Most recent paper

Diagnostics (Basel). 2026 Aug 27;16(17):2746. doi: 10.3390/diagnostics16172746.

ABSTRACT

Background/Objectives: Synolitic graphs (SGs) were developed for task-based fMRI, where edge weights encode the discriminative power of pairwise regional features; whether similar information can be recovered from resting-state data was untested. We benchmarked SGs for autism spectrum disorder (ASD) classification using the multisite ABIDE-I dataset (871 subjects: 403 subjects with ASD, 468 typical controls; 17 sites; CC200 atlas). Methods: Using 5-fold cross-validation with 10 repeats and balanced accuracy as the primary metric, we compared SGs with eight baselines including correlation matrices, tangent space connectivity, elastic net logistic regression, SVM, and XGBoost. Results: The vectorised correlation matrix achieved 67.9% balanced accuracy (AUC = 0.743), the combined model 68.0% (AUC = 0.744), and SGs 57.0% (AUC = 0.598). SGs performed above chance (permutation p = 0.001), but their performance was not significantly different from that of direct logistic regression (Nadeau-Bengio p = 0.82). After covariate residualisation, correlation-based methods retained 66.9-67.1% balanced accuracy, while SGs achieved 55.6%. Leave-one-site-out validation yielded 66.0-66.2% for correlation-based models and 55.0% for SGs, with similar declines of approximately 2 percentage points from standard cross-validation. SG-derived ROI rankings were unstable, and ADOS severity prediction among 193 ASD participants was underpowered and inconclusive. Conclusions: Conventional connectivity representations substantially outperformed SGs for resting-state ASD classification, contrasting with previously reported task-fMRI advantages. No evaluated method achieved performance suitable for stand-alone clinical screening or diagnosis; this study should therefore be interpreted as a methodological benchmark rather than a validation of a clinically deployable tool.

PMID:42739176 | DOI:10.3390/diagnostics16172746

Nutrients. 2026 Sep 3;18(17):2898. doi: 10.3390/nu18172898.

ABSTRACT

Introduction: Caffeine is a widely consumed psychoactive compound whose central pharmacological effects are mediated primarily through antagonism of adenosine receptors. Wakeful EEG provides a temporally sensitive method for examining caffeine-related changes in oscillatory activity and vigilance-related brain states. This systematic review synthesized evidence concerning the effects of acute and habitual caffeine exposure on non-ERP EEG measures during wakefulness. Materials and Methods: The review followed PRISMA 2020 guidelines. PubMed/MEDLINE, Scopus, Web of Science, Embase, PsycINFO, and the Cochrane Library were searched from database inception to 30 May 2026. Eligible studies included human participants exposed to caffeine, coffee, or caffeine-containing interventions and reported EEG outcomes during wakeful resting-state or task-related conditions. Risk of bias was assessed using RoB 2 for randomized trials and ROBINS-I for non-randomized studies. Findings were synthesized narratively because of substantial methodological heterogeneity. Results: Forty-eight studies were included. Resting-state spectral EEG was the dominant paradigm, although studies also examined task-related activity, prolonged wakefulness, sleep deprivation, withdrawal, driving-related drowsiness, coherence, nonlinear complexity, EEG microstates, and multimodal EEG-fMRI measures. Reductions in alpha power or amplitude were among the more frequently reported findings following acute caffeine administration, while attenuation of theta, delta, or other slow-frequency activity was particularly evident under conditions of sleep pressure, prolonged wakefulness, withdrawal, fatigue, or reduced vigilance. However, neither effect was universal. Beta findings were heterogeneous, and changes in alpha frequency, total EEG power, coherence, asymmetry, complexity, and microstates were less consistently examined. The direction and magnitude of EEG responses varied according to caffeine dose, habitual intake and withdrawal status, baseline vigilance, eye condition, task demands, participant characteristics, scalp region, frequency-band definition, and EEG methodology. Evidence concerning coherence, asymmetry, nonlinear complexity, microstates, and multimodal EEG-fMRI outcomes was preliminary. Conclusions: The available evidence does not establish a single reproducible EEG signature or validated electrophysiological biomarker of caffeine response. Reductions in alpha power and attenuation of slow-frequency activity during states of elevated sleep pressure or caffeine withdrawal were among the more frequently reported findings, but substantial methodological and state-dependent heterogeneity limits their specificity and generalizability. EEG changes should also not be interpreted as direct indicators of improved cognitive performance, because electrophysiological and behavioral effects were not consistently concordant across studies.

PMID:42739069 | DOI:10.3390/nu18172898

Mol Psychiatry. 2026 Sep 14. doi: 10.1038/s41380-026-03873-0. Online ahead of print.

