Dopamine (DA) neurons are fundamental to many aspects of behavior, and dysfunction of the DA system contributes to a wide range of disorders, including drug addiction. How does DA contribute to such a diversity of functions and dysfunctions? Part of the answer may relate to recent discoveries that DA neurons respond to a wide range of behavioral variables - not only to reward and reward-predicting cues, as traditionally examined, but also to other variables including position, movement, and behavioral choices. However, to date, the relative contributions of these behavioral variables to DA responses have not been examined quantitatively, in part because cellular resolution DA recordings have not been performed in behavioral settings with sufficient complexity and quantification to examine these diverse variables simultaneously. To address this gap, we propose to perform two-photon imaging from ensembles of midbrain DA neurons and their target neurons as mice learn to perform a complex decision-making task. However, characterizing the relationship between neural activity and behavior in this complex dataset presents a number of statistical challenges. These include the autocorrelation of the calcium indicator, the correlation between behavioral variables, the possibility of changes in the relationship between neural activity and behavior over time, and the need to leverage the availability of simultaneously measured neurons in order to improve statistical efficiency. Thus, we propose a suite of new statistical tools to address all of these challenges. These tools will be broadly applicable to the analysis of datasets throughout the addiction circuits (and the nervous system more broadly).

Public Health Relevance

Dopamine neurons are implicated in a wide range of normal behavioral functions, as well as a wide range of neuropsychiatric diseases, including addiction. The identification of sub-populations of dopamine neurons with different functional properties could provide much-needed insight into how dopamine neurons contribute to the neurobiology of addiction.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA047869-02
Application #
9775436
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Pariyadath, Vani
Project Start
2018-09-15
Project End
2022-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Washington
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195