Most recent paper

Front Neurol. 2026 Jun 24;17:1858348. doi: 10.3389/fneur.2026.1858348. eCollection 2026.

ABSTRACT

BACKGROUND: Rapid eye movement sleep behavior disorder (RBD) and visual hallucinations (VH) are prognostically relevant non-motor symptoms in Parkinson's disease (PD), but their combined effects on local brain dysfunction remain unclear.

OBJECTIVE: To characterize regional brain dysfunction patterns associated with RBD and VH in PD and to explore candidate-region symptom-related effects within regions showing overall between-group differences.

METHODS: In this cross-sectional study, 96 patients with PD were divided into four groups according to the presence or absence of RBD and VH (24 per group). Resting-state functional MRI was analyzed using amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Whole-brain four-group analyses were first used to identify regions with overall between-group differences, followed by exploratory ROI-based 2 × 2 factorial analyses within candidate regions. Additional whole-brain voxel-wise 2 × 2 factorial analyses were performed as supplementary analyses. Correlations between imaging indices and clinical scales were also examined.

RESULTS: Patients with both RBD and VH showed the greatest clinical burden and worse cognitive performance. Whole-brain analyses revealed abnormalities in frontal, temporal, cerebellar, supplementary motor, and precuneus regions. Exploratory candidate-region analyses with Benjamini-Hochberg FDR correction showed RBD-related patterns in precuneus ReHo, cerebellar lobule VIII ReHo, and SMA ALFF; VH-related patterns in OFC ReHo, precuneus ReHo, cerebellar Crus I ReHo, SMA ALFF, and temporal pole ALFF; and interaction-like patterns in OFC ReHo and temporal pole ALFF. These ROI-based findings were interpreted as post hoc exploratory results rather than independent confirmatory evidence. Imaging abnormalities were correlated with RBD severity, freezing of gait, hallucination burden, and cognition.

CONCLUSION: Coexisting RBD and VH may identify a clinically more severe PD subtype associated with regional abnormalities involving cerebellar, motor, default mode, and association-related regions. Symptom-related main and interaction patterns should be interpreted as candidate-region exploratory findings requiring further confirmation in larger studies.

PMID:42422208 | PMC:PMC13341548 | DOI:10.3389/fneur.2026.1858348

Behav Brain Res. 2026 Jul 8:116361. doi: 10.1016/j.bbr.2026.116361. Online ahead of print.

ABSTRACT

BACKGROUND: Adolescent major depressive disorder (MDD) emerges during a sensitive neurodevelopmental period and is frequently accompanied by non-suicidal self-injury (NSSI), a clinically important behavioral phenotype associated with affective dysregulation. Although prior resting-state fMRI studies have identified distributed functional abnormalities in adolescent MDD, it remains unclear whether MDD with NSSI is associated with alterations in macroscale functional organization, stepwise cross-network propagation, or both. We therefore combined functional gradient (FG) analysis and stepwise functional connectivity (SFC) to characterize group-related differences from the complementary perspectives of gradient-based functional organization and multi-step network propagation.

METHODS: Using resting-state fMRI data from 135 adolescents classified as healthy controls (HC), adolescents with major depressive disorder and non-suicidal self-injury (MDD-NSSI), and adolescents with major depressive disorder without NSSI (MDD-noNSSI), we estimated functional gradients based on the Schaefer-400 parcellation. Between-group differences in Gradient 1 (G1) and Gradient 2 (G2) were assessed using pairwise Welch's t-tests, followed by global BH-FDR correction across all 2400 ROI-wise tests. Bonferroni correction was additionally used as a conservative sensitivity analysis. To avoid circular seed selection, weighted SFC was performed using an a priori sgACC/BA25 seed set rather than ROIs selected from the gradient analysis. Stepwise propagation maps were computed from step 1 to step 7. For ROI-wise SFC comparisons, pairwise Welch's t-tests were performed within each contrast and step, followed by exploratory within-network BH-FDR correction separately within each canonical functional network.

RESULTS: Functional gradient analysis revealed distinct gradient profiles across the two patient groups. After global BH-FDR correction across 2400 ROI-wise tests, G1 showed extensive differences in MDD-noNSSI versus HC and in MDD-NSSI versus MDD-noNSSI, whereas the G1 difference between MDD-NSSI and HC was relatively limited. By contrast, G2 showed extensive and robust differences in MDD-NSSI versus HC and in MDD-NSSI versus MDD-noNSSI, while MDD-noNSSI showed a weaker G2 difference relative to HC. The exploratory sgACC/BA25-seeded SFC analysis showed HC-relative propagation abnormalities mainly involving limbic temporal pole and orbitofrontal parcels. Compared with HC, MDD-NSSI showed broader exploratory within-network-corrected limbic involvement and additional somatomotor reductions, whereas MDD-noNSSI showed a more focal left temporal pole propagation pattern. No direct SFC difference between MDD-NSSI and MDD-noNSSI survived exploratory within-network BH-FDR correction.

