Most recent paper

Netw Neurosci. 2025 Sep 19;9(3):1065-1086. doi: 10.1162/NETN.a.22. eCollection 2025.

ABSTRACT

Brain structure-function coupling has been studied in health and disease by many different researchers in recent years. Most of the studies have estimated functional connectivity matrices as correlation coefficients between different brain areas, despite well-known disadvantages compared with partial correlation connectivity matrices. Indeed, partial correlation represents a more sensible model for structural connectivity since, under a Gaussian approximation, it accounts only for direct dependencies between brain areas. Motivated by this and following previous results by different authors, we investigate structure-function coupling using partial correlation matrices of functional magnetic resonance imaging brain activity time series under various regularization (also known as noise-cleaning) algorithms. We find that, across different algorithms and conditions, partial correlation provides a higher match with structural connectivity retrieved from density-weighted imaging data than standard correlation, and this occurs at both subject and population levels. Importantly, we also show that regularization and thresholding are crucial for this match to emerge. Finally, we assess neurogenetic associations in relation to structure-function coupling, which presents promising opportunities to further advance research in the field of network neuroscience, particularly concerning brain disorders.

PMID:41142949 | PMC:PMC12548666 | DOI:10.1162/NETN.a.22

Int J Clin Health Psychol. 2025 Oct-Dec;25(4):100639. doi: 10.1016/j.ijchp.2025.100639. Epub 2025 Oct 15.

ABSTRACT

PURPOSES: To explore if pretreatment brain function/structure connectome could explain the response to a psychosocial intervention on resilience in breast cancer.

METHODS: Between February 2018 and October 2021, women newly diagnosed with breast cancer were retrospectively enrolled from the Be Resilient to Breast Cancer (BRBC) trial and received a supportive-expressive therapy intervention. Baseline Resting-state Functional Magnetic Resonance Imaging (rs-fMRI) combined with Diffusion Tensor Imaging (DTI) were administered and resilience was scored by 10-item Resilience Scale specific to Cancer (RS-SC-10) at baseline and after the intervention (6 months). Response to the supportive intervention on resilience was defined as > 0.5 standard deviation (SD) improvement at 6 months compared to baseline mean resilience score.

RESULTS: A total of 105 patients received intervention. At 6 months, the resilience score improved in 62.9 % (N = 66), defined as the Response group. Amygdala (53 %) and Hippocampus (15 %) in rs-fMRI and CorpusCallosum_ForcepsMinor (96 %) in DTI were recognized as the main significant brain regions associated with treatment response.

CONCLUSION: These preliminary data suggest that neuro-markers of brain function/structure connectome from MR imaging might be useful in evaluating response to behavioral interventions on resilience.

PMID:41142584 | PMC:PMC12550284 | DOI:10.1016/j.ijchp.2025.100639

Front Neurosci. 2025 Oct 10;19:1672129. doi: 10.3389/fnins.2025.1672129. eCollection 2025.

ABSTRACT

Spatial group independent component analysis (sgr-ICA) is widely used in resting-state fMRI to identify intrinsic connectivity networks (ICNs). While lower-order decompositions reveal large-scale networks, higher-order models provide finer granularity but have been limited by small sample sizes. In this study, we applied sgr-ICA with 500 components to more than 100,000 subjects with rsfMRI to generate a robust fine-grained ICN template. Using this template, we examined whole brain functional network connectivity (FNC) in 502 individuals with schizophrenia and 640 typical controls and compared the findings with a lower order multiscale template. The 500-component template yielded a large set of reliable ICNs, particularly in the cerebellar and paralimbic regions, and revealed schizophrenia-related dysconnectivity patterns that were not detected at larger spatial scales. Specifically, we observed hypoconnectivity between the cerebellar and subcortical domains (basal ganglia and thalamus) and hyperconnectivity between the cerebellar domain and the visual, sensorimotor and higher cognitive domains. These results demonstrate that very high-order ICA can capture distinct fine-grained ICNs, improving the detection of disease-related connectivity differences and enriching current multiscale ICN templates. The derived ICNs can serve as a valuable reference for future studies and potentially enhance the clinical utility of rsfMRI in psychiatric research.

PMID:41141424 | PMC:PMC12549557 | DOI:10.3389/fnins.2025.1672129

Brain Commun. 2025 Oct 24;7(5):fcaf346. doi: 10.1093/braincomms/fcaf346. eCollection 2025.

