Most recent paper

Eur Arch Psychiatry Clin Neurosci. 2026 Aug 17. doi: 10.1007/s00406-026-02351-6. Online ahead of print.

ABSTRACT

OBJECTIVE: This study aimed to investigate the whole-brain functional connectivity (FC) patterns of goal-directed/habitual systems in patients with obsessive-compulsive disorder (OCD), and to explore their exploratory classification potential and spatial associations with gene expression profiles.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) data and clinical variables were collected from 60 patients with OCD and 60 matched healthy controls (HCs). Seed-to-whole-brain FC analyses were conducted using the regions of interest (ROIs) implicated in goal-directed/habitual systems. Pearson correlation analyses were conducted to assess the associations between altered FCs and clinical characteristics. An exploratory support vector machine (SVM) analysis was utilized to evaluate whether altered FC patterns could distinguish patients with OCD from HCs, and neuroimaging-transcriptomic analysis was performed to investigate the spatial association between aberrant FCs and gene expression profiles.

RESULTS: Compared to HCs, patients with OCD exhibited decreased FCs between goal-directed system and the default mode network (DMN) and central executive network (CEN), as well as between habitual system and salience network (SN). Conversely, increased FCs were observed between habitual system and DMN. No significant correlations were observed between altered FCs and clinical characteristics after multiple-comparison correction. Exploratory SVM analysis indicated that altered FC patterns of goal-directed system showed higher classification performance (accuracy = 90.83%, AUC = 0.951) than those of the habitual system (accuracy = 79.17%, AUC = 0.867). Imaging-transcriptomic analysis revealed that regional FC alterations were spatially associated with gene (i.e., PPARD and SLC25A12), which were enriched in transmembrane ion transport and metal ion homeostasis.

CONCLUSION: OCD exhibited altered FCs patterns between goal-directed/habitual systems and the triple networks at rest. These findings may provide more information to understand the pathology of OCD.

PMID:42608583 | DOI:10.1007/s00406-026-02351-6

J Neurosci. 2026 Aug 17:e0274262026. doi: 10.1523/JNEUROSCI.0274-26.2026. Online ahead of print.

ABSTRACT

Anhedonia reflects a transdiagnostic deficit in a range of processes that impact reward and motivation. While human neuroimaging has mainly focused on striatal-related alterations in anhedonia, animal models suggest hippocampal [HPC] novelty processing regulates mesolimbic dopamine activity, implicating mesolimbic-HPC alterations in anhedonia. Childhood trauma, which disproportionately impacts HPC structure and function, may exacerbate this vulnerability. The present study of 37 males and 55 females examined whether HPC alterations interact with childhood trauma to predict anhedonia in humans. Using fMRI in a sample enriched for anhedonia, we assessed three HPC-related processes: resting-state connectivity with mesolimbic targets in the ventral tegmental area [VTA] and nucleus accumbens [NAc], task-based HPC novelty response, and task-based HPC modulation of VTA activation reflecting novelty-evoked facilitation of target detection. Significant interactions emerged for anticipatory anhedonia: reduced HPC-NAc connectivity, reduced novelty response, and weaker HPC→VTA modulation were each associated with greater anticipatory anhedonia among individuals with high childhood trauma. Moreover, LASSO regression confirmed these interactions as unique predictors. These findings suggest that early life adversity interacts with alterations in HPC-mesolimbic signaling to contribute to individual differences in anhedonia, highlighting the HPC as a potential target of motivation-related deficits in striatum.Significance Statement The ability to process rewarding stimuli and initiate goal-directed behavior is critical for human functioning. While human neuroimaging has highlighted the role of striatal function in these processes, animal evidence suggests that hippocampal modulation of mesolimbic dopamine signaling is critical for motivated behavior. The present study translates this framework to humans, demonstrating that hippocampal-mesolimbic functional integrity interacts with childhood trauma to predict individual differences in anticipatory anhedonia (i.e., impairments in one's ability to anticipate and pursue rewards). These findings implicate the hippocampus as a potential upstream contributor to motivational deficits and highlight early life stress as a key context in which mesolimbic circuit dysfunction becomes behaviorally relevant.

PMID:42608204 | DOI:10.1523/JNEUROSCI.0274-26.2026

J Affect Disord. 2026 Aug 17:122394. doi: 10.1016/j.jad.2026.122394. Online ahead of print.

ABSTRACT

BACKGROUND: Early-life exposure to chronic and unpredictable stress is a major risk factor for affective disorders, yet the neurodevelopmental mechanisms linking such exposure to emotional vulnerability remain unclear. War-related environments represent an extreme form of environmental unpredictability and may shape how children's attachment-related characteristics relate to the organization of cognitive-limbic brain systems. Here we test whether war-related exposure moderates this brain-behavior association, rather than producing uniform group-level differences.

