Reassessing the Functional Significance of Blood Oxygen Level Dependent Variability.


Journal

Journal of cognitive neuroscience
ISSN: 1530-8898
Titre abrégé: J Cogn Neurosci
Pays: United States
ID NLM: 8910747

Informations de publication

Date de publication:
26 Jun 2024
Historique:
medline: 28 6 2024
pubmed: 28 6 2024
entrez: 28 6 2024
Statut: aheadofprint

Résumé

Blood oxygen level dependent (BOLD) variability (SDBOLD) has emerged as a unique measure of the adaptive properties of neural systems that facilitate fast, stable responding, based on claims that SDBOLD is independent of mean BOLD signal (meanBOLD) and a powerful predictor of behavioral performance. We challenge these two claims. First, the apparent independence of SDBOLD and meanBOLD may reflect the presence of deactivations; we hypothesize that although SDBOLD may not be related to raw meanBOLD, it will be linearly related to "absolute" meanBOLD. Second, the observed relationship between SDBOLD and performance may be an artifact of using fixed-length trials longer than RTs. Such designs provide opportunities to toggle between on- and off-task states, and fast responders likely engage in more frequent state-switching, thereby artificially elevating SDBOLD. We hypothesize that SDBOLD will be higher and more strongly related to performance when using such fixed-length trials relative to self-paced trials that terminate upon a response. We test these two hypotheses in an fMRI study using blocks of fixed-length or self-paced trials. Results confirmed both hypotheses: (1) SDBOLD was robustly related with absolute meanBOLD, and (2) toggling between on- and off-task states during fixed-length trials reliably contributed to SDBOLD. Together, these findings suggest that a reappraisal of the functional significance of SDBOLD as a unique marker of cognitive performance is warranted.

Identifiants

pubmed: 38940728
pii: 123225
doi: 10.1162/jocn_a_02202
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-17

Subventions

Organisme : Rutherford Discovery Fellowship
ID : RDF-10-UOA-024
Organisme : Canada 150 Research Chair

Informations de copyright

© 2024 Massachusetts Institute of Technology.

Auteurs

Kristina Wiebels (K)

The University of Auckland.

David Moreau (D)

The University of Auckland.

Donna Rose Addis (DR)

Rotman Research Institute.
University of Toronto.

Classifications MeSH