Aberrant prefrontal-parietal-cerebellar circuits in alcohol dependence

Substance use disorders are characterised by increased voxel-wise intrinsic measures in sensorimotor cortices: An ALE meta-analysis

Substance use disorders (SUDs) are severe psychiatric illnesses. Seed region and independent component analyses are currently the dominant connectivity measures but carry the risk of false negatives due to selection. They can be complemented by a data-driven and whole-brain usage of voxel-wise intrinsic measures (VIMs). We meta-analytically integrated VIMs, namely regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF), voxel-mirrored homotopy connectivity (VMHC) and degree centrality (DC) across different SUDs using the Activation Likelihood Estimation (ALE) algorithm, functionally decoded emerging clusters, and analysed their connectivity profiles. Our systematic search identified 51 studies including 1439 SUD participants. Although no overall convergent pattern of alterations across VIMs in SUDs was found, sensitivity analyses demonstrated two ALE-derived clusters of increased ReHo and ALFF in SUDs, which peaked in the left pre- and postcentral cortices. Subsequent analyses showed their involvement in action execution, somesthesis, finger tapping and vibrotactile monitoring/discrimination. Their numerous clinical correlates across included studies highlight the under-discussed role of sensorimotor cortices in SUD, urging a more attentive exploration of their clinical significance.

The resting-state brain activity signatures for addictive disorders

BACKGROUND

Addiction is a chronic and relapsing brain disorder. Despite numerous neuroimaging and neurophysiological studies on individuals with substance use disorder (SUD) or behavioral addiction (BEA), currently a clear neural activity signature for the addicted brain is lacking.

METHODS

We first performed systemic coordinate-based meta-analysis and partial least-squares regression to identify shared or distinct brain regions across multiple addictive disorders, with abnormal resting-state activity in SUD and BEA based on 46 studies (55 contrasts), including regional homogeneity (ReHo) and low-frequency fluctuation amplitude (ALFF) or fractional ALFF. We then combined Neurosynth, postmortem gene expression, and receptor/transporter distribution data to uncover the potential molecular mechanisms underlying these neural activity signatures.

FINDINGS

The overall comparison between addiction cohorts and healthy subjects indicated significantly increased ReHo and ALFF in the right striatum (putamen) and bilateral supplementary motor area, as well as decreased ReHo and ALFF in the bilateral anterior cingulate cortex and ventral medial prefrontal cortex, in the addiction group. On the other hand, neural activity in cingulate cortex, ventral medial prefrontal cortex, and orbitofrontal cortex differed between SUD and BEA subjects. Using molecular analyses, the altered resting activity recapitulated the spatial distribution of dopaminergic, GABAergic, and acetylcholine system in SUD, while this also includes the serotonergic system in BEA.

CONCLUSIONS

These results indicate both common and distinctive neural substrates underlying SUD and BEA, which validates and supports targeted neuromodulation against addiction.

FUNDING

This work was supported by the National Natural Science Foundation of China and Intramural Research Program of the National Institute on Drug Abuse, National Institutes of Health.

A voxel-level resting-state fMRI study on patients with alcohol use disorders based on a power spectrum slope analysis method

Background

Earlier neuroimaging investigations showed that abnormal brain activity in patients with alcohol use disorder (AUD) was frequency dependent. However, there is lacking of a comprehensive method to capture the amplitude of multi-frequency bands directly. Here, we used a new method, the power spectrum slope (PSS) to explore abnormal spontaneous activity of brain in patients with AUD.

Methods

Thirty-three AUD patients and 29 healthy controls (HCs) enrolled in this study. The coefficient b and the power-law slope b' were calculated and compared between two groups. We also used the receiver operating characteristic (ROC) curve to examine the ability of the PSS analysis to distinguish between AUD and HCs. We next examined the correlation between PSS difference in the brain areas and the severity of alcohol dependence.

