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JOURNAL OF NEUROSCIENCE METHODS 2011年第2期199卷 296-309页

作者： Lyttle, David Fellous, Jean-Marc Univ Arizona Program Appl Math Tucson AZ 85721 USA Univ Arizona Dept Psychol Tucson AZ 85721 USA

An important problem in neuroscience is that of constructing quantitative measures of the similarity between neural spike trains. These measures can be used, for example, to assess the reliability of the response of a single neuron to repeated stimulus presentations, or to uncover relationships in the firing patterns of multiple neurons in a population. While several similarity measures have been proposed, the extent to which they take into account various biologically important spike train features such as bursts of spikes, or periods of inactivity remains poorly understood. Here we compare these measures using tests specifically designed to assess the sensitivity to bursts and silent periods. In addition, we propose two new measures. The first is designed to detect periods of shared silence between spike trains, while the second is designed to emphasize the presence of common bursts. To assist researchers in determining which measure is best suited to their particular data analysis needs, we also show how these measures can be combined and how their parameters can be determined on the basis of physiologically relevant quantities. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Spike train metrics Time series analysis Synchrony neural coding neural data analysis

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Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish

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JOURNAL OF NEUROPHYSIOLOGY 2011年第6期106卷 3102-3118页

作者： Vonderschen, Katrin Chacron, Maurice J. McGill Univ Dept Physiol Montreal PQ H3G 1Y6 Canada

Vonderschen K, Chacron MJ. Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish. J Neurophysiol 106: 3102-3118, 2011. First published September 21, 2011;doi:10.1152/jn.00588.2011.-While peripheral sensory neurons respond to natural stimuli with a broad range of spatiotemporal frequencies, central neurons instead respond sparsely to specific features in general. The nonlinear transformations leading to this emergent selectivity are not well understood. Here we characterized how the neural representation of stimuli changes across successive brain areas, using the electrosensory system of weakly electric fish as a model system. We found that midbrain torus semicircularis (TS) neurons were on average more selective in their responses than hindbrain electrosensory lateral line lobe (ELL) neurons. Further analysis revealed two categories of TS neurons: dense coding TS neurons that were ELL-like and sparse coding TS neurons that displayed selective responses. These neurons in general responded to preferred stimuli with few spikes and were mostly silent for other stimuli. We further investigated whether information about stimulus attributes was contained in the activities of ELL and TS neurons. To do so, we used a spike train metric to quantify how well stimuli could be discriminated based on spiking responses. We found that sparse coding TS neurons performed poorly even when their activities were combined compared with ELL and dense coding TS neurons. In contrast, combining the activities of as few as 12 dense coding TS neurons could lead to optimal discrimination. On the other hand, sparse coding TS neurons were better detectors of whether their preferred stimulus occurred compared with either dense coding TS or ELL neurons. Our results therefore suggest that the TS implements parallel detection and estimation of sensory input.

关键词： information theory neural coding electrocommunication

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Differential neural representation of oral ethanol by central taste-sensitive neurons in ethanol-preferring and genetically heterogeneous rats

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JOURNAL OF NEUROPHYSIOLOGY 2011年第6期106卷 3145-3156页

作者： Lemon, Christian H. Wilson, David M. Brasser, Susan M. St Louis Univ Sch Med Dept Pharmacol & Physiol Sci St Louis MO 63104 USA San Diego State Univ Dept Psychol San Diego CA 92182 USA