ABSTRACT

Schizophrenia (SCZ) is increasingly recognized as a multi-system disorder characterized by peripheral immunometabolic dysregulation. To investigate system-level blood-brain integration, we analyzed peripheral blood transcriptomics, resting-state fMRI (fALFF), and cognitive data from two cohorts (Discovery: 43 SCZ, 60 HCs; Validation: 41 SCZ, 29 HCs). Seven robust peripheral blood gene co-expression modules associated with SCZ were identified, enriched for immune and metabolic pathways. These modules showed reproducible disease associations in independent blood cohorts. Widespread alterations in functional coupling between these gene modules and intrinsic brain activity (fALFF) were observed in SCZ, characterized by a network-specific reconfiguration with an inverse pattern of correlation changes between limbic and frontoparietal/default mode networks. This dysregulated coupling pattern was highly reproducible across cohorts. We further identified putative core disease-associated module-network pairs: a downregulated metabolic module coupled with frontoparietal/default mode regions, and an upregulated ribosomal module coupled with limbic regions. Integration of these multimodal features yielded a proof-of-concept improvement in SCZ diagnostic classification (AUCs: 0.71-0.77 in an independent temporal but local validation cohort). Correlation and mediation analyses suggested that brain functional activity in these coupled regions may mediate the relationship between peripheral gene expression and cognitive impairment. Collectively, these findings reveal distinct, reproducible dysregulation of peripheral-central functional coupling in SCZ, offering a multi-scale framework for understanding its pathophysiology and highlighting the potential of trans-scale features as candidate biomarkers for diagnosis and mechanistic insight.

PMID:42736350 | DOI:10.1038/s41380-026-03873-0

Biol Psychiatry Cogn Neurosci Neuroimaging. 2026 Sep 14:S2451-9022(26)00260-0. doi: 10.1016/j.bpsc.2026.09.004. Online ahead of print.

ABSTRACT

BACKGROUNDS: Obsessive-compulsive disorder (OCD) has been consistently associated with alterations in cortico-striato-thalamo-cortical (CSTC) circuits, as demonstrated by numerous resting-state fMRI studies. However, given the high prevalence of comorbid anxiety disorders and anxiety-related traits in OCD patients, previous research has not clearly established whether these neural alterations are specific to OCD or represent shared pathophysiology with anxiety disorders (ANX).

METHODS: We conducted a coordinate-based meta-analysis using Signed Differential Mapping (SDM) of whole-brain resting-state fMRI studies in OCD (n = 1429 patients, n = 1509 healthy controls). To assess whether identified alterations were OCD-specific or shared with anxiety pathophysiology, we performed comparative meta-analyses including 15 ANX studies (n = 558 patients, n = 561 healthy controls) using conjunction and contrast analyses, and examined resting-state local brain activity as indexed by ALFF, fALFF, and ReHo.

RESULTS: Compared to ANX, OCD patients showed increased spontaneous activity in the left anterior cingulate cortex extending to the medial prefrontal cortex (ACC/MPFC), right globus pallidus, and left putamen, alongside decreased spontaneous activity in the left middle frontal gyrus. Both disorders shared decreased spontaneous activity in the left postcentral gyrus. However, this meta-analysis did not identify significant differences in amygdala activity in within-group or between-group comparisons, nor in conjunction analyses.

CONCLUSIONS: Overall, this meta-analysis reveals shared reductions in spontaneous activity in the left postcentral gyrus across OCD and ANX, suggesting a potential role for the somatosensory cortex in transdiagnostic emotional processing.

PMID:42735833 | DOI:10.1016/j.bpsc.2026.09.004

Zhonghua Nei Ke Za Zhi. 2026 Sep 1;65(9):970-980. doi: 10.3760/cma.j.cn112138-20260610-00355.

ABSTRACT

Objective: To investigate the characteristics and neural mechanisms of altered olfactory and spatial navigation abilities in individuals with subjective cognitive decline (SCD). Methods: A total of 44 cognitively normal participants and 69 participants meeting diagnostic criteria for SCD were recruited from Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University from September 2023 to October 2025. All participants underwent neuropsychological assessments, olfactory testing, spatial navigation testing, 3.0 T resting-state functional MRI (rs-fMRI), task-based functional MRI (task-fMRI), and high-resolution T1-weighted imaging. Independent samples t-tests and Mann-Whitney U tests were used to compare olfactory and spatial navigation behavioral differences between the two groups. Left and right anterior lateral entorhinal cortex (alEC), posterior medial entorhinal cortex (pmEC), and primary olfactory cortex (POC) were selected as seeds to analyze functional connectivity (FC) under resting state and during odor stimulation, with multiple comparisons corrected using false discovery rate (FDR). Partial correlation analysis was performed to explore the relationship between olfactory and spatial navigation and FC metrics in the SCD group, controlled age, gender and years of education. Results: No significant differences were found between the two groups regarding age, gender and years of education. Compared with the NC group, SCD participants showed reduced olfactory memory (old) (Z=-3.05, P=0.005), lower composite olfactory memory Z-score (t=3.53, P=0.001), and lower overall olfactory Z-score (t=2.48, P=0.014). They also exhibited increased average error distances in allo-egocentric navigation (AEN) (Z=-9.17, P=0.001), egocentric navigation (EN) (Z=-8.84, P=0.003), and allocentric navigation (AN) (Z=-8.09, P=0.024), along with a decreased composite spatial navigation Z-score (t=3.84, P<0.001). rs-fMRI results revealed that, SCD participants showed significantly reduced resting-state FC within EC and POC related pathways, but enhanced FC with frontal, cingulate, and parietal regions during odor stimulation (all q<0.05, FDR-corrected). Partial correlation analysis indicated that in the SCD group, the FC between left alEC and left angular gyrus (ANG) positively correlated with EN average error distance (r=0.26, P=0.033), while the FC between right POC and right posterior cingulate cortex(PCC) positively correlated with AEN average error distance (r=0.29, P=0.028). Conclusion: SCD individuals already exhibit deficits in olfactory memory and spatial navigation, suggesting possible coexistence of impaired baseline network connectivity and compensatory network activation during tasks, or inefficient and abnormal recruitment due to diminished network integration efficiency. Abnormal functional connectivity between alEC and ANG, and between POC and PCC, is associated with spatial navigation performance and may represent key neural substrates underlying olfactory and spatial navigation changes in SCD.