ABSTRACT

Glioma patients frequently suffer from cognitive impairments after surgery, but predicting these impairments preoperatively at an individual level remains challenging. Cognitive functions are increasingly studied from a network perspective, where an important role is played by the Default Mode Network (DMN) and Frontoparietal Network (FPN). Hypothesizing that postsurgical cognitive impairments arise from structural network vulnerabilities, we trained models using presurgical structural connectivity of DMN and FPN regions to predict postsurgical cognitive impairment. We obtained individualized structural connectomes in 63 glioma patients (grades II-IV) who underwent diffusion-weighted MRI before surgery (T0) and neuropsychological screening 3 months after surgery (T3) and, for a small majority, adjuvant treatment. Random forest classifiers were trained on a combination of baseline (sociodemographic and clinical), tumour location and structural network variables available before surgery to predict postsurgical cognitive impairment in individual patients. Classifier performance was measured as area under curve of the receiver operating characteristic (AUC-ROC), testing statistical significance via permutation testing. Predictor importance was calculated post-hoc using Shapley additive explanations for trees. Postsurgical impairment was predicted by baseline variables available at T0 (AUC = 0.69, P = 0.011), presurgical DMN degrees (AUC = 0.73, P = 0.001), presurgical FPN degrees (AUC = 0.73, P = 0.001) and combinations of network and baseline variables (AUC = 0.75, P < 0.001; AUC = 0.76, P < 0.001 for DMN and FPN, respectively), but not by tumour location only (AUC = 0.62, P = 0.068). The combination of baseline variables, DMN degrees and FPN degrees (AUC = 0.76, P < 0.001) did not improve results. Importantly, models including network variables performed better than models using baseline or tumour location variables only. The most important predictors of postsurgical cognitive impairment were older age and low connectivity of the left lateral superior frontal gyrus (DMN), right pars opercularis (FPN) and bilateral middle frontal gyrus (DMN). This study represents a step towards preoperative prediction of postsurgical cognitive impairments in individual glioma patients. Our results underscore the importance of the DMN and FPN for cognition and suggest a biomarker for cognitive resilience to damage from treatment. The success of our model illustrates the utility of individual structural connectomes for studying cognitive impairment. Future expansions, e.g. incorporating resting-state fMRI, could improve our model. Ultimately, a sufficiently accurate model could be applied in neurosurgical planning by assessing a patient's risk of postsurgical impairment from presurgical information only, improving counselling of glioma patients regarding surgical expectations.

PMID:41140809 | PMC:PMC12550501 | DOI:10.1093/braincomms/fcaf346

Front Neuroimaging. 2025 Oct 10;4:1650987. doi: 10.3389/fnimg.2025.1650987. eCollection 2025.

ABSTRACT

INTRODUCTION: Schizophrenia is extremely heterogenous, and the underlying brain mechanisms are not fully understood. Many attempts have been made to substantiate and delineate the relationship between schizophrenia and the brain through unbiased exploratory investigations of resting-state functional magnetic resonance imaging (rs-fMRI). The results of numerous data-driven rs-fMRI studies have converged in support of the disconnection hypothesis framework, reporting aberrant connectivity in cortical-subcortical-cerebellar circuitry. However, this model is vague and underspecified, encompassing a vast array of findings across studies. It is necessary to further refine this model to identify consistent patterns and establish stable imaging markers of schizophrenia and psychosis. The organizational structure of the NeuroMark atlas is especially well-equipped for describing functional units derived through independent component analysis (ICA) and uniting findings across studies utilizing data-driven whole-brain functional connectivity (FC) to characterize schizophrenia and psychosis.

METHODS: Toward this goal, a systematic literature review was conducted on primary empirical articles published in English in peer-reviewed journals between January 2019-February 2025 which utilized cortical-subcortical-cerebellar terminology to describe schizophrenia-control comparisons of whole-brain FC in human rs-fMRI. The electronic databases utilized included Google scholar, PubMed, and APA PsycInfo, and search terms included ("schizophrenia" OR "psychosis") AND "resting-state fMRI" AND ("cortical-subcortical-cerebellar" OR "cerebello-thalamo-cortical").

RESULTS: Ten studies were identified and NeuroMark nomenclature was utilized to describe findings within a common reference space. The most consistent patterns included cerebellar-thalamic hypoconnectivity, cerebellar-cortical (sensorimotor & insular-temporal) hyperconnectivity, subcortical (basal ganglia and thalamic)-cortical (sensorimotor, temporoparietal, insular-temporal, occipitotemporal, and occipital) hyperconnectivity, and cortical-cortical (insular-temporal and occipitotemporal) hypoconnectivity.

DISCUSSION: Patterns implicating prefrontal cortex are largely inconsistent across studies and may not be effective targets for establishing stable imaging markers based on static FC in rs-fMRI. Instead, adapting new analytical strategies, or focusing on nodes in the cerebellum, thalamus, and primary motor and sensory cortex may prove to be a more effective approach.

