Most recent paper

Sci Rep. 2025 Oct 20;15(1):36500. doi: 10.1038/s41598-025-21102-6.

ABSTRACT

Multiple sclerosis (MS) often leads to mobility impairments, yet the neural mechanisms underlying these deficits remain poorly understood. This study examined whether resting-state functional connectivity (rs-FC) differs between people with MS (PwMS) and healthy controls in relation to spatiotemporal mobility performance. We hypothesized that group differences within the default mode (DMN), frontoparietal (FPN), somatomotor (SN), and visual (VIS) networks would be associated with gait and turning metrics. Twenty-nine PwMS and 28 matched controls completed a two-minute walk test, 180° walking turns, and 360° in-place turns at natural and fast speeds. fMRI data were analyzed using multivariate pattern analysis (MVPA) and post-hoc seed-to-voxel analyses for gait speed, cadence, double support time, stride length, turn duration, peak velocity, and turn angle. PwMS exhibited slower gait speed, shorter stride length, and impaired 360° turning, but no group differences in cadence, double support, or 180° turn metrics. MVPA revealed rs-FC differences across DMN, FPN, SN, and VIS networks. While rs-FC differences were evident for walking metrics, within-group associations were not significant. In contrast, 360° turn angle showed distinct within-group rs-FC associations, particularly involving VAN and DAN networks. These findings highlight turning as a sensitive task for capturing functional neural differences in MS.

PMID:41115952 | PMC:PMC12537983 | DOI:10.1038/s41598-025-21102-6

Psychother Psychosom. 2025 Oct 20:1-32. doi: 10.1159/000548961. Online ahead of print.

ABSTRACT

INTRODUCTION: Obsessive-compulsive disorder (OCD) is a chronic condition where many patients remain symptomatic despite first-line treatments such as Cognitive Behavioural Therapy and selective serotonin reuptake inhibitors. This randomised controlled trial evaluated Mindfulness-Based Cognitive Therapy (MBCT) efficacy as an augmentation strategy and its impact on brain functional connectivity.

METHODS: Sixty-eight participants with moderately symptomatic OCD were randomised into MBCT or Treatment as Usual (TAU). Clinical outcomes were evaluated using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and the Obsessive-Compulsive Inventory, alongside other relevant secondary outcomes. Data were analysed using repeated measures ANOVA to assess time * group effects. Neuroimaging functional measures (resting-state network-connectivity), were collected before and after the intervention and analysed using independent component analysis.

RESULTS: Primary outcome: MBCT significantly reduced OCD symptoms compared to TAU (31.73% vs. 8.07% Y-BOCS reduction).

SECONDARY OUTCOMES: MBCT group also experienced reductions in depressive symptoms, rumination, perceived stress and quality of life. No significant post-treatment changes were observed in resting-state connectivity. However, baseline connectivity demonstrated significant predictive value, with lower connectivity in pre-selected networks of interest, including the fronto-striatal, salience, and default-mode networks, associated with greater reductions in Y-BOCS scores.

CONCLUSION: MBCT is an effective strategy for individuals with moderately symptomatic OCD who continue to experience symptoms despite prior gold-standard treatments. While no post-treatment changes in brain functional connectivity were observed, baseline connectivity patterns predicted symptom reduction, suggesting a neural basis for MBCT response. Trial name: Mindfulness-Based Cognitive Therapy: Efficacy and fMRI-based Response Predictors in a Group of OCD Patients. ID number: NCT03128749.

PMID:41115123 | DOI:10.1159/000548961

Imaging Neurosci (Camb). 2025 Oct 15;3:IMAG.a.936. doi: 10.1162/IMAG.a.936. eCollection 2025.

ABSTRACT

Ketamine produces fast-acting antidepressant effects in treatment-resistant depression (TRD). Prior studies have shown altered functional dynamics between brain networks in major depression. We thus sought to determine whether functional brain network dynamics are modulated by ketamine therapy in TRD. Participants with TRD (n = 58, mean age = 40.7 years, female = 48.3%) completed resting-state fMRI scans and clinical assessments (mood and rumination) at baseline and 24 h after receiving 4 ketamine infusions (0.5 mg/kg) over 2 weeks. Healthy controls (HC) (n = 56, mean age = 32.8 years, female = 57.1%) received the same assessments at baseline and after 2 weeks in a subsample without treatment. A co-activation pattern (CAP) analysis identified recurring patterns of brain activity across all subjects using k-means clustering. Statistical analyses compared CAP metrics including the fraction of time (FT) spent in a brain state, and the transition probability (TP) from one state to another over time and associations with clinical improvement. Follow-up analyses compared HC and TRD at baseline. Six brain state clusters were identified, including patterns resembling the salience (SN), central executive (CEN), visual (VN), default mode (DMN), and somatomotor (SMN) networks. Following ketamine treatment, TRD patients showed decreased FT for the VN (p = 7.4E-04) and increased FT for the CEN state (p = 1.9E-03). For TP metrics, SN-CEN increased (p = 5.8E-04) and SN-VN decreased (p = 3.6E-03). Decreased FT for the SN associated with improved rumination (p = 1.9E-03). At baseline, lower FT for CEN (p = 5.70E-04) and TP for SN-CEN (p = 0.016) and higher TP for SN-VN (p = 2.60E-03) distinguished TRD from HCs. CAP metrics remained stable over time in a subsample of HCs (n = 18). These findings suggest ketamine modulates brain network dynamics between SN, CEN, and VN in TRD, which may normalize dynamic patterns seen in TRD at baseline toward patterns seen in controls. Changes in SN state dynamics may correspond to improvements in ruminative symptoms following ketamine therapy.

