The long-term goal of the candidate is to be an independent investigator conducting interdisciplinary studies on neural correlates of substance use disorders (SUDs), especially brain-based predictors of treatment outcomes of SUDs by integrating neuroimaging and clinical trial methods. Brain-based predictors have the potential to guide the optimal patient-therapy matching to improve the efficacy of treatment for SUDs. His short-term goal is to gain required skills for achieving his long-term goal through the training supported by this K01 Award. The candidate received training in Medicine and Diagnostic Radiology in China, a Ph.D. in Neuroscience from the Medical College of Ohio, and T32 Postdoctoral training in functional magnetic resonance imaging (fMRI) on SUDs from the University of California Los Angeles (UCLA). Since 2007, the candidate has been a faculty level investigator in the Division of Substance Abuse at the Yale School of Medicine Department of Psychiatry. His research has focused on using fMRI to identify neural correlates of treatment outcomes of cocaine dependence. The candidate now seeks support to expand the scope of his research on neural predictors of treatment outcomes of other SUDs and to obtain additional training focused on mastering diffusion tensor imaging (DTI) analysis and on learning principles of SUD treatment and clinical trial methods. His preliminary findings indicate that better integrity of white matter in the frontal lobes and anterior corpus callosum positively correlates with better treatment outcomes of cognitive behavioral therapy for cocaine dependence. The candidate seeks to replicate and expand these initial findings in studies that use different therapies and with patients of other SUDs. His research strategy will be to conduct a series of analyses of fMRI, DTI, and treatment outcome data to identify neural predictors and correlates of treatment outcomes of patients dependent on cocaine or other substances participating in 5 clinical trials of several different therapies for SUDs. His training program will cover the following topics: 1) enhancing and expanding his expertise in neuroimaging, 2) learning clinical trial methodologies for SUDs, particularly as they relate to brain measures, 3) sharpening interdisciplinary thinking about brain correlates of addiction treatments, 4) enhancing statistical knowledge for longitudinal research, 5) enhancing knowledge on ethics related to human studies and responsible conduct of research, and 6) training in preparation for manuscripts and grant proposals. His mentors include internationally prominent experts in neuroimaging (Marc Potenza, M.D., Ph.D., Godfrey Pearlson, M.D.) and in SUD treatment research (Bruce Rounsaville, M.D., Kathleen Carroll, Ph.D.).

Public Health Relevance

Cocaine addiction is a major problem of public health, which is exacerbated by the fact that different patients respond to each therapy differently.
The aim of this project is to identify brain-based predictors of treatment outcomes of different therapies for cocaine addiction using state of the art brain mapping methods. Brain-based predictors can help optimal matching of different patients with different therapies to improve the treatment efficacy of current therapies for cocaine addiction.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01DA027750-04
Application #
8433403
Study Section
Human Development Research Subcommittee (NIDA)
Program Officer
Kautz, Mary A
Project Start
2010-03-01
Project End
2015-02-28
Budget Start
2013-03-01
Budget End
2014-02-28
Support Year
4
Fiscal Year
2013
Total Cost
$181,818
Indirect Cost
$13,468
Name
Yale University
Department
Psychiatry
Type
Schools of Medicine
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
Xu, Jiansong; Potenza, Marc N; Calhoun, Vince D et al. (2016) Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses. Neurosci Biobehav Rev 71:83-100
Yau, Yvonne H C; Potenza, Marc N; Mayes, Linda C et al. (2015) Blunted feedback processing during risk-taking in adolescents with features of problematic Internet use. Addict Behav 45:156-63
Mei, Songli; Xu, Jiansong; Carroll, Kathleen M et al. (2015) Self-reported impulsivity is negatively correlated with amygdalar volumes in cocaine dependence. Psychiatry Res 233:212-7
Xu, Jiansong; Healy, Stephen M; Truong, Dennis Q et al. (2015) A Feasibility Study of Bilateral Anodal Stimulation of the Prefrontal Cortex Using High-Definition Electrodes in Healthy Participants. Yale J Biol Med 88:219-25
Xu, Jiansong; Calhoun, Vince D; Worhunsky, Patrick D et al. (2015) Functional network overlap as revealed by fMRI using sICA and its potential relationships with functional heterogeneity, balanced excitation and inhibition, and sparseness of neuron activity. PLoS One 10:e0117029
Xu, Jiansong (2015) Implications of cortical balanced excitation and inhibition, functional heterogeneity, and sparseness of neuronal activity in fMRI. Neurosci Biobehav Rev 57:264-70
Xu, Jiansong; Calhoun, Vince D; Potenza, Marc N (2015) The absence of task-related increases in BOLD signal does not equate to absence of task-related brain activation. J Neurosci Methods 240:125-7
Xu, Jiansong; Calhoun, Vince D; Pearlson, Godfrey D et al. (2014) Opposite modulation of brain functional networks implicated at low vs. high demand of attention and working memory. PLoS One 9:e87078
Rahman, Ardeshir S; Xu, Jiansong; Potenza, Marc N (2014) Hippocampal and amygdalar volumetric differences in pathological gambling: a preliminary study of the associations with the behavioral inhibition system. Neuropsychopharmacology 39:738-45
Xu, Jiansong; Kober, Hedy; Wang, Xin et al. (2014) Hippocampal volume mediates the relationship between measures of pre-treatment cocaine use and within-treatment cocaine abstinence. Drug Alcohol Depend 143:74-80

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