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PubMed2026

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

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.

Humans↗

PubMed2026

Acupuncture improves depressive symptoms and prefrontal cortical function in mild to moderate depressive disorder: A randomized sham-controlled trial and fNIRS study.

BACKGROUND: Depressive disorder is a common mental illness associated with substantial functional impairment. Although pharmacotherapy is widely used, its effectiveness is often limited by adverse effects and poor adherence. Acupuncture has been increasingly applied as a complementary treatment for depression, and its neurobiological characteristics remain unclear. OBJECTIVE: This randomized, sham-controlled trial aimed to evaluate the clinical efficacy of acupuncture for mild to moderate depressive disorder and to investigate its effects on prefrontal cortical function using functional near-infrared spectroscopy (fNIRS). METHODS: Patients with mild to moderate depressive disorder were randomly assigned to a real acupuncture (RA) group or a sham acupuncture (SA) group and received standardized treatment for 8 weeks. Clinical outcomes were assessed using the Self-Rating Depression Scale (SDS), Self-Rating Anxiety Scale (SAS), Short Form-36 Health Survey (SF-36), and a traditional Chinese medicine syndrome score. A subset of participants underwent fNIRS assessment during resting-state and task-based conditions to evaluate prefrontal cortical activation and functional connectivity. RESULTS: Compared with baseline, the RA group showed significant reductions in SDS and SAS scores and significant improvements in SF-36 emotional domains, with effects emerging at Week 4 and persisting up to 12 weeks after treatment. Improvements were greater and more stable in the RA group than in the SA group. fNIRS analyses revealed enhanced activation in dorsolateral and medial prefrontal regions and strengthened prefrontal functional connectivity following acupuncture, whereas neural changes in the SA group were limited. CONCLUSION: Acupuncture is effective for improving depressive and anxiety symptoms and quality of life in patients with mild to moderate depressive disorder. Modulation of prefrontal cortical activation and connectivity may underlie its antidepressant effects.

Humans↗

PubMed2026

Targeting cortico-striatal-amygdalar networks via theta-band frontoparietal synchronization in opioid use disorder: a randomized tACS-fMRI Trial.

Theta-band oscillation is integral to fronto-parietal connectivity in the executive control network and its top-down regulation on subcortical areas. External frontoparietal synchronization using theta-frequency transcranial alternating current (tACS) is a technology to potentially engage this network. In this pre-registered, triple-blind, sham-controlled trial (NCT03907644), we tested this intervention targeting the right frontoparietal network in people with opioid use disorder (OUD) to measure network engagement and behavioral outcomes. Sixty male participants with OUD were randomized to receive 20 min of active or sham 6 Hz tACS (HD electrodes over F4 and P4). Structural, resting-state, task-based fMRI drug cue reactivity, and repeated cue-induced craving assessments were collected immediately before and after stimulation. Pre-registered outcome measures were analyzed using time × group interaction models to examine (1) modulation of drug cue-related brain activity, (2) changes in craving, (3) alterations in functional connectivity, and (4) relationship between electric field, neural responses, and craving behavior. (1) A significant Time × Group interaction revealed decreased post-stimulation opioid cue-related activity in the active group relative to sham, involving key nodes in reward processing (ventral striatum, amygdala and ventral tegmental area) (FWE corrected α = 0.05) (2) subjective craving did not differ significantly between groups (3) Group by time generalized psychophysiological interaction analyses showed increased right frontoparietal network engagement (β = 2.63, p= 0.0308) following stimulation, and increased top-down inhibitory regulation of frontoparietal network on right ventral striatum (β = 1.99, p= 0.037) and left medial amygdala (β = 1.97, p= 0.039) (4) Electric field strength in the right frontal/parietal node predicted frontoparietal network engagement in the active group (r = 0.43, p= 0.02). Together, these findings demonstrate that theta-band frontoparietal tACS can modulate activity and task-dependent coupling within cortical-subcortical circuits in OUD, supporting network-targeted neuromodulation as a potential intervention for addiction.

Humans↗

PubMed2026

Genetic Correlation Between Brain Imaging Phenotypes and Externalizing Behavior: A Large-Scale LDSC Analysis of UK Biobank IDPs.

Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing genome-wide association study (GWAS) results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. The imaging phenotypes covered structural magnetic resonance imaging (MRI), diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task-based functional MRI. Results were included in the primary analysis when the imaging phenotype had positive single-nucleotide polymorphism (SNP) heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests (ACATs) were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Statistical power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of the 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were classified as biological imaging phenotypes. No individual phenotype survived false discovery rate correction. The smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute genetic correlation of 0.0338. ACAT provided no evidence of an aggregate association across all biological imaging phenotypes (P = 0.302), and no predefined imaging category survived multiple-testing correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were fully contained within the interval [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under the stringent heritability quality-control definition. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of genome-wide genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Nevertheless, small, localized, mixed-direction, or developmentally specific genetic effects remain possible.

Journal Article↗