Department of Brain and Cognitive Sciences, Center for Visual Science, University of Rochester, Rochester, NY 14627, USA.
Center for Brain and Cognition & Department of Engineering, Universitat Pompeu Fabra, Barcelona 08002, Spain; Serra Húnter Fellow Programme, Universitat Pompeu Fabra, Barcelona 08002, Spain.
Curr Biol. 2024 Nov 4;34(21):4983-4997.e9. doi: 10.1016/j.cub.2024.09.030. Epub 2024 Oct 9.
For the brain to compute object motion in the world during self-motion, it must discount the global patterns of image motion (optic flow) caused by self-motion. Optic flow parsing is a proposed visual mechanism for computing object motion in the world, and studies in both humans and monkeys have demonstrated perceptual biases consistent with the operation of a flow-parsing mechanism. However, the neural basis of flow parsing remains unknown. We demonstrate, at both the individual unit and population levels, that neural activity in macaque middle temporal (MT) area is biased by peripheral optic flow in a manner that can at least partially account for perceptual biases induced by flow parsing. These effects cannot be explained by conventional surround suppression mechanisms or choice-related activity and have substantial neural latency. Together, our findings establish the first neural basis for the computation of scene-relative object motion based on flow parsing.
为了使大脑在自身运动期间计算世界中的物体运动,它必须扣除由自身运动引起的全局图像运动模式(光流)。光流解析是一种用于计算世界中物体运动的拟议视觉机制,人类和猴子的研究都证明了与流解析机制的运作一致的感知偏差。然而,光流解析的神经基础仍然未知。我们在个体单元和群体水平上都证明了猕猴中颞(MT)区的神经活动偏向于外围光流,这种方式至少可以部分解释由光流解析引起的感知偏差。这些影响不能用传统的环绕抑制机制或与选择相关的活动来解释,而且具有很大的神经潜伏期。总之,我们的发现确立了基于光流解析计算基于场景的相对物体运动的第一个神经基础。