Most recent paper

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

Neuroimage Rep. 2026 Feb 25;6(1):100330. doi: 10.1016/j.ynirp.2026.100330. eCollection 2026 Mar.

ABSTRACT

BACKGROUND: Subjects with temporal lobe epilepsy (TLE) often experience cognitive impairment in different domains. Currently, the mechanisms underlying neuropsychological dysfunction in TLE remain poorly understood. The main objective is to characterize the multivariate relationship between brain connectivity patterns and cognitive impairment detected by robotic testing in subjects with TLE.

METHODS: Kinarm robotic technology was used to evaluate motor, cognitive, and sensory domains of healthy controls and individuals with TLE. Structural connectivity (SC) and functional connectivity (FC) were obtained from multi-shell diffusion MRI and resting-state fMRI, respectively. After principal component analysis for dimension reduction of connectivity features, sparse canonical correlation analyses were used to identify the patterns of multivariate association between brain connectivity and cognitive dysfunctions.

RESULTS: Patients with TLE demonstrated worse performance mainly in the domains of memory, executive function and attention, and to a lesser extent in the perceptual-motor domain. We found that memory and executive function alterations were associated with an intra-hemispheric SC pattern between somatomotor network and default, limbic and frontoparietal networks. We also found that an intra-hemispheric SC pattern of the posterior parietal cortex was related to perceptual-motor and attention skills with FC between this region and the precentral ventral region of DAN and frontal operculum insula of VAN also associated to impairment in these domains.

CONCLUSIONS: This study identifies multivariate patterns of structural and functional connectivity that correlate with domain-specific cognitive impairment, as measured by robotic screening, in individuals with TLE. These findings support the conceptualization of TLE as a network disorder, contextualizing multidomain cognitive deficits within a network-level framework rather than interrogating specific functional circuits. This may in the future permit more personalized treatments or prediction of cognitive changes in response to planned treatment changes.

PMID:41993701 | PMC:PMC13080667 | DOI:10.1016/j.ynirp.2026.100330

Front Neurol. 2026 Apr 1;17:1766985. doi: 10.3389/fneur.2026.1766985. eCollection 2026.

ABSTRACT

PURPOSE: Neuroimaging studies exploring structural and functional brain changes of COVID-19 survivors have yielded regionally inconsistent findings. Although there is an increasing agreement that diseases are more accurately mapped to distributed neural network than to discrete brain areas, research examining network-level localization of structural and functional deficits in COVID-19 survivors remains limited.

METHOD: To bridge this gap, we first pinpointed sites of structural and functional impairment in COVID-19 survivors, drawing on 19 studies comprising 23 contrasts across a cohort of 703 survivors and 596 healthy controls. Using connectivity-based mapping, we projected these identified regions onto large-scale resting-state fMRI datasets to reconstruct a coordinated brain network associated with neurological abnormalities in COVID-19 survivors.

RESULTS: In COVID-19 survivors, structural and functional alternations were mapped to a widely distributed brain network, primarily involving the default mode and limbic systems.

CONCLUSION: Our results reveal both common and distinct neural correlates underlying structural and functional impairments among COVID-19 survivors. These insights not only elucidate the neuropathology of the disease through a network-based framework but also support the development of therapeutic interventions for affected individuals.

PMID:41993644 | PMC:PMC13079111 | DOI:10.3389/fneur.2026.1766985

bioRxiv [Preprint]. 2026 Apr 7:2026.04.07.716703. doi: 10.64898/2026.04.07.716703.

ABSTRACT

Nonlinearity is a hallmark of brain complexity at multiple scales. However, existing functional magnetic resonance imaging (fMRI) functional connectivity studies typically utilize linear methods. Therefore, links between nonlinear fMRI connectivity patterns and the development of the human brain during critical periods such as infancy remain unclear. To address this gap in knowledge, we developed a data-driven approach to capture brain intrinsic connectivity networks from explicitly nonlinear resting-state fMRI connectivity and profiled their developmental associations in a cohort of typically developing human infants. We identified neurobiologically structured nonlinear fMRI connectivity patterns during early postnatal life, indicating that macroscopic brain ensembles systematically participate in nonlinear relationships at birth. Furthermore, we found that linear and explicitly nonlinear network counterparts are linked to partially overlapping but complementary developmental profiles during this period of rapid brain maturation, with the explicitly nonlinear approach unveiling insights into the development of networks that have been associated with sensorimotor capacities, default mode processes, executive functioning, language production, and stimulus saliency. Our study marks the first comprehensive developmental investigation of whole-brain nonlinear fMRI networks in human infants and deepens contemporary perspectives on neuroimaging data discovery by emphasizing the informational richness of nonlinear relationships at fMRI scales of observation.

