Most recent paper

Front Neurol. 2026 Aug 7;17:1796906. doi: 10.3389/fneur.2026.1796906. eCollection 2026.

ABSTRACT

BACKGROUND AND PURPOSE: Clinical evaluation of subjective tinnitus mainly depends on patients' self-reported auditory complaints, and standardized neuroimaging biomarkers for characterizing its central brain functional abnormalities remain lacking. The aim of this study is to utilize the resting-state functional magnetic resonance imaging (rs-fMRI) machine learning technique based on the region of interest (ROI), and to construct an exploratory classification framework for subjective tinnitus by analyzing functional activities and connectivity.

METHODS: The rs-fMRI data of 63 patients with subjective tinnitus (38.79 ± 15.79) and 84 healthy controls (HCs) (42.01 ± 9.45) were collected from the Department of Otorhinolaryngology, the first affiliated Hospital of Nanchang University. Five analysis methods were used: regional homogeneity (ReHo), amplitude of low frequency fluctuation (ALFF), fraction amplitude of low frequency fluctuation (fALFF), resting state functional connectivity (RSFC) and degree centrality (DC). A total of 7,134 features are extracted after z conversion. Then, the predicted features were selected through Mann-Whitney U test, the variables with high pairwise correlation (the correlation coefficient is greater than 0.75) were removed, the least absolute shrinkage and selection operator method was used to screen the features. Finally, a machine learning model was constructed by combining logistic regression (LR), support vector machine (SVM) and random forest (RF), and the performance differences of the three models were compared.

RESULTS: 21 features are retained, including 3 zRSFCs, 1 zALFFs, 6 zfALFFs, 3 zDCs, and 8 zReHos. Based on these 21 features, the model accuracy and area under the curve constructed by LR, SVM and RF were 75.51% and 0.80, 80.27% and 0.82, 73.47% and 0.79, respectively.

CONCLUSION: Our findings indicate that the ROI-based rs-fMRI machine-learning provides preliminary proof-of-concept evidence for the objective confirmation of subjective tinnitus. The imaging information based on rs-fMRI has the potential to become a neuroimaging biomarker for tinnitus.

PMID:42630179 | PMC:PMC13493256 | DOI:10.3389/fneur.2026.1796906

Neuropsychopharmacology. 2026 Aug 21. doi: 10.1038/s41386-026-02515-x. Online ahead of print.

ABSTRACT

Evidence of heterogeneity in the trajectory of psychosis is abundant. Here, we applied group-based trajectory modeling on positive symptoms and collected resting state fMRI data of 81 medication-naïve first episode psychosis (FEP) patients during a 16-week antipsychotic drug (APD) trial. Data from 131 healthy controls (HCs) were also acquired during the trial for comparison. Three major trajectory subgroups were identified and labeled as Fast (50.6%), Delay (35.8%), and Partial responders (13.6%). Logistic regressions revealed that Fast responders (vs. Partial) showed significantly lower psychopathology symptoms prior to treatment and lower APD dosage after the trial. Moreover, Delay responders showed significant increases in executive control network resting state functional connectivity (ECN FC) during the trial towards a normalization (using HCs as reference), while Fast and Partial responders to a lesser extent. These changes were associated with treatment response (reduction in positive symptoms after the trial). Future work should harness the potential of ECN FC to inform the mechanism of delayed responses with the potential to start unraveling psychotic heterogeneity which has hampered our ability to identify new treatment strategies and lead to better clinical outcomes. (Clinical trial registration: Trajectories of Treatment Response as Window into the Heterogeneity of Psychosis: A Longitudinal Multimodal Imaging Study, NCT03442101 https://clinicaltrials.gov/ct2/show/NCT03442101 . Glutamate, Brain Connectivity and Duration of Untreated Psychosis (DUP), NCT02034253 https://clinicaltrials.gov/ct2/show/NCT02034253 ).

PMID:42629434 | DOI:10.1038/s41386-026-02515-x

J Autism Dev Disord. 2026 Aug 21. doi: 10.1007/s10803-026-07358-5. Online ahead of print.