PMID:41140643 | PMC:PMC12549315 | DOI:10.3389/fnimg.2025.1650987

Neuroimage. 2025 Oct 23:121554. doi: 10.1016/j.neuroimage.2025.121554. Online ahead of print.

ABSTRACT

The increasing scale and complexity of neuroimaging datasets aggregated from multiple study sites present substantial analytic challenges, as existing statistical analysis tools struggle to handle missing voxel-data, suffer from limited computational speed and inefficient memory allocation, and are restricted in the types of statistical designs they are able to model. We introduce Image-Based Meta- & Mega-Analysis (IBMMA), a novel software package implemented in R and Python that provides a unified framework for analyzing diverse neuroimaging features, efficiently handles large-scale datasets through parallel processing, offers flexible statistical modeling options, and properly manages missing voxel-data commonly encountered in multi-site studies. IBMMA successfully analyzed a large-n dataset of several thousand participants and revealed findings in brain regions that some traditional software overlooked due to missing voxel-data resulting in gaps in brain coverage. IBMMA has the potential to accelerate discoveries in neuroscience and enhance the clinical utility of neuroimaging findings.

PMID:41138791 | DOI:10.1016/j.neuroimage.2025.121554

Addiction. 2025 Oct 25. doi: 10.1111/add.70219. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Internet gaming addiction (IGA) is associated with altered reward/punishment sensitivity and risky decision-making. Nevertheless, the underlying neural mechanisms of such changes remain poorly understood. This study examined behavioral and neural predictors of IGA tendency with multiple datasets.

DESIGN: Observational study.

SETTING AND PARTICIPANTS: A total of 1142 university students [360 males and 782 females, mean (standard deviation) age of 18.75 (1.67) years] participated in the behavior-brain cross-sectional dataset (BBC). A subset of 303 BBC participants [71 males and 232 females, baseline mean age of 18.84 (1.72) years] participated in the behavior longitudinal dataset (BL).

MEASUREMENTS: The Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ) assessed sensitivity to reward and punishment stimuli. The Internet Game Addiction Questionnaire assessed levels of addiction symptoms in the context of internet games. The Iowa Gambling Task (IGT) assessed risky decision-making behavior. Resting-state functional magnetic resonance imaging (MRI) data were preprocessed using standard pipelines and analyzed based on Yeo's seven-network parcellation template, with particular focus on the Limbic Network (LN) and its functional connectivity patterns. Statistical analyses included Spearman correlation, structural equation modeling and cross-lagged panel models.

FINDINGS: Cross-sectional analyses revealed that the IGT net score (NS) was negatively associated with reward sensitivity (RS, rho = -0.181, P = 0.022), which was positively associated with punishment sensitivity (PS, rho = 0.125, P < 0.001). PS positively predicted IGA tendency (β = 0.180, P < 0.001). Additionally, LN strength exhibited a positive correlation with RS (rho = 0.077, P < 0.001) and a negative correlation with PS (rho = -0.045, P = 0.090). Moreover, the functional connectivity strength between LN and other functional networks was positively associated with RS. Longitudinal analyses demonstrated that (1) the IGT net score at the first time point (T1) negatively predicted RS at the second time point (T2, β = -0.123, P = 0.031), (2) RS at T1 positively predicted IGA tendency at T2 (β = 0.100, P = 0.019), (3) PS at T1 negatively predicted RS at T2 (β = 0.085, P = 0.056) and (4) LN strength at T1 directly predicted RS and PS at T1 (RS: β = 0.126, P = 0.027; PS: β = -0.104, P = 0.064), as well as RS at T2 (β = 0.079, P = 0.080).

CONCLUSION: Internet gaming activity net score appears to be negatively correlated with reward sensitivity. Punishment sensitivity appears to be positively correlated with tendency toward internet gaming activity. There appears to be a positive correlation between reward sensitivity and punishment sensitivity.

PMID:41137797 | DOI:10.1111/add.70219

Psychiatry Res Neuroimaging. 2025 Oct 16;354:112080. doi: 10.1016/j.pscychresns.2025.112080. Online ahead of print.

ABSTRACT

The pathophysiology of schizophrenia and its associated symptoms remains poorly understood despite decades of research utilizing diverse neuroimaging techniques. Recent advancements, such as the analysis of dynamic functional connectivity in resting-state fMRI signals and the application of generative whole-brain models - computational psychiatry tool, offer novel insights into the disorder. In this exploratory study we applied a recently developed phenotypic fitting approach for whole-brain modeling to investigate functional connectivity dynamics correlates of schizophrenia symptoms. Our findings showed that higher hallucination severity was strongly correlated with functional connectivity dynamics resembling those generated by a dynamic mean field model operating with elevated excitation/inhibition balance.

