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Schizophrenia (Heidelb). 2026 Jan 6. doi: 10.1038/s41537-025-00685-z. Online ahead of print.

ABSTRACT

Resting-state functional magnetic resonance imaging (rs-fMRI) has offered insights into the neural mechanisms underlying psychosis, particularly when associated with clinically relevant features. 102 individuals at ultra-high risk for psychosis (UHR) and 105 matched healthy controls (HC) aged 18-40 underwent clinical and cognitive assessments and rs-fMRI at baseline. Using a recently developed prediction-based extension of the network-based statistics (NBS-predict), incorporating nested cross-validation, we tested the predictive power of functional connectivity estimated from rs-fMRI data, investigating diagnostic classification and prediction of level of functioning, estimated IQ, and UHR-symptoms. Hyper-connectivity predicted group with a classification accuracy of 0.58, p = 0.043, and hypo-connectivity predicted group with a classification accuracy of 0.59, p = 0.018. Hyper-connectivity in UHR-individuals was observed primarily in interhemispheric and cortico-thalamic connections, within networks that predicted poorer levels of functioning across groups. Hypo-connectivity in UHR-individuals was observed mainly in thalamic connections with posterior cingulate cortex, frontal medial, and precuneus, within networks that predicted higher level of functioning across groups. Post hoc analyses identified a significant groupwise interaction effect on the association between functional connectivity and level of functioning (ρ = 0.34, p < 0.001), with main nodes in the frontal medial regions connected across hemispheres. Within-group, no connections predicted level of functioning or UHR-symptoms. Whole-brain functional connectivity predicted UHR-status in hyper- and hypo-connected networks, with thalamus as a central integrative hub across networks. Connections that predicted level of functioning across groups were equivalent to the connections predicting UHR-status, hence capturing a neural correlate to a key clinical component of the UHR-status.

PMID:41495085 | DOI:10.1038/s41537-025-00685-z

Transl Psychiatry. 2026 Jan 6. doi: 10.1038/s41398-025-03802-9. Online ahead of print.

ABSTRACT

Non-suicidal self-injury (NSSI) is a common behavior among adolescents, particularly within psychiatric populations. While neurobiological and psychosocial risk factors have been extensively studied, the mechanisms underlying NSSI's heterogeneity remain unclear. This study investigated 304 hospitalized adolescents/young adults (16-25 years) with NSSI and comorbid psychiatric diagnoses (major depressive disorder [MDD], bipolar disorder [BD], eating disorders [ED]) using psychological assessments and resting-state fMRI data from 163 participants. Orthogonal projection non-negative matrix factorization of Ottawa Self-Injury Inventory responses identified two latent factors: self-related factor and social-related factor. The self-related factor correlated with amygdala-centered cortico-limbic emotional regulation networks and predominated in affective disorders (MDD/BD), while the social-related factor linked to frontoparietal cognitive control and frontotemporal social cognition networks, particularly in ED. Fuzzy C-means clustering revealed three NSSI functional subtypes, independent of diagnostic categories: self-subtype primarily driven by self-related functions, social-subtype influenced by both self-related and social-related functions with greater exposure to psychosocial risks, and non-specific subtype characterized by mixed motivations. No subtype was exclusively driven by social-related functions. The "self-social" dual-dimensional framework with distinct neural mechanisms demonstrated subtype-specific profiles in functional connectivity, psychosocial risk exposure, and clinical features. Self-related mechanisms primarily engaged emotional regulation circuits, whereas social-related mechanisms emphasize the role of psychosocial risk factors and cognitive-emotional circuits. These findings provide neural evidence for the functional heterogeneity of NSSI and highlight the need for personalized interventions. Treatments targeting emotion regulation may benefit all subtypes, individuals with prominent social-related motivations may additionally require interventions aimed at improving interpersonal functioning.

PMID:41495020 | DOI:10.1038/s41398-025-03802-9

J Affect Disord. 2026 Jan 4:121073. doi: 10.1016/j.jad.2025.121073. Online ahead of print.

ABSTRACT

BACKGROUND: Identifying reproducible neurobiological markers for Major Depressive Disorder (MDD) remains challenging due to methodological heterogeneity across neuroimaging studies. Functional connectome (FC) uniqueness, an individual-level metric derived from brain fingerprinting, quantifies the distinctiveness of intrinsic connectivity patterns and may offer a robust framework for biomarker discovery.

METHODS: We analyzed multi-site resting-state fMRI data from healthy controls (HC) and patients with Major Depressive Disorder (MDD), aged 19-37 years. Individual functional connectomes were constructed using 300 regions of interest grouped into 14 canonical networks. FC uniqueness was defined as the ratio of self-similarity (calculated as Pearson correlation between connectomes from the same individual across different time points) to similarity-to-others (calculated as Pearson correlations between an individual's connectome and those of other participants at the next timepoint). An FC uniqueness index greater than one indicates successful individual identification, referred to as fingerprinting accuracy.

