Most recent paper

Front Psychiatry. 2026 Jul 30;17:1903951. doi: 10.3389/fpsyt.2026.1903951. eCollection 2026.

ABSTRACT

BACKGROUND: Internet addiction (IA) has emerged as a pervasive public health issue among young adults, frequently accompanied by severe emotion regulation difficulties. However, the precise static and dynamic functional architecture of the hippocampus and its interplay with emotion dysregulation in IA remain incompletely understood.

METHODS: This study enrolled 45 young adults with IA and 29 healthy controls (HC). Utilizing resting-state functional magnetic resonance imaging (fMRI), we computed both static functional connectivity (sFC) and dynamic functional connectivity (dFC) seeded from the rostral hippocampus. Partial correlation analyses were conducted to examine the associations between aberrant connectivity and clinical symptoms. Furthermore, we investigated whether emotion dysregulation mediates the relationship between altered hippocampal connectivity and internet addiction severity.

RESULTS: Compared to HCs, individuals with IA exhibited significantly increased sFC between the left rostral hippocampus and nodes of the default mode network (DMN; precuneus and inferior parietal lobule). Furthermore, the IA group displayed heightened temporal variability between the bilateral hippocampus and visual-temporal regions (superior temporal pole, lingual gyrus, middle, and superior occipital gyri). These aberrant sFC and dFC were significantly and positively correlated with IA severity and emotion regulation difficulties. Mediation analyses further revealed that emotion dysregulation significantly and partially mediated the relationship between altered hippocampal connectivity and internet addiction severity.

CONCLUSIONS: Static hyper-connectivity with the DMN and dynamic instability with visual-temporal networks constitute distinct neurobiological signatures of IA. Crucially, emotion dysregulation bridges these hippocampal network anomalies with addictive behaviors, highlighting targeted emotion regulation interventions as a promising therapeutic strategy for internet addiction.

PMID:42597244 | PMC:PMC13467981 | DOI:10.3389/fpsyt.2026.1903951

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Aug 13:111890. doi: 10.1016/j.pnpbp.2026.111890. Online ahead of print.

ABSTRACT

Electroconvulsive therapy (ECT) is an effective treatment for major depressive disorder (MDD), yet its underlying mechanisms remain unclear. This study investigated the antidepressant effects of ECT through a multimodal neuroimage meta-analysis combined with functional, genetic, and neurotransmitter assessments. Resting-state functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) data were analyzed using seed-based d mapping with permutation of subject images (SDM-PSI) to identify changes in spontaneous brain activity and gray matter volume (GMV) before and after ECT. Further analysis of regions with altered activation and GMV was conducted using Neurosynth, postmortem gene expression data, and receptor/transporter distribution maps to explore molecular underpinnings. The whole-brain multimodal meta-analysis included 291 patients from resting-state fMRI studies and 302 patients from VBM studies. The results showed convergent increases in spontaneous activity and GMV in the left angular gyrus (AG) following ECT. Functional annotation linked the left AG to memory, attention, and perceptual processing. Gene expression analysis identified TFAP2B and OTX2 as the most highly expressed genes in this region. Notably, ECT-associated changes in spontaneous brain activity and GMV were positively correlated with 5-HT1a receptor and dopamine transporter distribution. These findings suggest the left AG is a key region mediating ECT's effects. Neurotransmitter analysis further indicates that ECT may exert its antidepressant action by modulating neurotransmitter systems, offering insights into the neural and molecular basis of its therapeutic efficacy in MDD.

PMID:42595040 | DOI:10.1016/j.pnpbp.2026.111890

Exp Gerontol. 2026 Aug 13:113285. doi: 10.1016/j.exger.2026.113285. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by large-scale network disruption. While static functional connectivity (sFC) has been extensively studied, dynamic functional connectivity (dFC) and its discriminative value across the AD spectrum remain insufficiently understood. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) data from 174 participants in the Alzheimer's Disease Neuroimaging Initiative, including cognitively normal (CN, n = 44), subjective memory concern (SMC, n = 24), early mild cognitive impairment (EMCI, n = 46), late MCI (LMCI, n = 30), and AD (n = 30), were analyzed to assess group differences in sFC, dFC, and graph-theoretical metrics, as well as their associations with cognition. A BrainNetCNN model was further employed to evaluate the classification performance of sFC, dFC, and their combined features. The results revealed that sFC decreased across MCI stages but increased in AD, whereas dFC variability was predominantly reduced in the pre-dementia groups and increased in AD, particularly in frontal and temporal regions. Several static graph-theoretical metrics were significantly correlated with Mini-Mental State Examination (MMSE) scores, while dFC provided complementary information. In classification tasks, dFC showed higher accuracy than sFC in binary and five-class tasks, and their integration achieved the highest accuracy (CN vs. SMC: 89.6%; five-class: 82.7%). These findings suggest that dFC may provide complementary imaging information for characterizing stage-related network alterations and differentiating diagnostic groups across the AD spectrum.

PMID:42595023 | DOI:10.1016/j.exger.2026.113285

J Am Acad Child Adolesc Psychiatry. 2026 Aug 13:S0890-8567(26)01569-8. doi: 10.1016/j.jaac.2026.08.003. Online ahead of print.

