Most recent paper

Front Hum Neurosci. 2026 May 21;20:1786568. doi: 10.3389/fnhum.2026.1786568. eCollection 2026.

ABSTRACT

BACKGROUND: The potential negative influences of short video platforms (SVPs) usage on mental health have been attracting increasing attention in recent years. This study aimed to investigate the possible effects of SVP usage on brain functions using the resting-state functional magnetic resonance imaging (fMRI) methods.

METHODS: Resting-state fMRI data were acquired from a total of 55 young healthy adults. Based on self-reported daily usage time of SVPs, these participants were divided into a lower SVP usage (SVP-) group (< 1 h per day, n = 20) and a higher SVP usage (SVP+) group (≥1 h per day, n = 35). Between-group comparisons of functional brain measures were performed across multiple spatial levels.

RESULTS: At the single-edge level, the SVP + group showed significantly increased functional connectivity (FC) across many edges linking most major brain networks, including sensorimotor, visual, auditory, subcortical, default-mode, attention, and cingulo-opercular networks. Network-level analyses confirmed this widespread hyperconnectivity, with particularly robust increases within sensorimotor, auditory, subcortical, and cingulo-opercular networks after multiple comparisons correction. Voxel-wise analyses revealed higher fractional amplitude of low-frequency fluctuations (fALFF) in the left precentral gyrus and lower fALFF in the right frontal lobe in the SVP + group. Global topological analysis indicated that the SVP + group had significantly higher global efficiency, local efficiency, and clustering coefficient, as well as lower characteristic path length, suggesting an altered network topology.

CONCLUSION: This multi-level fMRI study suggests that a relatively higher-intensity SVP use is associated with an altered pattern of brain functional organization, characterized by widespread hyperconnectivity across most major brain networks, localized spontaneous activity alterations in sensorimotor regions, and an altered topology at the global level. These findings highlight the importance of considering potential impacts of SVP usage on brain functioning, and calls for future larger-sample and longitudinal studies to further understand such relationships.

PMID:42253790 | PMC:PMC13233705 | DOI:10.3389/fnhum.2026.1786568

Brain Behav Immun Health. 2026 May 25;54:101274. doi: 10.1016/j.bbih.2026.101274. eCollection 2026 Jul.

ABSTRACT

BACKGROUND: Post-COVID-19 Syndrome (PCS) is characterised by persistent fatigue, cognitive impairments, and affective symptoms, yet its underlying neural mechanisms remain poorly understood. While static neuroimaging studies have identified resting-state connectivity abnormalities in PCS, such approaches fail to capture the brain's dynamic functional organisation. This represents a missed opportunity to understand how alterations in large-scale network interactions may contribute to the fluctuating symptom profile of PCS. Cognitive and emotional processes rely on the brain's capacity to flexibly reconfigure large-scale networks over time; disruptions in this dynamic repertoire may therefore play a role in PCS pathophysiology.

METHODS: Resting-state fMRI data were acquired from 20 individuals with PCS (mean age = 41.8 years, SD = 9.4) and 20 age- and sex-matched healthy controls (mean age = 40.6 years, SD = 8.1) using a multi-echo sequence. Following denoising with multi-echo independent component analysis, we applied Leading Eigenvector Dynamics Analysis (LEiDA) to identify recurrent patterns of whole-brain phase synchrony. The optimal number of dynamic brain states was determined using the Dunn index. For each state, we quantified probability of occurrence, lifetime, and transition probabilities, and mapped spatial topographies onto canonical functional networks. Group differences were assessed using ANCOVAs controlling for age, sex, and handedness. Exploratory associations with clinical symptoms, cognitive performance, and inflammatory markers were examined using both frequentist and Bayesian approaches.

RESULTS: Five recurrent dynamic brain states were identified. Compared with controls, PCS participants showed reduced probability of occurrence and shorter lifetime of a visual/dorsal attention state, alongside increased probability of a limbic/default mode network (DMN) state. PCS was also characterised by tentative reduced transitions between visual/dorsal attention and frontoparietal-DMN states, and increased transitions from somatomotor/visual states toward the limbic-DMN configuration. Exploratory analyses (uncorrected for multiple comparisons) suggested that greater expression of the limbic-DMN state was associated with lower global cognitive performance (MoCA) and higher serum IL-1β levels, although these associations did not survive correction for multiple comparisons.