RESULTS: Replicating prior studies, fingerprinting accuracy was highest at the whole-brain level, followed by the default mode and frontoparietal networks. MDD patients exhibited significantly lower FC uniqueness with pronounced reductions in frontoparietal and sensorimotor networks. Notably, reduced FC uniqueness was associated with higher PHQ-9 and BDI-II scores in this study.

LIMITATIONS: Comorbidity and age distribution differences may have introduced confounding effects.

CONCLUSIONS: Reduced FC uniqueness in frontoparietal and sensorimotor networks corelate with neurobiological organization in MDD and represents a reproducible, clinically interpretable neuroimaging marker with potential utility for diagnosis and stratification.

PMID:41494549 | DOI:10.1016/j.jad.2025.121073

J Affect Disord. 2026 Jan 4:121103. doi: 10.1016/j.jad.2025.121103. Online ahead of print.

ABSTRACT

BACKGROUND: Alterations in neuronal activity and cerebral hemodynamics have been reported in adolescent patients with major depressive disorder (MDD), possibly resulting in neurovascular decoupling; however, no neuroimaging evidence has confirmed this disruption. The aim of this study was to investigate the possible presence of neurovascular decoupling and its clinical implications in adolescent MDD patients via resting-state functional magnetic resonance imaging (fMRI) and arterial spin labeling (ASL) imaging.

METHODS: In this prospective single-center study, we recruited adolescent patients with MDD and age-matched healthy controls (HC) between December 2023 and October 2024 for a comprehensive multimodal MRI investigation. Adolescent MDD patients and HCs underwent resting-state fMRI and ASL imaging to calculate low-frequency fluctuation amplitude (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), degree centrality (DC) and cerebral blood flow (CBF). Across-voxel CBF-ALFF, CBF-fALFF, CBF-DC, and CBF-ReHo correlations were analyzed to evaluate global gray matter neurovascular coupling (NVC), and the regional NVC of the brain region was assessed with the CBF/ALFF, CBF/fALFF, CBF/DC, and CBF/ReHo ratios. Subsequently, Pearson's correlation analyses were conducted to explore the relationship between brain regions exhibiting significant differences in local NVC and clinical Hamilton Depression Scale (HAMD).

RESULTS: This study included 45 adolescent MDD patients (mean age: 16.88 ± 3.02years, male: 32) and 50 sex- and age-matched HCs (mean age: 16.90 ± 2.55years, male: 34). Compared with the HCs, the MDD patients presented lower across-voxel CBF-ALFF, CBF-fALFF, CBF-DC and CBF-ReHo correlations and a lower CBF/ALFF ratio in the right middle temporal gyrus (MTG) and angular gyrus (AG). The brain regions with reduced a CBF/ReHo ratio included the bilateral superior parietal lobule (SPL), the left superior frontal gyrus (SFG), and the left medial superior frontal gyrus (MSFG). The right AG and right MTG, with significant differences in the CBF/ALFF ratio in adolescent MDD patients, were negatively correlated with the clinical HAMD score. The CBF/ReHo ratios in the left MSFG and bilateral SPL were negatively correlated with HAMD scores in adolescent patients with MDD, whereas CBF/ReHo ratios in the left SFG were positively correlated with HAMD scores.

CONCLUSION: Adolescent patients with MDD presented alterations in NVC mainly in higher-order brain regions in key areas such as emotion regulation, executive function, and cognitive control. These findings provide new insights into the pathophysiology of adolescent MDD and potential imaging biomarkers for assessing cognitive performance in adolescent patients with MDD.

PMID:41494542 | DOI:10.1016/j.jad.2025.121103

Neuroimage Clin. 2025 Dec 31;49:103941. doi: 10.1016/j.nicl.2025.103941. Online ahead of print.

ABSTRACT

Behavioral and imaging studies suggests that emotional biases in the perception of faces associated with major depression disorder (MD) may be embedded within a broader sensory processing deficit. Increased cortical acetylcholine in MD suggest that this deficit may be related to abnormal attention modulation of sensory areas. It is not clear, however, whether these problems are a manifestation of the disease or whether they precede symptom onset. To investigate this, we applied functional magnetic resonance imaging (fMRI) to look for brain activity changes that participants with a family risk of MD (N = 30) shared with participant with MD (N = 28), compared to matched controls (N = 28). Participants were scanned while performing gender categorization of sad, happy, and neutral face pictures, as well as during a state of rest. Task-related activity changes, shared by participants at risk of and suffering from MD, were mostly seen in the posterior brain: increased activity in dorsal attention and visual association cortex, and decreased in lower visual areas. The changes did not differ between neutral faces and faces expressing an emotion. The at risk and MD participants additionally showed increased functional connectivity between the dorsal attention clusters and the lingual gyrus, and decreased connectivity with the lateral occipital complex (LOC). Lastly, they also had in common increased functional connectivity of magnocellular basal forebrain seeds with LOC and visual association cortex. These changes are consistent with an acetylcholine-mediated change in attention-guided sensory processing of all environmental events, which is discernable even before the first MD episode.

