How do substance use disorders compare to other psychiatric conditions on structural brain abnormalities? A cross-disorder meta-analytic comparison using the ENIGMA consortium findings.

Alcohol use disorder (AUD) and cannabis use disorder (CUD) are associated with brain alterations particularly involving fronto-cerebellar and meso-cortico-limbic circuitry. However, such abnormalities have additionally been reported in other psychiatric conditions, and until recently there has been few large-scale investigations to compare such findings. The current study uses the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium method of standardising structural brain measures to quantify case-control differences and to compare brain-correlates of substance use disorders with those published in relation to other psychiatric disorders. Using the ENIGMA protocols, we report effect sizes derived from a meta-analysis of alcohol (seven studies, N = 798, 54% are cases) and cannabis (seven studies, N = 447, 45% are cases) dependent cases and age- and sex-matched controls. We conduct linear analyses using harmonised methods to process and parcellate brain data identical to those reported in the literature for ENIGMA case-control studies of major depression disorder (MDD), schizophrenia (SCZ) and bipolar disorder so that effect sizes are optimally comparable across disorders. R elationships between substance use disorder diagnosis and subcortical grey matter volumes and cortical thickness were assessed with intracranial volume, age and sex as co-variates . After correcting for multiple comparisons, AUD case-control meta-analysis of subcortical regions indicated significant differences in the thalamus, hippocampus, amygdala and accumbens, with effect sizes (0.23) generally equivalent to, or larger than |0.23| those previously reported for other psychiatric disorders (except for the pallidum and putamen). On measures of cortical thickness, AUD was associated with significant differences bilaterally in the fusiform gyrus, inferior temporal gyrus, temporal pole, superior frontal gyrus, and rostral and caudal anterior cingulate gyri. Meta-analysis of CUD case-control studies indicated reliable reductions in amygdala, accumbens and hippocampus volumes, with the former effect size comparable to, and the latter effect size around half of that reported for alcohol and SCZ. CUD was associated with lower cortical thickness in the frontal regions, particularly the medial orbitofrontal region, but this effect was not significant after correcting for multiple testing. This study allowed for an unbiased cross-disorder comparison of brain correlates of substance use disorders and showed alcohol-related brain anomalies equivalent in effect size to that found in SCZ in several subcortical and cortical regions and significantly greater alterations than those found in MDD in several subcortical and cortical regions. Although modest, CUD results overlapped with findings reported for AUD and other psychiatric conditions, but appear to be most robustly related to reduce thickness of the medial orbitofrontal cortex.

Omega-3 fatty acids and neurocognitive ability in young people at ultra-high risk for psychosis.

BACKGROUND: Neurocognitive impairments are core early features of psychosis and are observed in those at ultra-high risk (UHR) for psychosis. The aim of the present study was to explore whether neurocognition is associated with polyunsaturated fatty acids (PUFAs), as has been observed in other clinical populations. METHOD: Erythrocyte levels of total omega-3-and omega-6 PUFAs the omega-3/omega-6 ratio, were measured in 265 UHR individuals. Six domains of neurocognition as well a Composite Score, were assessed using the Brief Assessment of Cognition in Schizophrenia. Pearson's correlations were used to assess the relationship between PUFAs and neurocognition. All analyses were controlled for tobacco smoking. RESULTS: Verbal Fluency correlated positively with eicosapentaenoic acid (P = .024) and alpha-linolenic acid (P = .01), and negatively with docosahexanoic acid (P = .007) and Working Memory positively correlated with omega-3/omega-6 ratio (P = .007). CONCLUSIONS: The current results provide support for a relationship between Verbal Fluency and omega-3 PUFAs in UHR. Further investigation is required to elucidate whether these biomarkers are useful as risk markers or in understanding the biological underpinning of neurocognitive impairment in this population.

Processing of performance errors predicts memory formation: Enhanced feedback-related negativities for corrected versus repeated errors in an associative learning paradigm.