ABSTRACT

OBJECTIVE: Sensory over-responsivity (SOR), characterized by strong negative reactions to typically innocuous stimuli, is considered a symptom of autism spectrum disorder. However, SOR also affects 15-20% of children overall, including a majority of children with common psychiatric conditions. Despite its prevalence, the clinical specificity and neurobiological bases of SOR remain poorly understood. Our study aims to determine the specific clinical significance of SOR across diverse child samples and establish whether SOR is associated with replicable patterns of functional connectivity (FC).

METHOD: We analyzed data from 15,728 children (ages 6-17.9 years) across five datasets: three community samples, including the Adolescent Brain Cognitive Development [ABCD] and Healthy Brain Network [HBN] studies, and two autism-enriched samples. Bivariate and multivariate models examined associations between SOR and symptoms of anxiety, attention-deficit/hyperactivity disorder, depression, conduct disorder, and oppositional defiant disorder, as well as autistic traits. Analysis of resting-state functional MRI (fMRI) data from the ABCD study (n=4195) identified candidate brain-wide and circuit-specific FC correlates of mild SOR and tested replication of effects in an independent ABCD subsample (n=4190). Additional analyses tested extension to children with severe SOR in ABCD and replication in smaller samples [HBN (n=356), ABCD subset (n=356)].

RESULTS: Multivariate analyses revealed that SOR is associated with a remarkably consistent profile across samples: greater levels of both autistic traits and anxiety symptoms and, in community samples, lower levels of conduct disorder symptoms. Across samples, SOR is not reliably associated with symptoms of any other analyzed psychiatric conditions. Mild SOR is associated with brain-wide FC patterns and, specifically, reduced FC between cingulo-parietal network and bilateral caudate nucleus; these patterns show robust replication across independent ABCD subsamples and extension to severe SOR in ABCD but are not significant in smaller samples, indicating that large sample size is needed to reliably detect brain effects.

CONCLUSION: Results suggest that SOR may constitute a latent trait associated with both specific clinical risk and protection, and with replicable cortico-subcortical neural correlates. These findings advance our understanding of the neurobiology and clinical relevance of SOR. They may also inform clinical practice and future research aimed at understanding and supporting individuals with sensory challenges.

DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way.

PMID:42595007 | DOI:10.1016/j.jaac.2026.08.003

CNS Neurosci Ther. 2026 Aug;32(8):e71083. doi: 10.1002/cns.71083.

ABSTRACT

BACKGROUND: Identifying neuroimaging correlates of insomnia severity could provide insights into the underlying biological mechanisms of major depressive disorder (MDD). However, related findings remain inconsistent, and the functional connectivity patterns associated with insomnia severity are unclear.

METHODS: This study analyzed resting-state fMRI data from 385 patients with MDD and 336 healthy controls (HCs) sourced from nine sites of the DIRECT Consortium. Patients were stratified into high insomnia (MDDHI; HAMD insomnia subscale ≥ 4, n = 226) and low insomnia (MDDLI; HAMD insomnia subscale ≤ 3, n = 159) groups. Among patients with MDDHI, MDDLI and HCs, we first examined network-level functional connectivity abnormalities using the Craddock 200 atlas, and then local brain function was assessed using the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo) and degree centrality (DC). Finally, we adopted multiple analytical approaches to verify the robustness of the significant findings.

RESULTS: Compared to both patients with MDDHI and HCs, patients with MDDLI exhibited significantly reduced functional connectivity between the left angular gyrus (AG) and the right middle frontal gyrus (MFG). Both patients with MDDHI and MDDLI showed significantly decreased ALFF and ReHo values relative to HCs across multiple brain regions, including bilateral angular gyrus/precuneus/cerebellum posterior lobe and so on. For DC, patients with MDDHI showed significantly decreased values relative to HCs in all identified clusters, whereas patients with MDDLI showed significant DC reductions in a subset of these clusters. When these results were validated using multiple analytical approaches, the primary findings remained consistent.

CONCLUSIONS: Reduced functional connectivity between the left AG and the right MFG may be a candidate neuroimaging marker for sleep-related heterogeneity in MDD. However, widespread local brain function abnormalities may reflect core depressive pathology of MDD. These findings advance our understanding of the neurobiology of MDD.

PMID:42593839 | DOI:10.1002/cns.71083

Front Bioinform. 2026 Jul 29;6:1902380. doi: 10.3389/fbinf.2026.1902380. eCollection 2026.

ABSTRACT

INTRODUCTION: Large-scale multi-site magnetic resonance imaging (MRI) improves population coverage and statistical power, but scanner- and protocol-related variability can obscure biological effects. Most harmonization methods aim to reduce site-related variance for downstream analysis, whereas less attention has been paid to where site effects are spatially expressed, whether they are reproducible across site compositions, and which acquisition parameters contribute to them.