PMID:42733263 | DOI:10.3760/cma.j.cn112138-20260610-00355

IBRO Neurosci Rep. 2026 Aug 18;21:747-753. doi: 10.1016/j.ibneur.2026.08.014. eCollection 2026 Dec.

ABSTRACT

BACKGROUND: The purpose of this study was to explore if administration of N-acetylcysteine (NAC) in patients with multiple sclerosis (MS) resulted in altered neurophysiological function as determined by the combination of functional connectivity (FC) based on resting Blood Oxygen Level Dependent (BOLD) fMRI and cerebral glucose metabolism using Fluorodeoxyglucose Positron Emission Tomography (FDG PET) and whether those changes were associated with improvements in symptoms.

METHODS: Thirty-six patients with mild to moderate MS were randomized to either NAC plus standard of care, or standard of care only. The experimental group received NAC intravenously (50 mg/kg) once per week and orally (500 mg 2x/day) the other six days. Patients in both groups were evaluated initially and after 4 ± 2 months on an integrated PET-MRI platform with resting BOLD fMRI and FDG PET. Clinical symptom questionnaires were also completed at both time points.

RESULTS: The FC data showed significant differences in several brain regions including the inferior frontal gyrus, inferior temporal gyrus, inferior parietal gyrus, insula, cerebellum, and brain stem in the MS group after treatment with NAC. FDG PET demonstrated increased cerebral glucose metabolism in several of these structures including the inferior frontal gyrus and inferior temporal gyrus. Self-reported scores related to cognition and attention significantly correlated with these neurophysiological changes in the NAC group compared to controls.

CONCLUSIONS: The results of this study suggest that NAC administration alters resting functional connectivity along with cerebral glucose metabolism in MS patients, and this is associated with qualitative improvements in cognition and attention.

PMID:42732209 | PMC:PMC13570286 | DOI:10.1016/j.ibneur.2026.08.014

Netw Neurosci. 2026 Aug 25;10(3):787-808. doi: 10.1162/NETN.a.575. eCollection 2026.

ABSTRACT

Integrating neuroimaging data enhances our understanding of the brain. Structural magnetic resonance imaging (sMRI) offers high-resolution anatomical detail, while functional MRI (fMRI) captures dynamic neural activity. Combining these modalities can reveal significant structure-function relationships in the brain. However, existing approaches typically link sMRI to only a single fMRI network, overlooking the spatial complexity of multiple networks and thereby missing distributed structure-function relationships. To address this limitation, we present parallel multilink group joint ICA (pmg-jICA), a data-driven framework that fuses gray matter images from sMRI with multiple intrinsic fMRI networks within a single model. pmg-jICA captures cross-network structure-function coupling, preserves subject-specific variability, and enables robust group-level statistical analyses. To demonstrate the approach, we applied pmg-jICA to an Alzheimer's disease (AD) dataset, recovering linked structural and functional components for 53 brain networks. Notably, patients with AD exhibited alterations in subcortical, cognitive control and visual regions. Importantly, the subject loadings enabled the computation of functional network connectivity, revealing additional alterations in subcortical, visual, and cognitive control systems. Overall, our results demonstrate that pmg-jICA overcomes key limitations of existing multimodal fusion techniques, yielding deeper insights into structure-function disruptions in AD and potentially offering a flexible framework for studying other neurological and psychiatric disorders.

PMID:42730199 | PMC:PMC13569335 | DOI:10.1162/NETN.a.575

Front Neurosci. 2026 Aug 28;20:1820150. doi: 10.3389/fnins.2026.1820150. eCollection 2026.

ABSTRACT

BACKGROUND: Performance on MMSE language-related tasks may decline across the Alzheimer's disease (AD) spectrum and has clinical relevance for characterizing cognitive change. However, because the MMSE language subscore is a brief composite screening measure rather than a domain-specific language battery, its neural correlates should be interpreted cautiously. The intrinsic neural activity patterns associated with MMSE language-related task performance across the AD continuum remain insufficiently characterized. Most prior studies have examined isolated functional metrics or focused on global cognition, leaving unclear whether multidimensional spontaneous activity measures and their frequency-specific properties converge on common neural substrates associated with this composite behavioral measure.