ABSTRACT

PURPOSE: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by atypical interactions between brain networks. These interactions and the resulting dynamic shifts are effectively captured by Hidden Markov Models (HMMs) in comparison to static functional connectivity (FC)-based approaches. This review aims to meta-analyze the application of HMM to resting-state fMRI (rs-fMRI) in individuals with ASD.

METHODS: A systematic search of PubMed, Scopus, and Web of Science was conducted in May 2025. Screening followed PRISMA 2020 guidelines, with independent review and consensus resolution. Eligible studies were peer-reviewed, English-language publications that have applied HMMs to rs-fMRI in ASD, with either classification performance or state-metric outcomes reported.

RESULTS: Seven studies met eligibility criteria. HMM-derived metrics demonstrated diagnostic utility, with a pooled log odds ratio (log OR) of 2.86 (95% CI: 1.74-3.98; z = 5.01, p < 0.001; I² = 92%) and a pooled AUC of 0.85 (95% CI: 0.72-0.98; I² = 96.9%). Substantial heterogeneity exists across both accuracy outcomes. Relative to typically developing controls, individuals with ASD showed markedly reduced mean lifetime (MLT) in default mode network (DMN)-associated states (pooled Hedges' g = -4.19; 95% CI: -5.52 to -2.85; I² = 98%) and prolonged MLT in sensory/attention hyperactivation states (g = 3.80; 95% CI: 3.43-4.16; I² = 65%), the latter rated as high certainty evidence. Fractional occupancy (FO) in DMN states was also substantially reduced (g = -6.22; 95% CI: -9.87 to -2.58; I² = 99.6%), though this outcome was rated low certainty. Narrative synthesis across consistently identified reduced FO and MLT in DMN-hypersynchrony states alongside increased occupancy in sensory-motor and attention states, replicated across two studies despite variation in atlas choice, number of HMM states, and participant samples. HMM-derived metrics were significantly negatively correlated with ADOS scores (pooled r = -0.20; 95% CI: -0.27 to -0.13; I² = 0%; p < 0.001), rated as high certainty evidence. Transition probability analyses, reported narratively due to incompatible state taxonomies, indicated reduced transitions from sensory-related to DMN-related states and increased self-transitions in sensory-motor states in ASD. Overall risk of bias was low to moderate, with incomplete confounder adjustment being the most common limitation.

CONCLUSIONS: ASD involves rigid, imbalanced temporal dynamics, with reduced engagement of integrative networks and dominance of sensory states. Leveraging its high diagnostic accuracy, HMMs capture these alterations and hold promise for mechanistic insight and personalized diagnostics, though heterogeneity remains a challenge.

REVIEW REGISTRATION: PROSPERO CRD420251057196.

PMID:42627436 | DOI:10.1007/s10803-026-07358-5

Front Psychiatry. 2026 Aug 6;17:1886224. doi: 10.3389/fpsyt.2026.1886224. eCollection 2026.

ABSTRACT

BACKGROUND: The default mode network (DMN) plays an important role in depression and sleep regulation. However, whether sleep symptoms are associated with alterations in DMN homogeneity in adolescent major depressive disorder (MDD) remains unclear. This study aimed to investigate whether sleep symptom burden is associated with alterations in DMN homogeneity in adolescents with MDD.

METHODS: Following quality control procedures, the final sample comprised 162 first-episode, drug-naïve adolescents with MDD, including 86 participants with higher sleep symptom burden (MDD-S) and 76 participants with lower sleep symptom burden (MDD-NS), together with 53 healthy controls (HCs). Sleep grouping was based on Hamilton Depression Rating Scale (HAMD) sleep items. The DMN was identified using group independent component analysis (ICA). Voxel-wise network homogeneity (NH) values within the DMN were calculated and compared among groups. Correlation analyses and exploratory support vector machine (SVM) analyses were performed.

RESULTS: Opposite-direction NH alterations in the precuneus were observed between groups with different sleep symptom burdens. Compared with HCs, the MDD-NS group showed increased NH in the right precuneus, whereas the MDD-S group exhibited decreased NH in the bilateral precuneus. Relative to the MDD-NS group, the MDD-S group showed increased NH in the left anterior cingulate cortex, posterior cingulate cortex, and angular gyrus, together with decreased NH in the right middle temporal gyrus. Exploratory SVM analyses showed modest discriminative performance, indicating limited utility of NH alterations alone for individual-level classification.