METHODS: We developed a modality-wise Linked Independent Component Analysis (LICA) framework to identify and interpret site-effect patterns in structural and resting-state functional MRI. Grey matter (GM) volume, amplitude of low-frequency fluctuation (ALFF), and regional homogeneity (ReHo) maps were analyzed separately. For each imaging measure, LICA decomposed voxel-wise maps into spatial components and subject-level loadings. Components were classified according to their associations with site labels and biological covariates, their spatial reproducibility was assessed using stepwise site-inclusion analyses, and their technical attribution was evaluated using cross-validated models based on site labels and recorded acquisition parameters. The framework was applied to ABIDE II GM maps from 913 participants across 18 sites and ALFF and ReHo maps from 795 participants across 16 sites.

RESULTS: LICA identified site-related components across all three imaging measures. Site effects were not limited to uniform global shifts, but formed modality-specific spatial patterns. GM volume showed a dominant and highly stable whole-brain site-effect pattern, together with site-specific and regional components. In contrast, ALFF and ReHo showed more heterogeneous functional patterns, including global, focal, and scattered configurations. Site labels explained the largest proportion of loading variance, whereas recorded acquisition parameters showed modality-dependent contributions: TR and TE were more prominent for structural site effects, while FA, voxel size, TR, and scanner model contributed more strongly to functional site effects.

DISCUSSION: The proposed framework provides a component-level diagnostic approach for multi-site MRI analysis. By mapping, stabilizing, and technically interpreting site-effect patterns, it complements conventional harmonization methods and may improve the transparency and reproducibility of multi-site structural and functional MRI studies.

PMID:42591441 | PMC:PMC13461629 | DOI:10.3389/fbinf.2026.1902380

J Cereb Blood Flow Metab. 2026 Aug 12:271678X261479952. doi: 10.1177/0271678X261479952. Online ahead of print.

ABSTRACT

Electrophysiological recordings such as electroencephalogram (EEG) are gold standards for measuring neuronal activity, which requires substantial oxidative metabolism (CMRO2) for support. Although EEG-CMRO2 links have long been assumed or measured qualitatively, quantitative characterization in humans remains limited, hindering our understanding of neurometabolic mechanisms and the utility of electrophysiological biomarkers in brain disease. Given that the neurometabolic process is sensitive to baseline perfusion and aerobic glycolysis, we hypothesized EEG-CMRO2 associations would show strong network and sex dependence, as these factors strongly influence perfusion and glycolytic activity. Here, we quantified EEG-CMRO2 associations and their underlying profiles (with cerebral blood flow and oxygen extraction fraction) across brain networks and between sexes. We further investigated how the EEG-CMRO2 association influenced resting-state functional magnetic resonance imaging (rs-fMRI) measurements. Our main findings suggest: (1) globally, CMRO2 only partially mediated EEG-fMRI relationships, revealing O2-independent coupling pathways; (2) EEG-CMRO2 associations varied significantly across functional networks; (3) sex differences in EEG-CMRO2 associations showed minimal network dependence; (4) high-frequency and low-frequency EEG bands exhibited opposite-polarities CMRO2 associations between males and females. These findings demonstrate that neurometabolic coupling differs across functional networks, frequency bands, and importantly, across biological sexes, with important implications for interpreting developing electrophysiological biomarkers and rs-fMRI measurements.

PMID:42590893 | DOI:10.1177/0271678X261479952

CNS Neurosci Ther. 2026 Aug;32(8):e71041. doi: 10.1002/cns.71041.

ABSTRACT

BACKGROUND: Overlapping network architecture supports functional integration and multifunctional regional engagement in the brain, and may serve as a candidate biomarker for interventions in autism spectrum disorder (ASD). However, the biological context underlying intermittent theta-burst stimulation (iTBS)-related changes in overlapping network architecture remains poorly understood.

METHODS: Seventy patients with ASD and chronic insomnia were randomly assigned to receive either real or sham iTBS targeting the left orbitofrontal cortex, administered once daily for 8 weeks. The Insomnia Severity Index (ISI) and resting-state functional magnetic resonance imaging (fMRI) data were collected at baseline and after the intervention. The Shannon-entropy diversity coefficient was calculated to characterize overlapping network architecture. The JuSpace toolbox was used to assess spatial correspondence between iTBS-related network changes and neurotransmitter systems. Transcriptomic-neuroimaging association analyses were then performed using gene-expression data from the Allen Human Brain Atlas.

RESULTS: Sleep improvement following real iTBS was accompanied by changes in overlapping network architecture across 13 cortical regions. These changes showed spatial correspondence with mGluR5 and GABA_A receptor density maps. Regions showing iTBS-related network changes were associated with glutamatergic synaptic transmission and calcium-dependent signaling, enriched for cortical excitatory neuronal signatures with peak expression during adolescence, and organized into a highly interconnected protein-protein interaction network centered on the Ca2+-PKA signaling axis.

CONCLUSIONS: This study provides multiscale evidence for the biological context underlying iTBS-related changes in overlapping network architecture in ASD with chronic insomnia.

PMID:42590803 | DOI:10.1002/cns.71041

J Clin Med. 2026 Jul 23;15(15):5766. doi: 10.3390/jcm15155766.

