Distinct intrinsic functional brain network abnormalities in methamphetamine-dependent patients with and without a history of psychosis

Assessment of rTMS treatment effects for methamphetamine use disorder based on EEG microstates

Microstates have been proposed as topographical maps representing large-scale resting-state networks and have recently been suggested as markers for methamphetamine use disorder (MUD). However, it is unknown whether and how they change after repetitive transcranial magnetic stimulation (rTMS) intervention. This study included a comprehensive subject population to investigate the effect of rTMS on MUD microstates. 34 patients with MUD underwent a 4-week randomized, double-blind rTMS intervention (active=17, sham=17). Two resting-state EEG recordings and VAS evaluations were conducted before and after the intervention period. Additionally, 17 healthy individuals were included as baseline controls. The modified k-means clustering method was used to calculate four microstates (MS-A∼MS-D) of EEG, and the FC network was also analyzed. The differences in microstate indicators between groups and within groups were compared. The durations of MS-A and MS-B microstates in patients with MUD were significantly lower than that in HC but showed significant improvements after rTMS intervention. Changes in microstate indicators were found to be significantly correlated with changes in craving level. Furthermore, selective modulation of the resting-state network by rTMS was observed in the FC network. The findings indicate that changes in microstates in patients with MUD are associated with craving level improvement following rTMS, suggesting they may serve as valuable evaluation markers.

The evolution of Big Data in neuroscience and neurology

Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started to transform the fields of Neuroscience and Neurology. Scientists and clinicians are collaborating in global alliances, combining diverse datasets on a massive scale, and solving complex computational problems that demand the utilization of increasingly powerful computational resources. This Big Data revolution is opening new avenues for developing innovative treatments for neurological diseases. Our paper surveys Big Data's impact on neurological patient care, as exemplified through work done in a comprehensive selection of areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Disease, Pain, and Addiction (e.g., Opioid Use Disorder). We present an overview of research and the methodologies utilizing Big Data in each area, as well as their current limitations and technical challenges. Despite the potential benefits, the full potential of Big Data in these fields currently remains unrealized. We close with recommendations for future research aimed at optimizing the use of Big Data in Neuroscience and Neurology for improved patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40537-023-00751-2.

Aberrant topology of white matter networks in patients with methamphetamine dependence and its application in support vector machine-based classification

Brain white matter (WM) networks have been widely studied in neuropsychiatric disorders. However, few studies have evaluated alterations in WM network topological organization in patients with methamphetamine (MA) dependence. Therefore, using machine learning classification methods to analyze WM network topological attributes may give new insights into patients with MA dependence. In the study, diffusion tensor imaging-based probabilistic tractography was used to map the weighted WM networks in 46 MA-dependent patients and 46 control subjects. Using graph-theoretical analyses, the global and regional topological attributes of WM networks for both groups were calculated and compared to determine inter-group differences using a permutation-based general linear model. In addition, the study used a support vector machine (SVM) learning approach to construct a classifier for discriminating subjects with MA dependence from control subjects. Relative to the control group, the MA-dependent group exhibited abnormal topological organization, as evidenced by decreased small-worldness and modularity, and increased nodal efficiency in the right medial superior temporal gyrus, right pallidum, and right ventromedial putamen; the MA-dependent group had the higher hubness scores in 25 regions, which were mainly located in the default mode network. An SVM trained with topological attributes achieved classification accuracy, sensitivity, specificity, and kappa values of 98.09% ± 2.59%, 98.24% ± 4.00%, 97.94% ± 4.26%, and 96.18% ± 5.19% for patients with MA dependence. Our results may suggest altered global WM structural networks in MA-dependent patients. Furthermore, the abnormal WM network topological attributes may provide promising features for the construction of high-efficacy classification models.