METHODS: We analyzed resting-state fMRI data from 175 ADNI participants (32 AD, 90 MCI, 53 CN), computing four complementary amplitude-based metrics-ALFF, fALFF, PerAF, and wavelet-ALFF-with wavelet-ALFF further decomposed into slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands. To examine functional alterations associated with MMSE language-related task performance, participants were grouped according to MMSE language sub-scores into intact performance, mild language-related impairment, and greater reduction in performance. Voxel-wise ANCOVA, partial correlation, and multiple linear regression analyses were performed to evaluate associations between resting-state metrics and MMSE language-related task performance, modeled both categorically and continuously, while controlling for age, sex, and education. Multiple comparisons were corrected using Gaussian Random Field theory.

RESULTS: Across diagnostic groups, amplitude-based metrics revealed frequency-dependent alterations: slow-5 band changes predominated in temporal regions, while slow-4 band alterations characterized parietal areas, particularly the right angular gyrus (127 voxels, peak F = 24.44). When stratified by MMSE language-related task performance, the paravermal (predominantly right) cerebellar lobule VIII emerged as the only region consistently identified across multiple metrics, including ALFF, PerAF, wavelet-ALFF, and across analytic approaches. Critically, the cerebellar lobule VIII finding showed its most consistent cross-analytic support in the slow-4 band. In ROI-based partial-correlation analyses controlling for age, sex, and education, higher slow-4 wavelet-ALFF in this region was negatively associated with MMSE language-related task performance, and this association remained significant after additional adjustment for global disease severity (CDR-SB; partial r = -0.31, p < 0.001) and for non-language MMSE performance (partial r = -0.31, p < 0.001). The negative direction-whereby greater activity in this cerebellar cluster accompanied poorer performance-was consistent across conventional broadband, slow-4, and slow-5 analyses.

CONCLUSION: These findings suggest that right cerebellar lobule VIII activity is meaningfully associated with performance on MMSE language-related tasks across the AD spectrum, particularly within the slow-4 frequency range. Importantly, because the MMSE language subscore includes naming, repetition, reading, writing, command execution, and constructional praxis, the observed associations should not be interpreted as evidence for a purely language-specific cerebellar mechanism. Rather, they may reflect a combination of linguistic, executive, visuospatial, motor-planning, and sensorimotor processes required by MMSE language-related tasks. More broadly, the present study highlights the value of frequency-resolved spontaneous activity analyses for identifying clinically relevant brain-behavior associations in AD and suggests that cerebellar circuits warrant further investigation in relation to composite cognitive and language-related task performance.

PMID:42730172 | PMC:PMC13563651 | DOI:10.3389/fnins.2026.1820150

Front Hum Neurosci. 2026 Aug 28;20:1849595. doi: 10.3389/fnhum.2026.1849595. eCollection 2026.

ABSTRACT

OBJECTIVE: This study aimed to explore brain activity and functional connectivity changes associated with transcutaneous tibial nerve stimulation (TTNS) in patients with neurogenic overactive bladder (OAB), alongside changes in clinical symptoms.

METHODS: This prospective longitudinal self-controlled trial, conducted at the China Rehabilitation Research Center from 2024 to 2025, enrolled 15 adults with symptom-defined neurogenic OAB associated with spinal cord injury or multiple sclerosis. Resting-state functional magnetic resonance imaging (fMRI) was performed before and after standardized TTNS under full- and empty-bladder conditions. The primary imaging outcomes were fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity (FC).

RESULTS: TTNS significantly enhanced clinical outcomes, reducing 24 h urinary frequency from 15.53 ± 2.97 to 12.87 ± 2.88 (p < 0.001) and decreasing OABSS from 9.67 ± 1.50 to 8.53 ± 1.41 (p < 0.001). Neuroimaging indicated improvements were supported by notable increases in neural activity during bladder fullness, particularly in the fALFF of the left cerebellum posterior lobe (pFWE < 0.001) and right medial frontal gyrus (pFWE = 0.004). Additionally, FC between the left cerebellum posterior lobe and left fusiform gyrus was strengthened (pFWE = 0.005). Correlation analysis revealed that higher functional connectivity was associated with lower OAB symptom scores (p = 0.001). Importantly, Baseline fALFF differences between bladder states no longer met the corrected significance threshold after treatment (p < 0.05).

CONCLUSION: In this cohort, 1 month of TTNS was associated with reductions in urinary frequency and OABSS and with changes in fALFF and FC. These preliminary findings do not establish neuroplasticity, normalization, or a causal TTNS-specific mechanism and require confirmation in adequately powered sham-controlled studies.

CLINICAL TRIAL REGISTRATION: https://www.chictr.org.cn/hvshowprojectEN.html?id=300046&v=1.0, Identifier: ChiCTR2600122960.

PMID:42729348 | PMC:PMC13562249 | DOI:10.3389/fnhum.2026.1849595

J Neuroinflammation. 2026 Aug 1;23(1):312. doi: 10.1186/s12974-026-03962-5.

