Resting-state effective connectivity in the motive circuit of methamphetamine users: A case controlled fMRI study

Methamphetamine and REM sleep deprivation interact to affect behavioral performance in adult and adolescent rats

Drug addiction may result in sleep problems. Importantly, sleep deprivation (SD) is known as an important risk factor for relapse to drug abuse as SD mimics the effects of psychostimulants on dopamine system of the brain. Moreover, aging may affect sleep and drug addiction. This study, therefore, set out to assess the effects of methamphetamine (METH) and REM sleep deprivation (RSD) on locomotor activity, anxiety-like behavior and spatial memory in adult and adolescent rats. Adult and adolescent male Wistar rats received a neurotoxic METH regimen; four subcutaneous injections of 6 mg/kg, at 2 h intervals. Five days later, the animals underwent a 48-h RSD episode using the multiple platforms method. They were then examined using the open field (OF), elevated plus maze (EPM) and Y-maze tasks. We found that the METH and RSD paradigms showed synergistic effects to increase locomotion and risk-taking behavior in both adult and adolescent animals, while only adolescent rats revealed RSD-induced anxiety-like behavior. Moreover, adolescent animals revealed greater sensitization for vertical activity following METH plus RSD episode. In addition, METH and RSD paradigms revealed synergistic effects to impair spatial working memory, but neither METH nor RSD alone affected performance of animals in the Y-maze task. Our findings may indicate that there are important relationships between METH and RSD to induce hyperlocomotion, risk-taking behavior and spatial memory impairment, particularly in adolescent animals. Moreover, it seems that adolescent rats may be more susceptible to anxiety-like behavior and hyperlocomotion than adults.

Role of sex hormones in the effects of sleep deprivation on methamphetamine reward memory

Sleep deficiency is known as an important risk factor for relapse to drug abuse, especially for the powerful psychostimulant methamphetamine (METH). On the other hand, both drug addiction and sleep neurobiology are affected by sex hormones. We, therefore, aimed to examine the probable effects of sleep deprivation (SD) on methamphetamine (METH) reward memory in male and female rats. Moreover, we asked if sex hormones influence the effects of SD on METH reward memory. Adult male and female Wistar rats were divided into two main groups, sham and gonadectomized groups. Three weeks later, they were conditioned to receive METH (2 mg/kg, i.p.) in the conditioned place preference. METH reward memory was then reinstated following a 10-day extinction period. SD was induced for 72 h, either before or after extinction, in different groups. In gonadectomized animals, they daily received either subcutaneous administration of estrogen (5 μg/0.1 ml oil) or progesterone (2 mg/0.1 ml oil) or dihydrotestosterone (25 mg/0.1 ml oil) for thirteen days, from post-conditioning day to reinstatement session. We found that SD facilitated relapse to METH reward memory, depending on the time interval between SD and METH reinstatement. Furthermore, we found that estrogen and SD showed synergistic effects to facilitate METH reward memory, whereas testosterone and progesterone revealed inhibitory effects in the controls, but not in the SD, animals. Our findings would seem to suggest that sex hormones should be considered as determinant factors to manage METH abuse and relapse to METH seeking/taking behavior, especially for those with sleep deficiency.

Anhedonia symptoms: The assessment of brain functional mechanism following music stimuli using functional magnetic resonance imaging

PURPOSE

This study aimed to investigate the effect of music stimulation on the brain functional mechanism of depressed patients with anhedonia symptoms using functional magnetic resonance imaging (fMRI).

METHODS

Participants in this study included 20 healthy subjects as the control group, 25 subjects with depression and no anhedonia as the intervention group A, and 24 subjects with depression and anhedonia as the intervention group B. The safely emotional stimulation was done by Iranian music. To investigate the effect of music therapy on the brain, a task including 50 tracks of 12 s Iranian music (traditional and pop) was used. Finally, the data were analyzed using SPM Toolbox in MATLAB software.