CONCLUSIONS: PCS is associated with a reorganisation of intrinsic brain dynamics, marked by a shift from externally oriented attentional states toward limbic-DMN configurations and reduced transition flexibility. These findings suggest that PCS may involve alterations in the dynamic balance of large-scale brain systems supporting attention and internally oriented processing. While exploratory, the observed patterns are consistent with a potential link between brain-state dynamics, cognitive function, and inflammatory signalling, and provide a systems-level framework for future studies of post-viral brain dysfunction.

PMID:42253624 | PMC:PMC13234210 | DOI:10.1016/j.bbih.2026.101274

Imaging Neurosci (Camb). 2026 Jun 4;4:IMAG.a.1248. doi: 10.1162/IMAG.a.1248. eCollection 2026.

ABSTRACT

Brain activity unfolds over hierarchical timescales that reflect how brain regions integrate and process information, linking functional and structural organization. While timescale studies are prevalent, existing estimation methods rely on the restrictive assumption of exponentially decaying temporal autocorrelation and only provide point estimates without standard errors, limiting statistical inference. In this paper, we formalize and evaluate two methods for mapping timescales in resting-state fMRI: a time-domain fit of an autoregressive (AR1) model and an autocorrelation-domain fit of an exponential decay model. Rather than assuming exponential autocorrelation decay, we define timescales by projecting the fMRI time series onto these approximating models, requiring only stationarity and mixing conditions while incorporating robust standard errors to account for model misspecification. We introduce theoretical properties of timescale estimators and show parameter recovery in realistic simulations, as well as applications to fMRI from the Human Connectome Project. Comparatively, the time-domain method produces more accurate estimates under model misspecification, remains computationally efficient for high-dimensional fMRI data, and yields maps aligned with known functional brain organization. In this work, we show valid statistical inference on fMRI timescale maps, and provide Python implementations of all methods.

PMID:42253608 | PMC:PMC13237991 | DOI:10.1162/IMAG.a.1248

Imaging Neurosci (Camb). 2026 Jun 4;4:IMAG.a.1267. doi: 10.1162/IMAG.a.1267. eCollection 2026.

ABSTRACT

Intermittent theta-burst stimulation (iTBS) is increasingly used to neuromodulate prefrontal brain regions, such as the dorsolateral prefrontal cortex (DLPFC), allowing to effectively change local excitability in research settings and to optimize therapeutic outcomes. However, response variability remains high, and its clinical efficacy is modest. Priming with theta-burst stimulation (TBS), in which a preconditioning TBS protocol precedes a test iTBS protocol, has been proposed to enhance stimulation efficacy and reduce inter-individual variability, particularly when combining protocols that are expected to induce different changes in cortical excitability. Yet, its underlying neurobiological effects remain unclear. In this within-subjects study, we investigated the effects of TBS priming on resting-state functional connectivity in 47 healthy subjects. Each participant completed four counterbalanced sessions, 1 week apart, receiving either a control condition with sham priming and sham test stimulation, an iTBS-alone condition (without priming), a priming condition where iTBS preceded iTBS, or a priming condition where continuous TBS (cTBS) preceded iTBS. Resting-state scans were acquired before and after each stimulation condition, alongside assessments of self-reported mood and perseverative thinking. Contrary to our expectations, priming prefrontal iTBS with cTBS resulted in reduced connectivity changes in both regions near the stimulation site and more distal temporal areas, and priming with iTBS significantly reduced connectivity changes in prefrontal regions, both relative to iTBS alone. Changes in perseverative thinking further moderated stimulation effects, with greater increases associated with stronger decreases in left prefrontal connectivity following cTBS-iTBS priming. These findings highlight the complex effects of prefrontal TBS priming and its interaction with psychological states, underscoring the importance of accounting for state dependency in neuromodulation research.

