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人类大脑皮层中时间预期的神经特征代表事件概率密度。

Neural signatures of temporal anticipation in human cortex represent event probability density.

作者信息

Grabenhorst Matthias, Poeppel David, Michalareas Georgios

机构信息

Department of Cognitive Neuropsychology, Max-Planck-Institute for Empirical Aesthetics, Frankfurt, Germany.

Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany.

出版信息

Nat Commun. 2025 Mar 16;16(1):2602. doi: 10.1038/s41467-025-57813-7.

Abstract

Temporal prediction is a fundamental function of neural systems. Recent results show that humans anticipate future events by calculating probability density functions, rather than hazard rates. However, direct neural evidence for this hypothesized mechanism is lacking. We recorded neural activity using magnetoencephalography as participants anticipated auditory and visual events distributed in time. We show that temporal anticipation, measured as reaction times, approximates the event probability density function, but not hazard rate. Temporal anticipation manifests as spatiotemporally patterned activity in three anatomically and functionally distinct parieto-temporal and sensorimotor cortical areas. Each of these areas revealed a marked neural signature of anticipation: Prior to sensory cues, activity in a specific frequency range of neural oscillations, spanning alpha and beta ranges, encodes the event probability density function. These neural signals predicted reaction times to imminent sensory cues. These results demonstrate that supra-modal representations of probability density across cortex underlie the anticipation of future events.

摘要

时间预测是神经系统的一项基本功能。最近的研究结果表明,人类通过计算概率密度函数而非风险率来预测未来事件。然而,缺乏针对这一假设机制的直接神经证据。在参与者预期按时间分布的听觉和视觉事件时,我们使用脑磁图记录了神经活动。我们发现,以反应时间衡量的时间预期近似于事件概率密度函数,而非风险率。时间预期表现为三个在解剖学和功能上不同的顶颞叶及感觉运动皮层区域中的时空模式化活动。这些区域中的每一个都显示出明显的预期神经特征:在感觉线索出现之前,跨越阿尔法和贝塔范围的特定神经振荡频率范围内的活动对事件概率密度函数进行编码。这些神经信号预测了对即将到来的感觉线索的反应时间。这些结果表明,整个皮层上概率密度的超模态表征是对未来事件预期的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0868/11911442/bcbaa3168a06/41467_2025_57813_Fig1_HTML.jpg

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