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预测穿透感知:来自大脑、行为和疾病的融合见解。

Predictions penetrate perception: Converging insights from brain, behaviour and disorder.

作者信息

O'Callaghan Claire, Kveraga Kestutis, Shine James M, Adams Reginald B, Bar Moshe

机构信息

Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK; Department of Psychology, University of Cambridge, Cambridge, UK; Brain and Mind Centre, University of Sydney, Sydney, Australia.

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.

出版信息

Conscious Cogn. 2017 Jan;47:63-74. doi: 10.1016/j.concog.2016.05.003. Epub 2016 May 21.

Abstract

It is argued that during ongoing visual perception, the brain is generating top-down predictions to facilitate, guide and constrain the processing of incoming sensory input. Here we demonstrate that these predictions are drawn from a diverse range of cognitive processes, in order to generate the richest and most informative prediction signals. This is consistent with a central role for cognitive penetrability in visual perception. We review behavioural and mechanistic evidence that indicate a wide spectrum of domains-including object recognition, contextual associations, cognitive biases and affective state-that can directly influence visual perception. We combine these insights from the healthy brain with novel observations from neuropsychiatric disorders involving visual hallucinations, which highlight the consequences of imbalance between top-down signals and incoming sensory information. Together, these lines of evidence converge to indicate that predictive penetration, be it cognitive, social or emotional, should be considered a fundamental framework that supports visual perception.

摘要

有人认为,在持续的视觉感知过程中,大脑会生成自上而下的预测,以促进、引导和约束传入感觉输入的处理。在这里,我们证明这些预测来自各种各样的认知过程,以便生成最丰富、最具信息性的预测信号。这与认知可穿透性在视觉感知中的核心作用是一致的。我们回顾了行为和机制证据,这些证据表明包括物体识别、情境联想、认知偏差和情感状态在内的广泛领域都可以直接影响视觉感知。我们将来自健康大脑的这些见解与涉及视幻觉的神经精神疾病的新观察结果相结合,这些观察结果突出了自上而下信号与传入感觉信息之间不平衡的后果。总之,这些证据线索都表明,无论是认知、社会还是情感方面的预测性穿透,都应被视为支持视觉感知的基本框架。

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