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Stochastic dynamic causal modeling of working memory connections in cocaine dependence.
MedLine Citation:
PMID:  23151990     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Although reduced working memory brain activation has been reported in several brain regions of cocaine-dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging-based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine-dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level-dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine-dependent subjects had large differences compared with the control subjects in the strengths of prefrontal-striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical-striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between-group DCM study using stochastic methodology. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.
Authors:
Liangsuo Ma; Joel L Steinberg; Khader M Hasan; Ponnada A Narayana; Larry A Kramer; F Gerard Moeller
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-14
Journal Detail:
Title:  Human brain mapping     Volume:  -     ISSN:  1097-0193     ISO Abbreviation:  Hum Brain Mapp     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-15     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9419065     Medline TA:  Hum Brain Mapp     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012 Wiley Periodicals, Inc.
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center, Houston, Texas. liangsuo.ma@uth.tmc.edu.
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