Deficits in default mode network activity preceding error in cocaine dependent individuals.

BACKGROUND Cocaine dependence is associated with cognitive deficits and altered task-related cerebral activation in cognitive performance (see Li and Sinha, 2008, for a review). Relatively little is known whether these individuals are also impaired in regional brain activation of the default mode network (DMN). We demonstrated previously that greater activation of the default brain regions precedes errors in a stop signal task performed by healthy controls (SST, Li et al., 2007). We seek to determine whether individuals with cocaine dependence are impaired in DMN activity, specifically activity preceding error, as compared to the healthy people. We also examine the relation to years of cocaine use. METHODS Individuals with cocaine dependence (CD, n=23) and demographics-matched healthy controls (HC, n=27) performed a SST that employed a tracking procedure to adjust the difficulty of stop trials and elicit errors approximately half of the time. Blood oxygenation level dependent (BOLD) signals of go trials preceding stop error as compared to those preceding stop success trials were extracted with generalized linear models using statistical parametric mapping. RESULTS HC showed activation of bilateral precuneus and posterior cingulate cortices and ventromedial prefrontal cortex (vmPFC) preceding errors during the SST. In contrast, despite indistinguishable stop signal performance, CD did not show these error predicting activations. Furthermore, the effect size of error-preceding vmPFC activation was inversely correlated with years of cocaine use. CONCLUSIONS These findings indicate DMN deficits and could potentially add to our understanding of the effects of chronic cocaine use on cerebral functions in cocaine dependence. Work to further clarify potential changes in functional connectivity and gray matter volume is warranted to understand the relevance of DMN to the pathology of cocaine misuse.

[1]  Rajita Sinha,et al.  Neural Correlates of Impulse Control During Stop Signal Inhibition in Cocaine-Dependent Men , 2008, Neuropsychopharmacology.

[2]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[3]  M. Paulus,et al.  Location, location: using functional magnetic resonance imaging to pinpoint brain differences relevant to stimulant use. , 2007, Addiction.

[4]  Randy L. Buckner,et al.  Unrest at rest: Default activity and spontaneous network correlations , 2007, NeuroImage.

[5]  Hongtu Zhu,et al.  An FMRI study of the effects of psychostimulants on default-mode processing during Stroop task performance in youths with ADHD. , 2009, The American journal of psychiatry.

[6]  Cong Huang,et al.  Neural Correlates of Post-error Slowing during a Stop Signal Task: A Functional Magnetic Resonance Imaging Study , 2008, Journal of Cognitive Neuroscience.

[7]  L. Porrino,et al.  Loss of functional specificity in the dorsal striatum of chronic cocaine users. , 2009, Drug and alcohol dependence.

[8]  Yihong Yang,et al.  Mesocorticolimbic circuits are impaired in chronic cocaine users as demonstrated by resting-state functional connectivity , 2010, NeuroImage.

[9]  Julien Doyon,et al.  Dopamine modulates default mode network deactivation in elderly individuals during the Tower of London task , 2009, Neuroscience Letters.

[10]  G. Logan On the ability to inhibit thought and action , 1984 .

[11]  M. Ghilardi,et al.  Dopaminergic Suppression of Brain Deactivation Responses during Sequence Learning , 2008, The Journal of Neuroscience.

[12]  Abraham Z. Snyder,et al.  A default mode of brain function: A brief history of an evolving idea , 2007, NeuroImage.

[13]  E. Becoña,et al.  Depression and Cocaine Dependence , 2007, Psychological Reports.

[14]  M. Greicius,et al.  Default-Mode Activity during a Passive Sensory Task: Uncoupled from Deactivation but Impacting Activation , 2004, Journal of Cognitive Neuroscience.

[15]  C. Kelly,et al.  L-Dopa Modulates Functional Connectivity in Striatal Cognitive and Motor Networks: A Double-Blind Placebo-Controlled Study , 2009, NeuroImage.

[16]  Kristina M. Visscher,et al.  The neural bases of momentary lapses in attention , 2006, Nature Neuroscience.

[17]  George Bush,et al.  Attention-Deficit/Hyperactivity Disorder and Attention Networks , 2010, Neuropsychopharmacology.

[18]  Colleen A. Hanlon,et al.  Poor decision-making by chronic marijuana users is associated with decreased functional responsiveness to negative consequences , 2011, Psychiatry Research: Neuroimaging.

[19]  Russell A. Poldrack,et al.  Engagement of large-scale networks is related to individual differences in inhibitory control , 2010, NeuroImage.

[20]  Justin L. Vincent,et al.  Intrinsic functional architecture in the anaesthetized monkey brain , 2007, Nature.

[21]  Deborah A Yurgelun-Todd,et al.  Cerebellar Gray Matter Volume Correlates with Duration of Cocaine Use in Cocaine-Dependent Subjects , 2007, Neuropsychopharmacology.

[22]  Michael A. Nader,et al.  The effects of cocaine: A shifting target over the course of addiction , 2007, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[23]  Rita Z. Goldstein,et al.  Anterior cingulate cortex hypoactivations to an emotionally salient task in cocaine addiction , 2009, Proceedings of the National Academy of Sciences.

[24]  M. First,et al.  The Structured Clinical Interview for DSM-III-R Personality Disorders (SCID-II). II: Multi-site test-retest reliability study , 1995 .

[25]  Katherine H. Karlsgodt,et al.  Psychosocial Stress and the Duration of Cocaine Use in Non‐treatment Seeking Individuals with Cocaine Dependence , 2003, The American journal of drug and alcohol abuse.

[26]  Sheng Zhang,et al.  Increased error-related thalamic activity during early compared to late cocaine abstinence. , 2010, Drug and alcohol dependence.

