Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 62,736 bioRxiv papers from 278,376 authors.
Prefrontal cortex as a meta-reinforcement learning system
Jane X Wang,
Joel Z Leibo,
Posted 06 Apr 2018
bioRxiv DOI: 10.1101/295964 (published DOI: 10.1038/s41593-018-0147-8)
Posted 06 Apr 2018
Over the past twenty years, neuroscience research on reward-based learning has converged on a canonical model, under which the neurotransmitter dopamine 'stamps in' associations between situations, actions and rewards by modulating the strength of synaptic connections between neurons. However, a growing number of recent findings have placed this standard model under strain. In the present work, we draw on recent advances in artificial intelligence to introduce a new theory of reward-based learning. Here, the dopamine system trains another part of the brain, the prefrontal cortex, to operate as its own free-standing learning system. This new perspective accommodates the findings that motivated the standard model, but also deals gracefully with a wider range of observations, providing a fresh foundation for future research.
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