METHODS: Seventy-nine children (42 war-exposed; 37 non-exposed) underwent behavioral assessment and resting-state fMRI. Executive functions (EF) were assessed via parent report, attachment-related characteristics via the Experiences in Close Relationships questionnaire, and war exposure via a structured exposure index. Functional connectivity analyses focused on large-scale executive-control networks and limbic circuits.

RESULTS: The war-exposed and non-exposed groups did not differ significantly in attachment-related characteristics, and group differences in parent-reported EF were no longer significant after adjustment for scan timing and nonverbal ability. At the neural level, the two groups showed divergent patterns of association between attachment-related characteristics and limbic connectivity. Critically, attachment-related difficulties were associated with distinct connectivity patterns depending on exposure status: in the war-exposed group, greater attachment-related anxiety and avoidance were associated with reduced cingulate-amygdala connectivity, whereas in the non-exposed group the same characteristics were associated with reduced amygdala-hippocampal connectivity. For large-scale networks, the direction of the attachment-connectivity association shifted across exposure levels, from negative at lower exposure to positive at higher exposure; these within-level simple slopes did not survive correction for multiple comparisons and are interpreted with caution.

CONCLUSIONS: War-related exposure was associated with distinct patterns of association between children's attachment-related characteristics and cognitive-limbic connectivity, rather than with uniform group-level differences in attachment or connectivity. These findings provide preliminary evidence that environmental adversity may moderate brain-behavior coupling in childhood; longitudinal studies with validated exposure and symptom measures are needed to clarify causal mechanisms.

PMID:42607893 | DOI:10.1016/j.jad.2026.122394

Brain Inform. 2026 Jul 26;13(1):37. doi: 10.1186/s40708-026-00324-y.

ABSTRACT

This study introduces a graph theory-based machine learning framework to analyze functional brain networks in Multiple Sclerosis (MS) patients during working memory tasks. Using fMRI data from 22 participants (8 MS patients/14 controls) performing a Persian n-back task, we constructed functional connectivity networks with an automated anatomical labeling atlas (116 regions). Novel methodological contributions include: a proportional thresholding approach (5-80% connectivity strength) to optimize network analysis, and extraction of six graph-theoretic features (degree, clustering coefficient, betweenness/eigenvector/page-rank/k-coreness centrality) for classification. Machine learning models (SVM, decision trees, kNN) were trained on task-specific networks (1-back, 2-back, 3-back), with leave-one-subject-out validation. The 3-back task (high cognitive load) yielded superior classification (95.5% accuracy) using SVM with degree, k-coreness, and eigenvector centrality features, outperforming traditional resting-state approaches. Key innovations include identification of the cerebellum (1-back) and orbitofrontal cortex (3-back) as novel discriminative hubs, and demonstration that task difficulty modulates network separability. Results indicate MS patients exhibit impaired high-load connectivity patterns, with the proposed framework showing potential as an auxiliary diagnostic tool. The study provides both a technical blueprint for task-based network analysis and clinically relevant insights into MS-related cognitive impairment, bridging engineering methodologies with neurological applications.

PMID:42606763 | DOI:10.1186/s40708-026-00324-y

Biol Psychiatry Glob Open Sci. 2026 Jul 8;6(5):100787. doi: 10.1016/j.bpsgos.2026.100787. eCollection 2026 Sep.

ABSTRACT

BACKGROUND: Prevailing theories propose that autism is characterized by local cortical overconnectivity and long-range underconnectivity, but empirical evidence remains mixed.

METHODS: Here, we applied the turbulence dynamics framework to the ABIDE (Autism Brain Imaging Data Exchange) dataset (N = 1009) to examine how functional synchronization profiles dynamically change over time and across the cortex over different spatial scales.

RESULTS: Autistic individuals showed increased short-range and reduced long-range functional synchronization variability over time, as well as reduced synchronization strength across all spatial scales. Synchronization also decayed more rapidly with distance and exerted weaker influence across scales in autism. These distance-specific alterations suggest that local hyperconnectivity may be associated with turbulent synchronization dynamics that fail to propagate coherently across the cortex, resulting in an overly rigid brain organization at longer distances. Mapping these effects onto the sensorimotor-association cortical gradient revealed increased variability in sensorimotor regions and decreased variability in the association cortex.

CONCLUSIONS: Together, we found evidence of disturbances in functional synchronization dynamics at different spatial scales and along hierarchical brain gradients in autistic individuals. These results consolidate ideas about dynamic functional connectomic organization in autism and situate these alterations along hierarchical brain gradients that are closely linked to neurodevelopmental processes.

PMID:42602560 | PMC:PMC13475223 | DOI:10.1016/j.bpsgos.2026.100787

Front Hum Neurosci. 2026 Jul 31;20:1753838. doi: 10.3389/fnhum.2026.1753838. eCollection 2026.