PMID:41494451 | DOI:10.1016/j.nicl.2025.103941

Neuroimage Clin. 2025 Dec 31;49:103939. doi: 10.1016/j.nicl.2025.103939. Online ahead of print.

ABSTRACT

Prolonged alcohol use results in neuroadaptations that mark more severe and treatment-resistant alcohol use. The goal of this study was to identify functional connectivity brain patterns underlying Alcohol Use Disorder (AUD)-related characteristics in fifty-five adults (31 female) who endorsed heavy alcohol use. We hypothesized that resting-state functional connectivity (rsFC) of the Salience (SN), Frontoparietal (FPN), and Default Mode (DMN) networks would reflect self-reported recent and lifetime alcohol use, laboratory-based alcohol seeking, urgency, and sociodemographic characteristics related to AUD. To test our hypothesis, we combined the triple network model (TNM) of psychopathology with a multivariate data-driven approach, regularized partial least squares (rPLS), to unfold concurrent functional connectivity (FC) patterns and their association with AUD-related characteristics. We observed three concurrent associations of interest: i) drinking and age-related cross communication between the SN and both the FPN and DMN; ii) family history density of AUD and urgency anticorrelations between the SN and FPN; and iii) alcohol seeking and sex-associated SN and DMN interactions. These findings provide an integrative interpretation for many individual findings reported in the literature relating functional connectivity signatures and AUD factors. Moreover, we identified a set of neural mechanisms and brain regions concomitant with AUD-related characteristics that can serve as potential treatment targets across clinical and preclinical models.

PMID:41494450 | DOI:10.1016/j.nicl.2025.103939

Pediatr Cardiol. 2026 Jan 6. doi: 10.1007/s00246-025-04141-8. Online ahead of print.

ABSTRACT

Single ventricle heart disease (SVHD) adolescents show brain tissue injury in sites that mediate autonomic, mood, and cognition functions deficient in the condition, which may result from impaired neural interactions at resting state. However, it is unclear whether SVHD subjects have aberrant neural activities in those areas that can be examined with regional homogeneity (ReHo) measures, assessing local neural synchronization. We aimed to examine regional brain neural activity changes in SVHD compared to healthy controls using functional magnetic resonance imaging (fMRI). Resting fMRI data were collected from 27 SVHD and 31 controls using a 3.0-Tesla MRI scanner. Using the standard pre-processing steps, ReHo maps were calculated and transformed to z-scored maps, normalized to a common space, smoothed, and compared between groups (ANCOVA; qFDR corrected p ≤ 0.05; covariates: age and sex). Reduced ReHo appeared in brain sites, including the caudate, parietal cortex, frontal cortex, and amygdala, and increased ReHo emerged in the parietal cortex, insula, cerebellar vermis, hippocampus, para-hippocampal gyrus, cerebellar peduncles, and cerebellar cortex in SVHD over controls. SVHD adolescents show impaired neural synchronization at resting in areas involved in neurobehavior and cognition. The findings indicate the widespread impact on brain functional organization and may explain functional deficits observed in SVHD.

PMID:41493462 | DOI:10.1007/s00246-025-04141-8

Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2025 Sept 28;50(9):1579-1589. doi: 10.11817/j.issn.1672-7347.2025.250392.

ABSTRACT

OBJECTIVES: Major depressive disorder (MDD) is a common affective disorder with complex etiologies and largely unclear pathophysiological mechanisms. The nucleus accumbens (NAc) plays a central role in reward processing, motivational regulation, and emotional integration. Neuroimaging studies suggest that structural and functional abnormalities of the NAc are key contributors to the pathogenesis of MDD. However, the alterations in structure-function coupling (SFC) of the NAc in MDD remain poorly understood. This study aims to systematically investigate abnormal functional connectivity (FC) and SFC of the NAc in patients with MDD by integrating functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) techniques.

