Alzheimer's disease (AD) emerges from multi-scale interactions between molecular pathology and disruptions in large-scale brain network dynamics. Understanding how these processes co-evolve and relate to disease stages is essential for advancing complex systems models of aging and AD, and for developing system-informed interventions. However, progress has been limited by a lack of large-scale longitudinal data. To address this, we examined the longitudinal relationship between subsystems of the default mode network (DMN) (posterior DMN, ventral DMN, anterior dorsal DMN) using task-free functional MRI (fMRI) and amyloid positron emission tomography (PET) imaging in a large longitudinal cohort spanning the clinico-biological spectrum of AD (n = 1,451; 2,763 time points) using mixed-effect models. We also assessed whether patterns of DMN connectivity predicted conversion to amyloid positivity, mild cognitive impairment (MCI), and dementia using Cox proportional hazards models. Our findings reveal a dynamic interplay between amyloid accumulation and connectivity within and between DMN subsystems, with both hyper- and hypoconnectivity emerging across DMN subsystems in association with increasing amyloid burden. Importantly, survival models showed that DMN connectivity patterns predicted conversion to critical stages of the disease, including not only conversion to MCI and dementia, but also conversion to amyloid positivity in otherwise clinically unimpaired individuals who were amyloid negative at baseline. These associations were independent of age, APOE4 status, sex, education, and in-scanner motion. These results support a model in which breakdowns in tightly regulated feedback loops governing DMN physiology represent a core systems-level pathophysiology of AD. Notably, this functional dyshomeostasis precedes detectable amyloidosis on imaging. Future studies should focus on the development of robust biomarkers of brain function that can be applied at the individual level, which could in turn help support the development of therapeutic approaches targeting system-level pathophysiology.

Default mode network connectivity is associated with executive and language performance in mild cognitive impairment.

This study examines differences in large-scale resting-state networks (RSNs) connectivity between women who survived intimate partner violence (IPVAW) and non-victims. It also explores the association between specific resting-state functional connectivity (rs-FC) patterns in IPVAW survivors and both the severity of experienced violence and relevant clinical symptoms, including depression, anxiety, and posttraumatic stress disorder (PTSD). Participants underwent resting-state fMRI and completed self-report assessments on the severity of the IPVAW experience, adverse childhood experiences, PTSD, anxiety, depression, and alcohol use. Independent Component Analysis (ICA) was used to characterize RSNs. Between-group differences were examined using a T-test while controlling for age and level of education. Exploratory correlations were conducted to examine associations between the rs-FC patterns in IPVAW survivors and the severity of violence and clinical measures. IPVAW survivors showed less rs-FC within the default mode network (DMN) and dorsal attention network (DAN). They also showed greater rs-FC of the cerebellum with the posterior DMN, salience network (SN), and posterior sensorimotor network (pSMN) compared to non-victims. Specific rs-FC patterns in IPVAW survivors were significantly associated with clinical symptoms. The findings indicate that IPVAW survivors show specific intrinsic functional connectivity that is associated with psychopathological symptoms. The present study contributes to a deeper understanding of these neural correlates and may support intervention programs aimed at addressing long-term sequelae of IPVAW.

Background and Objectives: Mild cognitive impairment (MCI) is heterogeneous within the Alzheimer's disease (AD) continuum, and categorical labels may not reflect biological variability. We evaluated whether multimodal machine learning using routine clinical data and neuroimaging could support biologically informed enrichment across MCI and AD in a real-world memory clinic cohort. Methods: We analyzed 474 patients (1547 visits) with clinical and cognitive measures, laboratory parameters, MRI regional volumes, and FDG-PET regional uptake. Elastic Net and gradient boosting models were trained using nested cross-validation with strict patient-level separation. Results: Model discrimination improved as additional data modalities were added, and FDG-PET contributed the largest performance improvement. Hypometabolism in posterior default mode network regions consistently emerged as the most influential predictor. In the MCI subgroup, AD-like scores showed a continuous distribution consistent with biological enrichment. Conclusions: Multimodal models may provide an interpretable enrichment framework in heterogeneous memory clinic populations.

Alterations of static and dynamic brain functional network connectivity in preschool children with autism spectrum disorder.

Transcranial magnetic stimulation (TMS) is a novel approved therapy for treatment-resistant depression. Little is known about its neurocognitive mechanisms of action. The existing literature has focused on resting-state neuroimaging. It therefore remains unknown what information processing changes TMS induces during treatment that drive mood change. Here we tested the hypothesis that transcranial magnetic stimulation (TMS) treatment changes emotional bias, increasing the focus on positive (versus negative) information processing. 49 patients with major depression received 20 daily sessions of open-label intermittent theta-burst TMS to left dorsolateral prefrontal cortex. Emotional bias was measured using behavioural and functional magnetic resonance imaging tasks of emotional face processing, both at baseline and after eight days of treatment. We tested whether early changes in these measures after the first week predicted clinical outcome at the end of treatment (4 weeks). As predicted, an increase in behavioural and neural measures of positive bias after one week predicted clinical response after four weeks of treatment. Behaviourally, response to TMS treatment was associated with a bias towards interpreting ambiguous facial expressions as positive. Neurally, clinical improvement was related to increased neuroimaging response for the contrast of positive versus negative emotional faces in rostral anterior cingulate cortex (rACC), and a positive bias in task-related functional connectivity between rACC and posterior default mode network. These early neurocognitive changes predicted clinical outcomes after four weeks of treatment, beyond early symptom reduction. Thus, clinical response to TMS treatment was linked to increases in positive bias in emotional processing early during treatment which might represent a neurocognitive mechanism of TMS depression treatment, potentially neurally distinct from antidepressant drugs.

Episodic sequence memory is crucial for daily functioning and typically declines during aging. However, the neural mechanisms underlying this decline remain poorly understood. We examined the resting-state functional connectivity (FC) correlates of sequence memory in healthy older adults (OA), with a young adult (YA) group included for comparison. Thirty-eight OA (mean ± SD age: 69.9 ± 3.9years; 24 women) and 20 YA (mean ± SD age: 24.2 ± 3.4years; 14 women) completed a sequence memory task and resting-state functional magnetic resonance imaging (rsfMRI). Participants encoded sequences of greyscale pictures presented in colored frames and retrieved their sequential order. We compared the sequence memory performance (% correct) between age groups and examined associations between performance and seed-based FC patterns within each group, focusing on hippocampal and default mode network (DMN) regions. OA exhibited poorer sequence memory performance than YA. In OA, lower performance was associated with reduced FC between the left posterior hippocampus and DMN hubs, and the DMN and right posterior parietal cortex, suggesting that reduced intrinsic coupling within memory networks and between memory and attention networks contributes to sequence memory decline in aging. In YA, superior sequence memory performance correlated with higher FC between the left posterior hippocampus and right medial occipital cortex, indicating that hippocampal-perceptual integration benefits memory function. The FC in these networks did not differ between age groups, indicating a potential shift in memory-relevant connectivity in older adults rather than reduced network function per se. Our findings provide novel evidence of large-scale network correlates underlying sequence memory decline in old age and suggest qualitatively distinct connectivity patterns supporting sequence memory in young and older adults.

In China, the growing need for stratified cognitive assessment demands portable solutions. However, in community-based screening, neuropsychological assessments suffer from low acceptance and low efficiency. Thus, we aimed to develop a serum Raman spectroscopy-based ensemble learning approach for graded cognitive screening, and explore the Raman spectral features of cognitive impairment and their mapping relationship to brain function. We recruited 220 subjects for modeling and 40 subjects for validation. Ensemble learning model was built using serum Raman spectra. High-weight features were analyzed for inter-group differences, graph theory properties, and associations with brain networks. We developed a serum Raman spectroscopy-based ensemble learning approach for graded cognitive screening. The model distinguishing normal cognition, mild cognitive impairment, and dementia achieved area under curve of 0.92 (testing) and 0.89 (validation). Raman shifts at 1602, 1002, and 1666 cm⁻¹ showed intensity and nodal changes, linking their modulation to both cognitive decline and altered posterior default mode network (pDMN) interactions. The Raman spectroscopy-based ensemble learning model was powerful for cognitive screening. The alteration at the 1602, 1002, and 1666 cm⁻¹ represented key Raman signatures of cognitive impairment, reflecting impaired pDMN-related inter-network interactions.

Behavioural, structural, and functional neuroimaging differences exist between individuals with antisocial personality disorder with (ASPD + P) or without psychopathy (ASPD-P). However, the aetiological mechanisms underpinning such differences remain unclear, hindering treatment development. Intranasal oxytocin (OT) has shown modulatory effects on social brain function in healthy and antisocial populations. We investigated the effects of OT on resting-state brain function in individuals with violent offending histories with ASPD+/-P using arterial spin labelling to measure regional cerebral blood flow (rCBF). A double-blind, placebo-controlled, crossover design was employed with males with ASPD (ASPD + P: N = 17, ASPD-P: N = 14) and healthy male non-offenders (N = 22). Both ASPD subtypes exhibited reduced rCBF in frontotemporal regions compared to non-offenders. Individuals with ASPD + P showed significantly greater rCBF increases in posterior default mode network regions compared to individuals with ASPD-P. OT administration selectively decreased rCBF in the left basal ganglia of the ASPD-P group, an effect not observed in ASPD + P or non-offender groups. These findings highlight functional brain differences between individuals with ASPD + P and ASPD-P at rest and demonstrate oxytocin’s differential impact on resting-state measures. Further understanding of the origins of these neurobiological differences could inform targeted therapeutic strategies for individuals with ASPD with and without psychopathy.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-026-36661-5.

Functional dysconnectivity in triple and reward networks among adolescents with borderline personality disorder.

Plasma neurofilament light is associated with hippocampal volume and memory performance but not functional connectivity in older adults with and without mild cognitive decline

Network-based cortical atrophy predicts longitudinal clinical decline in sporadic behavioral variant frontotemporal dementia.

The neonatal period is critical for brain development, yet the mechanisms linking structural differentiation to functional reorganization remain poorly understood. Using multi-modal MRI data from 399 neonates (348 term-born, 51 preterm-born), here we characterize the dynamic structure-function coupling (SFC) across macroscale brain networks and examine its associations with cortical microstructure (indexed by the T1w/T2w ratio) and network flexibility. We show that the dynamic SFC varies markedly across the neocortex and increases with postmenstrual age, particularly within the default mode network (DMN). Notably, the dynamic SFC in the posterior DMN mediates the relationship between the T1w/T2w ratio and network flexibility. Preterm infants exhibit a significantly reduced dynamic SFC relative to term-born peers, along with an altered developmental trajectory of DMN linked to premature extra-uterine exposure. These findings establish dynamic SFC, especially within the DMN, as a potential biomarker for neonatal brain maturation, offering insight into the early emergence of internally directed cognition and its vulnerability to early-life adversity.

ABSTRACTIntroductionThe brain network correlates of personality traits in major depressive disorder (MDD) have not yet been investigated. Furthermore, it is still unclear whether personality traits relate to the depressive episode.MethodsThis study assessed network properties, depression severity, and personality traits in patients with MDD (n = 25) compared with age‐ and sex‐matched healthy controls (n = 22). We performed TCI questionnaire which assesses novelty seeking (NS, an urge to explore new experiences with heightened emotional responses), harm avoidance (HA, the tendency to hold back when faced with unpleasant situations), reward dependence (RD, a tendency to seek and value rewards rooted in social recognition), persistence (P, an individual's ability to remain focused and driven toward goals despite encountering challenges), self‐directness (SD, an expression of willpower that enables individuals to adapt their behavior to situational demands while remaining focused on their personal goals and values), cooperativeness (C, a behavioral trait reflecting a person's general approach to others; ranging from friendly and cooperative to hostile), and self‐transcendence (ST, lessening of self‐centeredness, allowing for expanded empathy) traits of participants.ResultsMDD patients with distinctive character traits exhibited significant differences in terms of depression diagnosis and severity of Hamilton Depression Rating Scale scores compared to the controls. The MDD patients also exhibited reduced resting‐state network activity between the posterior default mode network, right putamen, and right frontal pole, while SD was significantly less frequently diagnosed in MDD patients. In evaluating the network correlates, differences in the SD traits were significantly associated with critical brain network alterations that were not evident in other traits.DiscussionTo the best of our knowledge, this is the first study to provide preliminary evidence of an abnormal connectome in the SD trait in MDD, thus providing convincing evidence for personalized antidepressant treatment strategies in MDD. A small sample size and our depression group being not drug‐naive were our limitation for this research.

