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neural coding of Leg Proprioception in Drosophila

NEURON 2018年第3期100卷 636-+页

作者： Mamiya, Akira Gurung, Pralaksha Tuthill, John C. Univ Washington Dept Physiol & Biophys Seattle WA 98195 USA

Animals rely on an internal sense of body position and movement to effectively control motor behavior. This sense of proprioception is mediated by diverse populations of mechanosensory neurons distributed throughout the body. Here, we investigate neural coding of leg proprioception in Drosophila, using in vivo two-photon calcium imaging of proprioceptive sensory neurons during controlled movements of the fly tibia. We found that the axons of leg proprioceptors are organized into distinct functional projections that contain topographic representations of specific kinematic features. Using subclass-specific genetic driver lines, we show that one group of axons encodes tibia position (flexion/extension), another encodes movement direction, and a third encodes bidirectional movement and vibration frequency. Overall, our findings reveal how proprioceptive stimuli from a single leg joint are encoded by a diverse population of sensory neurons, and provide a framework for understanding how proprioceptive feedback signals are used by motor circuits to coordinate the body.

关键词： proprioception proprioceptor proprioceptive mechanosensation mechanosensory Drosophila two-photon imaging motor control neural coding chordotonal

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neural coding of taste by simultaneously recorded cells in the nucleus of the solitary tract of the rat

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JOURNAL OF NEUROPHYSIOLOGY 2012年第12期108卷 3301-3312页

作者： Rosen, Andrew M. Di Lorenzo, Patricia M. SUNY Binghamton Dept Psychol Binghamton NY 13902 USA

Rosen AM, Di Lorenzo PM. neural coding of taste by simultaneously recorded cells in the nucleus of the solitary tract of the rat. J Neurophysiol 108: 3301-3312, 2012. First published September 26, 2012;doi:10.1152/jn.00566.2012.-The nucleus of the solitary tract (NTS) receives input from taste buds on the rostral tongue from the chorda tympani (CT) nerve. How this input is processed by the NTS was the subject of the present investigation. Here we used tetrodes to record from pairs or small groups of NTS cells as they responded to taste stimuli or electrical stimulation of the CT nerve in urethane-anesthetized rats. Once a pair (or small group) of NTS cells were isolated and identified as showing an evoked response to CT nerve stimulation, taste stimuli were presented in separate trials. Tastants consisted of 0.1 M NaCl, 0.01 M HCl, 0.01 M quinine HCl, and 0.5 M sucrose. Responses to various patterns of CT stimulation were then recorded. Functional connections among simultaneously recorded NTS cells were implied from analysis of cross-correlation functions of spike trains. We identified four groups of cells, not all of which responded to taste, with staggered latencies of response to CT nerve stimulation, ranging from similar to 3 to 35 ms in similar to 8- to 12-ms increments. Analyses of putative functional connectivity along with latencies of CT-evoked responses suggested that CT input arrives at the NTS in pulses or waves, each of which activates recurrent excitatory connections among NTS cells. These actions may amplify the incoming signal and refine its temporal pattern.

关键词： taste gustatory neural coding nucleus of solitary tract nucleus tractus solitarii neurophysiology rat

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neural coding properties based on spike timing and pattern correlation of retinal ganglion cells

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COGNITIVE NEURODYNAMICS 2010年第4期4卷 337-346页

作者： Gong, Han-Yan Zhang, Ying-Ying Liang, Pei-Ji Zhang, Pu-Ming Shanghai Jiao Tong Univ Sch Life Sci & Biotechnol Shanghai 200240 Peoples R China

Correlation between spike trains or neurons sometimes indicates certain neural coding rules in the visual system. In this paper, the relationship between spike timing correlation and pattern correlation is discussed, and their ability to represent stimulus features is compared to examine their coding strategies not only in individual neurons but also in population. Two kinds of stimuli, natural movies and checkerboard, are used to arouse firing activities in chicken retinal ganglion cells. The spike timing correlation and pattern correlation are calculated by cross-correlation function and Lempel-Ziv distance respectively. According to the correlation values, it is demonstrated that spike trains with similar spike patterns are not necessarily concerted in firing time. Moreover, spike pattern correlation values between individual neurons' responses reflect the difference of natural movies and checkerboard;neurons cooperate with each other with higher pattern correlation values which represent spatiotemporal correlations during response to natural movies. Spike timing does not reflect stimulus features as obvious as spike patterns, caused by their particular coding properties or physiological foundation. As a result, separating the pattern correlation out of traditional timing correlation concept uncover additional insight in neural coding.