ABSTRACT

BACKGROUND: Previous work has shown that endurance training is associated with structural and functional plasticity in prefrontal, hippocampal, cerebellar and network level regions using both cross sectional and longitudinal designs. The present study extends this foundation by examining how key endurance indicators relate to multimodal neural characteristics across different training levels.

METHODS: Thirty-two male participants were classified into high level endurance athletes, moderately trained runners and healthy active controls. All participants completed structural MRI and resting state functional MRI together with graded exercise testing to assess maximal oxygen consumption, relative maximal oxygen consumption, lactate threshold and individual lactate threshold (ILT). Gray matter volume, fractional amplitude of low frequency fluctuations and degree centrality were extracted from predefined regions of interest. Correlation analyses were first conducted in the full sample and within subgroups, followed by false discovery rate correction within imaging modalities. Associations surviving FDR correction were further evaluated using Spearman rank correlations, bootstrap confidence intervals for subgroup findings, and covariate-adjusted partial correlations as sensitivity analyses.

RESULTS: Across all participants, incremental exercise-capacity indicators were associated with multimodal neural characteristics in prefrontal, premotor, precuneus, temporal, and posterior cerebellar regions, with additional negative associations observed in the thalamus and inferior cerebellum in the uncorrected analyses. After FDR correction, the surviving associations became more selective. Subgroup analyses suggested descriptively different association patterns across training levels, but these subgroup findings were less stable in sensitivity analyses and should therefore be interpreted cautiously.

CONCLUSION: Incremental exercise-capacity indicators were associated with distributed multimodal brain characteristics, and several core associations remained robust after multiple-comparison correction and supplementary analyses. The subgroup results suggested stage-related differences in brain-physiology coupling, particularly a broader pattern in moderately trained individuals and a more focal prefrontal-associated profile in high-level athletes, although these findings still require cautious interpretation.

PMID:42602297 | PMC:PMC13473415 | DOI:10.3389/fnhum.2026.1753838

Medicine (Baltimore). 2026 Aug 14;105(33):e50185. doi: 10.1097/MD.0000000000050185.

ABSTRACT

BACKGROUND: Depression poses a major global health burden. Many patients exhibit treatment resistance or experience intolerable side effects with standard therapies. Acupuncture shows promise as an adjunctive therapy for depression, but its neurobiological mechanisms remain incompletely understood.

METHODS: We conducted a coordinate-based meta-analysis to identify consistent patterns of acupuncture-induced neuroplastic changes in patients with major depressive disorder, quantified via resting-state functional magnetic resonance imaging measures of regional homogeneity and amplitude of low-frequency fluctuations (ALFF/fractional ALFF). We synthesized data from 7 randomized controlled trials involving 357 patients with major depressive disorder, comparing acupuncture-based interventions (manual acupuncture, electroacupuncture, or transcutaneous auricular vagus nerve stimulation) against sham acupuncture, conventional treatment, or treatment-as-usual. The seed-based d mapping with permutation of subject images algorithm was used for the imaging meta-analysis, and a leave-one-out sensitivity analysis was performed to assess the robustness of the pooled findings to intervention heterogeneity.

RESULTS: Acupuncture induced significant regional homogeneity /ALFF increases within the right cingulum and right caudate nucleus. In contrast, conventional treatments primarily increased activity in the left hippocampus and right middle occipital gyrus. Meta-regression linked clinical improvement specifically to plasticity changes in the left cerebellum and revealed a dose-dependent relationship between the number of acupuncture sessions and modulation of the left amygdala. Clinically, acupuncture produced significantly greater reductions in depression and anxiety scores than control conditions.

CONCLUSION: Our findings indicate that acupuncture-based interventions elicit a distinct pattern of neuroplastic remodeling, targeting key regions involved in emotion regulation and reward processing, which contrasts with the hippocampal-occipital effects of conventional treatments. The correlation between neuroplastic changes in affective circuits and clinical improvement supports a potential mechanism for acupuncture's efficacy in alleviating core depressive symptoms such as anhedonia and emotional dysregulation. Limitations include the small number of included trials, heterogeneity in acupuncture protocols and resting-state functional magnetic resonance imaging metrics, absence of long-term follow-up data, and methodological caveats inherent to coordinate-based meta-analysis. Future research requires larger, standardized trials with follow-up assessments and integration of neuroimaging with molecular biomarkers to advance personalized neuromodulation strategies for depression.

PMID:42601716 | DOI:10.1097/MD.0000000000050185

Geroscience. 2026 Aug 14. doi: 10.1007/s11357-026-02449-8. Online ahead of print.

