Recurrent Processing Drives Perceptual Plasticity

Ke Jia

doi:10.1016/j.cub.2020.08.016

2020-11-01

Christopher T. Rodgers

Guy Williams

Rainer Goebel

Zoe Kourtzi *

DOI：10.1016/j.cub.2020.08.016

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摘要

En 中文

学习和经验对于将模糊的感官信息从我们的环境转化为感知决策至关重要。然而，关于训练如何塑造成人大脑的证据仍然存在争议，因为标准分辨率的fMRI不允许我们辨别构成感觉可塑性基础的更精细的尺度机制。在这里，我们将亚毫米分辨率的超高场 (7t) 功能成像与方向辨别训练相结合，以询问已知支持可解离的大脑计算的皮质深度的经验依赖性可塑性。我们证明，学习改变了表面而不是中间或更深的V1层中的特定于方向的表示，这与通过水平连接的经常性可塑性机制一致。此外，学习增加了枕顶叶区域的前馈而不是反馈层到层的连通性，这表明感觉可塑性可以控制感知决策。我们的发现揭示了更精细的可塑性机制，重新加权感觉信号以告知改进的决策，弥合了依赖于经验的可塑性的微观和宏观电路之间的差距。

Keyword:

PRIMARY VISUAL-CORTEX

INTRINSIC CONNECTIONS

ANALYSIS STRATEGIES

GE BOLD

7 T

ORIENTATION

SPECIFICITY

LAYERS

MODEL

AI总结

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期刊

Current Biology

IF:

7.5

论文数:

2.2W

被引数:

7.8W

机构

Maastricht University

学者数:

3.1W

论文数: 2.8W

被引数: 277

University of Cambridge

学者数:

7.7W

论文数: 7.1W

被引数: 13.7W

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