ABSTRACT

Background: Perinatal brain network alterations, including changes in resting-state functional connectivity (rsFC), may increase vulnerability for perinatal mood and anxiety disorders (PMAD). The Fronto-Parietal Network (FPN), the Default-Mode Network (DMN), and the Salience Network (SN) are interconnected networks implicated in mood disorders. However, these networks' role in perinatal neuroplasticity and PMAD remains unclear. Methods: This pilot study prospectively followed twenty-two women from preconception to postpartum. Participants completed anxiety and depression questionnaires and underwent fMRI scans at preconception and postpartum. The FPN, DMN, and SN were defined and average connectivity of each network was determined. Differences in connectivity from preconception to postpartum within each network and to each network at the whole-brain level were computed. Results: While connectivity within the FPN, DMN, and SN did not show significant changes from preconception to postpartum, we found increased rsFC from the left anterior prefrontal cortex to the DMN, and decreased rsFC from the right ventral posterior cingulate cortex to the FPN, from preconception to postpartum. Bilateral supplementary motor areas (SMAs) showed increased connectivity to the FPN from preconception to postpartum, and this change in connectivity was negatively correlated with anxiety scores during pregnancy. Right SMA connectivity to the FPN at preconception showed positive association with postpartum depression scores (p < 0.05 for all comparisons). Conclusions: RsFC perinatal-related changes were demonstrated in cognitive and motor regions connected to the DMN and FPN. Among women with perinatal depressive and anxiety symptoms, changes in SMA rsFC to the FPN from preconception to postpartum were observed, indicating possible roles in PMAD.

PMID:42589870 | DOI:10.3390/jcm15155766

Neuroimage. 2026 Aug 12:122167. doi: 10.1016/j.neuroimage.2026.122167. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate abnormal coupling patterns between white matter functional activation (static and dynamic amplitude of low‑frequency fluctuations, sALFF and dALFF) and white matter (WM) microstructural integrity (fractional anisotropy, FA) in patients with noise‑induced hearing loss (NIHL).

METHODS: Fifty‑three patients with NIHL and 50 matched healthy controls (HCs) underwent resting‑state fMRI and diffusion tensor imaging. sALFF and dALFF were computed to characterize local neural activity in WM; WM microstructural integrity was assessed using tract‑based spatial statistics (TBSS) to generate a FA skeleton; WM functional-structural coupling was quantified by voxel‑wise ratios (ALFF/FA) on the skeleton; the overlapping regions relationship between ALFF and FA was further examined by correlation analysis (p < 0.05, Gaussian random field (GRF) correction). Significant abnormal imaging features and blood biomarkers were selected via least absolute shrinkage and selection operator (LASSO) to construct a support vector machine (SVM) classifier.

RESULTS: NIHL patients exhibited widespread FA reductions across multiple white matter tracts, with a single FA increase in the right anterior corona radiata. On the FA skeleton, sALFF was increased in the left middle cerebellar peduncle (MCP), right inferior longitudinal fasciculus (ILF), and left cingulum hippocampus, whereas dALFF was decreased in the left ILF and corpus callosum trunk. Voxel‑wise ratios revealed: (i) increased sALFF/individual FA in the right uncinate fasciculus and right cingulum bundle, and decreased sALFF/individual FA in the left fronto‑insular tract and left cingulum bundle; (ii) increased dALFF/individual FA in the right fronto‑insular tract, and decreased dALFF/individual FA in the left corticostriate fibers (all p < 0.05, GRF‑corrected). In overlapping regions where both FA and ALFF showed significant group differences, correlation analysis showed that sALFF tended to be negatively correlated with FA in NIHL patients, whereas dALFF showed a positive correlation trend - opposite to the pattern observed in HCs. Clinically, the sALFF/FA ratio in the overlapping left MCP region negatively correlated with noise exposure time (r = -0.330, p < 0.001), whereas the sALFF/FA ratio in the left cingulum hippocampus positively correlated with anxiety scores (r = 0.238, p = 0.015), and the dALFF/FA ratio in the left ILF1 positively correlated with hearing threshold (r = 0.311, p = 0.023). A LASSO‑based SVM model using six multimodal features discriminated NIHL from controls with 84.5% accuracy and an AUC of 0.893 (95% CI 0.83 - 0.95).

CONCLUSIONS: This study demonstrates widespread white matter abnormalities and functional-structural decoupling in NIHL, characterized by region‑specific alterations in sALFF/FA and dALFF/FA. These decoupling patterns correlate with key clinical variables (noise exposure duration, anxiety, and hearing threshold), supporting the dysconnectivity hypothesis and offering potential imaging biomarkers.

PMID:42586328 | DOI:10.1016/j.neuroimage.2026.122167

Biol Psychiatry Cogn Neurosci Neuroimaging. 2026 Aug 12:S2451-9022(26)00233-8. doi: 10.1016/j.bpsc.2026.08.001. Online ahead of print.

ABSTRACT

BACKGROUND: Often emerging in early adolescence, social anxiety disorder (SAD) is a mental health condition characterised by persistent fears of negative evaluation. Neuroimaging studies implicate disruptions in the default mode network (DMN) in SAD, however, it remains unclear whether specific DMN regions are driving broader network alterations during this developmental period.