ABSTRACT

Understanding how brain connectivity reorganizes with age is essential for characterizing healthy aging. While static functional connectivity (sFC) has revealed broad age-related shifts in network segregation and integration, recent work underscores the need to examine how these patterns dynamically fluctuate over time to better understand cognitive decline and resilience in aging. The present resting-state fMRI study was conducted to enhance comprehension of the temporal variability and dynamics of the brain's functional architecture in the context of the aging process. To this end, dynamic functional connectivity (dFC) was extracted in 817 older adults between 55 and 85 years from the 1000BRAINS study. Using a sliding window and clustering approach, we identified four recurring dFC states and quantified temporal metrics, e.g., mean dwell time, or number of transitions. Overall, aging was associated with slower and less flexible network dynamics: integrative states became less frequent, whereas segregated states dominated, reflecting reduced inter-network communication, although the effect size was relatively small. Age-stratified analyses yielded two novel insights, thereby suggesting a refinement of the so far established theories of aging and giving rise to a new model of age-related differences in functional connectivity: First, trajectories of dedifferentiation and segregation shown from younger to older adults seem to stabilize during the transition from mid-to-old age and turn into a process of re-segregation and overcompensation during older-old ages, challenging the assumption of a monotonic increase in integration across the lifespan. Secondly, opposing links between dFC and cognitive performance have been identified, with greater network integration supporting better cognitive performance in mid-to-old adults but poorer cognitive performance in older-old adults. This suggests a shift from dedifferentiated to re-segregated connectivity with advancing age. Sex-stratified modeling further demonstrated stronger age-related reductions in flexibility among females, indicating that pooled analyses might obscure systematic sex-specific dynamics and highlighting divergent adaptive and vulnerability profiles across aging. The findings of this study emphasize the necessity of accounting for temporal variability in age-related changes of functional brain connectivity when studying aging, specifically during advanced age, with the aim of enhancing comprehension of cognitive variability.

PMID:42601544 | DOI:10.1007/s11357-026-02449-8

Behav Brain Res. 2026 Aug 14:116425. doi: 10.1016/j.bbr.2026.116425. Online ahead of print.

ABSTRACT

Problematic online behaviors often span multiple digital platforms, yet previous research has focused on single forms of problematic use. It remains unclear whether distinct cross-platform behavioral profiles are associated with differential reward and punishment sensitivity and alterations in brain network topology. This study combined latent profile analysis with resting-state functional magnetic resonance imaging to identify latent risk profiles of cross-platform problematic online behaviors among Chinese university students and examine their motivational and neural correlates. In Study 1, 947 students completed measures of problematic usage of smartphones, video gaming, and social networking, and reward/punishment sensitivity. Latent profile analysis identified three graded profiles: Low-Risk, Medium-Risk, and High-Risk. In Study 2, a stratified subsample of 150 participants underwent resting-state functional magnetic resonance imaging; whole-brain eigenvector centrality (EC) indexed hub-like network properties. The Medium-Risk and High-Risk groups showed higher reward sensitivity than the Low-Risk group, with no difference between at-risk groups. Punishment sensitivity increased stepwise across profiles. Neuroimaging analyses revealed reduced EC in the left superior frontal gyrus and left precuneus in both at-risk groups relative to the Low-Risk group. Lower EC in these regions was associated with greater punishment sensitivity, whereas reward sensitivity showed no significant association with EC. These findings suggest that punishment sensitivity is not only a psychological marker of POB severity but is also associated with reduced hub centrality in the left superior frontal gyrus and left precuneus, indicating a potential neural correlate of heightened sensitivity to negative outcomes.

PMID:42600894 | DOI:10.1016/j.bbr.2026.116425

J Affect Disord. 2026 Aug 14:122383. doi: 10.1016/j.jad.2026.122383. Online ahead of print.

ABSTRACT

BACKGROUND: Orbitofrontal cortex (OFC) dysfunction contributes to major depressive disorder (MDD), particularly through disrupted network interactions. Current studies lack whole-brain coverage and fine-grained OFC mapping. We employed OFC parcellation and multi-metric connectivity to comprehensively profile OFC-related network disturbances in MDD.

METHODS: OFC was parcellated into medial (MOFC), anterior middle (aMidOFC), posterior middle (pMidOFC), and lateral (LOFC) subregions via community analysis of resting-state fMRI from 586 healthy individuals. Using these subregions and whole OFC as seeds, we computed whole-brain functional connectivity (FC), total interdependence (TI), and Granger causality (GC) from 83 MDD patients and 80 healthy controls. Group differences were evaluated, and a support vector machine integrated multi-metric indicators to identify key network alterations.

RESULTS: FC revealed altered coordination between OFC subregions and distributed networks in MDD. GC and TI showed imbalanced anterior/posterior default mode network (DMN) interactions with right MOFC, LOFC, and pMidOFC; enhanced ventral attention network influence to left MOFC and pMidOFC; increased right MOFC and left pMidOFC interactions with sensorimotor and visual systems; and reduced dorsal anterior cingulate cortex input to left LOFC. Machine learning identified that alterations involving bilateral LOFC, MOFC, and left pMidOFC with DMN, ventral attention network, and dACC contributed most to classification.

