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Spike Train Analysis Toolkit: Enabling Wider Application of Information-Theoretic Techniques to Neurophysiology

NEUROINFORMATICS 2009年第3期7卷 165-178页

作者： Goldberg, David H. Victor, Jonathan D. Gardner, Esther P. Gardner, Daniel Cornell Univ Weill Med Coll Lab Neuroinformat D404 New York NY 10065 USA Cornell Univ Weill Med Coll Dept Physiol New York NY 10065 USA Cornell Univ Weill Med Coll Dept Neurol & Neurosci New York NY 10065 USA Cornell Univ Weill Med Coll Lab Neuroinformat New York NY 10065 USA NYU Sch Med Dept Physiol & Neurosci New York NY 10016 USA

Conventional methods widely available for the analysis of spike trains and related neural data include various time- and frequency-domain analyses, such as peri-event and interspike interval histograms, spectral measures, and probability distributions. Information theoretic methods are increasingly recognized as significant tools for the analysis of spike train data. However, developing robust implementations of these methods can be time-consuming, and determining applicability to neural recordings can require expertise. In order to facilitate more widespread adoption of these informative methods by the neuroscience community, we have developed the Spike Train Analysis Toolkit. STAToolkit is a software package which implements, documents, and guides application of several information-theoretic spike train analysis techniques, thus minimizing the effort needed to adopt and use them. This implementation behaves like a typical Matlab toolbox, but the underlying computations are coded in C for portability, optimized for efficiency, and interfaced with Matlab via the MEX framework. STAToolkit runs on any of three major platforms: Windows, Mac OS, and Linux. The toolkit reads input from files with an easy-to-generate text-based, platform-independent format. STAToolkit, including full documentation and test cases, is freely available open source via http://***, maintained as a resource for the computational neuroscience and neuroinformatics communities. Use cases drawn from somatosensory and gustatory neurophysiology, and community use of STAToolkit, demonstrate its utility and scope.

关键词： Computational neuroscience Information theory neural coding Neurodatabases Data sharing

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Ruling out and ruling in neural codes

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2009年第14期106卷 5936-5941页

作者： Jacobs, Adam L. Fridman, Gene Douglas, Robert M. Alam, Nazia M. Latham, Peter. E. Prusky, Glen T. Nirenberg, Sheila Cornell Univ Weill Med Coll Dept Physiol & Biophys New York NY 10065 USA Univ British Columbia Dept Ophthalmol & Visual Sci Vancouver BC V5Z 3N9 Canada Univ Calif Los Angeles Dept Neurobiol Los Angeles CA 90095 USA UCL Gatsby Computat Neurosci Unit London WC1N 3AR England

The subject of neural coding has generated much debate. A key issue is whether the nervous system uses coarse or fine coding. Each has different strengths and weaknesses and, therefore, different implications for how the brain computes. For example, the strength of coarse coding is that it is robust to fluctuations in spike arrival times;downstream neurons do not have to keep track of the details of the spike train. The weakness, though, is that individual cells cannot carry much information, so downstream neurons have to pool signals across cells and/or time to obtain enough information to represent the sensory world and guide behavior. In contrast, with fine coding, individual cells can carry much more information, but downstream neurons have to resolve spike train structure to obtain it. Here, we set up a strategy to determine which codes are viable, and we apply it to the retina as a model system. We recorded from all the retinal output cells an animal uses to solve a task, evaluated the cells' spike trains for as long as the animal evaluates them, and used optimal, i.e., Bayesian, decoding. This approach makes it possible to obtain an upper bound on the performance of codes and thus eliminate those that are insufficient, that is, those that cannot account for behavioral performance. Our results show that standard coarse coding (spike count coding) is insufficient;finer, more information-rich codes are necessary.