Lemon CH, Wilson DM, Brasser SM. Differential neural representation of oral ethanol by central taste-sensitive neurons in ethanol-preferring and genetically heterogeneous rats. J Neurophysiol 106: 3145-3156, 2011. First published September 14, 2011;doi: 10.1152/jn.00580.2011.-In randomly bred rats, orally applied ethanol stimulates neural substrates for appetitive sweet taste. To study associations between ethanol's oral sensory characteristics and genetically mediated ethanol preference, we made electrophysiological recordings of oral responses (spike density) by taste-sensitive nucleus tractus solitarii neurons in anesthetized selectively bred ethanol-preferring (P) rats and their genetically heterogeneous Wistar (W) control strain. Stimuli (25 total) included ethanol [3%, 5%, 10%, 15%, 25%, and 40% (vol/vol)], a sucrose series (0.01, 0.03, 0.1, 0.3, 0.5, and 1 M), and other sweet, salt, acidic, and bitter stimuli;50 P and 39 W neurons were sampled. k-means clustering applied to the sucrose response series identified cells showing high (S-1) or relatively low (S-0) sensitivity to sucrose. A three-way factorial analysis revealed that activity to ethanol was influenced by a neuron's sensitivity to sucrose, ethanol concentration, and rat line (P = 0.01). Ethanol produced concentration-dependent responses in S-1 neurons that were larger than those in S-0 cells. Although responses to ethanol by S-1 cells did not differ between lines, neuronal firing rates to ethanol in S-0 cells increased across concentration only in P rats. Correlation and multivariate analyses revealed that ethanol evoked responses in W neurons that were strongly and selectively associated with activity to sweet stimuli, whereas responses to ethanol by P neurons were not easily associated with activity to representative sweet, sodium salt, acidic, or bitter stimuli. These findings show differential central neural representation of oral ethanol between genetically heterogeneous rats and P rats genetic

关键词： genetics neural coding solitary tract taste alcohol

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Encoding/decoding of first and second order tactile afferents in a neurorobotic application

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JOURNAL OF PHYSIOLOGY-PARIS 2011年第1-3期105卷 25-35页

作者： Bologna, Luca Leonardo Pinoteau, Jeremie Brasselet, Romain Maggiali, Marco Arleo, Angelo Univ Paris 06 CNRS Lab Neurobiol Adapt Proc UMR 7102 F-75005 Paris France Italian Inst Technol Dept Robot Brain & Cognit Sci I-16163 Genoa Italy

We present a neurorobotic framework to investigate tactile information processing at the early stages of the somatosensory pathway. We focus on spatiotemporal coding of first and second order responses to Braille stimulation, which offers a suitable protocol to investigate the neural bases of fine touch discrimination. First, we model Slow Adaptive type I fingertip mechanoreceptor responses to Braille characters sensed both statically and dynamically. We employ a network of spiking neurones to transduce analogue skin deformations into primary spike trains. Then, we model second order neurones in the cuneate nucleus (CN) of the brainstem to study how mechanoreceptor responses are possibly processed prior to their transmission to downstream central areas. In the model, the connectivity layout of mechanoreceptor-to-cuneate projections produces a sparse CN code. To characterise the reliability of neurotransmission we employ an information theoretical measure accounting for the metrical properties of spiking signals. Our results show that perfect discrimination of primary and secondary responses to a set of 26 Braille characters is achieved within 100 and 500 ms of stimulus onset, in static and dynamic conditions, respectively. Furthermore, clusters of responses to different stimuli are better separable after the CN processing. This finding holds for both statically and dynamically delivered stimuli. In the presented system, when sliding the artificial fingertip over a Braille line, a speed of 40 - 50 mm/s is optimal in terms of rapid and reliable character discrimination. This result is coherent with psychophysical observations reporting average reading speeds of 30 - 40 +/- 5 mm/s adopted by expert Braille readers. ((C) 2011 Elsevier Ltd. All rights reserved.

关键词： Primary tactile afferents Mechanoreceptors Second order cuneate nucleus neurones Braille reading Context separation Fine touch discrimination neural coding Information theory Neurorobotics

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Characterizing the fine structure of a neural sensory code through information distortion

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2011年第1期30卷 163-179页

作者： Dimitrov, Alexander G. Cummins, Graham I. Baker, Aditi Aldworth, Zane N. Washington State Univ Dept Math Vancouver WA 98686 USA Washington State Univ WSU Vancouver Sci Programs Vancouver WA 98686 USA Swiss Re New York NY 10036 USA Univ Washington Dept Biol Seattle WA 98195 USA

We present an application of the information distortion approach to neural coding. The approach allows the discovery of neural symbols and the corresponding stimulus space of a neuron or neural ensemble simultaneously and quantitatively, making few assumptions about the nature of either code or relevant features. The neural codebook is derived by quantizing sensory stimuli and neural responses into small reproduction sets, and optimizing the quantization to minimize the information distortion function. The application of this approach to the analysis of coding in sensory interneurons involved a further restriction of the space of allowed quantizers to a smaller family of parametric distributions. We show that, for some cells in this system, a significant amount of information is encoded in patterns of spikes that would not be discovered through analyses based on linear stimulus-response measures.

