Caudolateral orbitofrontal regional cerebral blood flow is decreased in abstinent cocaine-addicted subjects in two separate cohorts

Long-Term Cocaine Self-administration Produces Structural Brain Changes That Correlate With Altered Cognition

BACKGROUND

An enduring question from cross-sectional clinical studies is whether the structural and functional differences often observed between cocaine users and healthy control subjects result from a history of drug use or instead reflect preexisting differences. To assess causality from drug exposure, true predrug baseline imaging and neurocognitive assessments are needed.

METHODS

We addressed this fundamental question of causality using longitudinal anatomical magnetic resonance imaging and neurocognitive assessments in rhesus macaques. Cognitive tasks employed were stimulus reversal learning as a measure of cognitive flexibility/inhibitory control and delayed match to sample as a measure of visual working memory. Time points examined were before and following 12 months of chronic cocaine (n = 8) or water (n = 6) self-administration. A magnetic resonance imaging-only time point was also obtained following 2 years of forced abstinence.

RESULTS

We identified localized patterns of gray matter density (GMD) changes that were largely concordant with cross-sectional clinical studies. These included decreases in orbitofrontal cortex, insula, amygdala, and temporal cortex. There was also a prominent increase in GMD in the caudate putamen. GMD decreases were significantly correlated with cognitive impairments across individuals only in select cortical regions. Following abstinence, changes in GMD in some regions, including the orbitofrontal cortex, insula, and amygdala, were persistent and thus may play an important role in risk of relapse following extended abstinence.

CONCLUSIONS

Cocaine use is causal in producing regional changes in GMD, and those changes appear to drive cognitive impairments.

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach

Background

Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2–4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations.

Results

The voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of regional cerebral blood flow in brain regions in cocaine-dependent participants are presented with corresponding level of significance.

Conclusions

The SVM-based approach successfully classified cocaine-dependent and healthy control participants using voxels selected with information theoretic-based and statistical methods from participants’ SPECT data. The regions found in this study align with brain regions reported in the literature. These findings support the future use of brain imaging and SVM-based classifier in the diagnosis of substance use disorders and furthering an understanding of their underlying pathology.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1218-z) contains supplementary material, which is available to authorized users.

Decision-making processes as predictors of relapse and subsequent use in stimulant-dependent patients

BACKGROUND

Decision-making processes have been posited to affect treatment outcome in addicted patients.

OBJECTIVE

The present multi-site study assessed whether two measures of decision-making predicted relapse and subsequent use in stimulant-dependent patients.

METHODS

A total of 160 methamphetamine- or cocaine-dependent patients participating in a multi-site clinical trial evaluating a modified 12-step facilitation intervention for stimulant-dependent patients (STAGE-12) were assessed. Decision-making processes of risk and delay (Iowa Gambling Task [IGT]) and response reversal (Wisconsin Card Sorting Task [WCST]) were obtained shortly after treatment admission followed by assessment of stimulant use over the next six months. The relationships of the IGT and WCST (Perseverative Errors) with relapse (yes/no) and days of stimulant use during the 6-month period following post-randomization were evaluated.

RESULTS

Performance on the IGT and WCST did not significantly predict relapse status or time to relapse. Unexpectedly, worse performance on the IGT was associated with a fewer number of stimulant use days (p = 0.001). In contrast, worse performance on the WCST (more perseverative errors) was associated with a greater number of stimulant use days (p = 0.0003). The predictive effects of perseverative errors on subsequent use were confined to methamphetamine-dependent and Minority participants.

CONCLUSIONS

Decision-making processes, as measured in the current study, do not uniformly predict relapse or subsequent use. A decrease in the salience attribution of non-drug reinforcers may explain the positive relationship between IGT performance and post-relapse use. More comprehensive and global measures of impulsiveness may better assess relapse risk and use.

Brain perfusion single photon emission computed tomography in major psychiatric disorders: From basics to clinical practice

Brain single photon emission computed tomography (SPECT) is a well-established and reliable method to assess brain function through measurement of regional cerebral blood flow (rCBF). It can be used to define a patient's pathophysiological status when neurological or psychiatric symptoms cannot be explained by anatomical neuroimaging findings. Though there is ample evidence validating brain SPECT as a technique to track human behavior and correlating psychiatric disorders with dysfunction of specific brain regions, only few psychiatrists have adopted brain SPECT in routine clinical practice. It can be utilized to evaluate the involvement of brain regions in a particular patient, to individualize treatment on basis of SPECT findings, to monitor the treatment response and modify treatment, if necessary. In this article, we have reviewed the available studies in this regard from existing literature and tried to present the evidence for establishing the clinical role of brain SPECT in major psychiatric illnesses.

Striatal-insula circuits in cocaine addiction: implications for impulsivity and relapse risk

BACKGROUND

Dysregulated striatal functioning coupled with executive control deficits arising from abnormal frontal cortical function are considered key mechanisms in the development and maintenance of cocaine addiction. The same features are thought to underlie high trait impulsivity observed in cocaine-addicted populations.