ABSTRACT

Neuroinflammation has detrimental neurocognitive effects in patients with systemic and neuropsychiatric diseases. Yet, outside of these conditions, it is unclear to what extent neuroinflammation modulates brain network-level function in older adults in the general population and, what, if any cognitive performance issues arise as a result. To evaluate these questions, we compared cerebrospinal fluid (CSF) inflammatory cytokine levels, resting-state functional magnetic resonance imaging, and cognitive performance data in 96 community-dwelling older adults (age ≥ 60 yrs). Principal component analysis yielded three components, accounting for > 50% of the variance in CSF cytokine levels; of which, the first principal component (PC1) accounted for 32% of the overall variance. A multivariate pattern analysis regression model, adjusted for age, sex and in-scanner movement, revealed cytokine PC1 values were inversely associated with functional connectivity between the mediodorsal thalamus and multiple cortical regions associated with the frontoparietal, default mode and dorsal attention functional brain networks (p-FWE = 0.037). For the majority of these cortical regions, functional connectivity with the mediodorsal thalamus was not associated with cognitive performance. In a robust multivariable model, narrative memory performances were positively associated with thalamocortical connectivity to a posterior parietal hub region of the frontoparietal and dorsal attention networks [beta = 0.25 (95% CI; 0.01, 0.49); p = 0.040], but this association did not survive correction for the number of evaluated cognitive domains (Bonferroni-adjusted p < 0.01). Study results reveal that neuroinflammatory CSF cytokine levels were inversely associated with functional connectivity between the mediodorsal thalamus and cortical regions largely involved in frontoparietal, dorsal attention and default mode networks, but the functional consequences of this relationship remain to be determined and will require further investigation to determine if reduced corticothalamic functional connectivity may help account, in part, for common illness-related cognitive complaints.

PMID:42732056 | DOI:10.1186/s12974-026-03962-5

Neuropsychopharmacology. 2026 Sep 12. doi: 10.1038/s41386-026-02544-6. Online ahead of print.

ABSTRACT

To design network-based treatments, it is critical to understand dynamic changes in brain networks over time. We comprehensively examined network structure using regional activation-only, pairwise-coactivation-only, and systems-level maximum entropy models (MEM) applied to the Human Connectome Project-Early Psychosis (HCP-EP) resting fMRI data (patients = 109, controls = 56). The MEM integrates regional activation levels and pairwise correlation-based functional connectivity (FC), providing the potential for better characterization of clinically meaningful brain states and how they change over time. Using the HCP/Glasser atlas to define brain regions within the default mode (DMN) and dorsal attention (DAN) networks, group differences in regional activation, graph measures of FC, and MEM features such as transition rates between minima in an energy landscape along with correlations with cognitive and psychopathological measures were examined. Psychosis was associated with reduced activation in several regions and multiple FC graph metric alterations. MEM demonstrated a wider variety of DMN and DAN activation/deactivation configurations, with more frequent switching between them, more pronounced network configuration differences and higher basin transition rates with reduced basin dwell times suggesting temporally unstable network configurations, meaning the brain cannot rely on any particular configuration for cognitive processing. Activation of only three regions correlated with working memory, but none of the FC metrics did. MEM features, in particular basin transitions and total energy, correlated negatively with working memory. Our findings suggest that MEM provides unique information, specifically attenuated inter-network connectivity with reduced stability of DMN and DAN brain states, to characterize networks as targets and their features as markers for novel treatment development.

PMID:42731996 | DOI:10.1038/s41386-026-02544-6

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Sep 11:111931. doi: 10.1016/j.pnpbp.2026.111931. Online ahead of print.

ABSTRACT

BACKGROUND AND HYPOTHESIS: Obsessive-compulsive disorder (OCD) has been consistently associated with dysfunction within the cortico-striato-thalamo-cortical (CSTC) circuits. Brain entropy (BEN) is a nonlinear measure of the complexity and irregularity of neural signals, including blood oxygen level-dependent (BOLD) time series. Although OCD has been extensively studied using conventional resting-state fMRI (rs-fMRI) metrics, alterations in intrinsic temporal complexity remain unclear. We investigated BEN alterations in OCD and their associations with OCD symptoms.

STUDY DESIGN: Sixty-seven patients with OCD and 60 healthy controls underwent rs-fMRI. BEN maps were computed using sample entropy and compared between groups. Associations between regional BEN and OCD-related clinical measures were examined using correlation analyses.

STUDY RESULTS: Patients with OCD showed increased BEN in CSTC regions, including the orbitofrontal cortex, caudate, and thalamus, and in extra-CSTC regions, including the superior temporal gyrus (STG) and middle cingulate cortex (FDR-corrected p < .05). Within the OCD group, higher BEN was associated with DOCS total scores in the right thalamus (r = 0.380), contamination symptoms in the left caudate (r = 0.382), unacceptable thoughts in the right thalamus (r = 0.429), and importance/control of thoughts scores in the right STG (r = 0.384; all FDR-adjusted p = .023).

CONCLUSIONS: BEN revealed OCD-related alterations across both CSTC and extra-CSTC regions, with regional BEN associated with specific symptom dimensions and obsessive beliefs. BEN appeared to capture alterations particularly in subcortical and midline structures, providing complementary information beyond conventional rs-fMRI measures and offering a new perspective on the neural mechanisms underlying OCD.

