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Temporally dynamic frequency tuning of population responses in monkey primary auditory cortex

HEARING RESEARCH 2009年第1-2期254卷 64-76页

作者： Fishman, Yonatan I. Steinschneider, Mitchell Albert Einstein Coll Med Rose F Kennedy Ctr Dept Neurol Bronx NY 10461 USA Albert Einstein Coll Med Rose F Kennedy Ctr Dept Neurosci Bronx NY 10461 USA

Frequency tuning of auditory cortical neurons is typically determined by integrating spikes over the entire duration of a tone stimulus. However, this approach may mask functionally significant variations in tuning over the time course of the response. To explore this possibility, frequency response functions (FRFs) based on population multiunit activity evoked by pure tones of 175 or 200 ms duration were examined within four time windows relative to stimulus onset corresponding to "on" (10-30 ms), "early sustained" (30-100 ms), "late sustained" (100-175 ms), and "off" (185-235 or 210-260 ms) portions of responses in primary auditory cortex (A1) of 5 awake macaques. FRFs of "on" and "early sustained" responses displayed a good concordance, with best frequencies (BFs) differing, on average, by less than 0.25 octaves. In contrast, FRFs of "on" and "late sustained" responses differed considerably, with a mean difference in BF of 0.68 octaves. At many sites, tuning of "off' responses was inversely related to that of "on" responses, with "off" FRFs displaying a trough at the BF of "on" responses. Inversely correlated "on" and "off' FRFs were more common at sites with a higher "on" BF, thus suggesting functional differences between sites with low and high "on" BF. These results indicate that frequency tuning of population responses in A1 may vary considerably over the course of the response to a tone, thus revealing a temporal dimension to the representation of sound spectrum in A1. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Auditory cortex Spectral tuning Tonotopic organization Onset response Sustained response Off response population coding

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Neural coding of categories: information efficiency and optimal population codes

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2008年第1期25卷 169-187页

作者： Bonnasse-Gahot, Laurent Nadal, Jean-Pierre Ecole Hautes Etud Sci Sociales CNRS UMR 8557 CAMS F-75270 Paris 06 France ENS Paris 6 Paris 7 CNRS UMR 8550 Lab Phys Stat F-75231 Paris France

This paper deals with the analytical study of coding a discrete set of categories by a large assembly of neurons. We consider population coding schemes, which can also be seen as instances of exemplar models proposed in the literature to account for phenomena in the psychophysics of categorization. We quantify the coding efficiency by the mutual information between the set of categories and the neural code, and we characterize the properties of the most efficient codes, considering different regimes corresponding essentially to different signal-to-noise ratio. One main outcome is to find that, in a high signal-to-noise ratio limit, the Fisher information at the population level should be the greatest between categories, which is achieved by having many cells with the stimulus-discriminating parts (steepest slope) of their tuning curves placed in the transition regions between categories in stimulus space. We show that these properties are in good agreement with both psychophysical data and with the neurophysiology of the inferotemporal cortex in the monkey, a cortex area known to be specifically involved in classification tasks.

关键词： categorization population coding exemplar models mutual information inferotemporal cortex

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Learning Complex population-Coded Sequences

Learning Complex Population-Coded Sequences

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19th International Conference on Artificial Neural Networks (ICANN 2009)

作者： Byadarhaly, Kiran V. Perdoor, Mithun Vasa, Suresh Fernandez, Emmanuel Minai, Ali A. Univ Cincinnati Dept Elect & Comp Engn Cincinnati OH 45221 USA

ISBN: (纸本)9783642042737

In humans and primates, the sequential structure of complex actions is apparently learned at an abstract "cognitive" level in several regions of the frontal cortex, independent of the control of the immediate effectors by the motor system. At this level, actions are represented in terms of kinematic parameters especially direction of end effector movement and encoded using population codes. Muscle force signals are generated from this representation by downstream systems in the motor cortex and the spinal cord. In this paper, we consider the problem of learning population-coded kinematic sequences in an abstract neural network model of the medial frontal cortex. For concreteness, the sequences are represented as line drawings in a two-dimensional workspace. Learning such sequences presents several challenges because of the internal complexity of the individual sequences and extensive overlap between sequences. We show that, by using a simple module-selection mechanism, our model is capable of learning multiple sequences with complex structure and very high cross-sequence similarity.

关键词： Sequence learning population coding motor system

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Bayesian population decoding of spiking neurons

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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2009年第2009期3卷 21-21页

作者： Gerwinn, Sebastian Macke, Jakob Bethge, Matthias Max Planck Inst Biol Cybernet Computat Vis & Neurosci Grp D-72076 Tubingen Germany

The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.