CONCLUSION: Adolescents with MDD and different levels of sleep symptoms exhibit distinct DMN homogeneity patterns. Sleep symptoms may be associated with altered DMN synchronization patterns, particularly within the precuneus. The opposite-direction precuneus alterations observed across MDD subgroups may provide a potential perspective for understanding some of the heterogeneous DMN findings reported in previous depression studies.

PMID:42626602 | PMC:PMC13492238 | DOI:10.3389/fpsyt.2026.1886224

Brain Behav. 2026 Aug;16(8):e71696. doi: 10.1002/brb3.71696.

ABSTRACT

AIMS: Residual dizziness (RD) is commonly observed in patients with benign paroxysmal positional vertigo (BPPV) following successful canalith repositioning procedures. Targeted vestibular rehabilitation therapy (tVRT) is a novel strategy designed to address specific vestibular deficits. This study aims to investigate whether tVRT can accelerate the vestibular rehabilitation process in patients with RD of BPPV and explore its neural mechanisms.

METHODS: Ninety-four BPPV patients with RD were enrolled and received a 4-week tVRT program tailored to utricular deficits. A rs-fMRI subgroup (n = 43) was used to assess brain activity and functional connectivity (FC) before and after successful intervention.

RESULTS: The tVRT group demonstrated significantly lower DHI and SAS scores and higher ABC score. rs-fMRI revealed that tVRT increased ALFF in the right superior temporal gyrus (STG), positively correlated with ABC scores, and enhanced ReHo in the right anterior cingulate cortex (ACC). The tVRT group showed enhanced STG-cerebellar tonsil connectivity, along with reduced STG-posterior cingulate cortex connectivity. Using right ACC as seed, FC between the ACC and lingual gyrus was increased. STG-cerebellar tonsil FC was negatively correlated with RD duration.

CONCLUSION: tVRT accelerates vestibular compensation in patients, which may be mediated by enhanced neural activity and reorganization of brain networks involved in vestibular processing.

PMID:42625427 | DOI:10.1002/brb3.71696

eNeuro. 2026 Aug 20:ENEURO.0155-26.2026. doi: 10.1523/ENEURO.0155-26.2026. Online ahead of print.

ABSTRACT

Visual scene analysis relies on a set of scene-selective regions in posterior cerebral cortex (OPA, PPA, MPA), with a paired memory-responsive counterpart located in anterior (LPMA, VPMA) or overlapping (MPMA) cortex. The interaction between these pairs of regions is thought to integrate visual input with mnemonic context. Recently, a fourth scene-perception area in superior parietal cortex (SPA) was identified, with a proposed role in visually guided navigation. Whether this region also has an anterior paired memory region is currently unknown. Across two independent fMRI datasets (total N=24, 14 females) using static or dynamic stimuli and distinct memory tasks, we show that recalling visual scenes evokes robust responses in a region (referred to here as SPMA) immediately anterior and dorsal to SPA. During resting-state fMRI, SPA preferentially coupled with the other scene-perception areas, while SPMA preferentially coupled with the other place memory areas. At the whole-brain level, seed-based connectivity revealed that SPA sits at the confluence of four processing streams spanning regions implicated in egocentric scene perception, map-based navigation, perspective taking, and goal-directed movement. These findings extend the perception-memory motif associated with visual scene processing to a fourth cortical surface. The widespread anatomical coupling between scene-perception and memory processes reflects the importance of this interaction for flexible, context-grounded navigation.Significance statement Prior work has identified an anatomical pairing between cortical regions specialized for scene perception and memory on the lateral and ventral surfaces. This architectural motif is thought to support integration of visual input with environmental context. Using two independent fMRI datasets, we show that a recently identified fourth scene-perception area in superior parietal cortex follows the same organizational principle, and that it sits at the confluence of cortical streams linking egocentric vision, spatial memory, and goal-directed movement. This positions superior parietal cortex as a hub for context-grounded navigation.