Results

Thirty AUD patients and 26 HCs were retained after head motion correction. The two metrics of PSS values increased in the left precentral gyrus in AUD patients. The area under the curve values of PSS differences in the specific brain area were respectively 0.836 and 0.844, with sensitivities of 86.7% and 83.3% and specificities of 73.1% and 76.9%. The Michigan Alcoholism Screening Test (MAST) and Alcohol drinking scale (ADS) scores were not significantly correlated with the PSS values in the specific brain area.

Conclusion

As a novel method, the PSS can well detect abnormal local brain activity in the AUD patients and may offer new insights for future fMRI studies.

Alterations of brain activity in patients with alcohol use disorder: a resting-state fMRI study

BACKGROUND

Alcohol use disorder (AUD) has a negative impact on one's health and wastes a lot of societal resources since it damages one's brain tissue. Yet the knowledge of the neural mechanisms underlying alcohol addiction still remains limited. This study aims to investigate the neural mechanisms underlying alcohol addiction by using voxel-wise binarized degree centrality (DC), weighted DC and functional connectivity (FC) methods to analyze brain network activity in individuals with AUD.

METHODS

Thirty-three AUD patients and 29 healthy controls (HC) participated in this study. Binarized and weighted DC approach coupled with a second seed-based FC algorithm was used to assess the abnormal intrinsic hub features in AUD. We also examined the correlation between changes in functional network nodes and the severity of alcohol dependence.

RESULTS

Thirty AUD patients and 26 HC were retained after head motion correction. The spatial distribution maps of the binarized DC and weighted DC for the AUD and HC groups were roughly similar. In comparison to HC, the AUD group had decreased binarized DC and decreased weighted DC in the left precentral gyrus (PreCG) and the left inferior parietal lobule (IPL). Significantly different brain regions in the DC analysis were defined as seed points in the FC analysis. Compared with HC, changes in FC within the right inferior temporal gyrus (ITG), right middle temporal gyrus (MTG), left dorsolateral superior frontal gyrus (SFGdor), bilateral IPL, left precuneus (PCUN), left lingual gyrus (LING), right cerebellum_crus1/ITG/inferior occipital gyrus (IOG) and right superior parietal gyrus (SPG) were observed. The correlation analysis revealed that FC of right MTG-right PreCG was negatively correlated with MAST scores, and FC of right IPL-left IPL was positively correlated with ADS scores.

CONCLUSIONS

Alcohol use disorder is associated with aberrant regional activities in multiple brain areas. Binarized DC, weighted DC and FC analyses may be useful biological indicators for the detection of regional brain activities in patients with AUD. Intergroup differences in FC have also been observed in AUD patients, and these variations were connected to the severity of the symptoms. The AUD patients with lower FC value of the right IPL - left IPL has a lighter dependence on alcohol. This difference in symptom severity may be a compensation for cognitive impairment, indicating a difference in pathological pathways. Future AUD research will now have a fresh path thanks to these discoveries.

Characteristics of amplitude of low-frequency fluctuations in the resting-state functional magnetic resonance imaging of alcohol-dependent patients with depression

The high comorbidity of alcohol use disorder and depressive disorder is associated with poor patient prognosis. The mechanisms underlying this comorbidity, however, are largely unknown. By applying the amplitude of low-frequency fluctuations parameter in resting-state functional magnetic resonance imaging, this study investigated changes in the brain functioning of alcohol-dependent patients with and without depression. Alcohol-dependent patients (n = 48) and healthy controls (n = 31) were recruited. The alcohol-dependent patients were divided into those with and without depression, according to Patients Health Questionnaire-9 scores. Amplitude of low-frequency fluctuations in resting-state brain images were compared among the alcohol-dependent patients with depression, alcohol-dependent patients without depression, and healthy controls groups. We further examined associations between amplitude of low-frequency fluctuations alterations, alcohol-dependence severity, and depressive levels (assessed with scales). Compared with the healthy controls group, both alcohol groups showed amplitude of low-frequency fluctuations enhancement in the right cerebellum and amplitude of low-frequency fluctuations abatement in the posterior central gyrus. The alcohol-dependent patients with depression group had higher amplitude of low-frequency fluctuations in the right cerebellum than the alcohol-dependent patients without depression group. Additionally, we observed a positive correlation between amplitude of low-frequency fluctuations value and Patients Health Questionnaire-9 score in the right superior temporal gyrus in the alcohol-dependent patients with depression group. Alcohol-dependent subjects showed abnormally increased spontaneous neural activity in the right cerebellum, which was more significant in alcohol-dependent patients with depression. These findings may support a targeted intervention in this brain location for alcohol and depressive disorder comorbidity.

