Brain-wide dynamic coactivation states code for hand movements in the resting state

Resting brain activity, in the absence of explicit tasks, appears as distributed spatiotemporal patterns that reflect structural connectivity and correlate with behavioral traits. However, its role in shaping behavior remains unclear. Recent evidence shows that resting-state spatial patterns not only align with task-evoked topographies but also encode distinct visual (e.g., lines, contours, faces, places) and motor (e.g., hand postures) features, suggesting mechanisms for long-term storage and predictive coding. While prior research focused on static, time-averaged task activations, we examine whether dynamic, time-varying motor states seen during active hand movements are also present at rest. Three distinct motor activation states, engaging the motor cortex alongside sensory and association areas, were identified. These states appeared both at rest and during task execution but underwent temporal reorganization from rest to task. Thus, resting-state dynamics serve as strong spatiotemporal priors for task-based activation. Critically, resting-state patterns more closely resembled those associated with frequent ecological hand movements than with an unfamiliar movement, indicating a structured repertoire of movement patterns that is replayed at rest and reorganized during action. This suggests that spontaneous neural activity provides priors for future movements and contributes to long-term memory storage, reinforcing the functional interplay between resting and task-driven brain activity.

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Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-03-12
DOI
https://doi.org/10.1073/pnas.2415508122
Citations
5
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
7.16

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article

Brain-wide dynamic coactivation states code for hand movements in the resting state

Lorenzo Pini, Maurizio Corbetta, Lu Zhang, Gordon L. Shulman
5 citations
Proceedings of the National Academy of Sciences
EEG and Brain-Computer Interfaces
7.16
article

Brain-wide dynamic coactivation states code for hand movements in the resting state

Lorenzo Pini, Maurizio Corbetta, Lu Zhang, Gordon L. Shulman
article en
5 citations

Abstract

Resting brain activity, in the absence of explicit tasks, appears as distributed spatiotemporal patterns that reflect structural connectivity and correlate with behavioral traits. However, its role in shaping behavior remains unclear. Recent evidence shows that resting-state spatial patterns not only align with task-evoked topographies but also encode distinct visual (e.g., lines, contours, faces, places) and motor (e.g., hand postures) features, suggesting mechanisms for long-term storage and predictive coding. While prior research focused on static, time-averaged task activations, we examine whether dynamic, time-varying motor states seen during active hand movements are also present at rest. Three distinct motor activation states, engaging the motor cortex alongside sensory and association areas, were identified. These states appeared both at rest and during task execution but underwent temporal reorganization from rest to task. Thus, resting-state dynamics serve as strong spatiotemporal priors for task-based activation. Critically, resting-state patterns more closely resembled those associated with frequent ecological hand movements than with an unfamiliar movement, indicating a structured repertoire of movement patterns that is replayed at rest and reorganized during action. This suggests that spontaneous neural activity provides priors for future movements and contributes to long-term memory storage, reinforcing the functional interplay between resting and task-driven brain activity.

Proceedings of the National Academy of SciencesVol. 122(11)
Ningbo University (CN), University of Padua (IT), Washington University in St. Louis (US), Veneto Institute of Molecular Medicine (IT), Ningbo Kangning Hospital (CN), Institute of Molecular Medicine (IN)
Fondazione Cassa di Risparmio di Padova e Rovigo, Ministero della Salute
Openalex Percentile: Top 3%
EEG and Brain-Computer Interfaces
7.16
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