Abnormal resting-state functional connectome in methamphetamine-dependent patients and its application in machine-learning-based classification

Brain resting-state functional connectivity (rsFC) has been widely analyzed in substance use disorders (SUDs), including methamphetamine (MA) dependence. Most of these studies utilized Pearson correlation analysis to assess rsFC, which cannot determine whether two brain regions are connected by direct or indirect pathways. Moreover, few studies have reported the application of rsFC-based graph theory in MA dependence. We evaluated alterations in Tikhonov regularization-based rsFC and rsFC-based topological attributes in 46 MA-dependent patients, as well as the correlations between topological attributes and clinical variables. Moreover, the topological attributes selected by least absolute shrinkage and selection operator (LASSO) were used to construct a support vector machine (SVM)-based classifier for MA dependence. The MA group presented a subnetwork with increased rsFC, indicating overactivation of the reward circuit that makes patients very sensitive to drug-related visual cues, and a subnetwork with decreased rsFC suggesting aberrant synchronized spontaneous activity in subregions within the orbitofrontal cortex (OFC) system. The MA group demonstrated a significantly decreased area under the curve (AUC) for the clustering coefficient (Cp) (Pperm < 0.001), shortest path length (Lp) (Pperm = 0.007), modularity (Pperm = 0.006), and small-worldness (σ, Pperm = 0.004), as well as an increased AUC for global efficiency (E.glob) (Pperm = 0.009), network strength (Sp) (Pperm = 0.009), and small-worldness (ω, Pperm < 0.001), implying a shift toward random networks. MA-related increased nodal efficiency (E.nodal) and altered betweenness centrality were also discovered in several brain regions. The AUC for ω was significantly positively associated with psychiatric symptoms. An SVM classifier trained by 36 features selected by LASSO from all topological attributes achieved excellent performance, cross-validated prediction area under the receiver operating characteristics curve, accuracy, sensitivity, specificity, and kappa of 99.03 ± 1.79, 94.00 ± 5.78, 93.46 ± 8.82, 94.52 ± 8.11, and 87.99 ± 11.57%, respectively (Pperm < 0.001), indicating that rsFC-based topological attributes can provide promising features for constructing a high-efficacy classifier for MA dependence.

Common gray matter loss in the frontal cortex in patients with methamphetamine-associated psychosis and schizophrenia

BACKGROUND AND HYPOTHESIS

Methamphetamine (MA)-associated psychosis has become a public concern. However, its mechanism is not clear. Investigating similarities and differences between MA-associated psychosis and schizophrenia in brain alterations would be informative for neuropathology.

STUDY DESIGN

This study compared gray matter volumes of the brain across four participant groups: healthy controls (HC, n = 53), MA users without psychosis (MA, n = 22), patients with MA-associated psychosis (MAP, n = 34) and patients with schizophrenia (SCZ, n = 33). Clinical predictors of brain alterations, as well as association of brain alterations with psychotic symptoms and attention impairment were further investigated.

STUDY RESULTS

Compared with the HC, the MAP and the SCZ showed similar gray matter reductions in the frontal cortex, particularly in prefrontal areas. Moreover, a stepwise extension of gray matter reductions was exhibited across the MA - MAP - SCZ. Duration of abstinence was associated with regional volumetric recovery in the MAP, while this amendment in brain morphometry was not accompanied with symptom's remission. Illness duration of psychosis was among the predictive factors of regional gray matter reductions in both psychotic groups. Volume reductions were found to be associated with attention impairment in the SCZ, while this association was reversed in the MAP in frontal cortex.

CONCLUSIONS

This study suggested MA-associated psychosis and schizophrenia had common neuropathology in cognitive-related frontal cortices. A continuum of neuropathology between MA use and schizophrenia was tentatively implicated. Illness progressions and glial repairments could both play roles in neuropathological changes in MA-associated psychosis.

Differences in small-world networks between methamphetamine and heroin use disorder patients and their relationship with psychiatric symptoms

Both methamphetamine use disorder (MAUD) and heroin use disorder (HUD) implicated in substance-induced psychosis, but the psychiatirc symptoms induced by MAUD and HUD are significantly different. The functional network organizations that may underlie these differences remains unknown. Image data was acquired by resting-state fMRI from 19 MAUD patients, 21 HUD patients, and 20 healthy controls. The small-world properties, node attributes, and functional connectivity of brain regions were analyzed among the three groups. Psychiatric status was evaluated by the Symptom Checklist 90 in all participants. The MAUD patients had significantly higher psychiatric scores than the controls and HUD patients. Both MAUD and HUD patients still had economical small-world properties. The MAUD patients showed increased nodal efficiency and betweenness centrality in the right inferior occipital gyrus, left insular lobe, bilateral Heschl gyrus, and bilateral superior temporal gyrus, while the node attributes decreased in the right parahippocampal gyrus and right hippocampus compared to the HUD patients. The MAUD patients also showed reduced edge connectivity between left dorsolateral prefrontal cortex (dlPFC) and left middle occipital gyrus (MOG), as well as between bilateral orbitofrontal cortex (OFC) and bilateral superior occipital gyrus (SOG), left MOG, or right cuneus. In the MAUD group, the functional connection between left dlPFC and left MOG was negatively correlated with depression, while the connection between right cuneus lobe and right OFC was negatively correlated with depression and interpersonal sensitivity. These brain regions related to cognitive, emotional, and auditory/visual regulation may play an important role in the psychiatric symptoms of MAUD.