PMID:41135259 | DOI:10.1016/j.pscychresns.2025.112080

Pediatr Radiol. 2025 Oct 24. doi: 10.1007/s00247-025-06422-z. Online ahead of print.

ABSTRACT

BACKGROUND: Abnormal diffusion tensor imaging (DTI) metrics have been reported both near and distant from non-hemorrhagic punctate white matter lesions, suggesting abnormal brain connectivity.

OBJECTIVE: To evaluate the effect of non-hemorrhagic punctate white matter lesions on both structural and functional brain connectivity in preterm infants.

MATERIALS AND METHODS: DTI and resting-state functional magnetic resonance imaging (rs-fMRI) data acquired around term-equivalent age were analyzed using graph theory in nine preterm infants with non-hemorrhagic punctate white matter lesions (gestational age: mean±SD, 31.5 weeks±2.5 weeks) and nine gestational age-matched controls (mean, 31.4 weeks±2.5 weeks).

RESULTS: Both groups exhibited modularity, small-world topology, and rich-club organization. Compared with controls, infants with non-hemorrhagic punctate white matter lesions showed increased diffusion efficiency (0.0098±0.0003 vs. 0.0093±0.0003, P=0.03) in functional connectivity. In structural connectivity, the non-hemorrhagic punctate white matter lesions group demonstrated (a) increased betweenness centrality in the opercular part of the right inferior frontal gyrus (227.3±93.9 vs. 164.9±3.2, P<0.01); (b) increased characteristic path length in the left superior parietal lobe (48.7±3.1 vs. 46.9±3.1, P<0.01), left inferior parietal lobe (53.0±3.3 vs. 50.8±3.5, P<0.01), and right angular gyrus (61.1±4.3 vs. 55.8±4.3, P<0.01); and (c) increased participation coefficient in the inferior temporal gyrus (0.14±0.20 vs. 0.03±0.09, P<0.01).

CONCLUSIONS: In preterm infants, non-hemorrhagic punctate white matter lesions appear to disrupt modularity in functional networks and structural connectivity in the dorsal visual stream, with compensatory changes in the ventral stream. They are also associated with increased structural connectivity in regions linked to risk aversion.

PMID:41134347 | DOI:10.1007/s00247-025-06422-z

Neurosurgery. 2025 Oct 24. doi: 10.1227/neu.0000000000003823. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: Middle fossa arachnoid cysts (MFACs) are congenital benign lesions for which the indication for surgical intervention remains controversial. Although numerous studies have demonstrated that surgery can improve cognitive function in affected children, investigations into the neural mechanisms underlying these improvements are scarce. Our aim was to quantify neurocognitive outcomes and functional brain network alterations before and after microsurgical fenestration of MFAC in children.

METHODS: We acquired resting-state functional MRI data from 18 pediatric MFAC patients both preoperatively and at a mean of half year postoperatively, and obtained preoperative and postoperative cognitive test scores in 13 of these children. Twelve age-matched and sex-matched healthy participants served as controls. As primary outcome measures, we computed the amplitude of blood oxygen level-dependent fluctuations across multiple frequency bands and seed-based functional connectivity within the contralateral hemisphere.

RESULTS: We observed significant postoperative improvements in cognitive function among the children. Neuroimaging demonstrated that spontaneous neural activity and functional-connectivity strength were reduced across multiple frequency bands in the contralateral hemisphere-changes that may correlate the observed cognitive gains. By contrast, preoperative comparisons with healthy controls revealed elevated spontaneous activity and enhanced connectivity across the same bands in patients' contralateral hemispheres. These findings suggest that surgical decompression induces large-scale reorganization of brain networks, promoting normalization of neural function, potentially through cross-frequency modulation.

CONCLUSION: Microsurgical decompression of MFAC in children yields cognitive improvements and drives large-scale network reorganization, normalizing contralateral hyperactivation through cross-frequency modulation. These findings support surgical consideration even in minimally symptomatic cases, though further studies with larger cohorts are warranted.

PMID:41134016 | DOI:10.1227/neu.0000000000003823

Ann Clin Transl Neurol. 2025 Oct 24. doi: 10.1002/acn3.70231. Online ahead of print.

ABSTRACT

AIM: Multiple sclerosis is an autoimmune demyelination disease that is seen especially in the young population and has a progressive course, causing motor, sensory, and cognitive deficits. In the literature, the pathogenesis of MS disease and the interconnection between the immune and central nervous system in the disease have not been fully revealed. Recent studies indicate that gray matter damage, as well as white matter lesions, are frequently seen in MS patients. Based on this background, the present study aimed to explore whether relapsing-remitting MS patients in the attack phase demonstrate different patterns of functional connectivity compared to those in a stable phase.

