Population codes in the visual cortex

被引：12

作者：

Tanabe, Seiji ^{[1
]}

机构：

[1] Yeshiva Univ, Albert Einstein Coll Med, Dept Neurosci, Bronx, NY 10461 USA

来源：

NEUROSCIENCE RESEARCH | 2013年 / 76卷 / 03期

基金：

美国国家卫生研究院;

关键词：

Population code; Visual cortex; Perceptual decision; Linear decoder; Bayesian inference; INFERIOR TEMPORAL CORTEX; NEURONAL POPULATION; NEURAL POPULATION; CORTICAL-NEURONS; ORIENTATION; INFORMATION; CELLS; REPRESENTATION; VARIABILITY; PERFORMANCE;

D O I：

10.1016/j.neures.2013.03.010

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

Every sensory event elicits activity in a broad population of cells that is distributed within and across cortical areas. How these neurons function together to represent the sensory environment is a major question in systems neuroscience. A number of proposals have been made, and recent advances in multi-neuronal recording have begun to allow researchers to test the predictions of these population-coding theories. In this review, I provide an introduction to some of the key concepts in population coding and describe several studies in the recent literature. The focus of this review is on sensory representation in the visual cortex and related perceptual decisions. The frameworks used to study population coding include population vectors, linear decoders, and Bayesian inference. Simple examples are provided to illustrate these concepts. Testing theories of population coding is an emerging subject in systems neuroscience, but advances in multi-neuronal recording and analysis suggest that an understanding is within reach. (c) 2013 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

引用

页码：101 / 105

页数：5

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