PMID:41113939 | PMC:PMC12529346 | DOI:10.1162/IMAG.a.936

Nat Sci Sleep. 2025 Oct 14;17:2681-2698. doi: 10.2147/NSS.S550127. eCollection 2025.

ABSTRACT

PURPOSE: Poor sleep quality is prevalent across the population and may significantly impact both physical and mental health. However, our understanding of the complex mechanisms underlying poor sleep quality is still incomplete, particularly regarding the various contributing factors. To address this, we utilized a data-driven causal discovery analysis (CDA) approach to explore causal pathways of sleep quality.

PATIENTS AND METHODS: We relied on a large sample of healthy young adults from the Human Connectome Project (HCP; n = 1206 [54% female, 56% unmarried/non-cohabiting]) to explore causal pathways of sleep quality. We first used exploratory factor analysis to cluster 122 broad phenotypic variables into 21 factors and computed the functional connectivity of 13 resting-state brain networks. Then, using Greedy Fast Causal Inference (GFCI), we simultaneously integrated the obtained phenotypic factors, brain network connectivity, and sleep quality into the causal discovery analysis and ultimately constructed a causal model.

RESULTS: The model proposes a hierarchical structure with causal effects propagating through complex interactions across multiple domains, ultimately linked to changes in sleep quality. Our causal model identified three phenotypic factors (negative affect, somaticism, and delay discounting) as directly linked to sleep quality. In addition, we examined causal models of sleep quality across gender (male and female) and relationship status (unmarried/non-cohabiting and married/cohabiting) and found some demographic-specific pathways.

CONCLUSION: Our data-driven model reveals complex mechanisms by which factors from different domains influence sleep quality and highlights several key factors that influence sleep quality, which may have important implications for the development of sleep theories and the improvement of sleep quality.

PMID:41113905 | PMC:PMC12535245 | DOI:10.2147/NSS.S550127

World J Psychiatry. 2025 Oct 19;15(10):108861. doi: 10.5498/wjp.v15.i10.108861. eCollection 2025 Oct 19.

ABSTRACT

BACKGROUND: Sepsis is a life-threatening condition defined by organ dysfunction, triggered by a dysregulated host response to infection. there is limited published literature combining cognitive impairment with topological property alterations in brain networks in sepsis survivors. Therefore, we employed graph theory and Granger causality analysis (GCA) methods to analyze resting-state functional magnetic resonance imaging (rs-fMRI) data, aiming to explore the topological alterations in the brain networks of intensive care unit (ICU) sepsis survivors. Using correlation analysis, the interplay between topological property alterations and cognitive impairment was also investigated.

AIM: To explore the topological alterations of the brain networks of sepsis survivors and their correlation with cognitive impairment.

METHODS: Sixteen sepsis survivors and nineteen healthy controls from the community were recruited. Within one month after discharge, neurocognitive tests were administered to assess cognitive performance. Rs-fMRI was acquired and the topological properties of brain networks were measured based on graph theory approaches. GCA was conducted to quantify effective connectivity (EC) between brain regions showing positive topological alterations and other regions in the brain. The correlations between topological properties and cognitive were analyzed.

RESULTS: Sepsis survivors exhibited significant cognitive impairment. At the global level, sepsis survivors showed lower normalized clustering coefficient (γ) and small-worldness (σ) than healthy controls. At the local level, degree centrality (DC) and nodal efficiency (NE) decreased in the right orbital part of inferior frontal gyrus (ORBinf.R), NE decreased in the left temporal pole of superior temporal gyrus (TPOsup.L) whereas DC and NE increased in the right cerebellum Crus 2 (CRBLCrus2.R). Regarding directional connection alterations, EC from left cerebellum 6 (CRBL6.L) to ORBinf.R and EC from TPOsup.L to right cerebellum 1 (CRBLCrus1.R) decreased, whereas EC from right lingual gyrus (LING.R) to TPOsup.L increased. The implementation of correlation analysis revealed a negative correlation between DC in CRBLCrus2.R and both Mini-mental state examination (r = -0.572, P = 0.041) and Montreal cognitive assessment (MoCA) scores (r = -0.629, P = 0.021) at the local level. In the CRBLCrus2.R cohort, a negative correlation was identified between NE and MoCA scores, with a statistically significant result of r = -0.633 and P = 0.020.