METHODS: Thirty-six adolescents and young adults (aged 16-25) with SAD and 66 age- and gender-matched controls underwent resting-state functional magnetic resonance imaging. Using spectral dynamic causal modelling, we examined effective connectivity between core DMN nodes, including the medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), and bilateral inferior parietal cortex (IPL). Parametric empirical Bayes modelling was used to investigate between-group differences in these connectivity parameters.

RESULTS: Compared to controls, SAD patients demonstrated increased excitatory connectivity from the PCC to the right IPL as well as excitatory connectivity from the left to right IPL. We also observed reduced PCC and MPFC self-inhibition and increased right IPL self-inhibition within SAD patients. Furthermore, leave-one-out cross-validation revealed that altered PCC self-inhibition was associated with social anxiety severity (r = .18, p = 0.039).

CONCLUSIONS: Our findings suggest that SAD is associated with alterations in DMN effective connectivity, with converging evidence implicating the PCC as a dysfunctional hub. This is further highlighted by the association between PCC self-connectivity and social anxiety symptom severity. Future studies should determine whether modulating PCC connectivity could have therapeutic utility for those with SAD.

PMID:42586239 | DOI:10.1016/j.bpsc.2026.08.001

Neurology. 2026 Sep 8;107(5):e218416. doi: 10.1212/WNL.0000000000218416. Epub 2026 Aug 12.

ABSTRACT

BACKGROUND AND OBJECTIVES: Patients with temporal lobe epilepsy (TLE) can achieve seizure freedom in the early period after surgery, yet up to half experience seizure recurrence in the following years (i.e., long-term). TLE is associated with disruption of highly connected brain regions (hubs), which may reduce the likelihood of long-term surgical success. We tested whether disruption of physiologic (normative) hubs predicts long-term seizure outcomes.

METHODS: In a prospective, multimodal cohort of patients with drug-resistant TLE from 6 centers who underwent resective or laser ablative surgery and had more than 2 years of follow-up (mean = 5.4 years, SD = 3.2 years), we derived structural and functional connectomes from preoperative diffusion-weighted MRI and resting-state fMRI. Using a large multicenter healthy-control cohort, we identified normative connector hubs and quantified patient-specific disruption within these hubs using the graph-theory measure-participation coefficient. To classify seizure-free (positive class) and non-seizure-free (negative class) outcomes, we trained machine learning models using patient-specific disruption of the participation coefficient derived from structural and functional connectomes and their combination (multimodal approach). We evaluated model performance in an independent cohort. Models further incorporated clinical and demographic variables, as well as gray and white matter volumes.

RESULTS: In our cohort of 175 patients, the multimodal approach outperformed a model based on clinical and demographic variables only and unimodal approaches, achieving high specificity (mean = 80.0%, SD = 9.9%) and moderate-to-high negative predictive value (mean = 63.9%, SD = 3.6%). Using 362 healthy controls to define normative connector hubs, Shapley Additive Explanation analyses identified disruption of the participation coefficient in the hippocampi and connector hubs of the dorsal attention network as predictive of long-term seizure recurrence, which includes areas not typically targeted in TLE surgery.

DISCUSSION: Disruption of normative hub architecture provides biologically interpretable biomarkers of long-term seizure outcomes in TLE. Contrary to previous studies, the model achieved high specificity in predicting long-term seizure recurrence, which supports its potential clinical utility for postoperative risk stratification and counseling rather than surgical exclusion. By validating performance in an independent cohort under conservative evaluation, our study underscores the translational potential of network-level biomarkers to complement conventional predictors.

PMID:42585607 | DOI:10.1212/WNL.0000000000218416

J Alzheimers Dis. 2026 Aug 12:13872877261477016. doi: 10.1177/13872877261477016. Online ahead of print.

ABSTRACT

BackgroundDifferentiating individuals with mild cognitive impairment who convert to dementia due to Alzheimer's disease (MCI-C) from those who do not convert (MCI-NC) is increasingly important. Functional connectivity (FC) derived from resting state functional MRI (rs-fMRI) has been investigated as a potential biomarker. However, improved data analysis strategies are needed. One underexplored approach is pairwise voxel-to-voxel analysis.ObjectiveTo describe differences in FC between amyloid positive MCI-C and MCI-NC using a whole-cortex voxel-to-voxel pairwise approach.MethodsBaseline rs-fMRI from the Alzheimer's Disease Neuroimaging Initiative was retrieved for amyloid positive MCI participants. Voxel-to-voxel, pairwise, cortical FC was computed. Multivariate distance matrix regression was used to identify voxels presenting FC patterns that were significantly different between MCI-C and MCI-NC.Results21 MCI-C and 28 MCI-NC were included. The primary analysis with voxel-level threshold at p < 0.001 combined with cluster-level p < 0.05 yielded no significant results. At voxel-level p < 0.01 and the same cluster-level threshold, three significant clusters on the right visual cortex were found. These clusters, however, were not robust to head motion, fMRI protocol and additionally clinical or biological severity.ConclusionsProgression from Alzheimer-related MCI to dementia was not significantly associated with FC in the primary analysis. However, a less stringent threshold yielded FC differences in the occipital lobe in alignment with previous studies but were not robust to methodological and biological covariates between groups. Our findings highlight the need for larger samples and careful control of covariates to identify robust FC alterations related to dementia conversion.