CONCLUSION: These findings reveal widespread OFC-subnetwork dysregulation in MDD, reflecting impaired coordination with distributed neural systems that may underlie the disorder's pathophysiology.

PMID:42600783 | DOI:10.1016/j.jad.2026.122383

Neurosci Lett. 2026 Aug 14:138708. doi: 10.1016/j.neulet.2026.138708. Online ahead of print.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is highly prevalent and often complicated by anxiety symptoms, yet the neurobiological features associated with anxious depression remain incompletely characterized. The amygdala-prefrontal cortex (PFC) circuit, central to affect regulation, has been implicated in anxious depressive symptoms.

METHODS: We recruited 40 MDD patients and 69 healthy controls (HCs) from Tianjin Anding Hospital. All participants underwent resting-state functional magnetic resonance imaging(fMRI) and clinical assessments. Seed-based functional connectivity (FC) analyses were performed using the bilateral amygdala based on the Automated Anatomical Labeling (AAL) atlas. Group comparisons, partial correlations, and regression analyses tested associations between amygdala-based FC and HDRS-17 symptom dimensions, with subgroup analyses distinguishing MDD patients with and without anxiety.

RESULTS: Compared with HCs, MDD patients exhibited reduced FC between the right amygdala and prefrontal cortex, including the right middle frontal gyrus (MFG) and the left inferior frontal gyrus, triangular part (IFGtri) (GRF: voxel-level p < 0.001, cluster-level p < 0.05). Within the MDD group, higher right amygdala-MFG FC values were associated with HDRS-17 symptoms, including total scores and depressive and somatic symptom dimensions (r = 0.393, p = 0.020; r = 0.360, p = 0.033; r = 0.351, p = 0.039, uncorrected p). In exploratory subgroup analyses, right amygdala-MFG FC showed a positive association with HDRS-17 scores in MDD patients with anxiety (R2 = 0.280, F = 8.957, p = 0.006, Beta = 0.529, t = 2.993, p = 0.006); however, the FC × anxiety subgroup interaction did not reach statistical significance.

CONCLUSION: Our findings identify disrupted right amygdala-MFG connectivity as a potential neural correlate of symptom heterogeneity in MDD, particularly in patients with anxiety symptoms.

PMID:42600677 | DOI:10.1016/j.neulet.2026.138708

Brain Imaging Behav. 2026 Aug 14;20(4):121. doi: 10.1007/s11682-026-01192-0.

ABSTRACT

To investigate alterations in the amplitude of low-frequency fluctuations (ALFF) in herpes simplex encephalitis (HSE) patients using resting-state functional magnetic resonance imaging (rs-fMRI) and evaluate their associations with anxiety symptoms. In this single-center cohort study, 45 HSE patients and 46 healthy controls (HC) were recruited from the First Affiliated Hospital of Zhejiang University School of Medicine, China. HSE was confirmed by clinical features and positive herpes simplex virus (HSV) DNA in cerebrospinal fluid via polymerase chain reaction. Participants underwent rs-fMRI scans within one week of ICU admission. ALFF was calculated using REST software; group differences were assessed with voxel-wise two-sample t-tests (covariates: age, sex, education, framewise displacement; whole-brain voxel-wise FDR-corrected P < 0.05) and validated nonparametrically. Associations between ALFF and anxiety (Hamilton Anxiety Rating Scale, HAMA) were examined via general linear models, controlling for age, sex, hypertension, and education, with Spearman's correlations for robustness. Compared to HC, HSE patients exhibited increased ALFF in the left precuneus and right putamen, alongside decreased ALFF in the right angular gyrus and right caudate nucleus (whole-brain voxel-wise FDR-corrected P < 0.05). These changes correlated significantly with HAMA scores: positive associations in hyperactive regions (left precuneus: β = 0.558, 95% CI: 0.312 to 0.805, p < 0.001; right putamen: β = 0.511, 95% CI: 0.254 to 0.768, p < 0.001) and negative associations in hypoactive regions (right angular gyrus: β = -0.517, 95% CI: -0.773 to -0.261, p < 0.001; right caudate: β = -0.556, 95% CI: -0.804 to -0.307, p < 0.001). No significant correlations emerged with depression scores (Hamilton Depression Rating Scale). HSE induces region-specific ALFF disruptions, characterized by hyperactivity in the precuneus and putamen together with hypoactivity in the angular gyrus and caudate within limbic-paralimbic networks. These alterations show strong associations with anxiety severity, suggesting ALFF as a potential noninvasive biomarker for HSE-related functional and neuropsychiatric impairments. Larger longitudinal studies are warranted to elucidate underlying mechanisms and therapeutic implications.

PMID:42599335 | DOI:10.1007/s11682-026-01192-0

iScience. 2026 Aug 3;29(8):117015. doi: 10.1016/j.isci.2026.117015. eCollection 2026 Aug 21.