CONCLUSION: Frontal, temporal and cerebellar topological property alterations are possibly associated with cognitive impairment of ICU sepsis survivors and may serve as biomarkers for early diagnosis.

PMID:41112595 | PMC:PMC12531965 | DOI:10.5498/wjp.v15.i10.108861

Neuroimage. 2025 Oct 17:121533. doi: 10.1016/j.neuroimage.2025.121533. Online ahead of print.

ABSTRACT

BACKGROUND: Transcranial magnetic stimulation (TMS) activates neural circuits in targeted and connected areas, yet it remains unclear how "TMS-dose" relates to local or network responses, particularly outside the primary motor hand area.

METHODS: Eighteen healthy volunteers received TMS pulse-pairs (pp-TMS) of the left dorsal premotor cortex (PMd) during functional magnetic resonance imaging (fMRI) at 3 Tesla, using an inter-pulse interval of 33 ms. We mapped stimulus-response profiles across the premotor-motor network, applying pp-TMS as slow-frequency trains of pulse-pairs (i.e., blocked design) or single pulse-pairs (i.e., event-related design). Pulse-pairs were delivered at intensities of 65, 80, 95, or 110% of resting motor threshold (RMT).

RESULTS: Pooling the effects of pp-TMS across intensities revealed that both, single pulse-pairs and pp-TMS trains produced a bilateral reduction in regional activity within the targeted dorsal premotor-motor network. Dose-dependent analysis revealed a non-linear dose-response pattern, with maximal suppression of left and right PMd activity at 80% of RMT. The event-related and blocked fMRI design yielded similar results with net suppressive effects being more consistent during trains and dose-response dependencies being more consistent in response to single pulse-pairs. Auditory co-stimulation triggered bilateral increases in the auditory cortices.

CONCLUSION: Focal ppTMS may exert a net suppressive effect on neural activity within the targeted network. Network effects may follow a non-linear response pattern and may peak at relatively low stimulation intensities. These findings highlight the value of interleaved TMS-fMRI in elucidating the impact of stimulation parameters on regional and network-level brain dynamics.

PMID:41110651 | DOI:10.1016/j.neuroimage.2025.121533

Neuroimage. 2025 Oct 17:121544. doi: 10.1016/j.neuroimage.2025.121544. Online ahead of print.

ABSTRACT

AIM: Type 2 diabetes mellitus (T2DM) is a metabolic disorder associated with cognitive decline. This study investigated the interplay between altered effective connectivity (EC) in the Papez circuit, regional atrophy, and choroid plexus volume (CPV) in relation to T2DM-related cognitive deficits.

METHODS: Eighty T2DM patients and 75 healthy controls underwent multimodal MRI. Resting-state fMRI data were analyzed using spectral dynamic causal modeling (spDCM) to quantify EC between Papez circuit regions. Structural 3D-T1 images were processed to measure regional volumes and the CPV, which might serve as a proxy for glymphatic activity. Participants underwent standardized cognitive assessments to evaluate neurocognitive function.

RESULTS: T2DM patients exhibited significant EC reductions in three Papez circuit pathways: from the hippocampus (HPC) to the mammillary body (MB) (p = 0.001), from the anterior thalamic nucleus (AT) to the anterior cingulate cortex (ACC) (p = 0.005), and from the entorhinal cortex (ERC) to the HPC (p < 0.001). Structural atrophy was observed in the left hippocampus (p = 0.001) and left thalamic (p = 0.006), accompanied by CPV enlargement (p = 0.027). Notably, the HPC to MB connectivity was partially mediated by the CPV, with a significant indirect effect of 0.1456 (95% CI: 0.0335, 0.2665). The Complex Figure Test delay (CFT-delay) score was positively correlated with the reduced EC in Papez circuit pathways; however, there was a negative correlation between the CFT-delay score and the CPV (r = -0.344, p = 0.002). Furthermore, reduced EC in the Papez circuit exhibited a negative correlation with the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR).

CONCLUSION: Our study highlights the complex interplay between Papez circuit functional disruptions, structural atrophy within the circuit, as well as the CPV alterations in T2DM-related cognitive decline. These findings offer potential biomarkers for early detection of cognitive impairments and novel therapeutic targets for intervention in T2DM.

PMID:41110647 | DOI:10.1016/j.neuroimage.2025.121544

Psychiatry Res Neuroimaging. 2025 Oct 10;354:112077. doi: 10.1016/j.pscychresns.2025.112077. Online ahead of print.

ABSTRACT

BACKGROUND: Previous studies have demonstrated the efficacy of transcranial magnetic stimulation (TMS) on treating nicotine addiction. However, the underlying mechanisms remain unclear. This study aims to investigate the effects of repetitive TMS (rTMS) on nicotine addiction using resting-state functional magnetic resonance imaging (rs-fMRI).

