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Trial After Trial: Temporal Dynamics Reveal a Distinct Computational Phenotype of Chronic Cannabis Use

Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Background: Studies of effort-based decision-making (EBDM) related to chronic cannabis use have yielded inconsistent findings. This variability may reflect the limited ability of behavioral measures alone to distinguish the mechanisms driving observed choices. Computational modeling can help these discrepancies by isolating alterations in valuation, evidence-accumulation, and temporal processes.Methods: Forty-one individuals who chronically use cannabis (CU) and 45 individuals who do not (NU) completed the Effort Expenditure for Rewards Task (EEfRT). Drift diffusion, subjective value, and temporal dynamics models were used to characterize latent decision processes of effortful choice. Model-derived parameters were compared between groups and examined in relation to cannabis-use characteristics.Results: Greater effort allocation via hard-option choice in CU was characterized by less baseline effort avoidance during evidence accumulation and a weaker starting bias toward the easy option, implicating multiple decisional processes. They also showed lower between-participant variability in starting bias and, less definitively, decision caution. Subjective value modeling showed that both groups used similar decision strategies. Incorporating trial progression improved modeling and indicated that greater sustained hard-option choice in CU was related to weaker temporal decline in evidence accumulation and subjective value. Cannabis use characteristics showed no significant associations with latent parameters.Conclusions: Adults who use cannabis showed lower effort avoidance both at baseline and during evidence accumulation, greater homogeneity in selected decision processes, and attenuated decline in hard-option valuation. These findings suggest that cannabis-related differences in physical EBDM reflect altered evidence accumulation and temporal stability rather than broad differences in integration of reward, probability, and effort.
DOI: 10.31234/osf.io/6vh9p_v1
Language: English
Field: Medicine
Open Access status: green
OpenAlex ID: W7214203434
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