PMID:42624782 | DOI:10.1523/ENEURO.0155-26.2026

PLoS One. 2026 Aug 20;21(8):e0356601. doi: 10.1371/journal.pone.0356601. eCollection 2026.

ABSTRACT

BACKGROUND: Nonsuicidal self-injury (NSSI) is prevalent and harmful among adolescents with major depressive disorder (MDD), threatening mental and physical health. This study aims to elucidate the poorly understood neural mechanisms underlying NSSI behaviors and motivations in this group.

METHODS: 133 adolescent participants were recruited, comprising 45 MDD with NSSI, 46 MDD without NSSI, and 42 age- and sex-matched healthy controls. All underwent resting-state functional MRI, from which low-frequency amplitude fluctuations (ALFF) were assessed and regions showing group differences were used as seeds for functional connectivity (FC) analyses. Associations between ALFF/FC values and NSSI behaviors and motivations were then evaluated via a cross-validation prediction method for robustness and generalizability.

RESULTS: Adolescents with MDD who engaged in NSSI showed increased ALFF in the left precuneus, significantly associated with NSSI behaviors, and increased left precuneus-left cuneus FC, significantly associated with behaviors and intrapersonal negative reinforcement motivations. Prediction analyses confirmed the robustness of these associations, with ALFF (r(predicted, observed) = 0.653, p = 0.001) and FC (r(predicted, observed) = 0.601, p = 0.001; r(predicted, observed) = 0.587, p = 0.001).

CONCLUSION: Our study identified key alterations in brain activity associated with NSSI behaviors and motivations in adolescents with MDD, providing neural markers for NSSI prediction and diagnosis and targets for precision interventions.

PMID:42623393 | DOI:10.1371/journal.pone.0356601

Front Neurosci. 2026 Aug 5;20:1910411. doi: 10.3389/fnins.2026.1910411. eCollection 2026.

ABSTRACT

[This corrects the article DOI: 10.3389/fpubh.2025.1714795.].

PMID:42621443 | PMC:PMC13488161 | DOI:10.3389/fnins.2026.1910411

Front Hum Neurosci. 2026 Aug 5;20:1945667. doi: 10.3389/fnhum.2026.1945667. eCollection 2026.

ABSTRACT

Graphical abstract-Neuroimaging in affective neuroscience.Infographic presenting four interconnected panels describing convergent affective neurocircuitry using brain diagrams, connectivity maps, and summary points for mTBI, IBS and depression, nurse burnout, and alexithymia in multiple sclerosis, with central emphasis on network dysfunction and distributed brain region involvement.

PMID:42620957 | PMC:PMC13485877 | DOI:10.3389/fnhum.2026.1945667

bioRxiv [Preprint]. 2026 Aug 6:2026.08.05.743099. doi: 10.64898/2026.08.05.743099.

ABSTRACT

BACKGROUND: Individuals with early psychosis (EP) have elevated risk for suicide, the leading cause of death in the first five years following diagnosis. Non-suicidal self-injury (NSSI) significantly predicts suicidal behavior, yet studies of self-injury often exclude participants with psychosis. We investigated effective connectivity in emotion regulation and reward network regions among participants with lifetime history of NSSI or suicide attempt (SA) with and without EP.

METHODS: Resting-state fMRI data were acquired for 23 individuals with EP and 34 non-clinical controls (NCC). We estimated effective connectivity models for regions implicated in the self-injury literature: middle cingulate cortex (MCC), posterior cingulate cortex (PCC), caudate, putamen, posterior superior temporal gyrus (STG), orbitofrontal cortex (OFC), and insula. There were 3 models characterizing different groupings: diagnosis (NCC vs. EP); NSSI (present[+], n=21 vs. absent[-], n=36); and SA (present[+], n=21 vs. absent[-], n=36).

RESULTS: EP was associated with increased STG to PCC and insula to putamen connectivity. NSSI+ (n=7 NCC, 14 EP) had increased PCC to insula lagged connectivity and increased contemporaneous bilateral putamen activity, relative to NSSI- (n=27 NCC, 9 EP). NSSI was positively correlated with lagged insula to putamen activity (p=0.016). SA and NSSI were associated with reduced PCC to caudate connectivity.