MATERIALS AND METHODS: In this study, adult male participants with nicotine addiction were prospectively recruited, and assigned to either the rTMS group (n = 19) or Sham group (n = 12). Two groups underwent ten sessions of either real or sham rTMS treatment over a two-week period. Clinical assessments related to smoking craving and rs-fMRI scans were conducted before and after treatment. The regional homogeneity (ReHo) was utilized to explore differences in local neural synchronization between the rTMS and Sham groups.

RESULTS: After treatment, the smoking cravings were significantly reduced in two groups. Significant group-by-time interaction effects were observed in the left orbital part of the inferior frontal gyrus, left middle frontal gyrus (MFG), and right angular gyrus (AG). Post-hoc analyses revealed that, compared with pre-treatment, the rTMS group exhibited increased ReHo values after treatment in these areas, while the Sham group exhibited decreased values. Furthermore, within the rTMS group, post-treatment ReHo values in the left MFG were negatively correlated with post-treatment short Tobacco Craving Questionnaire (sTCQ)-Impulse scores. Similarly, the changes in ReHo values of the left MFG from pre- to post-treatment within the rTMS group were negatively correlated with changes in sTCQ-Impulse scores.

CONCLUSION: Our findings demonstrated that rTMS treatment may improve nicotine-related dependence by modulating local neural synchronization in the prefrontal cortex (PFC) and AG. Furthermore, ReHo values in the left MFG may serve as a promising neuroimaging biomarker for predicting nicotine addiction cessation.

PMID:41110183 | DOI:10.1016/j.pscychresns.2025.112077

Psychiatry Res Neuroimaging. 2025 Oct 16;354:112078. doi: 10.1016/j.pscychresns.2025.112078. Online ahead of print.

ABSTRACT

BACKGROUND: We tested the hypothesis that Schizophrenia (SCZ) involves a systematic breakdown in brain network organization across different levels of graph-theoretical hierarchy.

METHODS: Using resting-state fMRI from 43 SCZ patients and 63 matched healthy controls, we implemented an analytical multi-level framework. This integrated: global graph theory metrics to assess overall network topology; macronetwork metrics to measure functional specialization of large-scale systems; network-based statistics (NBS) to identify specific, altered pathways at the local level; a multigraph model to visualize hub reorganization between networks.

RESULTS: We revealed a coherent pattern of multi-level dysfunction. Globally, SCZ networks showed increased local clustering and connection density, indicating a shift toward a less efficient, overly segregated architecture. At the macroscale, sensory and salience networks displayed elevated local connectivity, while higher-order cognitive networks (e.g., DMN, DAN) showed reduced specialization and increased cross-talk. Locally, NBS identified a core subnetwork of weakened connectivity within temporal-orbitofrontal-cingulate circuits. The multigraph model synthesized these findings, showing a widespread reduction in the integrative role of key cognitive hubs.

CONCLUSIONS: Our findings establish a model of SCZ as a disorder of disintegrated brain network hierarchy, where disruptions at the level of local circuits and functional specializations collectively lead to global topological inefficiency.

PMID:41110182 | DOI:10.1016/j.pscychresns.2025.112078

Biol Psychiatry Cogn Neurosci Neuroimaging. 2025 Oct 16:S2451-9022(25)00303-9. doi: 10.1016/j.bpsc.2025.10.002. Online ahead of print.

ABSTRACT

BACKGROUND: It is unknown whether brain-based predictive models derived from sleep features are useful for the clinical diagnosis of Major Depressive Disorder (MDD).

METHODS: Using resting-state fMRI data from ABCD (Curated Data Release 3.0), we trained a connectome-based predictive model (CPM) on 35,778 pairwise connections (Pearson's r) from 2349 (234 participants with at least 1 psychiatric disorder, 2112 controls) participants aged 11-12 to predict sleep duration (measured from FitBit). Linear regression models were used to compare the predicted values from these CPMs with self-reported sleep duration and diagnostic group status in an independent cohort of 78 participants (57 MDD, 21 controls) aged 14-18.

RESULTS: The ABCD-based CPM predicted self-reported sleep duration in the independent cohort of MDD participants (partial r=0.332, p=0.009). Even though self-reported sleep duration did not significantly differ between diagnostic groups (t=0.13, p=0.90), the ABCD-based CPM successfully distinguished between diagnostic groups (partial r=0.334, p<0.001), and CPM-predicted sleep durations correlated with depression symptom severity (partial r=0.294, p<0.001). These diagnostic group differences were driven primarily by patterns of hypoconnectivity between various resting-state networks (including the default mode, frontoparietal, motor, subcortical, and visual associative networks).

CONCLUSIONS: CPMs trained to predict objective sleep duration are robust and generalizable. Intrinsic functional connectivity differences between clinically depressed and psychiatrically healthy adolescents are detectible by CPMs optimized for sleep prediction, underscoring the shared neural bases between sleep health and depression. Future work will test whether sleep-based CPMs are predictive of clinical course and if they generalize to other disorders beyond depression.

