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Priority coding in the visual system

delete2022-04-11
delete23
PRE
AI
N
Nicole C. Rust *
M
Marlene R. Cohen
DOI:10.1038/s41583-022-00582-9delete
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摘要

摘要

En 中文
Although we are continuously bombarded with visual input, only a fraction of incoming visual events is perceived, remembered or acted on. The neural underpinnings of various forms of visual priority coding, including perceptual expertise, goal-directed attention, visual salience, image memorability and preferential looking, have been studied. Here, we synthesize information from these different examples to review recent developments in our understanding of visual priority coding and its neural correlates, with a focus on the role of behaviour to evaluate candidate correlates. We propose that the brain combines different types of priority into a unified priority signal while also retaining the ability to differentiate between them, and that this happens by leveraging partially overlapping low-dimensional neural subspaces for each type of priority that are shared with the downstream neural populations involved in decision-making. Finally, we describe the gulfs in understanding that have resulted from different research approaches, and we point towards future directions that will lead to fundamental insights about neural coding and how prioritization influences visually guided behaviours. Prioritization of visual inputs manifests itself in different behavioural signatures. In this Review, Rust and Cohen describe these signatures and their neural correlates and suggest that the brain uses a unified priority signal from which downstream areas can decode different types of priority.
Keyword:
FEATURE-BASED ATTENTION
GAMMA-BAND SYNCHRONIZATION
CORRELATED NEURONAL-ACTIVITY
NEURAL MECHANISMS
TOP-DOWN
LONG-TERM
AREA V4
INTRINSIC MEMORABILITY
NORMALIZATION MODEL
POPULATION ACTIVITY

期刊

Nature Reviews Neuroscience 封面图
Nature Reviews Neuroscience
IF:
26.7
论文数:
4.0K
被引数:
4.8W

机构

U
university of pennsylvania
学者数:
9.2W
论文数: 7.8W
被引数: 153
P
pennsylvania commonwealth system of higher education (pcshe)
学者数:
12.9W
论文数: 11.7W
被引数: 177
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