PMID:42253606 | PMC:PMC13237992 | DOI:10.1162/IMAG.a.1267

Eur Psychiatry. 2026 Jun 8:1-36. doi: 10.1192/j.eurpsy.2026.12227. Online ahead of print.

NO ABSTRACT

PMID:42252837 | DOI:10.1192/j.eurpsy.2026.12227

Dev Cogn Neurosci. 2026 Jun 5;80:101753. doi: 10.1016/j.dcn.2026.101753. Online ahead of print.

ABSTRACT

Although developmental language delays affect approximately 10% of children in the general population, the neurodevelopmental mechanisms that support normative language acquisition, and atypicalities that may predict later language delay, across the first year of life are poorly understood. Here, resting-state fMRI data from the Baby Connectome Project was used to first evaluate age-related changes in language network functional connectivity and alterations associated with suboptimal language development. Additionally, a data-driven machine learning algorithm was used to partition our sample into three groups who showed Typical, Advanced, or Lagging trajectories of language development. These groups reliably differed on several assessments of language ability during infancy and toddlerhood. Using a priori brain regions involved in adult language processing, a seed-based functional connectivity analysis showed broad age-related increases in functional synchrony and specialization throughout the infant language network. Additionally, the Lagging group showed several distinct patterns of functional connectivity with language regions. Importantly, the magnitude of connectivity differences consistently predicted later language scores at two-year outcome across several different language assessments. These findings add to our understanding of normative neurodevelopmental patterns underlying language acquisition, and identify several potential biomarkers associated with language heterogeneity that could serve as future targets to inform diagnoses and clinical interventions.

PMID:42251849 | DOI:10.1016/j.dcn.2026.101753

Neuroimage. 2026 Jun 5;337:122038. doi: 10.1016/j.neuroimage.2026.122038. Online ahead of print.

ABSTRACT

Resting state functional magnetic resonance imaging (rs-fMRI) signals are sensitive to artifacts caused by head motion and non-neural physiological noise, complicating its use to investigate brain function. These effects contaminate rs-fMRI signal timeseries, confounding the calculation and analysis of functional connectivity measures and degrading the interpretation of brain function or changes due to neurological and psychiatric disorders. rs-fMRI denoising strategies play an essential role in addressing motion and non-neural noise and greatly enhance the interpretability of connectivity measures, yet this is still a highly active area of research. We propose an automated denoising method that performs data-driven noise estimation and suppression for rs-fMRI. The method is based on sliding window segmentation and nuisance regression in eigenspace for temporal and spatial eigenvectors, respectively. We show that efficient noise identification/rejection produces not only improved denoising but also enhances the reliability of functional connectivity. Without removing the global signal, the proposed method achieves denoising performance comparable to global signal regression, with trade-offs in different quality metrics. NESD shows advantages in motion and temporal noise suppression, while GSR excels in signal amplitude. Both methods produce similar negative connectivity correlations. We provide data quality visualization tools for automated assessment of noise contamination including time, space, frequency, and connectivity indicators. Our findings demonstrate that denoising is critical for processing rs-fMRI signals for connectivity analyses and that NESD offers a practical alternative to existing approaches, with trade-offs that should be considered based on specific study goals.

PMID:42250836 | DOI:10.1016/j.neuroimage.2026.122038

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Jun 6;147:111768. doi: 10.1016/j.pnpbp.2026.111768. Online ahead of print.

ABSTRACT

BACKGROUND: Patients with generalized anxiety disorder (GAD) show structural and functional striatal abnormalities. While state and trait anxiety are known to modulate neural circuits influencing anxiety progression, the specific role of striatal-cortical circuitry in relation to anxiety dimensions in GAD remains unclear.

METHODS: We included 43 GAD patients and 36 healthy controls (HCs), assessing trait/state anxiety and collecting resting-state fMRI data. The striatal seed-based functional connectivity (FC) was compared between groups. Correlation analyses evaluated links between striatal FC, clinical symptoms, and anxiety measures. Mediation analysis tested whether state anxiety mediates FC-symptom relationships. A linear support vector machine (SVM) model assessed striatal FC's ability to classify GAD vs. HCs.