RESULTS

The results showed that brain patterns in depressed patients with and without anhedonia could be distinguished based on positive and negative musical stimuli (p < 0.05). Important fMRI biomarker such as effective connectivity strength related to the fronto-limbic network, including the supragenual ACC, subgenual ACC, AMYG, and FFG were evaluated in depressed patients with anhedonia.

CONCLUSION

This was the first study to investigate the neural circuits involved in music-related emotional processing in patients with anhedonia symptoms. These findings could help advance neurological understandings of anhedonia and suggest new treatments.

A brainnetome atlas-based methamphetamine dependence identification using neighborhood component analysis and machine learning on functional MRI data

Addiction to methamphetamine (MA) is a major public health concern. Developing a predictive model that can classify and characterize the brain-based biomarkers predicting MA addicts may directly lead to improved treatment outcomes. In the current study, we applied the support vector machine (SVM)-based classification method to resting-state functional magnetic resonance imaging (rs-fMRI) data obtained from individuals with methamphetamine use disorder (MUD) and healthy controls (HCs) to identify brain-based features predictive of MUD. Brain connectivity analyses were conducted for 36 individuals with MUD as well as 37 HCs based on the brainnetome atlas, and the neighborhood component analysis was applied for feature selection. Eighteen most relevant features were screened out and fed into the SVM to classify the data. The classifier was able to differentiate individuals with MUD from HCs with a high prediction accuracy, sensitivity, specificity, and AUC of 88.00, 86.84, 89.19, and 0.94, respectively. The top six discriminative features associated with changes in the functional activity of key nodes in the default mode network (DMN), all the remaining discriminative features are related to the thalamic connections within the cortico-striato-thalamo-cortical (CSTC) loop. In addition, the functional connectivity (FC) between the bilateral inferior parietal lobule (IPL) and right cingulate gyrus (CG) was significantly correlated with the duration of methamphetamine use. The results of this study not only indicated that MUD-related FC alterations were predictive of group membership, but also suggested that machine learning techniques could be used for the identification of MUD-related imaging biomarkers.

Maternal sleep deprivation affects extinction and reinstatement of methamphetamine reward memory in male offspring: role of the D1-like and D2-like dopamine receptors

Maternal sleep-deprivation (MSD) has been shown to induce stress, hyperactivity, and risk taking behavior in the offspring; howbeit, it is not yet clear whether it may also affect vulnerability to psychostimulant abuse in the offspring. We aimed to determine whether MSD affects extinction and reinstatement of methamphetamine (METH) reward memory in the offspring and also to evaluate the possible role of dopamine D1-like and D2-like receptors in these processes. Thirty-day-old male offspring born to control and sleep-deprived dams (during the third week of pregnancy) were trained to acquire METH-induced place preference (2 mg/kg., i.p.). METH reward memory was then reinstated following an 8-day period of extinction. The offspring received SCH 23390 (0.03 or 0.1 mg/kg, i.p.) or sulpiride (20 or 60 mg/kg, i.p.) as antagonists of dopamine D1-like and D2-like receptors, respectively, either immediately after each daily extinction session or prior to the reinstatement session. MSD postponed METH extinction and facilitated METH reinstatement in the offspring. SCH 23390 facilitated METH extinction and decreased reinstatement of the extinguished METH preference. Sulpiride in the offspring from sleep-deprived dams facilitated METH extinction, but it did not affect reinstatement of the extinguished METH place preference. It seems that MSD may enhance vulnerability to METH abuse in the offspring. Furthermore, both dopamine D1-like and D2-like receptors may mediate METH extinction in the offspring born to the sleep-deprived dams; however, only the dopamine D1 receptor may play an important role in reinstating the extinguished METH reward memory in the offspring.

