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Updated: Apr 18, 2026

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
Published on: August 2, 2018
Ventral striatal dopamine reflects behavioral and neural signatures of model-based control during sequential decision
Lorenz Deserno1, Quentin J M Huys2, Rebecca Boehme3
1Max Planck Fellow Group "Cognitive and Affective Control of Behavioral Adaptation", Max Planck Institute for Human Cognitive and Brain Sciences, 04130 Leipzig, Germany; Department of Neurology, Otto von Guericke University, 39118 Magdeburg, Germany; Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité-Universitätsmedizin Berlin, 10115 Berlin, Germany; deserno@cbs.mpg.de.
Abstract:
Dual system theories suggest that behavioral control is parsed between a deliberative "model-based" and a more reflexive "model-free" system. A balance of control exerted by these systems is thought to be related to dopamine neurotransmission. However, in the absence of direct measures of human dopamine, it remains unknown whether this reflects a quantitative relation with dopamine either in the striatum or other brain areas. Using a sequential decision task performed during functional magnetic resonance imaging, combined with striatal measures of dopamine using [(18)F]DOPA positron emission tomography, we show that higher presynaptic ventral striatal dopamine levels were associated with a behavioral bias toward more model-based control. Higher presynaptic dopamine in ventral striatum was associated with greater coding of model-based signatures in lateral prefrontal cortex and diminished coding of model-free prediction errors in ventral striatum. Thus, interindividual variability in ventral striatal presynaptic dopamine reflects a balance in the behavioral expression and the neural signatures of model-free and model-based control. Our data provide a novel perspective on how alterations in presynaptic dopamine levels might be accompanied by a disruption of behavioral control as observed in aging or neuropsychiatric diseases such as schizophrenia and addiction.
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