MATERIAL AND METHOD: For this purpose, resting-state fMRI findings of the attack (n = 5) and stable (n = 14) groups were examined.

RESULTS: Compared to stable patients, the attack group appeared to show increased functional connectivity in several gray matter structures, including the left fusiform, posterior cingulate, orbitofrontal cortex, left supramarginal gyrus, thalamus, and precuneus.

CONCLUSION: The findings indicate that patients in the inflammatory phase may exhibit increased activation in distinct gray matter regions relative to those not in the attack phase. This pattern might reflect the development of compensatory functional connections aimed at limiting potential clinical damage during relapse. Moreover, considering the diverse roles of these regions, their involvement could hypothetically be linked to immune-related processes, a possibility that warrants further investigation in larger cohorts.

PMID:41133481 | DOI:10.1002/acn3.70231

Front Integr Neurosci. 2025 Oct 8;19:1506742. doi: 10.3389/fnint.2025.1506742. eCollection 2025.

ABSTRACT

OBJECTIVE: This study utilized resting-state functional magnetic resonance imaging (rs-fMRI) to investigate changes in the spontaneous activity of the default mode network (DMN) in patients with primary dysmenorrhea (PD) through amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) analyses, aiming to explore their relationship with emotional regulation.

METHODS: A total of 14 PD patients (the PD group) and 24 healthy controls matched by age, education, and gender (the HC group) underwent rs-fMRI scans. First, changes in ALFF were calculated for the PD group in comparison to the HC group, and brain regions with ALFF differences were used as regions of interest (ROIs). Subsequently, rs-fMRI was employed to detect differences in FC intensity between the two groups. Nine PD patients completed neuropsychological scale assessments, and correlations between their ALFF and FC values were analyzed.

RESULTS: Compared to the HC group, the PD group exhibited decreased ALFF in the middle temporal gyrus, temporal pole, and superior temporal gyrus on the left side. Using the temporal pole as the ROI, the PD group also showed decreased connectivity between the temporal pole and the superior frontal gyrus (SFG), dorsolateral supplementary motor area (SMA), and precentral gyrus on the right side. A trend suggesting a positive correlation between ALFF values and anxiety was observed.

CONCLUSION: PD patients exhibited multidimensional functional changes in the brain. ALFF and FC may serve as sensitive biomarkers for distinguishing PD patients from healthy individuals.

PMID:41133258 | PMC:PMC12540432 | DOI:10.3389/fnint.2025.1506742

Front Neurol. 2025 Oct 8;16:1659200. doi: 10.3389/fneur.2025.1659200. eCollection 2025.

ABSTRACT

PURPOSE: This study investigates glymphatic system dysfunction in primary open-angle glaucoma (POAG) patients and explores its potential role in the progressive decline of visual function associated with the disease.

METHODS: This prospective study compared 47 primary open-angle glaucoma (POAG) patients and 50 healthy controls (HCs) using multimodal MRI, including DTI, T1/T2-weighted imaging, and resting-state fMRI. Group differences in brain morphometry, spontaneous activity, perivascular space (PVS) volume, and DTI-ALPS index were analyzed, with regression and mediation models exploring their relationships. Ocular parameters (intraocular pressure, RNFL thickness, cup-to-disc ratio, visual field) were correlated with fMRI findings, particularly PVS and ALPS metrics.

RESULTS: Compared to HCs, POAG patients exhibited significantly reduced cortical thickness, lower volume-wise Resting-state fMRI (Rs-fMRI) concordance (p < 0.001) and voxel-wise Rs-fMRI concordance (p < 0.05) in local intracranial regions, lower bilateral ALPS indices (p < 0.001), and higher volume fraction of the lateral ventricle body perivascular space (LVB-PVS) (p < 0.001). Linear regression models showed significant associations among left RNFL thickness, left ALPS index, LVB-PVS volume fraction, and cortical thickness of the left lingual gyrus (LING.L) (p < 0.05). Mediation analysis revealed that the left ALPS index partially mediated the associations between volume-wise Rs-fMRI concordance, cortical thickness of LING.L, and RNFL thickness. Furthermore, the ALPS index significantly mediated the relationship between LING.L cortical thickness and LVB-PVS volume fraction. However, no significant correlation was found between ALPS and the degree of visual field defect.

CONCLUSION: The reduced ALPS index in POAG patients suggests impaired glymphatic clearance, which may impair metabolic clearance and contribute to RNFL damage, influencing disease progression.