OBJECTIVES

Employing resting state functional connectivity, the current study sought to identify cortico-striatal circuit alterations in cocaine addiction and examine the degree to which circuit connectivity contributes to relapse risk and impulsivity among cocaine-addicted individuals.

METHODS

Whole-brain resting-state functional magnetic resonance imaging connectivity was assessed in 45 cocaine-addicted individuals relative to 22 healthy controls using seed volumes in the left and right caudate, putamen and nucleus accumbens. Cocaine-addicted individuals completed scans in the final week of a 2-4 weeks residential treatment episode. Relapse by day 30 post-discharge served to separate cocaine-addicted individuals into relapse and non-relapse groups. All participants completed the Barratt Impulsivity Scale (BIS-11a).

RESULTS

Cocaine-addicted individuals exhibited reduced positive connectivity between the bilateral putamen and posterior insula and right postcentral gyrus. Group differences were primarily driven by reduced connectivity in relapse individuals relative to controls. No relapse versus non-relapse differences emerged. Impulsivity (BIS-11a) was higher in cocaine-addicted participants, an effect that was partially mediated by reduced putamen-posterior insula connectivity in this group.

CONCLUSION

Cocaine addiction, relapse risk and impulsivity were associated with reduced connectivity in putamen-posterior insula/postcentral gyrus circuits implicated in temporal discounting and habitual responding. Findings provide new insight into the neurobiological mechanisms underlying impulsivity and relapse in cocaine addiction.

A selective insular perfusion deficit contributes to compromised salience network connectivity in recovering alcoholic men

BACKGROUND

Alcoholism can disrupt neural synchrony between nodes of intrinsic functional networks that are maximally active when resting relative to engaging in a task, the default mode network (DMN) pattern. Untested, however, are whether the DMN in alcoholics can rebound normally from the relatively depressed task state to the active resting state and whether local perfusion deficits could disrupt network synchrony when switching from conditions of rest to task to rest, thereby indicating a physiological mechanism of neural network adaptation capability.

METHODS

Whole-brain, three-dimensional pulsed-continuous arterial spin labeling provided measurements of regional cerebral blood flow (CBF) in 12 alcoholics and 12 control subjects under three conditions: pretask rest, spatial working-memory task, and posttask rest.

RESULTS

With practice, alcoholics and control subjects achieved similar task accuracy and reaction times. Both groups exhibited a high-low-high pattern of perfusion levels in DMN regions during the rest-task-rest runs and the opposite pattern in posterior and cerebellar regions known to be associated with spatial working memory. Alcoholics showed selective differences from control subjects in the rest-task-rest CBF pattern in the anterior precuneus and CBF level in the insula, a hub of the salience network. Connectivity analysis identified activation synchrony from an insula seed to salience nodes (parietal, medial frontal, anterior cingulate cortices) in control subjects only.

CONCLUSIONS

We propose that attenuated insular CBF is a mechanism underlying compromised connectivity among salience network nodes. This local perfusion deficit in alcoholics has the potential to impair ability to switch from cognitive states of interoceptive cravings to cognitive control for curbing internal urges.

Frontal systems deficits in stimulant-dependent patients: evidence of pre-illness dysfunction and relationship to treatment response

BACKGROUND

Frontal systems dysfunction is present in stimulant-dependent patients. However, it is unclear whether this dysfunction is a pre-morbid risk factor or stimulant-induced, is severe enough to be clinically relevant, and if it is relevant to treatment response. These questions were addressed using the Frontal Systems Behavior Scale (FrSBe), a reliable and valid self-report assessment of three neurobehavioral domains associated with frontal systems functioning (Apathy, Disinhibition, and Executive Dysfunction, summed for a Total), that assesses both pre- and post-morbid functioning, and has a specific cutoff for defining clinically significant abnormalities.

METHOD

Six sites evaluating 12-step facilitation for stimulant abusers obtained the FrSBe from 180 methamphetamine- and/or cocaine-dependent participants. Dichotomous treatment response measures included self-reported stimulant use, stimulant urine drug screens, and treatment completion.

RESULTS

A substantial percentage of participants retrospectively reported clinically significant neurobehavioral abnormalities prior to lifetime stimulant abuse initiation (e.g., 67.5% on FrSBe-Total) with a significant increase in the proportion reporting such abnormalities for current functioning (86% on FrSBe-Total; p<0.0001). Treatment response was significantly worse for participants with, relative to those without, clinically significant Disinhibition as measured by treatment non-completion (31.6% vs. 15.6%, OR=2.51) and self-reported stimulant use during treatment (40.5% vs. 16.7%, OR=3.40).

CONCLUSION

These findings suggest that frontal systems dysfunction is present prior to stimulant-abuse onset and worsens with stimulant use. Disinhibition may be a prime target for intervention in stimulant-dependent individuals.