyroidism, and posterior brain abnormality), suggest involvement of a specific developmental field....

  9. Neural representation in the auditory midbrain of the envelope of vocalizations based on a peripheral ear model

    Directory of Open Access Journals (Sweden)

    Thilo eRode

    2013-10-01

    Full Text Available The auditory midbrain implant (AMI consists of a single shank array (20 sites for stimulation along the tonotopic axis of the central nucleus of the inferior colliculus (ICC and has been safely implanted in deaf patients who cannot benefit from a cochlear implant (CI. The AMI improves lip-reading abilities and environmental awareness in the implanted patients. However, the AMI cannot achieve the high levels of speech perception possible with the CI. It appears the AMI can transmit sufficient spectral cues but with limited temporal cues required for speech understanding. Currently, the AMI uses a CI-based strategy, which was originally designed to stimulate each frequency region along the cochlea with amplitude-modulated pulse trains matching the envelope of the bandpass-filtered sound components. However, it is unclear if this type of stimulation with only a single site within each frequency lamina of the ICC can elicit sufficient temporal cues for speech perception. At least speech understanding in quiet is still possible with envelope cues as low as 50 Hz. Therefore, we investigated how ICC neurons follow the bandpass-filtered envelope structure of natural stimuli in ketamine-anesthetized guinea pigs. We identified a subset of ICC neurons that could closely follow the envelope structure (up to ~100 Hz of a diverse set of species-specific calls, which was revealed by using a peripheral ear model to estimate the true bandpass-filtered envelopes observed by the brain. Although previous studies have suggested a complex neural transformation from the auditory nerve to the ICC, our data suggest that the brain maintains a robust temporal code in a subset of ICC neurons matching the envelope structure of natural stimuli. Clinically, these findings suggest that a CI-based strategy may still be effective for the AMI if the appropriate neurons are entrained to the envelope of the acoustic stimulus and can transmit sufficient temporal cues to higher

  10. Independent Aftereffects of Fat and Muscle: Implications for neural encoding, body space representation, and body image disturbance

    Science.gov (United States)

    Sturman, Daniel; Stephen, Ian D.; Mond, Jonathan; Stevenson, Richard J; Brooks, Kevin R.

    2017-01-01

    Although research addressing body size misperception has focused on socio-cognitive processes, such as internalization of the “ideal” images of bodies in the media, the perceptual basis of this phenomenon remains largely unknown. Further, most studies focus on body size per se even though this depends on both fat and muscle mass – variables that have very different relationships with health. We tested visual adaptation as a mechanism for inducing body fat and muscle mass misperception, and assessed whether these two dimensions of body space are processed independently. Observers manipulated the apparent fat and muscle mass of bodies to make them appear “normal” before and after inspecting images from one of four adaptation conditions (increased fat/decreased fat/increased muscle/decreased muscle). Exposure resulted in a shift in the point of subjective normality in the direction of the adapting images along the relevant (fat or muscle) axis, suggesting that the neural mechanisms involved in body fat and muscle perception are independent. This supports the viability of adaptation as a model of real-world body size misperception, and extends its applicability to clinical manifestations of body image disturbance that entail not only preoccupation with thinness (e.g., anorexia nervosa) but also with muscularity (e.g., muscle dysmorphia). PMID:28071712

  11. Independent Aftereffects of Fat and Muscle: Implications for neural encoding, body space representation, and body image disturbance.

    Science.gov (United States)

    Sturman, Daniel; Stephen, Ian D; Mond, Jonathan; Stevenson, Richard J; Brooks, Kevin R

    2017-01-10

    Although research addressing body size misperception has focused on socio-cognitive processes, such as internalization of the "ideal" images of bodies in the media, the perceptual basis of this phenomenon remains largely unknown. Further, most studies focus on body size per se even though this depends on both fat and muscle mass - variables that have very different relationships with health. We tested visual adaptation as a mechanism for inducing body fat and muscle mass misperception, and assessed whether these two dimensions of body space are processed independently. Observers manipulated the apparent fat and muscle mass of bodies to make them appear "normal" before and after inspecting images from one of four adaptation conditions (increased fat/decreased fat/increased muscle/decreased muscle). Exposure resulted in a shift in the point of subjective normality in the direction of the adapting images along the relevant (fat or muscle) axis, suggesting that the neural mechanisms involved in body fat and muscle perception are independent. This supports the viability of adaptation as a model of real-world body size misperception, and extends its applicability to clinical manifestations of body image disturbance that entail not only preoccupation with thinness (e.g., anorexia nervosa) but also with muscularity (e.g., muscle dysmorphia).

  12. Harmonic Training and the formation of pitch representation in a neural network model of the auditory brain

    Directory of Open Access Journals (Sweden)

    Nasir eAhmad

    2016-03-01

    Full Text Available Attempting to explain the perceptual qualities of pitch has proven to be, and remains, a difficult problem. The wide range of sounds which illicit pitch and a lack of agreement across neurophysiological studies on how pitch is encoded by the brain have made this attempt more difficult. In describing the potential neural mechanisms by which pitch may be processed, a number of neural networks have been proposed and implemented. However, no unsupervised neural networks with biologically accurate cochlear inputs have yet been demonstrated. This paper proposes a simplified system in which pitch representing neurons are easily produced under a highly biological setting. Purely unsupervised regimes of neural network learning are implemented and these prove to be sufficient in identifying the pitch of sounds with a variety of spectral profiles, including missing fundamental sounds.

  13. Aural localization of silent objects by active human biosonar: neural representations of virtual echo-acoustic space.

    Science.gov (United States)

    Wallmeier, Ludwig; Kish, Daniel; Wiegrebe, Lutz; Flanagin, Virginia L

    2015-03-01

    Some blind humans have developed the remarkable ability to detect and localize objects through the auditory analysis of self-generated tongue clicks. These echolocation experts show a corresponding increase in 'visual' cortex activity when listening to echo-acoustic sounds. Echolocation in real-life settings involves multiple reflections as well as active sound production, neither of which has been systematically addressed. We developed a virtualization technique that allows participants to actively perform such biosonar tasks in virtual echo-acoustic space during magnetic resonance imaging (MRI). Tongue clicks, emitted in the MRI scanner, are picked up by a microphone, convolved in real time with the binaural impulse responses of a virtual space, and presented via headphones as virtual echoes. In this manner, we investigated the brain activity during active echo-acoustic localization tasks. Our data show that, in blind echolocation experts, activations in the calcarine cortex are dramatically enhanced when a single reflector is introduced into otherwise anechoic virtual space. A pattern-classification analysis revealed that, in the blind, calcarine cortex activation patterns could discriminate left-side from right-side reflectors. This was found in both blind experts, but the effect was significant for only one of them. In sighted controls, 'visual' cortex activations were insignificant, but activation patterns in the planum temporale were sufficient to discriminate left-side from right-side reflectors. Our data suggest that blind and echolocation-trained, sighted subjects may recruit different neural substrates for the same active-echolocation task. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  14. Dimensionality of object representations in monkey inferotemporal cortex.

    Science.gov (United States)

    Lehky, Sidney R; Kiani, Roozbeh; Esteky, Hossein; Tanaka, Keiji

    2014-10-01

    We have calculated the intrinsic dimensionality of visual object representations in anterior inferotemporal (AIT) cortex, based on responses of a large sample of cells stimulated with photographs of diverse objects. Because dimensionality was dependent on data set size, we determined asymptotic dimensionality as both the number of neurons and number of stimulus image approached infinity. Our final dimensionality estimate was 93 (SD: ± 11), indicating that there is basis set of approximately 100 independent features that characterize the dimensions of neural object space. We believe this is the first estimate of the dimensionality of neural visual representations based on single-cell neurophysiological data. The dimensionality of AIT object representations was much lower than the dimensionality of the stimuli. We suggest that there may be a gradual reduction in the dimensionality of object representations in neural populations going from retina to inferotemporal cortex as receptive fields become increasingly complex.

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

    Science.gov (United States)

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

    2017-12-01

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

  16. Changes in pitch height elicit both language-universal and language-dependent changes in neural representation of pitch in the brainstem and auditory cortex.

    Science.gov (United States)

    Krishnan, Ananthanarayan; Suresh, Chandan H; Gandour, Jackson T

    2017-03-27

    Language experience shapes encoding of pitch-relevant information at both brainstem and cortical levels of processing. Pitch height is a salient dimension that orders pitch from low to high. Herein we investigate the effects of language experience (Chinese, English) in the brainstem and cortex on (i) neural responses to variations in pitch height, (ii) presence of asymmetry in cortical pitch representation, and (iii) patterns of relative changes in magnitude of pitch height between these two levels of brain structure. Stimuli were three nonspeech homologs of Mandarin Tone 2 varying in pitch height only. The frequency-following response (FFR) and the cortical pitch-specific response (CPR) were recorded concurrently. At the Fz-linked T7/T8 site, peak latency of Na, Pb, and Nb decreased with increasing pitch height for both groups. Peak-to-peak amplitude of Na-Pb and Pb-Nb increased with increasing pitch height across groups. A language-dependent effect was restricted to Na-Pb; the Chinese had larger amplitude than the English group. At temporal sites (T7/T8), the Chinese group had larger amplitude, as compared to English, across stimuli, but also limited to the Na-Pb component and right temporal site. In the brainstem, F0 magnitude decreased with increasing pitch height; Chinese had larger magnitude across stimuli. A comparison of CPR and FFR responses revealed distinct patterns of relative changes in magnitude common to both groups. CPR amplitude increased and FFR amplitude decreased with increasing pitch height. Experience-dependent effects on CPR components vary as a function of neural sensitivity to pitch height within a particular temporal window (Na-Pb). Differences between the auditory brainstem and cortex imply distinct neural mechanisms for pitch extraction at both levels of brain structure. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  17. Extracting the Neural Representation of Tone Onsets for Separate Voices of Ensemble Music Using Multivariate EEG Analysis

    DEFF Research Database (Denmark)

    Sturm, Irene; Treder, Matthias S.; Miklody, Daniel

    2015-01-01

    When listening to ensemble music even non-musicians can follow single instruments effortlessly. Electrophysiological indices for neural sensory encoding of separate streams have been described using oddball paradigms which utilize brain reactions to sound events that deviate from a repeating...... that optimizes the 106 correlation between EEG and a target function which represents the sequence of note onsets in the audio signal of the respective solo voice. This filter extracts an EEG projection that reflects the brain’s reaction to note onsets with enhanced sensitivity. We apply these instrument...

  18. Meaningful Representations Prevent Catastrophic Interference

    NARCIS (Netherlands)

    Bieger, J.; Sprinkhuizen-Kuyper, I.G.; Rooij, I.J.E.I. van; Calders, T.; Tuyls, K.; Pechenizkiy, M.

    2009-01-01

    Artificial Neural Networks (ANNs) attempt to mimic human neural networks in order to perform tasks. In order to do this, tasks need to be represented in ways that the network understands. In ANNs these representations are often arbitrary, whereas in humans it seems that these representations are

  19. Do You Believe It? Verbal Suggestions Influence the Clinical and Neural Effects of Escitalopram in Social Anxiety Disorder: A Randomized Trial.

    Science.gov (United States)

    Faria, Vanda; Gingnell, Malin; Hoppe, Johanna M; Hjorth, Olof; Alaie, Iman; Frick, Andreas; Hultberg, Sara; Wahlstedt, Kurt; Engman, Jonas; Månsson, Kristoffer N T; Carlbring, Per; Andersson, Gerhard; Reis, Margareta; Larsson, Elna-Marie; Fredrikson, Mats; Furmark, Tomas

    2017-10-01

    administration yielded significantly better outcome on the LSAS-SR (adjusted difference 21.17, 95% CI 10.69-31.65, p<0.0001) with more than three times higher response rate (50% vs. 14%; χ 2 (1)=6.91, p=0.009) and twice the effect size (d=2.24 vs. d=1.13) from pre-to posttreatment. There was no significant between-group difference on anticipatory speech anxiety (STAI-S), both groups improving with treatment. No serious adverse reactions were recorded. On fMRI outcomes, there was suggestive evidence for a differential neural response to treatment between groups in the posterior cingulate, superior temporal and inferior frontal gyri (all z thresholds exceeding 3.68, p≤0.001). Reduced social anxiety with treatment correlated significantly with enhanced posterior cingulate (z threshold 3.24, p=0.0006) and attenuated amygdala (z threshold 2.70, p=0.003) activity. The clinical and neural effects of escitalopram were markedly influenced by verbal suggestions. This points to a pronounced placebo component in SSRI-treatment of SAD and favors a biopsychosocial over a biomedical explanatory model for SSRI efficacy. The Swedish Research Council for Working Life and Social Research (grant 2011-1368), the Swedish Research Council (grant 421-2013-1366), Riksbankens Jubileumsfond - the Swedish Foundation for Humanities and Social Sciences (grant P13-1270:1). Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  20. Bearings Fault Diagnosis Based on Convolutional Neural Networks with 2-D Representation of Vibration Signals as Input

    Directory of Open Access Journals (Sweden)

    Zhang Wei

    2017-01-01

    Full Text Available Periodic vibration signals captured by the accelerometers carry rich information for bearing fault diagnosis. Existing methods mostly rely on hand-crafted time-consuming preprocessing of data to acquire suitable features. In this paper, we use an easy and effective method to transform the 1-D temporal vibration signal into a 2-D image. With the signal image, convolutional Neural Network (CNN is used to train the raw vibration data. As powerful feature extractor and classifier for image recognition, CNN can learn to acquire features most suitable for the classification task by being trained. With the image format of vibration signals, the neuron in fully-connected layer of CNN can see farther and capture the periodic feature of signals. According to the results of the experiments, when fed in enough training samples, the proposed method outperforms other common methods. The proposed method can also be applied to solve intelligent diagnosis problems of other machine systems.

  1. Estimating Neural Control from Concentric vs. Eccentric Surface Electromyographic Representations during Fatiguing, Cyclic Submaximal Back Extension Exercises

    Directory of Open Access Journals (Sweden)

    Gerold R. Ebenbichler

    2017-05-01

    Full Text Available Purpose: To investigate the differences in neural control of back muscles activated during the eccentric vs. the concentric portions of a cyclic, submaximal, fatiguing trunk extension exercise via the analysis of amplitude and time-frequency parameters derived from surface electromyographic (SEMG data.Methods: Using back dynamometers, 87 healthy volunteers performed three maximum voluntary isometric trunk extensions (MVC's, an isometric trunk extension at 80% MVC, and 25 cyclic, dynamic trunk extensions at 50% MVC. Dynamic testing was performed with the trunk angular displacement ranging from 0° to 40° and the trunk angular velocity set at 20°/s. SEMG data was recorded bilaterally from the iliocostalis lumborum at L1, the longissimus dorsi at L2, and the multifidus muscles at L5. The initial value and slope of the root mean square (RMS-SEMG and the instantaneous median frequency (IMDF-SEMG estimates derived from the SEMG recorded during each exercise cycle were used to investigate the differences in MU control marking the eccentric vs. the concentric portions of the exercise.Results: During the concentric portions of the exercise, the initial RMS-SEMG values were almost twice those observed during the eccentric portions of the exercise. The RMS-SEMG values generally increased during the concentric portions of the exercise while they mostly remained unchanged during the eccentric portions of the exercise with significant differences between contraction types. Neither the initial IMDF-SEMG values nor the time-course of the IMDF-SEMG values significantly differed between the eccentric and the concentric portions of the exercise.Conclusions: The comparison of the investigated SEMG parameters revealed distinct neural control strategies during the eccentric vs. the concentric portions of the cyclic exercise. We explain these differences by relying upon the principles of orderly recruitment and common drive governing motor unit behavior.

  2. Separate neural systems support representations for actions and objects during narrative speech in post-stroke aphasia.

    Science.gov (United States)

    Gleichgerrcht, Ezequiel; Fridriksson, Julius; Rorden, Chris; Nesland, Travis; Desai, Rutvik; Bonilha, Leonardo

    2016-01-01

    Representations of objects and actions in everyday speech are usually materialized as nouns and verbs, two grammatical classes that constitute the core elements of language. Given their very distinct roles in singling out objects (nouns) or referring to transformative actions (verbs), they likely rely on distinct brain circuits. We tested this hypothesis by conducting network-based lesion-symptom mapping in 38 patients with chronic stroke to the left hemisphere. We reconstructed the individual brain connectomes from probabilistic tractography applied to magnetic resonance imaging and obtained measures of production of words referring to objects and actions from narrative discourse elicited by picture naming tasks. Words for actions were associated with a frontal network strongly engaging structures involved in motor control and programming. Words for objects, instead, were related to a posterior network spreading across the occipital, posterior inferior temporal, and parietal regions, likely related with visual processing and imagery, object recognition, and spatial attention/scanning. Thus, each of these networks engaged brain areas typically involved in cognitive and sensorimotor experiences equivalent to the function served by each grammatical class (e.g. motor areas for verbs, perception areas for nouns). The finding that the two major grammatical classes in human speech rely on two dissociable networks has both important theoretical implications for the neurobiology of language and clinical implications for the assessment and potential rehabilitation and treatment of patients with chronic aphasia due to stroke.

  3. An fMRI study exploring the overlap and differences between neural representations of physical and recalled pain.

    Directory of Open Access Journals (Sweden)

    Merle Fairhurst

    Full Text Available Implementing a recall paradigm without hypnosis, we use functional MRI (fMRI to explore and compare nociceptive and centrally-driven pain experiences. We posit that a trace of a recent nociceptive event can be used to create sensory-re-experiencing of pain that can be qualified in terms of intensity and vividness. Fifteen healthy volunteers received three levels of thermal stimuli (warm, low pain and high pain and subsequently were asked to recall and then rate this experience. Neuroimaging results reveal that recalling a previous sensory experience activates an extensive network of classical pain processing structures except the contralateral posterior insular cortex. Nociceptive-specific activation of this structure and the rated intensity difference between physical and recalled pain events allow us to investigate the link between the quality of the original nociceptive stimulus and the mental trace, as well as the differences between the accompanying neural responses. Additionally, by incorporating the behavioural ratings, we explored which brain regions were separately responsible for generating either an accurate or vivid recall of the physical experience. Together, these observations further our understanding of centrally-mediated pain experiences and pain memory as well as the potential relevance of these factors in the maintenance of chronic pain.

  4. Emotions and a Prior Knowledge Representation in Artificial General Intelligence

    OpenAIRE

    Gavrilov, Andrey

    2008-01-01

    In this paper a prior knowledge representation for Artificial General Intelligence is proposed based on fuzzy rules using linguistic variables. These linguistic variables may be produced by neural network. Rules may be used for generation of basic emotions – positive and negative, which influence on planning and execution of behavior. The representation of Three Laws of Robotics as such prior knowledge is suggested as highest level of motivation in AGI.

  5. P3-18: Examining Neural Representation of Bi-Directional Motions with Directional Performance in Transparency Perception

    Directory of Open Access Journals (Sweden)

    Osamu Watanabe

    2012-10-01

    Full Text Available When we look at two overlapping random-dot patterns moving toward different directions, we perceive two global motions simultaneously in the same region of a visual field; this perception is known as motion transparency. After Braddick and his colleagues' work on comparing perceptual performances in transparent and single motion stimuli (2002 Vision Research 42 1237–1248, it has been considered as one of the promising cues for revealing how superimposed motions are represented in the brain. The perceptual performance would reflect encoding property of overlapping motions, and it enables us to examine the encoding models quantitatively. In the present study, we carried out psychophysical experiments to measure the directional performances in motion transparency and examined if established models of MT responses, a simple weighted sum and a normalization model, were consistent with the performances obtained experimentally. In psychophysical experiments, we measured precisions, or standard deviations, of perceived angles between two overlapping motion directions. The result showed that the perceptual performance was getting worse as a directional difference between two motions increased, while the precision was improved when dot densities of two motions differed considerably. In computational analyses, we compared the experimental results with the encoding properties of MT population models by using Fisher information that told us the lower bounds of the variances of decoded directions. The analyses showed that there was a qualitative difference between the model properties and experimentally obtained performances. Our results suggest that conventional models of MT responses cannot interpret perceptual property of motion transparency.

  6. Capgras syndrome: a novel probe for understanding the neural representation of the identity and familiarity of persons.

    Science.gov (United States)

    Hirstein, W; Ramachandran, V S

    1997-01-01

    Patients with Capgras syndrome regard people whom they know well such as their parents or siblings as imposters. Here we describe a case (DS) of this syndrome who presents several novel features. DS was unusual in that his delusion was modality-specific: he claimed that his parents were imposters when he was looking at them but not when speaking to them on the telephone. Unlike normals, DS's skin conductance responses to photographs of familiar people, including his parents, were not larger in magnitude than his responses to photographs of unfamiliar people. We suggest that in this patient connections from face-processing areas in the temporal lobe to the limbic system have been damaged, a loss which may explain why he calls his parents imposters. In addition, DS was very poor at judging gaze direction. Finally, when presented with a sequence of photographs of the same model's face looking in different directions, DS asserted that they were "different women who looked just like each other'. In the absence of limbic activation, DS creates separate memory "files' of the same person, apparently because he is unable to extract and link the common denominator of successive episodic memories. Thus, far from being a medical curiosity. Capgras syndrome may help us to explore the formation of new memories caught in flagrante delicto. PMID:9107057

  7. Genetic interactions among vestigial, hairy, and Notch suggest a role of vestigial in the differentiation of epidermal and neural cells of the wing and halter of Drosophila melanogaster.

    Science.gov (United States)

    Abu-Issa, R; Cavicchi, S

    1996-09-01

    In this paper we describe the results of genetic analysis of the vestigial locus by studying its interactions with hairy and Notch loci in Drosophila melanogaster. Different vestigial alleles in homo- and heterozygous combination with different hairy alleles show synergism in increasing both cell death and formation of ectopic bristles and produce ectopic veins. Interactions between N and vg also show synergism in increasing cell death and formation of ectopic bristles. Only synergism in cell death is seen between h and N. The interactions indicate that vg product plays a role in the differentiation of epidermal and neural cells of the wing disc by interacting with N and h products either directly or indirectly. Mechanisms of molecular interactions among the three loci are discussed.

  8. Distinguishing Representations as Origin and Representations as Input: Roles for Individual Cells

    Directory of Open Access Journals (Sweden)

    Jonathan C.W. Edwards

    2016-09-01

    Full Text Available It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with meaning, interpretation or significance (semantic content. It is suggested here that this problem may arise partly from the conflation of two vernacular senses of representation: representation-as-origin and representation-as-input. The flash of a neon sign may in one sense represent a popular drink, but to function as representation it must provide an input to a ‘consumer’ in the street. The arguments presented draw on two principles – the neuron doctrine and the need for a venue for ‘presentation’ or ‘reception’ of a representation at a specified site, consistent with the locality principle. It is also argued that domains of representation cannot be defined by signal traffic, since they can be expected to include ‘null’ elements based on non-firing cells. In this analysis, mental representations-as-origin are distributed patterns of cell firing. Each firing cell is given semantic value in its own right - some form of atomic propositional significance – since different axonal branches may contribute to integration with different populations of signals at different downstream sites. Representations-as-input are patterns of local co-arrival of signals in the form of synaptic potentials in dendrites. Meaning then draws on the relationships between active and null inputs, forming ‘scenarios’ comprising a molecular combination of ‘premises’ from which a new output with atomic propositional significance is generated. In both types of representation, meaning, interpretation or significance pivots on events in an individual cell. (This analysis only applies to ‘occurrent’ representations based on current neural activity. The concept of representations-as-input emphasises the need for a ‘consumer’ of a representation and the dependence of meaning on the co-relationships involved in an

  9. Restoring Latent Visual Working Memory Representations in Human Cortex.

    Science.gov (United States)

    Sprague, Thomas C; Ester, Edward F; Serences, John T

    2016-08-03

    Working memory (WM) enables the storage and manipulation of limited amounts of information over short periods. Prominent models posit that increasing the number of remembered items decreases the spiking activity dedicated to each item via mutual inhibition, which irreparably degrades the fidelity of each item's representation. We tested these models by determining if degraded memory representations could be recovered following a post-cue indicating which of several items in spatial WM would be recalled. Using an fMRI-based image reconstruction technique, we identified impaired behavioral performance and degraded mnemonic representations with elevated memory load. However, in several cortical regions, degraded mnemonic representations recovered substantially following a post-cue, and this recovery tracked behavioral performance. These results challenge pure spike-based models of WM and suggest that remembered items are additionally encoded within latent or hidden neural codes that can help reinvigorate active WM representations. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. Active Discriminative Text Representation Learning

    OpenAIRE

    Zhang, Ye; Lease, Matthew; Wallace, Byron C.

    2016-01-01

    We propose a new active learning (AL) method for text classification with convolutional neural networks (CNNs). In AL, one selects the instances to be manually labeled with the aim of maximizing model performance with minimal effort. Neural models capitalize on word embeddings as representations (features), tuning these to the task at hand. We argue that AL strategies for multi-layered neural models should focus on selecting instances that most affect the embedding space (i.e., induce discrim...

  11. Lexical is as lexical does: computational approaches to lexical representation

    Science.gov (United States)

    Woollams, Anna M.

    2015-01-01

    In much of neuroimaging and neuropsychology, regions of the brain have been associated with ‘lexical representation’, with little consideration as to what this cognitive construct actually denotes. Within current computational models of word recognition, there are a number of different approaches to the representation of lexical knowledge. Structural lexical representations, found in original theories of word recognition, have been instantiated in modern localist models. However, such a representational scheme lacks neural plausibility in terms of economy and flexibility. Connectionist models have therefore adopted distributed representations of form and meaning. Semantic representations in connectionist models necessarily encode lexical knowledge. Yet when equipped with recurrent connections, connectionist models can also develop attractors for familiar forms that function as lexical representations. Current behavioural, neuropsychological and neuroimaging evidence shows a clear role for semantic information, but also suggests some modality- and task-specific lexical representations. A variety of connectionist architectures could implement these distributed functional representations, and further experimental and simulation work is required to discriminate between these alternatives. Future conceptualisations of lexical representations will therefore emerge from a synergy between modelling and neuroscience. PMID:25893204

  12. Phoneme representation and classification in primary auditory cortex.

    Science.gov (United States)

    Mesgarani, Nima; David, Stephen V; Fritz, Jonathan B; Shamma, Shihab A

    2008-02-01

    A controversial issue in neurolinguistics is whether basic neural auditory representations found in many animals can account for human perception of speech. This question was addressed by examining how a population of neurons in the primary auditory cortex (A1) of the naive awake ferret encodes phonemes and whether this representation could account for the human ability to discriminate them. When neural responses were characterized and ordered by spectral tuning and dynamics, perceptually significant features including formant patterns in vowels and place and manner of articulation in consonants, were readily visualized by activity in distinct neural subpopulations. Furthermore, these responses faithfully encoded the similarity between the acoustic features of these phonemes. A simple classifier trained on the neural representation was able to simulate human phoneme confusion when tested with novel exemplars. These results suggest that A1 responses are sufficiently rich to encode and discriminate phoneme classes and that humans and animals may build upon the same general acoustic representations to learn boundaries for categorical and robust sound classification.

  13. [Neural codes for perception].

    Science.gov (United States)

    Romo, R; Salinas, E; Hernández, A; Zainos, A; Lemus, L; de Lafuente, V; Luna, R

    This article describes experiments designed to show the neural codes associated with the perception and processing of tactile information. The results of these experiments have shown the neural activity correlated with tactile perception. The neurones of the primary somatosensory cortex (S1) represent the physical attributes of tactile perception. We found that these representations correlated with tactile perception. By means of intracortical microstimulation we demonstrated the causal relationship between S1 activity and tactile perception. In the motor areas of the frontal lobe is to be found the connection between sensorial and motor representation whilst decisions are being taken. S1 generates neural representations of the somatosensory stimuli which seen to be sufficient for tactile perception. These neural representations are subsequently processed by central areas to S1 and seem useful in perception, memory and decision making.

  14. Action simulation: time course and representational mechanisms

    Science.gov (United States)

    Springer, Anne; Parkinson, Jim; Prinz, Wolfgang

    2013-01-01

    The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others' actions implies a mirroring of their activities, based on one's own sensorimotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the future course of actions that are temporarily occluded from view. We address transitions between perceptual mechanisms (referring to action representation before and after occlusion) and simulation mechanisms (referring to action representation during occlusion). Findings suggest that action simulation runs in real-time; acting on newly created action representations rather than relying on continuous visual extrapolations. A further focus of our discussion pertains to the functional characteristics of the mechanisms involved in predicting other people's actions. We propose that two processes are engaged, dynamic updating and static matching, which may draw on both semantic and motor information. In a concluding section, we discuss these findings in the context of broader theoretical issues related to action and event representation, arguing that a detailed functional analysis of action simulation in cognitive, neural, and computational terms may help to further advance our understanding of action cognition and motor control. PMID:23847563

  15. Deep feature representation with stacked sparse auto-encoder and convolutional neural network for hyperspectral imaging-based detection of cucumber defects

    Science.gov (United States)

    It is challenging to achieve rapid and accurate processing of large amounts of hyperspectral image data. This research was aimed to develop a novel classification method by employing deep feature representation with the stacked sparse auto-encoder (SSAE) and the SSAE combined with convolutional neur...

  16. Deconvolutional Paragraph Representation Learning

    OpenAIRE

    Zhang, Yizhe; Shen, Dinghan; Wang, Guoyin; Gan, Zhe; Henao, Ricardo; Carin, Lawrence

    2017-01-01

    Learning latent representations from long text sequences is an important first step in many natural language processing applications. Recurrent Neural Networks (RNNs) have become a cornerstone for this challenging task. However, the quality of sentences during RNN-based decoding (reconstruction) decreases with the length of the text. We propose a sequence-to-sequence, purely convolutional and deconvolutional autoencoding framework that is free of the above issue, while also being computationa...

  17. Representation in dynamical agents.

    Science.gov (United States)

    Ward, Ronnie; Ward, Robert

    2009-04-01

    This paper extends experiments by Beer [Beer, R. D. (1996). Toward the evolution of dynamical neural networks for minimally cognitive behavior. In P. Maes, M. Mataric, J. Meyer, J. Pollack, & S. Wilson (Eds.), From animals to animats 4: Proceedings of the fourth international conference on simulation of adaptive behavior (pp. 421-429). MIT Press; Beer, R. D. (2003). The dynamics of active categorical perception in an evolved model agent (with commentary and response). Adaptive Behavior, 11 (4), 209-243] with an evolved, dynamical agent to further explore the question of representation in cognitive systems. Beer's environmentally-situated visual agent was controlled by a continuous-time recurrent neural network, and evolved to perform a categorical perception task, discriminating circles from diamonds. Despite the agent's high levels of discrimination performance, Beer found no evidence of internal representation in the best-evolved agent's nervous system. Here we examine the generality of this result. We evolved an agent for shape discrimination, and performed extensive behavioral analyses to test for representation. In this case we find that agents developed to discriminate equal-width shapes exhibit what Clark [Clark, A. (1997). The dynamical challenge. Cognitive Science, 21 (4), 461-481] calls "weak-substantive representation". The agent had internal configurations that (1) were understandably related to the object in the environment, and (2) were functionally used in a task relevant way when the target was not visible to the agent.

  18. Neural representation of the acoustic biotope. A comparison of the response of auditory neurons to tonal and natural stimuli in the cat.

    Science.gov (United States)

    Smolders, J W; Aertsen, A M; Johannesma, P I

    1979-11-01

    Cats were stimulated with tones and with natural sounds selected from the normal acoustic environment of the animal. Neural activity evoked by the natural sounds and tones was recorded in the cochlear nucleus and in the medial geniculate body. The set of biological sounds proved to be effective in influencing neural activity of single cells at both levels in the auditory system. At the level of the cochlear nucleus the response of a neuron evoked by a natural sound stimulus could be understood reasonably well on the basis of the structure of the spectrograms of the natural sounds and the unit's responses to tones. At the level of the medial geniculate body analysis with tones did not provide sufficient information to explain the responses to natural sounds. At this level the use of an ensemble of natural sound stimuli allows the investigation of neural properties, which are not seen by analysis with simple artificial stimuli. Guidelines for the construction of an ensemble of complex natural sound stimuli, based on the ecology and ethology of the animal under investigation are discussed. This stimulus ensemble is defined as the Acoustic Biotope.

  19. Emergence of task-dependent representations in working memory circuits

    Directory of Open Access Journals (Sweden)

    Cristina eSavin

    2014-05-01

    Full Text Available A wealth of experimental evidence suggests that working memory circuits preferentially represent information that is behaviorally relevant. Still, we are missing a mechanistic account of how these representations come about. Here we provide a simple explanation for a range of experimental findings, in light of prefrontal circuits adapting to task constraints by reward-dependent learning. In particular, we model a neural network shaped by reward-modulated spike-timing dependent plasticity (r-STDP and homeostatic plasticity (intrinsic excitability and synaptic scaling. We show that the experimentally-observed neural representations naturally emerge in an initially unstructured circuit as it learns to solve several working memory tasks. These results point to a critical, and previously unappreciated, role for reward-dependent learning in shaping prefrontal cortex activity.

  20. Identifying Emotions on the Basis of Neural Activation.

    Directory of Open Access Journals (Sweden)

    Karim S Kassam

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

  1. Conceptual size representation in ventral visual cortex.

    Science.gov (United States)

    Gabay, Shai; Kalanthroff, Eyal; Henik, Avishai; Gronau, Nurit

    2016-01-29

    Recent findings suggest that visual objects may be mapped along the ventral occipitotemporal cortex according to their real-world size (Konkle and Oliva, 2012). It has been argued that such mapping does not reflect an abstract, conceptual size representation, but rather the visual or functional properties associated with small versus big real-world objects. To determine whether a more abstract conceptual size representation may affect visual cortical activation we used meaningless geometrical shapes, devoid of semantic or functional associations, which were associated with specific size representations by virtue of extensive training. Following training, participants underwent functional magnetic resonance imaging (fMRI) scanning while performing a conceptual size comparison task on the geometrical shapes. In addition, a size comparison task was conducted for numeral digits denoting small and big numbers. A region-of-interest analysis revealed larger blood oxygenation level dependent (BOLD) responses for conceptually 'big' than for conceptually 'small' shapes, as well as for big versus small numbers, within medial (parahippocampal place area, PPA) and lateral (occipital place area, OPA) place-selective regions. Processing of the 'big' visual shapes further elicited enhanced activation in early visual cortex, possibly reflecting top-down projections from PPA. By using arbitrary shapes and numbers we minimized visual, categorical, or functional influences on fMRI measurement, providing evidence for a possible neural mechanism underlying the representation of abstract conceptual size within the ventral visual stream. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Poetic representation

    DEFF Research Database (Denmark)

    Wulf-Andersen, Trine Østergaard

    2012-01-01

    be written up and disseminated. The article takes a methodological focus, considering general aims and methods of the research project, before turning to the elaboration on how poetic representations have been constructed and employed as a vehicle for certain kinds of participation, representation......, and dialogue, of situated participants. The article includes a lengthy example of a poetic representation of one participant’s story, and the author comments on the potentials of ‘doing’ poetic representations as an example of writing in ways that challenges what sometimes goes unasked in participative social...

  3. Space-Filling Curves as a Novel Crystal Structure Representation for Machine Learning Models

    CERN Document Server

    Jasrasaria, Dipti; Rappoport, Dmitrij; Aspuru-Guzik, Alan

    2016-01-01

    A fundamental problem in applying machine learning techniques for chemical problems is to find suitable representations for molecular and crystal structures. While the structure representations based on atom connectivities are prevalent for molecules, two-dimensional descriptors are not suitable for describing molecular crystals. In this work, we introduce the SFC-M family of feature representations, which are based on Morton space-filling curves, as an alternative means of representing crystal structures. Latent Semantic Indexing (LSI) was employed in a novel setting to reduce sparsity of feature representations. The quality of the SFC-M representations were assessed by using them in combination with artificial neural networks to predict Density Functional Theory (DFT) single point, Ewald summed, lattice, and many-body dispersion energies of 839 organic molecular crystal unit cells from the Cambridge Structural Database that consist of the elements C, H, N, and O. Promising initial results suggest that the S...

  4. Cortical pitch representations of complex tones in musicians and non-musicians

    DEFF Research Database (Denmark)

    Bianchi, Federica; Hjortkjær, Jens; Santurette, Sébastien

    enhancement. In a previous behavioral study, musicians showed an increased pitch-discrimination performance for both resolved and unresolved complex tones suggesting an enhanced neural representation of pitch at central stages of the auditory system. The aim of this study was to clarify whether musicians show...... (i) differential neural activation in response to complex tones as compared to non-musicians and/or (ii) finer fundamental frequency (F0) representation in the auditory cortex. Assuming that the right auditory cortex is specialized in processing fine spectral changes, we hypothesized that an enhanced...... F0 representation in musicians would be associated with a stronger right-lateralized response to complex tones compared to non-musicians. Fundamental frequency (F0) discrimination thresholds were obtained for harmonic complex tones with F0s of 100 and 500 Hz, filtered in either a low or a high...

  5. Estimation of pulmonary arterial pressure by a neural network analysis using features based on time-frequency representations of the second heart sound.

    Science.gov (United States)

    Tranulis, C; Durand, L G; Senhadji, L; Pibarot, P

    2002-03-01

    The objective of the study was to develop a non-invasive method for the estimation of pulmonary arterial pressure (PAP) using a neural network (NN) and features extracted from the second heart sound (S2). To obtain the information required to train and test the NN, an animal model of pulmonary hypertension (PHT) was developed, and nine pigs were investigated. During the experiments, the electrocardiogram, phonocardiogram and PAP were recorded. Subsequently, between 15 and 50 S2 heart sounds were isolated for each PAP stage and for each animal studied. A Coiflet wavelet decomposition and a pseudo smoothed Wigner-Ville distribution were used to extract features from the S2 sounds and train a one-hidden-layer NN using two-thirds of the data. The NN performance was tested on the remaining one-third of the data. NN estimates of the systolic and mean PAPs were obtained for each S2 and then ensemble averaged over the 15-50 S2 sounds selected for each PAP stage. The standard errors between the mean and systolic PAPs estimated by the NN and those measured with a catheter were 6.0 mmHg and 8.4 mmHg, respectively, and the correlation coefficients were 0.89 and 0.86, respectively. The classification accuracy, using 23 mmHg mean PAP and 30 mmHg systolic PAP thresholds between normal PAP and PHT, was 97% and 91%, respectively.