关键词： Bayesian decoding population coding spiking neurons approximate inference

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population coding of self-motion: Applying Bayesian analysis to a population of visual Interneurons in the fly

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JOURNAL OF NEUROPHYSIOLOGY 2005年第3期94卷 2182-2194页

作者： Karmeier, K Krapp, HG Egelhaaf, M Univ Bielefeld Lehrstuhl Neurobiol D-33501 Bielefeld Germany Univ Cambridge Dept Zool Cambridge England

coding of sensory information often involves the activity of neuronal populations. We demonstrate how the accuracy of a population code depends on integration time, the size of the population, and noise correlation between the participating neurons. The population we study consists of 10 identified visual interneurons in the blowfly Calliphora vicina involved in optic flow processing. These neurons are assumed to encode the animal's head or body rotations around horizontal axes by means of graded potential changes. From electrophysiological experiments we obtain parameters for modeling the neurons' responses. From applying a Bayesian analysis on the modeled population response we draw three major conclusions. First, integration of neuronal activities over a time period of only 5 ms after response onset is sufficient to decode accurately the rotation axis. Second, noise correlation between neurons has only little impact on the population's performance. And third, although a population of only two neurons would be sufficient to encode any horizontal rotation axis, the population of 10 vertical system neurons is advantageous if the available integration time is short. For the fly, short integration times to decode neuronal responses are important when controlling rapid flight maneuvers.

关键词： .visual system applying fly Bayesian Analysis interneurons Exp Biol motion information self-motion population coding van Hateren Warzecha population of Visual

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Neural representations that support invariant object recognition

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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2009年第2009期3卷 3-3页

作者： Goris, Robbe L. T. Op de Beeck, Hans P. Univ Louvain Expt Psychol Lab Tiensestr 102 B-3000 Louvain Belgium

Neural mechanisms underlying invariant behaviour such as object recognition are not well understood. For brain regions critical for object recognition, such as inferior temporal cortex (ITC), there is now ample evidence indicating that single cells code for many stimulus aspects, implying that only a moderate degree of invariance is present. However, recent theoretical and empirical work seems to suggest that integrating responses of multiple non-invariant units may produce invariant representations at population level. We provide an explicit test for the hypothesis that a linear read-out mechanism of a pool of units resembling ITC neurons may achieve invariant performance in an identification task. A linear classifier was trained to decode a particular value in a 2-D stimulus space using as input the response pattern across a population of units. Only one dimension was relevant for the task, and the stimulus location on the irrelevant dimension (ID) was kept constant during training. In a series of identification tests, the stimulus location on the relevant dimension (RD) and ID was manipulated, yielding estimates for both the level of sensitivity and tolerance reached by the network. We studied the effects of several single-cell characteristics as well as population characteristics typically considered in the literature, but found little support for the hypothesis. While the classifier averages out effects of idiosyncratic tuning properties and inter-unit variability, its invariance is very much determined by the (hypothetical) 'average' neuron. Consequently, even at population level there exists a fundamental trade-off between selectivity and tolerance, and invariant behaviour does not emerge spontaneously.

关键词： object recognition inferior temporal cortex population coding multidimensional tuning

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Linear ensemble-coding in midbrain superior colliculus specifies the saccade kinematics

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BIOLOGICAL CYBERNETICS 2008年第6期98卷 561-577页

作者： van Opstal, A. J. Goossens, H. H. L. M. Radboud Univ Nijmegen Donders Inst Neurosi Med Ctr Dept Biophys NL-6525 EZ Nijmegen Netherlands Radboud Univ Nijmegen Donders Inst Neurosi Dept Biophys NL-6525 EZ Nijmegen Netherlands

Recently, we proposed an ensemble-coding scheme of the midbrain superior colliculus (SC) in which, during a saccade, each spike emitted by each recruited SC neuron contributes a fixed minivector to the gaze-control motor output. The size and direction of this 'spike vector' depend exclusively on a cell's location within the SC motor map (Goossens and Van Opstal, in J Neurophysiol 95: 2326-2341, 2006). According to this simple scheme, the planned saccade trajectory results from instantaneous linear summation of all spike vectors across the motor map. In our simulations with this model, the brainstem saccade generator was simplified by a linear feedback system, rendering the total model (which has only three free parameters) essentially linear. Interestingly, when this scheme was applied to actually recorded spike trains from 139 saccade-related SC neurons, measured during thousands of eye movements to single visual targets, straight saccades resulted with the correct velocity profiles and nonlinear kinematic relations ('main sequence properties' and 'component stretching'). Hence, we concluded that the kinematic nonlinearity of saccades resides in the spatial-temporal distribution of SC activity, rather than in the brainstem burst generator. The latter is generally assumed in models of the saccadic system. Here we analyze how this behaviour might emerge from this simple scheme. In addition, we will show new experimental evidence in support of the proposed mechanism.

