Brain signal variability and executive functions across the life span.

Brain signal variability Cognitive flexibility Executive functions Life span Resting-state fMRI

Journal

Network neuroscience (Cambridge, Mass.)
ISSN: 2472-1751
Titre abrégé: Netw Neurosci
Pays: United States
ID NLM: 101719149

Informations de publication

Date de publication:
2024
Historique:
received: 21 04 2023
accepted: 23 10 2023
medline: 2 4 2024
pubmed: 2 4 2024
entrez: 2 4 2024
Statut: epublish

Résumé

Neural variability is thought to facilitate survival through flexible adaptation to changing environmental demands. In humans, such capacity for flexible adaptation may manifest as fluid reasoning, inhibition of automatic responses, and mental set-switching-skills falling under the broad domain of executive functions that fluctuate over the life span. Neural variability can be quantified via the BOLD signal in resting-state fMRI. Variability of large-scale brain networks is posited to underpin complex cognitive activities requiring interactions between multiple brain regions. Few studies have examined the extent to which network-level brain signal variability across the life span maps onto high-level processes under the umbrella of executive functions. The present study leveraged a large publicly available neuroimaging dataset to investigate the relationship between signal variability and executive functions across the life span. Associations between brain signal variability and executive functions shifted as a function of age. Limbic-specific variability was consistently associated with greater performance across subcomponents of executive functions. Associations between executive function subcomponents and network-level variability of the default mode and central executive networks, as well as whole-brain variability, varied across the life span. Findings suggest that brain signal variability may help to explain to age-related differences in executive functions across the life span. Traditionally, regional variability in brain signals has been viewed as a source of noise in human neuroimaging research. Our study demonstrates that brain signal variability may contain meaningful information related to psychological processes. We demonstrate that brain signal variability, particularly whole-brain variability, may serve as a reliable indicator of cognitive functions across the life span. Global variability and network-level variability play differing roles in supporting executive functions. Findings suggest that brain signal variability serves as a meaningful indicator of development and cognitive aging.

Autres résumés

Type: plain-language-summary (eng)
Traditionally, regional variability in brain signals has been viewed as a source of noise in human neuroimaging research. Our study demonstrates that brain signal variability may contain meaningful information related to psychological processes. We demonstrate that brain signal variability, particularly whole-brain variability, may serve as a reliable indicator of cognitive functions across the life span. Global variability and network-level variability play differing roles in supporting executive functions. Findings suggest that brain signal variability serves as a meaningful indicator of development and cognitive aging.

Identifiants

pubmed: 38562287
doi: 10.1162/netn_a_00347
pii: netn_a_00347
pmc: PMC10918754
doi:

Types de publication

Journal Article

Langues

eng

Pagination

226-240

Informations de copyright

© 2024 Massachusetts Institute of Technology.

Déclaration de conflit d'intérêts

Competing Interests: The authors have declared that no competing interests exist.

Auteurs

Zachary T Goodman (ZT)

Department of Psychology, University of Miami, Coral Gables, FL, USA.

Jason S Nomi (JS)

Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.

Salome Kornfeld (S)

Department of Psychology, University of Miami, Coral Gables, FL, USA.
REHAB Basel, Klinik für Neurorehabilitation und Paraplegiologie, Basel, Switzerland.

Taylor Bolt (T)

Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.

Roger A Saumure (RA)

Department of Psychology, University of Miami, Coral Gables, FL, USA.

Celia Romero (C)

Department of Psychology, University of Miami, Coral Gables, FL, USA.

Sierra A Bainter (SA)

Department of Psychology, University of Miami, Coral Gables, FL, USA.

Lucina Q Uddin (LQ)

Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.
Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA.

Classifications MeSH