  6. Estimation of pulmonary arterial pressure by a neural network analysis using features based on time-frequency representations of the second heart sound

    Science.gov (United States)

    Tranulis, Constantin; Durand, Louis-Gilles; Senhadji, Lotfi; Pibarot, Philippe

    2002-01-01

    The objective of this study was to develop a non-invasive method for the estimation of pulmonary arterial pressure (PAP) using a neural network (NN) and features extracted from the second heart sound (S2). To obtain the information required to train and test the NN, an animal model of pulmonary hypertension (PHT) was developed and 9 pigs were investigated. During the experiments, the electrocardiogram, the phonocardiogram, and the PAP were recorded. Subsequently, between 15 and 50 S2 were isolated for each PAP stage and for each animal studied. A Coiflet wavelet decomposition and a pseudo smoothed Wigner-Ville distribution were used to extract features from the S2 and train a one-hidden layer NN using 2/3 of the data. The NN performance was tested on the remaining 1/3 of the data. NN estimates of the systolic and mean PAPs were obtained for each S2 and then ensemble averaged over the 15 to 50 S2 selected for each PAP stage. The standard errors between the mean and systolic PAPs estimated by the NN and those measured with a catheter were of 6.0 mmHg and 8.4 mmHg, respectively, and the correlation coefficients were 0.89 and 0.86, respectively. The classification accuracy, using a 23 mmHg mean PAP and a 30 mmHg systolic PAP thresholds between normal PAP and PHT was 97% and 91% respectively. PMID:12043802

  7. Representational Similarity of Body Parts in Human Occipitotemporal Cortex.

    Science.gov (United States)

    Bracci, Stefania; Caramazza, Alfonso; Peelen, Marius V

    2015-09-23

    Regions in human lateral and ventral occipitotemporal cortices (OTC) respond selectively to pictures of the human body and its parts. What are the organizational principles underlying body part responses in these regions? Here we used representational similarity analysis (RSA) of fMRI data to test multiple possible organizational principles: shape similarity, physical proximity, cortical homunculus proximity, and semantic similarity. Participants viewed pictures of whole persons, chairs, and eight body parts (hands, arms, legs, feet, chests, waists, upper faces, and lower faces). The similarity of multivoxel activity patterns for all body part pairs was established in whole person-selective OTC regions. The resulting neural similarity matrices were then compared with similarity matrices capturing the hypothesized organizational principles. Results showed that the semantic similarity model best captured the neural similarity of body parts in lateral and ventral OTC, which followed an organization in three clusters: (1) body parts used as action effectors (hands, feet, arms, and legs), (2) noneffector body parts (chests and waists), and (3) face parts (upper and lower faces). Whole-brain RSA revealed, in addition to OTC, regions in parietal and frontal cortex in which neural similarity was related to semantic similarity. In contrast, neural similarity in occipital cortex was best predicted by shape similarity models. We suggest that the semantic organization of body parts in high-level visual cortex relates to the different functions associated with the three body part clusters, reflecting the unique processing and connectivity demands associated with the different types of information (e.g., action, social) different body parts (e.g., limbs, faces) convey. Significance statement: While the organization of body part representations in motor and somatosensory cortices has been well characterized, the principles underlying body part representations in visual cortex

  8. 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.

  9. ENTIRE SOUND REPRESENTATIONS ARE TIME-COMPRESSED IN SENSORY MEMORY: EVIDENCE FROM MMN

    Directory of Open Access Journals (Sweden)

    Seiji Tamakoshi

    2016-07-01

    Full Text Available In order to examine the encoding of partial silence included in a sound stimulus in neural representation, time flow of the sound representations was investigated using mismatch negativity (MMN, an ERP component that reflects neural representation in auditory sensory memory. Previous work suggested that time flow of auditory stimuli is compressed in neural representations. The stimuli used were a full-stimulus of 170 ms duration, an early-gap stimulus with silence for a 20 - 50 ms segment (i.e., an omitted segment, and a late-gap stimulus with an omitted segment of 110 - 140 ms. Peak MMNm latencies from oddball sequences of these stimuli, with a 500 ms SOA, did not reflect time point of the physical gap, suggesting that temporal information can be compressed in sensory memory. However, it was not clear whether the whole stimulus duration or only the omitted segment duration is compressed. Thus stimuli were used in which the gap was replaced by a tone segment with a 1/4 sound pressure level (filled, as well as the gap stimuli. Combinations of full-stimuli and one of four gapped or filled stimuli (i.e., early gap, late gap, early filled, and late filled were presented in an oddball sequence (85% vs. 15%. If compression occurs only for the gap duration, MMN latency for filled stimuli should show a different pattern from those for gap stimuli. MMN latencies for the filled conditions showed the same pattern as those for the gap conditions, indicating that the whole stimulus duration rather than only gap duration is compressed in sensory memory neural representation. These results suggest that temporal aspects of silence are encoded in the same manner as physical sound.

  10. Entire Sound Representations Are Time-Compressed in Sensory Memory: Evidence from MMN.

    Science.gov (United States)

    Tamakoshi, Seiji; Minoura, Nanako; Katayama, Jun'ichi; Yagi, Akihiro

    2016-01-01

    In order to examine the encoding of partial silence included in a sound stimulus in neural representation, time flow of the sound representations was investigated using mismatch negativity (MMN), an ERP component that reflects neural representation in auditory sensory memory. Previous work suggested that time flow of auditory stimuli is compressed in neural representations. The stimuli used were a full-stimulus of 170 ms duration, an early-gap stimulus with silence for a 20-50 ms segment (i.e., an omitted segment), and a late-gap stimulus with an omitted segment of 110-140 ms. Peak MMNm latencies from oddball sequences of these stimuli, with a 500 ms SOA, did not reflect time point of the physical gap, suggesting that temporal information can be compressed in sensory memory. However, it was not clear whether the whole stimulus duration or only the omitted segment duration is compressed. Thus, stimuli were used in which the gap was replaced by a tone segment with a 1/4 sound pressure level (filled), as well as the gap stimuli. Combinations of full-stimuli and one of four gapped or filled stimuli (i.e., early gap, late gap, early filled, and late filled) were presented in an oddball sequence (85 vs. 15%). If compression occurs only for the gap duration, MMN latency for filled stimuli should show a different pattern from those for gap stimuli. MMN latencies for the filled conditions showed the same pattern as those for the gap conditions, indicating that the whole stimulus duration rather than only gap duration is compressed in sensory memory neural representation. These results suggest that temporal aspects of silence are encoded in the same manner as physical sound.

  11. Value Representations

    DEFF Research Database (Denmark)

    Rasmussen, Majken Kirkegaard; Petersen, Marianne Graves

    2011-01-01

    Stereotypic presumptions about gender affect the design process, both in relation to how users are understood and how products are designed. As a way to decrease the influence of stereotypic presumptions in design process, we propose not to disregard the aspect of gender in the design process......, as the perspective brings valuable insights on different approaches to technology, but instead to view gender through a value lens. Contributing to this perspective, we have developed Value Representations as a design-oriented instrument for staging a reflective dialogue with users. Value Representations...

  12. Neural Computations in Binaural Hearing

    Science.gov (United States)

    Wagner, Hermann

    Binaural hearing helps humans and animals to localize and unmask sounds. Here, binaural computations in the barn owl's auditory system are discussed. Barn owls use the interaural time difference (ITD) for azimuthal sound localization, and they use the interaural level difference (ELD) for elevational sound localization. ITD and ILD and their precursors are processed in separate neural pathways, the time pathway and the intensity pathway, respectively. Representation of ITD involves four main computational steps, while the representation of ILD is accomplished in three steps. In the discussion neural processing in the owl's auditory system is compared with neural computations present in mammals.

  13. Representational similarity analysis - connecting the branches of systems neuroscience

    Directory of Open Access Journals (Sweden)

    2008-11-01

    Full Text Available A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g. single-cell recordings or voxels from functional magnetic resonance imaging (fMRI. Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement, and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices, which characterize the information carried by a given representation in a brain or model. We propose a new experimental and data-analytical framework called representational similarity analysis (RSA, in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing representational dissimilarity matrices. We demonstrate RSA by relating representations of visual objects as measured with fMRI to computational models spanning a wide range of complexities. We argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience.

  14. Representational Machines

    DEFF Research Database (Denmark)

    Petersson, Dag; Dahlgren, Anna; Vestberg, Nina Lager

    to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...

  15. Visual search for object categories is predicted by the representational architecture of high-level visual cortex.

    Science.gov (United States)

    Cohen, Michael A; Alvarez, George A; Nakayama, Ken; Konkle, Talia

    2017-01-01

    Visual search is a ubiquitous visual behavior, and efficient search is essential for survival. Different cognitive models have explained the speed and accuracy of search based either on the dynamics of attention or on similarity of item representations. Here, we examined the extent to which performance on a visual search task can be predicted from the stable representational architecture of the visual system, independent of attentional dynamics. Participants performed a visual search task with 28 conditions reflecting different pairs of categories (e.g., searching for a face among cars, body among hammers, etc.). The time it took participants to find the target item varied as a function of category combination. In a separate group of participants, we measured the neural responses to these object categories when items were presented in isolation. Using representational similarity analysis, we then examined whether the similarity of neural responses across different subdivisions of the visual system had the requisite structure needed to predict visual search performance. Overall, we found strong brain/behavior correlations across most of the higher-level visual system, including both the ventral and dorsal pathways when considering both macroscale sectors as well as smaller mesoscale regions. These results suggest that visual search for real-world object categories is well predicted by the stable, task-independent architecture of the visual system. Here, we ask which neural regions have neural response patterns that correlate with behavioral performance in a visual processing task. We found that the representational structure across all of high-level visual cortex has the requisite structure to predict behavior. Furthermore, when directly comparing different neural regions, we found that they all had highly similar category-level representational structures. These results point to a ubiquitous and uniform representational structure in high-level visual cortex

  16. What works in auditory working memory? A neural oscillations perspective.

    Science.gov (United States)

    Wilsch, Anna; Obleser, Jonas

    2016-06-01

    Working memory is a limited resource: brains can only maintain small amounts of sensory input (memory load) over a brief period of time (memory decay). The dynamics of slow neural oscillations as recorded using magneto- and electroencephalography (M/EEG) provide a window into the neural mechanics of these limitations. Especially oscillations in the alpha range (8-13Hz) are a sensitive marker for memory load. Moreover, according to current models, the resultant working memory load is determined by the relative noise in the neural representation of maintained information. The auditory domain allows memory researchers to apply and test the concept of noise quite literally: Employing degraded stimulus acoustics increases memory load and, at the same time, allows assessing the cognitive resources required to process speech in noise in an ecologically valid and clinically relevant way. The present review first summarizes recent findings on neural oscillations, especially alpha power, and how they reflect memory load and memory decay in auditory working memory. The focus is specifically on memory load resulting from acoustic degradation. These findings are then contrasted with contextual factors that benefit neural as well as behavioral markers of memory performance, by reducing representational noise. We end on discussing the functional role of alpha power in auditory working memory and suggest extensions of the current methodological toolkit. This article is part of a Special Issue entitled SI: Auditory working memory. Published by Elsevier B.V.

  17. Neural and response correlations to natural complex sounds in the auditory midbrain

    Directory of Open Access Journals (Sweden)

    Dominika Lyzwa

    2016-11-01

    Full Text Available How natural communication sounds are spatially represented across the inferior colliculus, the main center of convergence for auditory information in the midbrain, is not known. The neural representation of the acoustic stimuli results from the interplay of locally differing input and the organization of spectral and temporal neural preferences that change gradually across the nucleus. This raises the question how similar the neural representation of the communication sounds is across these gradients of neural preferences, and whether it also changes gradually. Analyzed neural recordings were multi-unit cluster spike trains from guinea pigs presented with a spectrotemporally rich set of eleven species-specific communication sounds. Using cross-correlation, we analyzed the response similarity of spiking activity across a broad frequency range for neurons of similar and different frequency tuning. Furthermore, we separated the contribution of the stimulus to the correlations to investigate whether similarity is only attributable to the stimulus, or, whether interactions exist between the multi-unit clusters that lead to neural correlations and whether these follow the same representation as the response correlations. We found that similarity of responses is dependent on the neurons' spatial distance for similarly and differently frequency-tuned neurons, and that similarity decreases gradually with spatial distance. Significant neural correlations exist, and contribute to the total response similarity. Our findings suggest that for multi-unit clusters in the mammalian inferior colliculus, the gradual response similarity with spatial distance to natural complex sounds is shaped by neural interactions and the gradual organization of neural preferences.

  18. Hand before foot? Cortical somatotopy suggests manual dexterity is primitive and evolved independently of bipedalism.

    Science.gov (United States)

    Hashimoto, Teruo; Ueno, Kenichi; Ogawa, Akitoshi; Asamizuya, Takeshi; Suzuki, Chisato; Cheng, Kang; Tanaka, Michio; Taoka, Miki; Iwamura, Yoshiaki; Suwa, Gen; Iriki, Atsushi

    2013-11-19

    People have long speculated whether the evolution of bipedalism in early hominins triggered tool use (by freeing their hands) or whether the necessity of making and using tools encouraged the shift to upright gait. Either way, it is commonly thought that one led to the other. In this study, we sought to shed new light on the origins of manual dexterity and bipedalism by mapping the neural representations in the brain of the fingers and toes of living people and monkeys. Contrary to the 'hand-in-glove' notion outlined above, our results suggest that adaptations underlying tool use evolved independently of those required for human bipedality. In both humans and monkeys, we found that each finger was represented separately in the primary sensorimotor cortex just as they are physically separated in the hand. This reflects the ability to use each digit independently, as required for the complex manipulation involved in tool use. The neural mapping of the subjects' toes differed, however. In the monkeys, the somatotopic representation of the toes was fused, showing that the digits function predominantly as a unit in general grasping. Humans, by contrast, had an independent neurological representation of the big toe (hallux), suggesting association with bipedal locomotion. These observations suggest that the brain circuits for the hand had advanced beyond simple grasping, whereas our primate ancestors were still general arboreal quadrupeds. This early adaptation laid the foundation for the evolution of manual dexterity, which was preserved and enhanced in hominins. In hominins, a separate adaptation, involving the neural separation of the big toe, apparently occurred with bipedality. This accords with the known fossil evidence, including the recently reported hominin fossils which have been dated to 4.4 million years ago.

  19. Response variance in functional maps: neural darwinism revisited.

    Directory of Open Access Journals (Sweden)

    Hirokazu Takahashi

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

  20. Response variance in functional maps: neural darwinism revisited.

    Science.gov (United States)

    Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei

    2013-01-01

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

  1. The neural representation of intrusive thoughts

    Science.gov (United States)

    Schmiedek, Florian; Brose, Annette; Schott, Björn H.; Lindenberger, Ulman; Lövden, Martin

    2013-01-01

    Based on the philosophical notion that language embodies thought we investigated whether a habitual tendency for intrusive thought that younger and older participants report over a period of 100 sessions, spread out over about 6 months, is associated with brain regions related to language production. In favour of this hypothesis, we found that individual differences in habitual intrusive thoughts are correlated with activity in the left inferior frontal gyrus (IFG, Broca’s area) as well as the cingulate cortex (CC) during a two-choice reaction-time task in fMRI. Participants who habitually tended to experience intrusive thoughts showed greater activity during task-free (baseline) compared to task periods in brain regions involved in language production. Task performance was unrelated to individual differences in intrusive thoughts. We conclude that intrusive thoughts may be represented in a language-like format and that individuals reporting a habitually higher tendency for intrusive thoughts may have stronger and more habitual inner speech processes. PMID:22563007

  2. 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...

  3. Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation

    Science.gov (United States)

    Khaligh-Razavi, Seyed-Mahdi; Kriegeskorte, Nikolaus

    2014-01-01

    Inferior temporal (IT) cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total), testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet) along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network). We compared the representational dissimilarity matrices (RDMs) of the model representations with the RDMs obtained from human IT (measured with fMRI) and monkey IT (measured with cell recording) for the same set of stimuli (not used in training the models). Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining IT requires

  4. Deep supervised, but not unsupervised, models may explain IT cortical representation.

    Directory of Open Access Journals (Sweden)

    Seyed-Mahdi Khaligh-Razavi

    2014-11-01

    Full Text Available Inferior temporal (IT cortex in human and nonhuman primates serves visual object recognition. Computational object-vision models, although continually improving, do not yet reach human performance. It is unclear to what extent the internal representations of computational models can explain the IT representation. Here we investigate a wide range of computational model representations (37 in total, testing their categorization performance and their ability to account for the IT representational geometry. The models include well-known neuroscientific object-recognition models (e.g. HMAX, VisNet along with several models from computer vision (e.g. SIFT, GIST, self-similarity features, and a deep convolutional neural network. We compared the representational dissimilarity matrices (RDMs of the model representations with the RDMs obtained from human IT (measured with fMRI and monkey IT (measured with cell recording for the same set of stimuli (not used in training the models. Better performing models were more similar to IT in that they showed greater clustering of representational patterns by category. In addition, better performing models also more strongly resembled IT in terms of their within-category representational dissimilarities. Representational geometries were significantly correlated between IT and many of the models. However, the categorical clustering observed in IT was largely unexplained by the unsupervised models. The deep convolutional network, which was trained by supervision with over a million category-labeled images, reached the highest categorization performance and also best explained IT, although it did not fully explain the IT data. Combining the features of this model with appropriate weights and adding linear combinations that maximize the margin between animate and inanimate objects and between faces and other objects yielded a representation that fully explained our IT data. Overall, our results suggest that explaining

  5. Explicit neural representations, recursive neural networks and conscious visual perception

    National Research Council Canada - National Science Library

    Pollen, Daniel A

    2003-01-01

    ... network remains unresolved. We inquire as to whether recursive processing-by which we mean the combined flow and integrated outcome of afferent and recurrent activity across a series of cortical areas-is essential...

  6. Predictive representations can link model-based reinforcement learning to model-free mechanisms.

    Science.gov (United States)

    Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

    2017-09-01

    Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

  7. Content-Adaptive Sketch Portrait Generation by Decompositional Representation Learning.

    Science.gov (United States)

    Zhang, Dongyu; Lin, Liang; Chen, Tianshui; Wu, Xian; Tan, Wenwei; Izquierdo, Ebroul

    2017-01-01

    Sketch portrait generation benefits a wide range of applications such as digital entertainment and law enforcement. Although plenty of efforts have been dedicated to this task, several issues still remain unsolved for generating vivid and detail-preserving personal sketch portraits. For example, quite a few artifacts may exist in synthesizing hairpins and glasses, and textural details may be lost in the regions of hair or mustache. Moreover, the generalization ability of current systems is somewhat limited since they usually require elaborately collecting a dictionary of examples or carefully tuning features/components. In this paper, we present a novel representation learning framework that generates an end-to-end photo-sketch mapping through structure and texture decomposition. In the training stage, we first decompose the input face photo into different components according to their representational contents (i.e., structural and textural parts) by using a pre-trained convolutional neural network (CNN). Then, we utilize a branched fully CNN for learning structural and textural representations, respectively. In addition, we design a sorted matching mean square error metric to measure texture patterns in the loss function. In the stage of sketch rendering, our approach automatically generates structural and textural representations for the input photo and produces the final result via a probabilistic fusion scheme. Extensive experiments on several challenging benchmarks suggest that our approach outperforms example-based synthesis algorithms in terms of both perceptual and objective metrics. In addition, the proposed method also has better generalization ability across data set without additional training.

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

    Science.gov (United States)

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

    2014-05-28

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

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

    Science.gov (United States)

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

    2014-01-01

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

  10. Effects of motion speed in action representations.

    Science.gov (United States)

    van Dam, Wessel O; Speed, Laura J; Lai, Vicky T; Vigliocco, Gabriella; Desai, Rutvik H

    2017-05-01

    Grounded cognition accounts of semantic representation posit that brain regions traditionally linked to perception and action play a role in grounding the semantic content of words and sentences. Sensory-motor systems are thought to support partially abstract simulations through which conceptual content is grounded. However, which details of sensory-motor experience are included in, or excluded from these simulations, is not well understood. We investigated whether sensory-motor brain regions are differentially involved depending on the speed of actions described in a sentence. We addressed this issue by examining the neural signature of relatively fast (The old lady scurried across the road) and slow (The old lady strolled across the road) action sentences. The results showed that sentences that implied fast motion modulated activity within the right posterior superior temporal sulcus and the angular and middle occipital gyri, areas associated with biological motion and action perception. Sentences that implied slow motion resulted in greater signal within the right primary motor cortex and anterior inferior parietal lobule, areas associated with action execution and planning. These results suggest that the speed of described motion influences representational content and modulates the nature of conceptual grounding. Fast motion events are represented more visually whereas motor regions play a greater role in representing conceptual content associated with slow motion. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Representational Thickness

    DEFF Research Database (Denmark)

    Mullins, Michael

    to improve design conditions for architects, thereby increasing the “thickness of representation”. The study commences from a broader theoretical enquiry, a review of previous research and examples of relevant context in which virtual reality has been used in practice. It develops from this discussion three......Contemporary communicational and informational processes contribute to the shaping of our physical environment by having a powerful influence on the process of design. Applications of virtual reality (VR) are transforming the way architecture is conceived and produced by introducing dynamic...... elements into the process of design. Through its immersive properties, virtual reality allows access to a spatial experience of a computer model very different to both screen based simulations as well as traditional forms of architectural representation. The dissertation focuses on processes of the current...

  12. Hypnotic suggestion and cognitive neuroscience.

    Science.gov (United States)

    Oakley, David A; Halligan, Peter W

    2009-06-01

    The growing acceptance of consciousness as a legitimate field of enquiry and the availability of functional imaging has rekindled research interest in the use of hypnosis and suggestion to manipulate subjective experience and to gain insights into healthy and pathological cognitive functioning. Current research forms two strands. The first comprises studies exploring the cognitive and neural nature of hypnosis itself. The second employs hypnosis to explore known psychological processes using specifically targeted suggestions. An extension of this second approach involves using hypnotic suggestion to create clinically informed analogues of established structural and functional neuropsychological disorders. With functional imaging, this type of experimental neuropsychopathology offers a productive means of investigating brain activity involved in many symptom-based disorders and their related phenomenology.

  13. Genetic control of active neural circuits

    Directory of Open Access Journals (Sweden)

    Leon Reijmers

    2009-12-01

    Full Text Available The use of molecular tools to study the neurobiology of complex behaviors has been hampered by an inability to target the desired changes to relevant groups of neurons. Specific memories and specific sensory representations are sparsely encoded by a small fraction of neurons embedded in a sea of morphologically and functionally similar cells. In this review we discuss genetics techniques that are being developed to address this difficulty. In several studies the use of promoter elements that are responsive to neural activity have been used to drive long lasting genetic alterations into neural ensembles that are activated by natural environmental stimuli. This approach has been used to examine neural activity patterns during learning and retrieval of a memory, to examine the regulation of receptor trafficking following learning and to functionally manipulate a specific memory trace. We suggest that these techniques will provide a general approach to experimentally investigate the link between patterns of environmentally activated neural firing and cognitive processes such as perception and memory.

  14. Hypnosis, suggestion, and suggestibility: an integrative model.

    Science.gov (United States)

    Lynn, Steven Jay; Laurence, Jean-Roch; Kirsch, Irving

    2015-01-01

    This article elucidates an integrative model of hypnosis that integrates social, cultural, cognitive, and neurophysiological variables at play both in and out of hypnosis and considers their dynamic interaction as determinants of the multifaceted experience of hypnosis. The roles of these variables are examined in the induction and suggestion stages of hypnosis, including how they are related to the experience of involuntariness, one of the hallmarks of hypnosis. It is suggested that studies of the modification of hypnotic suggestibility; cognitive flexibility; response sets and expectancies; the default-mode network; and the search for the neurophysiological correlates of hypnosis, more broadly, in conjunction with research on social psychological variables, hold much promise to further understanding of hypnosis.

  15. Native language shapes automatic neural processing of speech.

    Science.gov (United States)

    Intartaglia, Bastien; White-Schwoch, Travis; Meunier, Christine; Roman, Stéphane; Kraus, Nina; Schön, Daniele

    2016-08-01

    The development of the phoneme inventory is driven by the acoustic-phonetic properties of one's native language. Neural representation of speech is known to be shaped by language experience, as indexed by cortical responses, and recent studies suggest that subcortical processing also exhibits this attunement to native language. However, most work to date has focused on the differences between tonal and non-tonal languages that use pitch variations to convey phonemic categories. The aim of this cross-language study is to determine whether subcortical encoding of speech sounds is sensitive to language experience by comparing native speakers of two non-tonal languages (French and English). We hypothesized that neural representations would be more robust and fine-grained for speech sounds that belong to the native phonemic inventory of the listener, and especially for the dimensions that are phonetically relevant to the listener such as high frequency components. We recorded neural responses of American English and French native speakers, listening to natural syllables of both languages. Results showed that, independently of the stimulus, American participants exhibited greater neural representation of the fundamental frequency compared to French participants, consistent with the importance of the fundamental frequency to convey stress patterns in English. Furthermore, participants showed more robust encoding and more precise spectral representations of the first formant when listening to the syllable of their native language as compared to non-native language. These results align with the hypothesis that language experience shapes sensory processing of speech and that this plasticity occurs as a function of what is meaningful to a listener. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Congruent embodied representations for visually presented actions and linguistic phrases describing actions.

    Science.gov (United States)

    Aziz-Zadeh, Lisa; Wilson, Stephen M; Rizzolatti, Giacomo; Iacoboni, Marco

    2006-09-19

    The thesis of embodied semantics holds that conceptual representations accessed during linguistic processing are, in part, equivalent to the sensory-motor representations required for the enactment of the concepts described . Here, using fMRI, we tested the hypothesis that areas in human premotor cortex that respond both to the execution and observation of actions-mirror neuron areas -are key neural structures in these processes. Participants observed actions and read phrases relating to foot, hand, or mouth actions. In the premotor cortex of the left hemisphere, a clear congruence was found between effector-specific activations of visually presented actions and of actions described by literal phrases. These results suggest a key role of mirror neuron areas in the re-enactment of sensory-motor representations during conceptual processing of actions invoked by linguistic stimuli.

  17. Learning speaker-specific characteristics with a deep neural architecture.

    Science.gov (United States)

    Chen, Ke; Salman, Ahmad

    2011-11-01

    Speech signals convey various yet mixed information ranging from linguistic to speaker-specific information. However, most of acoustic representations characterize all different kinds of information as whole, which could hinder either a speech or a speaker recognition (SR) system from producing a better performance. In this paper, we propose a novel deep neural architecture (DNA) especially for learning speaker-specific characteristics from mel-frequency cepstral coefficients, an acoustic representation commonly used in both speech recognition and SR, which results in a speaker-specific overcomplete representation. In order to learn intrinsic speaker-specific characteristics, we come up with an objective function consisting of contrastive losses in terms of speaker similarity/dissimilarity and data reconstruction losses used as regularization to normalize the interference of non-speaker-related information. Moreover, we employ a hybrid learning strategy for learning parameters of the deep neural networks: i.e., local yet greedy layerwise unsupervised pretraining for initialization and global supervised learning for the ultimate discriminative goal. With four Linguistic Data Consortium (LDC) benchmarks and two non-English corpora, we demonstrate that our overcomplete representation is robust in characterizing various speakers, no matter whether their utterances have been used in training our DNA, and highly insensitive to text and languages spoken. Extensive comparative studies suggest that our approach yields favorite results in speaker verification and segmentation. Finally, we discuss several issues concerning our proposed approach.

  18. Neural architectures for stereo vision.

    Science.gov (United States)

    Parker, Andrew J; Smith, Jackson E T; Krug, Kristine

    2016-06-19

    Stereoscopic vision delivers a sense of depth based on binocular information but additionally acts as a mechanism for achieving correspondence between patterns arriving at the left and right eyes. We analyse quantitatively the cortical architecture for stereoscopic vision in two areas of macaque visual cortex. For primary visual cortex V1, the result is consistent with a module that is isotropic in cortical space with a diameter of at least 3 mm in surface extent. This implies that the module for stereo is larger than the repeat distance between ocular dominance columns in V1. By contrast, in the extrastriate cortical area V5/MT, which has a specialized architecture for stereo depth, the module for representation of stereo is about 1 mm in surface extent, so the representation of stereo in V5/MT is more compressed than V1 in terms of neural wiring of the neocortex. The surface extent estimated for stereo in V5/MT is consistent with measurements of its specialized domains for binocular disparity. Within V1, we suggest that long-range horizontal, anatomical connections form functional modules that serve both binocular and monocular pattern recognition: this common function may explain the distortion and disruption of monocular pattern vision observed in amblyopia.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Authors.

  19. The Representation of Three-Dimensional Space in Fish.

    Science.gov (United States)

    Burt de Perera, Theresa; Holbrook, Robert I; Davis, Victoria

    2016-01-01

    In mammals, the so-called "seat of the cognitive map" is located in place cells within the hippocampus. Recent work suggests that the shape of place cell fields might be defined by the animals' natural movement; in rats the fields appear to be laterally compressed (meaning that the spatial map of the animal is more highly resolved in the horizontal dimensions than in the vertical), whereas the place cell fields of bats are statistically spherical (which should result in a spatial map that is equally resolved in all three dimensions). It follows that navigational error should be equal in the horizontal and vertical dimensions in animals that travel freely through volumes, whereas in surface-bound animals would demonstrate greater vertical error. Here, we describe behavioral experiments on pelagic fish in which we investigated the way that fish encode three-dimensional space and we make inferences about the underlying processing. Our work suggests that fish, like mammals, have a higher order representation of space that assembles incoming sensory information into a neural unit that can be used to determine position and heading in three-dimensions. Further, our results are consistent with this representation being encoded isotropically, as would be expected for animals that move freely through volumes. Definitive evidence for spherical place fields in fish will not only reveal the neural correlates of space to be a deep seated vertebrate trait, but will also help address the questions of the degree to which environment spatial ecology has shaped cognitive processes and their underlying neural mechanisms.

  20. The representation of three-dimensional space in fish

    Directory of Open Access Journals (Sweden)

    Theresa eBurt De Perera

    2016-03-01

    Full Text Available In mammals, the so-called seat of the cognitive map is located in place cells within the hippocampus. Recent work suggests that the shape of place cell fields might be defined by the animals’ natural movement; in rats the fields appear to be laterally compressed (meaning that the spatial map of the animal is more highly resolved in the horizontal dimensions than in the vertical, whereas the place cell fields of bats are statistically spherical (which should result in a spatial map that is equally resolved in all three dimensions. It follows that navigational error should be equal in the horizontal and vertical dimensions in animals that travel freely through volumes, whereas in surface-bound animals would demonstrate greater vertical error. Here, we describe behavioural experiments on pelagic fish in which we investigated the way that fish encode three-dimensional space and we make inferences about the underlying processing. Our work suggests that fish, like mammals, have a higher order representation of space that assembles incoming sensory information into a neural unit that can be used to determine position and heading in three-dimensions. Further, our results are consistent with this representation being encoded isotropically, as would be expected for animals that move freely through volumes. Definitive evidence for spherical place fields in fish will not only reveal the neural correlates of space to be a deep seated vertebrate trait, but will also help address the questions of the degree to which environment spatial ecology has shaped cognitive processes and their underlying neural mechanisms.

  1. Open to Suggestion.

    Science.gov (United States)

    Journal of Reading, 1987

    1987-01-01

    Offers (1) suggestions for improving college students' study skills; (2) a system for keeping track of parent, teacher, and community contacts; (3) suggestions for motivating students using tic tac toe; (4) suggestions for using etymology to improve word retention; (5) a word search grid; and (6) suggestions for using postcards in remedial reading…

  2. Nonsymbolic number and cumulative area representations contribute shared and unique variance to symbolic math competence.

    Science.gov (United States)

    Lourenco, Stella F; Bonny, Justin W; Fernandez, Edmund P; Rao, Sonia

    2012-11-13

    Humans and nonhuman animals share the capacity to estimate, without counting, the number of objects in a set by relying on an approximate number system (ANS). Only humans, however, learn the concepts and operations of symbolic mathematics. Despite vast differences between these two systems of quantification, neural and behavioral findings suggest functional connections. Another line of research suggests that the ANS is part of a larger, more general system of magnitude representation. Reports of cognitive interactions and common neural coding for number and other magnitudes such as spatial extent led us to ask whether, and how, nonnumerical magnitude interfaces with mathematical competence. On two magnitude comparison tasks, college students estimated (without counting or explicit calculation) which of two arrays was greater in number or cumulative area. They also completed a battery of standardized math tests. Individual differences in both number and cumulative area precision (measured by accuracy on the magnitude comparison tasks) correlated with interindividual variability in math competence, particularly advanced arithmetic and geometry, even after accounting for general aspects of intelligence. Moreover, analyses revealed that whereas number precision contributed unique variance to advanced arithmetic, cumulative area precision contributed unique variance to geometry. Taken together, these results provide evidence for shared and unique contributions of nonsymbolic number and cumulative area representations to formally taught mathematics. More broadly, they suggest that uniquely human branches of mathematics interface with an evolutionarily primitive general magnitude system, which includes partially overlapping representations of numerical and nonnumerical magnitude.

  3. Visual perception from the perspective of a representational, non-reductionistic, level-dependent account of perception and conscious awareness.

    Science.gov (United States)

    Overgaard, Morten; Mogensen, Jesper

    2014-05-05

    This article proposes a new model to interpret seemingly conflicting evidence concerning the correlation of consciousness and neural processes. Based on an analysis of research of blindsight and subliminal perception, the reorganization of elementary functions and consciousness framework suggests that mental representations consist of functions at several different levels of analysis, including truly localized perceptual elementary functions and perceptual algorithmic modules, which are interconnections of the elementary functions. We suggest that conscious content relates to the 'top level' of analysis in a 'situational algorithmic strategy' that reflects the general state of an individual. We argue that conscious experience is intrinsically related to representations that are available to guide behaviour. From this perspective, we find that blindsight and subliminal perception can be explained partly by too coarse-grained methodology, and partly by top-down enhancing of representations that normally would not be relevant to action.

  4. Adult age differences in frontostriatal representation of prediction error but not reward outcome.

    Science.gov (United States)

    Samanez-Larkin, Gregory R; Worthy, Darrell A; Mata, Rui; McClure, Samuel M; Knutson, Brian

    2014-06-01

    Emerging evidence from decision neuroscience suggests that although younger and older adults show similar frontostriatal representations of reward magnitude, older adults often show deficits in feedback-driven reinforcement learning. In the present study, healthy adults completed reward-based tasks that did or did not depend on probabilistic learning, while undergoing functional neuroimaging. We observed reductions in the frontostriatal representation of prediction errors during probabilistic learning in older adults. In contrast, we found evidence for stability across adulthood in the representation of reward outcome in a task that did not require learning. Together, the results identify changes across adulthood in the dynamic coding of relational representations of feedback, in spite of preserved reward sensitivity in old age. Overall, the results suggest that the neural representation of prediction error, but not reward outcome, is reduced in old age. These findings reveal a potential dissociation between cognition and motivation with age and identify a potential mechanism for explaining changes in learning-dependent decision making in old adulthood.

  5. Engagement of neural circuits underlying 2D spatial navigation in a rodent virtual reality system.

    Science.gov (United States)

    Aronov, Dmitriy; Tank, David W

    2014-10-22

    Virtual reality (VR) enables precise control of an animal's environment and otherwise impossible experimental manipulations. Neural activity in rodents has been studied on virtual 1D tracks. However, 2D navigation imposes additional requirements, such as the processing of head direction and environment boundaries, and it is unknown whether the neural circuits underlying 2D representations can be sufficiently engaged in VR. We implemented a VR setup for rats, including software and large-scale electrophysiology, that supports 2D navigation by allowing rotation and walking in any direction. The entorhinal-hippocampal circuit, including place, head direction, and grid cells, showed 2D activity patterns similar to those in the real world. Furthermore, border cells were observed, and hippocampal remapping was driven by environment shape, suggesting functional processing of virtual boundaries. These results illustrate that 2D spatial representations can be engaged by visual and rotational vestibular stimuli alone and suggest a novel VR tool for studying rat navigation.

  6. Testing the sorption hypothesis in olfaction: a limited role for sniff strength in shaping primary odor representations during behavior.

    Science.gov (United States)

    Cenier, Tristan; McGann, John P; Tsuno, Yusuke; Verhagen, Justus V; Wachowiak, Matt

    2013-01-02

    The acquisition of sensory information during behavior shapes the neural representation, central processing, and perception of external stimuli. In mammals, a sniff represents the basic unit of odor sampling, yet how sniffing shapes odor representations remains poorly understood. Perhaps the earliest hypothesis of the role of sniffing in olfaction arises from the fact that odorants with different physicochemical properties exhibit different patterns of deposition across the olfactory epithelium, and that these patterns are differentially affected by flow rate. However, whether sniff flow rates shape odor representations during natural sniffing remains untested, and whether animals make use of odorant sorption-airflow relationships as part of an active odor-sampling strategy remains unclear. We tested these ideas in the intact rat using a threefold approach. First, we asked whether sniff strength shapes odor representations in vivo by imaging from olfactory receptor neuron (ORN) terminals during controlled changes in inhalation flow in the anesthetized rat. Second, we asked whether sniff strength shapes odor representations by imaging from ORNs during natural sniffing in the awake rat. Third, we asked whether rats actively modulate sniff strength during an odor discrimination task. We found that, while artificial changes in flow rate can alter ORN responses, sniff strength has negligible effect on odor representations during natural sniffing, and behaving rats do not modulate flow rate to improve odor discrimination. These data suggest that modulating sniff strength does not shape odor representations sufficiently to be part of a strategy for active odor sensing in the behaving animal.

  7. Neural Mechanisms of Conceptual Relations

    Science.gov (United States)

    Lewis, Gwyneth A.

    2017-01-01

    An over-arching goal in neurolinguistic research is to characterize the neural bases of semantic representation. A particularly relevant goal concerns whether we represent features and events (a) together in a generalized semantic hub or (b) separately in distinct but complementary systems. While the left anterior temporal lobe (ATL) is strongly…

  8. Double representation of the wrist and elbow in human motor cortex

    NARCIS (Netherlands)

    Strother, L.; Medendorp, W.P.; Coros, A.M.; Vilis, T.

    2012-01-01

    Movements of the fingers, hand and arm involve overlapping neural representations in primary motor cortex (M1). Monkey M1 exhibits a coresurround organisation in which cortical representation of the hand and fingers is surrounded by representations of the wrist, elbow and shoulder. A potentially

  9. Neural correlates of quantity processing of Chinese numeral classifiers.

    Science.gov (United States)

    Her, One-Soon; Chen, Ying-Chun; Yen, Nai-Shing

    2017-11-08

    Linguistic analysis suggests that numeral classifiers carry quantity information. However, previous neuroimaging studies have shown that classifiers did not elicit higher activation in the intraparietal sulcus (IPS), associated with representation of numerical magnitude, than tool nouns did. This study aimed to control the semantic attributes of classifiers and reexamine the underlying neural correlates. Participants performed a semantic distance comparison task in which they judged which one of the two items was semantically closer to the target. Processing classifiers elicited higher activation than tool nouns in the bilateral inferior parietal lobules (IPL), middle frontal gyri (MFG), right superior frontal gyrus (SFG), and left lingual gyrus. Conjunction analysis showed that the IPS was commonly activated for classifiers, numbers, dots, and number words. The results support that classifiers activate quantity representations, implicating that the system of classifiers is part of magnitude cognition. Furthermore, the results suggest that the IPS represents magnitude independent of notations. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Resonant Dynamics of Grounded Cognition: Explanation of Behavioral and Neuroimaging Data Using the ART Neural Network

    OpenAIRE

    Domijan, Dražen; Šetić, Mia

    2016-01-01

    Research on grounded cognition suggests that the processing of a word or concept reactivates the perceptual representations that are associated with the referent object. The objective of this work is to demonstrate how behavioral and functional neuroimaging data on grounded cognition can be understood as different manifestations of the same cortical circuit designed to achieve stable category learning, as proposed by the adaptive resonance theory (ART). We showed that the ART neural network p...