PMID:41109569 | DOI:10.1016/j.bpsc.2025.10.002

Dev Cogn Neurosci. 2025 Oct 12;76:101629. doi: 10.1016/j.dcn.2025.101629. Online ahead of print.

ABSTRACT

Preterm birth is a known risk factor for neurodevelopmental disabilities, but early neurobehavioral assessments and structural imaging often fail to predict long-term outcomes. This limitation underscores the need for alternative biomarkers that reflect early brain organization. Resting-state functional connectivity offers a powerful tool to track functional brain organization by characterizing resting-state networks (RSNs), potentially offering more sensitive biomarkers. However, most fMRI studies in infant populations use group-level analyses that average subject-specific data across several weeks of development, reducing sensitivity to subtle, time-sensitive deviations from typical brain trajectories, particularly in higher-order association networks. Using a recently introduced precision mapping approach, we estimated individual resting-state networks (RSNs) in a large cohort of term and preterm neonates from the developing Human Connectome Project. RSN connectivity strength increased linearly with age at scan, with primary sensory networks maturing earlier and higher-order association networks, including the default mode network (DMN), showing more gradual but pronounced changes, evolving from an immature organization in preterm infants to a more adult-like pattern in term-born infants. Longitudinal data from a subset of preterm infants confirmed ongoing network development shortly after birth. Despite this maturation, preterm infants did not reach the connectivity levels of term-born infants by term-equivalent age. These findings demonstrate that individualized RSN mapping captures heterogeneous developmental trajectories in the neonatal brain and highlights higher-order association networks, particularly the DMN, as promising early markers for monitoring neurodevelopmental outcomes in neonates.

PMID:41109198 | DOI:10.1016/j.dcn.2025.101629

Mov Disord Clin Pract. 2025 Oct 18. doi: 10.1002/mdc3.70391. Online ahead of print.

ABSTRACT

BACKGROUND: Apathy is a common early symptom of Parkinson's disease (PD), often co-occurring with cognitive decline and associated with fronto-striatal and mesocortico-limbic dysfunctions. Discrepancies between self- and caregiver-reported apathy have been preliminarily associated with cognitive impairments affecting patients' awareness and self-report accuracy.

OBJECTIVES: This study investigates discrepancies between PD patient- and informant-reported apathy in relation to the cognitive status (unimpaired-CU vs. impaired-CI), and explores neural correlates of apathy using magnetic resonance imaging (MRI).

METHODS: Apathy was assessed in 23 PD participants using self-report (AES-S) and informant (AES-I) versions of the Italian Apathy Evaluation Scale. Discrepancy scores (ΔAES) were compared between groups and correlated with cognitive performance. Resting-state fMRI examined associations between AES indices and connectivity from the bilateral nucleus accumbens, while whole-brain structural analyses assessed associations with gray matter (GM) volume.

RESULTS: PD-CI participants showed higher ΔAES, underestimating their apathy compared to PD-CU. ΔAES values correlated with attentional and visuospatial functioning. Higher AES-I scores were associated with hyperconnectivity between right nucleus accumbens, paracingulate, and medial frontal cortices. Structural analyses revealed associations between both AES-I and ΔAES values and GM volume in the cingulate gyrus.

DISCUSSION: These findings highlight the impact of cognitive dysfunction on apathy evaluation in PD, emphasizing the importance of caregiver perspective. Neuroimaging results further validated caregiver ratings, showing an association between fronto-striatal network changes and apathy. Further research is needed to clarify the role of such discrepancy in apathy assessment in predicting disease progression.

PMID:41108660 | DOI:10.1002/mdc3.70391

Magn Reson Med. 2025 Oct 17. doi: 10.1002/mrm.70110. Online ahead of print.

ABSTRACT

PURPOSE: To demonstrate the feasibility and performance of whole-brain blood oxygen level-dependent functional MRI (fMRI) in humans at 10.5 T by combining motion-robust three-dimensional gradient-echo echo-planar imaging, parallel transmission, and high-density radiofrequency (RF) receive coils.

METHODS: Resting-state fMRI time series were collected in healthy adults at 1.58 mm and approximately 2-s spatiotemporal resolution using a custom-built 16-channel transmit/80-channel receive RF array. Individualized parallel-transmission, spatial-spectral RF pulses were designed to achieve uniform water-selective excitation across the entire brain without the need for additional fat saturation. Images were reconstructed with navigator-guided joint motion and field correction. Reconstructed images were preprocessed using fMRIPrep and postprocessed using XCP-D pipelines. Relevant resting-state fMRI metrics were evaluated including temporal SNR (tSNR), amplitude of low-frequency fluctuation, and regional homogeneity. The results were compared with those obtained using uncorrected reconstruction (i.e., using same raw data but without motion or field correction).