CONCLUSION: FG findings provided direct evidence for different gradient-related profiles between adolescent MDD with and without NSSI, whereas sgACC/BA25-seeded SFC provided exploratory HC-relative propagation evidence. MDD-noNSSI was mainly associated with broad G1-related displacement, whereas MDD-NSSI was associated with G2-related redistribution and broader HC-relative limbic-cortical propagation abnormalities from the sgACC/BA25 seed.

PMID:42419463 | DOI:10.1016/j.bbr.2026.116361

J Affect Disord. 2026 Jul 8:122226. doi: 10.1016/j.jad.2026.122226. Online ahead of print.

ABSTRACT

INTRODUCTION: Bipolar depression (BD) is associated with altered intrinsic brain activity, and possibly impaired neurovascular coupling (NVC). Although rapid-acting chronotherapies are effective in BD, their neurophysiological mechanisms remain unclear.

METHODS: In this longitudinal resting-state fMRI study, we examined fractional amplitude of low-frequency fluctuations (fALFF), indexing spontaneous neural activity, and hemodynamic response function (HRF) parameters, used as proxies of NVC, in 50 BD inpatients undergoing three cycles of combined total sleep deprivation and light therapy (TSD + LT), and in 30 healthy controls (HCs). Patients were scanned before (day 0) and after treatment (day 7), and depressive symptoms were evaluated with the Beck Depression Inventory Short Form.

RESULTS: At baseline, BD patients showed reduced fALFF in frontal, temporal, insular-opercular, and cerebellar regions relative to HCs. After TSD + LT, fALFF increased in widespread occipito-temporal, frontal, and cerebellar clusters in BD patients. HRF analyses showed no baseline between-group differences, but revealed a significant post-treatment increase in HRF response height across occipital, temporal, frontal, and cerebellar regions. Remission after TSD + LT was associated with fALFF changes, whereas larger HRF response height increases were observed in patients who did not require antidepressant treatment switch or augmentation during hospitalization.

CONCLUSION: TSD + LT was associated with modulation of both intrinsic neural activity and resting-state hemodynamic responses, with fALFF and HRF reflecting partly distinct aspects of short-term clinical outcome.

PMID:42419456 | DOI:10.1016/j.jad.2026.122226

Neural Netw. 2026 Jun 29;205(Pt A):109305. doi: 10.1016/j.neunet.2026.109305. Online ahead of print.

ABSTRACT

Brain Network Analysis (BNA) from resting-state functional MRIs (rs-fMRIs) has been widely applied to the prediction and understanding of brain disorders, by modeling connectivities among brain regions of interest (ROIs) to identify potential biomarkers. However, the majority of existing studies construct static brain networks utilizing a single predefined spatial scale (i.e., the number of brain ROIs), neglecting the inherently hierarchical nature of brain networks across various temporal and spatial scales. To address these limitations, we propose AdapHBNA, an Adaptive Hierarchical spatio-temporal Brain Network Analysis framework for brain disorder diagnosis. Specifically, we incorporate feature-channel-guided temporal hierarchical learning and Modular Brain Clustering (MBC)-driven spatial hierarchical learning strategies into the spatio-temporal encoding process of brain network, utilizing Mamba and Graph Neural Networks. It seamlessly merges the multi-scale learning, hierarchical brain representation learning and automatic spatio-temporal fusion into a unified end-to-end framework, which adaptively adjusts the temporal and spatial scales to capture hierarchical complementary brain representations across a spectrum of fine-to-coarse granularities. Extensive validation on the ABIDE, ADNI and REST_MDD datasets for Autism Spectrum Disorder, Early Mild Cognitive Impairment and Major Depressive Disorder demonstrates that AdapHBNA outperforms state-of-the-art methods by leveraging complementary diagnostic insights across multiple scales.

PMID:42419253 | DOI:10.1016/j.neunet.2026.109305

Cereb Cortex. 2026 Jun 2;36(6):bhag076. doi: 10.1093/cercor/bhag076.

