环境运动先于自运动调制航向估计。

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
PLoS Computational Biology Pub Date : 2025-10-09 eCollection Date: 2025-10-01 DOI:10.1371/journal.pcbi.1013571
Liana Nafisa Saftari, Jongmin Moon, Oh-Sang Kwon
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引用次数: 0

摘要

运动观察者准确感知其前进方向的能力对于有效的运动和平衡控制至关重要。虽然先前的研究表明,观察者在运动过程中整合了视觉和前庭信号,但尚不清楚观察者是否以及如何使用运动前收集的视觉信号来感知方向。在此,我们研究了发生在自我运动之前的环境运动对自我运动感知的影响。人类观察者坐在一个运动平台上,观看视觉运动刺激,然后报告他们在平台移动后感知到的头部。结果表明,在观察者运动之前呈现的环境运动显著调节了他们的头球感知。我们使用一个规范的计算模型来解释这种影响,该模型考虑了观察者运动之前和运动期间产生的视觉信号之间的因果关系。总的来说,我们的研究强调了在自我运动之前呈现的环境运动在头球感知中的关键作用,拓宽了目前关于头球估计背后的计算机制的观点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Environmental motion presented ahead of self-motion modulates heading direction estimation.

The ability of a moving observer to accurately perceive their heading direction is essential for effective locomotion and balance control. While previous studies have shown that observers integrate visual and vestibular signals collected during movement, it remains unclear whether and how observers use visual signals collected before their movement to perceive heading direction. Here we investigate the effect of environmental motion that occurred ahead of self-motion on the perception of self-motion. Human observers sat on a motion platform, viewed visual motion stimuli, and then reported their perceived heading after the platform moved. The results reveal that environmental motion presented before the observers' movement significantly modulates their heading perception. We account for this effect using a normative computational model that takes into account the causal relationship between visual signals generated before and during the observers' movement. Overall, our study highlights the crucial role of environmental motion presented before self-motion in heading perception, broadening the current perspective on the computational mechanisms behind heading estimation.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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