PMID:41132877 | PMC:PMC12540159 | DOI:10.3389/fneur.2025.1659200

Netw Neurosci. 2025 Jul 29;9(3):896-912. doi: 10.1162/netn_a_00457. eCollection 2025.

ABSTRACT

In fMRI research, graphical models are used to uncover complex patterns of relationships between brain regions. Connectivity-based fMRI studies typically analyze nested data; raw observations, for example, BOLD responses, are nested within participants, which are nested within populations, for example, healthy controls. Often, studies ignore the nested structure and analyze participants either individually or in aggregate. This overlooks the distinction between within-participant and between-participant variance, which can lead to poor generalizability of results because group-level effects do not necessarily reflect effects for each member of the group and, at worst, risk paradoxical results where group-level effects are opposite to individual-level effects (e.g., Kievit, Frankenhuis, Waldorp, & Borsboom, 2013; Robinson, 2009; Simpson, 1951). To address these concerns, we propose a multilevel approach to model the fMRI networks, using a Gaussian graphical model at the individual level and a Curie-Weiss graphical model at the group level. Simulations show that our method outperforms individual or aggregate analysis in edge retrieval. We apply the proposed multilevel approach to resting-state fMRI data of 724 healthy participants, examining both their commonalities and individual differences. We not only recover the seven previously found resting-state networks at the group level but also observe considerable heterogeneity in the individual-level networks. Finally, we discuss the necessity of a multilevel approach, additional challenges, and possible future extensions.

PMID:41132689 | PMC:PMC12543299 | DOI:10.1162/netn_a_00457

Netw Neurosci. 2025 Jul 29;9(3):969-989. doi: 10.1162/netn_a_00461. eCollection 2025.

ABSTRACT

Functional MRI (fMRI) and diffusion-weighted imaging (DWI) help explore correlations between structural connectivity (SC) and functional connectivity (FC; SC-FC coupling). Studies on mild cognitive impairment (MCI) and Alzheimer's disease (AD) observed coupling disruptions, co-occurring with cognitive decline. Advanced "fixel-based" analyses improved DWI's accuracy in assessing microstructural and macrostructural features of white matter (WM), but previous aging coupling studies commonly defined SC via tensor-based tractography and streamline counts, thereby missing fiber-specific information. We investigated different types of fixel-FC coupling and their relation to cognition in 392 participants (Agemean = 73; 207 females) from the ADNI. Two hundred twenty-five controls, 142 MCI, and 25 AD with diffusion-weighted and resting-state fMRI scans were analyzed. Structural connectomes were constructed using average fixel metrics (fiber density (FD), fiber-bundle cross-section log, and combined [FDC]) as edges. SC-FC coupling for each SC metric was calculated at overall network, edge, and node levels. Overall DMN, node- and edge-specific coupling differences were found across SC measures and groups. DMN nodal coupling significantly predicted Mini-Mental Status Examination score and verbal memory. In conclusion, different types of fixel-based coupling alterations can be observed across the neurocognitive aging spectrum, in particular, FD-FC and FDC-FC coupling between DMN regions are associated with cognitive functioning.

PMID:41132687 | PMC:PMC12543303 | DOI:10.1162/netn_a_00461

Front Syst Neurosci. 2025 Oct 8;19:1654795. doi: 10.3389/fnsys.2025.1654795. eCollection 2025.

ABSTRACT

BACKGROUND: The pathophysiology of primary blepharospasm (BSP) remains incompletely understood. This study aimed to characterize whole-brain functional network topology in treatment-naive BSP patients.

METHODS: Thirty-nine treatment-naive BSP patients and 39 matched healthy controls (HCs) underwent resting-state fMRI. Graph theoretical analysis was applied to assess global and nodal network metrics. Network-Based Statistics (NBS) identified subnetworks with altered functional connectivity (FC). Correlations between network metrics and clinical variables [Jankovic Rating Scale (JRS), illness duration] were explored.

RESULTS: Compared to HCs, BSP patients exhibited significantly lower local efficiency [p = 0.0002, false discovery rate (FDR) corrected], while global efficiency, characteristic path length, clustering coefficient, normalized clustering coefficient, normalized characteristic path length, or small-worldness were preserved (all p > 0.05, FDR corrected). Nodal analysis revealed decreased efficiency/degree in the bilateral thalamus and left supplementary motor area, and increased efficiency/degree in the bilateral precentral gyri, right postcentral gyrus, and left insula (all p < 0.05, FDR corrected). NBS identified subnetworks with altered FC across sensorimotor, limbic-subcortical, frontoparietal, and default mode networks, featuring both hyper- and hypo-connectivity (p < 0.05, NBS-corrected). Notably, left thalamic efficiency negatively correlated with illness duration (r = -0.481, p = 0.0019), and right precentral gyrus efficiency positively correlated with JRS total score (r = 0.395, p = 0.0129).

