Metastable neural dynamics underlies cognitive performance across multiple behavioural paradigms. Issue 12 (17th April 2020)

• Record Type: Journal Article
• Authors: Alderson, Thomas H.; Bokde, Arun L. W.; Kelso, J. A. Scott; Maguire, Liam; Coyle, Damien
• Is Part Of: Human brain mapping. Volume 41:Issue 12(2020)
• Page Start: 3212
• Page End: 3234
• Publication Date: 2020-04-17
• Subjects: cognition -- coordination dynamics -- coordination dynamics -- deep learning -- fMRI -- metastability -- metastable neural dynamics -- neurocognitive networks -- resting state; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.25009
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Despite resting state networks being associated with a variety of cognitive abilities, it remains unclear how these local areas act in concert to express particular cognitive operations. Theoretical and empirical accounts indicate that large‐scale resting state networks reconcile dual tendencies towards integration and segregation by operating in a metastable regime of their coordination dynamics. Metastability may confer important behavioural qualities by binding distributed local areas into large‐scale neurocognitive networks. We tested this hypothesis by analysing fMRI data in a large cohort of healthy individuals ( N = 566) and comparing the metastability of the brain's large‐scale resting network architecture at rest and during the performance of several tasks. Metastability was estimated using a well‐defined collective variable capturing the level of 'phase‐locking' between large‐scale networks over time. Task‐based reasoning was principally characterised by high metastability in cognitive control networks and low metastability in sensory processing areas. Although metastability between resting state networks increased during task performance, cognitive ability was more closely linked to spontaneous activity. High metastability in the intrinsic connectivity of cognitive control networks was linked to novel problem solving or fluid intelligence, but was less important in tasks relying on previous experience or crystallised intelligence. Crucially, subjects with resting architectures similar or 'pre‐configured' to a task‐general arrangement demonstrated superior cognitive performance. Taken together, our findings support a key linkage between the spontaneous metastability of large‐scale networks in the cerebral cortex and cognition. Abstract : Although metastability between resting state networks increased during task, cognitive performance was more closely linked to the intrinsic or spontaneous metastability of network interactions. High resting state metastability in cognitive control networks was linked to novel problem solving or fluid intelligence, but was less important in tasks relying on previous experience or crystallized intelligence. Subjects with resting state architectures similar or 'pre‐configured' to a task‐general configuration demonstrated superior cognitive performance linked to efficient switching of network states.