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视觉神经元能够识别复杂的图像变换。

Visual neurons recognize complex image transformations.

作者信息

Hiramoto Masaki, Cline Hollis T

机构信息

Department of Neuroscience, Dorris Neuroscience Center, The Scripps Research Institute, La Jolla, CA 92037, USA.

出版信息

bioRxiv. 2024 Jun 10:2024.06.10.598314. doi: 10.1101/2024.06.10.598314.

Abstract

Natural visual scenes are dominated by sequences of transforming images. Spatial visual information is thought to be processed by detection of elemental stimulus features which are recomposed into scenes. How image information is integrated over time is unclear. We explored visual information encoding in the optic tectum. Unbiased stimulus presentation shows that the majority of tectal neurons recognize image sequences. This is achieved by temporally dynamic response properties, which encode complex image transitions over several hundred milliseconds. Calcium imaging reveals that neurons that encode spatiotemporal image sequences fire in spike sequences that predict a logical diagram of spatiotemporal information processing. Furthermore, the temporal scale of visual information is tuned by experience. This study indicates how neurons recognize dynamic visual scenes that transform over time.

摘要

自然视觉场景由变换图像序列主导。空间视觉信息被认为是通过检测重新组合成场景的基本刺激特征来处理的。目前尚不清楚图像信息如何随时间整合。我们探索了视顶盖中的视觉信息编码。无偏刺激呈现表明,大多数顶盖神经元能识别图像序列。这是通过时间动态响应特性实现的,该特性在数百毫秒内编码复杂的图像转换。钙成像显示,编码时空图像序列的神经元以尖峰序列放电,这些尖峰序列预测了时空信息处理的逻辑图。此外,视觉信息的时间尺度由经验调整。这项研究表明了神经元如何识别随时间变换的动态视觉场景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/094c/11195111/fd49a37d66de/nihpp-2024.06.10.598314v1-f0001.jpg

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