Local efficiency analysis of restingstate functional brain network in methamphetamine users

This study set out to assess restingstate functional connectivity (rs-FN) and graph theorybased local efficiency within the left and right hemispheres of methamphetamine (MA) abusers. Functional brain networks of 19 MA abusers and 21 control participants were analyzed using restingstate fMRI. Graph edges in functional networks of the brain were defined and recurrence plot was used. We found that MA abuse may be accompanied by alterations of rs-FN within the defaultmode network (DMN), executive control network (ECN), and the salience network (SN) in both hemispheres of the brain. We also observed that such effects of MA may be correlated with duration of MA abuse and abstinence in many components of the DMN and SN. The results would seem to suggest that MAinduced alterations of local efficiency may, in part, account for maladaptive decision making, deficits in executive function and control over drug seeking/taking, and relapse.

Impairments in the Default Mode and Executive Networks in Methamphetamine Users During Short-Term Abstinence

Purpose

Methamphetamine use may cause severe neurotoxicity and cognitive impairment, leading to addiction, overdose, and high rates of relapse. However, few studies have systematically focused on functional impairments detected by neuroimaging in methamphetamine abstainers (MAs) during short-term abstinence. This study aimed to investigate effective connectivity, resting-state networks, and internetwork functional connectivity in MA brains to improve clinical treatment.

Methods

Twenty MAs and 27 age- and education-matched healthy controls underwent resting-state functional magnetic resonance imaging. The amplitude of low-frequency fluctuations and Granger causality were analyzed to investigate disrupted brain regions and effective connectivity, respectively. Independent component analysis and functional network connectivity were used to identify resting-state networks and internetwork functional connectivity, respectively.

Results

Compared with healthy controls, MAs demonstrated abnormal amplitudes of low-frequency fluctuations in the bilateral precuneus, left posterior cingulate cortex (PCC), left middle frontal gyrus (MFG), left superior parietal lobule, left supplementary motor area (SMA), and left inferior parietal lobule (IPL). Moreover, MAs showed decreased effective connectivity from the left PCC to the left precuneus, increased effective connectivity from the left precuneus to the left MFG and from the right precuneus to the left SMA, and altered functional connectivity within the default mode network (DMN), frontoparietal network, sensorimotor network, ventral attention network, cerebellar network, and visual network. Importantly, hyperconnectivity between the DMN and ventral attention network and hypoconnectivity between the DMN and cerebellar network as well as the DMN and frontoparietal network were demonstrated in MAs.

Conclusion

Our study implies that in short-term methamphetamine abstinence, disruptions to the DMN and executive network may a play key role, providing new insights for early rehabilitation.

Dynamics of intrinsic whole-brain functional connectivity in abstinent males with methamphetamine use disorder

Background

The global prevalence of methamphetamine use disorder (MUD) and the associated economic burden are increasing, but effective pharmacological treatment is lacking. Therefore, understanding the neurological mechanisms underlying MUD is essential to develop clinical strategies and improve patient care. Individuals with MUD can show static brain network abnormalities during the resting state, but their alterations in dynamic functional network connectivity (dFNC) are unclear.

Methods

In this study, we obtained resting-state functional magnetic resonance imaging from 42 males with MUD and 41 healthy controls. Sliding-window and spatial independent component analyses with a k-means clustering algorithm were used to assess the recurring functional connectivity states. The temporal properties of the dFNC, including fraction and dwelling time of each state and the number of transitions between different states, were compared between the two groups. In addition, the relationships between the temporal properties of the dFNC and clinical characteristics of the MUDs, including their anxiety and depressive symptoms, were further explored.

Results

While the two groups shared many similarities in their dFNC, the occurrence of a highly integrated functional network state and a state featuring balanced integration and segregation in the MUDs significantly correlated with the total drug usage (Spearman's rho = 0.47, P = 0.002) and duration of abstinence (Spearman's rho = 0.38, P = 0.013), respectively.

Conclusions

The observed results in our study demonstrate that methamphetamines can affect dFNC, which may reflect the drug's influence on cognitive abilities. Our study justifies further studies into the effects of MUD on dynamic neural mechanisms.

