This 5 year proposal involving 3 universities explores the role of dopamine (DA) in the reinforcement learning working memory (WM), and decision making deficits of patients with schizophrenia (SZ) through behavioral experiments and computational modeling. While DA dysfunction is thought to be a fundamental aspect of SZ, rapid advances in the basic neuroscience understanding and modeling of the role of DA in reward processing remain to be translated into clinical research. The goal of this proposal is to provide an integrative account of how DA abnormalities may underlie the disabling cognitive/motivational deficits of SZ within a comprehensive computational framework that addresses the role of DA signaling in the basal ganglia and frontal cortex in action selection, learning, and WM. The experiments provide tests of model predictions of the types of impairments that result from the DA abnormalities that are thought to occur in SZ.
In Aims 1 -3, we test for deficits in processing of positive feedback signals that would be expected to result from abnormal increases of tonic DA across tasks tapping habit learning, decision making, and WM. We also test the novel, model based prediction that DA abnormalities in the orbital frontal cortex will result in impairment in processing the relative magnitudes of rewards and punishments with experiments designed where this will lead patients to perform at superior or inferior levels relative to controls.
Aim 4 addresses the impact of antipsychotic treatment through the testing of patients both before and after the initiation of treatment where we will test the hypothesis that treatments facilitate learning from negative reinforcement as predicted by the model. These behavioral results will then be explored using computational modeling to determine the fit of observed behavior to predictions based on models where we have explored the role of increasing and decreasing different aspects of DA signaling to approximate the hypothesized abnormalities in SZ. Relevance: Most SZ patients experience deficits in cognitive and motivational processing, resulting in significant disability. It is likely that abnormalities in the DA system may be involved in both types of impairments. Because all known antipsychotic treatments impact the DA system, the proposed work promises to increase understanding of how current treatments may have beneficial as well as possible adverse effects on these crucial areas of impairment.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH080066-05
Application #
8212436
Study Section
Adult Psychopathology and Disorders of Aging Study Section (APDA)
Program Officer
Meinecke, Douglas L
Project Start
2008-02-25
Project End
2014-01-31
Budget Start
2012-02-01
Budget End
2014-01-31
Support Year
5
Fiscal Year
2012
Total Cost
$635,563
Indirect Cost
$104,657
Name
University of Maryland Baltimore
Department
Psychiatry
Type
Schools of Medicine
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201
Catalano, Lauren T; Heerey, Erin A; Gold, James M (2018) The valuation of social rewards in schizophrenia. J Abnorm Psychol 127:602-611
Westbrook, Andrew; Frank, Michael (2018) Dopamine and Proximity in Motivation and Cognitive Control. Curr Opin Behav Sci 22:28-34
Nassar, Matthew R; Helmers, Julie C; Frank, Michael J (2018) Chunking as a rational strategy for lossy data compression in visual working memory. Psychol Rev 125:486-511
Pedersen, Mads Lund; Frank, Michael J; Biele, Guido (2017) The drift diffusion model as the choice rule in reinforcement learning. Psychon Bull Rev 24:1234-1251
Waltz, James A (2017) The neural underpinnings of cognitive flexibility and their disruption in psychotic illness. Neuroscience 345:203-217
Swart, Jennifer C; Froböse, Monja I; Cook, Jennifer L et al. (2017) Catecholaminergic challenge uncovers distinct Pavlovian and instrumental mechanisms of motivated (in)action. Elife 6:
Collins, Anne G E; Ciullo, Brittany; Frank, Michael J et al. (2017) Working Memory Load Strengthens Reward Prediction Errors. J Neurosci 37:4332-4342
Maia, Tiago V; Huys, Quentin J M; Frank, Michael J (2017) Theory-Based Computational Psychiatry. Biol Psychiatry 82:382-384
Collins, Anne G E; Albrecht, Matthew A; Waltz, James A et al. (2017) Interactions Among Working Memory, Reinforcement Learning, and Effort in Value-Based Choice: A New Paradigm and Selective Deficits in Schizophrenia. Biol Psychiatry 82:431-439
Maia, Tiago V; Frank, Michael J (2017) An Integrative Perspective on the Role of Dopamine in Schizophrenia. Biol Psychiatry 81:52-66

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