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IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Martins, Jaime A. Rodrigues, J. M. F. du Buf, J. M. H. Univ Algarve Inst Syst & Robot Vis Lab FCT Faro Portugal

ISBN: (纸本)9781467307536

Depth information using the biological Disparity Energy Model can be obtained by using a population of complex cells. This model explicitly involves cell parameters like their spatial frequency, orientation, binocular phase and position difference. However, this is a mathematical model. Our brain does not have access to such parameters, it can only exploit responses. Therefore, we use a new model for encoding disparity information implicitly by employing a trained binocular neuronal population. This model allows to decode disparity information in a way similar to how our visual system could have developed this ability, during evolution, in order to accurately estimate disparity of entire scenes.

关键词： disparity population coding learning biological model

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A Neural Network Model for Categorical Effects in Color Memory

A Neural Network Model for Categorical Effects in Color Memo...

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16th International Symposium on Artificial Life and Robotics (AROB 16th '11)

作者： Imai, Chihiro Tajima, Satohiro Aihara, Kazuyuki Suzuki, Hideyuki Univ Tokyo Meguro Ku 4-6-1 Komaba Tokyo 1538505 Japan NHK Japan Broadcasting Corp Nagano Stn Nagano Nagano 3808502 Japan

ISBN: (纸本)9784990288051

Human color perception is categorical. Previous experimental studies have shown that the color category has profound effects on cortical neural responses, perceptual color discrimination and color memory. However, existing theoretical studies are not enough to provide an inclusive model accounting for those categorical effects in color perception and memory. In this study, we propose a computational model for categorical color processing, where the color memory is represented by a population of color selective neurons in cortex Our model reproduces the characteristics of color memory reported in the previous experimental studies. Furthermore, it explains the properties of neurons in IT cortex, which change the activity depending on whether the task demands is color categorization or discrimination. This study suggests that perceptual biases found in color processing and task-dependent modulations of neural responses may be explained as a natural consequence of statistically optimal estimation.

关键词： color memory categorical color population coding

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Increased pattern separation in the aged fascia dentata

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NEUROBIOLOGY OF AGING 2011年第12期32卷 2317.e23-2317.e32页

作者： Marrone, Diano F. Adams, Allison A. Satvat, Elham Wilfrid Laurier Univ Dept Psychol Waterloo ON N2L 3C5 Canada Univ Arizona McKnight Brain Inst Tucson AZ 85719 USA

One prominent impairment associated with aging is a deficit in the ability of the hippocampus to form stable contextual representations. Place-specific firing in granule cells of the fascia dentata (FD) is thought to aid the formation of multiple stable memory representations by disambiguating similar experiences (a process termed pattern separation), such as when an animal repeatedly enters similar environments or contexts. Using zif268/egr1 as a marker of cellular activity, we show that aged animals, which have altered place maps in other areas of the hippocampal formation, also show altered granule cell activity during multiple visits to similar environments. That is, the FD of aged animals is more likely to recruit distinct granule cell populations, and thus show greater pattern separation, during two visits to similar (or even the same) environments. However, if two highly distinct environments are visited, this age-related increase in pattern separation is no longer apparent. Moreover, increased pattern separation in similar environments correlates with decline in the ability of aged animals to disambiguate similar contexts in a sequential spatial recognition task. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Aging Granule cell Hippocampal function Imaging Learning and memory population coding

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A Neurophysiologically Plausible population Code Model for Feature Integration Explains Visual Crowding

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PLOS COMPUTATIONAL BIOLOGY 2010年第1期6卷 1-11页

作者： van den Berg, Ronald Roerdink, Jos B. T. M. Cornelissen, Frans W. Univ Groningen Inst Math & Comp Sci Groningen Netherlands Univ Groningen Univ Med Ctr Groningen Lab Expt Ophthalmol Groningen Netherlands Univ Groningen Sch Behav & Cognit Neurosci Groningen Netherlands

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

关键词： .population Code Spatial Integration Feature Integration Visual Crowding population coding

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Suprathreshold stochastic resonance induced by ion channel fluctuation

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PHYSICA D-NONLINEAR PHENOMENA 2010年第6期239卷 327-334页

作者： Ashida, Go Kubo, Masayoshi Univ Maryland Dept Biol College Pk MD 20742 USA Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