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.

Brain dysfunction of methamphetamine-associated psychosis in resting state: Approaching schizophrenia and critical role of right superior temporal deficit

Methamphetamine (MA)-associated psychosis (MAP) is highly debilitating and common among individuals who use the drug, yet the underlying neural mechanism is not clear. This study compared brain functions between patients with MAP and those with schizophrenia during resting state and investigated the effect of brain alteration on the association between MA use and psychosis in patients with MAP. Three groups, including 24 patients with MAP, 17 with schizophrenia in first-episode (SCZ) and 31 healthy controls (HCs), were included after receiving a resting-state functional MRI scan. The severity of psychosis was assessed with Positive and Negative Syndrome Scale (PANSS). Imaging data were analysed using regional homogeneity (ReHo) to measure individual's brain function. Compared with the HC subjects, the MAP and SCZ groups had significantly lower ReHo in the cortical regions including left postcentral cortex, right superior temporal gyrus and right rolandic operculum, while had higher ReHo in the left putamen, with brain dysfunctions being more pronounced in the SCZ group. Among the MAP subjects, a mediating effect of ReHo in the right superior temporal gyrus was found on the association between MA use frequency and PANSS positive score. MAP and schizophrenia had a common trend of brain alteration, with the dysfunction being more pronounced in schizophrenia. This finding implicated that MAP might be a condition with neuropathology approaching schizophrenia. The observed critical role of right superior temporal deficit between MA use and psychosis proposed a potential target for interventions.

The Effect of Crystal Dependence on Brain Activity Related to the Perception of Pleasure Using fMRI

Background: Addiction is currently one of the problems of human society. Drug abuse is one of the most important issues in the field of addiction. Methamphetamine (crystal) is one of the drugs that has been abused in recent decades. Methods: In this case-control study, 10 individuals aged 20 to 40 years old with at least 2 years of experience of methamphetamine consumption without any history of drug use or other stimulants from clients and drug withdrawal centers in Tehran City, and 10 healthy volunteers were selected. Age, social status, and economic status of addicts were included in the fMRI apparatus, and 90 selected pleasurable, non-pleasurable, and neutral images (IAPS) were displayed by the projector through an event-related method. The playback time of each photo was 3 s, and after this process, the person outside the device, without the time limit selected the enjoyable and unpleasant images. Results: The results showed that there was no significant difference between the groups in terms of age, alcohol use, and smoking history (P < 0.05). There was no significant difference in terms of the age at first use between members of the methamphetamine-dependent group. Also, the methamphetamine-dependent group showed more brain activity in their pre-center and post-center gyrus than the normal (control) group. Conclusions: According to the results obtained in this study, in general, it can be concluded that there are some areas in the brain of addicts that are activated when watching pleasant photos, while these areas are not active in the brains of normal people.

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.

The changes of brain functional networks in young adult smokers based on independent component analysis

Intrinsic functional connectivity (FC) networks, including the default mode network (DMN), central executive network (CEN), and salience network (SN), have been implicated in nicotine addiction. However, litter evidence exists about the abnormalities in the three networks in young adult smokers. Forty-eight young adult smokers and 49 age- and gender-matched non-smokers were recruited in the present study. Resting-state functional magnetic resonance imaging (fMRI) data were analyzed by a combination of independent component analysis (ICA) and dual regression to identify potential differences of FC patterns in the DMN, CEN, and SN. Compared to non-smokers, young adult smokers showed enhanced FC of the left posterior cingulate cortex (LPCC), right medial prefrontal cortex (RMPFC) and right precuneus within the DMN network, of the right dorsolateral prefrontal cortex (DLPFC) within the right CEN, and of the left anterior insula (LAI) within the SN. We also found increased FC between the DMN, CEN and key node of the SN (anterior insula, AI). Correlation analysis showed that the increased FC within the networks was significantly correlated with smoking behaviors (pack-years, smoking duration, FTND, first smoking age, and number of cigarettes per day). Our findings may provide additional evidence for conceptualizing the framework of nicotine addiction as a disease of intercommunicating brain networks.