Cognitive decline is common in multiple sclerosis (MS), although neural mechanisms are not fully understood. The objective was to investigate the impact of mild cognitive impairment (MCI) on the relationship between resting state functional connectivity (RSFC) and cognitive function in older adults with multiple sclerosis (OAMS)and age matched healthy controls. Participants underwent magnetic resonance imaging (MRI) scans and cognitive assessments. The Oral Symbol Digit Modalities Test (SDMT) was the outcome measure. Multiple linear regressions examined the relationship between RSFC networks and SDMT performance across the cohort and within group-specific analyses. These analyses were repeated with MCI as a moderator. Adjusted analyses showed that better SDMT performance correlated significantly with higher RSFC in sensorimotor (p = 0.01), left frontoparietal (p = 0.027), and salience (p = 0.047) networks. Stratified analyses showed significant positive associations for the OAMS group in medial visual (p = 0.007) and sensorimotor (p = 0.018) networks. Among OAMS, MCI moderated the association between RSFC and SDMT performance in the posterior default mode (p = 0.016) and subcortical (p = 0.042) networks, while no significant moderation effects were observed for the control group. Higher RSFC in brain networks correlates with better cognition in aging, but this relationship is modified in the presence of MS and MCI.

Depression and cognitive decline frequently coexist in older individuals. However, effective treatment options remain limited. Neuromodulation has shown potential beyond traditional cognitive training; however, its specific effects on brain connectivity and white matter structures remain unclear. The purpose of this study was to evaluate the effects of combining transcranial direct current stimulation (tDCS) with cognitive training on white matter microstructure integrity and default mode network (DMN) homogeneity in older adults with cognitive deficits and depressive symptoms. This double-blind, randomized sham-controlled study compared cognitive training combined with either anodal or sham tDCS in older adults with late-life depression and cognitive decline. Multimodal magnetic resonance imaging was used to assess DMN homogeneity and white matter microstructure at baseline and after 5 weeks of treatment. Cognitive training, whether combined with active or sham tDCS, led to significantly increased fractional anisotropy averaged across all brain regions, indicating an overall improvement in white matter integrity. However, tDCS did not provide additional benefit to white matter integrity. A higher baseline anterior-posterior DMN association correlated with better cognitive function, and treatment remission increased posterior DMN homogeneity. Enhancements in cingulum white matter integrity were associated with improvements in depressive symptoms, cognition, and brain-derived neurotrophic factor levels. Cognitive training leads to improved white matter integrity in older adults experiencing cognitive deficit and depression. Changes in the structural integrity of the cingulum can predict clinical outcomes. No additional benefits of tDCS on white matter integrity or network homogeneity were observed. Registry: Clinical Research Information Service; URL: https://cris.nih.go.kr; Unique identifier: KCT0006594.

BackgroundPrevious studies have identified sex differences in brain structure, function, and connectivity. However, the sex differences and age-related changes at the large-scale brain network level remain unclear.MethodsResting-state functional MRI data from 436 healthy adults were analyzed using independent component analysis to extract large-scale brain networks. Multivariate analysis of covariance was applied to investigate sex differences in inter-network connectivity between these networks, and further performed voxel-level analysis to examine intra-network connectivity differences. Additionally, Pearson correlation analysis was used to explore the relationship between inter-network and intra-network functional connectivity (FC) and age.ResultsMales exhibited stronger inter-network FC across multiple networks compared to females. In contrast, females demonstrated stronger intra-network FC in several networks, including the sensorimotor, salience, auditory, and executive control networks. Males showed stronger intra-network FC only in specific regions of the posterior default mode and left frontoparietal networks. Additionally, inter-network FC in females appeared more susceptible to age-related changes, whereas males demonstrated relatively stable inter-network connectivity across the lifespan. Intra-network FC generally decreases with age in both males and females, with the exception of the ventral attention network in females and the dorsal sensorimotor network in males.ConclusionMales typically have stronger inter-network connectivity, while females show enhanced intra-network connectivity in key networks. Age-related inter-network connectivity declines are more pronounced in females, both sexes experience a reduction in most intra-network connectivity with age. The study offers valuable insights into how age and sex shape the large-scale brain networks.

