Evidence accumulation and associated error-related brain activity as computationally-informed prospective predictors of substance use in emerging adulthood.
Computational psychiatry
Diffusion model
Drift rate
Evidence accumulation
Salience network
Substance use
Journal
Psychopharmacology
ISSN: 1432-2072
Titre abrégé: Psychopharmacology (Berl)
Pays: Germany
ID NLM: 7608025
Informations de publication
Date de publication:
Sep 2021
Sep 2021
Historique:
received:
07
10
2020
accepted:
27
05
2021
pubmed:
27
6
2021
medline:
29
9
2021
entrez:
26
6
2021
Statut:
ppublish
Résumé
Substance use peaks during the developmental period known as emerging adulthood (ages 18-25), but not every individual who uses substances during this period engages in frequent or problematic use. Although individual differences in neurocognition appear to predict use severity, mechanistic neurocognitive risk factors with clear links to both behavior and neural circuitry have yet to be identified. Here, we aim to do so with an approach rooted in computational psychiatry, an emerging field in which formal models are used to identify candidate biobehavioral dimensions that confer risk for psychopathology. We test whether lower efficiency of evidence accumulation (EEA), a computationally characterized individual difference variable that drives performance on the go/no-go and other neurocognitive tasks, is a risk factor for substance use in emerging adults. In an fMRI substudy within a sociobehavioral longitudinal study (n = 106), we find that lower EEA and reductions in a robust neural-level correlate of EEA (error-related activations in salience network structures) measured at ages 18-21 are both prospectively related to greater substance use during ages 22-26, even after adjusting for other well-known risk factors. Results from Bayesian model comparisons corroborated inferences from conventional hypothesis testing and provided evidence that both EEA and its neuroimaging correlates contain unique predictive information about substance use involvement. These findings highlight EEA as a computationally characterized neurocognitive risk factor for substance use during a critical developmental period, with clear links to both neuroimaging measures and well-established formal theories of brain function.
Identifiants
pubmed: 34173032
doi: 10.1007/s00213-021-05885-w
pii: 10.1007/s00213-021-05885-w
pmc: PMC8452274
mid: NIHMS1738120
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2629-2644Subventions
Organisme : NIDA NIH HHS
ID : K01 DA044270
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH107741
Pays : United States
Organisme : NIAAA NIH HHS
ID : T32 AA007477
Pays : United States
Organisme : NIAAA NIH HHS
ID : R01 AA025790
Pays : United States
Organisme : NIAAA NIH HHS
ID : K01 AA024804
Pays : United States
Organisme : NIAAA NIH HHS
ID : R01 AA007065
Pays : United States
Organisme : NIAAA NIH HHS
ID : K01 AA027558
Pays : United States
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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