关键词： neural coding Information theory Quantization Rate distortion Dimensionality reduction Cricket Acheta domesticus

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neural coding strategies in auditory cortex

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HEARING RESEARCH 2007年第1-2期229卷 81-93页

作者： Wang, Xiaoqin Johns Hopkins Univ Sch Med Lab Auditory Neurophysiol Dept Biomed Engn Baltimore MD 21205 USA

In contrast to the visual system, the auditory system has longer subcortical pathways and more spiking synapses between the peripheral receptors and the cortex. This unique organization reflects the needs of the auditory system to extract behaviorally relevant information from a complex acoustic environment using strategies different from those used by other sensory systems. The neural representations of acoustic information in auditory cortex can be characterized by three types: (1) isomorphic (faithful) representations of acoustic structures;(2) non-isomorphic transformations of acoustic features and (3) transformations from acoustical to perceptual dimensions. The challenge facing auditory neurophysiologists is to understand the nature of the latter two transformations. In this article, I will review recent Studies front our laboratory regarding temporal discharge patterns in auditory cortex of awake marmosets and cortical representations of time-varying signals. Findings from these studies show that (1) firing patterns of neurons in auditory cortex are dependent on stimulus optimality and context and (2) the auditory cortex forms internal representations of sounds that are no longer faithful replicas of their acoustic structures. (c) 2007 Published by Elsevier B.V.

关键词： auditor cortex marmoset temporal processing neural coding

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Intuitive coding: Vision and delusion

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PHILOSOPHICAL PSYCHOLOGY 2011年第2期24卷 145-157页

作者： Radulescu, Anca Univ Colorado Dept Math Boulder CO 80309 USA

We review the hypothesis that the brain uses a generative model to explain the causes of sensory inputs, using prediction schemes that operate based upon assimilation of time-series sensory data. We put this hypothesis in the context of psychopathology, in particular, schizophrenia's positive symptoms. Building upon work of Helmholtz and upon theories in computational cognitive processing, we hypothesize that delusions in schizophrenia can be explained in terms of false inference. An impairment in inferring appropriate information from the sensory input reflects upon the ability to assess the environment and predict outcomes. Although the inference mechanism likely involves both conscious and unconscious processes, we hypothesize that the trigger of delusions may lie within the unconscious neural pathways. A collection of computational predictive codes have been proposed for modeling perception. We discuss two examples, which may be eligible as substrates for intuitive coding. We argue that failure of the psychotic patient to choose the correct computational scheme, or the optimal range of parameters, may readily lead to an altered reconstruction of the object and false inference, feeding into the delusion mechanism. We finally propose using these models in conjunction with cognitive and imaging data, in order to obtain more testable predictions.

关键词： Delusions Inference neural coding Paranoid Schizophrenia Prediction

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Evaluating dependence in spike train metric spaces

Evaluating dependence in spike train metric spaces

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International Joint Conference on neural Networks (IJCNN)

作者： Seth, Sohan Brockmeier, Austin J. Choi, John S. Semework, Mulugeta Francis, Joseph T. Principe, Jose C. Univ Florida Elect & Comp Engn Dept Gainesville FL 32610 USA SUNY Downstate Med Ctr Dept Physiol & Pharmacol Brooklyn NY USA

ISBN: (纸本)9781424496365

Assessing dependence between two sets of spike trains or between a set of input stimuli and the corresponding generated spike trains is crucial in many neuroscientific applications, such as in analyzing functional connectivity among neural assemblies, and in neural coding. Dependence between two random variables is traditionally assessed in terms of mutual information. However, although well explored in the context of real or vector valued random variables, estimating mutual information still remains a challenging issue when the random variables exist in more exotic spaces such as the space of spike trains. In the statistical literature, on the other hand, the concept of dependence between two random variables has been presented in many other ways, e. g. using copula, or using measures of association such as Spearman's rho, and Kendall's tau. Although these methods are usually applied on the real line, their simplicity, both in terms of understanding and estimating, make them worth investigating in the context of spike train dependence. In this paper, we generalize the concept of association to any abstract metric spaces. This new approach is an attractive alternative to mutual information, since it can be easily estimated from realizations without binning or clustering. It also provides an intuitive understanding of what dependence implies in the context of realizations. We show that this new methodology effectively captures dependence between sets of stimuli and spike trains. Moreover, the estimator has desirable small sample characteristic, and it often outperforms an existing similar metric based approach.