RESULTS: GAD patients exhibited increased FC between the right ventral superior striatum and medial prefrontal cortex, left dorsal caudal putamen (DCP) and left middle temporal gyrus, and right DCP and right MTG/fusiform gyrus, but decreased FC between the left ventral rostral putamen and left inferior parietal lobule/supramarginal gyrus. The FC between the right DCP and right MTG/fusiform exploratorily negatively correlated with HAMA and State Anxiety Inventory scores. State anxiety statistically mediate the relationship between striatal FC and anxiety severity. Linear and Gaussian SVM classifiers achieved accuracies of 81.07% and 79.82%, respectively.

CONCLUSIONS: GAD involves disrupted striato-cortical connectivity. State anxiety statistically mediate the relationship between striatal FC and clinical anxiety in an exploratory cross-sectional mediation framework, which may highlight its central role. Altered striatal-cortical FC may show potential candidate features for distinguish GAD patients from HC in exploratory proof-of-concept analyses.

PMID:42250636 | DOI:10.1016/j.pnpbp.2026.111768

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Jun 6;147:111771. doi: 10.1016/j.pnpbp.2026.111771. Online ahead of print.

ABSTRACT

The insular cortex is a pivotal hub for interoception and salience processing, yet subregion-specific circuit abnormalities in Internet Gaming Disorder (IGD) and their molecular correlates remain unclear. Using resting-state fMRI data from 71 IGD patients and 80 healthy controls, we conducted seed-based functional connectivity (FC) analyses across six bilateral insular subregions and applied Allen Human Brain Atlas (AHBA)-based imaging transcriptomics to characterize associated gene-expression patterns. IGD patients showed increased FC between the bilateral dorsal anterior insula (dAI) and paracingulate gyrus, reduced FC between the left dAI and frontal pole, and decreased FC between the bilateral posterior insula and postcentral gyrus. These findings suggest altered salience-network coordination with default-mode and executive-control systems, together with disrupted somatosensory-interoceptive integration. Right dAI-paracingulate FC was positively associated with symptom severity, suggesting clinical relevance of this circuit. Transcriptomic decoding revealed non-random spatial correspondence between right dAI FC abnormalities and AHBA gene-expression profiles. Associated genes were enriched in two molecular contexts: neuronal signal transmission and metabolic homeostasis (Corr+), and neurodevelopment and structural plasticity (Corr-). They further showed enrichment in neuronal and glial cell-type signatures, with the highest overlap ratios during three key developmental windows: early infancy, adolescence, and young adulthood. These findings reveal dissociable, subregion-specific insular circuit abnormalities in IGD, provide a multi-scale mechanistic account linking macroscale dysconnectivity to molecular and cellular substrates, consistent with and extending the triple network model in the context of behavioral addiction, and provide circuit-to-cellular candidate targets for intervention.

PMID:42250634 | DOI:10.1016/j.pnpbp.2026.111771

Hum Brain Mapp. 2026 Jun 1;47(8):e70549. doi: 10.1002/hbm.70549.

ABSTRACT

Adolescence is marked by significant changes in brain network organization that underlie cognitive and behavioral development. The sensorimotor-association (SA) axis has been proposed as a hierarchical framework for understanding functional connectivity development, but most studies rely on cross-sectional data and treat positive and negative connections equivalently. We analyzed longitudinal resting-state fMRI data from 125 adolescents who passed quality control of a total of 151 (ages 12-18, 364 total scan sessions across three time points) using both functional connectivity strength and graph-theoretical metrics, comparing results from absolute-value networks (collapsing connection signs) versus sign-aware approaches. Functional connectivity strength showed age-related changes following the SA axis selectively for positive connections (r = -0.614, p < 0.001), with stronger effects in sensorimotor regions, while negative connections showed no SA alignment (r = 0.031, p = 0.803). Critically, graph-theoretical measures revealed opposing developmental gradients depending on network construction: clustering coefficient and local efficiency showed association-dominant patterns in absolute-value networks (r = 0.317, p < 0.001; r = 0.427, p = 0.001) but sensorimotor-dominant patterns in positive-only networks (r = -0.225, p < 0.001; r = -0.277, p < 0.001). Participation coefficient, an integration-based measure, showed no significant SA association in either construction. These findings demonstrate that developmental inferences critically depend on how negative connections and network topology are treated, challenging the notion of a single organizational gradient and highlighting the necessity of sign-aware graph-theoretical approaches for understanding adolescent brain maturation.