CONCLUSION: NSSI is associated with increased connectivity within emotion regulation regions and disrupted connectivity between emotion regulation and reward networks modulated by the STG and striatum. Findings are consistent with broader self-injury literature, supporting the utility of using similar interventions from other disorders to address self-injury within EP.

PMID:42620300 | PMC:PMC13484717 | DOI:10.64898/2026.08.05.743099

ArXiv [Preprint]. 2026 Jul 28:arXiv:2607.24356v2.

ABSTRACT

Resting-state functional connectivity (FC) is altered in Alzheimer's disease (AD), widely regarded as a distributed network process; whether its signature reduces to a few focal sites has not been tested causally, a question central to targeted neuromodulation. We fit subject-specific, cross-subject-identifiable models whose free-running dynamics reproduce those of each individual patient. The fitted model parameters classify AD from controls at modest accuracy, below that of structural atrophy; we build on the functional model nonetheless, because dynamics, not tissue loss, are what stimulation can act on. Changing a virtual patient's model connectivity toward the control template reverts its AD classification, establishing in silico that the disease signature is correctable, yet the required correction is intrinsically distributed: a coordinated, multi-site change of the model connectivity that no single-node edit reproduces. Where, then, should a physically realisable focal drive act? A single-site drive at the node whose connectivity is most altered fails to revert the classification even at supra-physiological amplitudes, whereas selecting each patient's site by its effect on the disease discriminant achieves complete, individualised reclassification from one site, and a real-time closed-loop controller reaches comparable efficacy at lower dose using only causally available information. Optimal targets are cortical and heterogeneous: the site to stimulate is not where connectivity is most altered but where the network is most therapeutically responsive.

PMID:42619899 | PMC:PMC13484419

bioRxiv [Preprint]. 2026 Jul 28:2026.07.24.740545. doi: 10.64898/2026.07.24.740545.

ABSTRACT

INTRODUCTION: Anhedonia is a transdiagnostic psychiatric symptom linked to increased functional connectivity between the prefrontal cortex and striatum. Here, we examined how dimensions of early adversity contribute to this profile of connectivity.

METHODS: In a European community sample of young adults (IMAGEN), we examined cross-sectional (n=613) and longitudinal (n=332) associations of adversity dimensions with resting-state fMRI-derived connectivity. We selected 10 ROIs from anhedonia literature, defined in the functional images as 4mm-radius spheres. We then used network-based regression models to identify clusters of ROI-ROI connections associated with threat and deprivation scores, using interaction terms to examine sex and age-specific associations. We also examined associations between adversity and anhedonia, operationalized using factor analysis of six items from self-report surveys.

RESULTS: At age 18-22, we identified sex-specific associations between deprivation and connectivity for a cluster of 9 ROI-ROI connections ( p-FWE =0.038), primarily involving the nucleus accumbens. Specifically, we observed positive associations between deprivation and connectivity in males, and negative associations in females. In the longitudinal analysis, negative deprivation associations in females attenuated with age for a cluster of 14 connections ( p-FWE =0.009). A cluster of 17 connections also had initial positive associations with threat in females that attenuated with age ( p-FWE =0.008). No such longitudinal changes were observed in males. Higher deprivation was linked to increased later anhedonia in males but not females ( p =0.026).

CONCLUSION: Compared to females, young adult males may be more vulnerable to developing anhedonia after experiencing deprivation in childhood. Dimensions of early adversity are linked to distinct pathways of frontostriatal development.

PMID:42619809 | PMC:PMC13483791 | DOI:10.64898/2026.07.24.740545

Brain Res Bull. 2026 Aug 19:112090. doi: 10.1016/j.brainresbull.2026.112090. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate neurovascular coupling (NVC) alterations in pediatric acute lymphoblastic leukemia (ALL) patients following chemotherapy using multimodal neuroimaging.

METHODS: We combined arterial spin labeling (ASL) and resting-state functional MRI (rs-fMRI) to assess the relationship between cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD)-derived resting-state metrics, including amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and degree centrality (DC), in 23 children with ALL (age range, 7-15 years) and 30 healthy controls (age range, 6-13 years).

