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.
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|Bickel, W K; Moody, L; Quisenberry, A J et al. (2014) A Competing Neurobehavioral Decision Systems model of SES-related health and behavioral disparities. Prev Med 68:37-43|
|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; Bickel, Warren K (2014) Remember the future II: meta-analyses and functional overlap of working memory and delay discounting. Biol Psychiatry 75:435-48|
|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|
|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|
|Koffarnus, Mikhail N; Jarmolowicz, David P; Mueller, E Terry et al. (2013) Changing delay discounting in the light of the competing neurobehavioral decision systems theory: a review. J Exp Anal Behav 99:32-57|
|Bickel, Warren K; Jarmolowicz, David P; Mueller, E Terry et al. (2012) Excessive discounting of delayed reinforcers as a trans-disease process contributing to addiction and other disease-related vulnerabilities: emerging evidence. Pharmacol Ther 134:287-97|
|Bickel, Warren K; Jarmolowicz, David P; Mueller, E Terry et al. (2012) Are executive function and impulsivity antipodes? A conceptual reconstruction with special reference to addiction. Psychopharmacology (Berl) 221:361-87|
|Kurth-Nelson, Zeb; Bickel, Warren; Redish, A David (2012) A theoretical account of cognitive effects in delay discounting. Eur J Neurosci 35:1052-64|
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