METHODS: A case-control design was adopted. Patients who met diagnostic criteria for a current depressive episode of MDD and had a 17-item Hamilton Rating Scale for Depression (HAMD-17) total score ≥17 were enrolled as the MDD group, while age-, sex-, and education-matched healthy controls (HCs) were included as the HC group. All participants underwent high-resolution T1-weighted structural imaging, resting-state fMRI, and DTI scanning using a 3.0T MR system. fMRI data preprocessing was performed using SPM12 (Statistical Parametric Mapping 12) and DPARSF (Data Processing Assistant for Resting-State fMRI), while DTI preprocessing was conducted using FSL (FMRIB Software Library). Based on the Brainnetome Atlas, the cerebral cortex was parcellated into 246 regions. FC values between bilateral NAc and the whole brain and the strength of structural connectivity (sSC) derived from probabilistic tractography were calculated. SFC values of bilateral NAc were computed using region-wise Spearman correlations between sSC and FC (ρ). A multiple linear regression model was constructed using FC as the dependent variable and age, gender, years of education, and head motion parameters as covariates, and corrected FC values were extracted from the regression residuals. Group differences in corrected FC values were assessed using independent-sample t-tests with false discovery rate (FDR) correction at a significance level of P<0.1. Analysis of covariance was used to compare SFC values between groups, controlling for age, gender, and years of education (a significance level of P<0.05). FC values showing significant intergroup differences and SFC values of bilateral NAc were correlated with HAMD-17 total scores using Spearman correlation analysis.

RESULTS: There were no significant differences between the MDD and the HC groups in gender (χ2=0.792, P=0.373), age (t=-0.930, P=0.292), or years of education (t=0.003, P=0.059). Compared with HCs, patients with MDD exhibited significantly increased FC in the following connections: BG.L.3 (left NAc)-IPL.R.4 (right inferior parietal lobule), BG.R.3 (right NAc)-IPL.R.4, BG.R.3-Tha.R.8 (right lateral prefrontal thalamus), and BG.R.3- MFG.R.4 (right middle frontal gyrus) (all FDR-corrected P<0.1). The SFC values of bilateral NAc were significantly reduced in the MDD group compared with the HC group (left: F=11.768, P=0.001; right: F=4.386, P=0.047). Spearman correlation analyses showed no significant associations between altered FC or bilateral NAc SFC values and HAMD-17 total scores in the MDD group (all P>0.05).

CONCLUSIONS: Patients with MDD exhibit enhanced NAc FC, predominantly between the NAc and cognition-related regions such as the inferior parietal lobule and middle frontal gyrus, suggesting imbalance between the reward circuit and cognitive regulatory networks. Moreover, the significantly reduced SFC of bilateral NAc indicated impaired structural-functional integration in MDD. These findings provide potential neuroimaging evidence supporting the involvement of the NAc in the pathophysiological mechanisms of MDD.

PMID:41492742 | PMC:PMC12740730 | DOI:10.11817/j.issn.1672-7347.2025.250392

Aging Brain. 2025 Dec 12;9:100155. doi: 10.1016/j.nbas.2025.100155. eCollection 2026.

ABSTRACT

Subjective Cognitive Decline (SCD) is the perception of a persistent decline in cognitive function and self-reported concerns over cognitive ability in older adults with normal objective cognitive performance. SCD is associated with increased Alzheimer's Disease (AD) risk and early AD pathology. The neurobiological underpinnings of SCD and cognitive or neural circuit alterations during SCD remain unclear. This study aimed to identify patterns of brain network functional connectivity that are associated with quantitative measures of cognitive concerns, and to examine how these functional patterns are related to performance in the cognitive domains of visual-spatial processing, attentional control, and working memory. This analysis combined data from three studies of cognitively healthy older adults which included a quantified assessment of cognitive concern severity, resting-state fMRI, and cognitive testing in the above domains. We examined brain network-to-network functional connectivity associated with self-rated cognitive concern severity, and then how the identified patterns relate to cognitive performance. Results showed that greater cognitive concern severity was associated with unique patterns of functional connectivity between the Default Mode Network and the Language and Salience Networks in older adults without objective cognitive impairment. While greater cognitive concern severity alone was associated with slower processing reaction time, these functional connectivity patterns were associated with faster processing reaction time. This suggests that these functional connectivity patterns may alter the relationship between cognitive concern severity and psychomotor slowing. These findings support that despite the perception of cognitive changes in older adults, normal cognitive performance may be maintained through functional connectivity changes in brain networks important to directing visual-spatial attention and processing.

PMID:41492384 | PMC:PMC12764441 | DOI:10.1016/j.nbas.2025.100155

Psychogeriatrics. 2026 Jan;26(1):e70126. doi: 10.1111/psyg.70126.

ABSTRACT

BACKGROUND: Observational investigations have reported correlations between brain imaging-derived phenotypes (IDPs) and dementia, as well as dysfunctions in brain resting-state functional networks in dementia patients. However, the causal nature of these relationships remains largely unknown.