RESULTS: Children with ALL assessed after chemotherapy showed significant regional differences in NVC indices compared with healthy controls. The ALL group demonstrated significantly lower Perceptual Reasoning Index (PRI) and Full-Scale Intelligence Quotient (FSIQ) scores after adjustment for education (p < 0.05). No significant between-group differences were found in the whole-brain CBF-ALFF, CBF-fALFF, CBF-ReHo, or CBF-DC coefficients (all p > 0.05). Regional NVC analysis revealed consistently reduced ratios in the right middle temporal gyrus and increased ratios in several left-sided cortical and subcortical regions, including the hippocampus, thalamus, and lingual gyrus. After false discovery rate (FDR) correction, no significant correlations were found between regional NVC metrics and cognitive scores (all corrected q > 0.05).

CONCLUSION: Children with ALL show altered NVC in multiple brain regions after chemotherapy. However, no direct associations with cognitive scores survived stringent correction, and these findings should be considered preliminary imaging evidence of regional brain functional differences in this population.

PMID:42617922 | DOI:10.1016/j.brainresbull.2026.112090

Psychiatry Res Neuroimaging. 2026 Aug 17;363:112304. doi: 10.1016/j.pscychresns.2026.112304. Online ahead of print.

ABSTRACT

The pathological mechanisms of depression are not yet fully clear, and the causative factors remain somewhat ambiguous. Clinical diagnosis of depression is often challenging and complex, frequently leading to misdiagnosis and missed diagnoses. Combining deep learning with resting-state fMRI can quantify the degree of abnormal brain function caused by depression and automatically screen for discriminative features that aid in the classification and identification of depression, which may serve as hypothesis-generating discriminative features within the current dataset, providing candidate neuroimaging signatures that warrant further investigation. This paper proposes a cross-site fMRI data analysis framwork for depression. First, it contains a graph deep learning-based auxiliary diagnostic method, which fully leverages the topological structure of brain networks to achieve higher classification accuracy compared to existing models, with interpretable results. Building on this network, the framework also contains a domain-adversarial-based cross-site semi-supervised transfer method is proposed, making full use of multi-site data to analyze depression-related brain networks and ROIs. Finally, based on cross site data, the distribution of brain networks and brain regions was discussed. The research findings are consistent with existing studies, confirming the reliability of this method. Furthermore, we validated the cross-dataset generalizability of our framework on an independent OpenNeuro dataset, where adversarial transfer consistently outperformed direct transfer, demonstrating the potential of our approach to generalize beyond the original consortium.

PMID:42617283 | DOI:10.1016/j.pscychresns.2026.112304

Lasers Med Sci. 2026 Aug 19;41(1):197. doi: 10.1007/s10103-026-04992-4.

ABSTRACT

Purpose previous studies have suggested that laser acupuncture (LA) may influence autonomic nervous system (ANS) activity and brain functional connectivity (FC); however, the underlying neural mechanisms and potential sex-dependent responses remain to be further investigated. Using resting-state functional magnetic resonance imaging (fMRI), we examined the effects of LA at different energy densities (EDs), hypothesizing that varying dosages elicit differential brain responses influenced by biological sex. Methods we enrolled 60 healthy adults of both sexes aged 18-55 years with a BMI of 18.5-24 kg/m². Participants were randomized into three groups (n = 20 each) receiving LA at EDs of 0, 7.96, or 23.87 J/cm², with male/female distributions of 7/13, 7/13, and 9/11, respectively. Bilateral PC6 (Neiguan) was stimulated, and two 500-second resting-state fMRI scans were acquired before and after LA to analyze FC between ANS-related brainstem regions and other brain areas by sex. Results female-specific analyses more closely resembled previously reported sex-independent results, indicating females as the primary contributing subgroup. Accordingly, in females, LA at 23.87 J/cm² enhanced FC between the rostral ventrolateral medulla and orbitofrontal cortex (OFC), while reducing FC between the caudal ventrolateral medulla (CVLM), nucleus of the solitary tract/nucleus ambiguus, and dorsal motor nucleus of the vagus with the sensorimotor cortex (SMC). In males, 23.87 and 7.96 J/cm² LA decreased FC between the CVLM and OFC, with no significant changes between all regions of interest (ROIs) and SMC. Conclusion different EDs of LA elicited distinct FC changes in males and females between ROIs and other brain areas, while PRV findings showed limited evidence of sex-dependent autonomic modulation.