关键词： Bayesian ganglion cells ideal observer neural coding population coding

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Predictable irregularities in retinal receptive fields

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2009年第38期106卷 16499-16504页

作者： Liu, Yuan Sophie Stevens, Charles F. Sharpee, Tatyana O. Salk Inst Biol Studies Mol Neurobiol Lab La Jolla CA 92037 USA Salk Inst Biol Studies Computat Neurobiol Lab La Jolla CA 92037 USA Univ Calif San Diego Ctr Theoret Biol Phys La Jolla CA 92093 USA

Understanding how the nervous system achieves reliable performance using unreliable components is important for many disciplines of science and engineering, in part because it can suggest ways to lower the energetic cost of computing. In vision, retinal ganglion cells partition visual space into approximately circular regions termed receptive fields (RFs). Average RF shapes are such that they would provide maximal spatial resolution if they were centered on a perfect lattice. However, individual shapes have fine-scale irregularities. Here, we find that irregular RF shapes increase the spatial resolution in the presence of lattice irregularities from approximate to 60% to approximate to 92% of that possible for a perfect lattice. Optimization of RF boundaries around their fixed center positions reproduced experimental observations neuron-by-neuron. Our results suggest that lattice irregularities determine the shapes of retinal RFs and that similar algorithms can improve the performance of retinal prosthetics where substantial irregularities arise at their interface with neural tissue.

关键词： information theory neural coding optimal design retina

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A Method for Generating Natural and User-Defined Sniffing Patterns in Anesthetized or Reduced Preparations

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CHEMICAL SENSES 2009年第1期34卷 63-76页

作者： Cheung, Man Ching Carey, Ryan M. Wachowiak, Matt Boston Univ Dept Biol Boston MA 02215 USA Boston Univ Dept Biomed Engn Boston MA 02215 USA

Sniffing has long been thought to play a critical role in shaping neural responses to odorants at multiple levels of the nervous system. However, it has been difficult to systematically examine how particular parameters of sniffing behavior shape odorant-evoked activity, in large part because of the complexity of sniffing behavior and the difficulty in reproducing this behavior in an anesthetized or reduced preparation. Here we present a method for generating naturalistic sniffing patterns in such preparations. The method involves a nasal ventilator whose movement is controlled by an analog command voltage. The command signal may consist of intranasal pressure transients recorded from awake rats and mice or user-defined waveforms. This "sniff playback" device generates intranasal pressure and airflow transients in anesthetized animals that approximate those recorded from the awake animal and are reproducible across trials and across preparations. The device accurately reproduces command waveforms over an amplitude range of approximately 1 log unit and up to frequencies of approximately 12 Hz. Further, odorant-evoked neural activity imaged during sniff playback appears similar to that seen in awake animals. This method should prove useful in investigating how the parameters of odorant sampling shape neural responses in a variety of experimental settings.

关键词： active sensing artificial sniffing behavior imaging neural coding respiration

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A model of encoding and decoding in V1 and MT accounts for motion perception anisotropies in the human visual system

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BRAIN RESEARCH 2009年 1299卷 3-16页

作者： Rokem, Ayiel Silver, Michael A. Univ Calif Berkeley Sch Optometry Berkeley CA 94720 USA Univ Calif Berkeley Helen Wills Neurosci Inst Berkeley CA 94720 USA

We used the motion aftereffect (MAE) to psychophysically characterize tuning of motion perception in the human visual system. The function relating MAE strength and the range of directions present in the adapter Stimulus provides information regarding the width of direction tuning of motion adaptation. we compared the directional anisotropy in MAE tuning width to the well-known oblique effect in motion direction discrimination In agreement with previous research, we found that subjects had lower motion direction discrimination thresholds for cardinal compared to oblique directions For each subject, we also estimated MAE tuning width for a cardinal and an oblique direction by measuring the strength of the MAE for adapter stimuli containing different directional variances The MAE tuning width was smaller for the cardinal direction, suggesting. a fundamental similarity between motion direction discrimination and tuning of the MAE We constructed a model of encoding of motion stimuli by V1 and MT and decoding of stimulus information from the cells in area MT The model includes an anisotropy in the representation of different directions of motion in area V1. As a consequence of the connections implemented in the model, this anisotropy propagates to cells in MT Model simulations predicted an oblique effect for both direction discrimination thresholds and MAE tuning width, consistent with our experimental results The model also concurs with a recent r epsilon port that the magnitude of the oblique effect for direction discrimination is inversely proportional to the directional variance of the stimulus The agreement between model predictions and empirical data was obtained only when the model employed a maximum likelihood decoding algorithm Alternative decoding mechanisms such as vector averaging and winner-take-all failed to account for the psychophysical results (C) 2009 Elsevier B V All rights reserved.