PMID:41993476 | PMC:PMC13082082 | DOI:10.64898/2026.04.07.716703

bioRxiv [Preprint]. 2026 Apr 9:2026.04.06.716813. doi: 10.64898/2026.04.06.716813.

ABSTRACT

BACKGROUND: Children who are HIV-exposed but uninfected (CHEU) face elevated risks of hearing loss and language deficits compared to HIV-unexposed peers. The central auditory system (CAS) undergoes substantial maturational changes during adolescence, yet no neuroimaging study has examined its structural or functional integrity in CHEU. Prior work in this cohort identified white matter (WM) alterations in regions adjacent to the CAS at age 7, and reduced auditory working memory in CHEU relative to unexposed children (CHUU).

AIM: To characterise WM integrity and functional connectivity (FC) of the CAS and related regions in CHEU at age 11, to investigate structural and functional network topology, and to examine associations between imaging outcomes and neurocognitive function.

METHODS: Forty-eight children aged 11-12 (20 CHEU, 28 CHUU) from an ongoing longitudinal neurodevelopmental cohort underwent 3T MRI including diffusion tensor imaging (DTI) and resting-state fMRI (RS-fMRI). CAS regions (cochlear nucleus/superior olivary complex, inferior colliculus [IC], medial geniculate nucleus [MGN], and primary auditory cortex [PAC]) were manually segmented and combined with an automated atlas. DTI probabilistic tractography was performed, extracting FA, MD, AD, RD, fractional number of tracts, and tract volume. FC was computed using Pearson correlations between regional time series. Graph theory measures (degree, strength, transitivity, nodal and local efficiency) were derived for structural and functional networks. RS-fMRI group comparisons used Bayesian multilevel modelling (matrix-based and region-based analyses), while DTI comparisons used linear models with FDR correction. Neurocognitive testing employed the KABC-II.

RESULTS: No significant group differences in DTI WM metrics (FA, MD, AD, RD) were observed after FDR correction. CHEU demonstrated higher structural nodal strength in the left IC (FDR-significant) and in the bilateral rostral middle frontal cortex (rMFC) and right cuneus. RS-fMRI revealed lower FC between the bilateral IC in CHEU, alongside reduced FC in the left caudate, left hippocampus CA3, left pericalcarine, and left lingual gyrus. CHEU showed higher FC between the left MGN and right precentral, left postcentral, and right rMFC; the right PAC also showed higher FC to the right rMFC and left postcentral gyrus. No significant group differences were observed in functional nodal measures. No significant associations were found between structural or functional imaging outcomes and neurocognitive scores after multiple comparison correction.

DISCUSSION: Structural and functional alterations within the CAS were most prominent in the IC, with increased nodal strength in CHEU potentially reflecting compensatory structural connectivity, and reduced interhemispheric FC between the bilateral IC suggesting disrupted auditory integration. Altered FC between the MGN/PAC and cortical regions, including the rMFC and sensorimotor cortices, may reflect differences in top-down auditory processing. The absence of imaging-cognition associations at age 11 suggests that these connectivity differences do not, at this stage, translate into measurable deficits in auditory or language-related neurocognitive performance.

CONCLUSION: This is the first study to examine functional and structural connectivity of the CAS in CHEU children. HIV exposure is associated with subtle but discernible alterations in IC connectivity and in CAS links to cortical regions at age 11, without detectable neurocognitive correlates. Longitudinal follow-up and inclusion of audiological and ART exposure data are needed to clarify the developmental and functional consequences of these findings.

PMID:41993431 | PMC:PMC13081875 | DOI:10.64898/2026.04.06.716813

bioRxiv [Preprint]. 2026 Apr 9:2026.04.06.716832. doi: 10.64898/2026.04.06.716832.