Altered patterns of fractional amplitude of low-frequency fluctuation and regional homogeneity in abstinent methamphetamine-dependent users

Methamphetamine (MA) could induce functional and structural brain alterations in dependent subjects. However, few studies have investigated resting-state activity in methamphetamine-dependent subjects (MADs). We aimed to investigate alterations of brain activity during resting-state in MADs using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo). We analyzed fALFF and ReHo between MADs (n = 70) and healthy controls (HCs) (n = 84) and performed regression analysis using MA use variables. Compared to HCs, abstinent MADs showed increased fALFF and ReHo values in the bilateral striatum, decreased fALFF in the left inferior frontal gyrus, and decreased ReHo in the bilateral anterior cingulate cortex, sensorimotor cortex, and left precuneus. We also observed the fALFF values of bilateral striatum were positively correlated with the age of first MA use, and negatively correlated with the duration of MA use. The fALFF value of right striatum was also positively correlated with the duration of abstinence. The alterations of spontaneous cerebral activity in abstinent MADs may help us probe into the neurological pathophysiology underlying MA-related dysfunction and recovery. Since MADs with higher fALFF in the right striatum had shorter MA use and longer abstinence, the increased fALFF in the right striatum might implicate early recovery during abstinence.

Differences in the amplitude of low-frequency fluctuation between methamphetamine and heroin use disorder individuals: A resting-state fMRI study

INTRODUCTION

Methamphetamine has surpassed heroin as the most popular abused drug in China. Although the use of both heroin and methamphetamine leads to use disorders through dysfunction of the dopamine pathway, the incidence of psychiatric disorder caused by methamphetamine abuse is higher than the incidence of psychiatric disorder caused by heroin abuse. The difference in resting-state function between heroin use disorder (HUD) and methamphetamine use disorder (MAUD) and the relationship between resting-state function and psychiatric disorder related to MAUD are unknown.

METHODS

In the present study, 21 male individuals with MAUD, 21 demographically matched individuals with HUD, and 21 normal controls (NC) were recruited. The amplitude of low-frequency fluctuation (ALFF) during resting-state brain function was measured by magnetic resonance imaging. Psychiatric status was evaluated by the Symptom Checklist-90 (SCL90).

RESULTS

Individuals with MAUD had increased SCL90 scores compared to those of the NC for anxiety, paranoia, and additional items, and the hostility score was significantly increased compared to that of individuals with HUD. There is no significant difference between HUD and NC individuals. Individuals with MAUD had increased ALFF compared to those of the NC for thalamus, right postcentral, and right inferior temporal gyri, but a decreased ALFF in the cerebellum. Individuals with HUD had significantly increased ALFF compared to those of the NC for left middle frontal gyrus but a decreased ALFF in the left postcentral gyrus. Individuals with MAUD had significantly increased ALFF compared to those of the HUD for thalamus, the right inferior temporal, and bilateral postcentral gyri, and the ALFF of cerebellum and left middle frontal was significantly increased.

CONCLUSIONS

Methamphetamine can induce more serious psychiatric disorders than heroin. The resting-state function involved in mood adjustment, the auditory, and memory-related brain regions may affect psychotic symptoms related to MAUD.

Disrupted brain network dynamics and cognitive functions in methamphetamine use disorder: insights from EEG microstates

BACKGROUND

Dysfunction in brain network dynamics has been found to correlate with many psychiatric disorders. However, there is limited research regarding resting electroencephalogram (EEG) brain network and its association with cognitive process for patients with methamphetamine use disorder (MUD). This study aimed at using EEG microstate analysis to determine whether brain network dynamics in patients with MUD differ from those of healthy controls (HC).

METHODS

A total of 55 MUD patients and 27 matched healthy controls were included for analysis. The resting brain activity was recorded by 64-channel electroencephalography. EEG microstate parameters and intracerebral current sources of each EEG microstate were compared between the two groups. Generalized linear regression model was used to explore the correlation between significant microstates with drug history and cognitive functions.

