The neurocognitive role of working memory load when Pavlovian motivational control affects instrumental learning

• Published in: PLoS computational biology 2023-12, Vol.19 (12), p.e1011692-e1011692
• Main Authors: Park, Heesun, Doh, Hoyoung, Lee, Eunhwi, Park, Harhim, Ahn, Woo-Young
• Format: Article
• Language: English
• Subjects: Accuracy; Bias; Biology and Life Sciences; Cognition; Cognitive tasks; Computational neuroscience; Computer simulation; Computer-generated environments; Cooperation; Decision making; Embedded systems; Employee motivation; Equipment and supplies; Fractals; Functional magnetic resonance imaging; Go/no-go discrimination learning; Load distribution; Magnetic resonance imaging; Medicine and Health Sciences; Memory; Motivation; Neostriatum; Neural networks; Neuroimaging; Neurological research; Physical Sciences; Prefrontal cortex; Psychological research; Reinforcement (Psychology); Research and Analysis Methods; Short-term memory; Social Sciences; Teaching
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1011692

Research suggests that a fast, capacity-limited working memory (WM) system and a slow, incremental reinforcement learning (RL) system jointly contribute to instrumental learning. Thus, situations that strain WM resources alter instrumental learning: under WM loads, learning becomes slow and incremental, the reliance on computationally efficient learning increases, and action selection becomes more random. It is also suggested that Pavlovian learning influences people's behavior during instrumental learning by providing hard-wired instinctive responses including approach to reward predictors and avoidance of punishment predictors. However, it remains unknown how constraints on WM resources affect instrumental learning under Pavlovian influence. Thus, we conducted a functional magnetic resonance imaging (fMRI) study (N = 49) in which participants completed an instrumental learning task with Pavlovian-instrumental conflict (the orthogonalized go/no-go task) both with and without extra WM load. Behavioral and computational modeling analyses revealed that WM load reduced the learning rate and increased random choice, without affecting Pavlovian bias. Model-based fMRI analysis revealed that WM load strengthened RPE signaling in the striatum. Moreover, under WM load, the striatum showed weakened connectivity with the ventromedial and dorsolateral prefrontal cortex when computing reward expectations. These results suggest that the limitation of cognitive resources by WM load promotes slow and incremental learning through the weakened cooperation between WM and RL; such limitation also makes action selection more random, but it does not directly affect the balance between instrumental and Pavlovian systems.