PMID:42616158 | DOI:10.1007/s10103-026-04992-4

Sci Rep. 2026 Aug 18;16(1):24914. doi: 10.1038/s41598-026-63059-0.

ABSTRACT

College students often struggle to regulate emotions under changing academic and social stress, highlighting the need for interventions targeting adaptive emotion regulation (ER). Here, we tested a 5-week online intervention designed to enhance ER and cognitive flexibility in college students. Participants (N = 39) were pseudo-randomly assigned to the experimental (N = 20) or control (N = 19) group, with higher distress individuals preferentially assigned to the experimental condition. Behavioral, self-report, eye-tracking, and brain imaging measures were collected before and after the training. Compared to controls, the experimental group participants showed reduced emotional reactivity to negative stimuli and experiences, along with reduced visual attention to emotionally salient regions. They also showed improvements in the use of attention strategies, positive refocusing, and perceived cognitive control. In the imaging subsample (N = 23; Experimental: N = 15; Control: N = 8), these improvements were accompanied by changes in resting-state functional connectivity, including reduced coupling between affective and higher-order systems and increased efficiency of attentional control and self-referential pathways. These results suggest that training promoted more efficient and flexible interactions among emotion, attention, and cognitive control regions, providing a neural mechanism for the observed behavioral benefits. Overall, the findings support the intervention as a promising approach for improving adaptive ER and resilience during emerging adulthood.

PMID:42613380 | DOI:10.1038/s41598-026-63059-0

Transl Psychiatry. 2026 Aug 18;16(1):417. doi: 10.1038/s41398-026-04392-w.

ABSTRACT

Rumination has been associated with aberrant dynamics of a coactivation pattern (CAP) comprising the default mode (DMN) and frontoparietal (FPN) networks. Ketamine exerts rapid antidepressant effects and may influence these dynamics via glutamatergic mechanisms. In a randomized, double-blind, placebo-controlled fMRI study, we investigated ketamine's effects on dynamic CAPs associated with rumination and examined whether inhibition of glutamatergic release through lamotrigine attenuates these effects. Seventy-five healthy adults were randomized to placebo-placebo, placebo-ketamine, or lamotrigine-ketamine treatment. Resting-state fMRI was acquired at baseline, during ketamine/placebo infusion, and 24 h post-infusion. Whole-brain CAP analysis identified seven recurring network configurations. Occurrence rates were examined for group differences, while controlling for age, sex, and drug plasma concentrations. Rumination was assessed using a validated self-report questionnaire. A hybrid DMN + FPN CAP showed a positive association with rumination at baseline. Ketamine acutely reduced the occurrence rate of this hybrid CAP compared to placebo, with larger decreases in individuals reporting higher rumination. These effects were transient, returning to baseline after 24 h. Exploratorily, ketamine also reduced engagement of a canonical somatomotor CAP during infusion. Lamotrigine pretreatment nominally attenuated ketamine-induced changes across analyses. Ketamine transiently alters dynamic brain states implicated in rumination and somatosensory processing, and preliminary evidence suggests partial glutamatergic mediation. These findings provide insights into ketamine's mechanism of action.

PMID:42613319 | DOI:10.1038/s41398-026-04392-w

J Affect Disord. 2026 Aug 18:122395. doi: 10.1016/j.jad.2026.122395. Online ahead of print.

ABSTRACT

OBJECTIVE: Post-stroke depression (PSD) is under-recognized and associated with poorer rehabilitation outcomes and quality of life. We characterized PSD-related alterations in large-scale brain network dynamics and evaluated their cross-center classification performance.