ABSTRACT

Long-term exposure to a high-altitude (HA) hypoxic environment induces cognitive impairments, yet the underlying temporal mechanisms remain elusive. This longitudinal study investigated brain functional alterations associated with cognitive changes in 49 college freshmen relocated from sea level to Tibet, with comprehensive cognitive assessments and magnetic resonance imaging (MRI) at baseline and 2- and 4-year follow-ups. Resting-state fMRI quantified changes in regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF)/fractional ALFF (fALFF), static functional connectivity (sFC), and dynamic FC (dFC). Behavioral data confirmed persistent cognitive deficits, while neuroimaging analyses revealed biphasic patterns (initial suppression then partial/full recovery) in ReHo, ALFF/fALFF, and sFC. Notably, dFC variability in the right orbital middle frontal gyrus (ORBmid.R) and Heschl's gyrus (HES.R) increased at 2 years and remained elevated, with this alteration strongly correlated with cognitive changes. Our findings highlight that elevated dFC variability in two brain regions is a key contributor to chronic hypoxia-induced cognitive impairments.

PMID:42598111 | PMC:PMC13470281 | DOI:10.1016/j.isci.2026.117015

Front Psychiatry. 2026 Jul 30;17:1903951. doi: 10.3389/fpsyt.2026.1903951. eCollection 2026.

ABSTRACT

BACKGROUND: Internet addiction (IA) has emerged as a pervasive public health issue among young adults, frequently accompanied by severe emotion regulation difficulties. However, the precise static and dynamic functional architecture of the hippocampus and its interplay with emotion dysregulation in IA remain incompletely understood.

METHODS: This study enrolled 45 young adults with IA and 29 healthy controls (HC). Utilizing resting-state functional magnetic resonance imaging (fMRI), we computed both static functional connectivity (sFC) and dynamic functional connectivity (dFC) seeded from the rostral hippocampus. Partial correlation analyses were conducted to examine the associations between aberrant connectivity and clinical symptoms. Furthermore, we investigated whether emotion dysregulation mediates the relationship between altered hippocampal connectivity and internet addiction severity.

RESULTS: Compared to HCs, individuals with IA exhibited significantly increased sFC between the left rostral hippocampus and nodes of the default mode network (DMN; precuneus and inferior parietal lobule). Furthermore, the IA group displayed heightened temporal variability between the bilateral hippocampus and visual-temporal regions (superior temporal pole, lingual gyrus, middle, and superior occipital gyri). These aberrant sFC and dFC were significantly and positively correlated with IA severity and emotion regulation difficulties. Mediation analyses further revealed that emotion dysregulation significantly and partially mediated the relationship between altered hippocampal connectivity and internet addiction severity.

CONCLUSIONS: Static hyper-connectivity with the DMN and dynamic instability with visual-temporal networks constitute distinct neurobiological signatures of IA. Crucially, emotion dysregulation bridges these hippocampal network anomalies with addictive behaviors, highlighting targeted emotion regulation interventions as a promising therapeutic strategy for internet addiction.

PMID:42597244 | PMC:PMC13467981 | DOI:10.3389/fpsyt.2026.1903951

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Aug 13:111890. doi: 10.1016/j.pnpbp.2026.111890. Online ahead of print.

ABSTRACT

Electroconvulsive therapy (ECT) is an effective treatment for major depressive disorder (MDD), yet its underlying mechanisms remain unclear. This study investigated the antidepressant effects of ECT through a multimodal neuroimage meta-analysis combined with functional, genetic, and neurotransmitter assessments. Resting-state functional magnetic resonance imaging (fMRI) and voxel-based morphometry (VBM) data were analyzed using seed-based d mapping with permutation of subject images (SDM-PSI) to identify changes in spontaneous brain activity and gray matter volume (GMV) before and after ECT. Further analysis of regions with altered activation and GMV was conducted using Neurosynth, postmortem gene expression data, and receptor/transporter distribution maps to explore molecular underpinnings. The whole-brain multimodal meta-analysis included 291 patients from resting-state fMRI studies and 302 patients from VBM studies. The results showed convergent increases in spontaneous activity and GMV in the left angular gyrus (AG) following ECT. Functional annotation linked the left AG to memory, attention, and perceptual processing. Gene expression analysis identified TFAP2B and OTX2 as the most highly expressed genes in this region. Notably, ECT-associated changes in spontaneous brain activity and GMV were positively correlated with 5-HT1a receptor and dopamine transporter distribution. These findings suggest the left AG is a key region mediating ECT's effects. Neurotransmitter analysis further indicates that ECT may exert its antidepressant action by modulating neurotransmitter systems, offering insights into the neural and molecular basis of its therapeutic efficacy in MDD.

