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Regulating temporal Neural coding via Fast and Slow Synaptic Dynamics

IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS 2025年第1期17卷 102-114页

作者： Tang, Yuanhong An, Lingling Zhang, Xingyu Huang, Huiling Yu, Zhaofei Peking Univ Inst Artificial Intelligence Dept Comp Sci & Technol Natl Engn Lab Video Technol Beijing 100871 Peoples R China Xidian Univ Sch Comp Sci & Technol Xian 710071 Peoples R China Xidian Univ Guangzhou Inst Technol Guangzhou 510555 Peoples R China

The NMDA receptor (NMDAR), as a ubiquitous type of synapse in neural systems of the brain, presents slow dynamics to modulate neural spiking activity. For the cerebellum, NMDARs have been suggested for contributing complex spikes in Purkinje cells (PCs) as a mechanism for cognitive activity, learning, and memory. Recent experimental studies are debating the role of NMDAR in PC dendritic input, yet it remains unclear how the distribution of NMDARs in PC dendrites can affect their neural spiking coding properties. In this work, a detailed multiple-compartment PC model was used to study how slow-scale NMDARs together with fast-scale AMPA, regulate neural coding. We find that NMDARs act as a band-pass filter, increasing the excitability of PC firing under low-frequency input while reducing it under high frequency. This effect is positively related to the strength of NMDARs. For a response sequence containing a large number of regular and irregular spiking patterns, NMDARs reduce the overall regularity under high-frequency input while increasing the local regularity under low-frequency. Moreover, the inhibitory effect of NMDA receptors during high-frequency stimulation is associated with a reduced conductance of large conductance calcium-activated potassium (BK) channel. Taken together, our results suggest that NMDAR plays an important role in the regulation of neural coding strategies by utilizing its complex dendritic structure.

关键词： Dendrites (neurons) Firing Cerebellum Time-frequency analysis Synapses Sodium Physiology Neuronal morphology NMDA Purkinje cell (PC) spiking coding temporal coding

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temporal coding in an olfactory oscillatory model

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NEUROCOMPUTING 2001年 38卷 831-836页

作者： Quenet, B Horn, D Dreyfus, G Dubois, R ESPCI Elect Lab F-75005 Paris France Tel Aviv Univ Sch Phys & Astron IL-69978 Tel Aviv Israel

We propose a model of the glomerular stage of the insect olfactory pathway that exhibits coding of inputs through spatio-temporal patterns of the type observed experimentally in locust. Making use of the temporal bins provided by the oscillatory field potential we find that it suffices to employ simple little-Hopfield dynamics to account for a rich repertoire of patterns. In particular, we show that we are able to reproduce complex activity patterns from electrophysiological recordings in insects. Biologically plausible mechanisms of synaptic adaptation are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

关键词： temporal coding olfaction pattern generation learning

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temporal coding with synchronization and acceleration as complementary mechanisms

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NEUROCOMPUTING 2008年第7-9期71卷 1121-1133页

作者： Burwick, Thomas Goethe Univ Frankfurt Inst Adv Studies D-60438 Frankfurt Germany Thinking Networks AG D-52062 Aachen Germany

temporal coding requires an appropriate combination of synchronizing and desynchronizing mechanisms. We study temporal coding with a desynchronizing mechanism, referred to as acceleration, that causes the units of the network to oscillate with higher phase velocity in case of stronger and/or more coherent input. Recently, it was demonstrated that combining synchronization with acceleration implies a competition for coherence that has a profound and favorable effect on the segmentation of overlapping patterns. Here, we demonstrate, first, an effect of coupling non-identical oscillators. Second, we discuss how including inhibitory couplings enforces the segmenting effect of acceleration. Third, we show how stronger couplings between the units of a pattern may support it in winning this competition for coherence. (c) 2008 Elsevier B.V. All rights reserved.

关键词： autoassociative memory complex-valued neural networks oscillatory networks pattern recognition temporal coding

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temporal coding in conditioned inhibition: Retardation tests

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ANIMAL LEARNING & BEHAVIOR 2001年第3期29卷 281-290页

作者： Burger, DC Denniston, JC Miller, RR SUNY Binghamton Dept Psychol Binghamton NY 13902 USA Appalachian State Univ Boone NC 28608 USA

Two lick suppression experiments with rats were conducted in order to determine the nature of the temporal information that is encoded as a result of Pavlovian conditioned inhibition training (conditioned stimulus [CS] A --> unconditioned stimulus [US]/AX --> noUS). After inhibition training, the conditioned inhibitor (X) was paired with the US in order to measure inhibition, as assessed through retarded behavioral control by CS X. Three temporal relationships were manipulated: the A-US interval, the X-A interval of inhibition training, and the X-US interval of the retardation test pairings. Retardation was greatest when the X-US temporal relationship matched the time at which the US was expected (but not delivered) on the X-A inhibition training trials. Thus, the present experiments provide evidence with retardation tests that, during conditioned inhibition training, subjects encode the temporal location of the omitted US relative to the inhibitory CS. These findings complement those of previous studies using summation tests of conditioned inhibition (Barnet & Miller, 1996;Denniston, Blaisdell, & Miller, 1998;Denniston, Cole, & Miller, 1998).