  11. Network architecture underlying maximal separation of neuronal representations

    Directory of Open Access Journals (Sweden)

    Ron A Jortner

    2013-01-01

    Full Text Available One of the most basic and general tasks faced by all nervous systems is extracting relevant information from the organism’s surrounding world. While physical signals available to sensory systems are often continuous, variable, overlapping and noisy, high-level neuronal representations used for decision-making tend to be discrete, specific, invariant, and highly separable. This study addresses the question of how neuronal specificity is generated. Inspired by experimental findings on network architecture in the olfactory system of the locust, I construct a highly simplified theoretical framework which allows for analytic solution of its key properties. For generalized feed-forward systems, I show that an intermediate range of connectivity values between source- and target-populations leads to a combinatorial explosion of wiring possibilities, resulting in input spaces which are, by their very nature, exquisitely sparsely populated. In particular, connection probability ½, as found in the locust antennal-lobe–mushroom-body circuit, serves to maximize separation of neuronal representations across the target Kenyon-cells, and explains their specific and reliable responses. This analysis yields a function expressing response specificity in terms of lower network-parameters; together with appropriate gain control this leads to a simple neuronal algorithm for generating arbitrarily sparse and selective codes and linking network architecture and neural coding. I suggest a way to easily construct ecologically meaningful representations from this code.

  12. 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.

  13. Unlocking neural complexity with a robotic key.

    Science.gov (United States)

    Stratton, Peter; Hasselmo, Michael; Milford, Michael

    2016-11-15

    Complex brains evolved in order to comprehend and interact with complex environments in the real world. Despite significant progress in our understanding of perceptual representations in the brain, our understanding of how the brain carries out higher level processing remains largely superficial. This disconnect is understandable, since the direct mapping of sensory inputs to perceptual states is readily observed, while mappings between (unknown) stages of processing and intermediate neural states is not. We argue that testing theories of higher level neural processing on robots in the real world offers a clear path forward, since (1) the complexity of the neural robotic controllers can be staged as necessary, avoiding the almost intractable complexity apparent in even the simplest current living nervous systems; (2) robotic controller states are fully observable, avoiding the enormous technical challenge of recording from complete intact brains; and (3) unlike computational modelling, the real world can stand for itself when using robots, avoiding the computational intractability of simulating the world at an arbitrary level of detail. We suggest that embracing the complex and often unpredictable closed-loop interactions between robotic neuro-controllers and the physical world will bring about deeper understanding of the role of complex brain function in the high-level processing of information and the control of behaviour. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

  14. Manufacturer's Suggested Retail Prices

    NARCIS (Netherlands)

    Rosenkranz, S.|info:eu-repo/dai/nl/157222241

    2003-01-01

    Based on arguments of the `reference- dependent' theory of consumer choice we assume that a retailer's discount of a manufacturer's suggested retail price changes consumers' demand. We can show that the producer benefits from suggesting a retail price. If consumers are additionally sufficiently

  15. Psychophysiology of neural, cognitive and affective integration: fMRI and autonomic indicants.

    Science.gov (United States)

    Critchley, Hugo D

    2009-08-01

    Behaviour is shaped by environmental challenge in the context of homoeostatic need. Emotional and cognitive processes evoke patterned changes in bodily state that may signal emotional state to others. This dynamic modulation of visceral state is neurally mediated by sympathetic and parasympathetic divisions of the autonomic nervous system. Moreover neural afferents convey representations of the internal state of the body back to the brain to further influence emotion and cognition. Neuroimaging and lesion studies implicate specific regions of limbic forebrain in the behavioural generation of autonomic arousal states. Activity within these regions may predict emotion-specific autonomic response patterns within and between bodily organs, with implications for psychosomatic medicine. Feedback from the viscera is mapped hierarchically in the brain to influence efferent signals, and ultimately at the cortical level to engender and reinforce affective responses and subjective feeling states. Again neuroimaging and patient studies suggest discrete neural substrates for these representations, notably regions of insula and orbitofrontal cortex. Individual differences in conscious access to these interoceptive representations predict differences in emotional experience, but equally the misperception of heightened arousal level may evoke changes in emotional behaviour through engagement of the same neural centres. Perturbation of feedback may impair emotional reactivity and, in the context of inflammatory states give rise to cognitive, affective and psychomotor expressions of illness. Changes in visceral state during emotion may be mirrored in the responses of others, permitting a corresponding representation in the observer. The degree to which individuals are susceptible to this 'contagion' predicts individual differences in questionnaire ratings of empathy. Together these neuroimaging and clinical studies highlight the dynamic relationship between mind and body and help

  16. Fast and automatic activation of an abstract representation of money in the human ventral visual pathway.

    Directory of Open Access Journals (Sweden)

    Catherine Tallon-Baudry

    Full Text Available Money, when used as an incentive, activates the same neural circuits as rewards associated with physiological needs. However, unlike physiological rewards, monetary stimuli are cultural artifacts: how are monetary stimuli identified in the first place? How and when does the brain identify a valid coin, i.e. a disc of metal that is, by social agreement, endowed with monetary properties? We took advantage of the changes in the Euro area in 2002 to compare neural responses to valid coins (Euros, Australian Dollars with neural responses to invalid coins that have lost all monetary properties (French Francs, Finnish Marks. We show in magneto-encephalographic recordings, that the ventral visual pathway automatically distinguishes between valid and invalid coins, within only ∼150 ms. This automatic categorization operates as well on coins subjects were familiar with as on unfamiliar coins. No difference between neural responses to scrambled controls could be detected. These results could suggest the existence of a generic, all-purpose neural representation of money that is independent of experience. This finding is reminiscent of a central assumption in economics, money fungibility, or the fact that a unit of money is substitutable to another. From a neural point of view, our findings may indicate that the ventral visual pathway, a system previously thought to analyze visual features such as shape or color and to be influenced by daily experience, could also able to use conceptual attributes such as monetary validity to categorize familiar as well as unfamiliar visual objects. The symbolic abilities of the posterior fusiform region suggested here could constitute an efficient neural substrate to deal with culturally defined symbols, independently of experience, which probably fostered money's cultural emergence and success.

  17. Neural processing of reward and punishment in young people at increased familial risk of depression.

    Science.gov (United States)

    McCabe, Ciara; Woffindale, Caroline; Harmer, Catherine J; Cowen, Philip J

    2012-10-01

    Abnormalities in the neural representation of rewarding and aversive stimuli have been well-described in patients with acute depression, and we previously found abnormal neural responses to rewarding and aversive sight and taste stimuli in recovered depressed patients. The aim of the present study was to determine whether similar abnormalities might be present in young people at increased familial risk of depression but with no personal history of mood disorder. We therefore used functional magnetic resonance imaging to examine the neural responses to pleasant and aversive sights and tastes in 25 young people (16-21 years of age) with a biological parent with depression and 25 age- and gender-matched control subjects. We found that, relative to the control subjects, participants with a parental history of depression showed diminished responses in the orbitofrontal cortex to rewarding stimuli, whereas activations to aversive stimuli were increased in the lateral orbitofrontal cortex and insula. In anterior cingulate cortex the at-risk group showed blunted neural responses to both rewarding and aversive stimuli. Our findings suggest that young people at increased familial risk of depression have altered neural representation of reward and punishment, particularly in cortical regions linked to the use of positive and negative feedback to guide adaptive behavior. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  18. Extending peripersonal space representation without tool-use: evidence from a combined behavioural-computational approach

    Directory of Open Access Journals (Sweden)

    Andrea eSerino

    2015-02-01

    Full Text Available Stimuli from different sensory modalities occurring on or close to the body are integrated in a multisensory representation of the space surrounding the body, i.e. peripersonal space (PPS. PPS dynamically modifies depending on experience, e.g. it extends after using a tool to reach far objects. However, the neural mechanism underlying PPS plasticity after tool use is largely unknown. Here we use a combined computational-behavioural approach to propose and test a possible mechanism accounting for PPS extension. We first present a neural network model simulating audio-tactile representation in the PPS around one hand. Simulation experiments showed that our model reproduced the main property of PPS neurons, i.e. selective multisensory response for stimuli occurring close to the hand. We used the neural network model to simulate the effects of a tool-use training. In terms of sensory inputs, tool use was conceptualized as a concurrent tactile stimulation from the hand, due to holding the tool, and an auditory stimulation from the far space, due to tool-mediated action. Results showed that after exposure to those inputs, PPS neurons responded also to multisensory stimuli far from the hand. The model thus suggests that synchronous pairing of tactile hand stimulation and auditory stimulation from the far space is sufficient to extend PPS, such as after tool-use. Such prediction was confirmed by a behavioural experiment, where we used an audio-tactile interaction paradigm to measure the boundaries of PPS representation. We found that PPS extended after synchronous tactile-hand stimulation and auditory-far stimulation in a group of healthy volunteers. Control experiments both in simulation and behavioural settings showed that asynchronous tactile and auditory inputs did not change PPS. We conclude by proposing a biological-plausible model to explain plasticity in PPS representation after tool-use, supported by computational and behavioural data.

  19. Suggestive Objects at Work

    DEFF Research Database (Denmark)

    Ratner, Helene Gad

    2009-01-01

    In Western secular societies, spiritual life is no longer limited to classical religious institutions but can also be found at workplace organizations. While spirituality is conventionally understood as a subjective and internal process, this paper proposes the concept of ‘suggestive objects’, co...... scaffolding. This has deep implications for our understanding of the sacred, including a better appreciation of the way that suggestive objects make the sacred durable, the way they organize it....

  20. Suggestive techniques in advertising

    OpenAIRE

    Sora, Olena

    2011-01-01

    In my thesis I focused on a detailed analysis of suggestive techniques that appear in contemporary advertising. The issue of the effects of advertising has existed for many years and still staying timely. On the one side there are entrepreneurs and advertising agencies that are trying to influence opinions and suggest motivation for consuming. On the other side there is a potential customer, who is trying to obtain information about the product he needs and at the same time not letting anybod...

  1. Effects of reverberation on brainstem representation of speech in musicians and non-musicians.

    Science.gov (United States)

    Bidelman, Gavin M; Krishnan, Ananthanarayan

    2010-10-08

    Perceptual and neurophysiological enhancements in linguistic processing in musicians suggest that domain specific experience may enhance neural resources recruited for language specific behaviors. In everyday situations, listeners are faced with extracting speech signals in degraded listening conditions. Here, we examine whether musical training provides resilience to the degradative effects of reverberation on subcortical representations of pitch and formant-related harmonic information of speech. Brainstem frequency-following responses (FFRs) were recorded from musicians and non-musician controls in response to the vowel /i/ in four different levels of reverberation and analyzed based on their spectro-temporal composition. For both groups, reverberation had little effect on the neural encoding of pitch but significantly degraded neural encoding of formant-related harmonics (i.e., vowel quality) suggesting a differential impact on the source-filter components of speech. However, in quiet and across nearly all reverberation conditions, musicians showed more robust responses than non-musicians. Neurophysiologic results were confirmed behaviorally by comparing brainstem spectral magnitudes with perceptual measures of fundamental (F0) and first formant (F1) frequency difference limens (DLs). For both types of discrimination, musicians obtained DLs which were 2-4 times better than non-musicians. Results suggest that musicians' enhanced neural encoding of acoustic features, an experience-dependent effect, is more resistant to reverberation degradation which may explain their enhanced perceptual ability on behaviorally relevant speech and/or music tasks in adverse listening conditions. Copyright © 2010 Elsevier B.V. All rights reserved.

  2. [Psychoanalysis and suggestion].

    Science.gov (United States)

    Thomä, H

    1977-01-01

    In the history of psychoanalysis the problem of suggestion has been a central one. At first it involved the necessity to establish the psychoanalytic technique as independent scientific paradigm in contrast to persuasion and hypnosis. However, it was not only the symptom-oriented suggestion that had to be given up for scientific reasons and reasons of treatment technique. Since professional and human factors as well could have influenced the psychoanalytic situation to revert to the traditional "suggestion", Freud has given some technical considerations (e.g. the mirror-analogy), that were meant to counteract the confusion of the psychoanalytic technique with the persuasive one that had to come up to late. The discovery of the transference phenomena has further complicated the problem. It became obvious that the capacity of the analyst to exert an influence and to have impact, originated in very basic human categories and their specific psychogenetic developments and distortions. This understanding contributed to the development of psychoanalytic theories of suggestibility. Until the present day the discovery of the transference phenomena has determined the discussions of psychoanalytic technique in term of the relationship between the special and general therapeutic factors (i.e. interpretation versus relationship). The departure from the therapeutic mode of persuasive suggestion and the introduction of psychoanalytic technique signaled the revolutionary paradigm of Sigmund Freud, i.e. the active participation of the patient and the process of observation. Often scientific problems related to this pradigm and suggestion are discussed concurrently.

  3. 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 ...... the uncertainty in a latent path, like a state space model, we improve the state of the art results on the Blizzard and TIMIT speech modeling data sets by a large margin, while achieving comparable performances to competing methods on polyphonic music modeling....

  4. Neural markers of inhibition in human memory retrieval.

    Science.gov (United States)

    Wimber, Maria; Bäuml, Karl-Heinz; Bergström, Zara; Markopoulos, Gerasimos; Heinze, Hans-Jochen; Richardson-Klavehn, Alan

    2008-12-10

    Retrieving particular information from memory facilitates the later retrieval of that information, but also impairs the later retrieval of related, interfering information. It has been theorized that this retrieval-induced forgetting reflects inhibition of interfering memory representations. We used event-related fMRI to investigate the functional neuroanatomy of this impaired retrieval, at the time the impairment is observed. Neural activity differences between impaired and facilitated information occurred in left ventrolateral prefrontal cortex (VLPFC, BA 45 and 47), precuneus (BA 7), and right inferior parietal lobule (IPL, BA 40). Activity in left anterior VLPFC (BA 47) and left posterior temporal cortex (BA 22), regions implicated in the controlled retrieval of weak semantic memory representations, predicted the degree of retrieval-induced forgetting. In contrast, activity in precuneus and right IPL predicted the degree of retrieval-induced facilitation. Our findings demonstrate that impairment of interfering memories and facilitation of practiced memories involve distinct neural processes, and suggest that the impairment reflects inhibition that weakens interfering memory representations.

  5. Representation as the representation of experience

    NARCIS (Netherlands)

    Ankersmit, FR

    This essay deals, mainly, with the notion of representation. Representation is associated with texts and, as such, is contrasted to the true singular statement. It is argued that the relationship between the text and what the text represents can never be modeled on the relationship between the true

  6. A modular architecture for transparent computation in recurrent neural networks.

    Science.gov (United States)

    Carmantini, Giovanni S; Beim Graben, Peter; Desroches, Mathieu; Rodrigues, Serafim

    2017-01-01

    Computation is classically studied in terms of automata, formal languages and algorithms; yet, the relation between neural dynamics and symbolic representations and operations is still unclear in traditional eliminative connectionism. Therefore, we suggest a unique perspective on this central issue, to which we would like to refer as transparent connectionism, by proposing accounts of how symbolic computation can be implemented in neural substrates. In this study we first introduce a new model of dynamics on a symbolic space, the versatile shift, showing that it supports the real-time simulation of a range of automata. We then show that the Gödelization of versatile shifts defines nonlinear dynamical automata, dynamical systems evolving on a vectorial space. Finally, we present a mapping between nonlinear dynamical automata and recurrent artificial neural networks. The mapping defines an architecture characterized by its granular modularity, where data, symbolic operations and their control are not only distinguishable in activation space, but also spatially localizable in the network itself, while maintaining a distributed encoding of symbolic representations. The resulting networks simulate automata in real-time and are programmed directly, in the absence of network training. To discuss the unique characteristics of the architecture and their consequences, we present two examples: (i) the design of a Central Pattern Generator from a finite-state locomotive controller, and (ii) the creation of a network simulating a system of interactive automata that supports the parsing of garden-path sentences as investigated in psycholinguistics experiments. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Task-dependent neural and behavioral effects of verb argument structure features.

    Science.gov (United States)

    Malyutina, Svetlana; den Ouden, Dirk-Bart

    2017-05-01

    Understanding which verb argument structure (VAS) features (if any) are part of verbs' lexical entries and under which conditions they are accessed provides information on the nature of lexical representations and sentence construction. We investigated neural and behavioral effects of three understudied VAS characteristics (number of subcategorization options, number of thematic options and overall number of valency frames) in lexical decision and sentence well-formedness judgment in healthy adults. VAS effects showed strong dependency on processing conditions. As reflected by behavioral performance and neural recruitment patterns, increased VAS complexity in terms of subcategorization options and thematic options had a detrimental effect on sentence processing, but facilitated lexical access to single words, possibly by providing more lexico-semantic associations and access routes (facilitation through complexity). Effects of the number of valency frames are equivocal. We suggest that VAS effects may be mediated semantically rather than by a dedicated VAS module in verbs' representations. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. 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.

  9. Low dimensional representation of face space by face-selective inferior temporal neurons.

    Science.gov (United States)

    Salehi, Sina; Dehaqani, Mohammad-Reza A; Esteky, Hossein

    2017-05-01

    The representation of visual objects in primate brain is distributed and multiple neurons are involved in encoding each object. One way to understand the neural basis of object representation is to estimate the number of neural dimensions that are needed for veridical representation of object categories. In this study, the characteristics of the match between physical-shape and neural representational spaces in monkey inferior temporal (IT) cortex were evaluated. Specifically, we examined how the number of neural dimensions, stimulus behavioral saliency and stimulus category selectivity of neurons affected the correlation between shape and neural representational spaces in IT cortex. Single-unit recordings from monkey IT cortex revealed that there was a significant match between face space and its neural representation at lower neural dimensions, whereas the optimal match for the non-face objects was observed at higher neural dimensions. There was a statistically significant match between the face and neural spaces only in the face-selective neurons, whereas a significant match was observed for non-face objects in all neurons regardless of their category selectivity. Interestingly, the face neurons showed a higher match for the non-face objects than for the faces at higher neural dimensions. The optimal representation of face space in the responses of the face neurons was a low dimensional map that emerged early (~150 ms post-stimulus onset) and was followed by a high dimensional and relatively late (~300 ms) map for the non-face stimuli. These results support a multiplexing function for the face neurons in the representation of very similar shape spaces, but with different dimensionality and timing scales. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  10. Neural network applications

    Science.gov (United States)

    Padgett, Mary L.; Desai, Utpal; Roppel, T.A.; White, Charles R.

    1993-01-01

    A design procedure is suggested for neural networks which accommodates the inclusion of such knowledge-based systems techniques as fuzzy logic and pairwise comparisons. The use of these procedures in the design of applications combines qualitative and quantitative factors with empirical data to yield a model with justifiable design and parameter selection procedures. The procedure is especially relevant to areas of back-propagation neural network design which are highly responsive to the use of precisely recorded expert knowledge.

  11. Open to Suggestion.

    Science.gov (United States)

    Journal of Reading, 1986

    1986-01-01

    Offers (1) suggestions on how to teach students the importance of regular study habits for learning to spell, (2) story ideas to help students get started with creative writing, and (3) a model of a daily record assignment book to help students organize and remember their homework assignments. (SRT)

  12. Representational similarity analysis - connecting the branches of systems neuroscience.

    Science.gov (United States)

    Kriegeskorte, Nikolaus; Mur, Marieke; Bandettini, Peter

    2008-01-01

    A FUNDAMENTAL CHALLENGE FOR SYSTEMS NEUROSCIENCE IS TO QUANTITATIVELY RELATE ITS THREE MAJOR BRANCHES OF RESEARCH: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g., single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement (e.g., fMRI and invasive or scalp electrophysiology), and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices (RDMs), which characterize the information carried by a given representation in a brain or model. Building on a rich psychological and mathematical literature on similarity analysis, we propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing RDMs. We demonstrate RSA by relating representations of visual objects as measured with fMRI in early visual cortex and the fusiform face area to computational models spanning a wide range of complexities. The RDMs are simultaneously related via second-level application of multidimensional scaling and tested using randomization and bootstrap techniques. We discuss the broad potential of RSA, including novel approaches to experimental design, and argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience.

  13. Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

    Science.gov (United States)

    Kriegeskorte, Nikolaus; Mur, Marieke; Bandettini, Peter

    2008-01-01

    A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g., single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement (e.g., fMRI and invasive or scalp electrophysiology), and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices (RDMs), which characterize the information carried by a given representation in a brain or model. Building on a rich psychological and mathematical literature on similarity analysis, we propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing RDMs. We demonstrate RSA by relating representations of visual objects as measured with fMRI in early visual cortex and the fusiform face area to computational models spanning a wide range of complexities. The RDMs are simultaneously related via second-level application of multidimensional scaling and tested using randomization and bootstrap techniques. We discuss the broad potential of RSA, including novel approaches to experimental design, and argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience. PMID:19104670

  14. Neural tuning for face wholes and parts in human fusiform gyrus revealed by FMRI adaptation.

    Science.gov (United States)

    Harris, Alison; Aguirre, Geoffrey Karl

    2010-07-01

    Although the right fusiform face area (FFA) is often linked to holistic processing, new data suggest this region also encodes part-based face representations. We examined this question by assessing the metric of neural similarity for faces using a continuous carryover functional MRI (fMRI) design. Using faces varying along dimensions of eye and mouth identity, we tested whether these axes are coded independently by separate part-tuned neural populations or conjointly by a single population of holistically tuned neurons. Consistent with prior results, we found a subadditive adaptation response in the right FFA, as predicted for holistic processing. However, when holistic processing was disrupted by misaligning the halves of the face, the right FFA continued to show significant adaptation, but in an additive pattern indicative of part-based neural tuning. Thus this region seems to contain neural populations capable of representing both individual parts and their integration into a face gestalt. A third experiment, which varied the asymmetry of changes in the eye and mouth identity dimensions, also showed part-based tuning from the right FFA. In contrast to the right FFA, the left FFA consistently showed a part-based pattern of neural tuning across all experiments. Together, these data support the existence of both part-based and holistic neural tuning within the right FFA, further suggesting that such tuning is surprisingly flexible and dynamic.

  15. Representational Similarity Analysis Reveals Commonalities and Differences in the Semantic Processing of Words and Objects

    Science.gov (United States)

    Devereux, Barry J.; Clarke, Alex; Marouchos, Andreas; Tyler, Lorraine K.

    2013-01-01

    Understanding the meanings of words and objects requires the activation of underlying conceptual representations. Semantic representations are often assumed to be coded such that meaning is evoked regardless of the input modality. However, the extent to which meaning is coded in modality-independent or amodal systems remains controversial. We address this issue in a human fMRI study investigating the neural processing of concepts, presented separately as written words and pictures. Activation maps for each individual word and picture were used as input for searchlight-based multivoxel pattern analyses. Representational similarity analysis was used to identify regions correlating with low-level visual models of the words and objects and the semantic category structure common to both. Common semantic category effects for both modalities were found in a left-lateralized network, including left posterior middle temporal gyrus (LpMTG), left angular gyrus, and left intraparietal sulcus (LIPS), in addition to object- and word-specific semantic processing in ventral temporal cortex and more anterior MTG, respectively. To explore differences in representational content across regions and modalities, we developed novel data-driven analyses, based on k-means clustering of searchlight dissimilarity matrices and seeded correlation analysis. These revealed subtle differences in the representations in semantic-sensitive regions, with representations in LIPS being relatively invariant to stimulus modality and representations in LpMTG being uncorrelated across modality. These results suggest that, although both LpMTG and LIPS are involved in semantic processing, only the functional role of LIPS is the same regardless of the visual input, whereas the functional role of LpMTG differs for words and objects. PMID:24285896

  16. The representation of space in the brain.

    Science.gov (United States)

    Grieves, Roddy M; Jeffery, Kate J

    2017-02-01

    Animals can navigate vast distances and often display behaviours or activities that indicate a detailed, internal spatial representation of their surrounding environment or a 'cognitive map'. Over a century of behavioural research on spatial navigation in humans and animals has greatly increased our understanding of how this highly complex feat is achieved. In turn this has inspired half a century of electrophysiological spatial navigation and memory research which has further advanced our understanding of the brain. In particular, three functional cell types have been suggested to underlie cognitive mapping processes; place cells, head direction cells and grid cells. However, there are numerous other spatially modulated neurons in the brain. For a more complete understanding of the electrophysiological systems and behavioural processes underlying spatial navigation we must also examine these lesser understood neurons. In this review we will briefly summarise the literature surrounding place cells, head direction cells, grid cells and the evidence that these cells collectively form the neural basis of a cognitive map. We will then review literature covering many other spatially modulated neurons in the brain that perhaps further augment this cognitive map. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Effects of selective attention on the electrophysiological representation of concurrent sounds in the human auditory cortex.

    Science.gov (United States)

    Bidet-Caulet, Aurélie; Fischer, Catherine; Besle, Julien; Aguera, Pierre-Emmanuel; Giard, Marie-Helene; Bertrand, Olivier

    2007-08-29

    In noisy environments, we use auditory selective attention to actively ignore distracting sounds and select relevant information, as during a cocktail party to follow one particular conversation. The present electrophysiological study aims at deciphering the spatiotemporal organization of the effect of selective attention on the representation of concurrent sounds in the human auditory cortex. Sound onset asynchrony was manipulated to induce the segregation of two concurrent auditory streams. Each stream consisted of amplitude modulated tones at different carrier and modulation frequencies. Electrophysiological recordings were performed in epileptic patients with pharmacologically resistant partial epilepsy, implanted with depth electrodes in the temporal cortex. Patients were presented with the stimuli while they either performed an auditory distracting task or actively selected one of the two concurrent streams. Selective attention was found to affect steady-state responses in the primary auditory cortex, and transient and sustained evoked responses in secondary auditory areas. The results provide new insights on the neural mechanisms of auditory selective attention: stream selection during sound rivalry would be facilitated not only by enhancing the neural representation of relevant sounds, but also by reducing the representation of irrelevant information in the auditory cortex. Finally, they suggest a specialization of the left hemisphere in the attentional selection of fine-grained acoustic information.

  18. Ontogeny of neural circuits underlying spatial memory in the rat

    Directory of Open Access Journals (Sweden)

    James Alexander Ainge

    2012-03-01

    Full Text Available Spatial memory is a well characterised psychological function in both humans and rodents. The combined computations of a network of systems including place cells in the hippocampus, grid cells in the medial entorhinal cortex and head direction cells found in numerous structures in the brain have been suggested to form the neural instantiation of the cognitive map as first described by Tolman in 1948. However, while our understanding of the neural mechanisms underlying spatial representations in adults is relatively sophisticated, we know substantially less about how this network develops in young animals. In this article we review studies examining the developmental timescale that these systems follow. Electrophysiological recordings from very young rats show that directional information is at adult levels at the outset of navigational experience. The systems supporting allocentric memory, however, take longer to mature. This is consistent with behavioural studies of young rats which show that spatial memory based on head direction develops very early but that allocentric spatial memory takes longer to mature. We go on to report new data demonstrating that memory for associations between objects and their spatial locations is slower to develop than memory for objects alone. This is again consistent with previous reports suggesting that adult like spatial representations have a protracted development in rats and also suggests that the systems involved in processing non-spatial stimuli come online earlier.

  19. Representations of Circular Words

    Directory of Open Access Journals (Sweden)

    László Hegedüs

    2014-05-01

    Full Text Available In this article we give two different ways of representations of circular words. Representations with tuples are intended as a compact notation, while representations with trees give a way to easily process all conjugates of a word. The latter form can also be used as a graphical representation of periodic properties of finite (in some cases, infinite words. We also define iterative representations which can be seen as an encoding utilizing the flexible properties of circular words. Every word over the two letter alphabet can be constructed starting from ab by applying the fractional power and the cyclic shift operators one after the other, iteratively.

  20. Similar representations of emotions across faces and voices.

    Science.gov (United States)

    Kuhn, Lisa Katharina; Wydell, Taeko; Lavan, Nadine; McGettigan, Carolyn; Garrido, Lúcia

    2017-09-01

    [Correction Notice: An Erratum for this article was reported in Vol 17(6) of Emotion (see record 2017-18585-001). In the article, the copyright attribution was incorrectly listed and the Creative Commons CC-BY license disclaimer was incorrectly omitted from the author note. The correct copyright is "© 2017 The Author(s)" and the omitted disclaimer is below. All versions of this article have been corrected. "This article has been published under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s). Author(s) grant(s) the American Psychological Association the exclusive right to publish the article and identify itself as the original publisher."] Emotions are a vital component of social communication, carried across a range of modalities and via different perceptual signals such as specific muscle contractions in the face and in the upper respiratory system. Previous studies have found that emotion recognition impairments after brain damage depend on the modality of presentation: recognition from faces may be impaired whereas recognition from voices remains preserved, and vice versa. On the other hand, there is also evidence for shared neural activation during emotion processing in both modalities. In a behavioral study, we investigated whether there are shared representations in the recognition of emotions from faces and voices. We used a within-subjects design in which participants rated the intensity of facial expressions and nonverbal vocalizations for each of the 6 basic emotion labels. For each participant and each modality, we then computed a representation matrix with the intensity ratings of each emotion. These matrices allowed us to examine the patterns of confusions between emotions and to characterize the representations

  1. Letter representations in writing: An fMRI adaptation approach

    Directory of Open Access Journals (Sweden)

    Olivier eDufor

    2013-10-01

    Full Text Available Abstract:Behavioral and neuropsychological research in reading and spelling has provided evidence for the role of the following types of orthographic representations in letter writing: letter forms, letter case, and abstract letter identities. We report on the results of an fMRI investigation designed to identify the neural substrates of these different representational types. Using a neural adaptation paradigm we examined the neural distribution of inhibition and release from inhibition in a letter-writing task in which, on every trial, participants produced three repetitions of the same letter and a fourth letter that was either identical to (no-change trial or different from the previous three (change trial. Change trials involved a change in the shape, case and/or identity of the letter. After delineating the general letter writing network by identifying areas that exhibited significant neural adaptation effects on no-change trials, we used deconvolution analysis to examine this network for effects of release from inhibition on change trials. In this way we identified regions specifically associated with the representation of letter shape (left SFS and SFG/pre-CG and letter identity (left fusiform gyrus or both (cerebellum, post-central gyrus and middle frontal gyrus. No regions were associated with the representation of letter case. This study showcases an investigational approach that allows for the differentiation of the neurotopography of the representational types that are key to our ability to produce written language.

  2. Representation and processing of structures with binary sparse distributed codes

    OpenAIRE

    Rachkovskij, Dmitri A.

    1999-01-01

    The schemes for compositional distributed representations include those allowing on-the-fly construction of fixed dimensionality codevectors to encode structures of various complexity. Similarity of such codevectors takes into account both structural and semantic similarity of represented structures. In this paper we provide a comparative description of sparse binary distributed representation developed in the frames of the Associative-Projective Neural Network architecture and more well-know...

  3. 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.

  4. Neural correlates of side-specific odour memory in mushroom body output neurons.

    Science.gov (United States)

    Strube-Bloss, Martin F; Nawrot, Martin P; Menzel, Randolf

    2016-12-14

    Humans and other mammals as well as honeybees learn a unilateral association between an olfactory stimulus presented to one side and a reward. In all of them, the learned association can be behaviourally retrieved via contralateral stimulation, suggesting inter-hemispheric communication. However, the underlying neuronal circuits are largely unknown and neural correlates of across-brain-side plasticity have yet not been demonstrated. We report neural plasticity that reflects lateral integration after side-specific odour reward conditioning. Mushroom body output neurons that did not respond initially to contralateral olfactory stimulation developed a unique and stable representation of the rewarded compound stimulus (side and odour) predicting its value during memory retention. The encoding of the reward-associated compound stimulus is delayed by about 40 ms compared with unrewarded neural activity, indicating an increased computation time for the read-out after lateral integration. © 2016 The Author(s).

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

    Directory of Open Access Journals (Sweden)

    Gerard Marx

    2017-07-01

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

  6. Isolating neural correlates of the pacemaker for food anticipation.

    Directory of Open Access Journals (Sweden)

    Ian David Blum

    Full Text Available Mice fed a single daily meal at intervals within the circadian range exhibit food anticipatory activity. Previous investigations strongly suggest that this behaviour is regulated by a circadian pacemaker entrained to the timing of fasting/refeeding. The neural correlate(s of this pacemaker, the food entrainable oscillator (FEO, whether found in a neural network or a single locus, remain unknown. This study used a canonical property of circadian pacemakers, the ability to continue oscillating after removal of the entraining stimulus, to isolate activation within the neural correlates of food entrainable oscillator from all other mechanisms driving food anticipatory activity. It was hypothesized that continued anticipatory activation of central nuclei, after restricted feeding and a return to ad libitum feeding, would elucidate a neural representation of the signaling circuits responsible for the timekeeping component of the food entrainable oscillator. Animals were entrained to a temporally constrained meal then placed back on ad libitum feeding for several days until food anticipatory activity was abolished. Activation of nuclei throughout the brain was quantified using stereological analysis of c-FOS expressing cells and compared against both ad libitum fed and food entrained controls. Several hypothalamic and brainstem nuclei remained activated at the previous time of food anticipation, implicating them in the timekeeping mechanism necessary to track previous meal presentation. This study also provides a proof of concept for an experimental paradigm useful to further investigate the anatomical and molecular substrates of the FEO.

  7. A model of interval timing by neural integration

    Science.gov (United States)

    Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip

    2011-01-01

    We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374

  8. Neural processing of reward magnitude under varying attentional demands.

    Science.gov (United States)

    Stoppel, Christian Michael; Boehler, Carsten Nicolas; Strumpf, Hendrik; Heinze, Hans-Jochen; Hopf, Jens-Max; Schoenfeld, Mircea Ariel

    2011-04-06

    Central to the organization of behavior is the ability to represent the magnitude of a prospective reward and the costs related to obtaining it. Therein, reward-related neural activations are discounted in dependence of the effort required to resolve a given task. Varying attentional demands of the task might however affect reward-related neural activations. Here we employed fMRI to investigate the neural representation of expected values during a monetary incentive delay task with varying attentional demands. Following a cue, indicating at the same time the difficulty (hard/easy) and the reward magnitude (high/low) of the upcoming trial, subjects performed an attention task and subsequently received feedback about their monetary reward. Consistent with previous results, activity in anterior-cingulate, insular/orbitofrontal and mesolimbic regions co-varied with the anticipated reward-magnitude, but also with the attentional requirements of the task. These activations occurred contingent on action-execution and resembled the response time pattern of the subjects. In contrast, cue-related activations, signaling the forthcoming task-requirements, were only observed within attentional control structures. These results suggest that anticipated reward-magnitude and task-related attentional demands are concurrently processed in partially overlapping neural networks of anterior-cingulate, insular/orbitofrontal, and mesolimbic regions. Copyright © 2011 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2017-01-01

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

  10. Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

    Science.gov (United States)

    Orhan, A Emin; Ma, Wei Ji

    2017-07-26

    Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

  11. Social representations of women

    Directory of Open Access Journals (Sweden)

    Álvaro Estramiana, José Luis

    2006-05-01

    Full Text Available Social Representations is one of the most important theories in contemporary social psychology. Since the social psychologist Serge Moscovici developed his theory of social representations to explain how a scientific theory such as the psychoanalysis turns into a common sense knowledge many studies have been done by different social psychologists. The analysis of the social representations of women as represented in myths and popular beliefs is an excellent opportunity to study how this theory can be applied to this representational field. At the same time it makes possible to understand the formation of attitudes towards women

  12. Cortical mechanisms for the segregation and representation of acoustic textures.

    Science.gov (United States)

    Overath, Tobias; Kumar, Sukhbinder; Stewart, Lauren; von Kriegstein, Katharina; Cusack, Rhodri; Rees, Adrian; Griffiths, Timothy D

    2010-02-10

    Auditory object analysis requires two fundamental perceptual processes: the definition of the boundaries between objects, and the abstraction and maintenance of an object's characteristic features. Although it is intuitive to assume that the detection of the discontinuities at an object's boundaries precedes the subsequent precise representation of the object, the specific underlying cortical mechanisms for segregating and representing auditory objects within the auditory scene are unknown. We investigated the cortical bases of these two processes for one type of auditory object, an "acoustic texture," composed of multiple frequency-modulated ramps. In these stimuli, we independently manipulated the statistical rules governing (1) the frequency-time space within individual textures (comprising ramps with a given spectrotemporal coherence) and (2) the boundaries between textures (adjacent textures with different spectrotemporal coherences). Using functional magnetic resonance imaging, we show mechanisms defining boundaries between textures with different coherences in primary and association auditory cortices, whereas texture coherence is represented only in association cortex. Furthermore, participants' superior detection of boundaries across which texture coherence increased (as opposed to decreased) was reflected in a greater neural response in auditory association cortex at these boundaries. The results suggest a hierarchical mechanism for processing acoustic textures that is relevant to auditory object analysis: boundaries between objects are first detected as a change in statistical rules over frequency-time space, before a representation that corresponds to the characteristics of the perceived object is formed.

  13. Dissociation of response and feedback negativity in schizophrenia: Electrophysiological and computational evidence for a deficit in the representation of value

    Directory of Open Access Journals (Sweden)

    Sarah E Morris

    2011-10-01

    Full Text Available Contrasting theories of schizophrenia propose that the disorder is characterized by a deficit in phasic changes in dopamine activity in response to ongoing events or, alternatively, by a weakness in the representation of the value of responses. Schizophrenia patients have reliably reduced brain activity following incorrect responses but other research suggests that they may have intact feedback-related potentials, indicating that the impairment may be specifically response-related. We used event-related brain potentials and computational modeling to examine this issue by comparing the neural response to outcomes with the neural response to behaviors that predict outcomes in patients with schizophrenia and psychiatrically healthy comparison subjects. We recorded feedback-related activity in a passive gambling task and a time estimation task and error-related activity in a flanker task. Patients’ brain activity following an erroneous response was reduced compared to comparison subjects but feedback-related activity did not differ between groups. Using computational modeling, we simulated the effects of an overall reduction in patients’ sensitivity to feedback, selective insensitivity to positive or negative feedback, reduced learning rate and a decreased representation of the value of the response given the stimulus on each trial. The results of the computational modeling suggest that schizophrenia patients exhibit weakened representation of response values, possibly due to failure of the basal ganglia to strongly associate stimuli with appropriate response alternatives.

