Computational and electrochemical substrates of social decision-making in humans

  • Montague, P P.R (PI)
  • Gu, Xiaosi (CoPI)
  • Kishida, Kenneth Tucker (CoPI)
  • Kishida, Kenneth K.T (CoPI)
  • Montague, Read P. (CoPI)
  • Gu, Xiaosi (CoPI)

Project Details


SUMMARY Dopamine and serotonin systems in the human brain represent two key neuromodulatory signalling systems that impact mood, value-based decision-making, learning, and a host of other cognitive functions. Despite their importance, there is no consensus view from a psychological or computational perspective concerning their exact information-processing functions. Consequently, there is a scarceness of strategies to treat disorders that afflict these systems. We believe that this gap exists primarily because of methodological limitations. While there are many fast methods for recording action potential activity and local field potentials, similar progress for tracking `the other end of the problem' - neurochemical dynamics - has lagged far behind. This is unfortunate since just considering the catecholamines dopamine, serotonin, and norepinephrine, the worldwide health burden of dysfunction in these neuromodulatory systems is immense approaching 400 million people worldwide if one includes just Major Depression and Attention-deficit hyperactivity disorders (WHO, 2017). The overall goal of this project is to investigate the computational and neuromodulatory substrates of interactive social processes hypothesized to be trans-diagnostic RDoC constructs. We will utilize two levels of analysis (molecules/circuits and behavioral/computational) across two RDoC constructs (systems for social processes: perception and understanding of others, subconstruct understanding mental states, and positive valence systems: reward learning, subconstruct reward prediction error) to make inroads into understanding the computational and neural underpinnings of social interaction in humans. Crucially, the interactive social tasks used in this proposal generate an important class of learning signal – a reward prediction error signal – but expressed in the context of an inter-personal interaction. Our two levels of analysis employ (1) computational models of human (two-agent) social exchange estimated from detailed, observed behavior and (2) unique sub- second measurements of dopamine and serotonin from human striatum (three separate sites: caudate, putamen, ventral striatum) during the window-of-opportunity afforded by deep brain stimulating (DBS) electrode implantation surgery for Parkinson's Disease, Essential Tremors, Obsessive Compulsive Disorder.
Effective start/end date1/08/2031/05/23




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