关键词： saccades spatial accuracy population coding nonlinearity main sequence monkey

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Linking neurons to behavior in multisensory perception: A computational review

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BRAIN RESEARCH 2008年 1242卷 4-12页

作者： Ma, Wei Ji Pouget, Alexandre Univ Rochester Dept Brain & Cognit Sci Rochester NY 14627 USA

A large body of psychophysical. and physiological findings has characterized how information is integrated across multiple senses. This work has focused on two major issues: how do we integrate information, and when do we integrate, i.e., how do we decide if two signals come from the same source or different sources. Recent studies suggest that humans and animals use Bayesian strategies to solve both problems. With regard to how to integrate, computational studies have also started to shed light on the neural basis of this Bayes-optimal computation, suggesting that, if neuronal variability is Poisson-like, a simple linear combination of population activity is all that is required for optimality. We review both sets of developments, which together lay out a path towards a complete neural theory of multisensory perception. (c) 2008 Elsevier B.V. All rights reserved.

关键词： Multisensory integration Cue combination Computational modeling population coding Neural variability Superadditivity Segregation

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Communication call-evoked gamma-band activity in the auditory cortex of awake bats is modified by complex acoustic features

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BRAIN RESEARCH 2008年第1期1188卷 76-86页

作者： Medvedev, Andrei V. Kanwal, Jagmeet S. Georgetown Univ Med Ctr Dept Phys & Biophys Washington DC 20057 USA

Mustached bats emit an acoustically rich variety of calls for social communication. In the posterior primary auditory cortex, activity of neural ensembles measured as local field potentials (LFPs) can uniquely encode each call type. Here we report that LFPs recorded in response to calls contain oscillatory activity in the gamma-band frequency range (> 20 Hz). The power spectrum of these high-frequency oscillations shows either two peaks of energy (at 40 Hz and 100 Hz), or just one peak at 40 Hz. The relative power of gamma-band activity in the power spectrum of a call-evoked UP correlates significantly with the 'harmonic complexity' of a call. Gamma-band activity is attenuated with reversal of frequency-modulated calls. Amplitude modulation, even when asymmetric across call reversals, has no significant effect on gamma-band activity. These results provide the first experimental evidence that complex features within different groups of species-specific calls modify the power spectrum of evoked gamma-band activity. (c) 2007 Elsevier B.V. All rights reserved.

关键词： speech music gamma-band oscillations synchrony temporal coding population coding binding hearing auditory processing sensory and motor systems

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A study of the science of taste: On the origins and influence of the core ideas

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BEHAVIORAL AND BRAIN SCIENCES 2008年第1期31卷 59-+页

作者： Erickson, Robert P. Duke Univ Dept Psychol Durham NC 27708 USA Duke Univ Dept Neurosci Durham NC 27708 USA Duke Univ Dept Neurobiol Durham NC 27708 USA

Our understanding of the sense of taste is largely based on research designed and interpreted in terms of the traditional four "basic" tastes: sweet, sour, salty, and bitter, and now a few more. This concept of basic tastes has no rational definition to test, and thus it has not been tested. As a demonstration, a preliminary attempt to test one common but arbitrary psychophysical definition of basic tastes is included in this article;that the basic tastes are unique in being able to account for other tastes. This definition was falsified in that other stimuli do about as well as the basic words and stimuli. To the extent that this finding might show analogies with other studies of receptor, neural, and psychophysical phenomena, the validity of the century-long literature of the science of taste based on a few "basics" is called into question. The possible origins, meaning, and influence of this concept are discussed. Tests of the model with control studies are suggested in all areas of taste related to basic tastes. As a stronger alternative to the basic tradition, the advantages of the across-fiber pattern model are discussed;it is based on a rational data-based hypothesis, and has survived attempts at falsification. Such "population coding" has found broad acceptance in many neural systems.

关键词： across-fiber pattern basic tastes distributed neural coding population coding psychophysics receptors reductionism systems biology taste

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