关键词： Aerospace electronics Context Correlation Extraterrestrial measurements Mutual information Random variables abstract metric spaces bioelectric potentials dependence evaluation exotic spaces functional connectivity generated spike trains input stimuli intuitive understanding neural assembly neural coding neurophysiology neuroscientific applications random processes real valued random variables spike train dependence spike train metric spaces statistical analysis statistical literature vector valued random variables vectors

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Representing and Decoding Rank Order Codes Using Polychronization in a Network of Spiking Neurons

Representing and Decoding Rank Order Codes Using Polychroniz...

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International Joint Conference on neural Networks (IJCNN)

作者： Galluppi, Francesco Furber, Steve Univ Manchester Sch Comp Sci Manchester Lancs England

ISBN: (纸本)9781424496365

The introduction of axonal delays in networks of spiking neurons has enhanced the representational capabilities of neural networks, whilst also providing more biological realism. Approaches in neural coding such as rank order coding and polychronization have exploited the precise timing of action potential observed in real neurons. In a rank order code information is coded in the order of firing of a pool of neurons;on the other hand with polychronization it is the time of arrival of different spikes at the postsynaptic neuron which triggers different post-synaptic responses, with the axonal delays compensating for different timings in the afferents. In this paper we propose a model in which rank order coding is used to decode, represent and recall that symbol. To prove that the polychronous layer is able to do this a detector neuron is trained with a supervised learning strategy and associated with a single code. According to this premise the detector neuron only fires on the appearance of the associated code, even in the presence of noise. Tests prove that rank order coding and polychronization can be coupled to code and decode information such as intensity or significance using timing information in spiking neural networks in an effective way.

关键词： axonal delays decoding learning (artificial intelligence) neural coding neural nets neural networks polychronization polychronous layer postsynaptic neuron rank order code information representational capabilities spiking neural networks supervised learning strategy

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Limb-State Information Encoded by Peripheral and Central Somatosensory Neurons: Implications for an Afferent Interface

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IEEE TRANSACTIONS ON neural SYSTEMS AND REHABILITATION ENGINEERING 2011年第5期19卷 501-513页

作者： Weber, Douglas J. London, Brian M. Hokanson, James A. Ayers, Christopher A. Gaunt, Robert A. Torres, Ricardo R. Zaaimi, Boubker Miller, Lee E. Univ Pittsburgh Dept Phys Med & Rehabil Pittsburgh PA 15213 USA Univ Pittsburgh Dept Bioengn Pittsburgh PA 15213 USA Northwestern Univ Dept Physiol Feinberg Sch Med Chicago IL 60611 USA Univ Pittsburgh Dept Phys Med & Rehabil Pittsburgh PA 15213 USA Northwestern Univ Dept Physiol Chicago IL 60611 USA Northwestern Univ Dept Phys Med & Rehabil Feinberg Sch Med Chicago IL 60611 USA Northwestern Univ Dept Biomed Engn Chicago IL 60611 USA

A major issue to be addressed in the development of neural interfaces for prosthetic control is the need for somatosensory feedback. Here, we investigate two possible strategies: electrical stimulation of either dorsal root ganglia (DRG) or primary somatosensory cortex (S1). In each approach, we must determine a model that reflects the representation of limb state in terms of neural discharge. This model can then be used to design stimuli that artificially activate the nervous system to convey information about limb state to the subject. Electrically activating DRG neurons using naturalistic stimulus patterns, modeled on recordings made during passive limb movement, evoked activity in S1 that was similar to that of the original movement. We also found that S1 neural populations could accurately discriminate different patterns of DRG stimulation across a wide range of stimulus pulserates. In studying the neural coding in S1, we also decoded the kinematics of active limb movement using multi-electrode recordings in the monkey. Neurons having both proprioceptive and cutaneous receptive fields contributed equally to this decoding. Some neurons were most informative of limb state in the recent past, but many others appeared to signal upcoming movements suggesting that they also were modulated by an efference copy signal. Finally, we show that a monkey was able to detect stimulation through a large percentage of electrodes implanted in area 2. We discuss the design of appropriate stimulus paradigms for conveying time-varying limb state information, and the relative merits and limitations of central and peripheral approaches.

关键词： Dorsal root ganglia multielectrode array neural coding neural prostheses sensory cortex sensory feedback somatosensory

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