PubMed HealthSearch

PubMed · 42561566

Brain network alterations underlying cue reactivity and craving in abstinent methamphetamine users: a systematic review of functional MRI findings.

Abstract

BACKGROUND: Methamphetamine use disorder (MUD) is marked by intense craving and high relapse risk, often triggered by drug-related cues. Functional magnetic resonance imaging (fMRI) provides key insight into the neural basis of this cue reactivity, implicating large-scale brain networks for reward, motivation, and control. Yet, findings remain inconsistent across studies due to differences in task design, abstinence duration, and participant characteristics. OBJECTIVE: This systematic review synthesises evidence on how abstinence influences brain network alterations underlying cue reactivity and craving in methamphetamine users, integrating task-based and resting-state fMRI findings within leading neurobiological models of addiction. METHODS: A systematic search of PubMed, Scopus, Web of Science, and Ovid was conducted up to August 10, 2025, following PRISMA 2020 guidelines. Eligible fMRI studies examined cue reactivity or craving in abstinent methamphetamine users. Data were extracted on activation, connectivity, and brain-behaviour associations, and synthesised narratively. RESULTS: Task-based studies revealed heightened activation across reward, salience, and control networks during cue exposure, which diminished as parietal and executive control systems re-engaged with longer abstinence. Resting-state findings showed disrupted intrinsic connectivity among default mode, salience, and frontoparietal networks, reflecting persistent imbalances linked to craving and use severity. CONCLUSION: fMRI evidence shows that MUD is marked by network-level disruption linking reward, salience, and control systems. Task-based findings reveal strong cue reactivity in reward circuits, while resting-state data show persistent imbalance among default mode and control networks. With abstinence, partial restoration of network integrity emerges, highlighting both vulnerability and opportunities for targeted, recovery-based interventions.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Vaenusha Murugan, Yasmin Aishah Mohamad Hisham, Reshiika Poorvi, Isa Naina Mohamed, Rashidi Pakri Mohamed Pakri, Hanani Abdul Manan, Ching Soong Khoo, Jaya Kumar. 2026-08-03. Brain network alterations underlying cue reactivity and craving in abstinent methamphetamine users: a systematic review of functional MRI findings.. https://doi.org/10.1016/j.addbeh.2026.108825

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans