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coding processes involved in the cortical representation of complex tactile stimuli

JOURNAL OF PHYSIOLOGY-PARIS 2007年第1-3期101卷 22-31页

作者： Blanc, Jean-Luc Coq, Jacques-Olivier Univ Aix Marseille 1 CNRS UMR 6149 Ctr St Charles F-13331 Marseille 03 France

To understand how information is coded in the primary somatosensory cortex (S I) we need to decipher the relationship between neural activity and tactile stimuli. Such a relationship can be formally measured by mutual information. The present study was designed to determine how S1 neuronal populations code for the multidimensional kinetic features (i.e. random, time-varying patterns of force) of complex tactile stimuli, applied at different locations of the rat forepaw. More precisely, the stimulus localization and feature extraction were analyzed as two independent processes, using both rate coding and temporal coding strategies. To model the process of stimulus kinetic feature extraction, multidimensional stimuli were projected onto lower dimensional subspace and then clustered according to their similarity. Different combinations of stimuli clustering were applied to differentiate each stimulus identification process. Information analyses show that both processes are synergistic, this synergy is enhanced within the temporal coding framework. The stimulus localization process is faster than the stimulus feature extraction process. The latter provides more information quantity with rate coding strategy, whereas the localization process maximizes the mutual information within the temporal coding framework. Therefore, combining mutual information analysis with robust clustering of complex stimuli provides a framework to study neural coding mechanisms related to complex stimuli discrimination. (C) 2007 Elsevier Ltd. All rights reserved.

关键词： information theory neural coding stimulus feature extraction primary somatosensory cortex

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Ghost resonance in a pool of heterogeneous neurons

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BIOSYSTEMS 2007年第1-3期89卷 166-172页

作者： Balenzuela, Pablo Garcia-Ojalvo, Jordi Manjarrez, Elias Martinez, Lourdes Mirasso, Claudio R. Univ Politecn Cataluna Dept Fis & Engn Nucl E-08222 Terrassa Spain Univ Buenos Aires Fac Ciencias Exactas & Nat Dept Fis Ciudad Univ RA-1428 Buenos Aires DF Argentina Benemer Univ Autonoma Puebla Inst Fisiol Puebla 72570 Mexico Univ Illes Balears Dept Fis E-07122 Palma de Mallorca Spain

We numerically study the subharmonic response of a heterogeneous pool of neurons to a pair of independent inputs. The neurons are stimulated with periodic pulse trains of frequencies f(1) = 2 Hz and f(2) = 3 Hz, and with inharmonic pulses whose frequencies f(1) and f(2) are equally shifted an amount Delta f. When both inputs are subthreshold, we find that the neurons respond at a frequency equal to f(2) - f(1) in the harmonic situation (Delta f = 0), that increases linearly with Delta f in the inharmonic case. Thus the neurons detect a frequency not present in the input;this effect is termed "ghost resonance". When one of the inputs is slightly suprathreshold the ghost resonance persists, but responses related with,the frequency of the suprathreshold input also emerge. This behavior must be taken into account in experimental studies of signal integration and coincidence detection by neuronal pools. (C) 2006 Elsevier Ireland Ltd. All rights reserved.

关键词： neuronal dynamics neural coding signal integration coincidence detection pitch perception

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Dynamic programming algorithms for comparing multineuronal spike trains via cost-based metrics and alignments

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JOURNAL OF NEUROSCIENCE METHODS 2007年第2期161卷 351-360页

作者： Victor, Jonathan D. Goldberg, David H. Gardner, Daniel Cornell Univ Weill Med Coll Dept Neurol & Neurosci New York NY 10021 USA Cornell Univ Weill Med Coll Dept Physiol & Biophys Lab Neuroinformat New York NY 10021 USA

Cost-based metrics formalize notions of distance, or dissimilarity, between two spike trains, and are applicable to single- and multineuronal responses. As such, these metrics have been used to characterize neural variability and neural coding. By examining the structure of an efficient algorithm [Aronov D, 2003. Fast algorithm for the metric-space analysis of simultaneous responses of multiple single neurons. J Neurosci Methods 124(2), 175-79] implementing a metric for multineuronal responses, we determine criteria for its generalization, and identify additional efficiencies that are applicable when related dissimilarity measures are computed in parallel. The generalized algorithm provides the means to test a wide range of coding hypotheses. (C) 2006 Elsevier B.V. All rights reserved.

