# A translational determination of the mechanisms of maladaptive choice in cocaine use disorder

> **NIH NIH R01** · UNIVERSITY OF KENTUCKY · 2021 · $617,474

## Abstract

ABSTRACT
 Cocaine use disorder (CUD) is characterized by the decision to use cocaine at the expense of other activities.
Lab-based efforts to address this problem have therefore included cocaine choice self-administration procedures
that incorporate a non-drug alternative to model this defining feature. Studies using these procedures have
typically scheduled competing reinforcers so that the probabilities are certain. However, such deterministic
outcomes are not representative of real-world scenarios in which the consequences from drug-related decisions
are often unpredictable. Importantly, decision-making in a dynamic, uncertain context significantly alters the
value of choice options and requires continuous updating of option values, which engages learning processes
and related corticostriatal networks that might be functioning abnormally in CUD. Decision-making in dynamic
environments has been successfully modeled using probabilistic reinforcement-learning choice (PRLC) tasks.
The integration of these tasks with reinforcement-learning (RL) modeling has been used to capture moment-to-
moment changes in the mechanisms of dynamic choice, and the application of neuroscience techniques has
begun to identify the underlying neurobiology. This approach has uncovered biologically-based decision-making
abnormalities in multiple brain disorders, but has yet to be systematically applied to the experimental study of
CUD, The translation of combined RL and neuroscience approaches to CUD is logical considering the
maladaptive choice behavior that typifies the disorder, the varying reinforcement probabilities in cocaine users’
natural environments, and the learning impairments and neuroadaptations that have been documented in
individuals with CUD. Thus, there are critical gaps in our understanding of the mechanisms underlying dynamic
cocaine use decisions, and a strong scientific premise for applying an RL framework to fill these gaps. This
project proposes rigorous PRLC tasks, RL modeling, neuromodulation/fMRI neuroimaging techniques and
complementary, translational study designs in rats and humans to study dynamic choice in CUD. The first set of
cross-species experiments will demonstrate the impact of problematic cocaine use on dynamic decision-making
and reveal the neurobehavioral and neurobiological processes underlying this abnormal task performance. The
second set of experiments will use a PRLC task in which intravenous cocaine is available as an alternative to
the non-drug reinforcer to determine the behavioral and neural “profile” associated with the decision to use
cocaine and reduced cocaine choice during treatment. Amphetamine maintenance and non-drug alternative
reinforcer treatments reduce cocaine choice, which will be leveraged here to uncover behavioral and neural
mechanisms that can be targeted for future treatment development. This project will have a significant impact
on the field by establishing the experimental application of reinforcemen...

## Key facts

- **NIH application ID:** 10147006
- **Project number:** 5R01DA045023-04
- **Recipient organization:** UNIVERSITY OF KENTUCKY
- **Principal Investigator:** Joshua Beckmann
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $617,474
- **Award type:** 5
- **Project period:** 2018-07-01 → 2023-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10147006

## Citation

> US National Institutes of Health, RePORTER application 10147006, A translational determination of the mechanisms of maladaptive choice in cocaine use disorder (5R01DA045023-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10147006. Licensed CC0.

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