[27]  D. Chialvo,et al.  Beyond Feeling: Chronic Pain Hurts the Brain, Disrupting the Default-Mode Network Dynamics , 2008, The Journal of Neuroscience.

[28]  Karl J. Friston,et al.  Spatial registration and normalization of images , 1995 .

[29]  Torsten Rohlfing,et al.  Cerebral blood flow in posterior cortical nodes of the default mode network decreases with task engagement but remains higher than in most brain regions. , 2011, Cerebral cortex.

[30]  Tianzi Jiang,et al.  Changes in hippocampal connectivity in the early stages of Alzheimer's disease: Evidence from resting state fMRI , 2006, NeuroImage.

[31]  Bryon A Mueller,et al.  Brain macrostructural and microstructural abnormalities in cocaine dependence. , 2008, Drug and alcohol dependence.

[32]  Kenneth Hugdahl,et al.  Prediction of human errors by maladaptive changes in event-related brain networks , 2008, Proceedings of the National Academy of Sciences.

[33]  G. Paxinos,et al.  Atlas of the Human Brain , 2000 .

[34]  Karl J. Friston,et al.  Human Brain Function , 1997 .

[35]  W. D. Penny,et al.  Random-Effects Analysis , 2002 .

[36]  R. T. Constable,et al.  Error-specific medial cortical and subcortical activity during the stop signal task: A functional magnetic resonance imaging study , 2008, Neuroscience.

[37]  Guozhi Tao,et al.  Effect of cocaine on structural changes in brain: MRI volumetry using tensor-based morphometry. , 2010, Drug and alcohol dependence.

[38]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[39]  S. Debener,et al.  Default-mode brain dysfunction in mental disorders: A systematic review , 2009, Neuroscience & Biobehavioral Reviews.

[40]  Karl J. Friston,et al.  To Smooth or Not to Smooth? Bias and Efficiency in fMRI Time-Series Analysis , 2000, NeuroImage.

[41]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[42]  Trevor W Robbins,et al.  The Orbital Prefrontal Cortex and Drug Addiction in Laboratory Animals and Humans , 2007, Annals of the New York Academy of Sciences.

[43]  Chiang-shan R. Li,et al.  Biological markers of the effects of intravenous methylphenidate on improving inhibitory control in cocaine-dependent patients , 2010, Proceedings of the National Academy of Sciences.

[44]  Hugh Garavan,et al.  The Role of Cognitive Control in Cocaine Dependence , 2007, Neuropsychology Review.

[45]  C. Li,et al.  Inhibitory control and emotional stress regulation: Neuroimaging evidence for frontal–limbic dysfunction in psycho-stimulant addiction , 2008, Neuroscience & Biobehavioral Reviews.

[46]  J. Ashburner,et al.  Nonlinear spatial normalization using basis functions , 1999, Human brain mapping.

[47]  Rajita Sinha,et al.  Greater activation of the “default” brain regions predicts stop signal errors , 2007, NeuroImage.

[48]  Jean-Luc Anton,et al.  Region of interest analysis using an SPM toolbox , 2010 .

[49]  B. Biswal,et al.  Network homogeneity reveals decreased integrity of default-mode network in ADHD , 2008, Journal of Neuroscience Methods.

[50]  H. Siegal,et al.  The Prevalence and Correlates of Depressive Symptomatology Among a Community Sample of Crack-Cocaine Smokers , 2002, Journal of psychoactive drugs.

[51]  Nora D. Volkow,et al.  Methylphenidate Decreased the Amount of Glucose Needed by the Brain to Perform a Cognitive Task , 2008, PloS one.

[52]  E. Nunes,et al.  Early abstinence in cocaine dependence: influence of comorbid major depression. , 2007, The American journal on addictions.

[53]  N. Volkow,et al.  Dopamine Transporters in Striatum Correlate with Deactivation in the Default Mode Network during Visuospatial Attention , 2009, PloS one.

[54]  Wilkin Chau,et al.  An Empirical Comparison of SPM Preprocessing Parameters to the Analysis of fMRI Data , 2002, NeuroImage.

[55]  H. Levitt Transformed up-down methods in psychoacoustics. , 1971, The Journal of the Acoustical Society of America.

[56]  Paul J Laurienti,et al.  The association between frontal-striatal connectivity and sensorimotor control in cocaine users. , 2011, Drug and alcohol dependence.

[57]  M. Corbetta,et al.  Common Blood Flow Changes across Visual Tasks: II. Decreases in Cerebral Cortex , 1997, Journal of Cognitive Neuroscience.

[58]  R. Constable,et al.  Imaging Response Inhibition in a Stop-Signal Task: Neural Correlates Independent of Signal Monitoring and Post-Response Processing , 2006, The Journal of Neuroscience.

[59]  M. Greicius,et al.  Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI , 2004, Proc. Natl. Acad. Sci. USA.

[60]  V. Calhoun,et al.  Selective changes of resting-state networks in individuals at risk for Alzheimer's disease , 2007, Proceedings of the National Academy of Sciences.

[61]  Chiang-shan Ray Li,et al.  Neural correlates of speeded as compared with delayed responses in a stop signal task: an indirect analog of risk taking and association with an anxiety trait. , 2009, Cerebral cortex.

[62]  D. Tomasi,et al.  Common deactivation patterns during working memory and visual attention tasks: An intra‐subject fMRI study at 4 Tesla , 2006, Human brain mapping.

[63]  Nora D. Volkow,et al.  The effect of practice on a sustained attention task in cocaine abusers , 2007, NeuroImage.

[64]  S. Rombouts,et al.  Altered resting state networks in mild cognitive impairment and mild Alzheimer's disease: An fMRI study , 2005, Human brain mapping.