PMID:42727810 | DOI:10.1016/j.pnpbp.2026.111931

Neuroimage. 2026 Sep 11:122229. doi: 10.1016/j.neuroimage.2026.122229. Online ahead of print.

ABSTRACT

Long-term endurance training is associated with widespread changes in brain organization, but how these changes extend to large-scale networks across different temporal scales remains unclear. We combined static functional connectivity analysis with dynamic multilayer network modeling to examine resting-state fMRI data from 25 endurance athletes and 31 matched controls. At the static level, athletes exhibited significantly enhanced within-network functional connectivity in the sensorimotor, salience, cingulo-opercular, and auditory networks, together with reduced system segregation of the frontoparietal network. At the dynamic level, none of the between-group differences in flexibility, promiscuity, cohesion, or disjointedness survived correction for multiple comparisons. In exploratory analyses at uncorrected thresholds, several between-group patterns emerged, including reduced flexibility in the subcortical network, increased promiscuity in the sensorimotor network, and reduced disjointedness in the visual and auditory networks. Several static network measures and selected dynamic measures were also associated with cumulative training exposure across individuals. Overall, the statistically supported findings indicate that endurance training is primarily associated with strengthened baseline functional integration within motor, interoceptive, and cognitive-control systems. The exploratory dynamic analyses further suggest potential differences in the temporal organization of large-scale functional networks, providing hypotheses for future investigation.

PMID:42727740 | DOI:10.1016/j.neuroimage.2026.122229

Neuroimage Clin. 2026 Sep 9;52:104056. doi: 10.1016/j.nicl.2026.104056. Online ahead of print.

ABSTRACT

The clinical high-risk (CHR) state identifies individuals at elevated risk for psychosis, yet neurobiological markers of vulnerability remain incompletely characterized, particularly in African populations. Functional Network Area and Topography Analysis (FUNCATA) quantifies individualized network size and spatial organization, addressing limitations of group-average parcellations. Prior studies in schizophrenia identified dorsal attention network (DAN) enlargement and topographic abnormalities. We applied FUNCATA to a Kenyan CHR cohort to examine whether similar alterations are detectable. Twenty-four healthy controls and 63 CHR participants (ages 18-26) underwent resting-state fMRI in Nairobi. Individualized functional networks were derived using template matching. Network size and Topographic Abnormality Index (TAI) were compared between groups using ANCOVA. Associations with symptom dimensions (BPRS-derived principal components), global functioning, cognition, and longitudinal symptom trajectories were examined. CHR participants demonstrated modest left-lateralized DAN enlargement (d = 0.61) and reduced salience network (SAL) size (d = 0.50). More robust effects emerged for TAI, with significantly elevated spatial abnormalities across multiple networks, most prominently the DAN (d = 1.18), default mode network (d = 0.91) and cingulo-opercular network (d = 0.80). Larger left DAN size was associated with longitudinal worsening of general psychopathology, while SAL size was associated with unusual thought processing and role functioning. TAI measures showed limited associations with clinical outcomes after correction. These results suggest that functional network enlargement and spatial reorganization are detectable in CHR individuals within a non-Western cohort. DAN enlargement and widespread topographic abnormalities may represent early neurobiological features of psychosis vulnerability. TAI appears particularly sensitive to spatial deviations and may serve as a promising biomarker for risk stratification and longitudinal monitoring.

PMID:42727239 | DOI:10.1016/j.nicl.2026.104056

Brain Imaging Behav. 2026 Sep 11;20(5):127. doi: 10.1007/s11682-026-01197-9.

ABSTRACT

Fatigue is a prevalent non-motor symptom in Parkinson's disease (PD), yet its long-term neural substrates remain poorly understood. The aim of this study was to characterize eight-year, four-timepoint longitudinal changes in the fatigue-related brain functional connectivity (FC) in PD and examine their associations with fatigue severity. Fifty-one PD patients and 37 healthy controls (HC) were recruited. All variables were assessed at four timepoints: baseline (year-1), year-3, year-5, and year-8. Region of interest (ROI)-to-ROI analyses targeted a predefined fatigue-related network. A visual network served as a control system. Longitudinal FC effects were assessed using a 2 × 4 ANCOVA (group×time), adjusting for age, sex, and Levodopa Equivalent Daily dose. Fatigue severity was measured with the Fatigue Severity Scale. PD patients exhibited a significant progressive reduction in FC between the right dorsolateral prefrontal cortex (DLPFC) and left dorsal anterior cingulate cortex (dACC) compared with HC. Results remained significant also including depression and global cognition as covariates. Within PD, lower right DLPFC-left dACC FC was associated with higher fatigue, whereas no associations were observed in HC. The fatigue network was specifically associated with fatigue scores, but not with depression or cognition; no longitudinal or fatigue-related effects were found in the visual control network. Across eight years and four assessments, PD is characterized by a gradual disruption of prefrontal-cingulate connectivity within a key fatigue-related hub. This evolving DLPFC-dACC decoupling is linked to worsening fatigue and is specific to the fatigue network, providing preliminary evidence for a neural marker and therapeutic target for fatigue progression in PD.