RESULTS

MUD patients showed lower mean durations of the microstate classes A and B, and a higher global explained variance of the microstate class C. Besides, MUD patients presented with different current density power in microstates A, B, and C relative to the HC. The generalized linear model showed that MA use frequency is negatively correlated with the MMD of class A. Further, the generalized linear model showed that MA use frequency, scores of Two-back task, and the error rate of MA word are correlated with the MMD and GEV of class B, respectively.

CONCLUSIONS

Intracranial current source densities of resting EEG microstates are disrupted in MUD patients, hence causing temporal changes in microstate topographies, which are correlated with attention bias and history of drug use.

Brain networks underlying vulnerability and resilience to drug addiction

Resting-state functional connectivity provides novel insight into variations in neural networks associated with addiction to stimulant drugs in individuals with and without a family history of addiction, and both with and without personal drug use. An increased risk for addiction, either because of drug use or genetic/psychosocial vulnerability, is associated with hypoconnectivity in frontostriatal networks, which may weaken goal-directed decision-making. Resilience against addiction development, by contrast, is characterized by hyperconnectivity in two corticostriatal pathways, possibly reflecting compensatory responses in networks associated with regulatory control over habitual behaviors. It is thus conceivable that defying the risk of developing stimulant drug addiction requires increased efforts to control behavior—a hypothesis that may open up new pathways for therapeutic and preventative strategies.

Regular drug use can lead to addiction, but not everyone who takes drugs makes this transition. How exactly drugs of abuse interact with individual vulnerability is not fully understood, nor is it clear how individuals defy the risks associated with drugs or addiction vulnerability. We used resting-state functional MRI (fMRI) in 162 participants to characterize risk- and resilience-related changes in corticostriatal functional circuits in individuals exposed to stimulant drugs both with and without clinically diagnosed drug addiction, siblings of addicted individuals, and control volunteers. The likelihood of developing addiction, whether due to familial vulnerability or drug use, was associated with significant hypoconnectivity in orbitofrontal and ventromedial prefrontal cortical-striatal circuits—pathways critically implicated in goal-directed decision-making. By contrast, resilience against a diagnosis of substance use disorder was associated with hyperconnectivity in two networks involving 1) the lateral prefrontal cortex and medial caudate nucleus and 2) the supplementary motor area, superior medial frontal cortex, and putamen—brain circuits respectively implicated in top-down inhibitory control and the regulation of habits. These findings point toward a predisposing vulnerability in the causation of addiction, related to impaired goal-directed actions, as well as countervailing resilience systems implicated in behavioral regulation, and may inform novel strategies for therapeutic and preventative interventions.

A comparison of regional brain volumes and white matter connectivity in subjects with stimulant induced psychosis versus schizophrenia

RATIONALE

Schizophrenia and stimulant-induced psychosis (SIP) represent two different forms of psychotic disorder, with different etiologies. While many of the symptoms of psychosis are common to both disorders, there have been few direct comparisons between these conditions, especially when controlling for stimulant use in individuals with schizophrenia.

OBJECTIVES

We directly compared both psychotic disorders with a comprehensive battery of clinical, neurocognitive and neuroanatomical measures. This included one group with SIP (and concurrent stimulant dependence) and two groups with schizophrenia (either with or without concurrent stimulant dependence).

METHODS

Ninety-six participants were recruited from a marginalized urban population, which included 39 with SIP (and concurrent stimulant dependence), 18 with schizophrenia (without stimulant dependence), and 39 with schizophrenia (with concurrent stimulant dependence). All subjects had extensive clinical and neurocognitive evaluations, complemented with structural MRI including diffusion tensor imaging (DTI) sequences to determine regional brain volumes and white matter connectivity.

RESULTS

Both positive and negative symptoms were greater in the SZ-dependent group than the other two. Neurocognitive function was broadly similar. The structural brain imaging revealed lateralized changes to the left parietal/temporal lobe, in which regional volumes were smaller in the SZ-dependent than the SZ-non-dependent group. DTI analysis indicated extensive decreases in fractional anisotropy, with parallel increases in radial diffusivity, in the SIP group compared to the SZ-dependent group.

CONCLUSIONS

These findings reveal both similarities and differences between SIP and schizophrenia. Furthermore, schizophrenia with concurrent stimulant dependence may be associated with a different clinical and neuroanatomical profile as compared to schizophrenia alone.

