History of withdrawal modulates drug- and food-cue reactivity in cocaine dependent participants

Association of Cortico-Striatal Engagement During Cue Reactivity, Reappraisal, and Savoring of Drug and Non-Drug Stimuli With Craving in Heroin Addiction

OBJECTIVE

The authors investigated cortico-striatal reactivity to drug cues (as compared with neutral and food cues), drug cue reappraisal, food cue savoring, and their correlations with heroin craving in individuals with heroin use disorder compared with healthy control subjects.

METHODS

Cross-sectional changes in functional MRI blood-oxygen-level-dependent signal during a novel cue reactivity task were assessed in 32 individuals with heroin use disorder (mean age, 40.3 years; seven women) and 21 age- and sex-matched healthy control subjects (mean age, 40.6 years; eight women).

RESULTS

Drug cue reactivity (vs. neutral cues) was significantly higher in the nucleus accumbens in the heroin use disorder group compared with the control group and nominally significantly higher in the orbitofrontal cortex (OFC); ventromedial prefrontal cortex (vmPFC) activity positively correlated with drug craving. Drug cue reactivity (vs. salient food cues) was also higher in the inferior frontal gyrus (IFG) in the heroin use disorder group compared with the control group. Drug reappraisal and food savoring (vs. passive viewing) showed increased IFG and supplementary motor area activity in all participants; in the heroin use disorder group, higher IFG/dorsolateral PFC (dlPFC) activity during drug reappraisal and rostral anterior cingulate cortex (ACC) activity during food savoring were associated with lower drug cue-induced craving and longer treatment, respectively. A direct comparison of regulation of reactivity to both salient cues revealed widespread group differences such that drug reappraisal activity was higher in the heroin use disorder group and food savoring activity was higher in the control group in both cortical (e.g., OFC, IFG, ACC, vmPFC, and insula) and subcortical (e.g., dorsal striatum and hippocampus) regions. Higher drug reappraisal versus food savoring in the dlPFC was associated with higher self-reported methadone dosage in the heroin use disorder group.

CONCLUSIONS

The results demonstrate cortico-striatal upregulation during drug cue exposure and impaired reactivity during processing of alternative non-drug rewards in the heroin use disorder group. Normalizing cortico-striatal function by reducing drug cue reactivity and enhancing natural reward valuation may inform therapeutic mechanisms for reducing drug craving and seeking in heroin addiction.

The neurobiology of drug addiction: cross-species insights into the dysfunction and recovery of the prefrontal cortex

A growing preclinical and clinical body of work on the effects of chronic drug use and drug addiction has extended the scope of inquiry from the putative reward-related subcortical mechanisms to higher-order executive functions as regulated by the prefrontal cortex. Here we review the neuroimaging evidence in humans and non-human primates to demonstrate the involvement of the prefrontal cortex in emotional, cognitive, and behavioral alterations in drug addiction, with particular attention to the impaired response inhibition and salience attribution (iRISA) framework. In support of iRISA, functional and structural neuroimaging studies document a role for the prefrontal cortex in assigning excessive salience to drug over non-drug-related processes with concomitant lapses in self-control, and deficits in reward-related decision-making and insight into illness. Importantly, converging insights from human and non-human primate studies suggest a causal relationship between drug addiction and prefrontal insult, indicating that chronic drug use causes the prefrontal cortex damage that underlies iRISA while changes with abstinence and recovery with treatment suggest plasticity of these same brain regions and functions. We further dissect the overlapping and distinct characteristics of drug classes, potential biomarkers that inform vulnerability and resilience, and advancements in cutting-edge psychological and neuromodulatory treatment strategies, providing a comprehensive landscape of the human and non-human primate drug addiction literature as it relates to the prefrontal cortex.

Machine learning approaches for parsing comorbidity/heterogeneity in antisociality and substance use disorders: A primer

By some accounts, as many as 93% of individuals diagnosed with antisocial personality disorder (ASPD) or psychopathy also meet criteria for some form of substance use disorder (SUD). This high level of comorbidity, combined with an overlapping biopsychosocial profile, and potentially interacting features, has made it difficult to delineate the shared/unique characteristics of each disorder. Moreover, while rarely acknowledged, both SUD and antisociality exist as highly heterogeneous disorders in need of more targeted parcellation. While emerging data-driven nosology for psychiatric disorders (e.g., Research Domain Criteria (RDoC), Hierarchical Taxonomy of Psychopathology (HiTOP)) offers the opportunity for a more systematic delineation of the externalizing spectrum, the interrogation of large, complex neuroimaging-based datasets may require data-driven approaches that are not yet widely employed in psychiatric neuroscience. With this in mind, the proposed article sets out to provide an introduction into machine learning methods for neuroimaging that can help parse comorbid, heterogeneous externalizing samples. The modest machine learning work conducted to date within the externalizing domain demonstrates the potential utility of the approach but remains highly nascent. Within the paper, we make suggestions for how future work can make use of machine learning methods, in combination with emerging psychiatric nosology systems, to further diagnostic and etiological understandings of the externalizing spectrum. Finally, we briefly consider some challenges that will need to be overcome to encourage further progress in the field.

Altered power spectra in antisocial males during rest as a function of cocaine dependence: A network analysis

Abnormalities in the spectral power of offenders' neural oscillations have been noted within select Resting-State Networks (RSNs); however, no study has yet evaluated the influence of cocaine dependence, drug use severity, and psychopathic traits on these abnormalities. To this end, the present study compared rest-related power spectral characteristics between two groups of offenders (with and without a DSM-IV-TR cocaine-dependence diagnosis) and a non-offender control group. Results indicated that both offender groups presented with lower low frequency power ratio (LFPR) scores (i.e. across all RSNs) than non-offenders. These differences in LFPR scores were due to both higher high-frequency power (0.15-0.25 Hz; within seven (in non-dependent offenders) and five (in cocaine-dependent offenders) of eight investigated networks) and decreased low-frequency power (0.01-0.10 Hz; within six (in non-dependent offenders) and one (in cocaine-dependent offenders) of eight investigated networks) compared to non-offenders. Thus, both cocaine-dependent and non-dependent offenders displayed abnormal neural oscillations, suggesting that these oscillatory abnormalities could exist as neurobiological features associated with offender status. Offenders' LFPR levels correlated with lifetime years of cocaine use, but not with the level of psychopathic traits. These findings supplement our knowledge regarding the influence of substance use on resting-state activity in offenders; moreover, they provide further indication of the importance of evaluating shared/unique variance associated with drug use and pyschopathic personality traits.