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自我运动的神经编码。

The neural encoding of self-motion.

机构信息

Department of Physiology, McGill University, Montreal, PQ, H3G 1Y6, Canada.

出版信息

Curr Opin Neurobiol. 2011 Aug;21(4):587-95. doi: 10.1016/j.conb.2011.05.022.

Abstract

As we move through the world, information can be combined from multiple sources in order to allow us to perceive our self-motion. The vestibular system detects and encodes the motion of the head in space. In addition, extra-vestibular cues such as retinal-image motion (optic flow), proprioception, and motor efference signals, provide valuable motion cues. Here I focus on the coding strategies that are used by the brain to create neural representations of self-motion. I review recent studies comparing the thresholds of single versus populations of vestibular afferent and central neurons. I then consider recent advances in understanding the brain's strategy for combining information from the vestibular sensors with extra-vestibular cues to estimate self-motion. These studies emphasize the need to consider not only the rules by which multiple inputs are combined, but also how differences in the behavioral context govern the nature of what defines the optimal computation.

摘要

当我们在这个世界上移动时,信息可以从多个来源组合起来,以便我们感知自己的运动。前庭系统检测并编码头部在空间中的运动。此外,额外的前庭线索,如视网膜图像运动(视流)、本体感觉和运动传出信号,提供了有价值的运动线索。在这里,我专注于大脑用于创建自我运动神经表示的编码策略。我回顾了最近的研究,比较了单个和前庭传入和中枢神经元群体的阈值。然后,我考虑了最近在理解大脑结合来自前庭传感器和额外前庭线索的信息来估计自我运动的策略方面的进展。这些研究强调,不仅需要考虑多个输入组合的规则,还需要考虑行为背景的差异如何控制定义最佳计算的性质。

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