Aberrant Resting-State Cerebellar-Cerebral Functional Connectivity in Methamphetamine-Dependent Individuals After Six Months Abstinence

Li, Xiaotong; Su, Hang; Zhong, Na; Chen, Tianzhen; Du, Jing; Ke, Xiao; Xu, Ding; Song, Weidong; Jiang, Haifeng; Zhao, Min

doi:10.3389/fpsyt.2020.00191

Cited by 14 publications

(5 citation statements)

References 61 publications

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“…More importantly, although altered FC correlates with DMN activation in MAs after six months of abstinence, 32 our study confirmed DMN function is impaired in MAs with less than six months of abstinence. Taken together, the alterations in the DMN in short-term MAs may imply disrupted self-awareness and self-related decision-making.…”

Section: Discussionsupporting

confidence: 69%

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

Gong¹,

Shen²,

Liang³

et al. 2022

IJGM

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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.

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Section: Discussionsupporting

confidence: 69%

“…After six months of abstinence, MAs exhibited disrupted FC between the cerebellum and DMN. 32 Our findings further demonstrated decreased DMN-CN FC in short-term MAs, implying that impaired DMN-CN connectivity is characteristic of marked damage.…”

Section: Discussionsupporting

confidence: 69%

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

Gong¹,

Shen²,

Liang³

et al. 2022

IJGM

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show abstract

“…McKetin et al (2008) observed that methamphetamine is sometimes mixed with other drugs and sold as "ecstasy. Li X et al (2020) held that methamphetamine-dependent individuals show disrupted functional connectivity between the cerebellum and several cerebral functional networks compared to healthy controls, including default mode, affective-limbic, and sensorimotor networks. It also has socio-economic and legal consequences (Barman-Adhikari et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Church's Response to Methamphetamine (Mkpuru-Mmiri) Abuse Among Young People in Southeast Nigeria

Nnaemedo,

Nwoko,

Nwaugo

2023

IJEHSS

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This study aimed at the Catholic Church's response to methamphetamine abuse by young people in Southeast Nigeria. Methamphetamine is an amphetamine-type stimulant (ATS). This class of drugs excites or speeds up the nervous system and produces effects similar to adrenaline. The Igbo Language renders it as mkpurumiri (seed of water). Presently methamphetamine is a drug primarily abused in the Southeast zone. There is not yet a definite effort to study the phenomenon in-depth to know its remedial measures. Such is the reason for this investigation. It employs a selfconstructed questionnaire as a data-collecting instrument, and the theoretical framework is the integrative model. The study population is 21,955,414, and the sample size is 386. The finding showed that Catholic Church responds to methamphetamine abuse among young people through Christian counselling, prayers, awareness campaign, conferences, seminars, rehabilitation, care, and collaboration with the government. The study recommends the establishment of more clinics for the victims and synergising with others concerned the drug abuse in the zone.

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“…In this approach, differences in neural function can be identified by measuring the connectivity from the BOLD time series between the various regions of the brain. By using rs-fMRI data, previous studies examined the effects of MA on the functional connectivity (FC) of the brain and discovered significant differences that may be related to some of the core symptoms observed in MA addicts (Kohno et al, 2014 ; Dean et al, 2015 ; Zhang et al, 2018 ; Li et al, 2020 ). Although these findings provide new insights into the neural features of MA addiction, the great majority of these research are based on explanatory models and the generalizability of the results remains unclear.…”

Section: Introductionmentioning

confidence: 99%

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

Zhou

Sun²,

Yang³

et al. 2022

Front. Cell. Neurosci.

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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.

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Aberrant Resting-State Cerebellar-Cerebral Functional Connectivity in Methamphetamine-Dependent Individuals After Six Months Abstinence

Cited by 14 publications

References 61 publications

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

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

Church's Response to Methamphetamine (Mkpuru-Mmiri) Abuse Among Young People in Southeast Nigeria

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

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