Frontal lobe epilepsy (FLE), marked by recurrent seizures arising from the frontal lobes, can significantly impair cognitive and motor function, reducing quality of life. Recent studies suggest that epilepsies can involve functional networks throughout the brain that can be identified using resting-state functional magnetic resonance imaging (fMRI). In this study, we aimed to determine whether FLE is associated with a distinct functional network brain states. Using dynamic functional connectivity analysis in combination with k-means clustering, we investigated dynamic connectivity patterns of the somatomotor network (SMN) and default mode network (DMN) of ten right-hemisphere and six left-hemisphere FLE patients, as well as nine healthy controls. We found two distinct states of rest for both the SMN and DMN: a high connectivity state and a lower, more variable connectivity state that was often specific to individual patients. Both FLE groups showed reduced overall connectivity compared to controls, with the greatest differences emerging during the low connectivity state. Right FLE patients and controls exhibited relatively uniform reductions, whereas left FLE patients showed spatially specific disruptions, including reduced lateral-to-medial SMN connectivity and decreased connectivity in posterior and left-lateralized DMN regions. Our findings suggest that dynamic connectivity analysis can uncover the temporal complexity and patient-specific nature of brain network disruption in FLE, supporting the development of personalized diagnostic and treatment strategies. Further research with larger cohorts is necessary to validate these results and explore additional factors affecting brain functional connectivity.

BackgroundBeta‐thalassemia major (β‐TM) is a hereditary blood disorder characterized by chronic anemia and hypoxia, which may have profound effects on brain function. This study systematically evaluates alterations in both intra‐brain network functional connectivity (FC) and inter‐network functional connectivity (FNC) in β‐TM patients using resting‐state functional magnetic resonance imaging (rs‐fMRI) and independent component analysis (ICA), aiming to uncover the potential mechanisms underlying their neurofunctional impairments.MethodsThis study included 72 β‐TM patients and 50 age‐ and gender‐matched healthy controls (HC). rs‐fMRI was used to collect brain functional data, and ICA was applied to extract 14 resting‐state functional networks (RSNs). Differences in FC within networks and FNC between the two groups were further compared to investigate the brain network abnormalities in β‐TM patients.ResultsIn β‐TM patients, FC within brain networks was significantly reduced in the anterior default mode network (aDMN), posterior default mode network (pDMN), left frontoparietal network (lFPN), right frontoparietal network (rFPN), ventral attention network (VAN), and executive control network (ECN). In contrast, FC was significantly increased in the dorsal sensorimotor network (dSMN) and posterior visual network (pVN). FNC analysis revealed that β‐TM patients exhibited enhanced connectivity between the lFPN and rFPN, as well as between the dorsal attention network (DAN) and VAN. However, connectivity was significantly weakened between the DAN and lFPN, ECN, auditory network (AN), and salience network (SN); as well as between the pVN and dSMN. These findings suggest impairments in cognitive control, attention allocation, and sensory integration, with specific disruptions in the SN that may contribute to the observed dysfunctions.ConclusionBrain network abnormalities in β‐TM patients manifest as an alternating pattern of enhanced and weakened connectivity, revealing the profound impact of chronic anemia and hypoxia on cognitive, emotional, and sensory functions.

BackgroundLate-onset Alzheimer's disease is consistently associated with alterations in the default-mode network (DMN)—a large-scale brain network associated with self-related processing and memory. However, the functional organization of DMN is far less clear in young-onset Alzheimer's disease (YOAD).ObjectiveThe current study aimed to identify effective connectivity changes in the core DMN nodes between YOAD variants and healthy controls.MethodsWe assessed resting-state DMN effective connectivity in two common YOAD variants (i.e., amnestic variant (n = 26) and posterior cortical atrophy (n = 13) and healthy participants (n = 24) to identify disease- and variant-specific connectivity differences using spectral dynamic causal modelling.ResultsPatients with the amnestic variant showed increased connectivity from prefrontal cortex to posterior DMN nodes relative to healthy controls, whereas patients with posterior cortical atrophy exhibited decreased posterior DMN connectivity. Right hippocampus connectivity differentiated the two patient groups. Furthermore, disease-related connectivity alterations were also predictive of group membership and cognitive performance.ConclusionsThese findings suggest that resting-state DMN effective connectivity provides a new understanding of neural mechanisms underlying the disease pathology and cognition in YOAD.