关键词： neural coding Spike pattern correlation Spike timing correlation Cross-correlation Lempel-Ziv distance

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neural coding OF TEMPORAL INFORMATION IN AUDITORY THALAMUS AND CORTEX (vol 154, pg 294, 2008)

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NEUROSCIENCE 2008年第2期157卷 483-493页

作者： Wang, X. Lu, T. Bendor, D. Bartlett, E. Johns Hopkins Univ Sch Med Dept Biomed Engn Lab Auditory Neurophysiol Baltimore MD 21205 USA

How the brain processes temporal information embedded in sounds is a core question in auditory research. This article synthesizes recent studies from our laboratory regarding neural representations of time-varying signals in auditory cortex and thalamus in awake marmoset monkeys. Findings from these studies show that 1) the primary auditory cortex (A1) uses a temporal representation to encode slowly varying acoustic signals and a firing rate–based representation to encode rapidly changing acoustic signals, 2) the dual temporal-rate representations in A1 represent a progressive transformation from the auditory thalamus, 3) firing rate–based representations in the form of a monotonic rate-code are also found to encode slow temporal repetitions in the range of acoustic flutter in A1 and more prevalently in the cortical fields rostral to A1 in the core region of marmoset auditory cortex, suggesting further temporal-to-rate transformations in higher cortical areas. These findings indicate that the auditory cortex forms internal representations of temporal characteristics of sounds that are no longer faithful replicas of their acoustic structures. We suggest that such transformations are necessary for the auditory cortex to perform a wide range of functions including sound segmentation, object processing and multi-sensory integration.

关键词： auditory cortex medial geniculate body marmoset temporal processing neural coding

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A Hybrid neural coding Approach for Pattern Recognition With Spiking neural Networks

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2024年第5期46卷 3064-3078页

作者： Chen, Xinyi Yang, Qu Wu, Jibin Li, Haizhou Tan, Kay Chen Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 119077 Singapore Chinese Univ Hong Kong Shenzhen Res Inst Big Data Sch Data Sci Shenzhen 518172 Peoples R China

Recently, brain-inspired spiking neural networks (SNNs) have demonstrated promising capabilities in solving pattern recognition tasks. However, these SNNs are grounded on homogeneous neurons that utilize a uniform neural coding for information representation. Given that each neural coding scheme possesses its own merits and drawbacks, these SNNs encounter challenges in achieving optimal performance such as accuracy, response time, efficiency, and robustness, all of which are crucial for practical applications. In this study, we argue that SNN architectures should be holistically designed to incorporate heterogeneous coding schemes. As an initial exploration in this direction, we propose a hybrid neural coding and learning framework, which encompasses a neural coding zoo with diverse neural coding schemes discovered in neuroscience. Additionally, it incorporates a flexible neural coding assignment strategy to accommodate task-specific requirements, along with novel layer-wise learning methods to effectively implement hybrid coding SNNs. We demonstrate the superiority of the proposed framework on image classification and sound localization tasks. Specifically, the proposed hybrid coding SNNs achieve comparable accuracy to state-of-the-art SNNs, while exhibiting significantly reduced inference latency and energy consumption, as well as high noise robustness. This study yields valuable insights into hybrid neural coding designs, paving the way for developing high-performance neuromorphic systems.