CONCLUSION: BSP is characterized by complex functional network disruptions, including impaired local information processing, altered nodal importance in key motor and relay hubs, and widespread connectivity changes. These findings reinforce BSP as a network disorder. These network alterations may serve as objective markers for disease progression and could guide the development of targeted neuromodulation therapies.

PMID:41132214 | PMC:PMC12540509 | DOI:10.3389/fnsys.2025.1654795

Front Psychiatry. 2025 Oct 8;16:1660550. doi: 10.3389/fpsyt.2025.1660550. eCollection 2025.

ABSTRACT

BACKGROUND: Resting-state fMRI studies in postpartum depression (PPD) have reported voxel-wise alterations in measures of neural amplitude and synchronization, yet scarce meta-analysis has quantitatively synthesized these findings. We performed a coordinate-based meta-analysis to identify convergent amplitude and synchronization dysfunction in PPD.

METHODS: We conducted a comprehensive search for whole-brain voxel-wise resting-state fMRI studies comparing PPD patients with healthy postpartum controls that reported local amplitude or synchronization metrics. Peak coordinates were analyzed using the Anisotropic effect size-signed differential mapping to delineate whole-brain functional alterations.

RESULTS: Ten studies (288 PPD patients, 279 controls) contributed 62 peak foci. Our analysis revealed that PPD patients exhibited increased activity in the left fusiform gyrus (FFG.L), left middle occipital gyrus (MOG.L), while showing decreased activity in the left anterior cingulate gyrus (ACG.L), the right superior temporal gyrus (STG.R), the right insula (INS.R) and the right precentral gyrus (PreCG.R) compared to healthy subjects. Jackknife sensitivity analysis indicated minimal impact on the overall results when eliminating any single study. Meta-regression analysis revealed a correlation between MOG.L functional activity and Edinburgh postnatal depression scale scores.

CONCLUSION: Abnormally elevated functional activity in the FFG.L, MOG.L, along with reduced activity in the ACG.L, STG.R, INS.R and PreCG.R, may serve as potential biomarkers for PPD. Additionally, abnormal functional activity in the visual cortex, and the prefrontal cortex-limbic system may be associated with PPD.

PMID:41132202 | PMC:PMC12540480 | DOI:10.3389/fpsyt.2025.1660550

Biol Psychiatry. 2025 Oct 21:S0006-3223(25)01535-5. doi: 10.1016/j.biopsych.2025.10.015. Online ahead of print.

ABSTRACT

BACKGROUND: The impact of acute cannabis exposure on brain function and cognitive performance varies among individuals. Acute effects of cannabis on behavior may be absent or benign in chronic users while occasional users experience significant impairment in day to day operations. It is hypothesized that repeated cannabis use induces neuroadaptations leading to tolerance and desensitization, although the precise mechanisms underlying these adaptations remain unclear.

METHODS: This study investigated acute and persistent effects of vaporized cannabis on brain dynamics in a placebo-controlled neuroimaging trial involving occasional (N=23) and chronic cannabis users (N=20). Functional resting-state data were collected to assess dynamic functional connectivity changes during intoxication and their association with attentional performance and normative cannabinoid receptor 1 (CB1) density.

RESULTS: Cannabis intoxication induced significant acute alterations in the dynamics of brain network organization, as shown by a reduced occurrence of a hyperconnected brain state in both user groups. Chronic users also displayed decreased segregation of brain networks, independent from treatment condition, suggesting persisting neuroadaptations. Dynamic reconfiguration of hyperconnected brain motifs correlated with attentional performance, which was most impaired in occasional users, indicating tolerance in chronic users. Both the acute and persisting effects of cannabis on dynamic brain state organization were significantly associated with spatial CB1 receptor density.

CONCLUSION: Acute cannabis-induced cognitive impairment is influenced by (persistent) network reconfigurations and CB1 receptor density. These findings emphasize the relevance of neural dynamics and individual neuroadaptations to (prolonged) cannabis use when assessing the behavioral effects of cannabis in therapeutic, legal and societal settings.

PMID:41130555 | DOI:10.1016/j.biopsych.2025.10.015

J Neurosci. 2025 Oct 23:e0499252025. doi: 10.1523/JNEUROSCI.0499-25.2025. Online ahead of print.

