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

BackgroundCue-induced craving is widely considered to be the most important risk factor for relapse during abstinence from methamphetamine (Meth). There is limited research regarding electroencephalography (EEG) microstates of Meth-dependent patients under exposure to drug-related cues. Our objective was to investigate whether EEG microstate temporal characteristics could capture neural correlates of cue-induced Meth craving in virtual reality (VR) environments.MethodsEEG recordings of 35 Meth-dependent patients and 30 healthy controls (HCs) were collected during eyes-open state and cue-induced state, respectively. Group differences and condition differences in temporal parameters of four microstate classes were compared.ResultsThe results demonstrated the greater presence of microstate B in both Meth-dependent patients and HCs during the cue-induced condition, compared to resting state. In addition, for Meth-dependent patients, microstate C occurred significantly less frequently, along with a tendency of increased occurrence for class D during the cue-induced condition, compared to resting state. However, the change direction of class C and class D in HCs was completely opposite to that of Meth-dependent patients. The cue-induced condition also elicited different changes in transition probability between Meth-dependent patients and HCs.ConclusionThis study explored the features of EEG microstates in Meth-dependent patients during the cue-induced condition, which can improve our understanding of Meth addiction and contribute to the development of effective assessments and intervention tools.

Section: Discussioncontrasting

confidence: 92%

Altered EEG Microstates Dynamics During Cue-Induced Methamphetamine Craving in Virtual Reality Environments

Lin

Cheng³

et al. 2022

“…For example, the risk of relapse may increase after stimulation by drug-related cues. One alternative approach has been recorded, brain signals when participants are involved in cognitive tasks, to differentiate those suffering from an addiction from healthy controls (32); for example, in one study, EEG signals were analyzed when patients with METH addiction performed cognitive tasks, including the N-back task to assess working memory and Stroop task to assess attention (102).…”

Section: Stimulation Cuesmentioning

confidence: 99%

“…Other EEG biomarkers represented by topography include EEG microstates that show the spatial distribution of electrical signals recorded by the electrodes over the scalp (102,118). The dynamic changes of these electric potential states can be validated by examining a consecutive set of topographies.…”

Section: Biomarkers Of Eeg and Fnirs In Meth Addictionmentioning

confidence: 99%

Challenges and future trends in wearable closed-loop neuromodulation to efficiently treat methamphetamine addiction

Chen

Yang

et al. 2023

Achieving abstinence from drugs is a long journey and can be particularly challenging in the case of methamphetamine, which has a higher relapse rate than other drugs. Therefore, real-time monitoring of patients’ physiological conditions before and when cravings arise to reduce the chance of relapse might help to improve clinical outcomes. Conventional treatments, such as behavior therapy and peer support, often cannot provide timely intervention, reducing the efficiency of these therapies. To more effectively treat methamphetamine addiction in real-time, we propose an intelligent closed-loop transcranial magnetic stimulation (TMS) neuromodulation system based on multimodal electroencephalogram–functional near-infrared spectroscopy (EEG-fNIRS) measurements. This review summarizes the essential modules required for a wearable system to treat addiction efficiently. First, the advantages of neuroimaging over conventional techniques such as analysis of sweat, saliva, or urine for addiction detection are discussed. The knowledge to implement wearable, compact, and user-friendly closed-loop systems with EEG and fNIRS are reviewed. The features of EEG and fNIRS signals in patients with methamphetamine use disorder are summarized. EEG biomarkers are categorized into frequency and time domain and topography-related parameters, whereas for fNIRS, hemoglobin concentration variation and functional connectivity of cortices are described. Following this, the applications of two commonly used neuromodulation technologies, transcranial direct current stimulation and TMS, in patients with methamphetamine use disorder are introduced. The challenges of implementing intelligent closed-loop TMS modulation based on multimodal EEG-fNIRS are summarized, followed by a discussion of potential research directions and the promising future of this approach, including potential applications to other substance use disorders.

“…In recent years, EEG microstate analysis has been used in patients with mental disorder, such as bipolar disorder (26), methamphetamine use disorder (27), schizophrenia (28), and depression (21,22). Different psychopathological conditions showed different EEG microstate feature changes.…”

Section: Introductionmentioning

confidence: 99%

Abnormalities in Electroencephalographic Microstates Among Adolescents With First Episode Major Depressive Disorder

Yang

Zhang

et al. 2021

Background: Recent studies have reported changes in the electroencephalograms (EEG) of patients with major depressive disorder (MDD). However, little research has explored EEG differences between adolescents with MDD and healthy controls, particularly EEG microstates differences. The aim of the current study was to characterize EEG microstate activity in adolescents with MDD and healthy controls (HCs).Methods: A total of 35 adolescents with MDD and 35 HCs were recruited in this study. The depressive symptoms were assessed by Hamilton Depression Scale (HAMD) and Children's Depression Inventory (CDI), and the anxiety symptoms were assessed by Chinese version of DSM-5 Level 2-Anxiety-Child scale. A 64-channel EEG was recorded for 5 min (eye closed, resting-state) and analyzed using microstate analysis. Microstate properties were compared between groups and correlated with patients' depression scores.Results: We found increased occurrence and contribution of microstate B in MDD patients compared to HCs, and decreased occurrence and contribution of microstate D in MDD patients compared to HCs. While no significant correlation between depression severity (HAMD score) and the microstate metrics (occurrence and contribution of microstate B and D) differing between MDD adolescents and HCs was found.Conclusions: Adolescents with MDD showed microstate B and microstate D changes. The obtained results may deepen our understanding of dynamic EEG changes among adolescents with MDD and provide some evidence of changes in brain development in adolescents with MDD.