  14. Gravity influences the visual representation of object tilt in parietal cortex.

    Science.gov (United States)

    Rosenberg, Ari; Angelaki, Dora E

    2014-10-22

    Sensory systems encode the environment in egocentric (e.g., eye, head, or body) reference frames, creating inherently unstable representations that shift and rotate as we move. However, it is widely speculated that the brain transforms these signals into an allocentric, gravity-centered representation of the world that is stable and independent of the observer's spatial pose. Where and how this representation may be achieved is currently unknown. Here we demonstrate that a subpopulation of neurons in the macaque caudal intraparietal area (CIP) visually encodes object tilt in nonegocentric coordinates defined relative to the gravitational vector. Neuronal responses to the tilt of a visually presented planar surface were measured with the monkey in different spatial orientations (upright and rolled left/right ear down) and then compared. This revealed a continuum of representations in which planar tilt was encoded in a gravity-centered reference frame in approximately one-tenth of the comparisons, intermediate reference frames ranging between gravity-centered and egocentric in approximately two-tenths of the comparisons, and in an egocentric reference frame in less than half of the comparisons. Altogether, almost half of the comparisons revealed a shift in the preferred tilt and/or a gain change consistent with encoding object orientation in nonegocentric coordinates. Through neural network modeling, we further show that a purely gravity-centered representation of object tilt can be achieved directly from the population activity of CIP-like units. These results suggest that area CIP may play a key role in creating a stable, allocentric representation of the environment defined relative to an "earth-vertical" direction. Copyright © 2014 the authors 0270-6474/14/3414170-11$15.00/0.

  15. Body representation in patients after vascular brain injuries

    OpenAIRE

    Razmus, Magdalena

    2017-01-01

    Neuropsychological literature suggests that body representation is a multidimensional concept consisting of various types of representations. Previous studies have demonstrated dissociations between three types of body representation specified by the kind of data and processes, i.e. body schema, body structural description, and body semantics. The aim of the study was to describe the state of body representation in patients after vascular brain injuries and to provide evidence for the differe...

  16. Bilingual Lexical Interactions in an Unsupervised Neural Network Model

    Science.gov (United States)

    Zhao, Xiaowei; Li, Ping

    2010-01-01

    In this paper we present an unsupervised neural network model of bilingual lexical development and interaction. We focus on how the representational structures of the bilingual lexicons can emerge, develop, and interact with each other as a function of the learning history. The results show that: (1) distinct representations for the two lexicons…

  17. Self-other disturbance in borderline personality disorder: Neural, self-report, and performance-based evidence.

    Science.gov (United States)

    Beeney, Joseph E; Hallquist, Michael N; Ellison, William D; Levy, Kenneth N

    2016-01-01

    Individuals with borderline personality disorder (BPD) display an impoverished sense of self and representations of self and others that shift between positive and negative poles. However, little research has investigated the nature of representational disturbance in BPD. The present study takes a multimodal approach. A card sort task was used to investigate complexity, integration, and valence of self-representation in BPD. Impairment in maintenance of self and other representations was assessed using a personality representational maintenance task. Finally, functional MRI (fMRI) was used to assess whether individuals with BPD show neural abnormalities related specifically to the self and what brain areas may be related to poor representational maintenance. Individuals with BPD sorted self-aspects suggesting more complexity of self-representation, but also less integration and more negative valence overall. On the representational maintenance task, individuals with BPD showed less consistency in their representations of self and others over the 3-hr period, but only for abstract, personality-based representations. Performance on this measure mediated between-groups brain activation in several areas supporting social cognition. We found no evidence for social-cognitive disturbance specific to the self. Additionally, the BPD group showed main effects, insensitive to condition, of hyperactivation in the medial prefrontal cortex, temporal parietal junction, several regions of the frontal pole, the precuneus and middle temporal gyrus, all areas crucial social cognition. In contrast, controls evidenced greater activation in visual, sensory, motor, and mirror neuron regions. These findings are discussed in relation to research regarding hypermentalization and the overlap between self- and other-disturbance. (c) 2016 APA, all rights reserved).

  18. Incorporating linguistic knowledge for learning distributed word representations.

    Directory of Open Access Journals (Sweden)

    Yan Wang

    Full Text Available Combined with neural language models, distributed word representations achieve significant advantages in computational linguistics and text mining. Most existing models estimate distributed word vectors from large-scale data in an unsupervised fashion, which, however, do not take rich linguistic knowledge into consideration. Linguistic knowledge can be represented as either link-based knowledge or preference-based knowledge, and we propose knowledge regularized word representation models (KRWR to incorporate these prior knowledge for learning distributed word representations. Experiment results demonstrate that our estimated word representation achieves better performance in task of semantic relatedness ranking. This indicates that our methods can efficiently encode both prior knowledge from knowledge bases and statistical knowledge from large-scale text corpora into a unified word representation model, which will benefit many tasks in text mining.

  19. TUTORIAL: Neural blackboard architectures: the realization of compositionality and systematicity in neural networks

    Science.gov (United States)

    de Kamps, Marc; van der Velde, Frank

    2006-03-01

    In this paper, we will first introduce the notions of systematicity and combinatorial productivity and we will argue that these notions are essential for human cognition and probably for every agent that needs to be able to deal with novel, unexpected situations in a complex environment. Agents that use compositional representations are faced with the so-called binding problem and the question of how to create neural network architectures that can deal with it is essential for understanding higher level cognition. Moreover, an architecture that can solve this problem is likely to scale better with problem size than other neural network architectures. Then, we will discuss object-based attention. The influence of spatial attention is well known, but there is solid evidence for object-based attention as well. We will discuss experiments that demonstrate object-based attention and will discuss a model that can explain the data of these experiments very well. The model strongly suggests that this mode of attention provides a neural basis for parallel search. Next, we will show a model for binding in visual cortex. This model is based on a so-called neural blackboard architecture, where higher cortical areas act as processors, specialized for specific features of a visual stimulus, and lower visual areas act as a blackboard for communication between these processors. This implies that lower visual areas are involved in more than bottom-up visual processing, something which already was apparent from the large number of recurrent connections from higher to lower visual areas. This model identifies a specific role for these feedback connections. Finally, we will discuss the experimental evidence that exists for this architecture. .

  20. The effectiveness of cognitive- behavior therapy on illness representations of multiple-sclerosis and improving their emotional states

    Directory of Open Access Journals (Sweden)

    Farhad Hazhir

    2012-01-01

    Full Text Available Background: Illness representations (based on Leventhal's model are associated with chronic illness outcomes. It has been suggested that targeting these cognitive components improves illness outcomes. Multiple sclerosis is a common disorder between neural and immune systems that creates physical and psychological consequences. There are few pre psychological trails on these patients. The aim of this study was to determine effectiveness of cognitive-behavior therapy on altering illness representations and improving emotional states of the patients.Methods: By using a randomized controlled trial design, among 52 selected patients, 35 volunteers randomly were allocated into intervention and control groups. An extensive interventional cognitive behavior therapy based package was conducted to intervention group in 10 weekly sessions. The control group stayed in waiting list and participated in 5 group meeting sessions. (IPQR and (DASS-42 psychological scales were administered, Leven and T statistical tests were applied for dat analysis.Results: The results showed positive changes in four illness representation components of patients including illness (identity, consequences, coherence and personal control. Associated improvement occurred in depression, anxiety, stress and emotional representations.Conclusion: Mooney and Padeskey's theoretically based cognitive-behavior therapy, is effective on illness representations modification and improving emotional states of the patients. The findings are less similar to Goodman's trial on Systemic Lupus Erythematosus patients and more similar to Petrie's trail on cardiac patients.

  1. Neural correlates of adaptation to voice identity.

    Science.gov (United States)

    Schweinberger, Stefan R; Walther, Christian; Zäske, Romi; Kovács, Gyula

    2011-11-01

    Apart from speech content, the human voice also carries paralinguistic information about speaker identity. Voice identification and its neural correlates have received little scientific attention up to now. Here we use event-related potentials (ERPs) in an adaptation paradigm, in order to investigate the neural representation and the time course of vocal identity processing. Participants adapted to repeated utterances of vowel-consonant-vowel (VCV) of one personally familiar speaker (either A or B), before classifying a subsequent test voice varying on an identity continuum between these two speakers. Following adaptation to speaker A, test voices were more likely perceived as speaker B and vice versa, and these contrastive voice identity aftereffects (VIAEs) were much more pronounced when the same syllable, rather than a different syllable, was used as adaptor. Adaptation induced amplitude reductions of the frontocentral N1-P2 complex and a prominent reduction of the parietal P3 component, for test voices preceded by identity-corresponding adaptors. Importantly, only the P3 modulation remained clear for across-syllable combinations of adaptor and test stimuli. Our results suggest that voice identity is contrastively processed by specialized neurons in auditory cortex within ∼250 ms after stimulus onset, with identity processing becoming less dependent on speech content after ∼300 ms. ©2011 The British Psychological Society.

  2. Representation and Reference

    NARCIS (Netherlands)

    Ankersmit, F.R.

    2010-01-01

    This essay focuses on the historical text as a whole. It does so by conceiving of the historical text as representation - in the way the we may say of a photo or a painting that it represents the person depicted on it. It is argued that representation cannot be properly understood by modelling it on

  3. Wigner's Symmetry Representation Theorem

    Indian Academy of Sciences (India)

    IAS Admin

    This article elucidates the important role the no- tion of symmetry has played in physics. It dis- cusses the proof of one of the important theorems of quantum mechanics, viz., Wigner's Symmetry. Representation Theorem. It also shows how the representations of various continuous and dis- crete symmetries follow from the ...

  4. MORPHOLOGICAL REPRESENTATION AND SEMANTIC ...

    African Journals Online (AJOL)

    MORPHOLOGICAL REPRESENTATION AND SEMANTIC INTERPRETATION. Rudolf P. Botha. Introduction ... The morphological representation assigned to a complex word must provide the formal structure required ..... It has been argued in the literature that "markedness" claims such as. (16)(a) and (b) are unacceptable ...

  5. Time-frequency representation based on time-varying ...

    Indian Academy of Sciences (India)

    Abstract. A parametric time-frequency representation is presented based on time- varying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identification of time-varying model coefficients and the determination of model order, are addressed by means of neural ...

  6. Time-frequency representation based on time-varying ...

    Indian Academy of Sciences (India)

    A parametric time-frequency representation is presented based on timevarying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identification of time-varying model coefficients and the determination of model order, are addressed by means of neural networks and ...

  7. More than Skin Deep: Body Representation beyond Primary Somatosensory Cortex

    Science.gov (United States)

    Longo, Matthew R.; Azanon, Elena; Haggard, Patrick

    2010-01-01

    The neural circuits underlying initial sensory processing of somatic information are relatively well understood. In contrast, the processes that go beyond primary somatosensation to create more abstract representations related to the body are less clear. In this review, we focus on two classes of higher-order processing beyond Somatosensation.…

  8. Embedded data representations

    DEFF Research Database (Denmark)

    Willett, Wesley; Jansen, Yvonne; Dragicevic, Pierre

    2017-01-01

    We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles...... are making it increasingly easier to display data in-context. While researchers and artists have already begun to create embedded data representations, the benefits, trade-offs, and even the language necessary to describe and compare these approaches remain unexplored. In this paper, we formalize the notion...... of physical data referents – the real-world entities and spaces to which data corresponds – and examine the relationship between referents and the visual and physical representations of their data. We differentiate situated representations, which display data in proximity to data referents, and embedded...

  9. Group and representation theory

    CERN Document Server

    Vergados, J D

    2017-01-01

    This volume goes beyond the understanding of symmetries and exploits them in the study of the behavior of both classical and quantum physical systems. Thus it is important to study the symmetries described by continuous (Lie) groups of transformations. We then discuss how we get operators that form a Lie algebra. Of particular interest to physics is the representation of the elements of the algebra and the group in terms of matrices and, in particular, the irreducible representations. These representations can be identified with physical observables. This leads to the study of the classical Lie algebras, associated with unitary, unimodular, orthogonal and symplectic transformations. We also discuss some special algebras in some detail. The discussion proceeds along the lines of the Cartan-Weyl theory via the root vectors and root diagrams and, in particular, the Dynkin representation of the roots. Thus the representations are expressed in terms of weights, which are generated by the application of the elemen...

  10. Neural mechanisms of order information processing in working memory

    Directory of Open Access Journals (Sweden)

    Barbara Dolenc

    2013-11-01

    Full Text Available The ability to encode and maintain the exact order of short sequences of stimuli or events is often crucial to our ability for effective high-order planning. However, it is not yet clear which neural mechanisms underpin this process. Several studies suggest that in comparison with item recognition temporal order coding activates prefrontal and parietal brain regions. Results of various studies tend to favour the hypothesis that the order of the stimuli is represented and encoded on several stages, from primacy and recency estimates to the exact position of the item in a sequence. Different brain regions play a different role in this process. Dorsolateral prefrontal cortex has a more general role in attention, while the premotor cortex is more involved in the process of information grouping. Parietal lobe and hippocampus also play a significant role in order processing as they enable the representation of distance. Moreover, order maintenance is associated with the existence of neural oscillators that operate at different frequencies. Electrophysiological studies revealed that theta and alpha oscillations play an important role in the maintenance of temporal order information. Those EEG oscillations are differentially associated with processes that support the maintenance of order information and item recognition. Various studies suggest a link between prefrontal areas and memory for temporal order, implying that EEG neural oscillations in the prefrontal cortex may play a role in the maintenance of information on temporal order.

  11. Representation of Cognitive Reappraisal Goals in Frontal Gamma Oscillations

    Science.gov (United States)

    Kang, Jae-Hwan; Jeong, Ji Woon; Kim, Hyun Taek; Kim, Sang Hee; Kim, Sung-Phil

    2014-01-01

    Recently, numerous efforts have been made to understand the neural mechanisms underlying cognitive regulation of emotion, such as cognitive reappraisal. Many studies have reported that cognitive control of emotion induces increases in neural activity of the control system, including the prefrontal cortex and the dorsal anterior cingulate cortex, and increases or decreases (depending upon the regulation goal) in neural activity of the appraisal system, including the amygdala and the insula. It has been hypothesized that information about regulation goals needs to be processed through interactions between the control and appraisal systems in order to support cognitive reappraisal. However, how this information is represented in the dynamics of cortical activity remains largely unknown. To address this, we investigated temporal changes in gamma band activity (35–55 Hz) in human electroencephalograms during a cognitive reappraisal task that was comprised of three reappraisal goals: to decease, maintain, or increase emotional responses modulated by affect-laden pictures. We examined how the characteristics of gamma oscillations, such as spectral power and large-scale phase synchronization, represented cognitive reappraisal goals. We found that left frontal gamma power decreased, was sustained, or increased when the participants suppressed, maintained, or amplified their emotions, respectively. This change in left frontal gamma power appeared during an interval of 1926 to 2453 ms after stimulus onset. We also found that the number of phase-synchronized pairs of gamma oscillations over the entire brain increased when participants regulated their emotions compared to when they maintained their emotions. These results suggest that left frontal gamma power may reflect cortical representation of emotional states modulated by cognitive reappraisal goals and gamma phase synchronization across whole brain regions may reflect emotional regulatory efforts to achieve these goals

  12. 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.

  13. Letter representations in writing: an fMRI adaptation approach.

    Science.gov (United States)

    Dufor, Olivier; Rapp, Brenda

    2013-01-01

    BEHAVIORAL AND NEUROPSYCHOLOGICAL RESEARCH IN READING AND SPELLING HAS PROVIDED EVIDENCE FOR THE ROLE OF THE FOLLOWING TYPES OF ORTHOGRAPHIC REPRESENTATIONS IN LETTER WRITING: letter shapes, letter case, and abstract letter identities. We report on the results of an fMRI investigation designed to identify the neural substrates of these different representational types. Using an fMRI adaptation paradigm we examined the neural distribution of inhibition and release from inhibition in a letter-writing task in which, on every trial, participants produced three repetitions of the same letter and a fourth letter that was either identical to (no-change trial) or different from the previous three (change trial). Change trials involved a change in the shape, case, and/or identity of the letter. After delineating the general letter writing network by identifying areas that exhibited significant neural adaptation effects on no-change trials, we used deconvolution analysis to examine this network for effects of release from inhibition on change trials. In this way we identified regions specifically associated with the representation of letter shape (in the left SFS and SFG/pre-CG) and letter identity [in the left fusiform gyrus (FG)] or both [right cerebellum, left post-central gyrus (post-CG), and left middle frontal gyrus (MFG)]. No regions were associated with the representation of letter case. This study showcases an investigational approach that allows for the differentiation of the neurotopography of the representational types that are key to our ability to produce written language.

  14. Shared Representations and the Translation Process

    DEFF Research Database (Denmark)

    Schaeffer, Moritz; Carl, Michael

    2015-01-01

    The purpose of the present chapter is to investigate automated processing during translation. We provide evidence from a translation priming study which suggests that translation involves activation of shared lexico-semantic and syntactical representations, i.e., the activation of features of both...... source and target language items which share one single cognitive representation. We argue that activation of shared representations facilitates automated processing. The chapter revises the literal translation hypothesis and the monitor model (Ivir 1981; Toury 1995; Tirkkonen-Condit 2005), and re......-defines it in terms of findings from translation process research. On the basis of the evidence, we propose a recursive model of translation....

  15. Shared Representations and the Translation Process

    DEFF Research Database (Denmark)

    Schaeffer, Moritz; Carl, Michael

    2013-01-01

    The purpose of the present paper is to investigate automated processing during translation. We provide evidence from a translation priming study which suggests that translation involves activation of shared lexico-semantic and syntactical representations, i.e., the activation of features of both...... source and target language items which share one single cognitive representation. We argue that activation of shared representations facilitates automated processing. The paper revises the literal translation hypothesis and the monitor model (Ivir 1981; Toury 1995; Tirkkonen-Condit 2005), and re......-defines it in terms of findings from translation process research. On the basis of the evidence, we propose a recursive model of translation....

  16. Convolutional Neural Networks - Generalizability and Interpretations

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David

    from data despite it being limited in amount or context representation. Within Machine Learning this thesis focuses on Convolutional Neural Networks for Computer Vision. The research aims to answer how to explore a model's generalizability to the whole population of data samples and how to interpret...

  17. Neural modeling of prefrontal executive function

    Energy Technology Data Exchange (ETDEWEB)

    Levine, D.S. [Univ. of Texas, Arlington, TX (United States)

    1996-12-31

    Brain executive function is based in a distributed system whereby prefrontal cortex is interconnected with other cortical. and subcortical loci. Executive function is divided roughly into three interacting parts: affective guidance of responses; linkage among working memory representations; and forming complex behavioral schemata. Neural network models of each of these parts are reviewed and fit into a preliminary theoretical framework.

  18. A Neural Model of Distance-Dependent Percept of Object Size Constancy.

    Directory of Open Access Journals (Sweden)

    Jiehui Qian

    Full Text Available Size constancy is one of the well-known visual phenomena that demonstrates perceptual stability to account for the effect of viewing distance on retinal image size. Although theories involving distance scaling to achieve size constancy have flourished based on psychophysical studies, its underlying neural mechanisms remain unknown. Single cell recordings show that distance-dependent size tuned cells are common along the ventral stream, originating from V1, V2, and V4 leading to IT. In addition, recent research employing fMRI demonstrates that an object's perceived size, associated with its perceived egocentric distance, modulates its retinotopic representation in V1. These results suggest that V1 contributes to size constancy, and its activity is possibly regulated by feedback of distance information from other brain areas. Here, we propose a neural model based on these findings. First, we construct an egocentric distance map in LIP by integrating horizontal disparity and vergence through gain-modulated MT neurons. Second, LIP neurons send modulatory feedback of distance information to size tuned cells in V1, resulting in a spread of V1 cortical activity. This process provides V1 with distance-dependent size representations. The model supports that size constancy is preserved by scaling retinal image size to compensate for changes in perceived distance, and suggests a possible neural circuit capable of implementing this process.

  19. Media theory: Representations and examples

    National Research Council Canada - National Science Library

    Ovchinnikov, Sergei

    2008-01-01

    In this paper we develop a representational approach to media theory. We construct representations of media by well-graded families of sets and partial cubes and establish the uniqueness of these representations...

  20. Prospective coding in event representation.

    Science.gov (United States)

    Schütz-Bosbach, Simone; Prinz, Wolfgang

    2007-06-01

    A perceived event such as a visual stimulus in the external world and a to-be-produced event such as an intentional action are subserved by event representations. Event representations do not only contain information about present states but also about past and future states. Here we focus on the role of representing future states in event perception and generation (i.e., prospective coding). Relevant theoretical issues and paradigms are discussed. We suggest that the predictive power of the motor system may be exploited for prospective coding not only in producing but also in perceiving events. Predicting is more advantageous than simply reacting. Perceptual prediction allows us to select appropriate responses ahead of the realization of an (anticipated) event and therefore, it is indispensable to flexibly and timely adapt to new situations and thus, successfully interact with our physical and social environment.

  1. Understanding perception through neural "codes".

    Science.gov (United States)

    Freeman, Walter J

    2011-07-01

    A major challenge for cognitive scientists is to deduce and explain the neural mechanisms of the rapid transposition between stimulus energy and recalled memory-between the specific (sensation) and the generic (perception)-in both material and mental aspects. Researchers are attempting three explanations in terms of neural codes. The microscopic code: cellular neurobiologists correlate stimulus properties with the rates and frequencies of trains of action potentials induced by stimuli and carried by topologically organized axons. The mesoscopic code: cognitive scientists formulate symbolic codes in trains of action potentials from feature-detector neurons of phonemes, lines, odorants, vibrations, faces, etc., that object-detector neurons bind into representations of stimuli. The macroscopic code: neurodynamicists extract neural correlates of stimuli and associated behaviors in spatial patterns of oscillatory fields of dendritic activity, which self-organize and evolve on trajectories through high-dimensional brain state space. This multivariate code is expressed in landscapes of chaotic attractors. Unlike other scientific codes, such as DNA and the periodic table, these neural codes have no alphabet or syntax. They are epistemological metaphors that experimentalists need to measure neural activity and engineers need to model brain functions. My aim is to describe the main properties of the macroscopic code and the grand challenge it poses: how do very large patterns of textured synchronized oscillations form in cortex so quickly? © 2010 IEEE

  2. Neural Approaches to Machine Consciousness

    Science.gov (United States)

    Aleksander, Igor; Eng., F. R.

    2008-10-01

    `Machine Consciousness', which some years ago might have been suppressed as an inappropriate pursuit, has come out of the closet and is now a legitimate area of research concern. This paper briefly surveys the last few years of worldwide research in this area which divides into rule-based and neural approaches and then reviews the work of the author's laboratory during the last ten years. The paper develops a fresh perspective on this work: it is argued that neural approaches, in this case, digital neural systems, can address phenomenological consciousness. Important clarifications of phenomenology and virtuality which enter this modelling are explained in the early parts of the paper. In neural models, phenomenology is a form of depictive inner representation that has five specific axiomatic features: a sense of self-presence in an external world; a sense of imagination of past experience and fiction; a sense of attention; a capacity for planning; a sense of emotion-based volition that influences planning. It is shown that these five features have separate but integrated support in dynamic neural systems.

  3. Learning Semantic-Aligned Action Representation.

    Science.gov (United States)

    Ni, Bingbing; Li, Teng; Yang, Xiaokang

    2017-08-31

    A fundamental bottleneck for achieving highly discriminative action representation is that local motion/appearance features are usually not semantic aligned. Namely, a local feature, such as a motion vector or motion trajectory, does not possess any attribute that indicates which moving body part or operated object it is associated with. This mostly leads to global feature pooling/representation learning methods that are often too coarse. Inspired by the recent success of end-to-end (pixel-to-pixel) deep convolutional neural networks (DCNNs), in this paper, we first propose a DCNN architecture, which maps a human centric image region onto human body part response maps. Based on these response maps, we propose a second DCNN, which achieves semantic-aligned feature representation learning. Prior knowledge that only a few parts are responsible for a certain action is also utilized by introducing a group (part) sparseness prior during feature learning. The learned semantic-aligned feature not only boosts the discriminative capability of action representation, but also possesses the good nature of robustness to pose variations and occlusions. Finally, an iterative mining method is employed for learning discriminative action primitive detectors. Extensive experiments on action recognition benchmarks demonstrate a superior recognition performance of the proposed framework.

  4. Neural and behavioral correlates of drawing in an early blind painter: a case study.

    Science.gov (United States)

    Amedi, Amir; Merabet, Lotfi B; Camprodon, Joan; Bermpohl, Felix; Fox, Sharon; Ronen, Itamar; Kim, Dae-Shik; Pascual-Leone, Alvaro

    2008-11-25

    Humans rely heavily on vision to identify objects in the world and can create mental representations of the objects they encounter. Objects can also be identified and mentally represented through haptic exploration. However, it is unclear whether prior visual experience is necessary to generate these internal representations. Subject EA, an early blind artist, provides insight into this question. Like other blind individuals, EA captures the external world by touch. However, he is also able to reveal his internal representations through highly detailed drawings that are unequivocally understandable by a sighted person. We employed fMRI to investigate the neural correlates associated with EA's ability to transform tactilely explored three-dimensional objects into drawings and contrasted these findings with a series of control conditions (e.g. nonsensical scribbling as a sensory-motor control). Activation during drawing (compared to scribbling) occurred in brain areas normally associated with vision, including the striate cortex along with frontal and parietal cortical regions. Some of these areas showed overlap when EA was asked to mentally imagine the pictures he had to draw (albeit to a lesser anatomical extent and signal magnitude). These results have important implications as regards our understanding of the ways in which tactile information can generate mental representations of shapes and scenes in the absence of normal visual development. Furthermore, these findings suggest the occipital cortex plays a key role in supporting mental representations even without prior visual experience.

  5. 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

  6. Nest-representable tolerances

    OpenAIRE

    Lipparini, Paolo

    2017-01-01

    We introduce the notion of a nest-representable tolerance and show that some results from our former paper "From congruence identities to tolerance identities" [CT] can be extended to this more general setting.

  7. Hyperfinite representation of distributions

    Indian Academy of Sciences (India)

    Hyperfinite representation of distributions is studied following the method introduced by Kinoshita [2, 3], although we use a different approach much in the vein of [4]. Products and Fourier transforms of representatives of distributions are also analysed.

  8. Wigner's Symmetry Representation Theorem

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 19; Issue 10. Wigner's Symmetry Representation Theorem: At the Heart of Quantum Field Theory! Aritra Kr Mukhopadhyay. General Article Volume 19 Issue 10 October 2014 pp 900-916 ...

  9. Boundary representation modelling techniques

    CERN Document Server

    2006-01-01

    Provides the most complete presentation of boundary representation solid modelling yet publishedOffers basic reference information for software developers, application developers and users Includes a historical perspective as well as giving a background for modern research.

  10. Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language.

    Science.gov (United States)

    Ferjan Ramirez, Naja; Leonard, Matthew K; Davenport, Tristan S; Torres, Christina; Halgren, Eric; Mayberry, Rachel I

    2016-03-01

    One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772-2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language

    Science.gov (United States)

    Ferjan Ramirez, Naja; Leonard, Matthew K.; Davenport, Tristan S.; Torres, Christina; Halgren, Eric; Mayberry, Rachel I.

    2016-01-01

    One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772–2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience. PMID:25410427

  12. Exergy representations in thermodynamics

    OpenAIRE

    Favrat, Daniel; Maréchal, François

    2015-01-01

    The paper reviews various representations of exergy and exergy losses in energy systems going from simple heat exchanger (heat transfer, dissipation and embedded exergy) to the exergy of full energy systems from fossil or non fossil resources (including the diffusion exergy). The systems shown include shell in tube heat exchangers, thermal power cycles, cogeneration, heat pump direct heating systems and cryogenic systems. The representations include simple gravitational analogies to extended ...

  13. The neural component-process architecture of endogenously generated emotion.

    Science.gov (United States)

    Engen, Haakon G; Kanske, Philipp; Singer, Tania

    2017-02-01

    Despite the ubiquity of endogenous emotions and their role in both resilience and pathology, the processes supporting their generation are largely unknown. We propose a neural component process model of endogenous generation of emotion (EGE) and test it in two functional magnetic resonance imaging (fMRI) experiments (N = 32/293) where participants generated and regulated positive and negative emotions based on internal representations, usin self-chosen generation methods. EGE activated nodes of salience (SN), default mode (DMN) and frontoparietal control (FPCN) networks. Component processes implemented by these networks were established by investigating their functional associations, activation dynamics and integration. SN activation correlated with subjective affect, with midbrain nodes exclusively distinguishing between positive and negative affect intensity, showing dynamics consistent generation of core affect. Dorsomedial DMN, together with ventral anterior insula, formed a pathway supporting multiple generation methods, with activation dynamics suggesting it is involved in the generation of elaborated experiential representations. SN and DMN both coupled to left frontal FPCN which in turn was associated with both subjective affect and representation formation, consistent with FPCN supporting the executive coordination of the generation process. These results provide a foundation for research into endogenous emotion in normal, pathological and optimal function. © The Author (2016). Published by Oxford University Press.

  14. Contacts de langues et representations (Language Contacts and Representations).

    Science.gov (United States)

    Matthey, Marinette, Ed.

    1997-01-01

    Essays on language contact and the image of language, entirely in French, include: "Representations 'du' contexte et representations 'en' contexte? Eleves et enseignants face a l'apprentissage de la langue" ("Representations 'of' Context or Representations 'in' Context? Students and Teachers Facing Language Learning" (Laurent…

  15. Neural mechanisms of discourse comprehension: a human lesion study.

    Science.gov (United States)

    Barbey, Aron K; Colom, Roberto; Grafman, Jordan

    2014-01-01

    Discourse comprehension is a hallmark of human social behaviour and refers to the act of interpreting a written or spoken message by constructing mental representations that integrate incoming language with prior knowledge and experience. Here, we report a human lesion study (n = 145) that investigates the neural mechanisms underlying discourse comprehension (measured by the Discourse Comprehension Test) and systematically examine its relation to a broad range of psychological factors, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores obtained from these factors were submitted to voxel-based lesion-symptom mapping to elucidate their neural substrates. Stepwise regression analyses revealed that working memory and extraversion reliably predict individual differences in discourse comprehension: higher working memory scores and lower extraversion levels predict better discourse comprehension performance. Lesion mapping results indicated that these convergent variables depend on a shared network of frontal and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The observed findings motivate an integrative framework for understanding the neural foundations of discourse comprehension, suggesting that core elements of discourse processing emerge from a distributed network of brain regions that support specific competencies for executive and social function.

  16. Learning language with the wrong neural scaffolding: The cost of neural commitment to sounds.

    Directory of Open Access Journals (Sweden)

    Amy Sue Finn

    2013-11-01

    Full Text Available Does tuning to one’s native language explain the sensitive period for language learning? We explore the idea that tuning to (or becoming more selective for the properties of one’s native-language could result in being less open (or plastic for tuning to the properties of a new language. To explore how this might lead to the sensitive period for grammar learning, we ask if tuning to an earlier-learned aspect of language (sound structure has an impact on the neural representation of a later-learned aspect (grammar. English-speaking adults learned one of two miniature artificial languages over 4 days in the lab. Compared to English, both languages had novel grammar, but only one was comprised of novel sounds. After learning a language, participants were scanned while judging the grammaticality of sentences. Judgments were performed for the newly learned language and English. Learners of the similar-sounds language recruited regions that overlapped more with English. Learners of the distinct-sounds language, however, recruited the Superior Temporal Gyrus (STG to a greater extent, which was coactive with the Inferior Frontal Gyrus (IFG. Across learners, recruitment of IFG (but not STG predicted both learning success in tests conducted prior to the scan and grammatical judgment ability during the scan. Data suggest that adults’ difficulty learning language, especially grammar, could be due, at least in part, to the neural commitments they have made to the lower level linguistic components of their native language.

  17. Learning language with the wrong neural scaffolding: the cost of neural commitment to sounds

    Science.gov (United States)

    Finn, Amy S.; Hudson Kam, Carla L.; Ettlinger, Marc; Vytlacil, Jason; D'Esposito, Mark

    2013-01-01

    Does tuning to one's native language explain the “sensitive period” for language learning? We explore the idea that tuning to (or becoming more selective for) the properties of one's native-language could result in being less open (or plastic) for tuning to the properties of a new language. To explore how this might lead to the sensitive period for grammar learning, we ask if tuning to an earlier-learned aspect of language (sound structure) has an impact on the neural representation of a later-learned aspect (grammar). English-speaking adults learned one of two miniature artificial languages (MALs) over 4 days in the lab. Compared to English, both languages had novel grammar, but only one was comprised of novel sounds. After learning a language, participants were scanned while judging the grammaticality of sentences. Judgments were performed for the newly learned language and English. Learners of the similar-sounds language recruited regions that overlapped more with English. Learners of the distinct-sounds language, however, recruited the Superior Temporal Gyrus (STG) to a greater extent, which was coactive with the Inferior Frontal Gyrus (IFG). Across learners, recruitment of IFG (but not STG) predicted both learning success in tests conducted prior to the scan and grammatical judgment ability during the scan. Data suggest that adults' difficulty learning language, especially grammar, could be due, at least in part, to the neural commitments they have made to the lower level linguistic components of their native language. PMID:24273497

  18. Body representation in patients after vascular brain injuries.

    Science.gov (United States)

    Razmus, Magdalena

    2017-11-01

    Neuropsychological literature suggests that body representation is a multidimensional concept consisting of various types of representations. Previous studies have demonstrated dissociations between three types of body representation specified by the kind of data and processes, i.e. body schema, body structural description, and body semantics. The aim of the study was to describe the state of body representation in patients after vascular brain injuries and to provide evidence for the different types of body representation. The question about correlations between body representation deficits and neuropsychological dysfunctions was also investigated. Fifty patients after strokes and 50 control individuals participated in the study. They were examined with tasks referring to dynamic representation of body parts positions, topological body map, and lexical and semantic knowledge about the body. Data analysis showed that vascular brain injuries result in deficits of body representation, which may co-occur with cognitive dysfunctions, but the latter are a possible risk factor for body representation deficits rather than sufficient or imperative requisites for them. The study suggests that types of body representation may be separated on the basis not only of their content, but also of their relation with self. Principal component analysis revealed three factors, which explained over 66% of results variance. The factors, which may be interpreted as types or dimensions of mental model of a body, represent different degrees of connection with self. The results indicate another possibility of body representation types classification, which should be verified in future research.

  19. Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis.

    Directory of Open Access Journals (Sweden)

    Jörn Diedrichsen

    2017-04-01

    of a single data-analytical toolkit for understanding neural representations on the basis of multivariate brain-activity data.

  20. Does neuroimaging of suggestion elucidate hypnotic trance?

    Science.gov (United States)

    Raz, Amir

    2011-07-01

    Contemporary studies in the cognitive neuroscience of attention and suggestion shed new light on the underlying neural mechanisms that operationalize these effects. Without adhering to important caveats inherent to imaging of the living human brain, however, findings from brain imaging studies may enthrall more than explain. Scholars, practitioners, professionals, and consumers must realize that the influence words exert on focal brain activity is measurable but that these measurements are often difficult to interpret. While recent brain imaging research increasingly incorporates variations of suggestion and hypnosis, correlating overarching hypnotic experiences with specific brain substrates remains tenuous. This article elucidates the mounting role of cognitive neuroscience, including the relative merits and intrinsic limitations of neuroimaging, in better contextualizing trance-like concepts.

  1. Questions of Representations in Architecture

    DEFF Research Database (Denmark)

    2015-01-01

    Questions of Representations in Architecture is the first major Danish contribution to the current international discussion on architects' use of representations and the significance of visual media for architecture.......Questions of Representations in Architecture is the first major Danish contribution to the current international discussion on architects' use of representations and the significance of visual media for architecture....

  2. Realizations of the canonical representation

    Indian Academy of Sciences (India)

    This representation is called the canonical representation. The terminology comes from. Quantum Mechanics where the derived (Lie algebra) representation is known as the 'canon- ical commutation relation'. Traditionally, the canonical representation is realized on the Hilbert space L2(Rn) by the action. (ρ(x, y, z)f )(t) = ze.

  3. Neural art appraisal of painter: Dali or Picasso?

    Science.gov (United States)

    Yamamura, Hiromi; Sawahata, Yasuhito; Yamamoto, Miyuki; Kamitani, Yukiyasu

    2009-12-09

    One can infer an artist's identity from his or her artworks, but little is known about the neural representation of such elusive categorization. Here, we constructed a 'neural art appraiser' based on machine-learning methods that predicted the painter from the functional MRI activity pattern elicited by a painting. We found that Dali's and Picasso's artworks could be accurately classified based on brain activity alone, and that broadly distributed brain activity contributed to the neural prediction. Our approach provides a new means to probe into complex neural processes underlying art experiences.

  4. Representation Elements of Spatial Thinking

    Science.gov (United States)

    Fiantika, F. R.

    2017-04-01

    This paper aims to add a reference in revealing spatial thinking. There several definitions of spatial thinking but it is not easy to defining it. We can start to discuss the concept, its basic a forming representation. Initially, the five sense catch the natural phenomenon and forward it to memory for processing. Abstraction plays a role in processing information into a concept. There are two types of representation, namely internal representation and external representation. The internal representation is also known as mental representation; this representation is in the human mind. The external representation may include images, auditory and kinesthetic which can be used to describe, explain and communicate the structure, operation, the function of the object as well as relationships. There are two main elements, representations properties and object relationships. These elements play a role in forming a representation.

  5. Operator representations of frames

    DEFF Research Database (Denmark)

    Christensen, Ole; Hasannasab, Marzieh

    2017-01-01

    The purpose of this paper is to consider representations of frames {fk}k∈I in a Hilbert space ℋ of the form {fk}k∈I = {Tkf0}k∈I for a linear operator T; here the index set I is either ℤ or ℒ0. While a representation of this form is available under weak conditions on the frame, the analysis...... of the properties of the operator T requires more work. For example it is a delicate issue to obtain a representation with a bounded operator, and the availability of such a representation not only depends on the frame considered as a set, but also on the chosen indexing. Using results from operator theory we show...... that by embedding the Hilbert space ℋ into a larger Hilbert space, we can always represent a frame via iterations of a bounded operator, composed with the orthogonal projection onto ℋ. The paper closes with a discussion of an open problem concerning representations of Gabor frames via iterations of a bounded...

  6. Brain-to-text: Decoding spoken phrases from phone representations in the brain

    Directory of Open Access Journals (Sweden)

    Christian eHerff

    2015-06-01

    Full Text Available It has long been speculated whether communication between humans and machines based on natural speech related cortical activity is possible. Over the past decade, studies have suggested that it is feasible to recognize isolated aspects of speech from neural signals, such as auditory features, phones or one of a few isolated words. However, until now it remained an unsolved challenge to decode continuously spoken speech from the neural substrate associated with speech and language processing. Here, we show for the first time that continuously spoken speech can be decoded into the expressed words from intracranial electrocorticographic (ECoG recordings. Specifically, we implemented a system, which we call Brain-To-Text that models single phones, employs techniques from automatic speech recognition (ASR, and thereby transforms brain activity while speaking into the corresponding textual representation. Our results demonstrate that our system achieved word error rates as low as 25% and phone error rates below 50%. Additionally, our approach contributes to the current understanding of the neural basis of continuous speech production by identifying those cortical regions that hold substantial information about individual phones. In conclusion, the Brain-To-Text system described in this paper represents an important step towards human-machine communication based on imagined speech.

