scholarly journals Striatum–Medial Prefrontal Cortex Connectivity Predicts Developmental Changes in Reinforcement Learning

2012 ◽  
Vol 22 (6) ◽  
pp. 1247-1255 ◽  
Author(s):  
Wouter van den Bos ◽  
Michael X. Cohen ◽  
Thorsten Kahnt ◽  
Eveline A. Crone
Keyword(s):  
Prefrontal Cortex ◽  
Reinforcement Learning ◽  
Medial Prefrontal Cortex ◽  
Developmental Changes

scholarly journals Distentangling the systems contributing to changes in learning during adolescence

2019 ◽  
Author(s):  
Sarah L. Master ◽  
Maria K. Eckstein ◽  
Neta Gotlieb ◽  
Ronald Dahl ◽  
Linda Wilbrecht ◽  
...  
Keyword(s):  
Working Memory ◽  
Prefrontal Cortex ◽  
Reinforcement Learning ◽  
Computational Modeling ◽  
Developmental Trajectories ◽  
Learning Task ◽  
Developmental Changes ◽  
List Type ◽  
Precise Information ◽  
Learning Rates

AbstractMultiple neurocognitive systems contribute simultaneously to learning. For example, dopamine and basal ganglia (BG) systems are thought to support reinforcement learning (RL) by incrementally updating the value of choices, while the prefrontal cortex (PFC) contributes different computations, such as actively maintaining precise information in working memory (WM). It is commonly thought that WM and PFC show more protracted development than RL and BG systems, yet their contributions are rarely assessed in tandem. Here, we used a simple learning task to test how RL and WM contribute to changes in learning across adolescence. We tested 187 subjects ages 8 to 17 and 53 adults (25-30). Participants learned stimulus-action associations from feedback; the learning load was varied to be within or exceed WM capacity. Participants age 8-12 learned slower than participants age 13-17, and were more sensitive to load. We used computational modeling to estimate subjects’ use of WM and RL processes. Surprisingly, we found more robust changes in RL than WM during development. RL learning rate increased significantly with age across adolescence and WM parameters showed more subtle changes, many of them early in adolescence. These results underscore the importance of changes in RL processes for the developmental science of learning.Highlights- Subjects combine reinforcement learning (RL) and working memory (WM) to learn- Computational modeling shows RL learning rates grew with age during adolescence- When load was beyond WM capacity, weaker RL compensated less in younger adolescents- WM parameters showed subtler and more puberty-related changes- WM reliance, maintenance, and capacity had separable developmental trajectories- Underscores importance of RL processes in developmental changes in learning

scholarly journals Developmental changes in plasticity, synaptic, glia, and connectivity protein levels in rat medial prefrontal cortex

2018 ◽  
Vol 25 (10) ◽  
pp. 533-543 ◽  
Author(s):  
Margaret Jia ◽  
Alessio Travaglia ◽  
Gabriella Pollonini ◽  
Giuseppe Fedele ◽  
Cristina M. Alberini
Keyword(s):  
Prefrontal Cortex ◽  
Medial Prefrontal Cortex ◽  
Developmental Changes ◽  
Protein Levels
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