Disruption of regional homogeneity in the brains of chronic methamphetamine users

Previous studies have reported evidence supporting structural and functional alterations in the brains of methamphetamine (MA) users. The aim of the present study was to extend current knowledge regarding brain function(s) in MA users by examining regional homogeneity (ReHo). Chronic MA users (51 male, 46 female), who were undergoing supervised abstinence for 12 to 621 days, and 79 healthy controls (43 male, 36 female) underwent resting-state functional brain magnetic resonance imaging. Voxel-wise whole-brain scale group differences in ReHo were examined. The mean ReHo values of significant clusters were extracted, and linear regression was used to identify factors that contributed to these mean ReHo values. MA users exhibited lower ReHo values in the left orbital part of the inferior frontal gyrus extending to the left insula and left temporal pole, left amygdala, and left fusiform gyrus. MA users also exhibited greater ReHo values in the bilateral pre- and postcentral gyri and right cerebellum. Characteristics of MA use, including duration, duration of abstinence from MA, and age at onset of MA use, demonstrated no reliable contribution to ReHo of the significant clusters. Findings of the present study demonstrated that chronic MA use was associated with regional specific disruption of ReHo, which is relatively independent of structural and functional alterations and, apparently, does not recover after relatively long-term abstinence. This disruption may underlie overall neurocognitive deficits in MA users, which is difficult to recover.

Dynamic Causal Modeling on the Identification of Interacting Networks in the Brain: A Systematic Review

Dynamic causal modeling (DCM) has long been used to characterize effective connectivity within networks of distributed neuronal responses. Previous reviews have highlighted the understanding of the conceptual basis behind DCM and its variants from different aspects. However, no detailed summary or classification research on the task-related effective connectivity of various brain regions has been made formally available so far, and there is also a lack of application analysis of DCM for hemodynamic and electrophysiological measurements. This review aims to analyze the effective connectivity of different brain regions using DCM for different measurement data. We found that, in general, most studies focused on the networks between different cortical regions, and the research on the networks between other deep subcortical nuclei or between them and the cerebral cortex are receiving increasing attention, but far from the same scale. Our analysis also reveals a clear bias towards some task types. Based on these results, we identify and discuss several promising research directions that may help the community to attain a clear understanding of the brain network interactions under different tasks.

Functional connectivity abnormalities underlying mood disturbances in male abstinent methamphetamine abusers

Anxiety and depression are the most common withdrawal symptoms of methamphetamine (METH) abuse, which further exacerbate relapse of METH abuse. To date, no effective pharmacotherapy exists for METH abuse and its withdrawal symptoms. Therefore, understanding the neuromechanism underlying METH abuse and its withdrawal symptoms is essential for developing clinical strategies and improving patient care. The aims of this study were to investigate brain network abnormalities in METH abusers (MAs) and their associations with affective symptoms. Forty-eight male abstinent MAs and 48 age-gender matched healthy controls were recruited and underwent resting state functional magnetic resonance imaging (fMRI). The severity of patient anxiety and depressive symptoms were measured by Hamilton anxiety and depression rating scales, which decreased across the duration of abstinence. Independent component analysis was used to investigate the brain network functional connectivity (FC) properties. Compared with healthy controls, MAs demonstrated hypo-intra-network FC in the cerebellar network and hyper-intra-network FC in the posterior salience network. A whole-brain regression analysis revealed that FC strength of clusters located in the right rostral anterior cingulate cortex (rACC) within the ventromedial network (VMN) was associated with affective symptoms in the patients. Importantly, the intra-network FC strength of the rACC in VMN mediated the association between abstinence duration and the severity level of affective symptoms. Our results demonstrate alterations in brain functional networks underlying METH abuse, and that the FC of rACC within VMN serve as a neural substrate in the association between abstinence length and affective symptom severity in the MAs.