Compulsory drug seeking and consumption is a defining feature of cocaine dependence. Impairment in cognitive control contributes to such compulsory drug using behaviors. Despite abundant behavioral evidence for impaired cognitive control in patients with cocaine dependence (PCD), the neural processes underlying such a deficit remain unclear. In particular, how impairment in cognitive control is associated with relapse to drug use in PCD has not been explored. The current proposal fills this important gap by combining functional magnetic resonance imaging (fMRI) with a stop signal task (SST), in which successful performance requires prepotent, habitual behaviors (as in compulsory drug seeking) to be inhibited. With a component approach we have isolated response inhibition, conflict/error processing, and post-error behavioral adjustment as critical measures of cognitive control during the SST. In fMRI studies we have identified medial superior frontal and anterior cingulate activation during response inhibition, sequential dorsal cingulate/medial cortical activation and deactivation during error processing, and ventrolateral prefrontal activation during post-error remedial action. Furthermore, compared to healthy individuals (HC), PCD demonstrated altered activation of these cortical structures during the SST. Importantly, this altered pattern of cortical activations distinguished between PCD relapsers and non-relapsers. These preliminary data highlight, for the first time, neural aspects of cognitive control that predict relapse to drug use in PCD. Additionally, consistent with earlier reports, we observed that cocaine abstinence symptomatology decrease over time in PCD, suggesting that cognitive processes may also change, during the course of abstinence. On the basis of these preliminary results, we hypothesize that impaired response inhibition, error processing and remedial action contribute synergistically to cocaine dependence, and propose to address these specific aims: First, do PCD and HC differ in brain activations during response inhibition, error processing and remedial action? Second, how do these differences predict relapse to cocaine use in PCD? Third, does cerebral brain activation underlying cognitive control differ between early and later during abstinence? Do deficits in cognitive control early and later during abstinence predict relapse to drug use differently in PCD? Fourth, do these regional brain activations predict relapse differently between men and women PCD? This project thus proposes an innovative approach to study cognitive control in PCD and facilitates the development of novel therapeutic strategies targeting the failed "braking mechanisms," which perceptuate drug seeking and relapse in cocaine dependence.

Public Health Relevance

Cocaine dependence is a chronic, relapsing disorder. Patients with cocaine dependence oftentimes report that they understand the serious consequences of using cocaine, but they are not able to "control" their behaviors. One of the major goals of addiction neuroscience is thus to understand how our brain exercises inhibitory control and monitor our behaviors and how these processes are altered in the patients of cocaine dependence. The goal of this proposal is to combine functional brain imaging with a behavioral task as a cognitive proxy to examine these issues. The results gathered from the proposed projects will help us understand the "cocaine- dependent brain" and facilitate the development of novel therapeutic strategies to treat patients with cocaine dependence.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
5R01DA023248-05
Application #
8264013
Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Bjork, James M
Project Start
2008-06-15
Project End
2014-04-30
Budget Start
2012-05-01
Budget End
2014-04-30
Support Year
5
Fiscal Year
2012
Total Cost
$299,741
Indirect Cost
$87,910
Name
Yale University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
Manza, Peter; Zhang, Sheng; Hu, Sien et al. (2015) The effects of age on resting state functional connectivity of the basal ganglia from young to middle adulthood. Neuroimage 107:311-22
Farr, Olivia M; Zhang, Sheng; Hu, Sien et al. (2014) The effects of methylphenidate on resting-state striatal, thalamic and global functional connectivity in healthy adults. Int J Neuropsychopharmacol 17:1177-91
Li, Chiang-shan R; Ide, Jaime S; Zhang, Sheng et al. (2014) Resting state functional connectivity of the basal nucleus of Meynert in humans: in comparison to the ventral striatum and the effects of age. Neuroimage 97:321-32
Cai, Weidong; Ryali, Srikanth; Chen, Tianwen et al. (2014) Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and task-related functional parcellation, connectivity, and response profile analyses across multiple datasets. J Neurosci 34:14652-67
Zhang, Sheng; Li, Chiang-Shan R (2014) Functional clustering of the human inferior parietal lobule by whole-brain connectivity mapping of resting-state functional magnetic resonance imaging signals. Brain Connect 4:53-69
Farr, Olivia M; Hu, Sien; Matuskey, David et al. (2014) The effects of methylphenidate on cerebral activations to salient stimuli in healthy adults. Exp Clin Psychopharmacol 22:154-65
Hu, Sien; Tseng, Yuan-Chi; Winkler, Alissa D et al. (2014) Neural bases of individual variation in decision time. Hum Brain Mapp 35:2531-42
Ide, Jaime S; Zhang, Sheng; Hu, Sien et al. (2014) Cerebral gray matter volumes and low-frequency fluctuation of BOLD signals in cocaine dependence: duration of use and gender difference. Drug Alcohol Depend 134:51-62
Ide, Jaime S; Zhang, Sheng; Li, Chiang-Shan R (2014) Bayesian network models in brain functional connectivity analysis. Int J Approx Reason 56:
Luo, Xi; Zhang, Sheng; Hu, Sien et al. (2013) Error processing and gender-shared and -specific neural predictors of relapse in cocaine dependence. Brain 136:1231-44

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