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作者： Nandakumar S. Narayanan Mark Laubach

How do populations of neurons work together to control behavior? To study this issue, our group simultaneously records from populations of neurons across multiple electrodes in multiple brain regions during operant behavior. Here, we describe methods for quantifying the relationship between neuronal population activity and performance of operant behavioral tasks. We describe statistical techniques, based on time- and trial-shuffling, that can establish the significance of correlations between multiple and simultaneously recorded spike trains. Then, we describe several approaches to studying functional interactions between neurons, including principal component analysis, cross-correlation analysis, analyses of rate correlations, and analyses of shared predictive information. Finally, we compare these techniques using a sample data set and discuss how the combined use of these techniques can lead to novel insights regarding neuronal interactions during behavior. less

关键词： Principal Component Analysis MATLAB neural coding neural ensemble population activity correlated variability JPSTH multi-electrode recordings

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The power law of sensory adaptation: Simulation by a model of excitability in spider mechanoreceptor neurons

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ANNALS OF BIOMEDICAL ENGINEERING 2008年第1期36卷 153-161页

作者： French, Andrew S. Torkkeli, Paivi H. Dalhousie Univ Dept Physiol & Biophys Halifax NS B3H 1X5 Canada

The power law of sensory adaptation was introduced more than 50 years ago. It is characterized by action potential adaptation that follows fractional powers of time or frequency, rather than exponential decays and corresponding frequency responses. Power law adaptation describes the responses of a range of vertebrate and invertebrate sensory receptors to deterministic stimuli, such as steps or sinusoids, and to random (white noise) stimulation. Hypotheses about the physical basis of power law adaptation have existed since its discovery. Its cause remains enigmatic, but the site of power law adaptation has been located in the conversion of receptor potentials into action potentials in some preparations. Here, we used pseudorandom noise stimulation and direct spectral estimation to show that simulations containing only two voltage activated currents can reproduce the power law adaptation in two types of spider mechanoreceptors. Identical simulations were previously used to explain the different responses of these two types of sensory neurons to step inputs. We conclude that power law adaptation results during action potential encoding by nonlinear combination of a small number of activation and inactivation processes with different exponential time constants.

关键词： action potential neural coding information capacity ion channel Hodgkin-Huxley frequency response

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Comparing the Prefrontal Cortex of Rats and Primates: Insights from Electrophysiology

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NEUROTOXICITY RESEARCH 2008年第2-3期14卷 249-262页

作者： Seamans, Jeremy K. Lapish, Christopher C. Durstewitz, Daniel Univ British Columbia Dept Psychiat Vancouver BC V6T 2B5 Canada Univ British Columbia Brain Res Ctr Vancouver BC V6T 2B5 Canada Univ Plymouth Ctr Theoret & Computat Neurosci Plymouth PL4 8AA Devon England

There is a long-standing debate about whether rats have what could be considered a prefrontal cortex (PFC) and, if they do, what its primate homologue is. Anatomical evidence supports the view that the rat medial PFC is related to both the primate anterior cingulate cortex (ACC) and the dorsolateral PFC. Functionally the primate and human ACC are believed to be involved in the monitoring of actions and outcomes to guide decisions especially in challenging situations where cognitive conflict and errors arise. In contrast, the dorsolateral PFC is responsible for the maintenance and manipulation of goal-related items in memory in the service of planning, problem solving, and predicting forthcoming events. Recent multiple single-unit recording studies in rats have reported strong correlates of motor planning, movement and reward anticipation analogous to what has been observed in the primate ACC. There is also emerging evidence that rats may partly encode information over delays using body posture or variations in running path as embodied strategies, and that these are the aspects tracked by medial PFC neurons. The primate PFC may have elaborated on these rudimentary functions by carrying them over to more abstract levels of mental representation, more independent from somatic or other external mnemonic cues, and allowing manipulation of mental contents outside specific task contexts. Therefore, from an electrophysiological and computational perspective, the rat medial PFC seems to combine elements of the primate ACC and dorsolateral PFC at a rudimentary level. In primates, these functions may have formed the building blocks required for abstract rule encoding during the expansion of the cortex dorsolaterally.

关键词： Decision making Working memory Cell assemblies neural coding Higher cognition

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On the use of information theory for the analysis of the relationship between neural and imaging signals

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MAGNETIC RESONANCE IMAGING 2008年第7期26卷 1015-1025页

作者： Panzeri, Stefano Magri, Cesare Logothetis, Nikos K. Italian Inst Technol Robot Brain & Cognit Sci Dept I-16163 Genoa Italy Univ Manchester Fac Life Sci Manchester M60 1QD Lancs England Univ Milan Dipartimento Informat & Comunicaz I-20135 Milan Italy Max Planck Inst Biol Cybernet D-72076 Tubingen Germany Univ Manchester Manchester M13 9PT Lancs England

