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Adaptive spiking neuron with population coding for a residual spiking neural network

APPLIED INTELLIGENCE 2025年第4期55卷 1-24页

作者： Dan, Yongping Sun, Changhao Li, Hengyi Meng, Lin Zhongyuan Univ Technol Sch Integrated Circuits 1 Huaihe Rd Zhengzhou 451191 Henan Peoples R China Zhongyuan Univ Technol Sch Automat & Elect Engn 1 Huaihe Rd Zhengzhou 451191 Henan Peoples R China Ritsumeikan Univ Res Org Sci & Technol 1-1-1 Noji Higashi Kusatsu Shiga 5258577 Japan Ritsumeikan Univ Coll Sci & Engn 1-1-1 Noji Higashi Kusatsu Shiga 5258577 Japan

Spiking neural networks (SNNs) have attracted significant research attention due to their inherent sparsity and event-driven processing capabilities. Recent studies indicate that the incorporation of convolutional and residual structures into SNNs can substantially enhance performance. However, these converted spiking residual structures are associated with increased complexity and stacked parameterized spiking neurons. To address this challenge, this paper proposes a meticulously refined two-layer decision structure for residual-based SNNs, consisting solely of fully connected and spiking neuron layers. Specifically, the spiking neuron layers incorporate an innovative dynamic leaky integrate-and-fire (DLIF) neuron model with a nonlinear self-feedback mechanism, characterized by dynamic threshold adjustment and a self-regulating firing rate. Furthermore, diverging from traditional direct encoding, which focuses solely on individual neuronal frequency, we introduce a novel mixed coding mechanism that combines direct encoding with multineuronal population decoding. The proposed architecture improves the adaptability and responsiveness of spiking neurons in various computational contexts. Experimental results demonstrate the superior efficacy of our approach. Although it uses a highly simplified structure with only 6 timesteps, our proposal achieves enhanced performance in the experimental trials compared to multiple state-of-the-art methods. Specifically, it achieves accuracy improvements of 0.01-1.99% on three static datasets and of 0.14-7.50% on three N-datasets. The DLIF model excels in information processing, showing double mutual information compared to other neurons. In the sequential MNIST dataset, it balances biological realism and practicality, enhancing memory and the dynamic range. Our proposed method not only offers improved computational efficacy and simplified network structure but also enhances the biological plausibility of SNN models and can be easily

关键词： Spiking neural networks Spiking neuron population coding

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population coding for neuromorphic hardware

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NEUROCOMPUTING 2017年 239卷 153-164页

作者： Khan, Saad Qasim Ghani, Arfan Khurram, Muhammad NED Univ Engn & Technol Dept Comp & Informat Syst Engn Karachi Pakistan Coventry Univ Sch Comp Elect & Math Coventry CV1 5FB W Midlands England

population coding has been established as the key mechanism for decoding sensory information received from periphery organs such as retinas and cochlear. In this paper a novel architecture is presented to embed population coding in neuromorphic hardware. A resonance based mechanism between two layers of neuron is utilized in the presented work. The mechanism discussed in this paper facilitates selective triggering of higher layer neurons which serves as target ensemble for evaluation of a particular input of interest. It has been shown that presented model can be used to detect any physical quantity (light intensity, temperature, etc.) feed to the sensor on the basis of population coding. (C) 2017 Elsevier B.V. All rights reserved.

关键词： population coding Neuromorphic hardware Synaptic plasticity Interspike interval Tuning curve

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population coding under normalization

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VISION RESEARCH 2010年第22期50卷 2223-2232页

作者： Ringach, Dario L. Univ Calif Los Angeles David Geffen Sch Med Jules Stein Eye Inst Dept Neurobiol Los Angeles CA 90095 USA Univ Calif Los Angeles David Geffen Sch Med Jules Stein Eye Inst Dept Psychol Los Angeles CA 90095 USA

A common computation in visual cortex is the divisive normalization of responses by a pooled signal of the activity of cells within its neighborhood From a geometrical point of view normalization constraints the population response to high-contrast stimuli to lie on the surface of a high-dimensional sphere Here we study the implications this constraint imposes on the representation of a circular variable such as the orientation of a visual stimulus New results are derived for the infinite dimensional case of a homogeneous populations of neurons with identical tuning curves but different orientation preferences An important finding is that the ability of the population to discriminate between any two orientations depends exclusively on the Fourier amplitude spectrum of the orientation tuning curve We also study the problem of encoding by a finite set of neurons A central result is that under normalization optimal encoding can be achieved by a finite number of neurons with heterogeneous tuning curves In other words increasing the number of neurons in the population does not always allow for an improved population code These results are used to estimate the number of neurons involved in the coding of orientation at one position in the visual field If the cortex were to code orientation optimally we find that a small number (similar to 4) of neurons should suffice (C) 2010 Elsevier Ltd All rights reserved

关键词： Normalization Gain control population coding Optimal coding Visual cortex Electrostatic potential Thomson problem Minimum energy