  7. Brain-to-text: decoding spoken phrases from phone representations in the brain.

    Science.gov (United States)

    Herff, Christian; Heger, Dominic; de Pesters, Adriana; Telaar, Dominic; Brunner, Peter; Schalk, Gerwin; Schultz, Tanja

    2015-01-01

    It has long been speculated whether communication between humans and machines based on natural speech related cortical activity is possible. Over the past decade, studies have suggested that it is feasible to recognize isolated aspects of speech from neural signals, such as auditory features, phones or one of a few isolated words. However, until now it remained an unsolved challenge to decode continuously spoken speech from the neural substrate associated with speech and language processing. Here, we show for the first time that continuously spoken speech can be decoded into the expressed words from intracranial electrocorticographic (ECoG) recordings.Specifically, we implemented a system, which we call Brain-To-Text that models single phones, employs techniques from automatic speech recognition (ASR), and thereby transforms brain activity while speaking into the corresponding textual representation. Our results demonstrate that our system can achieve word error rates as low as 25% and phone error rates below 50%. Additionally, our approach contributes to the current understanding of the neural basis of continuous speech production by identifying those cortical regions that hold substantial information about individual phones. In conclusion, the Brain-To-Text system described in this paper represents an important step toward human-machine communication based on imagined speech.

  8. Introduction to computer data representation

    CERN Document Server

    Fenwick, Peter

    2014-01-01

    Introduction to Computer Data Representation introduces readers to the representation of data within computers. Starting from basic principles of number representation in computers, the book covers the representation of both integer and floating point numbers, and characters or text. It comprehensively explains the main techniques of computer arithmetic and logical manipulation. The book also features chapters covering the less usual topics of basic checksums and 'universal' or variable length representations for integers, with additional coverage of Gray Codes, BCD codes and logarithmic repre

  9. Representation Discovery using Harmonic Analysis

    CERN Document Server

    Mahadevan, Sridhar

    2008-01-01

    Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particu

  10. Heterogeneity of the left temporal lobe in semantic representation and control: priming multiple versus single meanings of ambiguous words.

    Science.gov (United States)

    Whitney, Carin; Jefferies, Elizabeth; Kircher, Tilo

    2011-04-01

    Semantic judgments involve both representations of meaning plus executive mechanisms that guide knowledge retrieval in a task-appropriate way. These 2 components of semantic cognition-representation and control-are commonly linked to left temporal and prefrontal cortex, respectively. This simple proposal, however, remains contentious because in most functional neuroimaging studies to date, the number of concepts being activated and the involvement of executive processes during retrieval are confounded. Using functional magnetic resonance imaging, we examined a task in which semantic representation and control demands were dissociable. Words with multiple meanings like "bank" served as targets in a double-prime paradigm, in which multiple meaning activation and maximal executive demands loaded onto different priming conditions. Anterior inferior temporal gyrus (ITG) was sensitive to the number of meanings that were retrieved, suggesting a role for this region in semantic representation, while posterior middle temporal gyrus (pMTG) and inferior frontal cortex showed greater activation in conditions that maximized executive demands. These results support a functional dissociation between left ITG and pMTG, consistent with a revised neural organization in which left prefrontal and posterior temporal areas work together to underpin aspects of semantic control.

  11. Mobilities and Representations

    DEFF Research Database (Denmark)

    Thelle, Mikkel

    2017-01-01

    , literature, and film. Moreover, we hope the authors of future reviews will reflect on the ways they approached those representations. Such commentaries would provide valuable methodological insights, and we hope to begin that effort with this interview. We have asked four prominent mobility scholars......As the centerpiece of the eighth T2M yearbook, the following interview about representations of mobility signals a new and exciting focus area for Mobility in History. In future issues we hope to include reviews that grapple more with how mobilities have been imagined and represented in the arts...... to consider how they and their peers are currently confronting representations of mobility. This is particularly timely given the growing academic focus on practices, material mediation, and nonrepresentational theories, as well as on bodily reactions, emotions, and feelings that, according to those theories...

  12. Post-representational cartography

    Directory of Open Access Journals (Sweden)

    Rob Kitchin

    2010-03-01

    Full Text Available Over the past decade there has been a move amongst critical cartographers to rethink maps from a post-representational perspective – that is, a vantage point that does not privilege representational modes of thinking (wherein maps are assumed to be mirrors of the world and automatically presumes the ontological security of a map as a map, but rather rethinks and destabilises such notions. This new theorisation extends beyond the earlier critiques of Brian Harley (1989 that argued maps were social constructions. For Harley a map still conveyed the truth of a landscape, albeit its message was bound within the ideological frame of its creator. He thus advocated a strategy of identifying the politics of representation within maps in order to circumnavigate them (to reveal the truth lurking underneath, with the ontology of cartographic practice remaining unquestioned.

  13. Memetics of representation

    Directory of Open Access Journals (Sweden)

    Roberto De Rubertis

    2012-06-01

    Full Text Available This article will discuss about the physiological genesis of representation and then it will illustrate the developments, especially in evolutionary perspective, and it will show how these are mainly a result of accidental circumstances, rather than of deliberate intention of improvement. In particular, it will be argue that the representation has behaved like a meme that has arrived to its own progressive evolution coming into symbiosis with the different cultures in which it has spread, and using in this activity human work “unconsciously”. Finally it will be shown how in this action the geometry is an element key, linked to representation both to construct images using graphics operations and to erect buildings using concrete operations.

  14. Memory-optimal neural network approximation

    Science.gov (United States)

    Bölcskei, Helmut; Grohs, Philipp; Kutyniok, Gitta; Petersen, Philipp

    2017-08-01

    We summarize the main results of a recent theory-developed by the authors-establishing fundamental lower bounds on the connectivity and memory requirements of deep neural networks as a function of the complexity of the function class to be approximated by the network. These bounds are shown to be achievable. Specifically, all function classes that are optimally approximated by a general class of representation systems-so-called affine systems-can be approximated by deep neural networks with minimal connectivity and memory requirements. Affine systems encompass a wealth of representation systems from applied harmonic analysis such as wavelets, shearlets, ridgelets, α-shearlets, and more generally α-molecules. This result elucidates a remarkable universality property of deep neural networks and shows that they achieve the optimum approximation properties of all affine systems combined. Finally, we present numerical experiments demonstrating that the standard stochastic gradient descent algorithm generates deep neural networks which provide close-to-optimal approximation rates at minimal connectivity. Moreover, stochastic gradient descent is found to actually learn approximations that are sparse in the representation system optimally sparsifying the function class the network is trained on.

  15. Fixed versus mixed RSA: Explaining visual representations by fixed and mixed feature sets from shallow and deep computational models.

    Science.gov (United States)

    Khaligh-Razavi, Seyed-Mahdi; Henriksson, Linda; Kay, Kendrick; Kriegeskorte, Nikolaus

    2017-02-01

    Studies of the primate visual system have begun to test a wide range of complex computational object-vision models. Realistic models have many parameters, which in practice cannot be fitted using the limited amounts of brain-activity data typically available. Task performance optimization (e.g. using backpropagation to train neural networks) provides major constraints for fitting parameters and discovering nonlinear representational features appropriate for the task (e.g. object classification). Model representations can be compared to brain representations in terms of the representational dissimilarities they predict for an image set. This method, called representational similarity analysis (RSA), enables us to test the representational feature space as is (fixed RSA) or to fit a linear transformation that mixes the nonlinear model features so as to best explain a cortical area's representational space (mixed RSA). Like voxel/population-receptive-field modelling, mixed RSA uses a training set (different stimuli) to fit one weight per model feature and response channel (voxels here), so as to best predict the response profile across images for each response channel. We analysed response patterns elicited by natural images, which were measured with functional magnetic resonance imaging (fMRI). We found that early visual areas were best accounted for by shallow models, such as a Gabor wavelet pyramid (GWP). The GWP model performed similarly with and without mixing, suggesting that the original features already approximated the representational space, obviating the need for mixing. However, a higher ventral-stream visual representation (lateral occipital region) was best explained by the higher layers of a deep convolutional network and mixing of its feature set was essential for this model to explain the representation. We suspect that mixing was essential because the convolutional network had been trained to discriminate a set of 1000 categories, whose frequencies

  16. Switch-Independent Task Representations in Frontal and Parietal Cortex.

    Science.gov (United States)

    Loose, Lasse S; Wisniewski, David; Rusconi, Marco; Goschke, Thomas; Haynes, John-Dylan

    2017-08-16

    Alternating between two tasks is effortful and impairs performance. Previous fMRI studies have found increased activity in frontoparietal cortex when task switching is required. One possibility is that the additional control demands for switch trials are met by strengthening task representations in the human brain. Alternatively, on switch trials, the residual representation of the previous task might impede the buildup of a neural task representation. This would predict weaker task representations on switch trials, thus also explaining the performance costs. To test this, male and female participants were cued to perform one of two similar tasks, with the task being repeated or switched between successive trials. Multivoxel pattern analysis was used to test which regions encode the tasks and whether this encoding differs between switch and repeat trials. As expected, we found information about task representations in frontal and parietal cortex, but there was no difference in the decoding accuracy of task-related information between switch and repeat trials. Using cross-classification, we found that the frontoparietal cortex encodes tasks using a generalizable spatial pattern in switch and repeat trials. Therefore, task representations in frontal and parietal cortex are largely switch independent. We found no evidence that neural information about task representations in these regions can explain behavioral costs usually associated with task switching.SIGNIFICANCE STATEMENT Alternating between two tasks is effortful and slows down performance. One possible explanation is that the representations in the human brain need time to build up and are thus weaker on switch trials, explaining performance costs. Alternatively, task representations might even be enhanced to overcome the previous task. Here, we used a combination of fMRI and a brain classifier to test whether the additional control demands under switching conditions lead to an increased or decreased strength

  17. 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.

  18. The evolution of representation in simple cognitive networks.

    Science.gov (United States)

    Marstaller, Lars; Hintze, Arend; Adami, Christoph

    2013-08-01

    Representations are internal models of the environment that can provide guidance to a behaving agent, even in the absence of sensory information. It is not clear how representations are developed and whether they are necessary or even essential for intelligent behavior. We argue here that the ability to represent relevant features of the environment is the expected consequence of an adaptive process, give a formal definition of representation based on information theory, and quantify it with a measure R. To measure how R changes over time, we evolve two types of networks--an artificial neural network and a network of hidden Markov gates--to solve a categorization task using a genetic algorithm. We find that the capacity to represent increases during evolutionary adaptation and that agents form representations of their environment during their lifetime. This ability allows the agents to act on sensorial inputs in the context of their acquired representations and enables complex and context-dependent behavior. We examine which concepts (features of the environment) our networks are representing, how the representations are logically encoded in the networks, and how they form as an agent behaves to solve a task. We conclude that R should be able to quantify the representations within any cognitive system and should be predictive of an agent's long-term adaptive success.

  19. Understanding representations in design

    DEFF Research Database (Denmark)

    Bødker, Susanne

    1998-01-01

    Representing computer applications and their use is an important aspect of design. In various ways, designers need to externalize design proposals and present them to other designers, users, or managers. This article deals with understanding design representations and the work they do in design....... The article is based on a series of theoretical concepts coming out of studies of scientific and other work practices and on practical experiences from design of computer applications. The article presents alternatives to the ideas that design representations are mappings of present or future work situations...

  20. Additive and polynomial representations

    CERN Document Server

    Krantz, David H; Suppes, Patrick

    1971-01-01

    Additive and Polynomial Representations deals with major representation theorems in which the qualitative structure is reflected as some polynomial function of one or more numerical functions defined on the basic entities. Examples are additive expressions of a single measure (such as the probability of disjoint events being the sum of their probabilities), and additive expressions of two measures (such as the logarithm of momentum being the sum of log mass and log velocity terms). The book describes the three basic procedures of fundamental measurement as the mathematical pivot, as the utiliz

  1. On the spinor representation

    Energy Technology Data Exchange (ETDEWEB)

    Hoff da Silva, J.M.; Rogerio, R.J.B. [Universidade Estadual Paulista, Departamento de Fisica e Quimica, Guaratingueta, SP (Brazil); Villalobos, C.H.C. [Universidade Estadual Paulista, Departamento de Fisica e Quimica, Guaratingueta, SP (Brazil); Universidade Federal Fluminense, Instituto de Fisica, Niteroi, RJ (Brazil); Rocha, Roldao da [Universidade Federal do ABC-UFABC, Centro de Matematica, Computacao e Cognicao, Santo Andre (Brazil)

    2017-07-15

    A systematic study of the spinor representation by means of the fermionic physical space is accomplished and implemented. The spinor representation space is shown to be constrained by the Fierz-Pauli-Kofink identities among the spinor bilinear covariants. A robust geometric and topological structure can be manifested from the spinor space, wherein the first and second homotopy groups play prominent roles on the underlying physical properties, associated to fermionic fields. The mapping that changes spinor fields classes is then exemplified, in an Einstein-Dirac system that provides the spacetime generated by a fermion. (orig.)

  2. Degenerate coding in neural systems.

    Science.gov (United States)

    Leonardo, Anthony

    2005-11-01

    When the dimensionality of a neural circuit is substantially larger than the dimensionality of the variable it encodes, many different degenerate network states can produce the same output. In this review I will discuss three different neural systems that are linked by this theme. The pyloric network of the lobster, the song control system of the zebra finch, and the odor encoding system of the locust, while different in design, all contain degeneracies between their internal parameters and the outputs they encode. Indeed, although the dynamics of song generation and odor identification are quite different, computationally, odor recognition can be thought of as running the song generation circuitry backwards. In both of these systems, degeneracy plays a vital role in mapping a sparse neural representation devoid of correlations onto external stimuli (odors or song structure) that are strongly correlated. I argue that degeneracy between input and output states is an inherent feature of many neural systems, which can be exploited as a fault-tolerant method of reliably learning, generating, and discriminating closely related patterns.

  3. The representation of polysemy: MEG evidence.

    Science.gov (United States)

    Pylkkänen, Liina; Llinás, Rodolfo; Murphy, Gregory L

    2006-01-01

    Most words in natural language are polysemous, that is, they can be used in more than one way. For example, paper can be used to refer to a substance made out of wood pulp or to a daily publication printed on that substance. Although virtually every sentence contains polysemy, there is little agreement as to how polysemy is represented in the mental lexicon. Do different uses of polysemous words involve access to a single representation or do our minds store distinct representations for each different sense? Here we investigated priming between senses with a combination of behavioral and magnetoencephalographic measures in order to test whether different senses of the same word involve identity or mere formal and semantic similarity. Our results show that polysemy effects are clearly distinct from similarity effects bilaterally. In the left hemisphere, sense-relatedness elicited shorter latencies of the M350 source, which has been hypothesized to index lexical activation. Concurrent activity in the right hemisphere, on the other hand, peaked later for sense-related than for unrelated target stimuli, suggesting competition between related senses. The obtained pattern of results supports models in which the representation of polysemy involves both representational identity and difference: Related senses connect to same abstract lexical representation, but are distinctly listed within that representation.

  4. Exploring the Structure of Spatial Representations

    Science.gov (United States)

    Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

    2016-01-01

    It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

  5. Exploring the Structure of Spatial Representations.

    Directory of Open Access Journals (Sweden)

    Tamas Madl

    Full Text Available It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these 'cognitive maps' are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics characterizing participants' psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants' cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants' spatial representations, providing further support for clustering in spatial memory.

  6. Exploring the Structure of Spatial Representations.

    Science.gov (United States)

    Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

    2016-01-01

    It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these 'cognitive maps' are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants' psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants' cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants' spatial representations, providing further support for clustering in spatial memory.

  7. The effect of training methodology on knowledge representation in categorization.

    Directory of Open Access Journals (Sweden)

    Sébastien Hélie

    Full Text Available Category representations can be broadly classified as containing within-category information or between-category information. Although such representational differences can have a profound impact on decision-making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule-based (RB category structures thought to promote between-category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between-category representations whereas concept training resulted in a bias toward within-category representations. Experiment 2 focused on information-integration (II category structures thought to promote within-category representations. With II structures, there was a bias toward within-category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within-category representations could support generalization during the test phase. These data suggest that within-category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization.

  8. Unveiling the metric structure of internal representations of space.

    Science.gov (United States)

    Stella, Federico; Cerasti, Erika; Treves, Alessandro

    2013-01-01

    How are neuronal representations of space organized in the hippocampus? The self-organization of such representations, thought to be driven in the CA3 network by the strong randomizing input from the Dentate Gyrus, appears to run against preserving the topology and even less the exact metric of physical space. We present a way to assess this issue quantitatively, and find that in a simple neural network model of CA3, the average topology is largely preserved, but the local metric is loose, retaining e.g., 10% of the optimal spatial resolution.

  9. A survey of visual preprocessing and shape representation techniques

    Science.gov (United States)

    Olshausen, Bruno A.

    1988-01-01

    Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).

  10. Decoding the dynamic representation of musical pitch from human brain activity.

    Science.gov (United States)

    Sankaran, N; Thompson, W F; Carlile, S; Carlson, T A

    2018-01-16

    In music, the perception of pitch is governed largely by its tonal function given the preceding harmonic structure of the music. While behavioral research has advanced our understanding of the perceptual representation of musical pitch, relatively little is known about its representational structure in the brain. Using Magnetoencephalography (MEG), we recorded evoked neural responses to different tones presented within a tonal context. Multivariate Pattern Analysis (MVPA) was applied to "decode" the stimulus that listeners heard based on the underlying neural activity. We then characterized the structure of the brain's representation using decoding accuracy as a proxy for representational distance, and compared this structure to several well established perceptual and acoustic models. The observed neural representation was best accounted for by a model based on the Standard Tonal Hierarchy, whereby differences in the neural encoding of musical pitches correspond to their differences in perceived stability. By confirming that perceptual differences honor those in the underlying neuronal population coding, our results provide a crucial link in understanding the cognitive foundations of musical pitch across psychological and neural domains.

  11. "Similar representations of emotions across faces and voices": Correction to Kuhn et al. (2017).

    Science.gov (United States)

    2017-09-01

    Reports an error in "Similar Representations of Emotions Across Faces and Voices" by Lisa Katharina Kuhn, Taeko Wydell, Nadine Lavan, Carolyn McGettigan and Lúcia Garrido (Emotion, Advanced Online Publication, Mar 02, 2017, np). In the article, the copyright attribution was incorrectly listed and the Creative Commons CC-BY license disclaimer was incorrectly omitted from the author note. The correct copyright is "© 2017 The Author(s)" and the omitted disclaimer is below. All versions of this article have been corrected. "This article has been published under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s). Author(s) grant(s) the American Psychological Association the exclusive right to publish the article and identify itself as the original publisher." (The following abstract of the original article appeared in record 2017-09406-001.) Emotions are a vital component of social communication, carried across a range of modalities and via different perceptual signals such as specific muscle contractions in the face and in the upper respiratory system. Previous studies have found that emotion recognition impairments after brain damage depend on the modality of presentation: recognition from faces may be impaired whereas recognition from voices remains preserved, and vice versa. On the other hand, there is also evidence for shared neural activation during emotion processing in both modalities. In a behavioral study, we investigated whether there are shared representations in the recognition of emotions from faces and voices. We used a within-subjects design in which participants rated the intensity of facial expressions and nonverbal vocalizations for each of the 6 basic emotion labels. For each participant and each modality, we then

  12. Gestalt-like representations hijack Chunk-and-Pass processing.

    Science.gov (United States)

    Dumitru, Magda L

    2016-01-01

    Christiansen & Chater (C&C) make two related and somewhat contradictory claims, namely that the ever abstract language representations built during Chunk-and-Pass processing allow for ever greater interference from extra-linguistic information, and that it is nevertheless the language system that re-codes incoming information into abstract representations. I analyse these claims and discuss evidence suggesting that Gestalt-like representations hijack Chunk-and-Pass processing.

  13. The role of physical digit representation and numerical magnitude representation in children's multiplication fact retrieval.

    Science.gov (United States)

    De Visscher, Alice; Noël, Marie-Pascale; De Smedt, Bert

    2016-12-01

    Arithmetic facts, in particular multiplication tables, are thought to be stored in long-term memory and to be interference prone. At least two representations underpinning these arithmetic facts have been suggested: a physical representation of the digits and a numerical magnitude representation. We hypothesized that both representations are possible sources of interference that could explain individual differences in multiplication fact performance and/or in strategy use. We investigated the specificity of these interferences on arithmetic fact retrieval and explored the relation between interference and performance on the different arithmetic operations and on general mathematics achievement. Participants were 79 fourth-grade children (M age =9.6 years) who completed a products comparison and a multiplication production task with verbal strategy reports. Performances on a speeded calculation test including the four operations and on a general mathematics achievement test were also collected. Only the interference coming from physical representations was a significant predictor of the performance across multiplications. However, both the magnitude and physical representations were unique predictors of individual differences in multiplication. The frequency of the retrieval strategy across multiplication problems and across individuals was determined only by the physical representation, which therefore is suggested as being responsible for memory storage issues. Interestingly, this impact of physical representation was not observed when predicting performance on subtraction or on general mathematical achievement. In contrast, the impact of the numerical magnitude representation was more general in that it was observed across all arithmetic operations and in general mathematics achievement. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Compact Information Representations

    Science.gov (United States)

    2016-08-02

    detections (e.g., DDoS attacks), machine learning, databases, and search. Fundamentally, compact data representations are highly beneficial because they...engineering problems in data stream computations, real-time network monitoring & anomaly detections (e.g., DDoS attacks), machine learning, databases, and

  15. Hyperfinite representation of distributions

    Indian Academy of Sciences (India)

    A nonstandard treatment of the theory of distributions in terms of a hyperfinite representa- tion has been presented in papers [2,3] by Kinoshita. A further exploitation of this treatment in an N-dimensional context has been given by Grenier [1]. In the present paper we offer a different approach to the hyperfinite representation, ...

  16. Reflection on Political Representation

    DEFF Research Database (Denmark)

    Kusche, Isabel

    2017-01-01

    This article compares how Members of Parliament in the United Kingdom and Ireland reflect on constituency service as an aspect of political representation. It differs from existing research on the constituency role of MPs in two regards. First, it approaches the question from a sociological...

  17. Between Representation and Eternity

    DEFF Research Database (Denmark)

    Atzbach, Rainer

    2016-01-01

    . At death, an indi- vidual’s corpse and burial primarily reflect the social act of representation during the funeral. The position of the arms, which have incorrectly been used as a chronological tool in Scandinavia, may indicate an evolution from a more collective act of prayer up to the eleventh century...

  18. Representation of the Divine

    DEFF Research Database (Denmark)

    Loddegaard, Anne

    2009-01-01

    out of place in a novel belonging to the serious combat literature of the Catholic Revival, and the direct representation of the supernatural is also surprising because previous Catholic Revival novelists, such as Léon Bloy and Karl-Joris Huysmans, maintain a realistic, non-magical world and deal...

  19. Representation of the Divine

    DEFF Research Database (Denmark)

    Loddegaard, Anne

    2012-01-01

    out of place in a novel belonging to the serious combat literature of the Catholic Revival, and the direct representation of the supernatural is also surprising because previous Catholic Revival novelists, such as Léon Bloy and Karl-Joris Huysmans, maintain a realistic, non-magical world and deal...

  20. Moment graphs and representations

    DEFF Research Database (Denmark)

    Jantzen, Jens Carsten

    2012-01-01

    Moment graphs and sheaves on moment graphs are basically combinatorial objects that have be used to describe equivariant intersectiion cohomology. In these lectures we are going to show that they can be used to provide a direct link from this cohomology to the representation theory of simple Lie ...

  1. The Problem of Representation

    Science.gov (United States)

    Tervo, Juuso

    2012-01-01

    In "Postphysical Vision: Art Education's Challenge in an Age of Globalized Aesthetics (AMondofesto)" (2008) and "Beyond Aesthetics: Returning Force and Truth to Art and Its Education" (2009), jan jagodzinski argued for politics that go "beyond" representation--a project that radically questions visual culture…

  2. Sociocognitive Perspectives on Representation.

    Science.gov (United States)

    Jacob, Elin K.; Shaw, Debora

    1998-01-01

    Discusses research dealing with the cognitive aspects of formal systems of knowledge representation. Highlights include the origins and theoretical foundations of the cognitive viewpoint; cognition and information science; cognitivism, mentalism, and subjective individualism; categorization; mental models; and sociocognitive approaches to indexing…

  3. Women and political representation.

    Science.gov (United States)

    Rathod, P B

    1999-01-01

    A remarkable progress in women's participation in politics throughout the world was witnessed in the final decade of the 20th century. According to the Inter-Parliamentary Union report, there were only eight countries with no women in their legislatures in 1998. The number of women ministers at the cabinet level worldwide doubled in a decade, and the number of countries without any women ministers dropped from 93 to 48 during 1987-96. However, this progress is far from satisfactory. Political representation of women, minorities, and other social groups is still inadequate. This may be due to a complex combination of socioeconomic, cultural, and institutional factors. The view that women's political participation increases with social and economic development is supported by data from the Nordic countries, where there are higher proportions of women legislators than in less developed countries. While better levels of socioeconomic development, having a women-friendly political culture, and higher literacy are considered favorable factors for women's increased political representation, adopting one of the proportional representation systems (such as a party-list system, a single transferable vote system, or a mixed proportional system with multi-member constituencies) is the single factor most responsible for the higher representation of women.

  4. Images of Galois representations

    NARCIS (Netherlands)

    Anni, Samuele

    2013-01-01

    In this thesis we investigate $2$-dimensional, continuous, odd, residual Galois representations and their images. This manuscript consists of two parts. In the first part of this thesis we analyse a local\\--global problem for elliptic curves over number fields. Let $E$ be an elliptic curve over a

  5. A universal multilingual weightless neural network tagger via quantitative linguistics.

    Science.gov (United States)

    Carneiro, Hugo C C; Pedreira, Carlos E; França, Felipe M G; Lima, Priscila M V

    2017-07-01

    In the last decade, given the availability of corpora in several distinct languages, research on multilingual part-of-speech tagging started to grow. Amongst the novelties there is mWANN-Tagger (multilingual weightless artificial neural network tagger), a weightless neural part-of-speech tagger capable of being used for mostly-suffix-oriented languages. The tagger was subjected to corpora in eight languages of quite distinct natures and had a remarkable accuracy with very low sample deviation in every one of them, indicating the robustness of weightless neural systems for part-of-speech tagging tasks. However, mWANN-Tagger needed to be tuned for every new corpus, since each one required a different parameter configuration. For mWANN-Tagger to be truly multilingual, it should be usable for any new language with no need of parameter tuning. This article proposes a study that aims to find a relation between the lexical diversity of a language and the parameter configuration that would produce the best performing mWANN-Tagger instance. Preliminary analyses suggested that a single parameter configuration may be applied to the eight aforementioned languages. The mWANN-Tagger instance produced by this configuration was as accurate as the language-dependent ones obtained through tuning. Afterwards, the weightless neural tagger was further subjected to new corpora in languages that range from very isolating to polysynthetic ones. The best performing instances of mWANN-Tagger are again the ones produced by the universal parameter configuration. Hence, mWANN-Tagger can be applied to new corpora with no need of parameter tuning, making it a universal multilingual part-of-speech tagger. Further experiments with Universal Dependencies treebanks reveal that mWANN-Tagger may be extended and that it has potential to outperform most state-of-the-art part-of-speech taggers if better word representations are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Social influence modulates the neural computation of value.

    Science.gov (United States)

    Zaki, Jamil; Schirmer, Jessica; Mitchell, Jason P

    2011-07-01

    Social influence--individuals' tendency to conform to the beliefs and attitudes of others--has interested psychologists for decades. However, it has traditionally been difficult to distinguish true modification of attitudes from mere public compliance with social norms; this study addressed this challenge using functional neuroimaging. Participants rated the attractiveness of faces and subsequently learned how their peers ostensibly rated each face. Participants were then scanned using functional MRI while they rated each face a second time. The second ratings were influenced by social norms: Participants changed their ratings to conform to those of their peers. This social influence was accompanied by modulated engagement of two brain regions associated with coding subjective value--the nucleus accumbens and orbitofrontal cortex--a finding suggesting that exposure to social norms affected participants' neural representations of value assigned to stimuli. These findings document the utility of neuroimaging to demonstrate the private acceptance of social norms.

  7. The extraction of information and knowledge from trained neural networks.

    Science.gov (United States)

    Livingstone, David J; Browne, Antony; Crichton, Raymond; Hudson, Brian D; Whitley, David C; Ford, Martyn G

    2008-01-01

    In the past, neural networks were viewed as classification and regression systems whose internal representations were incomprehensible. It is now becoming apparent that algorithms can be designed that extract comprehensible representations from trained neural networks, enabling them to be used for data mining and knowledge discovery, that is, the discovery and explanation of previously unknown relationships present in data. This chapter reviews existing algorithms for extracting comprehensible representations from neural networks and outlines research to generalize and extend the capabilities of one of these algorithms, TREPAN. This algorithm has been generalized for application to bioinformatics data sets, including the prediction of splice junctions in human DNA sequences, and cheminformatics. The results generated on these data sets are compared with those generated by a conventional data mining technique (C5) and appropriate conclusions are drawn.

  8. Usage of semantic representations in recognition memory.

    Science.gov (United States)

    Nishiyama, Ryoji; Hirano, Tetsuji; Ukita, Jun

    2017-11-01

    Meanings of words facilitate false acceptance as well as correct rejection of lures in recognition memory tests, depending on the experimental context. This suggests that semantic representations are both directly and indirectly (i.e., mediated by perceptual representations) used in remembering. Studies using memory conjunction errors (MCEs) paradigms, in which the lures consist of component parts of studied words, have reported semantic facilitation of rejection of the lures. However, attending to components of the lures could potentially cause this. Therefore, we investigated whether semantic overlap of lures facilitates MCEs using Japanese Kanji words in which a whole-word image is more concerned in reading. Experiments demonstrated semantic facilitation of MCEs in a delayed recognition test (Experiment 1), and in immediate recognition tests in which participants were prevented from using phonological or orthographic representations (Experiment 2), and the salient effect on individuals with high semantic memory capacities (Experiment 3). Additionally, analysis of the receiver operating characteristic suggested that this effect is attributed to familiarity-based memory judgement and phantom recollection. These findings indicate that semantic representations can be directly used in remembering, even when perceptual representations of studied words are available.

  9. The hippocampus and exploration: dynamically evolving behavior and neural representations

    Directory of Open Access Journals (Sweden)

    Adam eJohnson

    2012-07-01

    Full Text Available We develop a normative statistical approach to exploratory behavior called information foraging. Information foraging highlights the specific processes that contribute to active, rather than passive, exploration and learning. We hypothesize that the hippocampus plays a critical role in active exploration through directed information foraging by supporting a set of processes that allow an individual to determine where to sample. By examining these processes, we show how information directed information foraging provides a formal theoretical explanation for the common hippocampal substrates of constructive memory, vicarious trial and error behavior, schema-based facilitation of memory performance, and memory consolidation.

  10. The neural basis of individual face and object representation

    Directory of Open Access Journals (Sweden)

    Rebecca eWatson

    2016-03-01

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

  11. Neural representation of expected value in the adolescent brain

    OpenAIRE

    Barkley-Levenson, Emily; Galván, Adriana

    2014-01-01

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

  12. Neural representation of the sensorimotor speech-action-repository

    OpenAIRE

    Eckers, Cornelia; Kröger, Bernd J.; Sass, Katharina; Heim, Stefan

    2013-01-01

    A speech–action-repository (SAR) or “mental syllabary” has been proposed as a central module for sensorimotor processing of syllables. In this approach, syllables occurring frequently within language are assumed to be stored as holistic sensorimotor patterns, while non-frequent syllables need to be assembled from sub-syllabic units. Thus, frequent syllables are processed efficiently and quickly during production or perception by a direct activation of their sensorimotor patterns. Whereas seve...

  13. Representation in natural and artificial agents: an embodied cognitive science perspective.

    Science.gov (United States)

    Pfeifer, R; Scheier, C

    1998-01-01

    The goal of the present paper is to provide an embodied cognitive science view on representation. Using the fundamental task of category learning, we will demonstrate that this perspective enables us to shed new light on many pertinent issues and opens up new prospects for investigation. The main focus of this paper is on the prerequisites to acquire representations of objects in the real world. We suggest that the main prerequisite is embodiment which allows an agent--human, animal or robot--to manipulate its sensory input such that invariances are generated. These invariances, in turn, are the basis of representation formation. In other words, the paper does not focus on representations per se, but rather discusses the various processes involved in order to make learning and representation acquisition possible. The argument structure is as follows. First we introduce two new perspectives on representation, namely frame-of-reference, and complete agent. Then we elaborate the complete agent perspective and focus in particular on embodiment and situatedness. We argue that embodiment has two main aspects, a dynamic and an information theoretic one. Focusing on the latter, there are a number of implications: Representation can only be understood if the embedding of the neural substrate in the physical agent is known, which includes morphology (shape), positioning and nature of sensors. Because an autonomous mobile agent in the real world is exposed to a continuously changing high-dimensional stream of sensory stimulation, if it is to learn category distinctions, it first needs a focus of attention mechanism, and then it must have a way to reduce the dimensionality of this high-dimensional sensory stream. Learning is very hard because the invariances are typically not found in the sensory data directly--the classical problem of object constancy: it is a so-called type 2 problem. Rather than trying to improve the learning algorithms--which is the standard approach

  14. Deep Direct Reinforcement Learning for Financial Signal Representation and Trading.

    Science.gov (United States)

    Deng, Yue; Bao, Feng; Kong, Youyong; Ren, Zhiquan; Dai, Qionghai

    2017-03-01

    Can we train the computer to beat experienced traders for financial assert trading? In this paper, we try to address this challenge by introducing a recurrent deep neural network (NN) for real-time financial signal representation and trading. Our model is inspired by two biological-related learning concepts of deep learning (DL) and reinforcement learning (RL). In the framework, the DL part automatically senses the dynamic market condition for informative feature learning. Then, the RL module interacts with deep representations and makes trading decisions to accumulate the ultimate rewards in an unknown environment. The learning system is implemented in a complex NN that exhibits both the deep and recurrent structures. Hence, we propose a task-aware backpropagation through time method to cope with the gradient vanishing issue in deep training. The robustness of the neural system is verified on both the stock and the commodity future markets under broad testing conditions.

  15. Beyond slots and resources: grounding cognitive concepts in neural dynamics.

    Science.gov (United States)

    Johnson, Jeffrey S; Simmering, Vanessa R; Buss, Aaron T

    2014-08-01

    Research over the past decade has suggested that the ability to hold information in visual working memory (VWM) may be limited to as few as three to four items. However, the precise nature and source of these capacity limits remains hotly debated. Most commonly, capacity limits have been inferred from studies of visual change detection, in which performance declines systematically as a function of the number of items that participants must remember. According to one view, such declines indicate that a limited number of fixed-resolution representations are held in independent memory "slots." Another view suggests that such capacity limits are more apparent than real, but emerge as limited memory resources are distributed across more to-be-remembered items. Here we argue that, although both perspectives have merit and have generated and explained impressive amounts of empirical data, their central focus on the representations--rather than processes--underlying VWM may ultimately limit continuing progress in this area. As an alternative, we describe a neurally grounded, process-based approach to VWM: the dynamic field theory. Simulations demonstrate that this model can account for key aspects of behavioral performance in change detection, in addition to generating novel behavioral predictions that have been confirmed experimentally. Furthermore, we describe extensions of the model to recall tasks, the integration of visual features, cognitive development, individual differences, and functional imaging studies of VWM. We conclude by discussing the importance of grounding psychological concepts in neural dynamics, as a first step toward understanding the link between brain and behavior.

  16. Psychological and neural mechanisms of experimental extinction: a selective review.

    Science.gov (United States)

    Delamater, Andrew R; Westbrook, R Frederick

    2014-02-01

    The present review examines key psychological concepts in the study of experimental extinction and implications these have for an understanding of the underlying neurobiology of extinction learning. We suggest that many of the signature characteristics of extinction learning (spontaneous recovery, renewal, reinstatement, rapid reacquisition) can be accommodated by the standard associative learning theory assumption that extinction results in partial erasure of the original learning together with new inhibitory learning. Moreover, we consider recent behavioral and neural evidence that supports the partial erasure view of extinction, but also note shortcomings in our understanding of extinction circuits as these relate to the negative prediction error concept. Recent work suggests that common prediction error and stimulus-specific prediction error terms both may be required to explain neural plasticity both in acquisition and extinction learning. In addition, we suggest that many issues in the content of extinction learning have not been fully addressed in current research, but that neurobiological approaches should be especially helpful in addressing such issues. These include questions about the nature of extinction learning (excitatory CS-No US, inhibitory CS-US learning, occasion setting processes), especially as this relates to studies of the micro-circuitry of extinction, as well as its representational content (sensory, motivational, response). An additional understudied problem in extinction research is the role played by attention processes and their underlying neural networks, although some research and theory converge on the idea that extinction is accompanied by attention decrements (i.e., habituation-like processes). Copyright © 2013 Elsevier Inc. All rights reserved.

  17. Neural Tube Defects

    Science.gov (United States)

    ... vitamin, before and during pregnancy prevents most neural tube defects. Neural tube defects are usually diagnosed before the infant is ... or imaging tests. There is no cure for neural tube defects. The nerve damage and loss of function ...

  18. Self-Taught convolutional neural networks for short text clustering.

    Science.gov (United States)

    Xu, Jiaming; Xu, Bo; Wang, Peng; Zheng, Suncong; Tian, Guanhua; Zhao, Jun; Xu, Bo

    2017-04-01

    Short text clustering is a challenging problem due to its sparseness of text representation. Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC(2)), which can flexibly and successfully incorporate more useful semantic features and learn non-biased deep text representation in an unsupervised manner. In our framework, the original raw text features are firstly embedded into compact binary codes by using one existing unsupervised dimensionality reduction method. Then, word embeddings are explored and fed into convolutional neural networks to learn deep feature representations, meanwhile the output units are used to fit the pre-trained binary codes in the training process. Finally, we get the optimal clusters by employing K-means to cluster the learned representations. Extensive experimental results demonstrate that the proposed framework is effective, flexible and outperform several popular clustering methods when tested on three public short text datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Deepening sleep by hypnotic suggestion.