PMID:42595040 | DOI:10.1016/j.pnpbp.2026.111890

Exp Gerontol. 2026 Aug 13:113285. doi: 10.1016/j.exger.2026.113285. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by large-scale network disruption. While static functional connectivity (sFC) has been extensively studied, dynamic functional connectivity (dFC) and its discriminative value across the AD spectrum remain insufficiently understood. In this study, resting-state functional magnetic resonance imaging (rs-fMRI) data from 174 participants in the Alzheimer's Disease Neuroimaging Initiative, including cognitively normal (CN, n = 44), subjective memory concern (SMC, n = 24), early mild cognitive impairment (EMCI, n = 46), late MCI (LMCI, n = 30), and AD (n = 30), were analyzed to assess group differences in sFC, dFC, and graph-theoretical metrics, as well as their associations with cognition. A BrainNetCNN model was further employed to evaluate the classification performance of sFC, dFC, and their combined features. The results revealed that sFC decreased across MCI stages but increased in AD, whereas dFC variability was predominantly reduced in the pre-dementia groups and increased in AD, particularly in frontal and temporal regions. Several static graph-theoretical metrics were significantly correlated with Mini-Mental State Examination (MMSE) scores, while dFC provided complementary information. In classification tasks, dFC showed higher accuracy than sFC in binary and five-class tasks, and their integration achieved the highest accuracy (CN vs. SMC: 89.6%; five-class: 82.7%). These findings suggest that dFC may provide complementary imaging information for characterizing stage-related network alterations and differentiating diagnostic groups across the AD spectrum.

PMID:42595023 | DOI:10.1016/j.exger.2026.113285

J Am Acad Child Adolesc Psychiatry. 2026 Aug 13:S0890-8567(26)01569-8. doi: 10.1016/j.jaac.2026.08.003. Online ahead of print.

ABSTRACT

OBJECTIVE: Sensory over-responsivity (SOR), characterized by strong negative reactions to typically innocuous stimuli, is considered a symptom of autism spectrum disorder. However, SOR also affects 15-20% of children overall, including a majority of children with common psychiatric conditions. Despite its prevalence, the clinical specificity and neurobiological bases of SOR remain poorly understood. Our study aims to determine the specific clinical significance of SOR across diverse child samples and establish whether SOR is associated with replicable patterns of functional connectivity (FC).

METHOD: We analyzed data from 15,728 children (ages 6-17.9 years) across five datasets: three community samples, including the Adolescent Brain Cognitive Development [ABCD] and Healthy Brain Network [HBN] studies, and two autism-enriched samples. Bivariate and multivariate models examined associations between SOR and symptoms of anxiety, attention-deficit/hyperactivity disorder, depression, conduct disorder, and oppositional defiant disorder, as well as autistic traits. Analysis of resting-state functional MRI (fMRI) data from the ABCD study (n=4195) identified candidate brain-wide and circuit-specific FC correlates of mild SOR and tested replication of effects in an independent ABCD subsample (n=4190). Additional analyses tested extension to children with severe SOR in ABCD and replication in smaller samples [HBN (n=356), ABCD subset (n=356)].

RESULTS: Multivariate analyses revealed that SOR is associated with a remarkably consistent profile across samples: greater levels of both autistic traits and anxiety symptoms and, in community samples, lower levels of conduct disorder symptoms. Across samples, SOR is not reliably associated with symptoms of any other analyzed psychiatric conditions. Mild SOR is associated with brain-wide FC patterns and, specifically, reduced FC between cingulo-parietal network and bilateral caudate nucleus; these patterns show robust replication across independent ABCD subsamples and extension to severe SOR in ABCD but are not significant in smaller samples, indicating that large sample size is needed to reliably detect brain effects.

CONCLUSION: Results suggest that SOR may constitute a latent trait associated with both specific clinical risk and protection, and with replicable cortico-subcortical neural correlates. These findings advance our understanding of the neurobiology and clinical relevance of SOR. They may also inform clinical practice and future research aimed at understanding and supporting individuals with sensory challenges.

DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way.

PMID:42595007 | DOI:10.1016/j.jaac.2026.08.003

CNS Neurosci Ther. 2026 Aug;32(8):e71083. doi: 10.1002/cns.71083.

ABSTRACT

BACKGROUND: Identifying neuroimaging correlates of insomnia severity could provide insights into the underlying biological mechanisms of major depressive disorder (MDD). However, related findings remain inconsistent, and the functional connectivity patterns associated with insomnia severity are unclear.

METHODS: This study analyzed resting-state fMRI data from 385 patients with MDD and 336 healthy controls (HCs) sourced from nine sites of the DIRECT Consortium. Patients were stratified into high insomnia (MDDHI; HAMD insomnia subscale ≥ 4, n = 226) and low insomnia (MDDLI; HAMD insomnia subscale ≤ 3, n = 159) groups. Among patients with MDDHI, MDDLI and HCs, we first examined network-level functional connectivity abnormalities using the Craddock 200 atlas, and then local brain function was assessed using the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo) and degree centrality (DC). Finally, we adopted multiple analytical approaches to verify the robustness of the significant findings.