RESULTS: Our motion-corrected reconstruction largely improved image quality for fMRI time series, reducing motion confounds when compared with uncorrected reconstruction. The reduction in motion confounds translated into an improvement in tSNR, with tSNR averaged across all volunteers being increased by about 11%. Our motion-corrected reconstruction also improved both amplitude of low-frequency fluctuation and regional homogeneity in most cortical surfaces and subcortical regions.

CONCLUSION: It is feasible to perform quality three-dimensional whole-brain blood oxygen level-dependent fMRI in humans at 10.5 T using a new comprehensive motion-robust imaging method. This work paves the way for promising future applications at 10.5 T aimed at studying brain function and networks with high spatiotemporal resolution.

PMID:41108198 | DOI:10.1002/mrm.70110

Transl Psychiatry. 2025 Oct 17;15(1):405. doi: 10.1038/s41398-025-03678-9.

ABSTRACT

Adolescence is a critical period of neural development and a sensitive window for the emergence of psychiatric symptoms. Resting-state functional MRI (rs-fMRI) provides a unique opportunity to investigate brain-behavior associations. However, the role of sex-specific differences in these associations remains underexplored, despite their potential to reveal heterogeneous neurobiological mechanisms and guide personalized interventions. In this study, we analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study, comprising 7,892 adolescents (9-10 years old, 3,896 females). Using Canonical Correlation Analysis (CCA) and a rigorous cross-validation framework, we identified associations between cortical-to-cortical (Cor-Cor) and cortical-to-subcortical (Cor-Sub) functional connectivity and eight symptom domains from the Child Behavior Checklist (CBCL). Unlike previous approaches, we directly examined sex differences within the brain-behavior mappings by applying separate CCA models in boys and girls to uncover differential connectivity-behavior relationships. Our analysis uncovered two reproducible components for both Cor-Cor and Cor-Sub mappings on the whole cohort (r1 = 0.130, p < 0.001, r2 = 0.122, p < 0.01 for Cor-Cor; r1 = 0.157, p < 0.001, r2 = 0.115, p < 0.01 for Cor-Sub). Importantly, sex-stratified analyses revealed distinct patterns of brain-behavior associations. Among females, high loadings on attention and thought problems were linked to high loadings on default mode network, whereas in males, attention and thought problems were linked to sensorimotor networks. Compared to females, males also had higher loadings on internalizing symptoms, such as anxious/depressed and withdrawn/depressed symptoms, coupled with lower loadings on putamen and hippocampus functional connectivity. These findings suggest there may be fundamentally different brain-behavior mappings across the sexes in adolescence, in addition to previously reported sex differences in functional connectivity and behavioral profiles. By revealing sex-specific neural correlates of psychiatric symptoms in early adolescence, this study paves the way for sex-informed strategies in clinical risk assessment and personalized treatment design.

PMID:41107246 | DOI:10.1038/s41398-025-03678-9

Brain Res Bull. 2025 Oct 15:111587. doi: 10.1016/j.brainresbull.2025.111587. Online ahead of print.

ABSTRACT

PURPOSE: To comprehensively examine static and dynamic functional connectivity density (FCD) in temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS) and MRI-negative TLE and its potential correlation with cognition.

METHODS: Fifty-three healthy controls (HC), 38 TLE-HS patients, and 51 MRI-negative TLE patients underwent MRI scans of resting-state BOLD functional imaging and 3D T1WI sequence. Static functional connectivity density (FCD) and corresponding temporal dynamic FCD (dFCD) were calculated utilizing a sliding window approach and statistically compared among groups. Further seed-based functional connectivity FC analysis and ROC curve analysis were executed. Relationships between cognitive scores and FCD or dFCD values were analyzed by Spearman correlation.

RESULTS: The TLE-HS and MRI-negative TLE both demonstrated reduced static FCD values in the temporal neocortex ipsilateral to the epileptogenic focus. However, the TLE-HS revealed larger aberrant cluster sizes of reduced FC in the ipsilateral frontal and temporal lobes. For dFCD, its elevation in the ipsilateral temporal neocortex was detected only in MRI-negative TLE. The dFCD was significantly correlated with cognitive scores and revealed a moderate discrimination ability.

CONCLUSIONS: The combination of static FCD and dFCD could provide novel and complementary evidence to help deepen our understanding of the whole brain function's impairment and compensatory mechanism in TLE. The patterns of change in FCD abnormalities were similar between TLE-HS and MRI-negative TLE, which were more pronounced and widely involved in the TLE-HS group. Furthermore, dFCD may reveal more nuanced variations in MRI-negative TLE and help in discrimination.

PMID:41106485 | DOI:10.1016/j.brainresbull.2025.111587

J Affect Disord. 2025 Oct 15:120499. doi: 10.1016/j.jad.2025.120499. Online ahead of print.