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population coding by cell assemblies - What it really is in the brain

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NEUROSCIENCE RESEARCH 1996年第1期26卷 1-16页

作者： Sakurai, Y TOYAMA MED & PHARMACEUT UNIV DEPT PSYCHOL TOYAMA 93001 JAPAN

One of the central questions in neuroscience concerns the basic code for information processing in the brain. Much experimental evidence and theoretical consideration have suggested that single-neuron coding is no longer a tenable hypothesis. The present review explains why population neuronal coding is valid and discusses how it is carried out in the brain. The main context is experimental access to real features of the coding in working brains as deduced from experimental research. Several recent studies recording neuronal activities from behaving animals have shown that ensemble activity of neurons represents specific information, indicating the reality of population coding by many neurons. The key concept which can integrate the experimental evidence is the 'cell assembly', i.e., overlapped populations of neurons with flexible functional connections within and among the populations. Correlated activity among the neurons constructs the functional connection. In order to see features of the cell-assembly coding, two main properties of cell assemblies in processing several different kinds of information must be investigated, that is, the overlapping of neurons and the dynamics of synaptic connections. This manner of coding can provide both the experimental and theoretical framework to detect the real dynamic features of information processing by the brain.

关键词： population coding activity correlations synaptic connections cell assembly functional overlapping memory neuronal recording behaving animals

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population coding of electrosensory stimulus in receptor network

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NEUROCOMPUTING 2006年第10-12期69卷 1206-1210页

作者： Fujita, Kazuhisa Kashimori, Yoshiki Univ Electrocommun Grad Sch Informat Syst Dept Informat Network Sci Chofu Tokyo 1828585 Japan Univ Electrocommun Dept Appl Phys & Chem Chofu Tokyo 1828585 Japan

To investigate the mechanism of sensory coding of spatiotemporally varying stimuli, we study the population coding of receptor network in electrosensory system. Weakly electric fish use amplitude modulations of their self-generated electric organ discharge (EOD AM) to detect distance and size of an object such as prey. We developed a model of fish by which we calculate numerically the spatiotemporal patterns of electric field around the fish body, and made a model of electroreceptor network. We showed previously that the information of object distance and size are represented by a combination of two characteristic features of EOD AM, the maximum amplitude and half-maximum width of EOD AM. We show here that the information of object distance and its size are encoded as synchronous firing of receptor network, leading to a reliable encoding of the two features of EOD AM in target neurons to which the receptors project, through a rapid synaptic integration of the receptor outputs. We further show that an optimal distribution of receptor sensitivity to EOD stimuli may provide a significant change of the two EOD AM features depending on object distance. (c) 2006 Elsevier B.V. All rights reserved.

关键词： electrolocation population coding receptor afferent neural model synchronous firing

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population coding with unreliable spikes

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NEUROCOMPUTING 2002年 44卷 323-328页

作者： Bethge, M Pawelzik, K Univ Bremen Inst Theoret Phys D-28334 Bremen Germany

The need for a neuronal coding scheme that is robust against the corruption of action potentials seems to support the idea of population rate coding, where the relevance of a single spike decreases proportional to the increase of population size. In order to test this intuition, we here investigate the efficiency and robustness of a population rate coding scheme in comparison to a place coding scheme using identical noise model. It turns out that the efficiency of population rate coding is substantially worse than that of place coding even if the generation or propagation of spikes are highly unreliable processes. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： rate coding place coding reliability of spikes population coding synaptic reliability

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population coding BY SIMULTANEOUS ACTIVITIES OF NEURONS IN INTRINSIC COORDINATE SYSTEMS DEFINED BY THEIR RECEPTIVE-FIELD WEIGHTING FUNCTIONS

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NEURAL NETWORKS 1993年第4期6卷 499-515页

作者： GAAL, G UNIV PENN PHILADELPHIAPA 19104

In this paper we address the problem of how external stimuli from the outside world, which can be represented as vectors by a set of numbers, might be expressed, transformed, and possibly reconstructed in neuronal networks of sensory brain areas. Our work is based on the approach of modeling the firing rate responses of simple linear sensory neurons. As characteristic functions, the receptive field weighting profiles can be determined from the firing rate responses of linear neurons to external stimuli in electrophysiological experiments. The responses of such neurons to arbitrary stimuli can be described as a linear function of the dot product of the stimulus vector and a special vector, the receptive field weighting function. The stimulus vector can be reconstructed in the coordinate system whose basis vectors are the receptive field weighting functions of linear neurons as a linear combination of the basis vectors and some weighting coefficients calculated from the firing rates of the neurons. Georgopoulos, Kettner, and Schwartz developed a scheme of population coding to reconstruct a simple three-dimensional vector, the direction of an arm movement from results of electrophysiological observations in primate motor cortex. Daugman introduced an iterative algorithm to compress and reconstruct image vectors in a network of neural elements whose receptive field weighting functions were similar to receptive field weighting functions of orientation-selective neurons in cat visual cortex. Pellionisz and Llinas showed in their tensor network theory how sensorimotor transformations of vectors might take place in neuronal networks. We show how these seemingly different approaches are related and compare their advantages and disadvantages. We adopted the iterative algorithm of Daugman to code image vectors and calculated the weights of neural elements taking place in the reconstruction of the stimuli in different layers of the network. Then we determined what the receptive