关键词： neural coding spike trains metric space sequence comparison informatics

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Mode changes in activity of single neurons in anterior insular cortex across trials during multi-trial reward schedules

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NEUROSCIENCE RESEARCH 2007年第4期57卷 587-591页

作者： Mizuhiki, Takashi Richmond, Baffy J. Shidara, Munetaka Univ Tsukuba Grad Sch Comprehens Human Sci Tsukuba Ibaraki 3058577 Japan Natl Inst Adv Ind Sci & Technol Neurosci Res Inst Tsukuba Ibaraki 3058568 Japan NIMH Neuropsychol Lab NIH Dept Hlth & Human Serv Bethesda MD 20892 USA

We previously showed that spike count response distributions in anterior cingulate neurons can be fitted by a mixture of a few Poisson distributions in our reward schedule task. Here we report that the neuronal responses in insular cortex, an area connected to anterior cingulate cortex, can also be nicely fitted. The ratio of Poisson distributions changed with schedule progress, suggesting that neuronal responses in these areas fall into discrete firing modes. More insular neurons show mode changes across the schedules. The selection of firing modes might be related to cognitive processes, but seems independent across the two areas. (c) 2007 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

关键词： single unit spike count Poisson distribution neural coding response variability rhesus monkey reward expectancy

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Temporal sub units in dendritic trees

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BIOSYSTEMS 2007年第2-3期87卷 172-178页

作者： Griffin, M. Halliday, D. M. Univ York Dept Elect York YO10 5DD N Yorkshire England

This simulation study examines the possibility that dendritic sub units can be defined according to temporal aspects in the timing of populations of synaptic inputs. A two cell model with passive dendritic trees is used, which is subject to both common and independent synaptic inputs, the presence of common synaptic input results in a tendency for correlated firing in the two cell model. The strength of this correlation is used to measure the efficacy of the common synaptic inputs in modulating the output discharge of each neurone. Our results suggest that a small fraction of the total synaptic input can effectively modulate the timing of output spikes, this phenomenon is not dependent on the physical location of the inputs on the dendritic tree. This phenomenon depends on the presence of temporal correlation between the pre-synaptic spike trains that provide the common input. We propose to refer to these as temporal sub units. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

关键词： dendritic subunits correlation coherence neural coding simulation

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Point process adaptive filters for neural data analysis: Theory and applications

Point process adaptive filters for neural data analysis: The...

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46th IEEE Conference on Decision and Control

作者： Eden, Uri T. Boston Univ Dept Math & Stat Boston MA 02214 USA

ISBN: (纸本)9781424414970

Although it is well known that neurons receive, process and transmit signals via sequences of sudden stereotyped electrical events, called action potentials or spikes, many analyses of neural data ignore the highly localized nature of these events. We discuss a point process modeling framework for neural systems to perform inference, assess goodness-of-fit, and estimate a state variable from spiking observations. Under this framework, we develop state space estimation and inference algorithms by constructing state models that describe the stochastic evolution of the signals to estimate, and conditional intensity models that define the probability distribution of observing a particular sequence of spike times for a neuron or ensemble. Posterior densities can then be computed using a recursive Bayesian framework combined with the Chapman-Kolmogorov system of equations for discrete-time analyses or the forward Kolmogorov equation for continuous-time analyses. This allows us to derive a toolbox of estimation algorithms and adaptive filters to address questions of static and dynamic encoding and decoding. We discuss the application of these modeling and estimation methods to the problem of predicting an intended reaching arm movement from simulated neurons in primate primary motor cortex. We show that a Bayesian approximate Gaussian filter is able to maintain accurate estimates of intended arm trajectories.

