Article

Cannabis Abstinence During Treatment and One-Year Follow-up: Relationship to Neural Activity in Men.

Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology (Impact Factor: 8.68). 04/2014; DOI: 10.1038/npp.2014.82
Source: PubMed

ABSTRACT Cannabis is among the most frequently-abused substances in the United States. Cognitive control is a contributory factor in the maintenance of substance use disorders and may relate to treatment response. Therefore, we assessed whether cognitive-control-related neural activity prior to treatment differs between treatment-seeking cannabis-dependent and healthy individuals and relates to cannabis-abstinence measures during treatment and one-year follow-up. Cannabis-dependent males (N=20) completed a functional magnetic resonance imaging (fMRI) cognitive-control (Stroop) task prior to a 12-week randomized controlled trial of cognitive behavioral therapy and/or contingency management. A healthy-comparison group (N=20) also completed the fMRI task. Cannabis-use was assessed by urine toxicology and self-report during treatment, and by self-report across a 1-year follow-up period (N=18). The cannabis-dependent group displayed diminished Stroop-related neural activity relative to the healthy-comparison group in multiple regions including those strongly implicated in cognitive control and addiction-related processes (e.g. dorsolateral prefrontal cortex and ventral striatum). The groups did not significantly differ in response times (cannabis-dependent N=12; healthy-comparison N=14). Within the cannabis-dependent group, greater Stroop-related activity in regions including the dorsal anterior cingulate cortex was associated with less cannabis use during treatment. Greater activity in regions including the ventral striatum was associated with less cannabis use during one-year post-treatment follow-up. These data suggest that lower cognitive-control-related neural activity in classic "control" regions (e.g., dorsolateral prefrontal cortex, dorsal anterior cingulate) and classic "salience/reward/learning" regions (e.g., ventral striatum) differentiates cannabis-dependent from healthy individuals and relates to less abstinence within-treatment and during long-term follow-up. Clinically, results suggest that treatment development efforts that focus on enhancing cognitive control in addition to abstinence may improve treatment outcomes in cannabis dependence.Neuropsychopharmacology accepted article peview online, 07 April 2014; doi:10.1038/npp.2014.82.

0 Bookmarks
 · 
39 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background Selection of an appropriate indictor of treatment response in clinical trials is complex, particularly for the various illicit drugs of abuse. Most widely-used indicators have been selected based on expert group recommendation or convention rather than systematic empirical evaluation. Absence of an evidence-based, clinically meaningful index of treatment outcome hinders cross-study evaluations necessary for progress in addiction treatment science. Method Fifteen candidate indicators used in multiple clinical trials as well as some proposed recently are identified and discussed in terms of relative strengths and weaknesses (practicality, cost, verifiability, sensitivity to missing data). Using pooled data from five randomized controlled trials of cocaine dependence (N = 434), the indicators were compared in terms of sensitivity to the effects of treatment and relationship to cocaine use and general functioning during follow-up. Results Commonly used outcome measures (percent negative urine screens; percent days of abstinence) performed relatively well in that they were sensitive to the effects of the therapies evaluated. Others, including complete abstinence and reduction in frequency of use, were less sensitive to effects of specific therapies and were very weakly related to cocaine use or functioning during follow-up. Indicators more strongly related to cocaine use during follow-up were those that reflected achievement of sustained periods of abstinence, particularly at the end of treatment. Conclusions These analyses did not demonstrate overwhelming superiority of any single indicator, but did identify several that performed particularly poorly. Candidates for elimination included retention, complete abstinence, and indicators of reduced frequency of cocaine use.
    Drug and alcohol dependence 04/2014; · 3.60 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cannabis is the most widely used illicit drug in the U.S., and the number of illicit and licit users is rising. Lasting neurocognitive changes or deficits as a result of use are frequently noted despite a lack of clarity in the scientific literature. In an effort to resolve inconsistencies in the evidence of lasting residual effects of cannabis use, we conducted two meta-analyses. First, we updated a previous meta-analysis on broad nonacute cognitive effects of cannabis use through inclusion of newer studies. In a second meta-analysis, we focused on evidence for lasting residual effects by including only studies that tested users after at least 25 days of abstinence. In the first meta-analysis, 33 studies met inclusion criteria. Results indicated a small negative effect for global neurocognitive performance as well for most cognitive domains assessed. Unfortunately, methodological limitations of these studies prevented the exclusion of withdrawal symptoms as an explanation for observed effects. In the second meta-analysis, 13 of the original 33 studies met inclusion criteria. Results indicated no significant effect of cannabis use on global neurocognitive performance or any effect on the eight assessed domains. Overall, these meta-analyses demonstrate that any negative residual effects on neurocognitive performance attributable to either cannabis residue or withdrawal symptoms are limited to the first 25 days of abstinence. Furthermore, there was no evidence for enduring negative effects of cannabis use. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
    Experimental and Clinical Psychopharmacology 06/2012; 20(5):420-9. · 2.55 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Drug addiction is characterized by dysregulated dopamine neurotransmission. Although dopamine functioning appears to partially recover with abstinence, the specific regions that recover and potential impact on drug seeking remain to be determined. Here we used functional magnetic resonance imaging (fMRI) to study an ecologically valid sample of 15 treatment-seeking cocaine addicted individuals at baseline and 6-month follow-up. At both study sessions, we collected fMRI scans during performance of a drug Stroop task, clinical self-report measures of addiction severity and behavioral measures of cocaine seeking (simulated cocaine choice); actual drug use in between the two study sessions was also monitored. At 6-month follow-up (compared with baseline), we predicted functional enhancement of dopaminergically innervated brain regions, relevant to the behavioral responsiveness toward salient stimuli. Consistent with predictions, whole-brain analyses revealed responses in the midbrain (encompassing the ventral tegmental area/substantia nigra complex) and thalamus (encompassing the mediodorsal nucleus) that were higher (and more positively correlated) at follow-up than baseline. Increased midbrain activity from baseline to follow-up correlated with reduced simulated cocaine choice, indicating that heightened midbrain activations in this context may be marking lower approach motivation for cocaine. Normalization of midbrain function at follow-up was also suggested by exploratory comparisons with active cocaine users and healthy controls (who were assessed only at baseline). Enhanced self-control at follow-up was suggested by a trend for the commonly hypoactive dorsal anterior cingulate cortex to increase response during a drug-related context. Together, these results suggest that fMRI could be useful in sensitively tracking follow-up outcomes in drug addiction.
    Addiction Biology 03/2012; 17(6):1013-25. · 5.93 Impact Factor