Structural, functional, and neurochemical neuroimaging of methamphetamine-associated psychosis: A systematic review

Methamphetamine is a highly addictive psychostimulant. A subset of methamphetamine users develops methamphetamine-associated psychosis (MAP), which causes poorer prognoses and cognitive function than those with no psychosis (MNP). Comprehensive and integrative summaries of studies utilizing various neuroimaging modalities (structural, functional, and neurochemical) are limited. We conducted a systematic review of literature regarding clinical neuroimaging research published between January 1988 and July 2018 using the PubMed, Web of Science, Scopus, and ScienceDirect databases. Studies comparing the neuroimaging of patients with MAP with healthy controls or patients with MNP or schizophrenia were included to understand the distinct profiles associated with MAP. A total of six structural, three functional, and three neurochemical studies were reviewed. A general trend was identified that showed MAP-related brain alterations were mainly in the frontal lobe (especially the orbitofrontal cortex), striatum, and limbic systems (amygdala and hippocampus). Furthermore, some clinical manifestations, such as the severity of psychotic symptoms and cognitive performance, were correlated with neuroimaging abnormalities. In summary, distinct structural, functional, and neurochemical changes, especially in the frontostriatal circuit and network dynamic systems, play critical roles in the pathophysiology of MAP. Future studies using longitudinal study designs and including individuals with MNP and schizophrenia as controls are warranted.

Meta-analyses of the functional neural alterations in subjects with Internet gaming disorder: Similarities and differences across different paradigms

Internet gaming disorder (IGD) has become a global public health concern due to its increasing prevalence and potential negative consequences. Researchers have sought to identify which brain regions are associated with this disorder. However, inconsistent results have been reported among studies due to the heterogeneity of paradigms and subjects. The present research aimed to combine the results of individual studies to provide a more coherent and powerful explanation. By selecting 40 studies utilizing a qualified whole-brain analysis, we performed a comprehensive series of meta-analyses that employed seed-based d mapping. We divided the existing experimental paradigms into 3 categories: game-related cue-reactivity, executive control, and risk-reward-related decision-making tasks. We divided all studies into three subgroups according to their paradigms. In cue-reactivity tasks, patients with IGD exhibited significant hyperactivation in the bilateral precuneus and bilateral cingulate and significant hypoactivation in the insula, but there were no differences in the striatum. In executive control tasks, patients with IGD displayed significant hyperactivation in the right superior temporal gyrus, bilateral precuneus, bilateral cingulate, and insula and hypoactivation in the left inferior frontal gyrus. In risky decision-making paradigms, IGD patients exhibited significant hyperactivation in the left striatum, right inferior frontal gyrus, and insula and hypoactivation in the left superior frontal gyrus, left inferior frontal gyrus, and right precentral gyrus. Our study aimed to discover the similarities among all studies and to explore the uniqueness of the different paradigms. This study further confirmed the critical role of reward circuitry and executive control circuitry in IGD but not under all conditions.

Alterations in resting-state functional connectivity in substance use disorders and treatment implications

Substance use disorders (SUD) are diseases of the brain, characterized by aberrant functioning in the neural circuitry of the brain. Resting state functional connectivity (rsFC) can illuminate these functional changes by measuring the temporal coherence of low-frequency fluctuations of the blood oxygenation level-dependent magnetic resonance imaging signal in contiguous or non-contiguous regions of the brain. Because this data is easy to obtain and analyze, and therefore fairly inexpensive, it holds promise for defining biological treatment targets in SUD, which could help maximize the efficacy of existing clinical interventions and develop new ones. In an effort to identify the most likely "treatment targets" obtainable with rsFC we summarize existing research in SUD focused on 1) the relationships between rsFC and functionality within important psychological domains which are believed to underlie relapse vulnerability 2) changes in rsFC from satiety to deprived or abstinent states 3) baseline rsFC correlates of treatment outcome and 4) changes in rsFC induced by treatment interventions which improve clinical outcomes and reduce relapse risk. Converging evidence indicates that likely "treatment target" candidates, emerging consistently in all four sections, are reduced connectivity within executive control network (ECN) and between ECN and salience network (SN). Other potential treatment targets also show promise, but the literature is sparse and more research is needed. Future research directions include data-driven prediction analyses and rsFC analyses with longitudinal datasets that incorporate time since last use into analysis to account for drug withdrawal. Once the most reliable biological markers are identified, they can be used for treatment matching, during preliminary testing of new pharmacological compounds to establish clinical potential ("target engagement") prior to carrying out costly clinical trials, and for generating hypotheses for medication repurposing.

