Cognitive behavioral treatments (CBT) available for addiction produce efficacious and replicable results. However, those results provide considerable opportunity for increases in efficacy. CBT assumes that changes in cognition and improvement in relevant skills (such as drug refusal) will produce changes in target behaviors. Unfortunately, considerable evidence suggests that addicted individuals exhibit a variety of deficits in what is called """"""""executive function"""""""" (associated with a hypoactive prefrontal cortex). From this perspective, executive function refers to a self-directed action to alter behavior and change future outcomes. Executive dysfunction could impede learning and implementation of CBT skills, and executive function therapy (EFT) used in combination with CBT could increase efficacy of behavior change in addicted persons. We plan to develop and test EFT in a multi-step process in Aim 1. Task 1 will computerize, when possible, selected assessments, which are not computerized;control treatments;and a program allowing us to control automatically the type and sequence of modules for each therapy and control treatment. Measures and therapies were selected in a systematic review of research on measurement and rehabilitation of executive function. Task 2 will collect data on executive function assessment instruments from controls to develop an operational definition of dysfunction in the target population. Tasks 3 and 4 will develop each computational model of executive function, then evaluate if each produces improvement in the targeted executive function component in stimulant abusers. Task 5 will analyze and review pre- and post-evaluation data, and assess the model's robustness in accounting for data from Task 4. Models will be revised and re-tested as necessary.
In Aim 2, we plan to develop an innovative computational neuroscience model of executive function and dysfunction to aid in therapy development. Computational neuroscience employs computer and mathematical models constrained by empirical knowledge of the neural system to understand brain function, explain existing data, codify how variables influence cognitive function, and identify hypotheses for empirical testing. In this project, computational neuroscience will provide novel understanding of executive functioning, inform therapy development, contribute to a computational model of therapy, and aid in diagnostic assessments regarding particular treatments. Successfully achieving the aims could allow us to develop and target a treatment for empirically determined deficits in the addicted. This will be important for CBT and other therapies (motivational interviewing and 12- step approaches). This proposal will contribute to personalized medicine approaches in addictions, where treatment is defined by documented executive dysfunction in individual addicts. Our new treatment could spawn a variety of important areas of inquiry, such as neuroimaging studies to document changes in the prefrontal cortex, research on how the treatment could enhance treatment efficacy, studies exploring EFT for drug abuse prevention, and use of means like neurofeedback to enhance executive function. Project Narrative Stimulant addicts have been shown to exhibit executive dysfunction. Overall, this proposal will test treatments to improve executive function among stimulant addicts. This may enhance the efficacy of CBT treatment. Moreover, this proposal will contribute to personalized medicine approaches in the addictions, where the treatment delivered is defined by the documented executive dysfunction in individual addicts. Importantly, our work targets cocaine- and amphetamine- (including methamphetamine) addicted individuals. These addictions, particularly methamphetamine, represent a significant public health crisis that this study could positively impact.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA024080-03
Application #
7864082
Study Section
Human Development Research Subcommittee (NIDA)
Program Officer
Aklin, Will
Project Start
2008-09-01
Project End
2011-01-31
Budget Start
2010-07-01
Budget End
2011-01-31
Support Year
3
Fiscal Year
2010
Total Cost
$322,315
Indirect Cost
Name
University of Arkansas for Medical Sciences
Department
Psychiatry
Type
Schools of Medicine
DUNS #
122452563
City
Little Rock
State
AR
Country
United States
Zip Code
72205
Bickel, Warren K; Moody, Lara N; Eddy, Celia R et al. (2017) Neurocognitive dysfunction in addiction: Testing hypotheses of diffuse versus selective phenotypic dysfunction with a classification-based approach. Exp Clin Psychopharmacol 25:322-332
Moody, Lara; Franck, Christopher; Bickel, Warren K (2016) Comorbid depression, antisocial personality, and substance dependence: Relationship with delay discounting. Drug Alcohol Depend 160:190-6
Moody, Lara; Franck, Christopher; Hatz, Laura et al. (2016) Impulsivity and polysubstance use: A systematic comparison of delay discounting in mono-, dual-, and trisubstance use. Exp Clin Psychopharmacol 24:30-7
Bickel, Warren K; Quisenberry, Amanda J; Moody, Lara et al. (2015) Therapeutic Opportunities for Self-Control Repair in Addiction and Related Disorders: Change and the Limits of Change in Trans-Disease Processes. Clin Psychol Sci 3:140-153
Regier, Paul S; Redish, A David (2015) Contingency Management and Deliberative Decision-Making Processes. Front Psychiatry 6:76
Wilson, A George; Franck, Christopher T; Mueller, E Terry et al. (2015) Predictors of delay discounting among smokers: education level and a Utility Measure of Cigarette Reinforcement Efficacy are better predictors than demographics, smoking characteristics, executive functioning, impulsivity, or time perception. Addict Behav 45:124-33
Bickel, Warren K; George Wilson, A; Franck, Christopher T et al. (2014) Using crowdsourcing to compare temporal, social temporal, and probability discounting among obese and non-obese individuals. Appetite 75:82-9
Bickel, Warren K; Johnson, Matthew W; Koffarnus, Mikhail N et al. (2014) The behavioral economics of substance use disorders: reinforcement pathologies and their repair. Annu Rev Clin Psychol 10:641-77
Wesley, Michael J; Lohrenz, Terry; Koffarnus, Mikhail N et al. (2014) Choosing Money over Drugs: The Neural Underpinnings of Difficult Choice in Chronic Cocaine Users. J Addict 2014:189853
Koffarnus, Mikhail N; Bickel, Warren K (2014) A 5-trial adjusting delay discounting task: accurate discount rates in less than one minute. Exp Clin Psychopharmacol 22:222-8

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