Cognitive Challenges Are Better in Distinguishing Binge From Nonbinge Drinkers: An Exploratory Deep-Learning Study of fMRI Data of Multiple Behavioral Tasks and Resting State

BACKGROUND

Studies have identified imaging markers of binge drinking. Functional connectivity during both task challenges and resting state was shown to distinguish binge and nonbinge drinkers. However, no studies have compared the efficacy of task and resting data in the classification.

HYPOTHESIS

Task outperforms resting-state functional magnetic resonance imaging (fMRI) data in the differentiation of binge and nonbinge drinkers. We tested the hypothesis via multiple deep learning algorithms.

STUDY TYPE

Cross-sectional; retrospective.

POPULATION

A total of 149 binge (107 men) and 151 demographically matched, nonbinge (92 men) drinkers curated from the Human Connectome Project, with 80% randomly selected for model development and 20% for validation/test.

FIELD STRENGTH/SEQUENCE

A 3 T; fMRI with a blood oxygen level-dependent (BOLD) gradient-echo echo-planar sequence.

ASSESSMENT

FMRI data of resting state and seven behavioral tasks were acquired. Graph convolutional network (GCN), long short-term memory, convolutional, and recurrent neural network models were built to distinguish bingers and nonbingers using connectivity matrices of 8, 116, and 268 regions of interest (ROI). Nodal metrics including betweenness centrality, degree centrality, clustering coefficient, efficiency, local efficiency, and shortest path length were calculated from the GCN model.

STATISTICAL TESTS

Model performance was quantified by the area under the curve (AUC) in receiver operating characteristic analysis. A P value < 0.05 was considered statistically significant.

RESULTS

Task outperformed resting data in classification by approximately 8% by AUC in the test set. Across models and ROI sets, the gambling, motor, language and working memory tasks, each with AUC of 0.614, 0.612, 0.605, and 0.603, performed better than resting data (AUC = 0.548). Models with 116 ROIs (AUC = 0.602) consistently outperformed those with 8 ROIs (AUC = 0.569). Task data performed best with GCN (AUC = 0.619). Nodal metrics of left supplementary motor area and right cuneus showed significant group main effect across tasks.

CONCLUSION

Neural responses to cognitive challenges relative to resting state better characterize binge drinking. The performance of different network models may depend on behavioral tasks and the number of ROIs.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Advances in neuroimaging studies of alcohol use disorder (AUD)

Alcohol use disorder (AUD) is a worldwide problem and the most common substance use disorder. Chronic alcohol consumption may have negative effects on the body, the mind, the family, and even society. With the progress of current neuroimaging methods, an increasing number of imaging techniques are being used to objectively detect brain impairment induced by alcoholism and serve a vital role in the diagnosis, prognosis, and treatment assessment of AUD. This article organizes and analyzes the research on alcohol dependence concerning the main noninvasive neuroimaging methods, structural magnetic resonance imaging, functional magnetic resonance imaging, and electroencephalography, as well as the most common noninvasive brain stimulation - transcranial magnetic stimulation, and intersperses the article with joint intra- and intergroup studies, providing an outlook on future research directions.