ABSTRACT

With extensive anatomical interconnections with the cerebral cortex, the cerebellum is well-positioned to coordinate communication between cortical regions. Because different cerebellar subregions interconnect with distinct cortical networks, the impact of regional cerebellar activity should be network-specific. However, it is unclear whether or how cerebellar modulation impacts the functional connectivity of human cerebral cortical networks. To test this, young adults (n=33, 21.2±3.1 years, 22M/11F) were randomly assigned to receive 20min of 1.5mA transcranial direct current stimulation (tDCS) targeting either the posterior midline (n=17) or right posterolateral cerebellum (n=16). Each participant received anodal (excitatory), cathodal (inhibitory) or sham tDCS during separate MRI sessions. We analyzed post-tDCS resting-state fMRI data to determine whether modulating different cerebellar subregions impacted resting-state functional connectivity (FC) of distinct cortical networks. Multivariate Pattern Analyses revealed that posterior midline tDCS primarily modulated FC in the default mode network (DMN), while posterolateral cerebellar tDCS altered FC in the frontoparietal network (FPN). Seed-based connectivity analyses confirmed that posterior midline modulation increased within-network DMN FC while decreasing FC between DMN, visual, and somatomotor networks. In contrast, posterolateral cerebellar tDCS strengthened frontoparietal and attentional network FC while decoupling FPN-DMN and FPN-visual networks. These results support the hypothesis that the cerebellum modulates cortico-cortical connectivity and further suggest that the posterior midline modulates the DMN while the posterolateral cerebellum shifts the brain toward a task-ready cognitive state. These findings provide insight into how the cerebellum influences the cerebral cortex and have clinical implications for targeted interventions for a range of neurological and psychiatric conditions.Significance statement The cerebellum is extensively interconnected with the cerebral cortex, and it has been proposed that the cerebellum modulates cortico-cortical functional interactions. Confirming this, transcranial direct current stimulation (tDCS) targeting two cerebellar subregions modulated functional connectivity in different cortico-cortical networks. TDCS targeting the posterior cerebellar midline altered functional connectivity in regions of the default mode network. Right posterolateral cerebellar tDCS primarily impacted the functional connectivity of the fronto-parietal network. These data confirm that the cerebellum modulates interactions between cortical networks in a topographically-specific manner and could inform therapeutic interventions using cerebellar neuromodulation for a range of neurological and psychiatric conditions.

PMID:41130799 | DOI:10.1523/JNEUROSCI.0499-25.2025

Epilepsy Behav. 2025 Oct 22;173:110786. doi: 10.1016/j.yebeh.2025.110786. Online ahead of print.

ABSTRACT

OBJECTIVE: Juvenile myoclonic epilepsy (JME) is characterized by myoclonic seizures mostly occurring after awakening, and sleep deprivation is a common predisposing factor. This study aims to investigate the resting-state functional connectivity (rs-FC) of key regions in the sleep-wake circuit in patients with JME, focusing on the suprachiasmatic nucleus (SCN), posterior hypothalamus, and the ascending reticular activating system (ARAS).

METHODS: This study involved 33 patients with JME and 40 age and gender-matched healthy controls (HCs). All participants underwent sleep and cognitive learning-related neuropsychological scales and resting-state functional magnetic resonance imaging (rs-fMRI), and seed-based functional connectivity analysis was performed on regions within the sleep-wake circuit, including the SCN, posterior hypothalamus, and ARAS nuclei.

RESULTS: In patients with JME, significant alterations in rs-FC were observed, including increased connectivity between the left SCN and the left medial superior frontal gyrus (PFDR-corr = 0.002), and altered connectivity in the laterodorsal tegmental nucleus (LTN), periaqueductal gray (PAG), and parabrachial complex (PBC). LTN seed displayed significant hyperconnectivity with the cluster in the frontal lobe (right superior frontal gyrus, bilateral supplementary motor area, bilateral precentral gyrus, bilateral paracentral lobule), the parietal lobe (bilateral postcentral gyrus, right superior parietal lobule), right superior temporal gyrus, the occipital lobe (bilateral cuneus, bilateral superior occipital gyrus, bilateral calcarine fissure), and midbrain in JMEs (PFDR-corr< 0.001), and revealed significantly decreased rs-FC with pons (PFDR-corr< 0.001) compared to HCs. Furthermore, PAG seed showed significant hyperconnectivity with the left red nucleus and the dorsal raphe nucleus (PFDR-corr< 0.001) compared to HCs. Lastly, PBC seed showed significant hyperconnectivity with pons, and significantly decreased rs-FC with midbrain, cerebellar vermis, and bilateral locus coeruleus (PFDR-corr< 0.001).

CONCLUSIONS: The study reveals significant alterations in the functional connectivity of brain regions involved in the sleep-wake circuit in patients with JME, providing valuable information for understanding myoclonic seizures after awakening and seizures triggered by sleep deprivation.

PMID:41129955 | DOI:10.1016/j.yebeh.2025.110786