NIH VideoCast - The Riddle of Dopamine

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The Riddle of Dopamine

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Air date:	Monday, January 9, 2023, 12:00:00 PM Time displayed is Eastern Time, Washington DC Local
Views:	Total views: 573 (269 Live, 304 On-demand)
Category:	Neuroscience
Runtime:	00:59:29
Closed captioning:	Check box to display CC outside of the video Note: You can drag the captioning window around and resize it
Description:	NIH Neuroscience Series Seminar Our research aims to understand how richly structured knowledge about the environment is acquired, and how this knowledge aids adaptive behavior. We use a combination of behavioral, neuroimaging and computational techniques to pursue these questions. One prong of this research focuses on how humans and animals discover the hidden states underlying their observations, and how they represent these states. In some cases, these states correspond to complex data structures, like graphs, grammars or programs. These data structures strongly constrain how agents infer which actions will lead to reward. A second prong of our research is teasing apart the interactions between different learning systems. Evidence suggests the existence of at least two systems: a "goal-directed" system that builds an explicit model of the environment, and a "habitual" system that learns state-action response rules. These two systems are subserved by separate neural pathways that compete for control of behavior, but the systems may also cooperate with one another. For more information go to https://research.ninds.nih.gov/seminars-events/neuroscience-seminar-series

NLM Title:	The riddle of dopamine / Samuel Gersham.
Author:	Gersham, Samuel. National Institutes of Health (U.S.),
Publisher:
Abstract:	(CIT): NIH Neuroscience Series Seminar Our research aims to understand how richly structured knowledge about the environment is acquired, and how this knowledge aids adaptive behavior. We use a combination of behavioral, neuroimaging and computational techniques to pursue these questions. One prong of this research focuses on how humans and animals discover the hidden states underlying their observations, and how they represent these states. In some cases, these states correspond to complex data structures, like graphs, grammars or programs. These data structures strongly constrain how agents infer which actions will lead to reward. A second prong of our research is teasing apart the interactions between different learning systems. Evidence suggests the existence of at least two systems: a "goal-directed" system that builds an explicit model of the environment, and a "habitual" system that learns state-action response rules. These two systems are subserved by separate neural pathways that compete for control of behavior, but the systems may also cooperate with one another.
Subjects:	Behavior--drug effects Dopamine--pharmacology
Publication Types:	Lecture Webcast

NLM Classification:	WK 725
NLM ID:	9918573271006676
CIT Live ID:	48638
Permanent link:	https://videocast.nih.gov/watch=48638

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