Functional magnetic resonance imaging (fMRI) is a widely used method for studying the neural basis of cognition and of sensory function. A potential problem in the interpretation of fMRI data is that fMRI measures neural activity only indirectly, as a local change of deoxyhemoglobin concentration due to the metabolic demands of neural function. To build Correct sensory and cognitive maps in the human brain, it is thus crucial to Understand whether fMRI and neural activity convey the same type of information about external correlates. While a substantial experimental effort has been devoted to the simultaneous recordings of hemodynamic and neural signals, so Far, the development of analysis method, that elucidate how neural and hemodynamic signals represent sensory information has received less attention. In this article, we critically review why the analytical framework of information theory, the mathematical theory of communication, is ideally suited to this purpose. We review the principles of information theory and explain how they could be applied to the analysis of fMRI and neural signals. We how that a critical advantage of information theory over more traditional analysis paradigms commonly used in the fMRI literature is that it can elucidate, within a single framework, whether an empirically observed correlation between neural and fMRI signals reflects either a similar stimulus tuning or a common source of variability unrelated to the external stimuli. In addition, information theory determines the extent to which these shared sources of stimulus signal and of variability lead PORI and neural signals to convey similar information about external correlates. We then illustrate the formalism by applying it to the analysis of the information carried by different bands of the local field potential. We conclude by discussing the current methodological challenges that need to be addressed to make the information-theoretic approach more robustly applicable to the si

关键词： BOLD local field potential neural coding

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Regulation of information passing by synaptic transmission: A short review

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BRAIN RESEARCH 2008年 1225卷 26-38页

作者： Di Maio, Vito CNR Ist Cibernet E Caianiello I-80078 Pozzuoli NA Italy

The largest part of information passed among neurons in the brain occurs by the means of chemical synapses connecting the axons of presynaptic neurons to the dendritic tree of the postsynaptic ones. In the present paper, the most relevant open problems related to the mechanisms of control of the information passing among neurons by synaptic transmission will be shortly reviewed. The "cross talking" between synapses, their mutual interactions and the control of the information flow between different areas of the dendritic tree will be also considered. The threshold mechanism based on the "reversal potential" will be considered for its role in the control of information transfer among neurons and also for its contribution to the information flow among different areas of the dendritic tree and to the computational ability of the single neuron. The concept of "competition for plasticity" will be proposed as a mechanism of competition based on the synaptic activation time. (C) 2008 Elsevier B.V. All rights reserved.

关键词： synaptic interaction synaptic integration neural coding neuronal modelling neural information processing synaptic competition

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Successful choice behavior is associated with distinct and coherent network states in anterior cingulate cortex

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2008年第33期105卷 11963-11968页

作者： Lapish, Christopher C. Durstewitz, Daniel Chandler, L. Judson Seamans, Jeremy K. Univ Plymouth Ctr Theoret & Computat Neurosci Vancouver BC PL4 8AA Canada Med Univ S Carolina Dept Neurosci Charleston SC 29425 USA Univ British Columbia Dept Psychiat Vancouver BC V6T 2BS Canada Univ British Columbia Brain Res Ctr Vancouver BC V6T 2BS Canada

Successful decision making requires an ability to monitor contexts, actions, and outcomes. The anterior cingulate cortex (ACC) is thought to be critical for these functions, monitoring and guiding decisions especially in challenging situations involving conflict and errors. A number of different single-unit correlates have been observed in the ACC that reflect the diverse cognitive components involved. Yet how ACC neurons function as an integrated network is poorly understood. Here we show, using advanced population analysis of multiple single-unit recordings from the rat ACC during performance of an ecologically valid decision-making task, that ensembles of neurons move through different coherent and dissociable states as the cognitive requirements of the task change. This organization into distinct network patterns with respect to both firing-rate changes and correlations among units broke down during trials with numerous behavioral errors, especially at choice points of the task. These results point to an underlying functional organization into cell assemblies in the ACC that may monitor choices, outcomes, and task contexts, thus tracking the animal's progression through "task space."

关键词： cell assemblies decision making multiple single-unit recordings neural coding population analysis

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Signal compression in biological sensory systems: Information theoretic performance limits

Signal compression in biological sensory systems: Informatio...

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Conference on BioMEMS and Nanotechnology III

作者： McDonnell, Mark D. Univ S Australia Inst Telecommun Res Mawson Lakes SA 5095 Australia

ISBN: (纸本)9780819469700

The intensity of analog stimuli, such as the loudness of sounds, is converted by our biological sensory systems into short duration electrical pulses in nerve fibres. These pulses are known as action potentials. In many cases, the transduction process that converts stimulus intensity into an action-potential encoding introduces significant randomness that appears to reduce the quality of the encoding. Due to this inherent random noise, it is the average rate at which action potentials are produced, rather than the instantaneous rate, that encodes stimulus amplitude. In this paper the limits of performance of this transduction process are analyzed using an information theoretic perspective of neural rate coding.