METHODS: Herein we applied bidirectional two-sample Mendelian randomisation analysis to infer the causal relationships between 587 IDPs (N = 33 224) and 191 brain resting-state functional networks (n = 34 691) with dementia and its sub-types (AD, PDD, FTD and DLB; n = 3024-216 771) using genetic variants-single nucleotide polymorphism (SNPs) as instrumental variables.

RESULTS: The forward MR identified 14 IDP phenotypes that are causally related to the risk of dementia, including frontotemporal dementia (FTD) and Lewy body dementia (DLB). For example, a decrease in the thickness of the right rostral middle frontal cortex was strongly associated with an increased risk of dementia. The reverse MR analysis revealed significant associations between 153 IDP phenotypes and the risk of FTD and DLB and between 73 rs-fMRI phenotypes and the risk of dementia and AD. For instance, a higher risk of DLB was associated with a decrease in FA in the right posterior thalamic radiation. Additionally, the risk of Alzheimer's disease dementia is causally associated with reduced connectivity in the default mode and salience networks.

CONCLUSIONS: We identified 14 IDPs causally associated with dementia or its subtypes. We also identified potential causal effects of FTD and DLB on 153 IDPs and dementia and AD on 73 rs-fMRI phenotypes. Our findings provide insights into the aetiology of dementia and highlight structural brain changes and functional network impairments throughout the disease process. Furthermore, these results contribute to the identification of potential imaging-based predictors and therapeutic targets for dementia.

PMID:41492205 | DOI:10.1111/psyg.70126

J Neurooncol. 2026 Jan 5;176(2):151. doi: 10.1007/s11060-025-05361-x.

ABSTRACT

PURPOSE: Glioblastoma (GBM) is the most prevalent and lethal primary brain tumor. Non-invasive presurgical biomarkers are urgently needed to predict patients’ overall survival (OS). Here we demonstrated a nuanced prognostic tool using sample entropy to assess Blood-Oxygen-Level-Dependent (BOLD) complexity and predict survival outcome, which is computationally efficient, reproducible, robust to noise, and readily transferable across cohorts.

METHODS: Resting-state fMRI from 205 treatment-naïve GBM patients and 1148 cognitively stable healthy controls were evaluated. Sample entropy (SampEn), a complexity metric, was evaluated in relation to OS at four levels: whole brain voxel-wise, 15 resting state networks (RSNs), a 64-feature autoencoded latent space, and complexity dynamics along contrast-enhancing (CE) boundary.

RESULTS: GBM patients showed a significant reduction in global SampEn versus controls (p < 0.001). Among RSNs, medial temporal lobe (MTL) and basal ganglia (BGA) SampEn correlated inversely with OS (R² = 0.033 and 0.034; p = 0.008 and 0.006). The latent-space-dependent Cox risk score stratifies patients into high and low survival populations (p < 0.001). The number of SampEn peaks at the CE boundary also correlated negatively with OS (R² = 0.020, p = 0.037).

CONCLUSIONS: Voxel-wise SampEn revealed widespread loss of BOLD complexity in GBM. It identifies influences at RSNs and tumor-edge, characterizing survival. Latent space analysis revealed whole-brain SampEn characteristics, which provide a compact, data-driven biomarker that augments conventional Cox modelling and stratifies the patient survival. These findings show fMRI-derived SampEn measures are efficient and robust for risk stratification and mechanistic insight in glioblastoma.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11060-025-05361-x.

PMID:41491449 | PMC:PMC12769512 | DOI:10.1007/s11060-025-05361-x

iScience. 2025 Dec 1;29(1):114282. doi: 10.1016/j.isci.2025.114282. eCollection 2026 Jan 16.

ABSTRACT

The accurate identification of individuals from functional connectomes (FCs) is central to individualized neuro/psychiatric assessment. Traditional metrics (Pearson and Euclidean) fail to capture the non-Euclidean geometry of FCs, and geodesic metrics (affine-invariant and Log-Euclidean) require task- and scale-specific regularization and degrade in high-dimensional settings. To address these challenges, we propose the Alpha-Z Bures-Wasserstein divergence, a geometry-aware divergence for FC comparison that operates effectively without meticulous parameter tuning. Across Human Connectome Project tasks, scan lengths, and spatial resolutions, we benchmark Alpha-Z against classical and state-of-the-art manifold-based distances and quantify how varying regularization influences geodesic performance. Alpha-Z yields consistently higher identification rates, with pronounced advantages in rank-deficient regimes, and preserves performance across parcellations and conditions. We further verify generalization across resting-state and task fMRI under multiple parcellation schemes. These results position Alpha-Z as a reliable, robust, and scalable framework for functional connectivity analysis, improving sensitivity to cognitive and behavioral patterns and offering strong potential for individualized clinical neuroscience.

PMID:41488781 | PMC:PMC12757632 | DOI:10.1016/j.isci.2025.114282

Front Psychiatry. 2025 Dec 18;16:1695846. doi: 10.3389/fpsyt.2025.1695846. eCollection 2025.

