Johri, A. | bioRxiv Science

bioRxiv2025

Distributed activity in the human posterior putamen distinguishes goal-directed from habitual control in humans

How do some individuals rapidly form habits while others maintain flexible, goal-directed control? Using multivariate fMRI decoding in 199 participants, we show that distributed neural activity patterns in the left posterior putamen during initial learning predict individual behavioral strategy on a subsequent outcome devaluation test. This prediction generalized across two independent cohorts of healthy adults and psychiatric patients with heterogeneous diagnoses and was anatomically specific to the posterior putamen. Critically, predictive neural signatures were present during training, before strategy expression after devaluation, enabling prospective classification of habitual versus goal-directed behavior. These findings demonstrate that stable individual differences in behavioral control are reflected in circumscribed brain activity during learning, highlighting the posterior putamen as a candidate neural marker of habit propensity with potential clinical relevance.

neuroscience↗

bioRxiv2025

Model-based and model-free valuation signals in the human brain vary markedly in their relationship to individual differences in behavioral control

Human action selection under reinforcement is thought to rely on two distinct strategies: model-free and model-based reinforcement learning. While behavior in sequential decision-making tasks often reflects a mixture of both, the neural basis of individual differences in their expression remains unclear. To investigate this, we conducted a large-scale fMRI study with 179 participants performing a variant of the two-step task. Using both cluster-defined subgroups and computational parameter estimates, we found that the ventromedial prefrontal cortex encodes model-based and model-free value signals differently depending on individual strategy use. Model-based value signals were strongly linked to the degree of model-based behavioral reliance, whereas model-free signals appeared regardless of model-free behavioral influence. Leveraging the large sample, we found individuals lacking both model-based behavior and model-based neural signals exhibited impaired state prediction errors, suggesting a difficulty in building or updating their internal model of the environment. These findings indicate that model-free signals are ubiquitous across individuals, even in those not behaviorally relying on model-free strategies, while model-based representations appear only in those individuals utilizing such a strategy at the behavioral level, the absence of which may depend in part on underlying difficulties in forming accurate model-based predictions.

neuroscience↗