Using connectome-based models of working memory to predict emotion regulation in older adults

© The Author(s) 2023. Published by Oxford University Press..

Older adulthood is characterized by enhanced emotional well-being potentially resulting from greater reliance on adaptive emotion regulation strategies. However, not all older adults demonstrate an increase in emotional well-being and instead rely on maladaptive emotion regulation strategies. An important moderator of age-related shifts in strategy preferences is working memory (WM) and its underlying neural circuitry. As such, individual differences in the neural integrity underlying WM may predict older adults' emotion regulation strategy preferences. Our study used whole-brain WM networks-derived from young adults using connectome-based predictive modeling-to predict WM performance and acceptance strategy use in healthy older adults. Older adults (N = 110) completed baseline assessments as part of a randomized controlled trial examining the impact of mind-body interventions on healthy aging. Our results revealed that the WM networks predicted WM accuracy but not acceptance use or difficulties in emotion regulation in older adults. Individual differences in WM performance, but not WM networks, moderated relationships between image intensity and acceptance use. These findings highlight that robust neural markers of WM generalize to an independent sample of healthy older adults but may not generalize beyond cognitive domains to predict emotion-based behaviors.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:18

Enthalten in:

Social cognitive and affective neuroscience - 18(2023), 1 vom: 25. Juli

Sprache:

Englisch

Beteiligte Personen:

Fisher, Megan E [VerfasserIn]
Teng, James [VerfasserIn]
Gbadeyan, Oyetunde [VerfasserIn]
Prakash, Ruchika S [VerfasserIn]

Links:

Volltext

Themen:

Aging
Connectome-based predictive modeling
Emotion regulation
FMRI
Journal Article
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Working memory

Anmerkungen:

Date Completed 26.07.2023

Date Revised 06.11.2023

published: Print

Citation Status MEDLINE

doi:

10.1093/scan/nsad036

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM359222161