ABSTRACT

Long-term fibromyalgia syndrome (FMS) patients experience chronic pain, emotional disturbances, and poor treatment responses, yet the neural mechanisms underlying disease chronicity remain unclear. This study aimed to investigate the white matter-gray matter functional connectivity (WM-GM FC) in long-term FMS patients to explore changes in brain network communication associated with chronicity and their relationship with clinical symptoms. A total of 52 FMS patients (30 long-term, 22 short-term) and 49 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). WM-GM FC was analyzed by calculating Pearson correlation coefficients between 48 predefined white matter tracts and 82 Gy matter regions. Clinical evaluations included the Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), Visual Analogue Scale (VAS), and pain duration. The results revealed that long-term FMS patients had 64 significantly reduced WM-GM FCs compared to HCs, 44 of which involved the left uncinate fasciculus (UF) and multiple gray matter regions. No significant differences in WM-GM FC were observed between short-term FMS patients and HCs. In long-term FMS patients, FC between the left UF and several gray matter regions showed negative correlations with HAMD, HAMA, VAS, and pain duration. These findings suggest that widespread reductions in WM-GM FC in long-term FMS, particularly involving the left UF, may play a crucial role in pain modulation and emotional regulation. The study provides new insights into the neural mechanisms underlying FMS chronicity and supports the potential of WM-GM FC as a biomarker for identifying pathophysiological processes and therapeutic targets in FMS. PERSPECTIVE: Fibromyalgia syndrome (FMS) patients with prolonged symptoms often face treatment resistance and worsening emotional-pain comorbidities, yet the neural basis of chronicity remains unclear. This study explored white matter-gray matter functional connectivity (WM-GM FC) in 30 long-term FMS patients, 22 short-term patients, and 49 healthy controls. Long-term patients exhibited 64 reduced WM-GM FCs, predominantly between the left uncinate fasciculus (UF)-a tract linking emotion and pain networks-and limbic/cortical regions. These disruptions correlated with higher depression, anxiety, pain severity, and duration, while short-term patients showed no significant FC differences. The findings identify left UF dysfunction as a potential neural marker of FMS chronicity, offering insights into how prolonged pain reshapes brain connectivity. Clinically, WM-GM FC could guide early interventions to prevent progression or serve as a therapeutic target, addressing the unmet need for biomarkers in managing this debilitating disorder. This advances understanding of FMS pathophysiology and highlights pathways to mitigate its long-term societal and individual burden.

PMID:41106634 | DOI:10.1016/j.jad.2025.120499

Brain Res Bull. 2025 Oct 15:111588. doi: 10.1016/j.brainresbull.2025.111588. Online ahead of print.

ABSTRACT

BACKGROUND: Internet gaming disorder (IGD) is a behavioral addiction, as revealed by previous neuroimaging studies on gray matter volume alterations and functional connectivity abnormalities that patients with internet gaming disorder have. Combining different dimensions of resting-state functional indicators may help us to understand more about the neuropathological mechanisms of online gaming disorder.

METHODS: We conducted a systematic search in PubMed, Web of Science, and Scopus from January 2000 through December 2024 to identify eligible voxel-based morphometry(VBM) studies. Using an anisotropic seed-based D-Mapping (AES-SDM) meta-analysis approach, we compared structural brain abnormalities between IGDs and healthy controls(HCs). Subsequently, resting-state functional connectivity(rs-FC) analyses were performed on 56 IGDs and 43 HCs using meta-derived regions as seeds. In addition, we performed correlation analyses to assess the relationship between functional connectivity abnormalities and clinical features.

RESULTS: The meta-analysis showed reduced gray matter volume(GMV) in the prefrontal cortex and cingulate gyrus, alongside increased GMV in the caudate nucleus in IGD compared to HCs. Rs-FC analysis showed enhanced connectivity between the middle cingulate cortex and prefrontal, cingulate and Supplementary motor area in IGD, with functional connectivity values correlating with duration of illness; However, after correction, this correlation was not significant.

CONCLUSION: Our study suggest dysregulation of cognitive control, reward, and motor networks in IGD and emphasize the importance of prefrontal cortex and cingulate alterations in adolescent addiction mechanisms, providing insights for targeted interventions.

PMID:41106487 | DOI:10.1016/j.brainresbull.2025.111588

Neurology. 2025 Nov 11;105(9):e214298. doi: 10.1212/WNL.0000000000214298. Epub 2025 Oct 17.

ABSTRACT

BACKGROUND AND OBJECTIVES: Traumatic brain injury (TBI) is associated with widespread disruptions in functional connectivity (FC), yet how these alterations vary by injury severity remains unclear. Traditional classification systems fail to capture network-level dysfunction, limiting prognostic accuracy and targeted rehabilitation strategies. The aim of this study was to systematically evaluate fMRI-detected FC alterations after mild, moderate-severe, and severe TBI using coordinate-based meta-analysis and network-level mapping.