关键词： .lick summation conditioned inhibition training temporal relationships omitted temporal coding Retardation tests noUS

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temporal coding: The relevance of classical activity, its relation to pattern frequency bands, and a remark on recoding of excitatory drive into phase shifts

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BIOSYSTEMS 2008年第1-2期94卷 75-86页

作者： Burwick, Thomas Goethe Univ Frankfurt FIAS D-60438 Frankfurt Germany Thinking Networks AG D-52062 Aachen Germany

We consider an oscillatory network model that is obtained as complex-valued generalization of the classical Cohen-Grossberg-Hopfield (CGH) model. Apart from a synchronizing mechanism, a stronger and/or more coherent input to a unit in the network implies a higher phase velocity of this unit. This constitutes the desynchronizing mechanism, referred to as acceleration. The units' activity of the classical model translates into the amplitudes of the phase model oscillators. This allows to associate classical and temporal coding with amplitude and phase dynamics, respectively. We discuss how the two dynamics act together to achieve the unambiguous pattern recognition that avoids the superposition problem. With respect to coherence, dominating patterns may take coherent states also if only a subset of its units is on-state. The competition for coherence, introduced by acceleration, realizes a kind of feature counting that identifies the dominating pattern as the pattern with the most on-state units. This dominating but possibly only partially active pattern may take a coherent state with a frequency level that is related to the number of on-state units. We also speculate on neurophysiological findings, related to observed phase differences between optimally and suboptimally activated neurons, that may indicate the presence of acceleration. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

关键词： Complex-valued neural networks Oscillatory networks temporal coding

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temporal coding OF PHEROMONE PULSES AND TRAINS IN MANDUCA-SEXTA

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JOURNAL OF COMPARATIVE PHYSIOLOGY A-NEUROETHOLOGY SENSORY NEURAL AND BEHAVIORAL PHYSIOLOGY 1992年第4期171卷 505-512页

作者： MARIONPOLL, F TOBIN, TR UNIV ARIZONA ARLDN TUCSON AZ 85721 USA

We investigated the ability of pheromone-sensitive olfactory receptors of male Manduca sexta to respond to 20-ms pulses of bombykal, the major component of the conspecific pheromonal blend. Isolated pulses of bombykal elicited a burst of activity which decreased exponentially with a time constant of 160-250 ms. Trains of pulses delivered at increasing frequencies (0.5-10 Hz) elicited temporally modulated responses at up to 3 Hz. Concentration of the stimulus (1, 10, 100 ng per odor source) had a marginal effect on the temporal resolution of the receptors. Within a train, the responses to individual pulses remained constant, except for 10-Hz trains (short-term adaptation). A dose-dependent decline of responsiveness was observed during experiments (long-term adaptation). Although individual neurons may not respond faithfully to each pulse of a train, the population of receptors sampled in this study appears to be capable of encoding the onset of odor pulses at frequencies of up to at least 3 Hz.

关键词： MANDUCA-SEXTA OLFACTION PHEROMONES temporal coding ADAPTATION

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temporal coding in the gustatory system

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NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS 2006年第8期30卷 1145-1160页

作者： Hallock, Robert M. Di Lorenzo, Patricia M. SUNY Binghamton Dept Psychol Binghamton NY 13902 USA

Hallock, R.M. and Di Lorenzo, P.M. [2006. temporal coding in the gustatory system. Neurosci. Biobehav. Rev. XX(X) XXX-XXX]. Early investigations of temporal coding in the gustatory system showed that the time course of responses in some neurons showed systematic differences across the various classes of taste stimuli, implying that the temporal characterisics of a response can convey information about a taste stimulus. Studies of temporal coding in the gustatory system have grappled with several unique methodological challenges, including the quantitative description and comparison of temporal patterns as well as the assessment of the relative contributions of spatial and temporal coding to the information contained in a response to a tastant. Other investigations have suggested that the cooperative activity among synchronously firing ensembles of taste-responsive neurons at all levels of processing in the brain can convey information about taste quality (sweet, sour, salty, bitter and umami). Behavioral studies using patterned electrical stimulation of the brain in awake animals have supported the idea that temporal coding of taste stimuli may have functional significance. (c) 2006 Elsevier Ltd. All rights reserved.