METHODS: This dual-center cross-sectional study included 300 patients with post-stroke motor impairment: 100 with and 100 without PSD in the development cohort, and 50 per group in the external validation cohort. Resting-state functional MRI, sliding-window dynamic functional connectivity, and clustering across K = 2-8 state resolutions were combined with nested cross-validation, nine machine-learning classifiers, and SHAP interpretation. Sensitivity analysis excluded users of antidepressants, anxiolytics, or sedative-hypnotics.

RESULTS: The five-state solution provided the best balance of discrimination and interpretability. The support vector machine achieved internally cross-validated and external validation AUCs of 0.838 and 0.784, respectively. Higher proportion and longer dwell time of a globally integrated state, lower proportion and dwell time of a stable modular state, and higher self-transition probability of a low-integration state shifted classification toward PSD. After medication users were excluded, the artificial neural network under the five-state solution achieved internally cross-validated and external validation AUCs of 0.798 and 0.793, respectively; a higher proportion of the globally integrated state also remained among the most informative features.

CONCLUSIONS: PSD was associated with altered temporal organization and reduced stability of large-scale functional networks. Dynamic state features may serve as interpretable candidate imaging markers for PSD classification, but longitudinal multicenter validation is required before clinical application.

PMID:42612921 | DOI:10.1016/j.jad.2026.122395

Sleep Med. 2026 Aug 12;148:109214. doi: 10.1016/j.sleep.2026.109214. Online ahead of print.

ABSTRACT

Insomnia disorder is clinically heterogeneous, with variation in objective sleep duration, sleep perception, cognitive-emotional features, and spontaneous neural activity. We examined whether insomnia with normal sleep duration (INSD) has a distinct behavioral and neural profile relative to insomnia with short sleep duration (ISSD). In 233 participants (100 healthy controls, 67 INSD, 66 ISSD), we assessed objective and diary-based sleep, presleep arousal, and emotion regulation; resting-state fMRI was additionally acquired in a subset of 133 patients with insomnia. Analyses included group comparisons, phenotype-specific associations, moderated mediation, voxel-wise z-standardized amplitude of low-frequency fluctuation (zALFF), and exploratory brain-behavior partial least squares (PLS). Both insomnia groups reported poorer subjective sleep than controls. As expected from the phenotype definitions, INSD showed greater sleep misperception than ISSD; the novel findings were that INSD also showed greater presleep cognitive arousal and brooding, distinct regional zALFF alterations, and a conditional indirect association linking brooding to sleep misperception via presleep cognitive arousal that was evident in INSD but not ISSD. Compared with ISSD, INSD showed higher zALFF in the left insula, left hippocampus, and right precuneus, and lower zALFF in the right middle occipital gyrus. Exploratory PLS linked this INSD-like zALFF pattern to a behavioral profile dominated by sleep misperception and presleep cognitive arousal, mainly at the phenotype level. These findings suggest that INSD involves convergent cognitive-emotional and neural features related to sleep misperception, while causal and individual-prediction claims remain premature.

PMID:42612566 | DOI:10.1016/j.sleep.2026.109214

Brain Topogr. 2026 Aug 18;39(5):90. doi: 10.1007/s10548-026-01246-y.

ABSTRACT

Parkinson's disease (PD) disrupts intrinsic brain networks that support motor and cognitive functions. Using resting-state fMRI from 138 PD patients and 54 controls, we combined independent component analysis (ICA) with nonlinear functional connectivity (FC) based on distance correlation. Compared with conventional Pearson-based measures, nonlinear FC revealed stronger and spatially distinct connectivity patterns, especially in parietal and sensorimotor regions. Group comparisons showed robust differences (p < 1×10⁻⁷), with four ICA networks (Components 4, 10, 19, and 20) displaying consistent alterations. Importantly, hyperconnectivity within a posterior midline network (Component 10), overlapping with regions commonly associated with the default mode network, correlated positively with Hoehn & Yahr stage (r = 0.51, p = 0.022), linking network reorganization to clinical severity. These findings demonstrate that nonlinear FC enhances sensitivity to PD-related network alterations, while spatial features highlight clinically relevant biomarkers. By integrating advanced connectivity metrics with data-driven network analysis, our study contributes to the methodological development of resting-state fMRI and its translational application to PD.

PMID:42611380 | DOI:10.1007/s10548-026-01246-y