    Science.gov (United States)

    Cordi, Maren J; Schlarb, Angelika A; Rasch, Björn

    2014-06-01

    Slow wave sleep (SWS) plays a critical role in body restoration and promotes brain plasticity; however, it markedly declines across the lifespan. Despite its importance, effective tools to increase SWS are rare. Here we tested whether a hypnotic suggestion to "sleep deeper" extends the amount of SWS. Within-subject, placebo-controlled crossover design. Sleep laboratory at the University of Zurich, Switzerland. Seventy healthy females 23.27 ± 3.17 y. Participants listened to an auditory text with hypnotic suggestions or a control tape before napping for 90 min while high-density electroencephalography was recorded. After participants listened to the hypnotic suggestion to "sleep deeper" subsequent SWS was increased by 81% and time spent awake was reduced by 67% (with the amount of SWS or wake in the control condition set to 100%). Other sleep stages remained unaffected. Additionally, slow wave activity was significantly enhanced after hypnotic suggestions. During the hypnotic tape, parietal theta power increases predicted the hypnosis-induced extension of SWS. Additional experiments confirmed that the beneficial effect of hypnotic suggestions on SWS was specific to the hypnotic suggestion and did not occur in low suggestible participants. Our results demonstrate the effectiveness of hypnotic suggestions to specifically increase the amount and duration of slow wave sleep (SWS) in a midday nap using objective measures of sleep in young, healthy, suggestible females. Hypnotic suggestions might be a successful tool with a lower risk of adverse side effects than pharmacological treatments to extend SWS also in clinical and elderly populations.

  20. Initialization of multilayer forecasting artifical neural networks

    OpenAIRE

    Bochkarev, Vladimir V.; Maslennikova, Yulia S.

    2014-01-01

    In this paper, a new method was developed for initialising artificial neural networks predicting dynamics of time series. Initial weighting coefficients were determined for neurons analogously to the case of a linear prediction filter. Moreover, to improve the accuracy of the initialization method for a multilayer neural network, some variants of decomposition of the transformation matrix corresponding to the linear prediction filter were suggested. The efficiency of the proposed neural netwo...

  1. Texture Based Image Analysis With Neural Nets

    Science.gov (United States)

    Ilovici, Irina S.; Ong, Hoo-Tee; Ostrander, Kim E.

    1990-03-01

    In this paper, we combine direct image statistics and spatial frequency domain techniques with a neural net model to analyze texture based images. The resultant optimal texture features obtained from the direct and transformed image form the exemplar pattern of the neural net. The proposed approach introduces an automated texture analysis applied to metallography for determining the cooling rate and mechanical working of the materials. The results suggest that the proposed method enhances the practical applications of neural nets and texture extraction features.

  2. Efficient Representation of Timed UML 2 Interactions

    DEFF Research Database (Denmark)

    Knapp, Alexander; Störrle, Harald

    2014-01-01

    UML 2 interactions describe system behavior over time in a declarative way. The standard approach to defining their formal semantics enumerates traces of events; other representation formats, like Büchi automata or prime event structures, have been suggested, too. We describe another, more succinct...

  3. Realizations of the canonical representation

    Indian Academy of Sciences (India)

    A characterisation of the maximal abelian subalgebras of the bounded operators on Hilbert space that are normalised by the canonical representation of the Heisenberg group is given. This is used to classify the perfect realizations of the canonical representation.

  4. Minority Representation, Empowerment, and Participation

    NARCIS (Netherlands)

    Banducci, S.A.; Donovan, Todd; Karp, J.A.

    2004-01-01

    According to the minority empowerment thesis, minority representation strengthens representational links, fosters more positive attitudes toward government, and encourages political participation. We examine this theory from a cross-national perspective, making use of surveys that sampled minorities

  5. Topographical representation of odor hedonics in the olfactory bulb.

    Science.gov (United States)

    Kermen, Florence; Midroit, Maëllie; Kuczewski, Nicola; Forest, Jérémy; Thévenet, Marc; Sacquet, Joëlle; Benetollo, Claire; Richard, Marion; Didier, Anne; Mandairon, Nathalie

    2016-07-01

    Hedonic value is a dominant aspect of olfactory perception. Using optogenetic manipulation in freely behaving mice paired with immediate early gene mapping, we demonstrate that hedonic information is represented along the antero-posterior axis of the ventral olfactory bulb. Using this representation, we show that the degree of attractiveness of odors can be bidirectionally modulated by local manipulation of the olfactory bulb's neural networks in freely behaving mice.

  6. Experience with adults shapes multisensory representation of social familiarity in the brain of a songbird.

    Directory of Open Access Journals (Sweden)

    Isabelle George

    Full Text Available Social animals learn to perceive their social environment, and their social skills and preferences are thought to emerge from greater exposure to and hence familiarity with some social signals rather than others. Familiarity appears to be tightly linked to multisensory integration. The ability to differentiate and categorize familiar and unfamiliar individuals and to build a multisensory representation of known individuals emerges from successive social interactions, in particular with adult, experienced models. In different species, adults have been shown to shape the social behavior of young by promoting selective attention to multisensory cues. The question of what representation of known conspecifics adult-deprived animals may build therefore arises. Here we show that starlings raised with no experience with adults fail to develop a multisensory representation of familiar and unfamiliar starlings. Electrophysiological recordings of neuronal activity throughout the primary auditory area of these birds, while they were exposed to audio-only or audiovisual familiar and unfamiliar cues, showed that visual stimuli did, as in wild-caught starlings, modulate auditory responses but that, unlike what was observed in wild-caught birds, this modulation was not influenced by familiarity. Thus, adult-deprived starlings seem to fail to discriminate between familiar and unfamiliar individuals. This suggests that adults may shape multisensory representation of known individuals in the brain, possibly by focusing the young's attention on relevant, multisensory cues. Multisensory stimulation by experienced, adult models may thus be ubiquitously important for the development of social skills (and of the neural properties underlying such skills in a variety of species.

  7. Infants' somatotopic neural responses to seeing human actions: I've got you under my skin.

    Directory of Open Access Journals (Sweden)

    Joni N Saby

    Full Text Available Human infants rapidly learn new skills and customs via imitation, but the neural linkages between action perception and production are not well understood. Neuroscience studies in adults suggest that a key component of imitation-identifying the corresponding body part used in the acts of self and other-has an organized neural signature. In adults, perceiving someone using a specific body part (e.g., hand vs. foot is associated with activation of the corresponding area of the sensory and/or motor strip in the observer's brain-a phenomenon called neural somatotopy. Here we examine whether preverbal infants also exhibit somatotopic neural responses during the observation of others' actions. 14-month-old infants were randomly assigned to watch an adult reach towards and touch an object using either her hand or her foot. The scalp electroencephalogram (EEG was recorded and event-related changes in the sensorimotor mu rhythm were analyzed. Mu rhythm desynchronization was greater over hand areas of sensorimotor cortex during observation of hand actions and was greater over the foot area for observation of foot actions. This provides the first evidence that infants' observation of someone else using a particular body part activates the corresponding areas of sensorimotor cortex. We hypothesize that this somatotopic organization in the developing brain supports imitation and cultural learning. The findings connect developmental cognitive neuroscience, adult neuroscience, action representation, and behavioral imitation.

  8. A Drone Remote Sensing for Virtual Reality Simulation System for Forest Fires: Semantic Neural Network Approach

    Science.gov (United States)

    Narasimha Rao, Gudikandhula; Jagadeeswara Rao, Peddada; Duvvuru, Rajesh

    2016-09-01

    Wild fires have significant impact on atmosphere and lives. The demand of predicting exact fire area in forest may help fire management team by using drone as a robot. These are flexible, inexpensive and elevated-motion remote sensing systems that use drones as platforms are important for substantial data gaps and supplementing the capabilities of manned aircraft and satellite remote sensing systems. In addition, powerful computational tools are essential for predicting certain burned area in the duration of a forest fire. The reason of this study is to built up a smart system based on semantic neural networking for the forecast of burned areas. The usage of virtual reality simulator is used to support the instruction process of fire fighters and all users for saving of surrounded wild lives by using a naive method Semantic Neural Network System (SNNS). Semantics are valuable initially to have a enhanced representation of the burned area prediction and better alteration of simulation situation to the users. In meticulous, consequences obtained with geometric semantic neural networking is extensively superior to other methods. This learning suggests that deeper investigation of neural networking in the field of forest fires prediction could be productive.

  9. Harmonic Analysis and Group Representation

    CERN Document Server

    Figa-Talamanca, Alessandro

    2011-01-01

    This title includes: Lectures - A. Auslander, R. Tolimeri - Nilpotent groups and abelian varieties, M Cowling - Unitary and uniformly bounded representations of some simple Lie groups, M. Duflo - Construction de representations unitaires d'un groupe de Lie, R. Howe - On a notion of rank for unitary representations of the classical groups, V.S. Varadarajan - Eigenfunction expansions of semisimple Lie groups, and R. Zimmer - Ergodic theory, group representations and rigidity; and, Seminars - A. Koranyi - Some applications of Gelfand pairs in classical analysis.

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

    Directory of Open Access Journals (Sweden)

    Géraldine Rauchs

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

  11. Spikes not slots: noise in neural populations limits working memory.

    Science.gov (United States)

    Bays, Paul M

    2015-08-01

    This opinion article argues that noise (randomness) in neural activity is the limiting factor in visual working memory (WM), determining how accurately we can maintain stable internal representations of external stimuli. Sharing of a fixed amount of neural activity between items in memory explains why WM can be successfully described as a continuous resource. This contrasts with the popular conception of WM as comprising a limited number of memory slots, each holding a representation of one stimulus - I argue that this view is challenged by computational theory and the latest neurophysiological evidence. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Constructing visual representations

    DEFF Research Database (Denmark)

    Huron, Samuel; Jansen, Yvonne; Carpendale, Sheelagh

    2014-01-01

    The accessibility of infovis authoring tools to a wide audience has been identified as a major research challenge. A key task in the authoring process is the development of visual mappings. While the infovis community has long been deeply interested in finding effective visual mappings......, comparatively little attention has been placed on how people construct visual mappings. In this paper, we present the results of a study designed to shed light on how people transform data into visual representations. We asked people to create, update and explain their own information visualizations using only...... tangible building blocks. We learned that all participants, most of whom had little experience in visualization authoring, were readily able to create and talk about their own visualizations. Based on our observations, we discuss participants’ actions during the development of their visual representations...

  13. Lexical and syntactic representations in the brain: An fMRI investigation with multi-voxel pattern analyses

    Science.gov (United States)

    Fedorenko, Evelina; Nieto-Castañon, Alfonso; Kanwisher, Nancy

    2011-01-01

    Work in theoretical linguistics and psycholinguistics suggests that human linguistic knowledge forms a continuum between individual lexical items and abstract syntactic representations, with most linguistic representations falling between the two extremes and taking the form of lexical items stored together with the syntactic/semantic contexts in which they frequently occur. Neuroimaging evidence further suggests that no brain region is selectively sensitive to only lexical information or only syntactic information. Instead, all the key brain regions that support high-level linguistic processing have been implicated in both lexical and syntactic processing, suggesting that our linguistic knowledge is plausibly represented in a distributed fashion in these brain regions. Given this distributed nature of linguistic representations, multi-voxel pattern analyses (MVPAs) can help uncover important functional properties of the language system. In the current study we use MVPAs to ask two questions: 1) Do language brain regions differ in how robustly they represent lexical vs. syntactic information?; and 2) Do any of the language bran regions distinguish between “pure” lexical information (lists of words) and “pure” abstract syntactic information (jabberwocky sentences) in the pattern of activity? We show that lexical information is represented more robustly than syntactic information across many language regions (with no language region showing the opposite pattern), as evidenced by a better discrimination between conditions that differ along the lexical dimension (sentences vs. jabberwocky, and word lists vs. nonword lists) than between conditions that differ along the syntactic dimension (sentences vs. word lists, and jabberwocky vs. nonword lists). This result suggests that lexical information may play a more critical role than syntax in the representation of linguistic meaning. We also show that several language regions reliably discriminate between

  14. Political Representation in Africa: Towards a Conceptual Framework ...

    African Journals Online (AJOL)

    Political representation as a central component of democratic governance is a key challenge in the African quest for democratic development. Accordingly, this article reviews theories of political representation. On the basis of the review and subsequent critique of existing theories, I suggest some areas that require attention ...

  15. Communication Relationships, Conventions of Meaning, and Social Representations.

    Science.gov (United States)

    Ritchie, David

    The concept of social representations, which was developed by Moscovici in 1984, suggests new ways of understanding the social processes that underlie communication between individuals. A social representation is a set of concepts, statements, and explanations originating in daily life in the course of inter-individual communication. The purpose…

  16. Elderly listeners with low intelligibility scores under reverberation show degraded subcortical representation of reverberant speech.

    Science.gov (United States)

    Fujihira, H; Shiraishi, K; Remijn, G B

    2017-01-10

    In order to elucidate why many elderly listeners have difficulty understanding speech under reverberation, we investigated the relationship between word intelligibility and auditory brainstem responses (ABRs) in 28 elderly listeners. We hypothesized that the elderly listeners with low word intelligibility scores under reverberation would show degraded subcortical encoding information of reverberant speech as expressed in their ABRs towards a reverberant /da/ syllable. The participants were divided into two groups (top and bottom performance groups) according to their word intelligibility scores for anechoic and reverberant words, and ABR characteristics between groups were compared. We found that correlation coefficients between responses to anechoic and reverberant /da/ were lower in the bottom performance group than in the top performance group. This result suggests that degraded neural representation toward information of reverberant speech may account for lower intelligibility of reverberant speech in elderly listeners. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  17. Data Representation, Coding, and Communication Standards.

    Science.gov (United States)

    Amin, Milon; Dhir, Rajiv

    2015-06-01

    The immense volume of cases signed out by surgical pathologists on a daily basis gives little time to think about exactly how data are stored. An understanding of the basics of data representation has implications that affect a pathologist's daily practice. This article covers the basics of data representation and its importance in the design of electronic medical record systems. Coding in surgical pathology is also discussed. Finally, a summary of communication standards in surgical pathology is presented, including suggested resources that establish standards for select aspects of pathology reporting. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Valensbaserad semantisk representation

    OpenAIRE

    Lönngren, Lennart

    2010-01-01

    This is a brief outline of a semantic representation of linguistic objects in Russian—words, phrases, sentences—based on the concept of valency. Valency is explored as a property of all kinds of linguistic signs: words, parts of words, signs with non-phonological expression, and completely implicit signs. An important distinction is made between semantic and syntactic signs, and amongst semantic signs between signs with and without valency (signs denoting "facts" versus signs denoting "things...

  19. Representation of Knowledge

    Science.gov (United States)

    1980-03-01

    methodology involves the design of programs that exhibit Intelligent behavior, Al researchers have often taken a rather pragmatic approach to the subject...This article has not been about representation formalisms per se, but rather about the pragmatics of epistemology, the study of the nature of knowledge...1977. Levels of complexity In discourse for anaphora disambiguation and speech act interpretation. IJCAI 3, 43-49. Carbonell, J. R. 1970. Al in CAI: An

  20. Non-Representational Theory

    DEFF Research Database (Denmark)

    Jensen, Ole B.

    2016-01-01

    Dette kapitel gennemgår den såkaldte ”Non-Representational Theory” (NRT), der primært er kendt fra den Angelsaksiske humangeografi, og som særligt er blevet fremført af den engelske geograf Nigel Thrift siden midten af 2000 årtiet. Da positionen ikke kan siges at være specielt homogen vil kapitlet...

  1. The Knowledge Representation Project

    Science.gov (United States)

    1989-07-01

    representing k nowledge. I,- ONE was designed to represent the kinds of knowlodge constriicts encountered by developers of natural language processing systems...project called Empirically Valid Knowledge Representation in 1986. One of the first tasks of the new project was to translate NIKL into Common LISP -- a...constraints -- the syntactic structures that appear in LOO% :constraints or implies clauses translate into knowledge structures for which we have

  2. Learning Multisensory Representations

    Science.gov (United States)

    2016-05-23

    how the use of these representations influences perceptual judgements and decision making. The program focuses on people’s performances in visual ...organization of visual short-term memory . Psychological Review, 120, 297-328. Yildirim, I. & Jacobs, R. A. (2013). Transfer of object category...in visual short-term memory research. Attention, Perception, & Psychophysics, 76, 2158-2170. Orhan, A. E., Sims, C. R., Jacobs, R. A., & Knill, D. C

  3. Representations of orthogonal polynomials

    OpenAIRE

    Koepf, Wolfram; Schmersau, Dieter

    1998-01-01

    Zeilberger's algorithm provides a method to compute recurrence and differential equations from given hypergeometric series representations, and an adaption of Almquist and Zeilberger computes recurrence and differential equations for hyperexponential integrals. Further versions of this algorithm allow the computation of recurrence and differential equations from Rodrigues type formulas and from generating functions. In particular, these algorithms can be used to compute the differential/diffe...

  4. Deepening Sleep by Hypnotic Suggestion

    Science.gov (United States)

    Cordi, Maren J.; Schlarb, Angelika A.; Rasch, Björn

    2014-01-01

    Study Objectives: Slow wave sleep (SWS) plays a critical role in body restoration and promotes brain plasticity; however, it markedly declines across the lifespan. Despite its importance, effective tools to increase SWS are rare. Here we tested whether a hypnotic suggestion to “sleep deeper” extends the amount of SWS. Design: Within-subject, placebo-controlled crossover design. Setting: Sleep laboratory at the University of Zurich, Switzerland. Participants: Seventy healthy females 23.27 ± 3.17 y. Intervention: Participants listened to an auditory text with hypnotic suggestions or a control tape before napping for 90 min while high-density electroencephalography was recorded. Measurements and Results: After participants listened to the hypnotic suggestion to “sleep deeper” subsequent SWS was increased by 81% and time spent awake was reduced by 67% (with the amount of SWS or wake in the control condition set to 100%). Other sleep stages remained unaffected. Additionally, slow wave activity was significantly enhanced after hypnotic suggestions. During the hypnotic tape, parietal theta power increases predicted the hypnosis-induced extension of SWS. Additional experiments confirmed that the beneficial effect of hypnotic suggestions on SWS was specific to the hypnotic suggestion and did not occur in low suggestible participants. Conclusions: Our results demonstrate the effectiveness of hypnotic suggestions to specifically increase the amount and duration of slow wave sleep (SWS) in a midday nap using objective measures of sleep in young, healthy, suggestible females. Hypnotic suggestions might be a successful tool with a lower risk of adverse side effects than pharmacological treatments to extend SWS also in clinical and elderly populations. Citation: Cordi MJ, Schlarb AA, Rasch B. Deepening sleep by hypnotic suggestion. SLEEP 2014;37(6):1143-1152. PMID:24882909

  5. Translation between representation languages

    Science.gov (United States)

    Vanbaalen, Jeffrey

    1994-01-01

    A capability for translating between representation languages is critical for effective knowledge base reuse. A translation technology for knowledge representation languages based on the use of an interlingua for communicating knowledge is described. The interlingua-based translation process consists of three major steps: translation from the source language into a subset of the interlingua, translation between subsets of the interlingua, and translation from a subset of the interlingua into the target language. The first translation step into the interlingua can typically be specified in the form of a grammar that describes how each top-level form in the source language translates into the interlingua. In cases where the source language does not have a declarative semantics, such a grammar is also a specification of a declarative semantics for the language. A methodology for building translators that is currently under development is described. A 'translator shell' based on this methodology is also under development. The shell has been used to build translators for multiple representation languages and those translators have successfully translated nontrivial knowledge bases.

  6. Pioneers of representation theory

    CERN Document Server

    Curtis, Charles W

    1999-01-01

    The year 1897 was marked by two important mathematical events: the publication of the first paper on representations of finite groups by Ferdinand Georg Frobenius (1849-1917) and the appearance of the first treatise in English on the theory of finite groups by William Burnside (1852-1927). Burnside soon developed his own approach to representations of finite groups. In the next few years, working independently, Frobenius and Burnside explored the new subject and its applications to finite group theory. They were soon joined in this enterprise by Issai Schur (1875-1941) and some years later, by Richard Brauer (1901-1977). These mathematicians' pioneering research is the subject of this book. It presents an account of the early history of representation theory through an analysis of the published work of the principals and others with whom the principals' work was interwoven. Also included are biographical sketches and enough mathematics to enable readers to follow the development of the subject. An introductor...

  7. Representation Learning Based Speech Assistive System for Persons With Dysarthria.

    Science.gov (United States)

    Chandrakala, S; Rajeswari, Natarajan

    2017-09-01

    An assistive system for persons with vocal impairment due to dysarthria converts dysarthric speech to normal speech or text. Because of the articulatory deficits, dysarthric speech recognition needs a robust learning technique. Representation learning is significant for complex tasks such as dysarthric speech recognition. We focus on robust representation for dysarthric speech recognition that involves recognizing sequential patterns of varying length utterances. We propose a hybrid framework that uses a generative learning based data representation with a discriminative learning based classifier. In this hybrid framework, we propose to use Example Specific Hidden Markov Models (ESHMMs) to obtain log-likelihood scores for a dysarthric speech utterance to form fixed dimensional score vector representation. This representation is used as an input to discriminative classifier such as support vector machine.The performance of the proposed approach is evaluatedusingUA-Speechdatabase.The recognitionaccuracy is much better than the conventional hidden Markov model based approach and Deep Neural Network-Hidden Markov Model (DNN-HMM). The efficiency of the discriminative nature of score vector representation is proved for "very low" intelligibility words.

  8. Neural Networks as a Tool for Georadar Data Processing

    Directory of Open Access Journals (Sweden)

    Szymczyk Piotr

    2015-12-01

    Full Text Available In this article a new neural network based method for automatic classification of ground penetrating radar (GPR traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.

  9. Neural networks for relational learning: An experimental comparison

    OpenAIRE

    Uwents, Werner; Monfardini, Gabriele; Blockeel, Hendrik; Gori, Marco De; Scarselli, Franco

    2011-01-01

    In the last decade, connectionist models have been proposed that can process structured information directly. These methods, which are based on the use of graphs for the representation of the data and the relationships within the data, are particularly suitable for handling relational learning tasks. In this paper, two recently proposed architectures of this kind, i.e. Graph Neural Networks (GNNs) and Relational Neural Networks (RelNNs), are compared and discussed, along with their correspond...

  10. Response of neural reward regions to food cues in autism spectrum disorders

    Directory of Open Access Journals (Sweden)

    Cascio Carissa J

    2012-05-01

    Full Text Available Abstract Background One hypothesis for the social deficits that characterize autism spectrum disorders (ASD is diminished neural reward response to social interaction and attachment. Prior research using established monetary reward paradigms as a test of non-social reward to compare with social reward may involve confounds in the ability of individuals with ASD to utilize symbolic representation of money and the abstraction required to interpret monetary gains. Thus, a useful addition to our understanding of neural reward circuitry in ASD includes a characterization of the neural response to primary rewards. Method We asked 17 children with ASD and 18 children without ASD to abstain from eating for at least four hours before an MRI scan in which they viewed images of high-calorie foods. We assessed the neural reward network for increases in the blood oxygenation level dependent (BOLD signal in response to the food images Results We found very similar patterns of increased BOLD signal to these images in the two groups; both groups showed increased BOLD signal in the bilateral amygdala, as well as in the nucleus accumbens, orbitofrontal cortex, and insula. Direct group comparisons revealed that the ASD group showed a stronger response to food cues in bilateral insula along the anterior-posterior gradient and in the anterior cingulate cortex than the control group, whereas there were no neural reward regions that showed higher activation for controls than for ASD. Conclusion These results suggest that neural response to primary rewards is not diminished but in fact shows an aberrant enhancement in children with ASD.

  11. Asymmetric translation between multiple representations in chemistry

    Science.gov (United States)

    Lin, Yulan I.; Son, Ji Y.; Rudd, James A., II

    2016-03-01

    Experts are more proficient in manipulating and translating between multiple representations (MRs) of a given concept than novices. Studies have shown that instruction using MR can increase student understanding of MR, and one model for MR instruction in chemistry is the chemistry triplet proposed by Johnstone. Concreteness fading theory suggests that presenting concrete representations before abstract representations can increase the effectiveness of MR instruction; however, little work has been conducted on varying the order of different representations during instruction and the role of concreteness in assessment. In this study, we investigated the application of concreteness fading to MR instruction and assessment in teaching chemistry. In two experiments, undergraduate students in either introductory psychology courses or general chemistry courses were given MR instruction on phase changes using different orders of presentation and MR assessment questions based on the representations in the chemistry triplet. Our findings indicate that the order of presentation based on levels of concreteness in MR chemistry instruction is less important than implementation of comprehensive MR assessments. Even after MR instruction, students display an asymmetric understanding of the chemical phenomenon on the MR assessments. Greater emphasis on MR assessments may be an important component in MR instruction that effectively moves novices toward more expert MR understanding.

  12. Designing and evaluating representations to model pedagogy

    Directory of Open Access Journals (Sweden)

    Elizabeth Masterman

    2013-08-01

    Full Text Available This article presents the case for a theory-informed approach to designing and evaluating representations for implementation in digital tools to support Learning Design, using the framework of epistemic efficacy as an example. This framework, which is rooted in the literature of cognitive psychology, is operationalised through dimensions of fit that attend to: (1 the underlying ontology of the domain, (2 the purpose of the task that the representation is intended to facilitate, (3 how best to support the cognitive processes of the users of the representations, (4 users’ differing needs and preferences, and (5 the tool and environment in which the representations are constructed and manipulated.Through showing how epistemic efficacy can be applied to the design and evaluation of representations, the article presents the Learning Designer, a constructionist microworld in which teachers can both assemble their learning designs and model their pedagogy in terms of students’ potential learning experience. Although the activity of modelling may add to the cognitive task of design, the article suggests that the insights thereby gained can additionally help a lecturer who wishes to reuse a particular learning design to make informed decisions about its value to their practice.

  13. Cognitive representation of orientation: a case study.

    Science.gov (United States)

    Valtonen, Jussi; Dilks, Daniel D; McCloskey, Michael

    2008-10-01

    Although object orientation in the human brain has been discussed extensively in the literature, the nature of the underlying cognitive representation(s) remains uncertain. We investigated orientation perception in BC, a patient with bilateral occipital and parietal damage from a herpes encephalitis infection. Our results show that in addition to general inaccuracy in discriminating and reproducing line orientations, her errors take the form of left-right mirror reflections across a vertical coordinate axis. We propose that in BC, the cognitive impairment is in failing to represent the direction of tilt for line orientations. Our results suggest that there exists a level of representation in the human brain at which line orientations are represented compositionally, such that the direction of a line orientation's tilt from a vertical mental reference meridian is coded independently of the magnitude of its angular displacement. Reflection errors across a vertical axis were observed both in visual and tactile line orientation tasks, demonstrating that these errors arise at a supra-modal level of representation not restricted to vision, or, alternatively, that visual-like representations are being constructed from the tactile input.

  14. Multilayer Extreme Learning Machine With Subnetwork Nodes for Representation Learning.

    Science.gov (United States)

    Yang, Yimin; Wu, Q M Jonathan

    2016-11-01

    The extreme learning machine (ELM), which was originally proposed for "generalized" single-hidden layer feedforward neural networks, provides efficient unified learning solutions for the applications of clustering, regression, and classification. It presents competitive accuracy with superb efficiency in many applications. However, ELM with subnetwork nodes architecture has not attracted much research attentions. Recently, many methods have been proposed for supervised/unsupervised dimension reduction or representation learning, but these methods normally only work for one type of problem. This paper studies the general architecture of multilayer ELM (ML-ELM) with subnetwork nodes, showing that: 1) the proposed method provides a representation learning platform with unsupervised/supervised and compressed/sparse representation learning and 2) experimental results on ten image datasets and 16 classification datasets show that, compared to other conventional feature learning methods, the proposed ML-ELM with subnetwork nodes performs competitively or much better than other feature learning methods.

  15. Neural correlates of face gender discrimination learning.

    Science.gov (United States)

    Su, Junzhu; Tan, Qingleng; Fang, Fang

    2013-04-01

    Using combined psychophysics and event-related potentials (ERPs), we investigated the effect of perceptual learning on face gender discrimination and probe the neural correlates of the learning effect. Human subjects were trained to perform a gender discrimination task with male or female faces. Before and after training, they were tested with the trained faces and other faces with the same and opposite genders. ERPs responding to these faces were recorded. Psychophysical results showed that training significantly improved subjects' discrimination performance and the improvement was specific to the trained gender, as well as to the trained identities. The training effect indicates that learning occurs at two levels-the category level (gender) and the exemplar level (identity). ERP analyses showed that the gender and identity learning was associated with the N170 latency reduction at the left occipital-temporal area and the N170 amplitude reduction at the right occipital-temporal area, respectively. These findings provide evidence for the facilitation model and the sharpening model on neuronal plasticity from visual experience, suggesting a faster processing speed and a sparser representation of face induced by perceptual learning.

  16. Neural substrates for semantic memory of familiar songs: is there an interface between lyrics and melodies?

    Directory of Open Access Journals (Sweden)

    Yoko Saito

    Full Text Available Findings on song perception and song production have increasingly suggested that common but partially distinct neural networks exist for processing lyrics and melody. However, the neural substrates of song recognition remain to be investigated. The purpose of this study was to examine the neural substrates involved in the accessing "song lexicon" as corresponding to a representational system that might provide links between the musical and phonological lexicons using positron emission tomography (PET. We exposed participants to auditory stimuli consisting of familiar and unfamiliar songs presented in three ways: sung lyrics (song, sung lyrics on a single pitch (lyrics, and the sung syllable 'la' on original pitches (melody. The auditory stimuli were designed to have equivalent familiarity to participants, and they were recorded at exactly the same tempo. Eleven right-handed nonmusicians participated in four conditions: three familiarity decision tasks using song, lyrics, and melody and a sound type decision task (control that was designed to engage perceptual and prelexical processing but not lexical processing. The contrasts (familiarity decision tasks versus control showed no common areas of activation between lyrics and melody. This result indicates that essentially separate neural networks exist in semantic memory for the verbal and melodic processing of familiar songs. Verbal lexical processing recruited the left fusiform gyrus and the left inferior occipital gyrus, whereas melodic lexical processing engaged the right middle temporal sulcus and the bilateral temporo-occipital cortices. Moreover, we found that song specifically activated the left posterior inferior temporal cortex, which may serve as an interface between verbal and musical representations in order to facilitate song recognition.

  17. [Neural repair].

    Science.gov (United States)

    Kitada, Masaaki; Dezawa, Mari

    2008-05-01

    Recent progress of stem cell biology gives us the hope for neural repair. We have established methods to specifically induce functional Schwann cells and neurons from bone marrow stromal cells (MSCs). The effectiveness of these induced cells was evaluated by grafting them either into peripheral nerve injury, spinal cord injury, or Parkinson' s disease animal models. MSCs-derived Schwann cells supported axonal regeneration and re-constructed myelin to facilitate the functional recovery in peripheral and spinal cord injury. MSCs-derived dopaminergic neurons integrated into host striatum and contributed to behavioral repair. In this review, we introduce the differentiation potential of MSCs and finally discuss about their benefits and drawbacks of these induction systems for cell-based therapy in neuro-traumatic and neuro-degenerative diseases.

  18. Understanding leader representations: Beyond implicit leadership theory

    OpenAIRE

    Knee, Robert Everett

    2006-01-01

    The purpose of the present study was to establish evidence for the suggested integration of the theories of connectionism and leadership. Recent theoretical writings in the field of leadership have suggested that the dynamic representations generated by the connectionist perspective is an appropriate approach to understanding how we perceive leaders. Similarly, implicit leadership theory (ILT) explains that our cognitive understandings of leaders are based on a cognitive structure that we u...

  19. Neural repair in the adult brain

    Science.gov (United States)

    Jessberger, Sebastian

    2016-01-01

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

  20. Categorification and higher representation theory

    CERN Document Server

    Beliakova, Anna

    2017-01-01

    The emergent mathematical philosophy of categorification is reshaping our view of modern mathematics by uncovering a hidden layer of structure in mathematics, revealing richer and more robust structures capable of describing more complex phenomena. Categorified representation theory, or higher representation theory, aims to understand a new level of structure present in representation theory. Rather than studying actions of algebras on vector spaces where algebra elements act by linear endomorphisms of the vector space, higher representation theory describes the structure present when algebras act on categories, with algebra elements acting by functors. The new level of structure in higher representation theory arises by studying the natural transformations between functors. This enhanced perspective brings into play a powerful new set of tools that deepens our understanding of traditional representation theory. This volume exhibits some of the current trends in higher representation theory and the diverse te...

  1. Genetic Algorithm Optimized Neural Networks Ensemble as ...

    African Journals Online (AJOL)

    Improvements in neural network calibration models by a novel approach using neural network ensemble (NNE) for the simultaneous spectrophotometric multicomponent analysis are suggested, with a study on the estimation of the components of an antihypertensive combination, namely, atenolol and losartan potassium.

  2. 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.

  3. Distributed representations accelerate evolution of adaptive behaviours.

    Directory of Open Access Journals (Sweden)

    James V Stone

    2007-08-01

    Full Text Available Animals with rudimentary innate abilities require substantial learning to transform those abilities into useful skills, where a skill can be considered as a set of sensory-motor associations. Using linear neural network models, it is proved that if skills are stored as distributed representations, then within-lifetime learning of part of a skill can induce automatic learning of the remaining parts of that skill. More importantly, it is shown that this "free-lunch" learning (FLL is responsible for accelerated evolution of skills, when compared with networks which either 1 cannot benefit from FLL or 2 cannot learn. Specifically, it is shown that FLL accelerates the appearance of adaptive behaviour, both in its innate form and as FLL-induced behaviour, and that FLL can accelerate the rate at which learned behaviours become innate.

  4. Dissociated neural mechanisms for face detection and configural encoding: evidence from N170 and induced gamma-band oscillation effects.

    Science.gov (United States)

    Zion-Golumbic, Elana; Bentin, Shlomo

    2007-08-01

    Despite ample research, the structure and the functional characteristics of neural systems involved in human face processing are still a matter of active debate. Here we dissociated between a neural mechanism manifested by the face-sensitive N170 event-related potential effect and a mechanism manifested by induced electroencephalographic oscillations in the gamma band, which have been previously associated with the integration of individually coded features and activation of corresponding neural representations. The amplitude of the N170 was larger in the absence of the face contour but not affected by the configuration of inner components (ICs). Its latency was delayed by scrambling the configuration of the components as well as by the absence of the face contour. Unlike the N170, the amplitude of the induced gamma activity was sensitive to the configuration of ICs but insensitive to their presence within or outside a face contour. This pattern suggests a dual mechanism for early face processing, each utilizing different visual cues, which might indicate their respective roles in face processing. The N170 seems to be associated primarily with the detection and categorization of faces, whereas the gamma oscillations may be involved in the activation of their mental representation.

  5. 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.

  6. Semiclassical initial value representation for the quantum propagator in the Heisenberg interaction representation.

    Science.gov (United States)

    Petersen, Jakob; Pollak, Eli

    2015-12-14

    One of the challenges facing on-the-fly ab initio semiclassical time evolution is the large expense needed to converge the computation. In this paper, we suggest that a significant saving in computational effort may be achieved by employing a semiclassical initial value representation (SCIVR) of the quantum propagator based on the Heisenberg interaction representation. We formulate and test numerically a modification and simplification of the previous semiclassical interaction representation of Shao and Makri [J. Chem. Phys. 113, 3681 (2000)]. The formulation is based on the wavefunction form of the semiclassical propagation instead of the operator form, and so is simpler and cheaper to implement. The semiclassical interaction representation has the advantage that the phase and prefactor vary relatively slowly as compared to the "standard" SCIVR methods. This improves its convergence properties significantly. Using a one-dimensional model system, the approximation is compared with Herman-Kluk's frozen Gaussian and Heller's thawed Gaussian approximations. The convergence properties of the interaction representation approach are shown to be favorable and indicate that the interaction representation is a viable way of incorporating on-the-fly force field information within a semiclassical framework.

  7. Neural crest contributions to the lamprey head

    Science.gov (United States)

    McCauley, David W.; Bronner-Fraser, Marianne

    2003-01-01

    The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.

  8. Going beyond representational anthropology

    DEFF Research Database (Denmark)

    Winther, Ida Wentzel

    Going beyond representational anthropology: Re-presenting bodily, emotional and virtual practices in everyday life. Separated youngsters and families in Greenland Greenland is a huge island, with a total of four high-schools. Many youngsters (age 16-18) move far away from home in order to get...... transformation work into the young people and their families. In this presentation I want to screen two sequences from the film, in order to show and clarify how mobility and transformation are made and dealt with both from the youngsters’ and their parents’ perspectives, but in asynchronous loups. I want...

  9. Representations of commonsense knowledge

    CERN Document Server

    Davis, Ernest

    1990-01-01

    Representations of Commonsense Knowledge provides a rich language for expressing commonsense knowledge and inference techniques for carrying out commonsense knowledge. This book provides a survey of the research on commonsense knowledge.Organized into 10 chapters, this book begins with an overview of the basic ideas on artificial intelligence commonsense reasoning. This text then examines the structure of logic, which is roughly analogous to that of a programming language. Other chapters describe how rules of universal validity can be applied to facts known with absolute certainty to deduce ot

  10. Statistical learning of parts and wholes: A neural network approach.

    Science.gov (United States)

    Plaut, David C; Vande Velde, Anna K

    2017-03-01

    Statistical learning is often considered to be a means of discovering the units of perception, such as words and objects, and representing them as explicit "chunks." However, entities are not undifferentiated wholes but often contain parts that contribute systematically to their meanings. Studies of incidental auditory or visual statistical learning suggest that, as participants learn about wholes they become insensitive to parts embedded within them, but this seems difficult to reconcile with a broad range of findings in which parts and wholes work together to contribute to behavior. Bayesian approaches provide a principled description of how parts and wholes can contribute simultaneously to performance, but are generally not intended to model the computations that actually give rise to this performance. In the current work, we develop an account based on learning in artificial neural networks in which the representation of parts and wholes is a matter of degree, and the extent to which they cooperate or compete arises naturally through incidental learning. We show that the approach accounts for a wide range of findings concerning the relationship between parts and wholes in auditory and visual statistical learning, including some findings previously thought to be problematic for neural network approaches. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  11. Representations of stem cell clinics on Twitter.

    Science.gov (United States)

    Kamenova, Kalina; Reshef, Amir; Caulfield, Timothy

    2014-12-01

    The practice of travelling abroad to receive unproven and unregulated stem cell treatments has become an increasingly problematic global phenomenon known as 'stem cell tourism'. In this paper, we examine representations of nine major clinics and providers of such treatments on the microblogging network Twitter. We collected and conducted a content analysis of Twitter posts (n = 363) by these establishments and by other users mentioning them, focusing specifically on marketing claims about treatment procedures and outcomes, discussions of safety and efficacy of stem cell transplants, and specific representations of patients' experiences. Our analysis has shown that there were explicit claims or suggestions of benefits associated with unproven stem cell treatments in approximately one third of the tweets and that patients' experiences, whenever referenced, were presented as invariably positive and as testimonials about the efficacy of stem cell transplants. Furthermore, the results indicated that the tone of most tweets (60.2 %) was overwhelmingly positive and there were rarely critical discussions about significant health risks associated with unproven stem cell therapies. When placed in the context of past research on the problems associated with the marketing of unproven stem cell therapies, this analysis of representations on Twitter suggests that discussions in social media have also remained largely uncritical of the stem cell tourism phenomenon, with inaccurate representations of risks and benefits for patients.

