Distinct distributed brain networks dissociate self-generated mental states DOI Creative Commons
Nathan Anderson, Joseph J. Salvo, Jonathan Smallwood

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

Human cognition relies on two modes: a perceptually-coupled mode where mental states are driven by sensory input and perceptually-decoupled featuring self-generated content. Past work suggests that imagined supported the reinstatement of activity in cortex, but transmodal systems within canonical default network also implicated mind-wandering, recollection, imagining future. We identified brain supporting using precision fMRI. Participants different scenarios scanner, then rated their several properties multi-dimensional experience sampling. found thinking involving scenes evoked or near network, while speech language network. Imagining-related regions overlapped with viewing listening to speech, respectively; however, this overlap was predominantly association networks, rather than adjacent unimodal networks. The results suggest networks support high visual auditory vividness. Different large-scale audiolinguistic

Language: Английский

Situating the salience and parietal memory networks in the context of multiple parallel distributed networks using precision functional mapping DOI Creative Commons
Young Hye Kwon, Joseph J. Salvo, Nathan Anderson

et al.

Cell Reports, Journal Year: 2025, Volume and Issue: 44(1), P. 115207 - 115207

Published: Jan. 1, 2025

Language: Английский

Citations

2

Within-Individual Precision Mapping of Brain Networks Exclusively Using Task Data DOI Creative Commons
Jingnan Du, Maxwell L. Elliott, Joanna Ladopoulou

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 25, 2025

Precision mapping of brain networks within individuals has become a widely used tool that prevailingly relies on functional connectivity analysis resting-state data. Here we explored whether could be precisely estimated solely using data acquired during active task paradigms. The straightforward strategy involved extracting residualized after application task-based general linear model (GLM) and then applying standard analysis. Functional correlation matrices from were highly similar to those derived traditional fixation largest factor affecting similarity between was the amount Networks within-individual displayed strong spatial overlap with predicted same triple dissociation in independent implications these findings are (1) existing can reanalyzed estimate network organization, (2) restingstate pooled increase statistical power, (3) future studies exclusively acquire both extract responses. Most broadly, present results suggest there is an underlying, stable architecture idiosyncratic individual persists across states.

Language: Английский

Citations

0

Distinct distributed brain networks dissociate self-generated mental states DOI Creative Commons
Nathan Anderson, Joseph J. Salvo, Jonathan Smallwood

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 27, 2025

Human cognition relies on two modes: a perceptually-coupled mode where mental states are driven by sensory input and perceptually-decoupled featuring self-generated content. Past work suggests that imagined supported the reinstatement of activity in cortex, but transmodal systems within canonical default network also implicated mind-wandering, recollection, imagining future. We identified brain supporting using precision fMRI. Participants different scenarios scanner, then rated their several properties multi-dimensional experience sampling. found thinking involving scenes evoked or near network, while speech language network. Imagining-related regions overlapped with viewing listening to speech, respectively; however, this overlap was predominantly association networks, rather than adjacent unimodal networks. The results suggest networks support high visual auditory vividness. Different large-scale audiolinguistic

Language: Английский

Citations

0