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

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Olfactory coding in the insect brain: molecular receptive ranges, spatial and temporal coding

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ENTOMOLOGIA EXPERIMENTALIS ET APPLICATA 2008年第1期128卷 81-92页

作者： Galizia, C. Giovanni Szyszka, Paul Univ Konstanz Dept Neurobiol D-78457 Constance Germany

Odor information is coded in the insect brain in a sequence of steps, ranging from the receptor cells, via the neural network in the antennal lobe, to higher order brain centers, among which the mushroom bodies and the lateral horn are the most prominent. Across all of these processing steps, coding logic is combinatorial, in the sense that information is represented as patterns of activity across a population of neurons, rather than in individual neurons. Because different neurons are located in different places, such a coding logic is often termed spatial, and can be visualized with optical imaging techniques. We employ in vivo calcium imaging in order to record odor-evoked activity patterns in olfactory receptor neurons, different populations of local neurons in the antennal lobes, projection neurons linking antennal lobes to the mushroom bodies, and the intrinsic cells of the mushroom bodies themselves, the Kenyon cells. These studies confirm the combinatorial nature of coding at all of these stages. However, the transmission of odor-evoked activity patterns from projection neuron dendrites via their axon terminals onto Kenyon cells is accompanied by a progressive sparsening of the population code. Activity patterns also show characteristic temporal properties. While a part of the temporal response properties reflect the physical sequence of odor filaments, another part is generated by local neuron networks. In honeybees, gamma-aminobutyric acid (GABA)-ergic and histaminergic neurons both contribute inhibitory networks to the antennal lobe. Interestingly, temporal properties differ markedly in different brain areas. In particular, in the antennal lobe odor-evoked activity develops over slow time courses, while responses in Kenyon cells are phasic and transient. The termination of an odor stimulus is reflected by a decrease in activity within most glomeruli of the antennal lobe and an off-response in some glomeruli, while in the mushroom bodies about half of the

关键词： olfaction receptor neurons neural coding antennal lobe mushroom body Kenyon cells Drosophila melanogaster Apis mellifera combinatorial coding

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Mixed observation filtering for neural data

Mixed observation filtering for neural data

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33rd IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Eden, Uri T. Brown, Emery N. Boston Univ Dept Math & Stat Boston MA 02215 USA

ISBN: (纸本)9781424414833

Electrophysiological recordings of brain activity include point process spike trains as well as continuous valued signals such as electroencephalograms (EEG), electrocorticograms (ECoG), and local field potentials (LFP). The brain represents information about the outside world in neural spiking activity, which is reflected in each of these signal modalities. An important problem in neuroscience data analysis involves estimating dynamic biological and behavioral signals from neural recordings. Here, we develop an adaptive filtering paradigm for estimating dynamic state processes from mixed observation processes that contain both point process and continuous valued observations. In our analysis of these filtering algorithms, we draw analogies to well-studied linear estimation algorithms such as the Kalman and Extended Kalman filters. We demonstrate the application of this mixed filtering paradigm to the problem of estimating a reaching movement trajectory from simulated simultaneously recorded motor cortical spiking and LFP activity. We demonstrate that the mixed filter is better able to capture information about the movement trajectory than are filters based on the spiking activity or LFPs alone.

关键词： adaptive filters Kalman filtering point processes neural coding brain-computer interface

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Oscillation and coding in a formal neural network considered as a guide for plausible simulations of the insect olfactory system

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BIOSYSTEMS 2007年第1-3期89卷 244-256页

作者： Horcholle-Bossavit, Ginette Quenet, Brigitte Foucart, Olivier Ecole Super Phys & Chim Ind Ville Paris Equipe Stat Appl F-75005 Paris France Ecole Super Phys & Chim Ind Ville Paris CNRS UMR 7084 F-75005 Paris France

For the analysis of coding mechanisms in the insect olfactory system, a fully connected network of synchronously updated McCulloch and Pitts neurons (MC-P type) was developed [Quenet, B., Horn, D., 2003. The dynamic neural filter: a binary model of spatio-temporal coding. neural Comput. 15 (2), 309-329]. Considering the update time as an intrinsic clock, this "Dynamic neural Filter" (DNF), which maps regions of input space into spatio-temporal sequences of neuronal activity, is able to produce exact binary codes extracted from the synchronized activities recorded at the level of projection neurons (PN) in the locust antennal lobe (AL) in response to different odors [Wehr, M., Laurent, G., 1996. Odor encoding by temporal sequences of firing in oscillating neural assemblies. Nature 384, 162-166]. Here, in a first step, we separate the populations of PN and local inhibitory neurons (LN) and use the DNF as a guide for simulations based on biological plausible neurons (Hodgkin-Huxley: H-H type). We show that a parsimonious network of 10 H-H neurons generates action potentials whose timing represents the required codes. In a second step, we construct a new type of DNF in order to study the population dynamics when different delays are taken into account. We find synaptic matrices which lead to both the emergence of robust oscillations and spatio-temporal patterns, using a formal criterion, based on a Normalized Euclidian Distance (NED), in order to measure the use of the temporal dimension as a coding dimension by the DNF. Similarly to biological PN, the activity of excitatory neurons in the model can be both phase-locked to different cycles of oscillations which remind local field potential (LFP), and nevertheless exhibit dynamic behavior complex enough to be the basis of spatio-temporal codes. (C) 2007 Published by Elsevier Ireland Ltd.

关键词： oscillations complex dynamics neural coding spatio-temporal patterns Hodgkin-Huxley model formal neural network

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