关键词： adaptive filters Bayesian estimation neural coding point processes

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A biologically inspired model for signal compression

A biologically inspired model for signal compression

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Conference on Biomedical Applications of Micro- and Nanoengineering

作者： McDonnell, Mark D. Abbott, Derek Univ Adelaide Sch Elect & Elect Engn Ctr Biomed Engn Adelaide SA 5005 Australia

ISBN: (纸本)9780819465245

A model of a biological sensory neuron stimulated by a noisy analog information source is considered. It is demonstrated that action-potential generation by the neuron model can be described in terms of lossy compression theory. Lossy compression is generally characterized by (i) how much distortion is introduced, on average, due to a loss of information, and (ii) the 'rate.' or the amount of compression. Conventional compression theory is used to measure the performance of the model in terms of both distortion and rate, and the tradeoff between each. The model's applicability to a number of situations relevant to biomedical engineering, including cochlear implants, and bio-sensors is discussed.

关键词： lossy compression quantization cochlear implants biosensors neural coding bioinspired compression

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Optimal coding of a random stimulus by a population of parallel neuron models

Optimal coding of a random stimulus by a population of paral...

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Conference on Noise and Fluctuations in Biological, Biophysical, and Biomedical Systems

作者： McDonnell, Mark D. Stocks, Nigel G. Abbott, Derek Univ Adelaide Ctr Biomed Engn CBME Adelaide SA 5005 Australia Univ Adelaide Sch Elect & Elect Engn Adelaide SA 5005 Australia Univ Warwick Sch Engn Coventry CV4 7AL W Midlands England

ISBN: (纸本)9780819467393

We examine the question of how a population of independently noisy sensory neurons should be configured to optimize the encoding of a random stimulus into sequences of neural action potentials. For the case where firing rates are the same in all neurons, we consider the problem of optimizing the noise distribution for a known stimulus distribution, and the converse problem of optimizing the stimulus for a given noise distribution. This work is related to suprathreshold stochastic resonance (SSR). It is shown that, for a large number of neurons, the SSR model is equivalent to a single rate-coding neuron with multiplicative output noise.

关键词： neural coding population coding suprathreshold stochastic resonance information theory noisy neurons

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Point Process Adaptive Filters for neural Data Analysis: Theory and Applications

Point Process Adaptive Filters for Neural Data Analysis: The...

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Proceedings of the 46th IEEE Conference on Decision and Control, Pages 4135-4592

作者： Uri T. Eden The Department of Mathematics and Statistics Boston University Boston MA USA

ISBN: (纸本)9781424414970;1424414970

关键词： Adaptive Filters Bayesian Estimation neural coding Point Processes

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neural coding of spatial phase in V1 of the macaque monkey

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JOURNAL OF NEUROPHYSIOLOGY 2003年第6期89卷 3304-3327页

作者： Aronov, D Reich, DS Mechler, F Victor, JD Cornell Univ Weill Med Coll Dept Neurol & Neurosci New York NY 10021 USA Columbia Univ Dept Biol Sci New York NY 10027 USA Johns Hopkins Univ Johns Hopkins Hosp Dept Radiol Baltimore MD 21287 USA Johns Hopkins Univ Johns Hopkins Hosp Dept Neurol Baltimore MD 21287 USA Rockefeller Univ New York NY 10021 USA

We examine the responses of single neurons and pairs of neurons, simultaneously recorded with a single tetrode in the primary visual cortex of the anesthetized macaque monkey, to transient presentations of stationary gratings of varying spatial phase. Such simultaneously recorded neurons tended to have similar tuning to the phase of the grating. To determine the response features that reliably discriminate these stimuli, we use the metric-space approach extended to pairs of neurons. We find that paying attention to the times of individual spikes, at a resolution of similar to30 ms, and keeping track of which neuron fires which spike rather than just the summed local activity contribute substantially to phase coding. The contribution is both quantitative (increasing the fidelity of phase coding) and qualitative (enabling a 2-dimensional "response space" that corresponds to the spatial phase cycle). We use a novel approach, the extraction of "temporal profiles" from the metric space analysis, to interpret and compare temporal coding across neurons. Temporal profiles were remarkably consistent across a large subset of neurons. This consistency indicates that simple mechanisms (e.g., comparing the size of the transient and sustained components of the response) allow the temporal contribution to phase coding to be decoded.

关键词： .two-dimensional macaque interval modulated monkey spike train Spatial Phase neural coding

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