Alcohol-induced brain deficit in alcohol dependence

Although numerous adverse effects of alcohol addiction on health, behavior, and brain function were widely reported, the neurobiological mechanism of alcohol dependence remains largely unknown. In this study, a total of twenty-nine patients with alcohol dependence and twenty-nine status-matched normal controls (NCs) were recruited. Percent amplitude of fluctuation (PerAF) was applied to identify alcohol-related brain activity deficits. We found that alcohol dependence was associated with widespread differences in the left orbitofrontal cortex, right higher visual cortex, right supramarginal gyrus, right postcentral gyrus, and bilateral cerebellum posterior lobe with decreased PerAF, but no brain areas with increased PerAF differences were found. ROC curve showed that decreased PerAF revealed extremely high discriminatory power with a high AUC value of 0.953, as well as a high degree of sensitivity (96.6%) and specificity (86.2%), in distinguishing patients with alcohol dependence from NCs. In the alcohol dependence group, the amount of daily alcohol consumption showed significant negative correlations with the right cerebellum posterior lobe and right higher visual cortex. These findings suggest that the cerebellar-visual-orbitofrontal circuit was disturbed by alcohol dependence. The proposed new method of PerAF may be served as a potential biomarker to identify the regional brain activity deficits of alcohol dependence.

Aberrant intrinsic neural network strength in individuals with "smartphone addiction": An MRI data fusion study

BACKGROUND AND OBJECTIVES

Excessive smartphone use, also referred to as "smartphone addiction" (SPA), has increasingly attracted neuroscientific interest due to its similarities with other behavioral addictions, particularly internet gaming disorder. Little is known about the neural mechanisms underlying smartphone addiction. We explored interrelationships between brain structure and function to specify neurobiological correlates of SPA on a neural system level.

METHODS

Gray matter volume (GMV) and intrinsic neural activity (INA) were investigated in individuals with SPA (n = 20) and controls (n = 24), using multimodal magnetic resonance imaging and multivariate data fusion techniques, that is, parallel independent component analysis.

RESULTS

The joint analysis of both data modalities explored shared information between GMV and INA. In particular, two amplitudes of low frequency fluctuations-based independent neural systems significantly differed between individuals with SPA and controls. A medial/dorsolateral prefrontal system exhibited lower functional network strength in individuals with SPA versus controls, whereas the opposite pattern was detected in a parietal cortical/cerebellar system. Neural network strength was significantly related to duration of smartphone use and sleep difficulties.

DISCUSSION AND CONCLUSIONS

We show modality-specific associations of the brain's resting-state activity with distinct and shared SPA symptom dimensions. In particular, the data suggest contributions of aberrant prefrontal and parietal neural network strength as a possible signature of deficient executive control in SPA.

SCIENTIFIC SIGNIFICANCE

This study suggests distinct neural mechanisms underlying specific biological and behavioral dimensions of excessive smartphone use.

Differential effects of alcohol-drinking patterns on the structure and function of the brain and cognitive performance in young adult drinkers: A pilot study

INTRODUCTION

This study was aimed to determine how different patterns of alcohol consumption drive changes to brain structure and function and their correlation with cognitive impairments in young adult alcohol drinkers.

METHODS

In this study, we enrolled five groups participants and defined as: long-term abstinence from alcohol (LA), binge drinking (BD), long-term low dosage alcohol consumption but exceeding the safety drinking dosage (LD), long-term alcohol consumption of damaging dosage (LDD), and long-term heavy drinking (HD). All participants underwent magnetic resonance imaging (MRI) and functional MRI (fMRI) to acquire data on brain structure and function, including gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), functional connectivity (FC), and brain network properties. The cognitive ability was evaluated with the California Verbal Learning Test (CVLT), intelligence quotient (IQ), and short delay free recall (SDFR).

RESULTS

Compared to LA, GMV significantly decreased in the brain regions in VN, SMN, and VAN in the alcohol-drinking groups (BD, LD, LDD, and HD). ReHo was significantly enhanced in the brain regions in VN, SMN, and VAN, while fALFF significantly increased in the brain regions in VN and SMN. The number of intra- and inter-modular connections within networks (VN, SMN, sensory control network [SCN], and VAN) and their connections to other modules were abnormally changed. These changes adversely affected cognition (e.g., IQ, CVLT, SDFR).