PMID:42585347 | DOI:10.1177/13872877261477016

Brain Imaging Behav. 2026 Aug 12;20(4):120. doi: 10.1007/s11682-026-01183-1.

ABSTRACT

Although resting-state fMRI is a promising alternative to task-fMRI in presurgical mapping, protocols to simultaneously assess language lateralization and sensorimotor networks within a single acquisition remain limited. To evaluate the feasibility of using connectivity analysis derived from a language fMRI task to assess language lateralization and extract the sensorimotor network in presurgical patients with space-occupying lesions. In a retrospective study, 40 presurgical patients underwent a verb generation task (VGT) and a hand motor task (HMT). Single-subject spatially-constrained ICA (scICA) was performed on VGT scans to extract sensorimotor components. Sensitivity, specificity and Dice coefficient between scICA-derived scans and HMT activation maps were calculated. The effects of different variables were analyzed using ANOVA. Forty patients (mean age, 40.50 ± 13.99; 21 men) were included. Sensorimotor components could be extracted in all patients within the predefined constrained scICA framework. Using HMT activation as comparative reference, mean ipsilesional voxelwise sensitivity, specificity and Dice coefficient of scICA-derived maps were 78%, 75% and 36%, respectively. No significant differences were found between ipsilesional and contralesional hemispheres in sensitivity or specificity. Exploratory analyses suggested higher sensitivity values in the right contralesional hemisphere, higher magnetic field strength, and typical language lateralization, although most effects did not survive FDR correction. Our study supports the feasibility of extracting sensorimotor-related networks from a language task while simultaneously determining language lateralization in patients with space-occupying lesions. This approach may provide complementary presurgical information, potentially reducing acquisition time. Further validation using direct cortical stimulation and larger prospective cohorts is warranted.

PMID:42584801 | DOI:10.1007/s11682-026-01183-1

J Sex Med. 2026 Aug 5;23(9):qdag238. doi: 10.1093/jsxmed/qdag238.

ABSTRACT

BACKGROUND: Sleep-related painful erections (SRPE) are a rare parasomnia featuring recurrent nocturnal awakenings from painful penile erections, with daytime erections remaining painless; their central neural mechanisms remain poorly characterized.

AIM: To delineate the structural and functional neuroimaging signatures of SRPE using multimodal cerebral magnetic resonance imaging (MRI).

METHODS: Twenty-two men with SRPE and 23 age-matched healthy men (HCs) underwent structural and resting-state functional MRI. Grey matter volume (GMV) was compared using voxel-based morphometry (VBM), and regional spontaneous activity using the fractional amplitude of low-frequency fluctuations (fALFF). VBM and fALFF clusters served as seeds for whole-brain seed-to-voxel and region-of-interest-to-region-of-interest (ROI-to-ROI) functional connectivity (FC). All imaging analyses were corrected for multiple comparisons at P < .05 (peak-level family-wise-error for VBM; cluster-level false-discovery-rate for fALFF and seed-to-voxel FC; threshold-free cluster enhancement for ROI-to-ROI FC). Sensitivity analyses adjusted each finding individually for erectile function, premature ejaculation, anxiety, and depression.

OUTCOMES: Primary outcomes were between-group differences in GMV, fALFF, and FC; secondary outcomes were correlations between altered imaging metrics and clinical features.

RESULTS: Relative to HCs, SRPE patients showed reduced GMV in the bilateral putamen, right posterior orbitofrontal cortex, and bilateral superior temporal gyri (STG). fALFF was decreased in the right inferior temporal gyrus and the left middle occipital gyrus and increased in the left orbital superior frontal gyrus; this increase correlated negatively with the Pittsburgh Sleep Quality Index (r = -0.499, P < .001) and SRPE frequency (r = -0.616, P = .002) but did not survive adjustment for erectile function. Seed-to-voxel FC was increased between the bilateral STG and the anterior cingulate cortex (ACC), the left putamen and left middle temporal gyrus, and the left middle and superior occipital gyri. ROI-to-ROI analysis showed increased connectivity of the bilateral ACC and right midcingulate cortex with the left central operculum, left Heschl's gyrus, and bilateral STG. The right-hemisphere structural findings, the reduced-fALFF findings, and the bilateral STG-ACC hyperconnectivity were robust to all covariates; left-hemisphere and intra-occipital effects were not.

CLINICAL IMPLICATIONS: These findings offer preliminary evidence of central nervous system involvement in SRPE that may eventually inform neuromodulation-based approaches.

STRENGTHS AND LIMITATIONS: This is the first multimodal cerebral MRI study of SRPE. Limitations include the modest sample, cross-sectional design, absence of sleep-state recording, and comorbidities that preclude causal and fully specific inference.

