Mechanically Induced Motor Tremors Disrupt the Perception of Time.

IF 2.7 3区 医学 Q3 NEUROSCIENCES eNeuro Pub Date : 2024-09-16 Print Date: 2024-09-01 DOI:10.1523/ENEURO.0013-24.2024
Keri Gladhill, Rose De Kock, Weiwei Zhou, Wilsaan Joiner, Martin Wiener
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Abstract

Contemporary research has begun to show a strong relationship between movements and the perception of time. More specifically, concurrent movements serve to both bias and enhance time estimates. To explain these effects, we recently proposed a mechanism by which movements provide a secondary channel for estimating duration that is combined optimally with sensory estimates. However, a critical test of this framework is that by introducing "noise" into movements, sensory estimates of time should similarly become noisier. To accomplish this, we had human participants move a robotic arm while estimating intervals of time in either auditory or visual modalities (n = 24, ea.). Crucially, we introduced an artificial "tremor" in the arm while subjects were moving, that varied across three levels of amplitude (1-3 N) or frequency (4-12 Hz). The results of both experiments revealed that increasing the frequency of the tremor led to noisier estimates of duration. Further, the effect of noise varied with the base precision of the interval, such that a naturally less precise timing (i.e., visual) was more influenced by the tremor than a naturally more precise modality (i.e., auditory). To explain these findings, we fit the data with a recently developed drift-diffusion model of perceptual decision-making, in which the momentary, within-trial variance was allowed to vary across conditions. Here, we found that the model could recapitulate the observed findings, further supporting the theory that movements influence perception directly. Overall, our findings support the proposed framework, and demonstrate the utility of inducing motor noise via artificial tremors.

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机械诱发的运动震颤会扰乱时间感知
当代的研究已经开始表明,动作与时间感知之间有着密切的关系。更具体地说,同时发生的动作既会使时间估计出现偏差,又会增强时间估计。为了解释这些影响,我们最近提出了一种机制,即根据贝叶斯线索组合,动作为估计持续时间提供了一个辅助渠道,该渠道与感官估计进行了优化组合。然而,对这一框架的一个关键测试是,通过在动作中引入 "噪音",感官对时间的估计也应按照线索组合方程所预测的方式变得更加嘈杂。为了实现这一目标,我们让人类参与者一边移动机械臂,一边用听觉或视觉模式估计时间间隔(24 人,每人)。最重要的是,我们在受试者移动时在手臂上引入了人工 "震颤",震颤幅度(1-3 N)或频率(4-12 Hz)分为三个等级。这两项实验的结果都表明,增加震颤频率会导致对持续时间的估算变得更加嘈杂;然而,这种影响在频率较高时趋于平稳,而不是线性增加,这一发现与最佳整合相一致。此外,噪声的影响随时间间隔的基本精度而变化,因此,自然精度较低的计时方式(即视觉)比自然精度较高的计时方式(即听觉)受震颤的影响更大。为了解释这些发现,我们用最近开发的知觉决策漂移-扩散模型对数据进行了拟合。在此,我们发现该模型可以再现观察到的结果,进一步支持了运动直接影响知觉的理论。总之,我们的研究结果支持所提出的框架,并证明了通过人工震颤诱发运动噪音的实用性,从而为临床上以震颤为特征的运动障碍提供了实用性。然而,人们对身体运动如何偏差或增强时间估算仍不甚了解。我们最近提出,通过贝叶斯线索组合机制,肢体运动的时间估计与其他感官模式的时间估计相结合。这表明,通过在肢体运动中加入噪声,其他感官模式的时间估计值也会变得更加嘈杂。在这里,我们在两个实验中发现了这种效应的证据,在这两个实验中,人类受试者在不同的震颤程度下移动机械臂时判断时间间隔。这些发现支持了肢体运动与时间之间的联系,并为利用噪声运动影响感官估计提供了新的研究途径。
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来源期刊
eNeuro
eNeuro Neuroscience-General Neuroscience
CiteScore
5.00
自引率
2.90%
发文量
486
审稿时长
16 weeks
期刊介绍: An open-access journal from the Society for Neuroscience, eNeuro publishes high-quality, broad-based, peer-reviewed research focused solely on the field of neuroscience. eNeuro embodies an emerging scientific vision that offers a new experience for authors and readers, all in support of the Society’s mission to advance understanding of the brain and nervous system.
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