CONCLUSION

Despite the small sample size, this study provides new evidence supporting the need for young people to abstain from alcohol to protect their brains. These findings present strong reasoning for updating anti-alcohol slogans and guidelines for young people in the future.

Heavy drinking from adolescence to young adulthood is associated with an altered cerebellum

Excessive alcohol use results in cerebellar damage in adults, but there has been less research on how alcohol use during adolescence affects the cerebellum. In this study, we observed that heavy drinking from adolescence to young adulthood was associated with altered volumes of cerebellar lobules. The study included two groups consisting of 33 heavy-drinking and 25 light-drinking participants. The heavy-drinking participants were highly functional young adults without alcohol use disorder, but with a history of regular heavy alcohol consumption. The participants were 13-18 years old at baseline and were followed for 10 years. At the age of 21-28 years, the participants underwent magnetic resonance imaging (MRI). From the MR images, the cerebellum was segmented into 12 lobules using the CERES pipeline. Heavy drinking did not influence the absolute cerebellar volume, but changes were observed in posterior cerebellar lobules associated with motor and cognitive functions. The absolute volume (p = 0.038) and gray matter volume (p = 0.034) of Crus II (hemispheres combined) were smaller in the heavy-drinking group. Furthermore, the relative volume of the right VIIIB lobule was larger in the HD group (p = 0.036). However, there were no differences in the absolute right VIIIB volumes (p = 0.198) between the groups. Our results suggest changes in the cerebellum in healthy young adults with a history of heavy drinking from adolescence. The exact implications and significance of these findings require further research.

Neural correlates of visuoperceptive changes in severe alcohol use disorder: A critical review of neuroimaging and electrophysiological findings

Visuoperceptive deficits are frequently reported in severe alcohol use disorder (SAUD) and are considered as pervasive and persistent in time. While this topic of investigation has previously driven researchers' interest, far fewer studies have focused on visuoperception in SAUD since the '90s, leaving open central questions regarding the origin and implications of these deficits. To renew research in the field and provide a solid background to work upon, this paper reviews the neural correlates of visuoperception in SAUD, based on data from neuroimaging and electrophysiological studies. Results reveal structural and functional changes within the visual system but also in the connections between occipital and frontal areas. We highlight the lack of integration of these findings in the dominant models of vision which stress the dynamic nature of the visual system and consider the presence of both bottom-up and top-down cerebral mechanisms. Visuoperceptive changes are also discussed in the framework of long-lasting debates regarding the influence of demographic and alcohol-related factors, together stressing the presence of inter-individual differences. Capitalizing on this review, we provide guidelines to inform future research, and ultimately improve clinical care.

Structural and functional correlates of smartphone addiction

Popularity and availability of smartphones have dramatically increased in the past years. This trend is accompanied by increased concerns regarding potentially adverse effects of excessive smartphone use, particularly with respect to physical and mental health. Recently, the term "smartphone addiction" (SPA) has been introduced to describe smartphone-related addictive behavior and associated physical and psychosocial impairment. Here, we used structural and functional magnetic resonance imaging (MRI) at 3 T to investigate gray matter volume (GMV) and intrinsic neural activity in individuals with SPA (n = 22) compared to a control group (n = 26). SPA was assessed using the Smartphone Addiction Inventory (SPAI), GMV was investigated by means of voxel-based morphometry, and intrinsic neural activity was measured by the amplitude of low frequency fluctuations (ALFF). Compared to controls, individuals with SPA showed lower GMV in left anterior insula, inferior temporal and parahippocampal cortex (p < 0.001, uncorrected for height, followed by correction for spatial extent). Lower intrinsic activity in SPA was found in the right anterior cingulate cortex (ACC). A significant negative association was found between SPAI and both ACC volume and activity. In addition, a significant negative association between SPAI scores and left orbitofrontal GMV was found. This study provides first evidence for distinct structural and functional correlates of behavioral addiction in individuals meeting psychometric criteria for SPA. Given their widespread use and increasing popularity, the present study questions the harmlessness of smartphones, at least in individuals that may be at increased risk for developing smartphone-related addictive behaviors.