ABSTRACT

Global Signal Removal (GSR) is a widely applied step in functional magnetic resonance imaging (fMRI) preprocessing. Although GSR conventionally denotes `Global Signal Regression,' we use `Global Signal Removal' to encompass a broader family of spatial filtering operations. GSR in general remains controversial due to concerns about introducing spurious anticorrelations and removing neurally meaningful signals. In this paper, we provide a precise geometric characterization by formalizing GSR as graph spatial filtering. We demonstrate that the most common form of GSR, Regression-GSR, equates to a rank-1 deflation of the covariance matrix (i.e. functional connectivity) by the degree vector. Empirically, the degree vector is dominated by the first principal component of the functional connectivity matrix (correlation = 0.88 +/- 0.12 in resting-state HCP data), making Regression-GSR an approximation to first eigenmode removal. This view of GSR as a spatial projection framework allows us to develop a family of GSR variants, each expressible in a unified spatial filter: Naive-GSR removes the uniform vector, PCA-GSR precisely removes the first eigenvector, and SC-GSR, a new variant we introduce that removes the first harmonic of the structural connectivity matrix. A key distinction emerges: while Naive, PCA, and SC-GSR are orthogonal projections, Regression-GSR is an oblique projection that computes regional weights proportional to the degree vector but removes a spatially uniform signal. All GSR variants induce numerical singularity in the covariance matrix, but they differ in their effects on task-state separability, which we examine empirically. In summary, we reframe GSR as a family of graph spatial filters that enable interpretability of its effects, with systematically varying effects on network connectivity across variants.

PMID:41993320 | PMC:PMC13081951 | DOI:10.64898/2026.04.06.716832

Imaging Neurosci (Camb). 2026 Apr 13;4:IMAG.a.1200. doi: 10.1162/IMAG.a.1200. eCollection 2026.

ABSTRACT

The state regulation deficit account of attention-deficit hyperactivity disorder (ADHD) posits that symptoms and performance deficits associated with ADHD are context-dependent and explained by a deficit in arousal regulation. Research into this topic has often used event rate manipulations to induce different arousal states, and has demonstrated deficits at both overstimulating and understimulating event rate levels. Although existing research has provided strong support for the state regulation deficit account, little is known about the neurobiological substrate of state regulation deficits. An important candidate brain network is the Locus Coeruleus-noradrenergic (LC-NE) system, which has been hypothesized by several researchers to play a key role in state regulation deficits in ADHD. In the current study, we examined, for the first time, the role of the LC in state regulation deficits in ADHD using high-resolution fMRI scans. We presented a target detection task at three event rate levels (fast, moderate, slow) to adults with (n = 27) and without ADHD (n = 28), with 20-s resting intervals at the start and the middle of each event rate condition. No group difference was found for performance, whereas results indicated significantly higher self-reports of state regulation deficits in daily life in the ADHD group. Anatomically guided region-of-interest analyses based on a high-resolution turbo-spin-echo anatomical scan of the pons region indicated an overall lower LC activity during resting intervals in the ADHD group, irrespective of event rate. Event-related LC activity was not impacted by event rate or by group. Our results, therefore, support the notion of a general "underarousal" in ADHD, but do not confirm a relationship between LC activity and behavior, raising doubts on a direct implication of the LC-NE system in state regulation deficits in ADHD.

PMID:41993143 | PMC:PMC13081741 | DOI:10.1162/IMAG.a.1200

Front Hum Neurosci. 2026 Apr 1;20:1767772. doi: 10.3389/fnhum.2026.1767772. eCollection 2026.

ABSTRACT

OBJECTIVE: Anodal transcranial direct current stimulation (tDCS) is known to improve cognition in patients with mild cognitive impairment (MCI) and Alzheimer's disease (mild AD).

METHODS: We aimed to examine the brain functional alterations accompanying improvement in cognitive performance following anodal tDCS at the left dorsolateral prefrontal cortex (DLPFC) in a sample of patients with early AD (N = 40; MCI, n = 19, and mild AD, n = 21) using functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG).

