Valuation mechanisms that shape the interaction of phasic and tonic dopamine

The National Institute of Mental Health awarded the Regents of the University of Minnesota $149,177 on February 27, 2026, under the Mental Health Research Grants program (CFDA 93.242) to conduct research into valuation mechanisms linking phasic and tonic dopamine dynamics and their role in flexible motivational engagement.

The award funds a two-aim research project that uses a novel broadband dopamine measurement technique to analyze how dopamine fluctuates across fast phasic and slower tonic timescales to support reactive versus proactive motivational flexibility. Aim 1 assesses how valuation processes influence the relationship between phasic and tonic dopamine. Aim 2 identifies circuit mechanisms regulating how phasic dopamine signals accumulate into tonic levels under varying task demands of reactive versus proactive value learning. The research addresses conflicting theoretical interpretations of whether tonic dopamine arises from accumulated phasic reward prediction errors reflecting reactive motivation or from independent proactive effort allocation based on internal calculations. Resolving this distinction is intended to clarify dopamine's role in motivation and its dysfunction in psychiatric and substance use disorders.

Work is performed at the University of Minnesota in Minneapolis, Minnesota, with a period of performance through August 26, 2028. This is a project grant, a form of assistance awarded on the basis of scientific and technical merit as determined by peer review and evaluated against program priorities.

Abstract

Dopamine (DA) is a critical neuromodulator for mood, motivation, and reward-based learning. Dysregulated DA dynamics across brain regions and timescales contribute to psychiatric and substance use disorders, yet how DA timescales mediate the relationship between learning and motivation remains unresolved. Striatal DA release is documented to fluctuate on fast "phasic" and slower "tonic" timescales, hypothesized to regulate learning and motivation, respectively. Prevailing reinforcement learning (RL) theories suggest that phasic DA transients encode reward prediction errors (RPES), which diffuse and accumulate into tonic DA levels to regulate motivational engagement. This interpretation assumes that subjective values driving motivational engagement are reactive to recent reward exposure. However, alternative theories propose that tonic DA may arise independently from phasic DA, reflecting proactive effort allocation based on internal calculations rather than recent reward exposure. Resolving these conflicting views is essential for understanding DA's role in motivation and its dysfunction in psychopathology. This proposal aims to define the circuit and computational mechanisms linking phasic and tonic DA to flexible motivational engagement. Using a novel broadband DA measurement technique we recently developed, I will analyze how DA dynamics across timescales interact to support reactive-VS-proactive motivational flexibility. Aim 1 will assess how these valuation processes influence the relationship between phasic and tonic DA. Aim 2 will identify circuit mechanisms regulating how phasic DA signals accumulate into tonic levels under varying task demands of reactive-VS-proactive value learning. These studies will reconcile longstanding theoretical debates on DA function, providing a mechanistic and computational framework for understanding how DA shapes motivation and learning across timescales. The insights gained from these experiments will inform targeted interventions for circuit-specific vulnerabilities in addiction, depression, and psychosis.