Learning from errors or negative feedback is crucial for adaptive behavior. FMRI studies have demonstrated enhanced anterior cingulate cortex activity for errors that were later corrected versus repeated errors even when a substantial delay between the error and the opportunity to correct was introduced. We aimed at identifying the electrophysiological correlates of these processes by investigating the feedback-related negativity (FRN) and stimulus-locked P3. Participants had to learn and recall the location of 2-digit targets over consecutive rounds. Feedback was provided in two steps, first a color change indicated a correct or incorrect response (feedback phase) followed by presentation of the correct digit information (re-encoding phase). Behaviorally, participants improved performance from the first to the third round. FRN amplitudes time-locked to feedback were enhanced for corrected compared to repeated errors. The P3 in response to re-encoding did not differ between the two error types. The finding that FRN amplitudes positively predicted memory performance is consistent with the idea that the FRN reflects prediction errors and the need for enhanced cognitive control. Interestingly, this happens early during feedback processing and not at a later time point when re-encoding of correct information takes place. The prediction error signal reflected in the FRN is usually elicited by performance errors, but may thus also play a role in preparing/optimizing the system for memory formation. This supports the existence of a close link between action control and memory processes even when there is a substantial delay between error feedback and the opportunity to correct the error.

A Roadmap for Integrating Neuroscience Into Addiction Treatment: A Consensus of the Neuroscience Interest Group of the International Society of Addiction Medicine.

Although there is general consensus that altered brain structure and function underpins addictive disorders, clinicians working in addiction treatment rarely incorporate neuroscience-informed approaches into their practice. We recently launched the Neuroscience Interest Group within the International Society of Addiction Medicine (ISAM-NIG) to promote initiatives to bridge this gap. This article summarizes the ISAM-NIG key priorities and strategies to achieve implementation of addiction neuroscience knowledge and tools for the assessment and treatment of substance use disorders. We cover two assessment areas: cognitive assessment and neuroimaging, and two interventional areas: cognitive training/remediation and neuromodulation, where we identify key challenges and proposed solutions. We reason that incorporating cognitive assessment into clinical settings requires the identification of constructs that predict meaningful clinical outcomes. Other requirements are the development of measures that are easily-administered, reliable, and ecologically-valid. Translation of neuroimaging techniques requires the development of diagnostic and prognostic biomarkers and testing the cost-effectiveness of these biomarkers in individualized prediction algorithms for relapse prevention and treatment selection. Integration of cognitive assessments with neuroimaging can provide multilevel targets including neural, cognitive, and behavioral outcomes for neuroscience-informed interventions. Application of neuroscience-informed interventions including cognitive training/remediation and neuromodulation requires clear pathways to design treatments based on multilevel targets, additional evidence from randomized trials and subsequent clinical implementation, including evaluation of cost-effectiveness. We propose to address these challenges by promoting international collaboration between researchers and clinicians, developing harmonized protocols and data management systems, and prioritizing multi-site research that focuses on improving clinical outcomes.

Neurobiological substrate of smoking-related attentional bias.

Substance-dependent patients automatically and involuntarily allocate their attention to drug cues in the environment, a process referred to as attentional bias. Attentional bias is increased during periods of subjective craving and predictive of treatment outcome and relapse in substance dependence. Despite recent theoretical and clinical advances with regard to attentional bias, the underlying neurobiological mechanisms are largely unknown. The objective of the current study was to investigate the neural substrate of attentional bias and associated subjective craving in smokers. A group of smokers (n=20) and a group of age- and gender-matched nonsmoking controls (n=22) were recruited from the general population and participated in a single session of fMRI scanning while attentional processes were manipulated. Main outcome measures were blood oxygen level-dependent (BOLD) fMRI activation during an attentional bias paradigm and self-reported cigarette craving. Results of the current study show that the dorsal anterior cingulate cortex, the superior parietal gyrus, and the superior temporal gyrus were more strongly activated in smokers, as compared to controls, when they had to pay attention to task-relevant information (line counting) while smoking cues were present as distracters (attentional bias). Subjective craving measures during attentional bias correlated with brain activation in the insula and putamen. To our knowledge, this is the first controlled study that shows the brain regions involved in attentional bias in smokers. The current study demonstrates that brain regions contributing to top-down attentional processing are implicated in attentional bias in smokers, suggesting that smokers have to employ more attentional resources to focus on a standard cognitive task when smoking cues are present.