Treffer: Spontaneous Activity Patterns in Human Attention Networks Code for Hand Movements.

Title:
Spontaneous Activity Patterns in Human Attention Networks Code for Hand Movements.
Authors:
Lu Zhang1, Pini, Lorenzo1, DoHyun Kim2, Shulman, Gordon L.2, Corbetta, Maurizio1,2,3,4 maurizio.corbetta@unipd.it
Source:
Journal of Neuroscience. 3/15/2023, Vol. 43 Issue 11, p1976-1986. 11p.
Database:
Academic Search Index

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Recent evidence suggests that, in the absence of any task, spontaneous brain activity patterns and connectivity in the visual and motor cortex code for natural stimuli and actions, respectively. These “resting-state” activity patterns may underlie the maintenance and consolidation (replay) of information states coding for ecological stimuli and behaviors. In this study, we examine whether replay patterns occur in resting-state activity in association cortex grouped into high-order cognitive networks not directly processing sensory inputs or motor outputs. Fifteen participants (7 females) performed four hand movements during an fMRI study. Three movements were ecological. The fourth movement as control was less ecological. Before and after the task scans, we acquired resting-state fMRI scans. The analysis examined whether multivertex task activation patterns for the four movements computed at the cortical surface in different brain networks resembled spontaneous activity patterns measured at rest. For each movement, we computed a vector of r values indicating the strength of the similarity between the mean task activation pattern and frame-by-frame resting-state patterns. We computed a cumulative distribution function of r² values and used the 90th percentile cutoff value for comparison. In the dorsal attention network, resting-state patterns were more likely to match task patterns for the ecological movements than the control movement. In contrast, resttask pattern correlation was more likely for less ecological movement in the ventral attention network. These findings show that spontaneous activity patterns in human attention networks code for hand movements. [ABSTRACT FROM AUTHOR]