PMID:42249734 | PMC:PMC13241828 | DOI:10.1002/hbm.70549

J Transl Med. 2026 Jun 5;24(1):744. doi: 10.1186/s12967-026-08324-6.

ABSTRACT

BACKGROUND: Hyperbaric oxygen therapy (HBOT) has been proposed as a treatment for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), but evidence remains limited. This study evaluated its clinical effectiveness and feasibility, as well as associated functional brain changes.

METHODS: Thirty patients with ME/CFS (mean age 42.3 ± 11.7 years; 7 males, 23 females) received 40 HBOT sessions. Clinical outcomes were assessed at baseline, during treatment, and four weeks post-treatment. The primary outcome was change in the physical functioning subscale of the Short Form-36 Health Survey (SF-36 PF). Secondary outcomes included severity of core symptoms assessed via questionnaires, exercise capacity, handgrip strength, cognitive performance, orthostatic intolerance, and brain magnetic resonance imaging (MRI; volumetry and functional connectivity [FC]). Thirty age- and sex-matched healthy controls (mean age 42.3 ± 11.3 years; 7 males, 23 females) were included for MRI comparison.

RESULTS: SF-36 PF significantly improved during HBOT compared with baseline (g = 0.71, p = 0.006). SF-36 pain (p = 0.002, g = 0.79) and Chalder Fatigue Scale also showed clinically meaningful reductions (p < 0.001, g = -0.87). Exercise capacity (g = 0.66), muscle strength (g = 0.40), and information processing speed (g = 0.52) improved significantly after treatment (all p < 0.05). Treatment adherence was high and tolerability was favorable, with no major adverse events reported. Functional MRI analyses revealed increased thalamic FC in ME/CFS patients compared to healthy controls in bilateral sensorimotor (p < 0.001, t = 5.65, FDR-corrected) and visuo-occipital regions (p < 0.001, t = 5.40, FDR-corrected) at baseline. Following HBOT, thalamic hyperconnectivity shifted toward patterns observed in healthy controls. Responders, defined as a ≥ 10 points increase in SF-36 PF, showed greater reductions in thalamic hyperconnectivity than non-responders (p < 0.001, t = -4.34 to -5.18, FDR-corrected).

CONCLUSIONS: HBOT was well tolerated and associated with significant improvements in physical functioning, fatigue, pain, and cognitive performance in ME/CFS. The post-treatment shift in thalamocortical connectivity toward healthy control patterns and its association with clinical response support the hypothesis that functional thalamic dysregulation contributes to ME/CFS pathophysiology and may be modulated by HBOT. This provides a network-level rationale for controlled trials to confirm therapeutic efficacy.

TRIAL REGISTRATION: ClinicalTrials.gov NCT06118138. Registered 01 November 2023 - Retrospectively registered, https://clinicaltrials.gov/study/NCT06118138?cond=ME%2FCFSamp;term=HBOTamp;rank=1 .

PMID:42249466 | PMC:PMC13244963 | DOI:10.1186/s12967-026-08324-6

J Neuroeng Rehabil. 2026 Jun 5. doi: 10.1186/s12984-026-02037-z. Online ahead of print.

ABSTRACT

BACKGROUND: Dynamic functional connectivity (FC) studies have shown that motor recovery after stroke was associated with functional reorganization of brain networks. However, most previous studies have focused on interregional variability rather than the temporal variability (TV) of specific regions or networks. TV quantifies the dynamic reconfiguration of a region's or network's functional connectivity profile over time and reflects neural flexibility.

PURPOSE: This study investigated functional reorganization in chronic subcortical stroke using TV of brain networks derived from resting-state fMRI.