关键词： Hybrid neural coding and learning framework layer-wise learning neural coding neuromorphic computing spiking neural network

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Anthropic Correction of Information Estimates and Its Application to neural coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2010年第2期56卷 890-900页

作者： Gastpar, Michael C. Gill, Patrick R. Huth, Alexander G. Theunissen, Frederic E. Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA Delft Univ Technol Fac Elect Engn Math & Comp Sci EEMCS Delft Netherlands Cornell Univ Sch Elect & Comp Engn Ithaca NY 14853 USA Univ Calif Berkeley Helen Wills Neurosci Inst Berkeley CA 94720 USA Univ Calif Berkeley Dept Psychol Berkeley CA 94720 USA

Information theory has been used as an organizing principle in neuroscience for several decades. Estimates of the mutual information (MI) between signals acquired in neurophysiological experiments are believed to yield insights into the structure of the underlying information processing architectures. With the pervasive availability of recordings from many neurons, several information and redundancy measures have been proposed in the recent literature. A typical scenario is that only a small number of stimuli can be tested, while ample response data may be available for each of the tested stimuli. The resulting asymmetric information estimation problem is considered. It is shown that the direct plug-in information estimate has a negative bias. An anthropic correction is introduced that has a positive bias. These two complementary estimators and their combinations are natural candidates for information estimation in neuroscience. Tail and variance bounds are given for both estimates. The proposed information estimates are applied to the analysis of neural discrimination and redundancy in the avian auditory system.

关键词： Anthropic principle information estimation neural coding neuron redundancy

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Information-theoretic analysis of neural coding

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2001年第1期10卷 47-69页

作者： Johnson, DH Gruner, CM Baggerly, K Seshagiri, C Rice Univ Dept Elect & Comp Engn Houston TX 77251 USA Rice Univ Ctr Informat & Comp Technol Dept Stat Houston TX 77251 USA

We describe an approach to analyzing single- and multiunit (ensemble) discharge patterns based on information-theoretic distance measures and on empirical theories derived from work in universal signal processing. In this approach, we quantify the difference between response patterns, whether time-varying or not, using information-theoretic distance measures. We apply these techniques to single- and multiple-unit processing of sound amplitude and sound location. These examples illustrate that neurons can simultaneously represent at least two kinds of information with different levels of fidelity. The fidelity can persist through a transient and a subsequent steady-state response, indicating that it is possible for an evolving neural code to represent information with constant fidelity.

关键词： neural coding information theory lateral superior olive

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Differentially synchronized spiking enables multiplexed neural coding

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2019年第20期116卷 10097-10102页

作者： Lankarany, Milad Al-Basha, Dhekra Ratte, Stephanie Prescott, Steven A. Hosp Sick Children Neurosci & Mental Hlth Toronto ON M5G 0A4 Canada Univ Toronto Dept Physiol Toronto ON M5S 1A8 Canada Univ Toronto Inst Biomat & Biomed Engn Toronto ON M5S 3G9 Canada Univ Hlth Network Krembil Res Inst Toronto ON M5T 0S8 Canada

Multiplexing refers to the simultaneous encoding of two or more signals. Neurons have been shown to multiplex, but different stimuli require different multiplexing strategies. Whereas the frequency and amplitude of periodic stimuli can be encoded by the timing and rate of the same spikes, natural scenes, which comprise areas over which intensity varies gradually and sparse edges where intensity changes abruptly, require a different multiplexing strategy. Recording in vivo from neurons in primary somatosensory cortex during tactile stimulation, we found that stimulus onset and offset (edges) evoked highly synchronized spiking, whereas other spikes in the same neurons occurred asynchronously. Stimulus intensity modulated the rate of asynchronous spiking, but did not affect the timing of synchronous spikes. From this, we hypothesized that spikes driven by high- and low-contrast stimulus features can be distinguished on the basis of their synchronization, and that differentially synchronized spiking can thus be used to form multiplexed representations. Applying a Bayesian decoding method, we verified that information about high- and low-contrast features can be recovered from an ensemble of model neurons receiving common input. Equally good decoding was achieved by distinguishing synchronous from asynchronous spikes and applying reverse correlation methods separately to each spike type. This result, which we verified with patch clamp recordings in vitro, demonstrates that neurons receiving common input can use the rate of asynchronous spiking to encode the intensity of low-contrast features while using the timing of synchronous spikes to encode the occurrence of high- contrast features. We refer to this strategy as synchrony-division multiplexing.