关键词： Vision Motion perception Psychophysics neural coding Computational model Computational cognitive neuroscience Adaptation Motion aftereffect

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OVER-REPRESENTATION OF SPECIES-SPECIFIC VOCALIZATIONS IN THE AWAKE MOUSE INFERIOR COLLICULUS

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NEUROSCIENCE 2009年第2期162卷 486-500页

作者： Portfors, C. V. Roberts, P. D. Jonson, K. Washington State Univ Sch Biol Sci Vancouver WA 98686 USA Oregon Hlth & Sci Univ Div Biomed Engn Portland OR 97239 USA

Social vocalizations are particularly important stimuli in an animal's auditory environment. Because of their importance, vocalizations should be strongly represented in auditory pathways. Mice commonly emit ultrasonic vocalizations with spectral content between 45 and 100 kHz. However, there is limited representation of these ultra-high frequencies (particularly those greater than 60 kHz) throughout the ascending auditory system. Here, we show that neurons in the inferior colliculus (IC) of mice respond strongly to conspecific vocalizations even though the energy in the vocalizations is above the neurons' frequency tuning curves. This results in an over-representation of species-specific vocalizations in the IC. In addition, neurons in mouse IC show selectivity among different vocalizations. Many vocalization-responsive neurons do not respond to the individual ultrasonic frequencies contained within the vocalizations, but they do respond to combinations of ultrasonic tones if the difference between the tones is within the excitatory frequency tuning curve. The combinations of tones that elicit responses are the quadratic and/or cubic intermodulation distortion components that are generated by the cochlea. Thus, the intermodulation distortions in the cochlea may provide a previously overlooked mechanism for auditory processing of complex stimuli such as vocalizations. The implication of these findings is that nonlinear interactions of frequencies, possibly caused by distortions in the system, may be used to enhance the sensitivity to behaviorally important stimuli. Published by Elsevier Ltd on behalf of IBRO.

关键词： hearing frequency tuning ultrasonic neural coding complex sounds cochlear distortion

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neural dynamics of envelope coding

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MATHEMATICAL BIOSCIENCES 2008年第1-2期214卷 87-99页

作者： Longtin, Andre Middleton, Jason W. Cieniak, Jakub Maler, Leonard Univ Ottawa Dept Phys Ottawa ON K1N 6N5 Canada Univ Ottawa Ctr Neural Dynam Ottawa ON K1N 6N5 Canada Univ Ottawa Dept Cellular & Mol Med Ottawa ON K1N 6N5 Canada

We consider the processing of narrowband signals that modulate carrier waveforms in sensory systems. The tuning of sensory neurons to the carrier frequency results in a high sensitivity to the amplitude modulations of the carrier. Recent work has revealed how specialized circuitry can extract the lower-frequency modulation associated with the slow envelope of a narrowband signal, and send. it to higher brain along with the full signal. This paper first summarizes the experimental evidence for this processing in the context of electroreception, where the narrowband signals arise in the context of social communication between the animals. It then examines the mechanism of this extraction by single neurons and neural populations, using intracellular recordings and new modeling results contrasting envelope extraction and stochastic resonance. Low noise and peri-threshold stimulation are necessary to obtain a firing pattern than, shows high coherence with the envelope of the input. Further, the output must be fed through a slow synapse. Averaging networks are then considered for their ability to detect, using additional noise, signals with power in the envelope bandwidth. The circuitry that (toes support envelope extraction beyond the primary receptors is available in many areas of the brain including cortex. The mechanism of envelope extraction and its gating by noise and bias currents is thus accessible to non-carrier-based coding as well, as long as the input to the circuit is a narrowband signal. Novel results are also presented on a more biophysical model of the receptor population, showing that it can encode a narrowband signal, but not its envelope, as observed experimentally. The model is modified from previous models by reducing stimulus contrast in order to make it sufficiently linear to agree with the experimental data. (C) 2008 Elsevier Inc. All rights reserved.