CONCLUSION: Multimodal MRI identified associative structural and functional alterations in regions implicated in pain processing, sleep regulation, and affective-cognitive integration in SRPE.

PMID:42580700 | DOI:10.1093/jsxmed/qdag238

J Pharm Biomed Anal. 2026 Aug 8;282:117695. doi: 10.1016/j.jpba.2026.117695. Online ahead of print.

ABSTRACT

Depression is characterized by a dysregulated brain-gut axis. Xiaoyao San (XYS), a classic Traditional Chinese Medicine formula for soothing Liver and strengthening Spleen, is clinically effective in alleviating depression. However, the systems-level mechanisms by which XYS coordinates gut-brain communication to exert its antidepressant effects remain insufficiently understood. This study aimed to systematically elucidate the antidepressant mechanisms of XYS, with a focus on identifying a key gut-derived metabolic pathway that modulates prefrontal cortex (PFC) function. A mouse model of depression was established using isolated housing combined with chronic unpredictable mild stress (CUMS). Mice were treated with XYS at low, medium, and high doses or paroxetine. We employed a multimodal approach, integrating behavioral tests, resting-state functional magnetic resonance imaging (rs-fMRI), gut microbiota profiling (16S rRNA sequencing), serum metabolomics and PFC transcriptomics. To establish causal evidence, pseudo-germ-free mice received fecal microbiota transplantation (FMT) from donor mice treated with XYS, followed by comprehensive behavioral and biochemical assessments. XYS treatment significantly ameliorated depressive-like behaviors and restored functional connectivity within emotion-regulation brain networks. Multi-omics integration revealed that XYS reshaped the gut microbiota, which was associated with a reduction in systemic levels of kynurenine (KYN), a key tryptophan-derived metabolite. In the PFC, this decrease in KYN was accompanied by the normalization of aryl hydrocarbon receptor (AhR) signaling activity. Furthermore, GABAergic neurotransmission, mediated by γ-aminobutyric acid (GABA), was enhanced, as evidenced by upregulated expression of glutamate decarboxylase 1 (Gad1), gamma-aminobutyric acid type A receptor subunit alpha1 (Gabra1), increased GABA content, and elevated levels of key synaptic plasticity-related molecules, including brain-derived neurotrophic factor (BDNF), postsynaptic density protein-95 (PSD-95), and synaptophysin (SYN). Critically, FMT from XYS-treated donors recapitulated the antidepressant phenotype in recipient mice, directly implicating the gut microbiota in these therapeutic effects. This study demonstrates that XYS alleviates depression by orchestrating a gut-brain signaling cascade that converges on the PFC to enhance inhibitory synaptic transmission. These findings provide novel and causal mechanistic insights into the brain-gut modulatory action of XYS, offering a comprehensive framework for its therapeutic potential in treating depression.

PMID:42580208 | DOI:10.1016/j.jpba.2026.117695

Eur J Radiol. 2026 Aug 5;204:113138. doi: 10.1016/j.ejrad.2026.113138. Online ahead of print.

ABSTRACT

Carbon monoxide poisoning (COP) often leads to acute brain injury and delayed neuropsychiatric sequelae (DNS), resulting in heavy social and economic burdens. Conventional imaging can detect gross structural lesions, and acute brain lesions on routine MRI are an established biomarker for predicting DNS. However, it fails to identify early occult injury and interpret pathological mechanisms. Advanced multimodal neuroimaging techniques enable comprehensive assessment of COP-associated brain damage. Structural changes are dominated by prefrontal and limbic lobe atrophy. Diffusion tensor imaging and diffusion kurtosis imaging can both assess microstructural damage of cerebral white matter; accumulating observational data suggest that kurtosis-derived metrics may yield higher sensitivity for detecting subtle white matter injuries. Abnormalities of the default mode network are commonly detected on resting-state functional MRI (rs-fMRI), while DNS patients show more severe damage in deep brain areas and the brainstem. Nuclear medicine imaging confirms basal ganglia and lobar hypoperfusion, and clarifies the unique pattern of striatal dopaminergic injury in COP-related parkinsonism. Magnetic resonance spectroscopy and glutamate chemical exchange saturation transfer characterize metabolic disturbances and excessive glutamate release, which are closely correlated with cognitive impairment. Advanced rs-fMRI approaches contribute greatly to exploring DNS pathogenesis, yet high-quality evidence across different modalities is insufficient, and no unified predictive biomarkers have been recognized to date. Given the limitations of existing single-center, small-sample and cross-sectional studies, further multicenter, longitudinal and multimodal investigations are needed to optimize predictive models and improve the diagnosis, treatment and mechanistic research of COP.

PMID:42580076 | DOI:10.1016/j.ejrad.2026.113138

Asian J Psychiatr. 2026 Aug 7;123:105112. doi: 10.1016/j.ajp.2026.105112. Online ahead of print.

ABSTRACT

BACKGROUND: The neuropathological mechanisms of schizophrenia remain unclear. Intrinsic neural timescale (INT) reflects the temporal organization of neural activity. This study aimed to characterize INT alterations in patients with first-episode schizophrenia who were drug-naïve or minimally treated, while minimizing confounding effects of chronic illness and medication exposure.