关键词： population coding 2-D GABOR TRANSFORMS TENSOR NETWORK THEORY COVARIANT AND CONTRAVARIANT COORDINATES

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population coding and neural rhythmicity in the orbitofrontal cortex

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CRITICAL CONTRIBUTIONS OF THE ORBITOFRONTAL CORTEX TO BEHAVIOR 2011年第1期1239卷 149-161页

作者： Pennartz, Cyriel M. A. van Wingerden, Marijn Vinck, Martin Univ Amsterdam Cognit & Syst Neurosci Grp Ctr Neurosci Swammerdam Inst Life SciFac Sci NL-1098 XH Amsterdam Netherlands Univ Amsterdam Cognit Sci Ctr Amsterdam NL-1098 XH Amsterdam Netherlands Univ Dusseldorf Dept Comparat Psychol Inst Expt Psychol D-40225 Dusseldorf Germany

The orbitofrontal cortex has been implicated in the prediction of valuable outcomes based on environmental stimuli. However, it remains unknown how it represents outcome predictive information at the population level, and how it provides temporal structure to such representations. Here, we pay attention especially to the population coding of probabilistic reward, and to the importance of orbitofrontal theta- and gamma-band rhythmicity in relation to target areas. When rats learned to associate odors to food outcome with variable likelihood, we found single-cell and population coding of reward probability, but not uncertainty. In related experiments, reward anticipation correlated to firing activity locking to theta-band oscillations. In contrast, gamma-band activity was associated with a firing-rate suppression of neurons that was most active during goal-directed movement. Orbitofrontal coding of outcome-relevant parameters appears bound to all relevant temporal phases of behavioral tasks, has a distributed nature, and is temporally structured according to multiple modes of rhythmicity.

关键词： phase locking population coding probability reward synchrony uncertainty

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population coding of self-motion: Applying Bayesian analysis to a population of visual Interneurons in the fly

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JOURNAL OF NEUROPHYSIOLOGY 2005年第3期94卷 2182-2194页

作者： Karmeier, K Krapp, HG Egelhaaf, M Univ Bielefeld Lehrstuhl Neurobiol D-33501 Bielefeld Germany Univ Cambridge Dept Zool Cambridge England

coding of sensory information often involves the activity of neuronal populations. We demonstrate how the accuracy of a population code depends on integration time, the size of the population, and noise correlation between the participating neurons. The population we study consists of 10 identified visual interneurons in the blowfly Calliphora vicina involved in optic flow processing. These neurons are assumed to encode the animal's head or body rotations around horizontal axes by means of graded potential changes. From electrophysiological experiments we obtain parameters for modeling the neurons' responses. From applying a Bayesian analysis on the modeled population response we draw three major conclusions. First, integration of neuronal activities over a time period of only 5 ms after response onset is sufficient to decode accurately the rotation axis. Second, noise correlation between neurons has only little impact on the population's performance. And third, although a population of only two neurons would be sufficient to encode any horizontal rotation axis, the population of 10 vertical system neurons is advantageous if the available integration time is short. For the fly, short integration times to decode neuronal responses are important when controlling rapid flight maneuvers.

关键词： .visual system applying fly Bayesian Analysis interneurons Exp Biol motion information self-motion population coding van Hateren Warzecha population of Visual

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population coding in an Innately Relevant Olfactory Area

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NEURON 2017年第5期93卷 1180-+页

作者： Iurilli, Giuliano Datta, Sandeep Robert Harvard Med Sch Dept Neurobiol Boston MA 02115 USA

Different olfactory cortical regions are thought to harbor distinct sensory representations, enabling each area to play a unique role in odor perception and behavior. In the piriform cortex (PCx), spatially dispersed sensory inputs evoke activity in distributed ensembles of neurons that act as substrates for odor learning. In contrast, the posterolateral cortical amygdala (plCoA) receives hardwired inputs that may link specific odor cues to innate olfactory behaviors. Here we show that despite stark differences in the patterning of plCoA and PCx inputs, odor-evoked neural ensembles in both areas are equally capable of discriminating odors, and exhibit similar odor tuning, reliability, and correlation structure. These results demonstrate that brain regions mediating odor-driven innate behaviors can, like brain areas involved in odor learning, represent odor objects using distributive population codes;these findings suggest both alternative mechanisms for the generation of innate odor-driven behaviors and additional roles for the plCoA in odor perception.

关键词： olfaction piriform cortex cortical amygdala innate population coding innate behavior sensory tuning

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