PMID:42726348 | DOI:10.1007/s11682-026-01197-9

Biometrics. 2026 Jul 1;82(3):ujag151. doi: 10.1093/biomtc/ujag151.

ABSTRACT

Functional connectivity (FC) analysis of resting-state fMRI data provides a framework for characterizing brain networks and their association with participant-level covariates. Due to the high dimensionality of neuroimaging data, standard approaches often average signals within regions of interest (ROIs), which ignores the underlying spatiotemporal dependence among voxels and can lead to biased or inefficient inference. We propose to use a summary statistic-the empirical voxel-wise correlations between ROIs-and, crucially, model the complex covariance structure among these correlations through a new positive definite covariance function. Building on this foundation, we develop a computationally efficient two-step estimation procedure that enables scalable statistical inference on covariate effects on region-level connectivity. Simulation studies show calibrated uncertainty quantification and substantial gains in validity of the statistical inference over the standard averaging method. With data from the Autism Brain Imaging Data Exchange, we show that autism spectrum disorder is associated with altered FC between attention-related ROIs after adjusting for age and gender. The proposed framework offers an interpretable and statistically rigorous approach to estimation of covariate effects on FC suitable for large-scale neuroimaging studies.

PMID:42725473 | DOI:10.1093/biomtc/ujag151

Psychoradiology. 2026 Jul 30;6:kkag027. doi: 10.1093/psyrad/kkag027. eCollection 2026.

ABSTRACT

BACKGROUND: Suggestibility refers to an individual's tendency to accept, believe, and act on information or ideas presented by others with limited critical evaluation or independent judgment. It reflects the extent to which a person's behaviors, choices, thoughts, and memories can be shaped by external prompts, leading questions, or social influences. Despite its relevance to human behaviors, its neuropsychological basis remains poorly understood. In this study, we examined the behavioral, structural, and functional neural correlates of suggestibility in the domains of working memory and attentional control.

METHODS: We employed the validated Multidimensional Iowa Suggestibility Scale (MISS) to measure the suggestibility of 42 healthy female participants. They were classified into the high suggestibility (HS) (n = 21) and low suggestibility (LS) (n = 21) groups based on their MISS scores. All participants underwent fMRI while performing working memory (N-back) and attentional control (Flanker) tasks, in addition to structural and resting-state scans.

RESULTS: Behaviorally, the HS group exhibited reduced reaction time interference in the Flanker task, suggesting enhanced attentional control. Voxel-based morphometry revealed greater gray matter volume in the right superior frontal gyrus and left postcentral gyrus among HS participants. Task-based activation analyses showed increased activation in frontal, parietal, and temporal regions in the HS group. Resting-state regions of interest (ROI)-to-ROI connectivity analysis revealed a significant increase in connectivity between the salience network (right supramarginal gyrus) and default mode network (right lateral parietal cortex) in the HS group.

DISCUSSION: Our findings indicate that high and low levels of suggestibility are associated with distinct patterns of intrinsic functional connectivity. Also, suggestibility modulates attentional control, brain structure, and intrinsic functional connectivity. These findings provide important translational insights for applying suggestibility in therapeutic contexts. Future research should continue to elucidate the mechanisms underlying suggestibility and explore how these traits may be leveraged to enhance interventions across diverse populations.

PMID:42724509 | PMC:PMC13559191 | DOI:10.1093/psyrad/kkag027

Front Psychiatry. 2026 Aug 27;17:1921553. doi: 10.3389/fpsyt.2026.1921553. eCollection 2026.

ABSTRACT

BACKGROUND: Schizophrenia is characterized by substantial clinical heterogeneity, with average differences between males and females in symptom presentation, cognitive function, and treatment response. The cortico-thalamo-cerebellar circuit (CTCC) has been implicated in schizophrenia; however, whether schizophrenia-related alterations in CTCC functional connectivity vary by sex remains unclear. This study examined diagnosis-by-sex interaction effects on CTCC-related functional connectivity using resting-state functional magnetic resonance imaging.

METHODS: Resting-state fMRI data were obtained from 108 patients with schizophrenia (53 females) and 93 healthy controls (54 females). Seed-based functional connectivity (FC) analysis and independent component analysis (ICA) were used to examine group-by-sex interaction effects on CTCC-related functional organization.

RESULTS: Significant diagnosis-by-sex interaction effects were identified in several connections involving CTCC-related basal ganglia, thalamic, cerebellar, and cortical regions. Post hoc analyses indicated that male patients exhibited increased FC between basal ganglia, thalamic, or cerebellar seed regions and temporal or calcarine cortical areas. Female patients showed a different pattern, including reduced FC between primary sensory cortical regions and basal ganglia or thalamic seed regions. These findings indicate that schizophrenia-related CTCC connectivity alterations differed between male and female participants. Chlorpromazine-equivalent dose was not significantly associated with the interaction-related functional connectivity values in either female or male patients.