Effects of Naltrexone on Large-Scale Network Interactions in Methamphetamine Use Disorder

Naltrexone attenuates craving, and the subjective effects of methamphetamine and extended-release naltrexone (XR-NTX) reduces functional connectivity between regions of the striatum and limbic cortex. Naltrexone modulates neural activity at dopaminergic synapses; however, it is unclear whether naltrexone has an effect on large-scale brain networks. Functional networks interact to coordinate behavior, and as substance-use disorders are associated with an imbalance between reward and cognitive control networks, treatment approaches that target interactive brain systems underlying addiction may be a useful adjunct for behavioral therapies. The objective of this study was to examine the effect of XR-NTX on large-scale brain networks and to determine whether changes in network relationships attenuate drug use, craving, and addiction severity. Thirty-nine participants in or seeking treatment for methamphetamine-use disorder were enrolled in a clinical trial of XR-NTX between May 2013 and March 2015 (Clinicaltrials.gov NCT01822132). Functional magnetic resonance imaging (fMRI) and questionnaires were conducted before and after double-blinded randomization to a 4-week injection of XR-NTX or placebo. In the XR-NTX group, methamphetamine use was reduced along with a decrease in the coupling between executive control (ECN) and default mode (DMN) networks. As decoupling of ECN and DMN networks was associated with change in the severity of dependence, the results suggest that XR-NTX may modulate and enhance ECN attentional resources and suppress DMN self-referential and emotional processing. This study identifies the effect of naltrexone on changes in the intrinsic functional coupling of large-scale brain networks and provides a more systematic understanding of how large-scale networks interact to promote behavioral change in methamphetamine-use disorder.

Changes in Gray Matter Density, Regional Homogeneity, and Functional Connectivity in Methamphetamine-Associated Psychosis: A Resting-State Functional Magnetic Resonance Imaging (fMRI) Study

Background

Using regional homogeneity (ReHo) blood oxygen level-dependent functional MR (BOLD-fMRI), we investigated the structural and functional alterations of brain regions among patients with methamphetamine-associated psychosis (MAP).

Material/Methods

This retrospective study included 17 MAP patients, 16 schizophrenia (SCZ) patients, and 18 healthy controls. Informed consent was obtained from all patients before the clinical assessment, the severity of clinical symptoms was evaluated prior to the fMRI scanning, and then images were acquired and preprocessed after each participant received 6-min fRMI scanning. The participants all underwent BOLD-fMRI scanning. Voxel-based morphometry was used to measure gray matter density (GMD). Resting-state fMRI (rs-fMRI) was conducted to analyze functional MR, ReHo, and functional connectivity (FC).

Results

GMD analysis results suggest that MAP patients, SCZ patients, and healthy volunteers show different GMDs within different brain regions. Similarly, the ReHo analysis results suggest that MAP patients, SCZ patients, and healthy volunteers have different GMDs within different brain regions. Negative correlations were found between ReHo- and the PANSS-positive scores within the left orbital interior frontal gyrus (L-orb-IFG) of MAP patients. ReHo- and PANSS-negative scores of R-SFG were negatively correlated among SCZ patients. The abnormal FC of R-MFG showed a negative correlation with the PANSS score among MAP patients.

Conclusions

The abnormalities in brain structure and FC were associated with the development of MAP.

The relationship between interleukin-6 and functional connectivity in methamphetamine users

Methamphetamine (MA) causes an increase in pro-inflammatory cytokines in animal models and in humans. Resulting activation of microglia and neuro-inflammation could, via effects on reward networks, mediate behavioral characteristics of addiction. We examined the relationship between interleukin-6 (IL-6) and corticolimbic and striatolimbic resting-state functional connectivity (RSFC). Thirty adults diagnosed with MA dependence and 20 control subjects underwent a resting-state functional magnetic resonance imaging (fMRI) scan and gave a blood sample for determination of plasma IL-6 levels. Seed-based RSFC analyses were performed to examine the interactive effect of group and IL-6 on ventral striatal and prefrontal connectivity. Within the MA group, IL-6 levels were positively related to striatolimbic RSFC but negatively related to corticostriatal RSFC. Our findings with IL-6 support the idea that inflammation may at least partly mediate the link among MA use disorder, RSFC, and behavior, possibly via effects on mesolimbic and mesocortical dopaminergic systems.