In this study, we examine the signal detection ability of an array of neurons with intrinsic channel fluctuation. Numerical simulations show that estimation of the input signal from the output spiking activity of the neuronal array is most accurate if a proper amount of channel noise exists. Theoretical calculation of the mutual and Fisher information confirms the effect of the noise-aided information transfer in the array, or the presence of suprathreshold stochastic resonance. These results indicate that the channel noise, which induces response variability, may play an essential role in population coding. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Noise Stochastic resonance Neuronal modeling Ion channel population coding Information theory

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Schema generation in recurrent neural nets for intercepting a moving target

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BIOLOGICAL CYBERNETICS 2010年第6期102卷 451-473页

作者： Fleischer, Andreas G. Univ Hamburg Dept Biol D-22527 Hamburg Germany

The grasping of a moving object requires the development of a motor strategy to anticipate the trajectory of the target and to compute an optimal course of interception. During the performance of perception-action cycles, a preprogrammed prototypical movement trajectory, a motor schema, may highly reduce the control load. Subjects were asked to hit a target that was moving along a circular path by means of a cursor. Randomized initial target positions and velocities were detected in the periphery of the eyes, resulting in a saccade toward the target. Even when the target disappeared, the eyes followed the target's anticipated course. The Gestalt of the trajectories was dependent on target velocity. The prediction capability of the motor schema was investigated by varying the visibility range of cursor and target. Motor schemata were determined to be of limited precision, and therefore visual feedback was continuously required to intercept the moving target. To intercept a target, the motor schema caused the hand to aim ahead and to adapt to the target trajectory. The control of cursor velocity determined the point of interception. From a modeling point of view, a neural network was developed that allowed the implementation of a motor schema interacting with feedback control in an iterative manner. The neural net of the Wilson type consists of an excitation-diffusion layer allowing the generation of a moving bubble. This activation bubble runs down an eye-centered motor schema and causes a planar arm model to move toward the target. A bubble provides local integration and straightening of the trajectory during repetitive moves. The schema adapts to task demands by learning and serves as forward controller. On the basis of these model considerations the principal problem of embedding motor schemata in generalized control strategies is discussed.

关键词： Schema theory Feedforward controller Interception of a moving target Eye-hand coordination Recurrent neural nets Neural field theory population coding

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Information-theoretic methods for studying population codes

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NEURAL NETWORKS 2010年第6期23卷 713-727页

作者： Ince, Robin A. A. Senatore, Riccardo Arabzadeh, Ehsan Montani, Fernando Diamond, Mathew E. Panzeri, Stefano Italian Inst Technol Dept Robot Brain & Cognit Sci I-16163 Genoa Italy Univ Manchester Fac Life Sci Manchester Lancs England Univ New S Wales Sch Psychol Sydney NSW Australia Univ Nacl La Plata IFLP La Plata Buenos Aires Argentina INIFTA La Plata Buenos Aires Argentina Italian Inst Technol SISSA Unit Trieste Italy Scuola Int Super Studi Avanzati Cognit Neurosci Sector Trieste Italy

population coding is the quantitative study of which algorithms or representations are used by the brain to combine together and evaluate the messages carried by different neurons. Here, we review an information-theoretic approach to population coding. We first discuss how to compute the information carried by simultaneously recorded neural populations, and in particular how to reduce the limited sampling bias which affects the calculation of information from a limited amount of experimental data. We then discuss how to quantify the contribution of individual members of the population, or the interaction between them, to the overall information encoded by the considered group of neurons. We focus in particular on evaluating what is the contribution of interactions up to any given order to the total information. We illustrate this formalism with applications to simulated data with realistic neuronal statistics and to real simultaneous recordings of multiple spike trains. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Mutual information Sampling bias population coding Somatosensory cortex

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A cortical model for binocular vergence control without explicit calculation of disparity

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NEUROCOMPUTING 2010年第7-9期73卷 1065-1073页

作者： Gibaldi, Agostino Chessa, Manuela Canessa, Andrea Sabatini, Silvio P. Solari, Fabio Univ Genoa Dept Biophys & Elect Engn I-16145 Genoa Italy