RESULTS: Significant (p-FDR < 0.05) reduction in seed(left middle frontal gyrus, lMFG)-to-voxel resting-state functional connectivity (rsFC) with precuneus and posterior cingulate gyrus (PCC) was noted following tDCS intervention, while task-based fMRI (tbfMRI) analysis revealed significant (p-FDR < 0.05) increases in blood oxygen level-dependent (BOLD) activations at PCC and right MFG (rMFG) during episodic memory encoding and retrieval tasks, respectively. Furthermore, a significant decrease (p-FDR < 0.05) in resting-state MEG (rsMEG) gamma power at the right occipital cortex and an increase in phase (theta) and amplitude (gamma) coupling at the left entorhinal cortex were observed post-tDCS.

CONCLUSION: The findings of this comprehensive study using resting fMRI and MEG, as well as task-based fMRI, provide mechanistic insights regarding brain functional alterations that underlie the cognitive modulatory effects of anodal tDCS in early AD.

PMID:41993066 | PMC:PMC13079595 | DOI:10.3389/fnhum.2026.1767772

Behav Brain Res. 2026 Apr 14:116223. doi: 10.1016/j.bbr.2026.116223. Online ahead of print.

ABSTRACT

Implicit self-esteem is typically viewed as a unidimensional aspect of self-concept. However, emerging evidence suggests that individuals can simultaneously hold strong positive and negative implicit self-evaluations-termed implicit self-evaluation bivalence. This resting-state fMRI study examined the intrinsic neural architecture of implicit self-evaluation bivalence using a multilevel framework that integrates regional activity and connectivity. In 101 healthy adults, higher bivalence was associated with reduced amplitude of low-frequency fluctuations (ALFF) in the right angular gyrus, left precuneus, right precentral gyrus, and left supplementary motor area. Bivalence also corresponded to stronger static functional connectivity between the angular gyrus and right middle orbitofrontal cortex, increased mean dynamic connectivity between the angular gyrus and posterior default-mode and somatosensory regions, and reduced temporal variability of connectivity between the precuneus and supplementary motor area. Together, these findings suggest that implicit self-evaluation bivalence is associated with an intrinsic neural architecture characterized by altered static and dynamic coupling among self-referential and motor systems, extending unidimensional models of implicit self-esteem toward a more network-based understanding of the implicit self.

PMID:41991005 | DOI:10.1016/j.bbr.2026.116223

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Apr 14:111703. doi: 10.1016/j.pnpbp.2026.111703. Online ahead of print.

ABSTRACT

BACKGROUND: Tobacco use disorder (TUD) is recognized as a significant neurobehavioral disorder, associated with alterations in functional network connectivity (FNC) within and between the triple-network and visual-network.

METHODS: We recruited 87 male TUD patients and 45 male healthy control (HC), collecting resting-state functional magnetic resonance imaging(rs-fMRI) and smoking-related clinical scales. Group independent component analysis (ICA) combined with a sliding window method and k-means clustering analysis was used to assess static and dynamic time-varying FNC within networks. Spectral dynamic causal modelling (Sp DCM) and Parametric empirical bayes (PEB) framework were used to explore the aberrant effective connectivity (EC) among these networks in TUD.

RESULTS: Compared to HC, TUD patients exhibited within-network hyperconnectivity in the middle temporal gyrus (MTG) of the salience network (SAL), medial prefrontal cortex (MPFC) of the default mode network (DMN), and superior frontal gyrus (SFG) of the higher-order visual-network (HVN), alongside hypoconnectivity in the superior parietal lobule (SPL) of the HVN and posterior cingulate cortex (PCC) of the primary visual-network (PVN). Statically, increased connectivity was observed between SAL and executive control network (ECN). Dynamically, hyperconnectivity between SAL and PVN was identified in State I. EC analysis revealed enhanced self-inhibition within SAL, increased excitatory drive from ECN to SAL and HVN, and decreased excitatory influence from PVN to HVN in TUD. Correlation analyses indicated that static SAL-ECN connectivity positively correlated with Russell Reasons for Smoking Questionnaire (RRSQ)IV-VII scores, while EC from ECN to HVN negatively correlated with Fagerstr¨om Test for Nicotine Dependence (FTND) scores and cigarettes per day.