RESULTS: Compared to both patients with MDDHI and HCs, patients with MDDLI exhibited significantly reduced functional connectivity between the left angular gyrus (AG) and the right middle frontal gyrus (MFG). Both patients with MDDHI and MDDLI showed significantly decreased ALFF and ReHo values relative to HCs across multiple brain regions, including bilateral angular gyrus/precuneus/cerebellum posterior lobe and so on. For DC, patients with MDDHI showed significantly decreased values relative to HCs in all identified clusters, whereas patients with MDDLI showed significant DC reductions in a subset of these clusters. When these results were validated using multiple analytical approaches, the primary findings remained consistent.

CONCLUSIONS: Reduced functional connectivity between the left AG and the right MFG may be a candidate neuroimaging marker for sleep-related heterogeneity in MDD. However, widespread local brain function abnormalities may reflect core depressive pathology of MDD. These findings advance our understanding of the neurobiology of MDD.

PMID:42593839 | DOI:10.1002/cns.71083

Front Bioinform. 2026 Jul 29;6:1902380. doi: 10.3389/fbinf.2026.1902380. eCollection 2026.

ABSTRACT

INTRODUCTION: Large-scale multi-site magnetic resonance imaging (MRI) improves population coverage and statistical power, but scanner- and protocol-related variability can obscure biological effects. Most harmonization methods aim to reduce site-related variance for downstream analysis, whereas less attention has been paid to where site effects are spatially expressed, whether they are reproducible across site compositions, and which acquisition parameters contribute to them.

METHODS: We developed a modality-wise Linked Independent Component Analysis (LICA) framework to identify and interpret site-effect patterns in structural and resting-state functional MRI. Grey matter (GM) volume, amplitude of low-frequency fluctuation (ALFF), and regional homogeneity (ReHo) maps were analyzed separately. For each imaging measure, LICA decomposed voxel-wise maps into spatial components and subject-level loadings. Components were classified according to their associations with site labels and biological covariates, their spatial reproducibility was assessed using stepwise site-inclusion analyses, and their technical attribution was evaluated using cross-validated models based on site labels and recorded acquisition parameters. The framework was applied to ABIDE II GM maps from 913 participants across 18 sites and ALFF and ReHo maps from 795 participants across 16 sites.

RESULTS: LICA identified site-related components across all three imaging measures. Site effects were not limited to uniform global shifts, but formed modality-specific spatial patterns. GM volume showed a dominant and highly stable whole-brain site-effect pattern, together with site-specific and regional components. In contrast, ALFF and ReHo showed more heterogeneous functional patterns, including global, focal, and scattered configurations. Site labels explained the largest proportion of loading variance, whereas recorded acquisition parameters showed modality-dependent contributions: TR and TE were more prominent for structural site effects, while FA, voxel size, TR, and scanner model contributed more strongly to functional site effects.

DISCUSSION: The proposed framework provides a component-level diagnostic approach for multi-site MRI analysis. By mapping, stabilizing, and technically interpreting site-effect patterns, it complements conventional harmonization methods and may improve the transparency and reproducibility of multi-site structural and functional MRI studies.

PMID:42591441 | PMC:PMC13461629 | DOI:10.3389/fbinf.2026.1902380

J Cereb Blood Flow Metab. 2026 Aug 12:271678X261479952. doi: 10.1177/0271678X261479952. Online ahead of print.

ABSTRACT

Electrophysiological recordings such as electroencephalogram (EEG) are gold standards for measuring neuronal activity, which requires substantial oxidative metabolism (CMRO2) for support. Although EEG-CMRO2 links have long been assumed or measured qualitatively, quantitative characterization in humans remains limited, hindering our understanding of neurometabolic mechanisms and the utility of electrophysiological biomarkers in brain disease. Given that the neurometabolic process is sensitive to baseline perfusion and aerobic glycolysis, we hypothesized EEG-CMRO2 associations would show strong network and sex dependence, as these factors strongly influence perfusion and glycolytic activity. Here, we quantified EEG-CMRO2 associations and their underlying profiles (with cerebral blood flow and oxygen extraction fraction) across brain networks and between sexes. We further investigated how the EEG-CMRO2 association influenced resting-state functional magnetic resonance imaging (rs-fMRI) measurements. Our main findings suggest: (1) globally, CMRO2 only partially mediated EEG-fMRI relationships, revealing O2-independent coupling pathways; (2) EEG-CMRO2 associations varied significantly across functional networks; (3) sex differences in EEG-CMRO2 associations showed minimal network dependence; (4) high-frequency and low-frequency EEG bands exhibited opposite-polarities CMRO2 associations between males and females. These findings demonstrate that neurometabolic coupling differs across functional networks, frequency bands, and importantly, across biological sexes, with important implications for interpreting developing electrophysiological biomarkers and rs-fMRI measurements.

PMID:42590893 | DOI:10.1177/0271678X261479952