The effects of working memory and interference control on reinforcement learning: Evidence from computational...

Area of Science:

• Cognitive Neuroscience
• Neuroimaging
• Computational Psychiatry

Background:

• Reinforcement learning (RL) is vital for adapting to dynamic environments.
• While working memory (WM) effects on RL are studied, the combined roles of WM and interference control (IC) and their neural underpinnings are less understood.

Purpose of the Study:

• To investigate the joint contributions of WM and IC to RL.
• To explore the relationship between WM, IC, RL performance, and brain morphology.

Main Methods:

• 169 healthy adults performed a probabilistic RL task with varied WM load and interference.
• RL model parameters (learning rate, inverse temperature, forgetting) and learning accuracy were measured.
• Structural MRI data (GMV, cortical thickness, sulcal depth) were acquired from 144 participants.

Main Results:

• Increased WM load impaired learning accuracy, reduced learning rates, and slowed forgetting, associated with frontoparietal/limbic network morphology.
• Interference exposure decreased learning rates and accelerated forgetting, with IC effects linked to cingulate gyrus sulcal depth.
• A significant interaction showed interference particularly impaired learning under high WM load, linked to thalamic and temporal pole structures.

Conclusions:

• WM and IC interact to shape learning processes, influencing adaptive decision-making.
• Individual differences in learning are significantly associated with specific cortical and subcortical brain structural features.
• Findings highlight the neural basis of cognitive control in complex learning environments.