  12. Audio Spatial Representation Around the Body.

    Science.gov (United States)

    Aggius-Vella, Elena; Campus, Claudio; Finocchietti, Sara; Gori, Monica

    2017-01-01

    Studies have found that portions of space around our body are differently coded by our brain. Numerous works have investigated visual and auditory spatial representation, focusing mostly on the spatial representation of stimuli presented at head level, especially in the frontal space. Only few studies have investigated spatial representation around the entire body and its relationship with motor activity. Moreover, it is still not clear whether the space surrounding us is represented as a unitary dimension or whether it is split up into different portions, differently shaped by our senses and motor activity. To clarify these points, we investigated audio localization of dynamic and static sounds at different body levels. In order to understand the role of a motor action in auditory space representation, we asked subjects to localize sounds by pointing with the hand or the foot, or by giving a verbal answer. We found that the audio sound localization was different depending on the body part considered. Moreover, a different pattern of response was observed when subjects were asked to make actions with respect to the verbal responses. These results suggest that the audio space around our body is split in various spatial portions, which are perceived differently: front, back, around chest, and around foot, suggesting that these four areas could be differently modulated by our senses and our actions.

  13. Individual Representation: A Different Approach to Political Representation

    OpenAIRE

    Ruedin, Didier

    2012-01-01

    This article presents a new conceptualisation and measure of political representation to complement conventional approaches. Individual representation scores place the individual rather than the legislature at the centre, providing a fresh perspective on the relationship between inequality and representation. They are calculated by comparing first the position of the individual with other citizens, and second the position of the individual with the legislature. The article outlines how to mak...

  14. Social Representations of Intelligence

    Directory of Open Access Journals (Sweden)

    Elena Zubieta

    2016-02-01

    Full Text Available The article stresses the relationship between Explicit and Implicit theories of Intelligence. Following the line of common sense epistemology and the theory of Social Representations, a study was carried out in order to analyze naive’s explanations about Intelligence Definitions. Based on Mugny & Carugati (1989 research, a self-administered questionnaire was designed and filled in by 286 subjects. Results are congruent with the main hyphotesis postulated: A general overlap between explicit and implicit theories showed up. According to the results Intelligence appears as both, a social attribute related to social adaptation and as a concept defined in relation with contextual variables similar to expert’s current discourses. Nevertheless, conceptions based on “gifted ideology” still are present stressing the main axes of Intelligence debate: biological and sociological determinism. In the same sense, unfamiliarity and social identity are reaffirmed as organizing principles of social representation. The distance with the object -measured as the belief in intelligence differences as a solve/non solve problem- and the level of implication with the topic -teachers/no teachers- appear as discriminating elements at the moment of supporting specific dimensions. 

  15. Why Overlearned Sequences are Special: Distinct Neural Networks for Ordinal Sequences

    Directory of Open Access Journals (Sweden)

    Vani ePariyadath

    2012-12-01

    Full Text Available Several observations suggest that overlearned ordinal categories (e.g., letters, numbers, weekdays, months are processed differently than non-ordinal categories in the brain. In synesthesia, for example, anomalous perceptual experiences are most often triggered by members of ordinal categories (Rich et al., 2005; Eagleman, 2009. In semantic dementia, the processing of ordinal stimuli appears to be preserved relative to non-ordinal ones (Cappelletti et al., 2001. Moreover, ordinal stimuli often map onto unconscious spatial representations, as observed in the SNARC effect (Dehaene et al, 1993; Fias, 1996. At present, little is known about the neural representation of ordinal categories. Using functional neuroimaging, we show that words in ordinal categories are processed in a fronto-temporo-parietal network biased toward the right hemisphere. This differs from words in non-ordinal categories (such as names of furniture, animals, cars and fruit, which show an expected bias toward the left hemisphere. Further, we find that increased predictability of stimulus order correlates with smaller regions of BOLD activation, a phenomenon we term prediction suppression. Our results provide new insights into the processing of ordinal stimuli, and suggest a new anatomical framework for understanding the patterns seen in synesthesia, unconscious spatial representation, and semantic dementia.

  16. A Simple Shallow Convolutional Neural Network for Accurate Handwritten Digit Classification

    OpenAIRE

    Golovko, V.; Mikhno, E.; Brichk, A.

    2016-01-01

    At present the deep neural network is the hottest topic in the domain of machine learning and can accomplish a deep hierarchical representation of the input data. Due to deep architecture the large convolutional neural networks can reach very small test error rates below 0.4% using the MNIST database. In this work we have shown, that high accuracy can be achieved using reduced shallow convolutional neural network without adding distortions for digits. The main contribu...

  17. Representation of identities and the politics of representation in cognition

    OpenAIRE

    Kanavillil Rajagopalan

    2001-01-01

    In this paper, I make a plea for viewing representation as first and foremost a political matter. I argue that by so doing we may avoid the many of pitfalls of contemporary theories of cognition as they attempt to tackle the issue of representation. Most of these problems have to do with the fact that representation is treated exclusively as a mimetic or theatrical question. The fact of the matter is however that representation also has a political dimension. Indeed it has always had...

  18. Mapping phantom movement representations in the motor cortex of amputees.

    Science.gov (United States)

    Mercier, Catherine; Reilly, Karen T; Vargas, Claudia D; Aballea, Antoine; Sirigu, Angela

    2006-08-01

    Limb amputation results in plasticity of connections between the brain and muscles, with the cortical motor representation of the missing limb seemingly shrinking, to the presumed benefit of remaining body parts that have cortical representations adjacent to the now-missing limb. Surprisingly, the corresponding perceptual representation does not suffer a similar fate but instead persists as a phantom limb endowed with sensory and motor qualities. How can cortical reorganization after amputation be reconciled with the maintenance of a motor representation of the phantom limb in the brain? In an attempt to answer this question we explored the relationship between the cortical representation of the remaining arm muscles and that of phantom movements. Using transcranial magnetic stimulation (TMS) we systematically mapped phantom movement perceptions while simultaneously recording stump muscle activity in three above-elbow amputees. TMS elicited sensations of movement in the phantom hand when applied over the presumed hand area of the motor cortex. In one subject the amplitude of the perceived movement was positively correlated with the intensity of stimulation. Interestingly, phantom limb movements that the patient could not produce voluntarily were easily triggered by TMS, suggesting that the inability to voluntarily move the phantom is not equivalent to a loss of the corresponding movement representation. We suggest that hand movement representations survive in the reorganized motor area of amputees even when these cannot be directly accessed. The activation of these representations is probably necessary for the experience of phantom movement.

  19. Deepening sleep by hypnotic suggestion.

    OpenAIRE

    Cordi, Maren J.; Schlarb, Angelika A; Rasch, Björn

    2014-01-01

    STUDY OBJECTIVES Slow wave sleep (SWS) plays a critical role in body restoration and promotes brain plasticity; however it markedly declines across the lifespan. Despite its importance effective tools to increase SWS are rare. Here we tested whether a hypnotic suggestion to "sleep deeper" extends the amount of SWS. DESIGN Within subject placebo controlled crossover design. SETTING Sleep laboratory at the University of Zurich Switzerland. PARTICIPANTS Seventy healthy females 23.27 ± 3.17 y. IN...

  20. Neural scaling laws for an uncertain world

    CERN Document Server

    Howard, Marc W

    2016-01-01

    The Weber-Fechner law describes the form of psychological space in many behavioral experiments involving perception of one-dimensional physical quantities. If the physical quantity is expressed using multiple neural receptors, then placing receptive fields evenly along a logarithmic scale naturally leads to the psychological Weber-Fechner law. In the visual system, the spacing and width of extrafoveal receptive fields are consistent with logarithmic scaling. Other sets of neural "receptors" appear to show the same qualitative properties, suggesting that this form of neural scaling reflects a solution to a very general problem. This paper argues that these neural scaling laws enable the brain to represent information about the world efficiently without making any assumptions about the statistics of the world. This analysis suggests that the organization of neural scales to represent one-dimensional quantities, including more abstract quantities such as numerosity, time, and allocentric space, should have a uni...

  1. Representational Flexibility and Specificity following Spatial Descriptions of Real-World Environments

    Science.gov (United States)

    Brunye, Tad T.; Rapp, David N.; Taylor, Holly A.

    2008-01-01

    Current theories are mixed with regard to the nature of mental representations following spatial description reading. Whereas some findings argue that individuals' representations are invariant following text-based, map-based, or first-person experience, other studies have suggested that representations can also exhibit considerable flexibility.…

  2. Visual Representations of DNA Replication: Middle Grades Students' Perceptions and Interpretations

    Science.gov (United States)

    Patrick, Michelle D.; Carter, Glenda; Wiebe, Eric N.

    2005-01-01

    Visual representations play a critical role in the communication of science concepts for scientists and students alike. However, recent research suggests that novice students experience difficulty extracting relevant information from representations. This study examined students' interpretations of visual representations of DNA replication. Each…

  3. Do Monkeys Think in Metaphors? Representations of Space and Time in Monkeys and Humans

    Science.gov (United States)

    Merritt, Dustin J.; Casasanto, Daniel; Brannon, Elizabeth M.

    2010-01-01

    Research on the relationship between the representation of space and time has produced two contrasting proposals. ATOM posits that space and time are represented via a common magnitude system, suggesting a symmetrical relationship between space and time. According to metaphor theory, however, representations of time depend on representations of…

  4. A conceptual lemon: theta burst stimulation to the left anterior temporal lobe untangles object representation and its canonical color.

    Science.gov (United States)

    Chiou, Rocco; Sowman, Paul F; Etchell, Andrew C; Rich, Anina N

    2014-05-01

    Object recognition benefits greatly from our knowledge of typical color (e.g., a lemon is usually yellow). Most research on object color knowledge focuses on whether both knowledge and perception of object color recruit the well-established neural substrates of color vision (the V4 complex). Compared with the intensive investigation of the V4 complex, we know little about where and how neural mechanisms beyond V4 contribute to color knowledge. The anterior temporal lobe (ATL) is thought to act as a "hub" that supports semantic memory by integrating different modality-specific contents into a meaningful entity at a supramodal conceptual level, making it a good candidate zone for mediating the mappings between object attributes. Here, we explore whether the ATL is critical for integrating typical color with other object attributes (object shape and name), akin to its role in combining nonperceptual semantic representations. In separate experimental sessions, we applied TMS to disrupt neural processing in the left ATL and a control site (the occipital pole). Participants performed an object naming task that probes color knowledge and elicits a reliable color congruency effect as well as a control quantity naming task that also elicits a cognitive congruency effect but involves no conceptual integration. Critically, ATL stimulation eliminated the otherwise robust color congruency effect but had no impact on the numerical congruency effect, indicating a selective disruption of object color knowledge. Neither color nor numerical congruency effects were affected by stimulation at the control occipital site, ruling out nonspecific effects of cortical stimulation. Our findings suggest that the ATL is involved in the representation of object concepts that include their canonical colors.

  5. Neural correlates of maintaining generated images in visual working memory.

    Science.gov (United States)

    Ewerdwalbesloh, Julia A; Palva, Satu; Rösler, Frank; Khader, Patrick H

    2016-12-01

    How are images that have been assembled from their constituting elements maintained as a coherent representation in visual working memory (vWM)? Here, we compared two conditions of vWM maintenance that only differed in how vWM contents had been created. Participants maintained images that they either had to assemble from single features or that they had perceived as complete objects. Object complexity varied between two and four features. We analyzed electroencephalogram phase coupling as a measure of cortical connectivity in a time interval immediately before a probe stimulus appeared. We assumed that during this time both groups maintained essentially the same images, but that images constructed from their elements would require more neural coupling than images based on a complete percept. Increased coupling between frontal and parietal-to-occipital cortical sources was found for the maintenance of constructed in comparison to nonconstructed objects in the theta, alpha, beta, and gamma frequency bands. A similar pattern was found for an increase in vWM load (2 vs. 4 features) for nonconstructed objects. Under increased construction load (2 vs. 4 features for constructed images), the pattern was restricted to fronto-parietal couplings, suggesting that the fronto-parietal attention network is coping with the higher attentional demands involved in maintaining constructed images, but without increasing the communication with the occipital visual buffer in which the visual representations are assumed to be stored. We conclude from these findings that the maintenance of constructed images in vWM requires additional attentional processes to keep object elements together as a coherent representation. Hum Brain Mapp 37:4349-4362, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  6. From image edges to geons to viewpoint-invariant object models: a neural net implementation

    Science.gov (United States)

    Biederman, Irving; Hummel, John E.; Gerhardstein, Peter C.; Cooper, Eric E.

    1992-03-01

    Three striking and fundamental characteristics of human shape recognition are its invariance with viewpoint in depth (including scale), its tolerance of unfamiliarity, and its robustness with the actual contours present in an image (as long as the same convex parts [geons] can be activated). These characteristics are expressed in an implemented neural network model (Hummel & Biederman, 1992) that takes a line drawing of an object as input and generates a structural description of geons and their relations which is then used for object classification. The model's capacity for structural description derives from its solution to the dynamic binding problem of neural networks: independent units representing an object's parts (in terms of their shape attributes and interrelations) are bound temporarily when those attributes occur in conjunction in the system's input. Temporary conjunctions of attributes are represented by synchronized activity among the units representing those attributes. Specifically, the model induces temporal correlation in the firing of activated units to: (1) parse images into their constituent parts; (2) bind together the attributes of a part; and (3) determine the relations among the parts and bind them to the parts to which they apply. Because it conjoins independent units temporarily, dynamic binding allows tremendous economy of representation, and permits the representation to reflect an object's attribute structure. The model's recognition performance conforms well to recent results from shape priming experiments. Moreover, the manner in which the model's performance degrades due to accidental synchrony produced by an excess of phase sets suggests a basis for a theory of visual attention.

  7. Combinatorial structures and processing in neural blackboard architectures

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; de Kamps, Marc; Besold, Tarek R.; d'Avila Garcez, Artur; Marcus, Gary F.; Miikkulainen, Risto

    2015-01-01

    We discuss and illustrate Neural Blackboard Architectures (NBAs) as the basis for variable binding and combinatorial processing the brain. We focus on the NBA for sentence structure. NBAs are based on the notion that conceptual representations are in situ, hence cannot be copied or transported.

  8. Application of the minimum fuel neural network to music signals

    DEFF Research Database (Denmark)

    Harbo, Anders La-Cour

    2004-01-01

    Finding an optimal representation of a signal in an over-complete dictionary is often quite difficult. Since general results in this field are not very application friendly it truly helps to specify the framework as much as possible. We investigate the method Minimum Fuel Neural Network (MFNN...

  9. Ambiguity resolution in a Neural Blackboard Architecture for sentence structure

    NARCIS (Netherlands)

    van der Velde, Frank; van der Velde, Frank; de Kamps, Marc; Besold, Tarek R.; Kühnberger, Kai-Uwe

    2015-01-01

    We simulate two examples of ambiguity resolution found in human language processing in a neural blackboard architecture for sentence representation and processing. The architecture also accounts for a related garden path effect. The architecture represents and processes sentences in terms of

  10. Preparing for knowledge extraction in modular neural networks

    NARCIS (Netherlands)

    Spaanenburg, Lambert; Slump, Cornelis H.; Venema, Rienk; van der Zwaag, B.J.

    Neural networks learn knowledge from data. For a monolithic structure, this knowledge can be easily used but not isolated. The many degrees of freedom while learning make knowledge extraction a computationally intensive process as the representation is not unique. Where existing knowledge is

  11. Integral geometry and representation theory

    CERN Document Server

    Gel'fand, I M; Vilenkin, N Ya

    1966-01-01

    Generalized Functions, Volume 5: Integral Geometry and Representation Theory is devoted to the theory of representations, focusing on the group of two-dimensional complex matrices of determinant one.This book emphasizes that the theory of representations is a good example of the use of algebraic and geometric methods in functional analysis, in which transformations are performed not on the points of a space, but on the functions defined on it. The topics discussed include Radon transform on a real affine space, integral transforms in the complex domain, and representations of the group of comp

  12. Sparse distributed representation of odors in a large-scale olfactory bulb circuit.

    Directory of Open Access Journals (Sweden)

    Yuguo Yu

    Full Text Available In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and generation of testable hypotheses of the functional mechanisms underlying odor representation in the olfactory bulb circuit. Specifically, we demonstrate that lateral inhibition emerges within the olfactory bulb network through recurrent dendrodendritic synapses when constrained by a range of balanced excitatory and inhibitory conductances. We find that the spatio-temporal dynamics of lateral inhibition plays a critical role in building the glomerular-related cell clusters observed in experiments, through the modulation of synaptic weights during odor training. Lateral inhibition also mediates the development of sparse and synchronized spiking patterns of mitral cells related to odor inputs within the network, with the frequency of these synchronized spiking patterns also modulated by the sniff cycle.

  13. Allocentric or Craniocentric Representation of Acoustic Space: An Electrotomography Study Using Mismatch Negativity

    Science.gov (United States)

    Altmann, Christian F.; Getzmann, Stephan; Lewald, Jörg

    2012-01-01

    The world around us appears stable in spite of our constantly moving head, eyes, and body. How this is achieved by our brain is hardly understood and even less so in the auditory domain. Using electroencephalography and the so-called mismatch negativity, we investigated whether auditory space is encoded in an allocentric (referenced to the environment) or craniocentric representation (referenced to the head). Fourteen subjects were presented with noise bursts from loudspeakers in an anechoic environment. Occasionally, subjects were cued to rotate their heads and a deviant sound burst occurred, that deviated from the preceding standard stimulus either in terms of an allocentric or craniocentric frame of reference. We observed a significant mismatch negativity, i.e., a more negative response to deviants with reference to standard stimuli from about 136 to 188 ms after stimulus onset in the craniocentric deviant condition only. Distributed source modeling with sLORETA revealed an involvement of lateral superior temporal gyrus and inferior parietal lobule in the underlying neural processes. These findings suggested a craniocentric, rather than allocentric, representation of auditory space at the level of the mismatch negativity. PMID:22848643

  14. A cortical network that marks the moment when conscious representations are updated.

    Science.gov (United States)

    Stöttinger, Elisabeth; Filipowicz, Alex; Valadao, Derick; Culham, Jody C; Goodale, Melvyn A; Anderson, Britt; Danckert, James

    2015-12-01

    In order to survive in a complex, noisy and constantly changing environment we need to categorize the world (e.g., Is this food edible or poisonous?) and we need to update our interpretations when things change. How does our brain update when object categories change from one to the next? We investigated the neural correlates associated with this updating process. We used event-related fMRI while people viewed a sequence of images that morphed from one object (e.g., a plane) to another (e.g., a shark). All participants were naïve as to the identity of the second object. The point at which participants 'saw' the second object was unpredictable and uncontaminated by any dramatic or salient change to the images themselves. The moment when subjective perceptual representations changed activated a circumscribed network including the anterior insula, medial and inferior frontal regions and inferior parietal cortex. In a setting where neither the timing nor nature of the visual transition was predictable, this restricted cortical network signals the time of updating a perceptual representation. The anterior insula and mid-frontal regions (including the ACC) were activated not only at the actual time when change was reported, but also immediately before, suggesting that these areas are also involved in processing alternative options after a mismatch has been detected. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Enhancing business intelligence by means of suggestive reviews.

    Science.gov (United States)

    Qazi, Atika; Raj, Ram Gopal; Tahir, Muhammad; Cambria, Erik; Syed, Karim Bux Shah

    2014-01-01

    Appropriate identification and classification of online reviews to satisfy the needs of current and potential users pose a critical challenge for the business environment. This paper focuses on a specific kind of reviews: the suggestive type. Suggestions have a significant influence on both consumers' choices and designers' understanding and, hence, they are key for tasks such as brand positioning and social media marketing. The proposed approach consists of three main steps: (1) classify comparative and suggestive sentences; (2) categorize suggestive sentences into different types, either explicit or implicit locutions; (3) perform sentiment analysis on the classified reviews. A range of supervised machine learning approaches and feature sets are evaluated to tackle the problem of suggestive opinion mining. Experimental results for all three tasks are obtained on a dataset of mobile phone reviews and demonstrate that extending a bag-of-words representation with suggestive and comparative patterns is ideal for distinguishing suggestive sentences. In particular, it is observed that classifying suggestive sentences into implicit and explicit locutions works best when using a mixed sequential rule feature representation. Sentiment analysis achieves maximum performance when employing additional preprocessing in the form of negation handling and target masking, combined with sentiment lexicons.

  16. Intentionality, Representation, and Anticipation

    Science.gov (United States)

    De Preester, Helena

    2002-09-01

    Both Brentano and Merleau-Ponty have developed an account of intentionality, which nevertheless differ profoundly in the following respect. According to Brentano, intentionality mainly is a matter of mental presentations. This marks the beginning of phenomenology's difficult relation with the nature of the intentional reference. Merleau-Ponty, on the other hand, has situated intentionality on the level of the body, a turn which has important implications for the nature of intentionality. Intentionality no longer is primarily based on having (re)presentations, but is rooted in the dynamics of the living body. To contrast those approaches enables us to make clear in what way intentionality is studied nowadays. On the one hand, intentionality is conceived of as a matter of formal-syntactical causality in cognitive science, and in particular in classical-computational theory. On the other hand, a interactivist approach offers a more Merleau-Ponty-like point of view, in which autonomy, embodiment and interaction are stressed.

  17. Resource representation in COMPASS

    Science.gov (United States)

    Fox, Barry R.

    1991-01-01

    A set of viewgraphs on resource representation in COMPASS is given. COMPASS is an incremental, interactive, non-chronological scheduler written in Ada with an X-windows user interface. Beginning with an empty schedule, activities are added to the schedule one at a time, taking into consideration the placement of the activities already on the timeline and the resources that have been reserved for them. The order that the activities are added to the timeline and their location on the timeline are controlled by selection and placement commands invoked by the user. The order that activities are added to the timeline and their location are independent. The COMPASS code library is a cost effective platform for the development of new scheduling applications. It can be effectively used off the shelf for compatible scheduling applications or it can be used as a parts library for the development of custom scheduling systems.

  18. Effects of microgravity on muscle and cerebral cortex: a suggested interaction

    Science.gov (United States)

    D'Amelio, F.; Fox, R. A.; Wu, L. C.; Daunton, N. G.; Corcoran, M. L.

    The ``slow'' antigravity muscle adductor longus was studied in rats after 14 days of spaceflight (SF). The techniques employed included standard methods for light microscopy, neural cell adhesion molecule (N-CAM) immunocytochemistry and electron microscopy. Light and electron microscopy revealed myofiber atrophy, segmental necrosis and regenerative myofibers. Regenerative myofibers were N-CAM immunoreactive (N-CAM-IR). The neuromuscular junctions showed axon terminals with a decrease or absence of synaptic vesicles, degenerative changes, vacant axonal spaces and changes suggestive of axonal sprouting. No alterations of muscle spindles was seen either by light or electron microscopy. These observations suggest that muscle regeneration and denervation and synaptic remodeling at the level of the neuromuscular junction may take place during spaceflight. In a separate study, GABA immunoreactivity (GABA-IR) was evaluated at the level of the hindlimb representation of the rat somatosensory cortex after 14 days of hindlimb unloading by tail suspension (``simulated'' microgravity). A reduction in number of GABA-immunoreactive cells with respect to the control animals was observed in layer Va and Vb. GABA-IR terminals were also reduced in the same layers, particularly those terminals surrounding the soma and apical dendrites of pyramidal cells in layer Vb. On the basis of previous morphological and behavioral studies of the neuromuscular system after spaceflight and hindlimb suspension it is suggested that after limb unloading there are alterations of afferent signaling and feedback information from intramuscular receptors to the cerebral cortex due to modifications in the reflex organization of hindlimb muscle groups. We propose that the changes observed in GABA immunoreactivity of cells and terminals is an expression of changes in their modulatory activity to compensate for the alterations in the afferent information.

  19. Neural ensemble dynamics underlying a long-term associative memory

    Science.gov (United States)

    Grewe, Benjamin F.; Gründemann, Jan; Kitch, Lacey J.; Lecoq, Jerome A.; Parker, Jones G.; Marshall, Jesse D.; Larkin, Margaret C.; Jercog, Pablo E.; Grenier, Francois; Li, Jin Zhong; Lüthi, Andreas; Schnitzer, Mark J.

    2017-01-01

    The brain’s ability to associate different stimuli is vital to long-term memory, but how neural ensembles encode associative memories is unknown. Here we studied how cell ensembles in the basal and lateral amygdala (BLA) encode associations between conditioned and unconditioned stimuli (CS, US). Using a miniature fluorescence microscope, we tracked BLA ensemble neural Ca2+ dynamics during fear learning and extinction over six days in behaving mice. Fear conditioning induced both up- and down-regulation of individual cells’ CS-evoked responses. This bi-directional plasticity mainly occurred after conditioning and reshaped the CS ensemble neural representation to gain similarity to the US-representation. During extinction training with repetitive CS presentations, the CS-representation became more distinctive without reverting to its original form. Throughout, the strength of the ensemble-encoded CS-US association predicted each mouse’s level of behavioral conditioning. These findings support a supervised learning model in which activation of the US-representation guides the transformation of the CS-representation. PMID:28329757

  20. Shared neural circuits for mentalizing about the self and others.

    Science.gov (United States)

    Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

    2010-07-01

    Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

  1. Dermatomal Organization of SI Leg Representation in Humans: Revising the Somatosensory Homunculus.

    Science.gov (United States)

    Dietrich, Caroline; Blume, Kathrin R; Franz, Marcel; Huonker, Ralph; Carl, Maria; Preißler, Sandra; Hofmann, Gunther O; Miltner, Wolfgang H R; Weiss, Thomas

    2017-09-01

    Penfield and Rasmussen's homunculus is the valid map of the neural body representation of nearly each textbook of biology, physiology, and neuroscience. The somatosensory homunculus places the foot representation on the mesial surface of the postcentral gyrus followed by the representations of the lower leg and the thigh in superio-lateral direction. However, this strong homuncular organization contradicts the "dermatomal" organization of spinal nerves. We used somatosensory-evoked magnetic fields and source analysis to study the leg's neural representation in the primary somatosensory cortex (SI). We show that the representation of the back of the thigh is located inferior to the foot's representation in SI whereas the front of the thigh is located laterally to the foot's representation. This observation indicates that the localization of the leg in SI rather follows the dermatomal organization of spinal nerves than the typical map of neighboring body parts as depicted in Penfield and Rasmussen's illustration of the somatosensory homunculus. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  2. Representation of differences in Brazilian journalistic discourse

    Directory of Open Access Journals (Sweden)

    Fernando Resende

    2015-08-01

    Full Text Available Considering the technological advance, which enhances the production of mediatic discourses, and the notion of a libidinal power installed in our globalized societies, reflecting upon representation of differences seems to be a major issue. This essay discusses the production of journalistic discourses from an epistemological perspective. The field of media is taken as constituted by a triple component – discourse/narrative/machines – and we suggest that this triad has proved to be incomplete: discourse and narrative, once they really are vertexes of the triangle, are absences. Two journalistic-documentary productions – which intend to represent life in the slums of Brazil – are compared in order to reflect upon representation of differences in Brazilian journalistic discourse. In view of the up-to-date polarization and pulverization of discourses, we suggest that in the perspective of the journalistic discourse, one can only speak about alterity if one tries to comprehend the ways news is staged.

  3. Accurate metacognition for visual sensory memory representations.

    Science.gov (United States)

    Vandenbroucke, Annelinde R E; Sligte, Ilja G; Barrett, Adam B; Seth, Anil K; Fahrenfort, Johannes J; Lamme, Victor A F

    2014-04-01

    The capacity to attend to multiple objects in the visual field is limited. However, introspectively, people feel that they see the whole visual world at once. Some scholars suggest that this introspective feeling is based on short-lived sensory memory representations, whereas others argue that the feeling of seeing more than can be attended to is illusory. Here, we investigated this phenomenon by combining objective memory performance with subjective confidence ratings during a change-detection task. This allowed us to compute a measure of metacognition--the degree of knowledge that subjects have about the correctness of their decisions--for different stages of memory. We show that subjects store more objects in sensory memory than they can attend to but, at the same time, have similar metacognition for sensory memory and working memory representations. This suggests that these subjective impressions are not an illusion but accurate reflections of the richness of visual perception.

  4. Neural recording and modulation technologies

    Science.gov (United States)

    Chen, Ritchie; Canales, Andres; Anikeeva, Polina

    2017-01-01

    In the mammalian nervous system, billions of neurons connected by quadrillions of synapses exchange electrical, chemical and mechanical signals. Disruptions to this network manifest as neurological or psychiatric conditions. Despite decades of neuroscience research, our ability to treat or even to understand these conditions is limited by the capability of tools to probe the signalling complexity of the nervous system. Although orders of magnitude smaller and computationally faster than neurons, conventional substrate-bound electronics do not recapitulate the chemical and mechanical properties of neural tissue. This mismatch results in a foreign-body response and the encapsulation of devices by glial scars, suggesting that the design of an interface between the nervous system and a synthetic sensor requires additional materials innovation. Advances in genetic tools for manipulating neural activity have fuelled the demand for devices that are capable of simultaneously recording and controlling individual neurons at unprecedented scales. Recently, flexible organic electronics and bio- and nanomaterials have been developed for multifunctional and minimally invasive probes for long-term interaction with the nervous system. In this Review, we discuss the design lessons from the quarter-century-old field of neural engineering, highlight recent materials-driven progress in neural probes and look at emergent directions inspired by the principles of neural transduction.

  5. Bodies adapt orientation-independent face representations.

    Science.gov (United States)

    Kessler, Ellyanna; Walls, Shawn A; Ghuman, Avniel S

    2013-01-01

    Faces and bodies share a great number of semantic attributes, such as gender, emotional expressiveness, and identity. Recent studies demonstrate that bodies can activate and modulate face perception. However, the nature of the face representation that is activated by bodies remains unknown. In particular, face and body representations have previously been shown to have a degree of orientation specificity. Here we use body-face adaptation aftereffects to test whether bodies activate face representations in an orientation-dependent manner. Specifically, we used a two-by-two design to examine the magnitude of the body-face aftereffect using upright and inverted body adaptors and upright and inverted face targets. All four conditions showed significant body-face adaptation. We found neither a main effect of body orientation nor an interaction between body and face orientation. There was a main effect of target face orientation, with inverted target faces showing larger aftereffects than upright target faces, consistent with traditional face-face adaptation. Taken together, these results suggest that bodies adapt and activate a relatively orientation-independent representation of faces.

  6. Plasticity of the hippocampal place cell representation.

    Science.gov (United States)

    Jeffery, Kathryn J; Hayman, Robin

    2004-01-01

    The role of the hippocampus in the representation of 'place' has been attributed to the place cells, whose spatially localised firing suggests their participation in forming a cognitive map of the environment. That this map is necessary for spatial memory formation is indicated by the propensity of almost all navigational tasks to be disrupted by hippocampal damage. The hippocampus has also long been implicated in the formation of episodic memories, and the unusually plastic nature of hippocampal synapses testifies to its probable mnemonic role. Arguably, the place cell representation should, if it is to support spatial learning, be modifiable according to known principles of synaptic reorganization. The present article reviews evidence that the place cell representation is indeed plastic, and that its plasticity depends on the same neurobiological mechanisms known to underlie experimentally induced synaptic plasticity. Inferences are drawn regarding the architecture of the spatial representation and the principles by which it is modified. Spatial learning is promising to be the first kind of memory which is completely understood at all levels, from molecular through circuitry to behaviour and beyond.

  7. Bodies adapt orientation-independent face representations

    Directory of Open Access Journals (Sweden)

    Ellyanna eKessler

    2013-07-01

    Full Text Available Faces and bodies share a great number of semantic attributes, such as gender, emotional expression, and identity. Recent studies demonstrate that bodies can activate and modulate face perception. However, the nature of the face representation that is activated by bodies remains unknown. In particular, face and body representations have previously been shown to have a degree of orientation specificity. Here we use body-face adaptation aftereffects to test whether bodies activate face representations in an orientation-dependent manner. Specifically, we used a two-by-two design to examine the magnitude of the body-face aftereffect using upright and inverted body adaptors and upright and inverted face targets. All four conditions showed significant body-face adaptation. We found neither a main effect of body orientation nor an interaction between body and face orientation. There was a main effect of target face orientation, with inverted target faces showing larger aftereffects than upright target faces, consistent with traditional face-face adaptation. Taken together, these results suggest that bodies adapt and activate a relatively orientation-invariant representation of faces.

  8. A model for integrating elementary neural functions into delayed-response behavior.

    Directory of Open Access Journals (Sweden)

    Thomas Gisiger

    2006-04-01

    Full Text Available It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning, and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task, or recalling from this image another one that has been associated with it during training (delayed-pair association task. The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

  9. The functional role of neural oscillations in non-verbal emotional communication

    Directory of Open Access Journals (Sweden)

    Ashley E Symons

    2016-05-01

    Full Text Available Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS, and orbitofrontal cortex (OFC. However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterise the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronisation appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronisation may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronisation reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities, presence or absence of predictive information, and attentional or task demands. Thus, the synchronisation of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity

  10. A Neural Substrate for Rapid Timbre Recognition? Neural and Behavioral Discrimination of Very Brief Acoustic Vowels.

    Science.gov (United States)

    Occelli, F; Suied, C; Pressnitzer, D; Edeline, J-M; Gourévitch, B

    2016-06-01

    The timbre of a sound plays an important role in our ability to discriminate between behaviorally relevant auditory categories, such as different vowels in speech. Here, we investigated, in the primary auditory cortex (A1) of anesthetized guinea pigs, the neural representation of vowels with impoverished timbre cues. Five different vowels were presented with durations ranging from 2 to 128 ms. A psychophysical experiment involving human listeners showed that identification performance was near ceiling for the longer durations and degraded close to chance level for the shortest durations. This was likely due to spectral splatter, which reduced the contrast between the spectral profiles of the vowels at short durations. Effects of vowel duration on cortical responses were well predicted by the linear frequency responses of A1 neurons. Using mutual information, we found that auditory cortical neurons in the guinea pig could be used to reliably identify several vowels for all durations. Information carried by each cortical site was low on average, but the population code was accurate even for durations where human behavioral performance was poor. These results suggest that a place population code is available at the level of A1 to encode spectral profile cues for even very short sounds. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Representations for Supporting Students' Context Awareness

    DEFF Research Database (Denmark)

    Demetriadis, Stavros N.; Papadopoulos, Pantelis M.

    2005-01-01

    in contextual information material, in a way that improves both their context awareness and metacontextual competence. After presenting a context model, we discuss the design of such representations based on this model and explain why we expect that their use in a learning situation would enhance context...... awareness. A research agenda is also included, suggesting specific research activities for evaluating the instructional efficiency of the proposed design....

  12. Motor Memory Is Encoded as a Gain-Field Combination of Intrinsic and Extrinsic Action Representations

    Science.gov (United States)

    Brayanov, Jordan B.; Press, Daniel Z.; Smith, Maurice A.

    2013-01-01

    Actions can be planned in either an intrinsic (body-based) reference frame or an extrinsic (world-based) frame, and understanding how the internal representations associated with these frames contribute to the learning of motor actions is a key issue in motor control. We studied the internal representation of this learning in human subjects by analyzing generalization patterns across an array of different movement directions and workspaces after training a visuomotor rotation in a single movement direction in one workspace. This provided a dense sampling of the generalization function across intrinsic and extrinsic reference frames, which allowed us to dissociate intrinsic and extrinsic representations and determine the manner in which they contributed to the motor memory for a trained action. A first experiment showed that the generalization pattern reflected a memory that was intermediate between intrinsic and extrinsic representations. A second experiment showed that this intermediate representation could not arise from separate intrinsic and extrinsic learning. Instead, we find that the representation of learning is based on a gain-field combination of local representations in intrinsic and extrinsic coordinates. This gain-field representation generalizes between actions by effectively computing similarity based on the (Mahalanobis) distance across intrinsic and extrinsic coordinates and is in line with neural recordings showing mixed intrinsic-extrinsic representations in motor and parietal cortices. PMID:23100418

  13. $\\alpha$-Representation for QCD

    OpenAIRE

    Tuan, Richard Hong

    1998-01-01

    An $\\alpha$-parameter representation is derived for gauge field theories.It involves, relative to a scalar field theory, only constants and derivatives with respect to the $\\alpha$-parameters. Simple rules are given to obtain the $\\alpha$-representation for a Feynman graph with an arbitrary number of loops in gauge theories in the Feynman gauge.

  14. Using Integer Manipulatives: Representational Determinism

    Science.gov (United States)

    Bossé, Michael J.; Lynch-Davis, Kathleen; Adu-Gyamfi, Kwaku; Chandler, Kayla

    2016-01-01

    Teachers and students commonly use various concrete representations during mathematical instruction. These representations can be utilized to help students understand mathematical concepts and processes, increase flexibility of thinking, facilitate problem solving, and reduce anxiety while doing mathematics. Unfortunately, the manner in which some…

  15. Scientific Representation and Science Learning

    Science.gov (United States)

    Matta, Corrado

    2014-01-01

    In this article I examine three examples of philosophical theories of scientific representation with the aim of assessing which of these is a good candidate for a philosophical theory of scientific representation in science learning. The three candidate theories are Giere's intentional approach, Suárez's inferential approach and Lynch and…

  16. Congruence properties of induced representations

    DEFF Research Database (Denmark)

    Mayer, Dieter; Momeni, Arash; Venkov, Alexei

    In this paper we study representations of the projective modular group induced from the Hecke congruence group of level 4 with Selberg's character. We show that the well known congruence properties of Selberg's character are equivalent to the congruence properties of the induced representations...

  17. University Students' Representations of Study.

    Science.gov (United States)

    Volet, Simone E.; Lawrence, Jeanette A.

    1988-01-01

    Five women university students' representations of their learning were analyzed and related to their on-going adaptations to course demands. Representations involved their goals, working plans and perceptions of difficulties. Qualitative data from students' accounts were tabulated schematically in relation to Duncker's concepts of productive…

  18. Combinatorial representations of token sequences

    NARCIS (Netherlands)

    Elzinga, C.H.

    2005-01-01

    This paper presents new representations of token sequences, with and without associated quantities, in Euclidean space. The representations are free of assumptions about the nature of the sequences or the processes that generate them. Algorithms and applications from the domains of structured

  19. Electrocorticographic Representations of Segmental Features in Continuous Speech

    Directory of Open Access Journals (Sweden)

    Fabien eLotte

    2015-02-01

    Full Text Available Acoustic speech output results from coordinated articulation of dozens of muscles, bones and cartilages of the vocal mechanism. While we commonly take the fluency and speed of our speech productions for granted, the neural mechanisms facilitating the requisite muscular control are not completely understood. Previous neuroimaging and electrophysiology studies of speech sensorimotor control has typically concentrated on speech sounds (i.e., phonemes, syllables and words in isolation; sentence-length investigations have largely been used to inform coincident linguistic processing. In this study, we examined the neural representations of segmental features (place and manner of articulation, and voicing status in the context of fluent, continuous speech production. We used recordings from the cortical surface (electrocorticography (ECoG to simultaneously evaluate the spatial topography and temporal dynamics of the neural correlates of speech articulation that may mediate the generation of hypothesized gestural or articulatory scores. We found that the representation of place of articulation involved broad networks of brain regions during all phases of speech production: preparation, execution and monitoring. In contrast, manner of articulation and voicing status were dominated by auditory cortical responses after speech had been initiated. These results provide a new insight into the articulatory and auditory processes underlying speech production in terms of their motor requirements and acoustic correlates.