ABSTRACT

INTRODUCTION: Emotion regulation is a key domain of social cognition, and its impairment contributes to poor psychosocial functioning in schizophrenia (SZ). The "Managing Emotions" (ME) branch of the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT) is widely used to assess this ability, yet its neural correlates remain unclear.

METHODS: We examined resting-state functional connectivity (rsFC) associated with MSCEIT-ME performance in 56 patients with schizophrenia and 56 healthy controls matched for age, sex, and years of education. Seed-based correlation analyses focused on three large-scale networks previously implicated in emotion regulation: the salience network (SN), the language network (LN), and the ventral attention network (VAN). Between-group differences and brain-behavior relationships were tested while controlling for IQ scores on the Wechsler Abbreviated Scale of Intelligence (WASI). False discovery rate Benjamini-Yekutieli (FDR-BY) correction was applied to all analyses.

RESULTS: Patients with SZ scored significantly lower on the MSCEIT-ME compared to healthy subjects (HCs). Moreover, SZ patients exhibited reduced left-lateralized rsFC between SN and LN regions relative to HCs. These findings indicate altered language-salience connectivity in schizophrenia and show that, while connectivity is associated with emotion regulation ability in healthy individuals, no significant brain-behavior association was detected in patients. Therefore, the neural mechanisms underlying emotion regulation deficits in schizophrenia remain to be clarified.

CONCLUSION: Schizophrenia was characterized by altered left-lateralized language-salience connectivity. However, because no significant brain-behavior associations were found in patients, the neural basis of emotion-regulation deficits in schizophrenia remains unresolved, highlighting the need for network-level investigations in larger samples.

PMID:41488561 | PMC:PMC12756178 | DOI:10.3389/fpsyt.2025.1695846

Front Neurosci. 2025 Dec 18;19:1725420. doi: 10.3389/fnins.2025.1725420. eCollection 2025.

ABSTRACT

INTRODUCTION: In this study, we propose a data-driven approach that integrates behavioral diagnosis with neuroimaging features to identify representative UWS and MCS patients from a large inpatient cohort.

METHODS: Clinical information was extracted using a subset of UWS patients with CRS-R scores ≤ 5. Neuroimaging biomarkers were established as the increased and decreased functional connectivity indices of anatomically defined regions covering the whole brain. The algorithm was implemented through an iterative refinement process that converged on a division of UWS and MCS patients into representative and excluded (or nonrepresentative) patient groups.

RESULTS: Thirty-one out of 58 UWS patients and 23 out of 30 MCS patients were identified as representative, with an average classification accuracy of 90.2% in differentiating between the two groups. In contrast, differentiating between excluded UWS patients (n = 27) and representative MCS patients (n = 23) and between all UWS (n = 58) and MCS (n = 30) patients produced average classification accuracies of 50.9 and 64.3%, respectively. Furthermore, altered DMN functional connectivity between representative UWS and MCS patients revealed a consistent pattern as shown in prior studies, while comparisons involving excluded patients did not.

DISCUSSION: These results highlight the value of integrating behavioral scores and neural connectivity features for DOC classification, providing a more coherent basis for downstream analysis and machine-learning applications in DOC classification.

PMID:41488324 | PMC:PMC12756502 | DOI:10.3389/fnins.2025.1725420

Innov Aging. 2025 Nov 14;10(1):igaf129. doi: 10.1093/geroni/igaf129. eCollection 2026.

ABSTRACT

BACKGROUND AND OBJECTIVES: Subjective cognitive decline (SCD) is a preclinical stage of mild cognitive impairment (MCI). Although dance training has been shown to be beneficial for mental health, cognitive function, and neural activity in older adults with MCI, its effect on SCD remains unclear. This study aimed to examine the effects of dance training on the aforementioned factors and on oxytocin secretion in older adults with SCD.

RESEARCH DESIGN AND METHODS: Participants (aged 65-84 years) were assigned to either the intervention group (n = 22) with a 12-week dance training program or the control group without any alternative training (n = 22). Apathy, depression, Montreal Cognitive Assessment scores, urinary oxytocin levels, and resting-state functional magnetic resonance imaging indices, including amplitude of low-frequency fluctuations (ALFF) and functional connectivity (FC), were evaluated pre- and post-intervention.

RESULTS: Compared to the control group, the intervention group exhibited significantly higher urinary oxytocin levels and significantly higher ALFF in the left medial orbitofrontal cortex post-intervention. Moreover, the intervention group showed more enhanced FC between the left medial orbitofrontal cortex and the left precuneus post-intervention than the control group. However, mental health or cognitive performance was not significantly different between the groups.

