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神经群体编码中相关性的结构与功能。

The structures and functions of correlations in neural population codes.

作者信息

Panzeri Stefano, Moroni Monica, Safaai Houman, Harvey Christopher D

机构信息

Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.

Istituto Italiano di Tecnologia, Rovereto, Italy.

出版信息

Nat Rev Neurosci. 2022 Sep;23(9):551-567. doi: 10.1038/s41583-022-00606-4. Epub 2022 Jun 22.

Abstract

The collective activity of a population of neurons, beyond the properties of individual cells, is crucial for many brain functions. A fundamental question is how activity correlations between neurons affect how neural populations process information. Over the past 30 years, major progress has been made on how the levels and structures of correlations shape the encoding of information in population codes. Correlations influence population coding through the organization of pairwise-activity correlations with respect to the similarity of tuning of individual neurons, by their stimulus modulation and by the presence of higher-order correlations. Recent work has shown that correlations also profoundly shape other important functions performed by neural populations, including generating codes across multiple timescales and facilitating information transmission to, and readout by, downstream brain areas to guide behaviour. Here, we review this recent work and discuss how the structures of correlations can have opposite effects on the different functions of neural populations, thus creating trade-offs and constraints for the structure-function relationships of population codes. Further, we present ideas on how to combine large-scale simultaneous recordings of neural populations, computational models, analyses of behaviour, optogenetics and anatomy to unravel how the structures of correlations might be optimized to serve multiple functions.

摘要

一群神经元的集体活动,超越了单个细胞的特性,对许多脑功能至关重要。一个基本问题是神经元之间的活动相关性如何影响神经群体处理信息的方式。在过去30年里,关于相关性的水平和结构如何塑造群体编码中的信息编码方面取得了重大进展。相关性通过成对活动相关性的组织(相对于单个神经元调谐的相似性)、通过其刺激调制以及通过高阶相关性的存在来影响群体编码。最近的研究表明,相关性还深刻地塑造了神经群体执行的其他重要功能,包括在多个时间尺度上生成编码以及促进信息向下游脑区的传输和读出以指导行为。在这里,我们回顾这项近期工作,并讨论相关性结构如何对神经群体的不同功能产生相反的影响,从而为群体编码的结构 - 功能关系创造权衡和限制。此外,我们提出了关于如何结合神经群体的大规模同步记录、计算模型、行为分析、光遗传学和解剖学来揭示相关性结构如何可能被优化以服务多种功能的想法。

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