A computational model for the control of horizontal vergence, based on a population of disparity tuned complex cells, is presented. Since the population is able to extract the disparity map only in a limited range, using the map to drive vergence control means to limit its functionality inside this range. The model directly extracts the disparity-vergence response by combining the outputs of the disparity detectors without explicit calculation of the disparity map. The resulting vergence control yields to stable fixation and has small response time to a wide range of disparities. Experimental simulations with synthetic stimuli in depth validated the approach. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Vergence movements Retinal disparity population coding

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Multineuronal vectorization is more efficient than time-segmental vectorization for information extraction from neuronal activities in the inferior temporal cortex

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NEURAL NETWORKS 2010年第6期23卷 733-742页

作者： Kaneko, Hidekazu Tamura, Hiroshi Tate, Shunta Kawashima, Takahiro Suzuki, Shinya S. Fujita, Ichiro Natl Inst Adv Ind Sci & Technol Inst Human Sci & Biomed Engn Tsukuba Ibaraki 3058566 Japan Osaka Univ Grad Sch Frontier Biosci Lab Cognit Neurosci Osaka 5608531 Japan Japan Sci & Technol Agcy CREST Kawaguchi Saitama 3320012 Japan Toyohashi Univ Technol Cooperat Res Facil Ctr Toyohashi Aichi 4418580 Japan

In order for patients with disabilities to control assistive devices with their own neural activity, multineuronal spike trains must be efficiently decoded because only limited computational resources can be used to generate prosthetic control signals in portable real-time applications. In this study, we compare the abilities of two vectorizing procedures (multineuronal and time-segmental) to extract information from spike trains during the same total neuron-seconds. In the multineuronal vectorizing procedure, we defined a response vector whose components represented the spike counts of one to five neurons. In the time-segmental vectorizing procedure, a response vector consisted of components representing a neuron's spike counts for one to five time-segment(s) of a response period of 1 s. Spike trains were recorded from neurons in the inferior temporal cortex of monkeys presented with visual stimuli. We examined whether the amount of information of the visual stimuli carried by these neurons differed between the two vectorizing procedures. The amount of information calculated with the multineuronal vectorizing procedure, but not the time-segmental vectorizing procedure, significantly increased with the dimensions of the response vector. We conclude that the multineuronal vectorizing procedure is superior to the time-segmental vectorizing procedure in efficiently extracting information from neuronal signals. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Information theory Temporal coding population coding Decoding Single-unit recording Vision Inferior temporal cortex Brain-machine interface

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Sensory information in local field potentials and spikes from visual and auditory cortices: time scales and frequency bands

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2010年第3期29卷 533-545页

作者： Belitski, Andrei Panzeri, Stefano Magri, Cesare Logothetis, Nikos K. Kayser, Christoph Max Planck Inst Biol Cybernet D-72076 Tubingen Germany Italian Inst Technol Robot Brain & Cognit Sci Dept I-16163 Genoa Italy Univ Manchester Div Imaging Sci & Biomed Engn Manchester M13 9PT Lancs England

Studies analyzing sensory cortical processing or trying to decode brain activity often rely on a combination of different electrophysiological signals, such as local field potentials (LFPs) and spiking activity. Understanding the relation between these signals and sensory stimuli and between different components of these signals is hence of great interest. We here provide an analysis of LFPs and spiking activity recorded from visual and auditory cortex during stimulation with natural stimuli. In particular, we focus on the time scales on which different components of these signals are informative about the stimulus, and on the dependencies between different components of these signals. Addressing the first question, we find that stimulus information in low frequency bands (< 12 Hz) is high, regardless of whether their energy is computed at the scale of milliseconds or seconds. Stimulus information in higher bands (> 50 Hz), in contrast, is scale dependent, and is larger when the energy is averaged over several hundreds of milliseconds. Indeed, combined analysis of signal reliability and information revealed that the energy of slow LFP fluctuations is well related to the stimulus even when considering individual or few cycles, while the energy of fast LFP oscillations carries information only when averaged over many cycles. Addressing the second question, we find that stimulus information in different LFP bands, and in different LFP bands and spiking activity, is largely independent regardless of time scale or sensory system. Taken together, these findings suggest that different LFP bands represent dynamic natural stimuli on distinct time scales and together provide a potentially rich source of information for sensory processing or decoding brain activity.

关键词： Information theory Vision Audition population coding Oscillations Firing rates

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