DISCUSSION AND IMPLICATIONS: Our results are particularly important in light of previous findings that older adults with SCD show a reduced FC between the medial orbitofrontal cortex and the precuneus, and that oxytocin levels are positively associated with the prefrontal-amygdala oxytocinergic circuit in socioemotional processing. Thus, dance training may contribute to socioemotional resilience-related neural and molecular adaptations in SCD.

PMID:41487488 | PMC:PMC12759060 | DOI:10.1093/geroni/igaf129

J Affect Disord. 2026 Jan 1:121110. doi: 10.1016/j.jad.2025.121110. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVE: Dysfunction in the cortical-striatal-thalamo-cortical circuit is considered a core pathological mechanism of obsessive-compulsive disorder (OCD) and may contribute to abnormalities in the sensorimotor network (SMN). Although altered SMN patterns in OCD have been reported using resting-state fMRI, SMN alterations remain underexplored in resting-state EEG (rsEEG). This study aimed to identify frequency-specific SMN alterations in patients with OCD compared to healthy controls (HCs) using rsEEG.

METHODS: Eyes-closed rsEEG were collected from 41 patients with OCD and 41 HCs. SMN was constructed by eight cortical regions and functional connectivity (FC) with the weighted phase-lag index across six frequency bands. Group differences in FC and strength were assessed using permutation testing. Correlation analysis was conducted between significantly altered measures and Yale-Brown Obsessive Compulsive Scale (Y-BOCS). Machine learning-based classification was applied to assess the potential of SMN features as biomarkers for OCD.

RESULTS: In the theta band, FC between the left primary somatosensory cortex (S1) and the left supplementary motor area was significantly increased in OCD relative to HC. In the high alpha band, FCs between the left S1 and right primary motor cortex (M1), and between the left S1 and right premotor cortex (PMC), as well as local strength in the right PMC, were significantly increased in OCD. FCs between left S1 and right M1 in the high alpha band positively correlated with Y-BOCS. Classification accuracy was achieved at 78.05 %.

CONCLUSION: These findings suggest that rsEEG-derived SMN alterations may reflect neurophysiological mechanisms of OCD and serve as candidate biomarkers.

PMID:41483883 | DOI:10.1016/j.jad.2025.121110

Psychiatry Res Neuroimaging. 2025 Dec 24;357:112116. doi: 10.1016/j.pscychresns.2025.112116. Online ahead of print.

ABSTRACT

This study investigated resting-state functional connectivity (rsFC) patterns in individuals with opioid use disorder (OUD), stimulant use disorder (StUD) and healthy controls (HC). Using seed-based analysis of key subcortical regions, we found distinct connectivity profiles associated with each substance type. OUD showed reduced connectivity between limbic/basal ganglia structures and sensorimotor regions, along with increased pallidum-angular gyrus connectivity compared to HC. StUD exhibited decreased striatal-default mode network and limbic-prefrontal connectivity relative to HC. Direct comparison between OUD and StUD revealed widespread corticostriatal, striato-cerebellar, and prefrontal-limbic hyperconnectivity in OUD compared to StUD. These substance-specific alterations in intrinsic brain organization may reflect differential neuroadaptations underlying the cognitive and behavioral manifestations of opioid versus stimulant use disorders. Our findings highlight the potential of rsFC patterns as a biomarker for distinguishing among different subtypes of addiction and informing targeted interventions.

PMID:41483578 | DOI:10.1016/j.pscychresns.2025.112116

J Affect Disord. 2025 Dec 31:120969. doi: 10.1016/j.jad.2025.120969. Online ahead of print.

ABSTRACT

BACKGROUND: The increasing incidence of adolescent depression represents a serious public health concern. Despite clear diagnostic criteria, the wide range of symptoms and their overlap with other psychiatric disorders make it difficult to provide effective personalized treatment in adolescents. The integration of resting-state functional magnetic resonance imaging (rs-fMRI) and machine learning has shown promise in identifying diagnostic biomarkers and shedding light on personalized treatments in adult depression. However, equivalent studies in adolescent depression are lacking. Therefore, the present study aimed to identify diagnostic rs-fMRI biomarkers for adolescent depression.

METHODS: Phenotypic and rs-fMRI data of 127 adolescents (64 adolescents with depression; 63 healthy controls) were acquired from the Boston Adolescent Neuroimaging of Depression and Anxiety dataset. Partial correlation was used to compute the functional connectome of the whole brain. Repeated nested cross validation with Boruta feature selection and support vector machine was employed to build a classification model to discriminate adolescents with depression from healthy controls.

RESULTS: The classification model identified 46 fine-scale connectivity features of the functional connectome as co-biomarkers in adolescent depression. The connectivity between the right medial/superior temporal gyrus and left pars triangularis/rostral middle frontal gyrus, as well as between the right medial orbitofrontal/ rostral anterior cingulate cortex and right precuneus/isthmus cingulate gyrus were identified as the most important features in adolescent depression.

