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Brain Commun. 2025 Oct 29;7(5):fcaf343. doi: 10.1093/braincomms/fcaf343. eCollection 2025.

ABSTRACT

The treatment of chronic pain represents a widespread clinical challenge. Current approaches to network-based mapping of the cerebral cortex have the potential to localize chronic pain in the brain. In an effort to further characterize the dynamical brain networks, or the 'dynome' in the setting of chronic pain, we performed a Coordinate-Based Meta-Analysis of resting-state functional Magnetic Resonance Imaging studies on chronic pain to create a multinetwork dynome of chronic pain. A cluster-level analysis generated seven statistically significant activation likelihood estimates (ALEs): one for chronic pain as a whole dynome, three for chronic pain conditions, and three for chronic pain mechanisms. Chronic pain is a complex disease process involving tripartite network dysfunction encompassing the Default Mode Network, Central Executive Network and Salience Network. Chronic visceral pain was distinct from chronic headache and chronic musculoskeletal pain, and chronic pain mechanisms have the potential to share common cortical network rearrangements with their respective chronic pain conditions. Collectively, this work represents the first anatomically specific network-based cortical map of chronic pain, with representation of disease-specific and mechanism-specific disruptions in cortical function.

PMID:41169268 | PMC:PMC12569763 | DOI:10.1093/braincomms/fcaf343

BMC Psychiatry. 2025 Oct 30;25(1):1040. doi: 10.1186/s12888-025-07483-y.

ABSTRACT

BACKGROUND: Suicide thoughts and behaviors (STB), including suicidal ideation (SI) and suicide attempts (SA), are significant concerns in major depressive disorder (MDD), yet their neurobiological mechanisms remain poorly understood. This study aims to identify key regional brain activity and connectivity abnormalities associated with STB in MDD by combining a meta-analysis of regional brain activity comparing MDD patients with STB to non-STB controls (both MDD without STB and healthy controls) and an exploratory functional connectivity (FC) analysis in an independent sample of MDD patients.

METHODS: A meta-analysis employing Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software identified regional brain abnormalities. Studies included were those comparing MDD patients with STB to non-STB controls, employing resting-state fMRI with whole-brain analyses, using ALFF, fALFF, and ReHo metrics. The identified abnormal brain regions were used as regions of interest (ROIs) for FC analyses in 57 first-episode, drug-naive MDD patients.

RESULTS: The meta-analysis included 12 studies (13 datasets) comprising 555 MDD patients with STB and 430 non-STB controls. Compared to non-STB controls, MDD-STB patients showed increased activity in the right middle occipital gyrus (MOG) and right inferior frontal gyrus, triangular part (IFGtriang), while decreased activity in right precuneus. Subgroup analysis of SA revealed increased activity in the left angular gyrus in MDD patients with SA, compared to non-SA controls. SI subgroup analysis and two medication status subgroup analyses showed no significant results. In independent sample, FC analysis yielded two significant FCs after Bonferroni correction. Correlation analysis showed a negative association between right MOG-IFGtriang FC and most severe SI scores measured by the Beck Scale for Suicidal Ideation (P = 0.04), though it was non-significant after correction.

CONCLUSIONS: These findings provide novel insights into the neural mechanisms of STB in MDD, identifying specific brain regions and FC patterns associated with STB. These results align with prior studies, highlighting the role of visual processing and cognitive control regions in STB. By combining a meta-analysis of regional abnormalities with an exploratory FC analysis, this study offers a comprehensive understanding of the brain networks implicated in STB and suggests potential targets for future interventions.

PMID:41168736 | DOI:10.1186/s12888-025-07483-y

Nat Commun. 2025 Oct 30;16(1):9359. doi: 10.1038/s41467-025-64988-6.

ABSTRACT

The microbiome-gut-brain-axis plays a critical role in mental health. However, research linking the microbiome to brain function is limited, particularly during development, when tremendous plasticity occurs and many mental health issues, like depression and anxiety, initially manifest. Further complicating attempts to understand interactions between the brain and microbiome is the complex and multidimensional nature of both systems. In the current observational study (N = 55), we use sparse partial least squares to identify linear combinations of brain networks (brain signatures) derived from resting state fMRI scans at age 6 years that maximally covary with internalizing symptoms at age 7.5 years, before identifying microbe abundances (microbial profiles) derived from 16S rRNA sequencing of stool samples at age 2 years that maximally covary with those brain signatures. Finally, we test whether any early microbial profiles are indirectly associated with later internalizing symptoms via the brain signatures, highlighting potential microbial programming effects. We find that microbes in the Clostridiales order and Lachnospiraceae family are associated with internalizing symptoms in middle childhood through connectivity alterations within emotion-related brain networks.

PMID:41168153 | DOI:10.1038/s41467-025-64988-6