The representation and valuation of subgoals in the human brain during model-based hierarchical behavior DOI Creative Commons
Cooper D. Grossman, Vincent Man, John P. O’Doherty

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

The human capacity to plan and perform long, complex sequences of behavior achieve distant goals depends in part on a hierarchical organization that divides into structured segments. Such mechanism requires the internal designation certain states as subgoals mark successful implementation behavioral segment. How brain represents over time computes decision values function is unknown. While most characterizations lack knowledge environment, decision-making also relies planning with an model world. Consequently, it remains be determined how using model-based order drive hierarchical, decisions. Using sequential-subgoal task designed evoke combination fMRI, we decoded representation current subgoal insula ventromedial prefrontal cortex during persisted time–a critical, latent for computing orienting correct sequence. model-based, reinforcement learning model, found key signals based from several regions frontal cortex. These findings thereby shed light neural correlates illustrate value can computed basis these environment structure.

Language: Английский

The representation and valuation of subgoals in the human brain during model-based hierarchical behavior DOI Creative Commons
Cooper D. Grossman, Vincent Man, John P. O’Doherty

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

The human capacity to plan and perform long, complex sequences of behavior achieve distant goals depends in part on a hierarchical organization that divides into structured segments. Such mechanism requires the internal designation certain states as subgoals mark successful implementation behavioral segment. How brain represents over time computes decision values function is unknown. While most characterizations lack knowledge environment, decision-making also relies planning with an model world. Consequently, it remains be determined how using model-based order drive hierarchical, decisions. Using sequential-subgoal task designed evoke combination fMRI, we decoded representation current subgoal insula ventromedial prefrontal cortex during persisted time–a critical, latent for computing orienting correct sequence. model-based, reinforcement learning model, found key signals based from several regions frontal cortex. These findings thereby shed light neural correlates illustrate value can computed basis these environment structure.

Language: Английский

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