CONCLUSIONS: This study reveals a novel, hierarchical dysregulated connectivity configuration involving the triple-network and visual-network in TUD, characterized by static hyperconnectivity, dynamic state-specific abnormalities, and a causal model of enhanced top-down control coupled with disrupted bottom-up processing. This study also provides new insights into the neurobiology of TUD in males, highlighting the need for future studies to investigate sex-specific effects. These findings advance the neurobiological understanding of TUD and emphasize potential network-based targets for neuromodulation therapies.

PMID:41990961 | DOI:10.1016/j.pnpbp.2026.111703

Neuroimage. 2026 Apr 14:121926. doi: 10.1016/j.neuroimage.2026.121926. Online ahead of print.

ABSTRACT

BACKGROUND: Insomnia disorder (ID) affects 10-15% of adults globally but remains poorly characterized at the neural level. This study integrated meta-analytic neuroimaging findings with transcriptomic data to elucidate neural-molecular signatures of ID.

METHODS: We conducted coordinate-based meta-analyses of 29 fMRI studies (2,579 participants: 1,305 ID, 1,274 controls) examining resting-state and taskbased functional alterations in ID. Altered brain activity patterns were correlated with Allen Human Brain Atlas (AHBA) gene expression data using partial least squares (PLS) regression to identify ID-related genes. Further enrichment analyses revealed biological pathways associated with ID-related brain dysfunction.

RESULTS: Metaanalysis revealed convergent functional abnormalities across rest and task states, including salience network alterations (bilateral insula hyperactivity, anterior cingulate hypoactivity), decreased default mode network activity (bilateral precuneus), and executive function circuit disruptions. Critically, conjunction analysis identified stateindependent hypoactivation of the right inferior frontal gyrus. Functional decoding revealed this region's involvement in executive functions including inhibitory control, working memory, and attention. At molecular level, transcriptomic analysis identified 1,036 genes related to neural functional alterations. Positive genetic components were enriched for synaptic functions, whereas negative components linked to carbohydrate metabolism and mitochondrial processes.

CONCLUSIONS: These findings reveal convergent neural dysfunction and underlying molecular mechanisms in ID, highlighting right inferior frontal gyrus hypoactivation as a candidate biomarker, and the identified synaptic and metabolic pathways as therapeutic targets for insomnia treatment.

PMID:41990895 | DOI:10.1016/j.neuroimage.2026.121926

J Affect Disord. 2026 Apr 14:121803. doi: 10.1016/j.jad.2026.121803. Online ahead of print.

ABSTRACT

BACKGROUND: Robust and clinically meaningful neural mechanisms of major depression disorder (MDD) have yet to be identified. Although resting-state functional connectivity (rs-FC) from static and dynamic perspectives has provided valuable insights, findings across these approaches remain fragmented. This study sought to systematically investigate MDD-related abnormalities in static FC (sFC) and dynamic FC (dFC), and importantly, their relationship in MDD pathophysiology.

METHOD: Connectome-based predictive modeling (CPM) was applied to resting-state fMRI data from 192 patients with MDD and 182 healthy controls to identify functional networks positively or negatively predicting depression severity (static neuromarkers). dFC states were derived using sliding-window approach and K-means clustering. Group differences in temporal characteristics and summed dFC strength of CPM-derived networks were assessed, and multivariate linear regression was conducted to examine relationships between static and dynamic neuromarkers.

RESULTS: CPM identified a High-depression Network with enriched default-mode network (DMN)-sensory FC; and a Low-depression Network with greater intra-network FC, particularly within the DMN and sensory networks. dFC analysis revealed four states; patients with MDD showed a higher occurrence of a weakly-connected state(State 2) and exhibited summed within-state dFC strength that was significantly higher in the High-depression Network and lower in the Low-depression Network. Both within-state dFC and temporal characteristics significantly predicted summed sFC within CPM networks, together explaining 75%-82% of the variance in summed sFC strength.

CONCLUSIONS: These findings suggest that static neuromarkers in MDD may reflect both within-state dFC strength and temporal characteristics, bridging static and dynamic approaches and emphasizing that static neuromarkers may capture certain temporal dynamics.

PMID:41990888 | DOI:10.1016/j.jad.2026.121803