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自然 ITD 统计数据可预测人类听觉空间感知。

Natural ITD statistics predict human auditory spatial perception.

机构信息

Dominick P. Purpura Department of Neuroscience - Albert Einstein College of Medicine, New York, United States.

Centro de Matemática, Computação e Cognição - Universidade Federal do ABC, Santo André, Brazil.

出版信息

Elife. 2020 Oct 12;9:e51927. doi: 10.7554/eLife.51927.

Abstract

A neural code adapted to the statistical structure of sensory cues may optimize perception. We investigated whether interaural time difference (ITD) statistics inherent in natural acoustic scenes are parameters determining spatial discriminability. The natural ITD rate of change across azimuth (ITDrc) and ITD variability over time (ITDv) were combined in a Fisher information statistic to assess the amount of azimuthal information conveyed by this sensory cue. We hypothesized that natural ITD statistics underlie the neural code for ITD and thus influence spatial perception. To test this hypothesis, sounds with invariant statistics were presented to measure human spatial discriminability and spatial novelty detection. Human auditory spatial perception showed correlation with natural ITD statistics, supporting our hypothesis. Further analysis showed that these results are consistent with classic models of ITD coding and can explain the ITD tuning distribution observed in the mammalian brainstem.

摘要

一种适应于感觉提示的统计结构的神经编码可能会优化感知。我们研究了在自然声场景中固有的耳间时间差(ITD)统计是否是决定空间可分辨性的参数。在方位角上的自然 ITD 变化率(ITDrc)和随时间的 ITD 可变性(ITDv)被组合在 Fisher 信息统计中,以评估该感觉提示传递的方位信息的数量。我们假设自然 ITD 统计是 ITD 神经编码的基础,因此会影响空间感知。为了检验这一假设,我们呈现了具有不变统计特性的声音,以测量人类的空间可分辨性和空间新颖性检测。人类听觉空间感知与自然 ITD 统计具有相关性,支持了我们的假设。进一步的分析表明,这些结果与 ITD 编码的经典模型一致,并且可以解释在哺乳动物脑干中观察到的 ITD 调谐分布。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d8/7661036/80000022147e/elife-51927-fig1.jpg

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