METHODS: Resting-state fMRI data were collected from 123 first-episode, drug-naïve or minimally treated schizophrenia patients and 102 matched healthy controls. INT values were derived from the autocorrelation function of the fMRI signal. Group differences in INT were assessed using analysis of covariance (ANCOVA), controlling for age, gender and scanner site. Additional analyses included correlation analyses, gene annotation and enrichment analyses, and spatial correlation analyses.

RESULTS: Patients exhibited a divergent cortical-subcortical pattern, characterized by reduced cortical INT and prolonged subcortical INT. Compared with healthy controls, patients showed significant INT alterations in 13 regions of interest (p-fdr < 0.05), predominantly involving the default mode network (5 regions) and subcortical network (4 regions), as well as the sensorimotor network, memory retrieval network, salience network, and ventral attention network. Regions with altered INT were enriched for synapse-related genes, and their spatial distribution was correlated with cerebral blood flow.

CONCLUSIONS: Our findings show that first-episode drug-naïve or minimally treated schizophrenia patients are characterized by disrupted intrinsic neural timescales with distinct cortical-subcortical alterations. These abnormalities may be related to cerebral perfusion, synaptic function and symptom severity. The distinct cortical-subcortical alterations of INTs may represent a candidate neurobiological marker of early-stage schizophrenia.

PMID:42579964 | DOI:10.1016/j.ajp.2026.105112

Hum Brain Mapp. 2026 Aug;47(11):e70586. doi: 10.1002/hbm.70586.

ABSTRACT

Functional MRI (fMRI) is widely used to assess brain function, but neural-derived fMRI signals are susceptible to contamination from in-scanner head motion. Preprocessing pipelines often regress out and censor head motion artifacts using six rigid-body motion parameters. However, recent research suggests these head-motion estimates are susceptible to contamination from other sources of noise, such as respiratory rate, body size, and estimated cardiorespiratory fitness (eCRF), that correspond to apparent head motion at higher frequencies (HF-motion; > 0.1 Hz). Thus, these health variables are thought to be linked to the artifactual inflation of head motion estimates, introducing additional challenges to appropriate modeling and preprocessing procedures that reduce noise. Whether this artifactual relationship extends to changes in body size, midline abdominal fat (i.e., body composition), CRF measured with gold-standard methods, and respiratory rate measured during scanning remains unclear. The Brain EXTEND Trial acquired multiple health variables before and after an exercise intervention that changed CRF, offering a means to test the relationship between these health variables and HF-motion in a longitudinal design. Subjects (55-80 years of age) completed a 6-month chronic exercise intervention at two intensities. We analyzed baseline and longitudinal (EXTEND, baseline n = 122; longitudinal n = 84) relationships between HF-motion and health variables that included body mass index (BMI), waist circumference (WC), CRF measured with a maximal exercise test (VO2max), and resting respiratory rate. HF-motion was examined in each head-motion parameter as the proportion of HF-motion above > 0.1 Hz-the typical upper bound of fMRI signals at rest. At baseline, HF-motion for all translational axes was positively associated with body size (BMI, WC) while CRF was negatively associated with only the roll y-rotation. Additionally, longitudinally, decreased BMI related to reduced HF-motion in the z-translation. Results indicate health changes related to body size associate with the presentation of high-frequency MRI head-motion artifacts. We caution researchers against ignoring the presence of HF-motion in their analyses as their use of contaminated motion traces will negatively affect their modeling of fMRI measures. Results have implications for a wide range of investigations in health neuroscience involving body size, respiratory function, and cardiorespiratory fitness.

PMID:42578518 | DOI:10.1002/hbm.70586

Front Neurosci. 2026 Jul 27;20:1780430. doi: 10.3389/fnins.2026.1780430. eCollection 2026.

ABSTRACT

Autism Spectrum Disorder (ASD) is associated with atypical large-scale brain network organization, yet how spatial-functional dependencies relate to clinical features and molecular reference maps remains incompletely understood. To quantify spatial functional heterogeneity (Sill) and coherence persistence (Range), we analyzed resting-state fMRI data from 162 ASD and 175 TD adolescents, all aged 12-18. Compared with TD, adolescents with ASD exhibited significantly increased Sill within higher-order association networks, including the left Language and right Posterior Multimodal networks, whereas no group differences in Range survived multiple-comparison correction. Within the ASD group, elevated Sill was selectively associated with greater social-affective symptom severity but not restricted and repetitive behaviors. To explore potential biological correlates, we integrated cortical gene expression reference data and identified transcriptomic patterns associated with regional Sill differences. These genes showed enrichment for synaptic signaling, mitochondrial processes, and glial-related functions, highlighting multiscale correspondence between spatial-functional organization and molecular reference maps. Together, these results demonstrate statistical associations among altered spatial-functional properties, clinical severity, and transcriptomic profiles related to synaptic signaling, mitochondrial processes, and glial-related functions in ASD, providing a complementary spatial perspective on large-scale functional organization.

PMID:42577408 | PMC:PMC13454100 | DOI:10.3389/fnins.2026.1780430