CONCLUSIONS: The identification of a novel neuroimaging composite-biomarker panel here sheds light on depression diagnosis in adolescence. The retention of anatomical resolution within these composite biomarkers may facilitate the development of individualized neuromodulation treatment strategies.

PMID:41482270 | DOI:10.1016/j.jad.2025.120969

Int J Rheum Dis. 2026 Jan;29(1):e70531. doi: 10.1111/1756-185x.70531.

ABSTRACT

OBJECTIVES: The subdivisions of the anterior cingulate cortex (ACC) are involved in distinct functions in the processing of chronic pain and regulation of emotions. However, the specific impact of each ACC subdivision on fibromyalgia (FM) remains unclear. This study aimed to systematically investigate the abnormal resting-state functional connectivity (rsFC) patterns between the ACC (and its subregions) and other chronic-pain-related limbic cortices and subcortical nuclei in patients with FM.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) was conducted in 31 patients diagnosed with fibromyalgia (FM) and 32 demographically matched healthy controls (HCs). Using subdivisions of the anterior cingulate cortex (ACC) as regions of interest, we employed a seed-based resting-state functional connectivity (rsFC) approach to identify alterations in connectivity between limbic cortex and subcortical nuclei. A two-sample t-test was applied to compare functional connectivity differences between the two groups. Additionally, Pearson correlation analysis was performed to examine the relationships between rsFC alterations and measures of executive function and clinical symptom severity.

RESULTS: Patients with FM demonstrated aberrant rsFC of the dorsal ACC (dACC) with the limbic system, notably the amygdala (t = 2.840, SE = 0.942, p = 0.007), parahippocampal gyrus (t = 2.340, SE = 0.905, p = 0.024), and insula (t = 2.159, SE = 0.835, p = 0.036). Subregion analyses further revealed heightened connectivity of the anterior midcingulate cortex (aMCC) with the parahippocampal gyrus (t = 2.737, SE = 1.064, p = 0.009), and increased connectivity of the superior anterior cingulate cortex (supACC) with the insula (t = 2.596, SE = 0.706, p = 0.013) and amygdala (t = 2.398, SE = 0.812, p = 0.021), which were significantly associated with pain severity and depressive symptoms in FM.

CONCLUSION: This study revealed specific abnormalities in the rsFC between the dACC and the limbic cortices and subcortical nuclei in FM patients. The heightened connectivity of the aMCC with the parahippocampal gyrus and of the supACC with the insula and amygdala was closely associated with the regulation of emotion and processing of chronic pain.

PMID:41480821 | PMC:PMC12757978 | DOI:10.1111/1756-185x.70531

medRxiv [Preprint]. 2025 Dec 22:2025.12.19.25342404. doi: 10.64898/2025.12.19.25342404.

ABSTRACT

BACKGROUND: Cerebellar transcranial magnetic stimulation (TMS) may serve as an adjuvant therapy for psychosis symptoms, most recently we have shown improvements in negative symptoms. Historically, cerebellum TMS has not utilized functional neuroanatomy for targeting, and the precision of TMS to the cerebellum is unclear. A classical view of the cerebellum as solely involved in motor computations has been updated with the discovery of rich non-motor connectivity including the default, dorsal attention, frontoparietal control and ventral attention networks. We sought to assess cerebellar TMS magnetic field effect within individually defined networks of the cerebellum.

METHODS: Imaging data from schizophrenia and schizoaffective participants (n=27) in a double-blinded trial of cerebellar TMS ( NCT05343598 ) was used. Individualized resting-state connectivity fMRI maps of the cerebellum was computed for 7 canonical networks (Yeo et al 2011; Buckner et al 2011). Individualized TMS simulations were computed in SimNIBS with real-world participant-specific coil placement and intensity determination.

RESULTS: The peak stimulation effect (99th percentile) for each network in each participant was computed. The electric field induced by cerebellar TMS predominantly engaged specific functional networks more than others (p<0.001), indicating selective targeting of these networks. The strongest effects were found on default (44.4%), limbic (37%) and frontoparietal control (11.1%) networks. Cerebellar brain network organization was found to be similar in the patient sample to previously published large-sample organization.

CONCLUSIONS: For personalized TMS, it is important to consider the targeted network, as well as the potential off-target network effects. Our findings demonstrate that cerebellar TMS has the strongest field effect on non-motor, cognitive and affective networks within the cerebellum. These results suggest cerebellar TMS may be ideal for schizophrenia symptoms unaddressed by pharmacological treatments, and effects may vary by individual network topology.

PMID:41480026 | PMC:PMC12755297 | DOI:10.64898/2025.12.19.25342404