  20. Electrocorticographic representations of segmental features in continuous speech.

    Science.gov (United States)

    Lotte, Fabien; Brumberg, Jonathan S; Brunner, Peter; Gunduz, Aysegul; Ritaccio, Anthony L; Guan, Cuntai; Schalk, Gerwin

    2015-01-01

    Acoustic speech output results from coordinated articulation of dozens of muscles, bones and cartilages of the vocal mechanism. While we commonly take the fluency and speed of our speech productions for granted, the neural mechanisms facilitating the requisite muscular control are not completely understood. Previous neuroimaging and electrophysiology studies of speech sensorimotor control has typically concentrated on speech sounds (i.e., phonemes, syllables and words) in isolation; sentence-length investigations have largely been used to inform coincident linguistic processing. In this study, we examined the neural representations of segmental features (place and manner of articulation, and voicing status) in the context of fluent, continuous speech production. We used recordings from the cortical surface [electrocorticography (ECoG)] to simultaneously evaluate the spatial topography and temporal dynamics of the neural correlates of speech articulation that may mediate the generation of hypothesized gestural or articulatory scores. We found that the representation of place of articulation involved broad networks of brain regions during all phases of speech production: preparation, execution and monitoring. In contrast, manner of articulation and voicing status were dominated by auditory cortical responses after speech had been initiated. These results provide a new insight into the articulatory and auditory processes underlying speech production in terms of their motor requirements and acoustic correlates.

  1. Experience-driven formation of parts-based representations in a model of layered visual memory

    Directory of Open Access Journals (Sweden)

    Jenia Jitsev

    2009-09-01

    Full Text Available Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.

  2. Reconstructing dynamic mental models of facial expressions in prosopagnosia reveals distinct representations for identity and expression.

    Science.gov (United States)

    Richoz, Anne-Raphaëlle; Jack, Rachael E; Garrod, Oliver G B; Schyns, Philippe G; Caldara, Roberto

    2015-04-01

    The human face transmits a wealth of signals that readily provide crucial information for social interactions, such as facial identity and emotional expression. Yet, a fundamental question remains unresolved: does the face information for identity and emotional expression categorization tap into common or distinct representational systems? To address this question we tested PS, a pure case of acquired prosopagnosia with bilateral occipitotemporal lesions anatomically sparing the regions that are assumed to contribute to facial expression (de)coding (i.e., the amygdala, the insula and the posterior superior temporal sulcus--pSTS). We previously demonstrated that PS does not use information from the eye region to identify faces, but relies on the suboptimal mouth region. PS's abnormal information use for identity, coupled with her neural dissociation, provides a unique opportunity to probe the existence of a dichotomy in the face representational system. To reconstruct the mental models of the six basic facial expressions of emotion in PS and age-matched healthy observers, we used a novel reverse correlation technique tracking information use on dynamic faces. PS was comparable to controls, using all facial features to (de)code facial expressions with the exception of fear. PS's normal (de)coding of dynamic facial expressions suggests that the face system relies either on distinct representational systems for identity and expression, or dissociable cortical pathways to access them. Interestingly, PS showed a selective impairment for categorizing many static facial expressions, which could be accounted for by her lesion in the right inferior occipital gyrus. PS's advantage for dynamic facial expressions might instead relate to a functionally distinct and sufficient cortical pathway directly connecting the early visual cortex to the spared pSTS. Altogether, our data provide critical insights on the healthy and impaired face systems, question evidence of deficits

  3. Pre-attentive, context-specific representation of fear memory in the auditory cortex of rat.

    Science.gov (United States)

    Funamizu, Akihiro; Kanzaki, Ryohei; Takahashi, Hirokazu

    2013-01-01

    Neural representation in the auditory cortex is rapidly modulated by both top-down attention and bottom-up stimulus properties, in order to improve perception in a given context. Learning-induced, pre-attentive, map plasticity has been also studied in the anesthetized cortex; however, little attention has been paid to rapid, context-dependent modulation. We hypothesize that context-specific learning leads to pre-attentively modulated, multiplex representation in the auditory cortex. Here, we investigate map plasticity in the auditory cortices of anesthetized rats conditioned in a context-dependent manner, such that a conditioned stimulus (CS) of a 20-kHz tone and an unconditioned stimulus (US) of a mild electrical shock were associated only under a noisy auditory context, but not in silence. After the conditioning, although no distinct plasticity was found in the tonotopic map, tone-evoked responses were more noise-resistive than pre-conditioning. Yet, the conditioned group showed a reduced spread of activation to each tone with noise, but not with silence, associated with a sharpening of frequency tuning. The encoding accuracy index of neurons showed that conditioning deteriorated the accuracy of tone-frequency representations in noisy condition at off-CS regions, but not at CS regions, suggesting that arbitrary tones around the frequency of the CS were more likely perceived as the CS in a specific context, where CS was associated with US. These results together demonstrate that learning-induced plasticity in the auditory cortex occurs in a context-dependent manner.

  4. Pre-attentive, context-specific representation of fear memory in the auditory cortex of rat.

    Directory of Open Access Journals (Sweden)

    Akihiro Funamizu

    Full Text Available Neural representation in the auditory cortex is rapidly modulated by both top-down attention and bottom-up stimulus properties, in order to improve perception in a given context. Learning-induced, pre-attentive, map plasticity has been also studied in the anesthetized cortex; however, little attention has been paid to rapid, context-dependent modulation. We hypothesize that context-specific learning leads to pre-attentively modulated, multiplex representation in the auditory cortex. Here, we investigate map plasticity in the auditory cortices of anesthetized rats conditioned in a context-dependent manner, such that a conditioned stimulus (CS of a 20-kHz tone and an unconditioned stimulus (US of a mild electrical shock were associated only under a noisy auditory context, but not in silence. After the conditioning, although no distinct plasticity was found in the tonotopic map, tone-evoked responses were more noise-resistive than pre-conditioning. Yet, the conditioned group showed a reduced spread of activation to each tone with noise, but not with silence, associated with a sharpening of frequency tuning. The encoding accuracy index of neurons showed that conditioning deteriorated the accuracy of tone-frequency representations in noisy condition at off-CS regions, but not at CS regions, suggesting that arbitrary tones around the frequency of the CS were more likely perceived as the CS in a specific context, where CS was associated with US. These results together demonstrate that learning-induced plasticity in the auditory cortex occurs in a context-dependent manner.

  5. A Novel Method of Case Representation and Retrieval in CBR for E-Learning

    Science.gov (United States)

    Khamparia, Aditya; Pandey, Babita

    2017-01-01

    In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the…

  6. Towards learning domain-general representations for language from multi-modal data

    NARCIS (Netherlands)

    Kadar, Akos; Chrupala, Grzegorz; Alishahi, Afra

    2015-01-01

    Recurrent neural networks (RNN) have gained a reputation for producing state-of-the-art results on many NLP tasks and for producing representations of words, phrases and larger linguistic units that encode complex syntactic and semantic structures. Recently these types of models have also been used

  7. Fuzzy Morphological Polynomial Image Representation

    Directory of Open Access Journals (Sweden)

    Chin-Pan Huang

    2010-01-01

    Full Text Available A novel signal representation using fuzzy mathematical morphology is developed. We take advantage of the optimum fuzzy fitting and the efficient implementation of morphological operators to extract geometric information from signals. The new representation provides results analogous to those given by the polynomial transform. Geometrical decomposition of a signal is achieved by windowing and applying sequentially fuzzy morphological opening with structuring functions. The resulting representation is made to resemble an orthogonal expansion by constraining the results of opening to equate adapted structuring functions. Properties of the geometric decomposition are considered and used to calculate the adaptation parameters. Our procedure provides an efficient and flexible representation which can be efficiently implemented in parallel. The application of the representation is illustrated in data compression and fractal dimension estimation temporal signals and images.

  8. Multiple representations in physics education

    CERN Document Server

    Duit, Reinders; Fischer, Hans E

    2017-01-01

    This volume is important because despite various external representations, such as analogies, metaphors, and visualizations being commonly used by physics teachers, educators and researchers, the notion of using the pedagogical functions of multiple representations to support teaching and learning is still a gap in physics education. The research presented in the three sections of the book is introduced by descriptions of various psychological theories that are applied in different ways for designing physics teaching and learning in classroom settings. The following chapters of the book illustrate teaching and learning with respect to applying specific physics multiple representations in different levels of the education system and in different physics topics using analogies and models, different modes, and in reasoning and representational competence. When multiple representations are used in physics for teaching, the expectation is that they should be successful. To ensure this is the case, the implementati...

  9. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  10. 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.

  11. Neural markers of opposite-sex bias in face processing

    Directory of Open Access Journals (Sweden)

    Alice Mado eProverbio

    2010-10-01

    Full Text Available Some behavioral and neuroimaging studies suggest that adults prefer to view attractive faces of the opposite sex more than attractive faces of the same sex. However, unlike the other-race face effect (ORE; Caldara et al., 2004, little is known regarding the existence of an opposite-/same-sex bias in face processing. In this study, the faces of 130 attractive male and female adults were foveally presented to 40 heterosexual university students (20 men and 20 women who were engaged in a secondary perceptual task (landscape detection. The automatic processing of face gender was investigated by recording ERPs from 128 scalp sites. Neural markers of opposite- vs. same-sex bias in face processing included larger and earlier centro-parietal N400s in response to faces of the opposite sex and a larger late positivity (LP to same-sex faces. Analysis of intra-cortical neural generators (swLORETA showed that facial processing-related (FG, BA37, BA20/21 and emotion-related brain areas (the right parahippocampal gyrus, BA35; uncus, BA36/38; and the cingulate gyrus, BA24 had higher activations in response to opposite- than same-sex faces. The results of this analysis, along with data obtained from ERP recordings, support the hypothesis that both genders process opposite-sex faces differently than same-sex faces. The data also suggest a hemispheric asymmetry in the processing of opposite-/same-sex faces, with the right hemisphere involved in processing same-sex faces and the left hemisphere involved in processing faces of the opposite sex. The data support previous literature suggesting a right lateralization for the representation of self-image and body awareness.

  12. Biphasic influence of Miz1 on neural crest development by regulating cell survival and apical adhesion complex formation in the developing neural tube

    Science.gov (United States)

    Kerosuo, Laura; Bronner, Marianne E.

    2014-01-01

    Myc interacting zinc finger protein-1 (Miz1) is a transcription factor known to regulate cell cycle– and cell adhesion–related genes in cancer. Here we show that Miz1 also plays a critical role in neural crest development. In the chick, Miz1 is expressed throughout the neural plate and closing neural tube. Its morpholino-mediated knockdown affects neural crest precursor survival, leading to reduction of neural plate border and neural crest specifier genes Msx-1, Pax7, FoxD3, and Sox10. Of interest, Miz1 loss also causes marked reduction of adhesion molecules (N-cadherin, cadherin6B, and α1-catenin) with a concomitant increase of E-cadherin in the neural folds, likely leading to delayed and decreased neural crest emigration. Conversely, Miz1 overexpression results in up-regulation of cadherin6B and FoxD3 expression in the neural folds/neural tube, leading to premature neural crest emigration and increased number of migratory crest cells. Although Miz1 loss effects cell survival and proliferation throughout the neural plate, the neural progenitor marker Sox2 was unaffected, suggesting a neural crest–selective effect. The results suggest that Miz1 is important not only for survival of neural crest precursors, but also for maintenance of integrity of the neural folds and tube, via correct formation of the apical adhesion complex therein. PMID:24307680

  13. Archival Representation in the Digital Age

    Science.gov (United States)

    Zhang, Jane

    2012-01-01

    This study analyzes the representation systems of three digitized archival collections using the traditional archival representation framework of provenance, order, and content. The results of the study reveal a prominent role of provenance representation, a compromised role of order representation, and an active role of content representation in…

  14. Aging Disrupts the Neural Transformations that Link Facial Identity Across Views

    Science.gov (United States)

    Habak, Claudine; Wilkinson, Frances; Wilson, Hugh R.

    2016-01-01

    Healthy human aging can have adverse effects on cortical function and on the brain’s ability to integrate visual information to form complex representations. Facial identification is crucial to successful social discourse, and yet, it remains unclear whether the neuronal mechanisms underlying face perception per se, and the speed with which they process information, change with age. We present face images whose discrimination relies strictly on the shape and geometry of a face at various stimulus durations. Interestingly, we demonstrate that facial identity matching is maintained with age when faces are shown in the same view (e.g. front-front or side-side), regardless of exposure duration, but degrades when faces are shown in different views (e.g. front and turned 20° to the side) and does not improve at longer durations. Our results indicate that perceptual processing speed for complex representations and the mechanisms underlying same-view facial identity discrimination are maintained with age. In contrast, information is degraded in the neural transformations that represent facial identity across views. We suggest that the accumulation of useful information over time to refine a representation within a population of neurons saturates earlier in the aging visual system than it does in the younger system and contributes to the age-related deterioration of face discrimination across views. PMID:18054981

  15. Neural Network Model of memory retrieval

    Directory of Open Access Journals (Sweden)

    Stefano eRecanatesi

    2015-12-01

    Full Text Available Human memory can store large amount of information. Nevertheless, recalling is often achallenging task. In a classical free recall paradigm, where participants are asked to repeat abriefly presented list of words, people make mistakes for lists as short as 5 words. We present amodel for memory retrieval based on a Hopfield neural network where transition between itemsare determined by similarities in their long-term memory representations. Meanfield analysis ofthe model reveals stable states of the network corresponding (1 to single memory representationsand (2 intersection between memory representations. We show that oscillating feedback inhibitionin the presence of noise induces transitions between these states triggering the retrieval ofdifferent memories. The network dynamics qualitatively predicts the distribution of time intervalsrequired to recall new memory items observed in experiments. It shows that items having largernumber of neurons in their representation are statistically easier to recall and reveals possiblebottlenecks in our ability of retrieving memories. Overall, we propose a neural network model ofinformation retrieval broadly compatible with experimental observations and is consistent with ourrecent graphical model (Romani et al., 2013.

  16. Differential dorsal and ventral medial prefrontal representations of the implicit self modulated by individualism and collectivism: An fMRI study.

    Science.gov (United States)

    Harada, Tokiko; Li, Zhang; Chiao, Joan Y

    2010-01-01

    Individualism and collectivism, or self-construal style, refer to cultural values that influence how people think about themselves and their relation to the social and physical environment. Recent neuroimaging evidence suggests that cultural values of individualism and collectivism dynamically modulate neural response within cortical midline structures, such as the medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC), during explicit self-evaluation. However, it remains unknown whether cultural priming modulates neural response during self-evaluation due to explicit task demands. Here we investigated how cultural priming of self-construal style affects neural activity within cortical midline structures during implicit self-evaluation in bicultural individuals. Results indicate that ventral MPFC showed relatively less deactivation during implicit evaluation of both self- and father-relevant information as compared to control condition (e.g., information of an unfamiliar person), irrespective of cultural priming. By contrast, dorsal MPFC showed relatively less deactivation during implicit evaluation of father-relevant information, but not self-relevant information, as compared to control condition, only when they were primed with individualism. Furthermore, dorsal MPFC showed relatively less deactivation during implicit evaluation of father-relevant information as compared to self-relevant condition only when they were primed with individualism. Hence, our results indicate that cultural priming modulates neural response within dorsal, but not ventral, portions of MPFC in a stimulus-driven rather than task-driven manner. More broadly, these findings suggest that cultural values dynamically shape neural representations during the evaluation, rather than the detection, of self-relevant information.

  17. Islam and Media Representations

    Directory of Open Access Journals (Sweden)

    Mohamed Bensalah

    2006-04-01

    Full Text Available For the author of this article, the media’s treatment of Islam has raised numerous polymorphous questions and debates. Reactivated by the great scares of current events, the issue, though an ancient one, calls many things into question. By way of introduction, the author tries to analyse the complex processes of elaboration and perception of the representations that have prevailed during the past century. In referring to the semantic decoding of the abundant colonial literature and iconography, the author strives to translate the extreme xenophobic tensions and the identity crystallisations associated with the current media orchestration of Islam, both in theWest and the East. He then evokes the excesses of the media that are found at the origin of many amalgams wisely maintained between Islam, Islamism and Islamic terrorism, underscoring their duplicity and their willingness to put themselves, consciously, in service to deceivers and directors of awareness, who are very active at the heart of the politico-media sphere. After levelling a severe accusation against the harmful drifts of the media, especially in times of crisis and war, the author concludes by asserting that these tools of communication, once they are freed of their masks and invective apparatuses, can be re-appropriated by new words and bya true communication between peoples and cultures.

  18. Neural encoding of the speech envelope by children with developmental dyslexia.

    Science.gov (United States)

    Power, Alan J; Colling, Lincoln J; Mead, Natasha; Barnes, Lisa; Goswami, Usha

    2016-09-01

    Developmental dyslexia is consistently associated with difficulties in processing phonology (linguistic sound structure) across languages. One view is that dyslexia is characterised by a cognitive impairment in the "phonological representation" of word forms, which arises long before the child presents with a reading problem. Here we investigate a possible neural basis for developmental phonological impairments. We assess the neural quality of speech encoding in children with dyslexia by measuring the accuracy of low-frequency speech envelope encoding using EEG. We tested children with dyslexia and chronological age-matched (CA) and reading-level matched (RL) younger children. Participants listened to semantically-unpredictable sentences in a word report task. The sentences were noise-vocoded to increase reliance on envelope cues. Envelope reconstruction for envelopes between 0 and 10Hz showed that the children with dyslexia had significantly poorer speech encoding in the 0-2Hz band compared to both CA and RL controls. These data suggest that impaired neural encoding of low frequency speech envelopes, related to speech prosody, may underpin the phonological deficit that causes dyslexia across languages. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  19. Separating neural activity associated with emotion and implied motion: An fMRI study.

    Science.gov (United States)

    Kolesar, Tiffany A; Kornelsen, Jennifer; Smith, Stephen D

    2017-02-01

    Previous research provides evidence for an emo-motoric neural network allowing emotion to modulate activity in regions of the nervous system related to movement. However, recent research suggests that these results may be due to the movement depicted in the stimuli. The purpose of the current study was to differentiate the unique neural activity of emotion and implied motion using functional MRI. Thirteen healthy participants viewed 4 sets of images: (a) negative stimuli implying movement, (b) negative stimuli not implying movement, (c) neutral stimuli implying movement, and (d) neutral stimuli not implying movement. A main effect for implied motion was found, primarily in regions associated with multimodal integration (bilateral insula and cingulate), and visual areas that process motion (bilateral middle temporal gyrus). A main effect for emotion was found primarily in occipital and parietal regions, indicating that emotion enhances visual perception. Surprisingly, emotion also activated the left precentral gyrus, a motor region. These results demonstrate that emotion elicits activity above and beyond that evoked by the perception of implied movement, but that the neural representations of these characteristics overlap. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  20. Explicit representation of confidence informs future value-based decisions

    DEFF Research Database (Denmark)

    Folke, Tomas; Jacobsen, Catrine; Fleming, Stephen M.

    2016-01-01

    follow a more consistent pattern (fewer transitivity violations). Finally, by tracking participants’ eye movements, we demonstrate that lower-level gaze dynamics can track uncertainty but do not directly impact changes of mind. These results suggest that an explicit and accurate representation......Humans can reflect on decisions and report variable levels of confidence. But why maintain an explicit representation of confidence for choices that have already been made and therefore cannot be undone? Here we show that an explicit representation of confidence is harnessed for subsequent changes...... of confidence has a positive impact on the quality of future value-based decisions....

  1. Diffeomorphism Group Representations in Relativistic Quantum Field Theory

    Energy Technology Data Exchange (ETDEWEB)

    Goldin, Gerald A. [Rutgers Univ., Piscataway, NJ (United States); Sharp, David H. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-12-20

    We explore the role played by the di eomorphism group and its unitary representations in relativistic quantum eld theory. From the quantum kinematics of particles described by representations of the di eomorphism group of a space-like surface in an inertial reference frame, we reconstruct the local relativistic neutral scalar eld in the Fock representation. An explicit expression for the free Hamiltonian is obtained in terms of the Lie algebra generators (mass and momentum densities). We suggest that this approach can be generalized to elds whose quanta are spatially extended objects.

  2. Patterns of multiple representation use by experts and novices during physics problem solving

    Directory of Open Access Journals (Sweden)

    Patrick B. Kohl

    2008-06-01

    Full Text Available It is generally believed that students should use multiple representations in solving certain physics problems, and earlier work in PER has begun to outline how experts and novices differ in their use of multiple representations. In this study, we build on this foundation by interviewing expert and novice physicists as they solve two types of multiple representation problems: those in which multiple representations are provided for them and those in which the students must construct their own representations. We analyze in detail the types of representations subjects use and the order and manner in which they are used. Expert and novice representation use is surprisingly similar in some ways, especially in that both experts and novices make significant use of multiple representations. Some significant differences also emerge. Experts are more flexible in terms of starting point and move between the available representations more quickly, and novices tend to move between more representations in total. In addition, we find that an examination of how often and when multiple representations are used is inadequate to fully characterize a problem-solving episode; one must also consider the purpose behind the use of the available representations. This analysis of how experts and novices use representations sharpens the differences between the two groups, demonstrates analysis techniques that may be useful in future work, and suggests possible paths for instruction.

  3. Distributed Neural Processing Predictors of Multi-dimensional Properties of Affect

    Directory of Open Access Journals (Sweden)

    Keith A. Bush

    2017-09-01

    Full Text Available Recent evidence suggests that emotions have a distributed neural representation, which has significant implications for our understanding of the mechanisms underlying emotion regulation and dysregulation as well as the potential targets available for neuromodulation-based emotion therapeutics. This work adds to this evidence by testing the distribution of neural representations underlying the affective dimensions of valence and arousal using representational models that vary in both the degree and the nature of their distribution. We used multi-voxel pattern classification (MVPC to identify whole-brain patterns of functional magnetic resonance imaging (fMRI-derived neural activations that reliably predicted dimensional properties of affect (valence and arousal for visual stimuli viewed by a normative sample (n = 32 of demographically diverse, healthy adults. Inter-subject leave-one-out cross-validation showed whole-brain MVPC significantly predicted (p < 0.001 binarized normative ratings of valence (positive vs. negative, 59% accuracy and arousal (high vs. low, 56% accuracy. We also conducted group-level univariate general linear modeling (GLM analyses to identify brain regions whose response significantly differed for the contrasts of positive versus negative valence or high versus low arousal. Multivoxel pattern classifiers using voxels drawn from all identified regions of interest (all-ROIs exhibited mixed performance; arousal was predicted significantly better than chance but worse than the whole-brain classifier, whereas valence was not predicted significantly better than chance. Multivoxel classifiers derived using individual ROIs generally performed no better than chance. Although performance of the all-ROI classifier improved with larger ROIs (generated by relaxing the clustering threshold, performance was still poorer than the whole-brain classifier. These findings support a highly distributed model of neural processing for the

  4. Distributed Neural Processing Predictors of Multi-dimensional Properties of Affect.

    Science.gov (United States)

    Bush, Keith A; Inman, Cory S; Hamann, Stephan; Kilts, Clinton D; James, G Andrew

    2017-01-01

    Recent evidence suggests that emotions have a distributed neural representation, which has significant implications for our understanding of the mechanisms underlying emotion regulation and dysregulation as well as the potential targets available for neuromodulation-based emotion therapeutics. This work adds to this evidence by testing the distribution of neural representations underlying the affective dimensions of valence and arousal using representational models that vary in both the degree and the nature of their distribution. We used multi-voxel pattern classification (MVPC) to identify whole-brain patterns of functional magnetic resonance imaging (fMRI)-derived neural activations that reliably predicted dimensional properties of affect (valence and arousal) for visual stimuli viewed by a normative sample (n = 32) of demographically diverse, healthy adults. Inter-subject leave-one-out cross-validation showed whole-brain MVPC significantly predicted (p < 0.001) binarized normative ratings of valence (positive vs. negative, 59% accuracy) and arousal (high vs. low, 56% accuracy). We also conducted group-level univariate general linear modeling (GLM) analyses to identify brain regions whose response significantly differed for the contrasts of positive versus negative valence or high versus low arousal. Multivoxel pattern classifiers using voxels drawn from all identified regions of interest (all-ROIs) exhibited mixed performance; arousal was predicted significantly better than chance but worse than the whole-brain classifier, whereas valence was not predicted significantly better than chance. Multivoxel classifiers derived using individual ROIs generally performed no better than chance. Although performance of the all-ROI classifier improved with larger ROIs (generated by relaxing the clustering threshold), performance was still poorer than the whole-brain classifier. These findings support a highly distributed model of neural processing for the affective

  5. Evidence for multiple, distinct representations of the human body.

    Science.gov (United States)

    Schwoebel, John; Coslett, H Branch

    2005-04-01

    Previous data from single-case and small group studies have suggested distinctions among structural, conceptual, and online sensorimotor representations of the human body. We developed a battery of tasks to further examine the prevalence and anatomic substrates of these body representations. The battery was administered to 70 stroke patients. Fifty-one percent of the patients were impaired relative to controls on at least one body representation measure. Further, principal components analysis of the patient data as well as direct comparisons of patient and control performance suggested a triple dissociation between measures of the 3 putative body representations. Consistent with previous distinctions between the "what" and "how" pathways, lesions of the left temporal lobe were most consistently associated with impaired performance on tasks assessing knowledge of the shape or lexical-semantic information about the body, whereas lesions of the dorsolateral frontal and parietal regions resulted in impaired performance on tasks requiring on-line coding of body posture.

  6. Electrophysiological correlates of refreshing: Event-related potentials associated with directing reflective attention to face, scene, or word representations

    Science.gov (United States)

    Johnson, Matthew R.; McCarthy, Gregory; Muller, Kathleen A.; Brudner, Samuel N.; Johnson, Marcia K.

    2016-01-01

    Refreshing is the component cognitive process of directing reflective attention to one of several active mental representations. Previous studies using functional magnetic resonance imaging (fMRI) suggested that refresh tasks involve a component process of initiating refreshing as well as the top-down modulation of representational regions central to refreshing. However, those studies were limited by fMRI’s low temporal resolution. In the present study, we used electroencephalography (EEG) to examine the timecourse of refreshing on the scale of milliseconds rather than seconds. Event-related potential (ERP) analyses showed that a typical refresh task does have a distinct electrophysiological response as compared to a control condition, and includes at least two main temporal components: an earlier (~400ms) positive peak reminiscent of a P3 response, and a later (~800ms–1400ms) sustained positivity over several sites reminiscent of the late directing attention positivity (LDAP). Overall, the evoked potentials for refreshing representations from three different visual categories (faces, scenes, words) were similar, but multivariate pattern analysis (MVPA) showed that some category information was nonetheless present in the EEG signal. When related to previous fMRI studies, these results are consistent with a two-phase model, with the first phase dominated by frontal control signals involved in initiating refreshing and the second by the top-down modulation of posterior perceptual cortical areas that constitutes refreshing a representation. This study also lays the foundation for future studies of the neural correlates of reflective attention at a finer temporal resolution than is possible using fMRI. PMID:25961640

  7. The neural subjective frame: from bodily signals to perceptual consciousness

    Science.gov (United States)

    Park, Hyeong-Dong; Tallon-Baudry, Catherine

    2014-01-01

    The report ‘I saw the stimulus’ operationally defines visual consciousness, but where does the ‘I’ come from? To account for the subjective dimension of perceptual experience, we introduce the concept of the neural subjective frame. The neural subjective frame would be based on the constantly updated neural maps of the internal state of the body and constitute a neural referential from which first person experience can be created. We propose to root the neural subjective frame in the neural representation of visceral information which is transmitted through multiple anatomical pathways to a number of target sites, including posterior insula, ventral anterior cingulate cortex, amygdala and somatosensory cortex. We review existing experimental evidence showing that the processing of external stimuli can interact with visceral function. The neural subjective frame is a low-level building block of subjective experience which is not explicitly experienced by itself which is necessary but not sufficient for perceptual experience. It could also underlie other types of subjective experiences such as self-consciousness and emotional feelings. Because the neural subjective frame is tightly linked to homeostatic regulations involved in vigilance, it could also make a link between state and content consciousness. PMID:24639580

  8. Seeding neural progenitor cells on silicon-based neural probes.

    Science.gov (United States)

    Azemi, Erdrin; Gobbel, Glenn T; Cui, Xinyan Tracy

    2010-09-01

    showed differentiation potential similar to those grown on polylysine-treated well plates, as previously reported. Viable (still expressing GFP) NPCs were found on and in proximity to the neural implant after 1 and 7 days postimplantation. Preliminary examinations indicated that the probe's NPC coating might reduce the glial response at these 2 different time points. The authors' findings suggest that NPCs can differentiate and strongly adhere to laminin-immobilized surfaces, providing a stable matrix for these cells to be implanted in brain tissue on the neural probe's surface. In addition, NPCs were found to improve the astrocytic reaction around the implant site. Further in vivo work revealing the mechanisms of this effect could lead to improvement of biocompatibility and chronic recording performance of neural probes.

  9. From Local to Global Additive Representation

    NARCIS (Netherlands)

    Wakker, P.P.; Chateauneuf, A.

    1993-01-01

    This paper studies continuous additive representations of transitive preferences on connected subdomains of product sets. Contrary to what has sometimes been thought, local additive representability does not imply global additive representability. It is shown that the result can nevertheless be

  10. From local to global additive representation

    NARCIS (Netherlands)

    A. Chateauneuf (Alain); P.P. Wakker (Peter)

    1993-01-01

    textabstractThis paper studies continuous additive representations of transitive preferences on connected subdomains of product sets. Contrary to what has sometimes been thought, local additive representability does not imply global additive representability. It is shown that the result can

  11. Toward a Multilevel Cognitive Probabilistic Representation of Space

    OpenAIRE

    Tapus, A.; Vasudevan, S.; Siegwart, R.

    2005-01-01

    This paper addresses the problem of perception and representation of space for a mobile agent. A probabilistic hierarchical framework is suggested as a solution to this problem. The method proposed is a combination of probabilistic belief with “Object Graph Models”(OGM). The world is viewed from a topological optic, in terms of objects and relationships between them. The hierarchical representation that we propose permits an efficient and reliable modeling of the information that the mobile a...

  12. Towards a Cognitive Probabilistic Representation of Space for Mobile Robots

    OpenAIRE

    Vasudevan, Shrihari; Nguyen, Viet; Siegwart, Roland Y.

    2006-01-01

    Robots are rapidly evolving from factory “workhorses” to “robot-companions”. The future of robots, as our companions, is highly dependent on their abilities to understand, interpret and represent the environment in an efficient and consistent fashion, in a way that is comprehensible to humans. This paper is oriented in this direction. It suggests a hierarchical probabilistic representation of space that is based on objects. A global topological representation of places with object graphs s...

  13. Intrinsic resonance representation of quantum mechanics

    DEFF Research Database (Denmark)

    Carioli, M.; Heller, E.J.; Møller, Klaus Braagaard

    1997-01-01

    an optimal representation, based purely on classical mechanics. ''Hidden'' constants of the motion and good actions already known to the classical mechanics are thus incorporated into the basis, leaving the quantum effects to be isolated and included by small matrix diagonalizations. This simplifies......The choice of basis states in quantum calculations can be influenced by several requirements, and sometimes a very natural basis suggests itself. However often one retreats to a ''merely complete'' basis, whose coefficients in the eigenstates carry Little physical insight. We suggest here...

  14. Neural Predictors of Visuomotor Adaptation Rate and Multi-Day Savings

    Science.gov (United States)

    Cassady, Kaitlin; Ruitenberg, Marit; Koppelmans, Vincent; Reuter-Lorenz, Patricia; De Dios, Yiri; Gadd, Nichole; Wood, Scott; Riascos Castenada, Roy; Kofman, Igor; Bloomberg, Jacob; hide

    2017-01-01

    Recent studies of sensorimotor adaptation have found that individual differences in task-based functional brain activation are associated with the rate of adaptation and savings at subsequent sessions. However, few studies to date have investigated offline neural predictors of adaptation and multi-day savings. In the present study, we explore whether individual differences in the rate of visuomotor adaptation and multi-day savings are associated with differences in resting state functional connectivity and gray matter volume. Thirty-four participants performed a manual adaptation task during two separate test sessions, on average 9 days apart. We found that resting state functional connectivity strength between sensorimotor, anterior cingulate, and temporoparietal areas of the brain was a significant predictor of adaptation rate during the early, cognitive phase of practice. In contrast, default mode network functional connectivity strength was found to predict late adaptation rate and savings on day two, which suggests that these behaviors may rely on overlapping processes. We also found that gray matter volume in temporoparietal and occipital regions was a significant predictor of early learning, whereas gray matter volume in superior posterior regions of the cerebellum was a significant predictor of late adaptation. The results from this study suggest that offline neural predictors of early adaptation facilitate the cognitive mechanisms of sensorimotor adaptation, with support from by the involvement of temporoparietal and cingulate networks. In contrast, the neural predictors of late adaptation and savings, including the default mode network and the cerebellum, likely support the storage and modification of newly acquired sensorimotor representations. These findings provide novel insights into the neural processes associated with individual differences in sensorimotor adaptation.

  15. Animal Reasoning: Negation and Representations of Absence.

    Directory of Open Access Journals (Sweden)

    Morales Ladrón de Guevara, Jorge

    2011-05-01

    Full Text Available In this paper I reject the possibility that animal reasoning, negation in particular, necessarily involves the representation of Absence, as suggested by José Luis Bermúdez, since this would still work as a logical negation (unavailable for non-linguistic creatures. False belief, pretense, and communication experiments show that non-human animals (at least some primates have difficulties representing absent entities or properties. I offer an alternative account resorting to the sub-symbolic similarity judgments proposed by Vigo & Allen and I introduce the notion of expectation: animal proto-negation takes place through the incompatibility between an expected and the actual representation. Finally, I propose that the paradigm of expectations can be extrapolated to other experiments in cognitive psychology (both with pre-linguistic children and animals in order to design “fair” experiments which test other minds considering their true abilities.

  16. Functional Plasticity of Odor Representations during Motherhood

    Directory of Open Access Journals (Sweden)

    Amit Vinograd

    2017-10-01

    Full Text Available Motherhood is accompanied by new behaviors aimed at ensuring the wellbeing of the offspring. Olfaction plays a key role in guiding maternal behaviors during this transition. We studied functional changes in the main olfactory bulb (OB of mothers in mice. Using in vivo two-photon calcium imaging, we studied the sensory representation of odors by mitral cells (MCs. We show that MC responses to monomolecular odors become sparser and weaker in mothers. In contrast, responses to biologically relevant odors are spared from sparsening or strengthen. MC responses to mixtures and to a range of concentrations suggest that these differences between odor responses cannot be accounted for by mixture suppressive effects or gain control mechanisms. In vitro whole-cell recordings show an increase in inhibitory synaptic drive onto MCs. The increase of inhibitory tone may contribute to the general decrease in responsiveness and concomitant enhanced representation of specific odors.

  17. Toward a brain-based componential semantic representation.

    Science.gov (United States)

    Binder, Jeffrey R; Conant, Lisa L; Humphries, Colin J; Fernandino, Leonardo; Simons, Stephen B; Aguilar, Mario; Desai, Rutvik H

    2016-01-01

    Componential theories of lexical semantics assume that concepts can be represented by sets of features or attributes that are in some sense primitive or basic components of meaning. The binary features used in classical category and prototype theories are problematic in that these features are themselves complex concepts, leaving open the question of what constitutes a primitive feature. The present availability of brain imaging tools has enhanced interest in how concepts are represented in brains, and accumulating evidence supports the claim that these representations are at least partly "embodied" in the perception, action, and other modal neural systems through which concepts are experienced. In this study we explore the possibility of devising a componential model of semantic representation based entirely on such functional divisions in the human brain. We propose a basic set of approximately 65 experiential attributes based on neurobiological considerations, comprising sensory, motor, spatial, temporal, affective, social, and cognitive experiences. We provide normative data on the salience of each attribute for a large set of English nouns, verbs, and adjectives, and show how these attribute vectors distinguish a priori conceptual categories and capture semantic similarity. Robust quantitative differences between concrete object categories were observed across a large number of attribute dimensions. A within- versus between-category similarity metric showed much greater separation between categories than representations derived from distributional (latent semantic) analysis of text. Cluster analyses were used to explore the similarity structure in the data independent of a priori labels, revealing several novel category distinctions. We discuss how such a representation might deal with various longstanding problems in semantic theory, such as feature selection and weighting, representation of abstract concepts, effects of context on semantic retrieval, and

  18. Representation of identities and the politics of representation in cognition

    Directory of Open Access Journals (Sweden)

    Kanavillil Rajagopalan

    2001-02-01

    Full Text Available

    In this paper, I make a plea for viewing representation as first and foremost a political matter. I argue that by so doing we may avoid the many of pitfalls of contemporary theories of cognition as they attempt to tackle the issue of representation. Most of these problems have to do with the fact that representation is treated exclusively as a mimetic or theatrical question. The fact of the matter is however that representation also has a political dimension. Indeed it has always had this political dimension which, counterintuitive though it may seem at first glimpse, manifests itself even in very the attempt to aestheticise the whole issue of representation (as in some versions of postmodernism or to deny its role altogether as a tertium quid between the external world and the cognising mind (as in contemporary neo-pragmatism. I also contend that, by recognising the political nature of representation, we also pave the way for endorsing the thesis that the mind is a social construct, thereby taking some steam out of the thesis of "mind-brain identity" (so-called "identity theory of mind".

  19. Identification of the non-linear systems using internal recurrent neural networks

    Directory of Open Access Journals (Sweden)

    Bogdan CODRES

    2006-12-01

    Full Text Available In the past years utilization of neural networks took a distinct ampleness because of the following properties: distributed representation of information, capacity of generalization in case of uncontained situation in training data set, tolerance to noise, resistance to partial destruction, parallel processing. Another major advantage of neural networks is that they allow us to obtain the model of the investigated system, systems that is not necessarily to be linear. In fact, the true value of neural networks is seen in the case of identification and control of nonlinear systems. In this paper there are presented some identification techniques using neural networks.

  20. The Representation of Prediction Error in Auditory Cortex

    Science.gov (United States)

    Rubin, Jonathan; Ulanovsky, Nachum; Tishby, Naftali

    2016-01-01

    To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence. PMID:27490251