METHODS: A systematic search of MEDLINE/PubMed, Embase, and Web of Science was conducted to identify studies examining FC changes in TBI using fMRI. This review was not funded or prospectively registered. Studies were stratified by TBI severity and time since injury. Significant peak Montreal Neurological Institute coordinates were extracted, matched to the Yeo-17 brain network atlas, and analyzed using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI). Study quality and evidence level were assessed using an adapted NIH Quality Assessment Tool and the Oxford Centre for Evidence-Based Medicine criteria. Eligible studies included adult participants with TBI assessed using resting-state or task-based fMRI; studies lacking severity classification or involving pediatric populations were excluded.

RESULTS: Seventy-six studies were included, totaling 5,064 participants (2,993 patients with TBI, 1,914 controls; mean age 35.5 vs 35.0 years; 37.6% female overall). Mild TBI (mTBI) was the most common severity (n = 59 studies; 77.6%). Twenty-two studies contributed data for meta-analysis: 15 with resting-state fMRI and 7 with task-based fMRI. Aggregated peak coordinates most frequently mapped to subcomponents of the default mode (22.9%), ventral attention (18.8%), and somatomotor (10.1%) networks in mTBI and to the frontoparietal (36%), ventral attention (20%), and dorsal attention (14.7%) networks in moderate-severe/severe TBI. SDM-PSI identified uncorrected clusters in default mode and frontoparietal regions in mTBI and moderate-severe/severe TBI, respectively, but no clusters survived family-wise error rate correction (standardized mean difference Z score range -1.986 to 3.911, p < 0.05 uncorrected). Heterogeneity was low across analyses (I2 < 21%).

DISCUSSION: FC changes after TBI potentially involve large-scale brain networks such as the default mode, attention, and executive control networks in a severity-dependent and phase-dependent manner. Although meta-analysis revealed consistent patterns, corrected statistical significance was not achieved, highlighting the need for larger, harmonized data sets and standardized analysis pipelines in future research.

PMID:41105904 | DOI:10.1212/WNL.0000000000214298

J Alzheimers Dis. 2025 Oct 17:13872877251386844. doi: 10.1177/13872877251386844. Online ahead of print.

ABSTRACT

BackgroundResting-state functional magnetic resonance imaging (fMRI) studies in dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) have described connectivity alterations in large-scale brain networks. However, little is known about functional changes across disease stages, particularly in DLB.ObjectiveTo investigate functional connectivity of key brain networks in DLB patients at different stages, compare them to AD patients and healthy controls (HC), and examine associations with core clinical symptoms.MethodsNinety DLB patients (63 with mild cognitive impairment [MCI-DLB] and 27 with dementia [d-DLB]), 25 AD patients (11 MCI-AD and 14 d-AD) and 34 HC underwent clinical, neuropsychological and resting-state fMRI assessments. Region of interest (ROI)-to-ROI analyses were performed using the CONN toolbox (pFDR < 0.05).ResultsThe overall DLB group showed reduced functional connectivity within the salience network (SN) compared to HC, but not to the overall AD group. At the subgroup level, d-DLB patients showed reduced SN and frontoparietal network (FPN) connectivity compared to both HC and the overall AD group, whereas MCI-DLB did not significantly differ from either group. In the overall DLB group, SN connectivity correlated with fluctuation severity and FPN connectivity correlated with both REM sleep behavior disorder and cognitive decline. In the overall AD group, decreased default mode network (DMN) connectivity was associated with lower Mini-Mental State Examination scores.ConclusionsSN and FPN connectivity impairments relate to disease progression and core clinical features in DLB, whereas DMN connectivity is linked to cognitive decline in AD. These distinct patterns highlight divergent paths of network dysfunction in the two diseases.Clinical Trial: This study is part of the AlphaLewyMA cohort, registered on ClinicalTrials.gov (identifier: NCT01876459; registered on June 12, 2013).

PMID:41105629 | DOI:10.1177/13872877251386844

Hum Brain Mapp. 2025 Oct 15;46(15):e70377. doi: 10.1002/hbm.70377.

ABSTRACT

Large-scale functional brain networks have most commonly been evaluated using static methods that assess patterns of activation or functional connectivity over an extended period. However, this approach does not capture time-varying features of functional networks, such as variability in functional connectivity or transient network states that form and dissolve over time. Addressing this gap, dynamic methods for analyzing functional magnetic resonance imaging (fMRI) data estimate time-varying properties of brain functioning. In the context of resting-state neuroimaging, dynamic methods can reveal spontaneously occurring network configurations and temporal properties of such networks. Patterns of network functioning over time during the resting state may be indicative of individual differences in cognitive-affective processes such as rumination, or the tendency to engage in a pattern of repetitive negative thinking. We first introduce the current landscape of dynamic methods and then review an emerging body of literature applying these methods to the study of rumination and depression to illustrate how dynamic methods may be used to study clinical and cognitive phenomena. An emerging body of research suggests that rumination is related to altered functional flexibility of brain networks that overlap with the canonical default mode network. An important future direction for dynamic fMRI analyses is to explore associations with more specific features of cognition.

PMID:41104784 | DOI:10.1002/hbm.70377