关键词： taste gustatory neural coding temporal coding neurophysiology

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A Supervised Learning Algorithm for Multilayer Spiking Neural Networks Based on temporal coding Toward Energy-Efficient VLSI Processor Design

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023年第1期34卷 394-408页

作者： Sakemi, Yusuke Morino, Kai Morie, Takashi Aihara, Kazuyuki Univ Tokyo Inst Ind Sci Tokyo 1538505 Japan NEC Corp Ltd Kawasaki Kanagawa 2118666 Japan Kyushu Univ Interdisciplinary Grad Sch Engn Sci Fukuoka 8168580 Japan Kyushu Inst Technol Grad Sch Life Sci & Syst Engn Kitakyushu Fukuoka 8080196 Japan Univ Tokyo Inst Adv Study Int Res Ctr Neurointelligence WPI IRCN Tokyo 1130033 Japan

Spiking neural networks (SNNs) are brain-inspired mathematical models with the ability to process information in the form of spikes. SNNs are expected to provide not only new machine-learning algorithms but also energy-efficient computational models when implemented in very-large-scale integration (VLSI) circuits. In this article, we propose a novel supervised learning algorithm for SNNs based on temporal coding. A spiking neuron in this algorithm is designed to facilitate analog VLSI implementations with analog resistive memory, by which ultrahigh energy efficiency can be achieved. We also propose several techniques to improve the performance on recognition tasks and show that the classification accuracy of the proposed algorithm is as high as that of the state-of-the-art temporal coding SNN algorithms on the MNIST and Fashion-MNIST datasets. Finally, we discuss the robustness of the proposed SNNs against variations that arise from the device manufacturing process and are unavoidable in analog VLSI implementation. We also propose a technique to suppress the effects of variations in the manufacturing process on the recognition performance.

关键词： Encoding Neurons Very large scale integration Task analysis Nonhomogeneous media Timing Supervised learning Edge computing spiking neural network (SNN) supervised learning temporal coding very-large-scale integration (VLSI)

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Classification of somatosensory stimuli on the basis of the temporal coding at the cuneate nucleus

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NEUROCOMPUTING 2015年第Part1期151卷 62-68页

作者： Navarro, Juan Sanchez, Eduardo Ferreiroa, Ruben Canedo, Antonio Univ Santiago de Compostela Fac Med Dept Fisiol Santiago De Compostela 15782 Spain Univ Santiago de Compostela Grp Sistemas Inteligentes Ctr Singular Invest Tecnol Informac CITIUS Santiago De Compostela 15782 Spain

The present study explores the capacity of a temporal code generated by the projection neurons of a realistic computational model of the cuneate nucleus to classify somesthetic stimuli. Four classification experiments were carried out with a feedforward network trained under a supervised learning algorithm in which the input is a vector including the sequence of outputs of the cuneate nucleus. The number of correct responses on each classification task varied with the complexity of the experiment, but a decrease in the number of errors was observed when presenting the optimal length of the input vector. This suggests that the cuneate nucleus might (1) transmit the appropriate information required for input classification, and (2) function as an information processing center and not merely as a relay or filtering stage. (C) 2014 Published by Elsevier B.V.

关键词： Classification temporal coding Cuneate nucleus Somatosensory system

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temporal coding of Neural Stimuli 28th

Temporal Coding of Neural Stimuli

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28th International Conference on Artificial Neural Networks (ICANN)

作者： Horzyk, Adrian Goldon, Krzysztof Starzyk, Janusz A. AGH Univ Sci & Technol Krakow Poland Univ Informat Technol & Management Rzeszow Rzeszow Poland Ohio Univ Sch EECS Athens OH 45701 USA

ISBN: (纸本)9783030304935;9783030304928

Contemporary artificial neural networks use various metrics to code input data and usually do not use temporal coding, unlike biological neural systems. Real neural systems operate in time and use the time to code external stimuli of various kinds to produce a uniform internal data representation that can be used for further neural computations. This paper shows how it can be done using special receptors and neurons which use the time to code external data as well as internal results of computations. If neural processes take different time, the activation time of neurons can be used to code the results of computations. Such neurons can automatically find data associated with the given inputs. In this way, we can find the most similar objects represented by the network and use them for recognition or classification tasks. Conducted research and results prove that time space, temporal coding, and temporal neurons can be used instead of data feature space, direct use of input data, and classic artificial neurons. Time and temporal coding might be an important branch for the development of future artificial neural networks inspired by biological neurons.

关键词： temporal coding temporal neurons Feature representation in the time space Stimuli receptor transformation into the time space Associative temporal neural networks Associative graph data structure

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