关键词： multiplexing neural coding rate code temporal code synchrony

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From Skin Mechanics to Tactile neural coding: Predicting Afferent neural Dynamics During Active Touch and Perception

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 2022年第12期69卷 3748-3759页

作者： Wei, Yuyang McGlone, Francis P. Marshall, Andrew G. Makdani, Adarsh Zou, Zhenmin Ren, Lei Wei, Guowu Univ Manchester Dept Mech Aerosp & Civil Engn Manchester M13 9PL Lancs England Liverpool John Moores Univ Sch Nat Sci & Psychol Liverpool Merseyside England Univ Liverpool Inst Aging & Chron Dis Liverpool Merseyside England Jilin Univ Key Lab Bion Engn Minist Educ Changchun 130012 Peoples R China Univ Salford Sch Sci Engn & Environm Manchester M5 4WT Lancs England

First order cutaneous neurons allow object recognition, texture discrimination, and sensorimotor feedback. Their function is well-investigated under passive stimulation while their role during active touch or sensorimotor control is understudied. To understand how human perception and sensorimotor controlling strategy depend on cutaneous neural signals under active tactile exploration, the finite element (FE) hand and lzhikevich neural dynamic model were combined to predict the cutaneous neural dynamics and the resulting perception during a discrimination test. Using in-vivo microneurography generated single afferent recordings, 75% of the data was applied for the model optimization and another 25% was used for validation. By using this integrated numerical model, the predicted tactile neural signals of the single afferent fibers agreed well with the microneurography test results, achieving the out-of-sample values of 0.94 and 0.82 for slowly adapting type I (SAI) and fast adapting type I unit (FAI) respectively. Similar discriminating capability with the human subject was achieved based on this computational model. Comparable performance with the published numerical model on predicting the cutaneous neural response under passive stimuli was also presented, ensuring the potential applicability of this multi-level numerical model in studying the human tactile sensing mechanisms during active touch. The predicted population-level 1st order afferent neural signals under active touch suggest that different coding strategies might be applied to the afferent neural signals elicited from different cutaneous neurons simultaneously.

关键词： Neurophysiological skin mechanics FE Human hand neural coding active touch

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Selective enhancement of neural coding in V1 underlies fine-discrimination learning in tree shrew

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CURRENT BIOLOGY 2022年第15期32卷 3245-+页

作者： Schumacher, Joseph W. McCann, Matthew K. Maximov, Katherine J. Fitzpatrick, David Max Planck Florida Inst Neurosci Funct Architecture & Dev Cerebral Cortex 1 Max Planck Way Jupiter FL 33458 USA Max Planck Inst Biol Intelligence Synapses Circuits Plast Am Klopferspitz 18 D-82152 Martinsried Germany Johns Hopkins Univ Sch Med Solomon H Snyder Dept Neurosci 1003 Wood Basic Sci Bldg 725 N Wolfe St Baltimore MD 21205 USA

Visual discrimination improves with training, a phenomenon that is thought to reflect plastic changes in the responses of neurons in primary visual cortex (V1). However, the identity of the neurons that undergo change, the nature of the changes, and the consequences of these changes for other visual behaviors remain unclear. We used chronic in vivo 2-photon calcium imaging to monitor the responses of neurons in the V1 of tree shrews learning a Go/No-Go fine orientation discrimination task. We observed increases in neural population measures of discriminability for task-relevant stimuli that correlate with performance and depend on a select subset of neurons with preferred orientations that include the rewarded stimulus and nearby orientations biased away from the non-rewarded stimulus. Learning is accompanied by selective enhancement in the response of these neurons to the rewarded stimulus that further increases their ability to discriminate the task stimuli. These changes persist outside of the trained task and predict observed enhancement and impairment in performance of other discriminations, providing evidence for selective and persistent learning-induced plasticity in the V1, with significant consequences for perception.

关键词： visual cortex perceptual learning neural coding tree shrew neural discrimination

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