CONCLUSIONS: Sex moderated selected patterns of CTCC-related functional connectivity in schizophrenia. The findings represent group-level differences with substantial potential overlap between males and females and should not be interpreted as evidence of categorical brain sexual dimorphism or directional circuit mechanisms. Larger, prospectively sex-balanced studies incorporating longitudinal, dynamic, and effective-connectivity analyses are needed to confirm these findings and clarify their functional significance.

PMID:42724138 | PMC:PMC13558228 | DOI:10.3389/fpsyt.2026.1921553

Pain Res Manag. 2026;2026(1):e2433241. doi: 10.1155/prm/2433241.

ABSTRACT

BACKGROUND: Migraine is considered a common neurological disorder. Acupuncture at Zuqiaoyin (GB44) is effective in the treatment of migraine without aura, but its central mechanism is still unclear.

OBJECTIVES: The purpose is to compare the therapeutic effect and brain functional activity difference between acupuncture at GB44 and nonacupoints and explore the central affect mechanism of acupuncture in the treatment of migraine without aura.

METHODS: Our study is a randomized controlled trial. A total of 20 patients with migraine without aura were included in the study. Twelve patients received acupuncture at GB44 as the acupuncture group and eight patients received acupuncture at nonacupoints as the sham acupuncture group. Both groups received a 10-time acupuncture intervention for 1 month. Visual analogue scale (VAS) score evaluated the clinical outcomes of acupuncture. Resting-state functional magnetic resonance imaging (fMRI) and fractional amplitude of low frequency fluctuation (fALFF) analysis were adopted to compare differences of brain functional activity between the two groups.

RESULTS: We found that improvements in headache severity and migraine-related quality of life in both groups after a 4-week acupuncture intervention but better clinical improvement were observed in the acupuncture group. A decreased fALFF in the right superior frontal gyrus, right insula, and right precuneus and an increased fALFF in the left postcentral gyrus and left precuneus were observed in the acupuncture group, while a decreased fALFF was observed in the left superior frontal gyrus and left precuneus in the sham acupuncture group. The acupuncture group showed a higher fALFF in the right precentral gyrus and right precuneus than the sham acupuncture group.

CONCLUSION: Acupuncture at GB44 can significantly relieve the clinical symptoms and improve the quality of life of patients with migraine without aura. More importantly, acupuncture at GB44 can cause changes of brain activity in migraine-affected key regions, which may be one of the central mechanisms of acupuncture in the treatment of migraine without aura.

TRIAL REGISTRATION: Chinese Clinical Trial Registry: ChiCTR2000033995.

PMID:42723472 | DOI:10.1155/prm/2433241

BMC Pediatr. 2026 Aug 18;26(1):859. doi: 10.1186/s12887-026-07512-z.

ABSTRACT

BACKGROUND: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with widespread neurobiological alterations. Repetitive transcranial magnetic stimulation (rTMS) is a potential neuromodulation intervention, but its neural mechanisms remain unclear in preschool-aged children with ASD. This study aimed to use resting-state fMRI (rs-fMRI) metrics-ALFF and ReHo and behavioral assessments to investigate neural mechanisms underlying clinical response to low-frequency (1 Hz) rTMS over the left dorsolateral prefrontal cortex (DLPFC) in this population.

METHODS: Thirty-four preschool-aged children with ASD (aged 2-6 years) were recruited and randomly assigned to rTMS group (n = 17) or control group (n = 17). After dropout exclusions, 32 children completed the study (16 per group). The rTMS group received 12 weeks of low-frequency (1 Hz) rTMS over the left DLPFC in addition to conventional rehabilitation, while the control group received sham stimulation. Behavioral assessments (ABC, CARS, RBS-R, ATEC) and rs-fMRI scans for ReHo/ALFF were conducted at baseline and post-treatment.

RESULTS: The rTMS group showed significantly greater improvements in CARS (t = 2.111, P = 0.043), RBS-R (Z = - 2.175, P = 0.030), and ATEC (t = 2.093, P = 0.044) scores compared with the control group. Post-treatment rs-fMRI analysis revealed increased ReHo in the right caudate nucleus, right angular gyrus, and left anterior cingulate gyrus, and decreased ReHo in the left cerebellar Crus II, left inferior occipital gyrus, and left middle temporal gyrus. Increased ALFF was observed in the right inferior orbital frontal gyrus, right angular gyrus, and right dorsolateral superior frontal gyrus. After controlling for age, sex, and mean frame-wise displacement, the right angular gyrus ALFF remained significantly correlated with ATEC (rₚ = -0.710, P = 0.002), ABC (rₚ = -0.578, P = 0.019), and CARS (rₚ = -0.625, P = 0.009); the right caudate nucleus ReHo remained significantly correlated with ATEC (rₚ = -0.572, P = 0.020).

CONCLUSIONS: Low-frequency rTMS targeting the left DLPFC is safe and effective in improving core symptoms in preschool-aged children with ASD, possibly by enhancing spontaneous neuronal activity in cognitive/executive function-related regions. The right angular gyrus and right caudate nucleus may serve as potential neuroimaging biomarkers for treatment response.

PMID:42723030 | DOI:10.1186/s12887-026-07512-z