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爆发式放电通过电感觉神经群体优化自然通信信号的不变编码。

Burst firing optimizes invariant coding of natural communication signals by electrosensory neural populations.

作者信息

Metzen Michael G, Akhshi Amin, Bashivan Pouya, Khadra Anmar, Chacron Maurice J

机构信息

Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada.

Mila, Québec AI Institute, Université de Montréal, Montreal, QC H2S 3H1, Canada.

出版信息

iScience. 2025 Apr 9;28(5):112399. doi: 10.1016/j.isci.2025.112399. eCollection 2025 May 16.

Abstract

Accurate perception of objects within the environment independent of context is essential for the survival of an organism. While neurons that respond in an invariant manner to different stimulus waveforms resulting from identitypreserving transformations of objects are thought to provide a neural correlate of context-independent perception, how such responses emerge in the brain remains poorly understood. Here, we demonstrate that burst firing in neural populations can give rise to an invariant representation of highly heterogeneous natural communication stimuli. Multi-unit recordings from central sensory neural populations showed that considering burst spike trains led to invariant representations at the population but not the single neuron level. Computational modeling further revealed that optimal invariance is achieved at burst firing levels seen experimentally. Taken together, our results demonstrate an important function for burst firing toward establishing invariant representations of sensory input in neural populations.

摘要

独立于上下文准确感知环境中的物体对于生物体的生存至关重要。虽然那些对物体身份保持变换产生的不同刺激波形以不变方式做出反应的神经元被认为提供了与上下文无关感知的神经关联,但这种反应如何在大脑中出现仍知之甚少。在这里,我们证明神经群体中的爆发式放电可以产生高度异质的自然通信刺激的不变表示。来自中枢感觉神经群体的多单元记录表明,考虑爆发式尖峰序列会在群体水平而非单个神经元水平上产生不变表示。计算模型进一步揭示,在实验观察到的爆发式放电水平上可实现最佳不变性。综合来看,我们的结果证明了爆发式放电对于在神经群体中建立感觉输入的不变表示具有重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/135f/12245443/a179fe22ae79/fx1.jpg

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