METHODS: Thirty-three patients with left subcortical stroke (LSS), thirty with right subcortical stroke (RSS), and fifty-six age- and sex-matched healthy controls (HCs) were enrolled. Stroke patients underwent resting-state fMRI and Upper Extremity Fugl-Meyer Assessment (UE-FMA) at two time points. TV was computed to characterize dynamic functional connectivity at regional, intra-network, and inter-network levels. Group differences were assessed using one-way ANCOVA with post hoc tests. Linear regression was used to examine associations between TV and motor outcomes. The false discovery rate was used to multiple comparisons correction.

RESULTS: Compared with HCs, both LSS and RSS showed significantly reduced TV in the right frontal-cingulate regions, the somatomotor hand network (SSH), and the connections between SSH and higher-order cognitive networks (all p < 0.05, |Cohen's d| > 0.49). Increased TV was observed in the left postcentral gyrus, inferior frontal gyrus, cerebellar network (CEN), and somatomotor mouth network (all p < 0.05, |Cohen's d| > 0.48). Relative to LSS, RSS exhibited additional TV reductions in the right middle occipital gyrus, orbital middle frontal gyrus, default mode network (DMN), and interactions among higher-order cognitive networks (all p < 0.05, |Cohen's d| > 0.65). Notably, TV in the right opercular inferior frontal gyrus (IFGoperc) (β = 102.69, adjusted p = 6.4 × 10- 5) and CEN (β = 27.87, adjusted p = 0.011) at the first observation positively correlated with UE-FMA scores at follow-up, with effects modulated by lesion laterality.

CONCLUSION: TV captures multiscale functional reorganization in chronic subcortical stroke involving motor, cognitive, and sensory networks. TV of the right IFGoperc showed potential as a neuroimaging biomarker for predicting post-stroke motor recovery.

PMID:42249418 | DOI:10.1186/s12984-026-02037-z

BMC Psychiatry. 2026 Jun 5. doi: 10.1186/s12888-026-08253-0. Online ahead of print.

ABSTRACT

BACKGROUND: Adolescents hospitalized with mood disorders face a heightened risk of repeated self-harm (SH) after discharge. Neuroimaging phenotype may complement traditional symptom-based approaches by revealing neural mechanisms of SH vulnerability. This study aimed to investigate longitudinal changes in functional connectivity (FC) in adolescents with repeated SH and to examine how these neural dynamics relate to SH-related symptoms.

METHODS: We recruited 201 adolescent inpatients with mood disorders and SH behaviors, who were classified into repeated (RESH; n = 63) and non-repeated (NRESH; n = 138) SH groups based on a six-month follow-up. Resting-state fMRI and clinical assessments were conducted at three time points: acute (T1, admission ≤ 1 week), subacute (T2, 1-2 weeks), and discharge (T3). Voxel-wise ANCOVA identified regions showing significant group-by-time interaction effects in amygdala functional connectivity. Partial least squares correlation (PLSC) was used to examine associations between changes in FC (ΔFC) and suicidal symptoms, while logistic regression tested whether baseline and dynamic FC predicted SH recurrence at follow-up.

RESULTS: ANCOVA revealed significant group-by-time interaction effects in amygdala-cortical connectivity, particularly with the left supplementary motor area (L-SMA) (Gaussian random field, GRF corrected, P < 0.05). PLSC showed that ΔFC between the amygdala and L-SMA was significantly associated with suicidal measures. Logistic regression indicated that both baseline (AUC = 0.75, 95% CI: 0.63-0.79) and ΔFC (AUC = 0.76, 95% CI: 0.68-0.82) between the amygdala and L-SMA, along with sex and Beck Scale for Suicide Ideation (BSS) item 3("Reasons for Living or Dying"), were significant predictors of SH behavior.

CONCLUSIONS: Longitudinal changes in amygdala-L-SMA connectivity are associated with suicidal symptoms and predict SH recurrence, supporting the integration of neurobiological and clinical indicators for early suicide risk stratification.

CLINICAL TRIAL NUMBER: Not applicable.

PMID:42249288 | DOI:10.1186/s12888-026-08253-0