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大脑是如何计算视觉显著性的?来自行为学、神经生物学和建模的见解。

How is visual salience computed in the brain? Insights from behaviour, neurobiology and modelling.

作者信息

Veale Richard, Hafed Ziad M, Yoshida Masatoshi

机构信息

Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Japan.

Physiology of Active Vision Laboratory, Werner Reichardt Centre for Integrative Neuroscience, University of Tuebingen, Tuebingen, Germany.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2017 Feb 19;372(1714). doi: 10.1098/rstb.2016.0113. Epub 2017 Jan 2.

Abstract

Inherent in visual scene analysis is a bottleneck associated with the need to sequentially sample locations with foveating eye movements. The concept of a 'saliency map' topographically encoding stimulus conspicuity over the visual scene has proven to be an efficient predictor of eye movements. Our work reviews insights into the neurobiological implementation of visual salience computation. We start by summarizing the role that different visual brain areas play in salience computation, whether at the level of feature analysis for bottom-up salience or at the level of goal-directed priority maps for output behaviour. We then delve into how a subcortical structure, the superior colliculus (SC), participates in salience computation. The SC represents a visual saliency map via a centre-surround inhibition mechanism in the superficial layers, which feeds into priority selection mechanisms in the deeper layers, thereby affecting saccadic and microsaccadic eye movements. Lateral interactions in the local SC circuit are particularly important for controlling active populations of neurons. This, in turn, might help explain long-range effects, such as those of peripheral cues on tiny microsaccades. Finally, we show how a combination of in vitro neurophysiology and large-scale computational modelling is able to clarify how salience computation is implemented in the local circuit of the SC.This article is part of the themed issue 'Auditory and visual scene analysis'.

摘要

视觉场景分析中固有的一个瓶颈与通过注视眼动顺序采样位置的需求相关。“显著性图”的概念,即在视觉场景上对刺激显著性进行地形编码,已被证明是眼动的有效预测指标。我们的工作回顾了对视觉显著性计算的神经生物学实现的见解。我们首先总结不同视觉脑区在显著性计算中所起的作用,无论是在自下而上显著性的特征分析层面,还是在输出行为的目标导向优先级图层面。然后,我们深入探讨一个皮层下结构,即上丘(SC),如何参与显著性计算。上丘通过表层的中心-外周抑制机制来表示视觉显著性图,该机制输入到深层的优先级选择机制中,从而影响扫视和微扫视眼动。上丘局部回路中的侧向相互作用对于控制神经元的活跃群体尤为重要。这反过来可能有助于解释远距离效应,例如外周线索对微小微扫视的影响。最后,我们展示了体外神经生理学和大规模计算建模的结合如何能够阐明显著性计算在上丘局部回路中是如何实现的。本文是主题为“听觉和视觉场景分析”的特刊的一部分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f129/5206280/c9c4940a3069/rstb20160113-g1.jpg

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