关键词： neural coding integrate-and-fire model Hilbert transform coherence electroreceptors stochastic resonance

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Noise Correlations Have Little Influence on the coding of Selective Attention in Area V1

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CEREBRAL CORTEX 2009年第3期19卷 543-553页

作者： Poort, Jasper Roelfsema, Pieter R. Netherlands Inst Neurosci Dept Vis & Cognit NL-1105 BA Amsterdam Netherlands Vrije Univ Amsterdam Ctr Neurogenom & Cognit Res Dept Expt Neurophysiol NL-1081 HV Amsterdam Netherlands

Neurons in the visual primary cortex (area V1) do not only code simple features but also whether image elements are attended or not. These attentional signals are weaker than the feature-selective responses, and their reliability may therefore be limited by the noisiness of neuronal responses. Here we show that it is possible to decode the locus of attention on a single trial from the activity of a small population of neurons in area V1. Previous studies suggested that correlations between the activities of neurons that are part of a population limit the information gain, but here we report that the impact of these noise correlations depends on the relative position of the neurons' receptive fields. Correlations reduce the benefit of pooling neuronal responses evoked by the same object but actually enhance the advantage of pooling responses evoked by different objects. These opposing effects cancelled each other at the population level, so that the net effect of the noise correlations was negligible and attention could be decoded reliably. Our results suggest that noise correlations are caused by large-scale fluctuations in cortical excitability, which can be removed by a comparison of the response strengths evoked by different objects.

关键词： attention discrimination neural coding noise correlation vision visual cortex

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Feature mixing rather than feature replacement during perceptual filling-in

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VISION RESEARCH 2009年第4期49卷 439-450页

作者： Hsieh, P. -J. Tse, P. U. Dartmouth Coll Dept Psychol & Brain Sci Hanover NH 03755 USA

'Filling-in' occurs when a retinally stabilized object subjectively appears to vanish following perceptual fading of its boundaries. The term 'filling-in' literally means that information about the apparently vanished object is lost and replaced solely by information arising from the surrounding background. However, we find evidence that the mechanism of 'filling-in' can actually involve a process of 'feature mixing' rather than 'feature replacement,' whereby features on either side of a perceptually faded boundary merge. Here we investigate the properties of feature mixing and specify certain conditions under which such mixing occurs. Our results show that, when using visual stimuli composed of spatially alternating stripes containing different luminances or motion signals, and when using the neon-color-spreading paradigm, the filled-in luminance, motion, or color is approximately the area and magnitude weighted average of the background and the foreground luminance, motion, or color, respectively. Together, these results demonstrate that, under at least certain conditions, 'filling-in' may involve a process of feature mixing or feature averaging rather than one of feature replacement. Published by Elsevier Ltd.

关键词： Perceptual filling-in Perceptual mixing Feature mixing neural coding

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The minimum information principle and its application to neural code analysis

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2009年第9期106卷 3490-3495页

作者： Globerson, Amir Stark, Eran Vaadiab, Eilon Tishby, Naftali Hebrew Univ Jerusalem Sch Engn & Comp Sci IL-91904 Jerusalem Israel Hebrew Univ Jerusalem Hadassah Med Sch Dept Physiol IL-91120 Jerusalem Israel Hebrew Univ Jerusalem Interdisciplinary Ctr Neural Computat IL-91904 Jerusalem Israel

The study of complex information processing systems requires appropriate theoretical tools to help unravel their underlying design principles. Information theory is one such tool, and has been utilized extensively in the study of the neural code. Although much progress has been made in information theoretic methodology, there is still no satisfying answer to the question: "What is the information that a given property of the neural population activity (e.g., the responses of single cells within the population) carries about a set of stimuli?" Here, we answer such questions via the minimum mutual information (MinMI) principle. We quantify the information in any statistical property of the neural response by considering all hypothetical neuronal populations that have the given property and finding the one that contains the minimum information about the stimuli. All systems with higher information values necessarily contain additional information processing mechanisms and, thus, the minimum captures the information related to the given property alone. MinMI may be used to measure information in properties of the neural response, such as that conveyed by responses of small subsets of cells (e.g., singles or pairs) in a large population and cooperative effects between subunits in networks. We show how the framework can be used to study neural coding in large populations and to reveal properties that are not discovered by other information theoretic methods.

关键词： neural coding information theory maximum entropy population coding

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