ABSTRACT

The lateral frontoparietal (FP) network, also referred to as the central executive network, is critical for goal-directed behavior in primates. Resting-state functional MRI (rs-fMRI) studies have revealed functional homologies between humans and macaques; however, methodological disparities, particularly the use of anesthesia in non-human primates, raise questions about the validity of interspecies comparisons. Anesthetic agents such as isoflurane have been shown to alter functional connectivity (FC), but whether they differentially affect lateral FP subnetworks remains unclear. Here, we investigated the impact of isoflurane on FC patterns in dorsal and ventral FP subnetworks by acquiring rs-fMRI data in awake and anesthetized states from the same macaques. Using anatomically precise seeds and regions of interest defined by sulcal landmarks and known short- and long-range FP connections, we demonstrate that anesthesia reduces FC within short-range lateral FP subnetworks, with preserved connectivity in long-range projections. Notably, we also observed increased FC between lateral frontal and posterior medial cortical regions under isoflurane, suggesting a shift in network dynamics. These findings underscore the non-uniform effects of anesthesia on FP circuitry and offer insights into network reconfigurations associated with unconscious states.

PMID:42418823 | DOI:10.1093/cercor/bhag076

Alpha Psychiatry. 2026 Jun 25;27(3):49872. doi: 10.31083/AP49872. eCollection 2026 Jun.

ABSTRACT

BACKGROUND: Etomidate misuse (EM) has recently become an increasing public health concern in East and Southeast Asia, but its neurobiological mechanisms are still not well understood. Although substance use disorders (SUDs) are commonly associated with disruptions in large-scale brain network organization, the effects of EM on brain network topology remain largely unexplored.

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from individuals with EM and healthy controls (HC). Graph theoretical analyses were employed to and characterize global and nodal topological properties of functional brain networks. Clinical assessments captured substance use characteristics, craving, impulsivity, and addiction severity. Partial correlation analyses were conducted to examine associations between network metrics and substance use characteristics. Additonally, a support vector machine (SVM) classifier was implemented to discriminate individuals with EM from HC based on network features.

RESULTS: A total of 103 individuals with EM and 57 HC were included in the final analysis. Global topological organization that appeared was largely preserved in the EM group, with the exception of a significantly reduced clustering coefficient. At the nodal level, individuals with EM exhibited significant alterations in degree centrality, betweenness centrality, and nodal efficiency across regions predominantly distributed within the default mode, attention, and sensorimotor networks. Correlation analyses revealed no significant associations between network metrics and substance use characteristics following correction for multiple comparisons. Furthermore, the SVM model achieved moderate classification performance (accuracy = 66.7%) with an area under the curve (AUC) of 0.711.

CONCLUSIONS: This study provides the first systematic investigation of the brain network topology in EM. The findings indicate widespread alterations in nodal network properties alongside relatively preserved global topological organization. While these results may offer preliminary indicators related to EM, their clinical relevance requires further in future research.

PMID:42416184 | PMC:PMC13339792 | DOI:10.31083/AP49872

Imaging Neurosci (Camb). 2026 Jul 6;4:IMAG.a.1295. doi: 10.1162/IMAG.a.1295. eCollection 2026.

ABSTRACT

Sex differences in child neurobehavioral health suggest that male and female brains differ early in development. We took advantage of recent advances for in-utero magnetic resonance imaging (MRI) to conduct a pre-registered systematic review and meta-analysis of sex differences in brain structure and network connectivity of human fetuses. PubMed literature searching yielded 4,738 studies published between 2002 and 2025. All studies were screened by two independent reviewers and included if either structural or functional MRI was used to image brains of healthy human fetuses in utero and any results were reported stratified by sex. After title and abstract screening, 545 studies remained for full-text screening, resulting in 34 total studies meeting inclusion criteria. Analysis focused on 28 of these that reported sex-disaggregated data on the same measure across three or more independent samples. Pooled effect sizes revealed significantly larger male brains based on both linear measures (cerebral fronto-occipital and biparietal diameters and corpus callosum length) and global volumes (intracranial, total brain, lateral ventricles) by the start of the third trimester. Among 11 studies reporting brain growth trajectories, a majority reported faster growth in males. Among nine studies measuring functional connectivity using resting state functional MRI (rs-fMRI), six reported no significant sex differences and the others reported sporadic differences that were not replications. Together with large ultrasound studies, this review demonstrates larger brain size and faster brain growth in human males compared to females beginning in the second trimester, comparable to overall body size and other internal organ volumes. However, existing MRI and ultrasound research has not identified specific brain regions that differ disproportionately between male and female fetuses or any reliable sex differences in functional connectivity. Faster fetal growth in males, including the brain, does not readily explain neonatal male vulnerability and appears to be a product of genetic, rather than hormonal influences. These findings provide a reference for the emergence of brain sex differences later in development.

PMID:42416082 | PMC:PMC13338799 | DOI:10.1162/IMAG.a.1295

Neurosciences (Riyadh). 2026 Mar;31(3):262-271. doi: 10.17712/1658-3183.2804. Epub 2026 Jun 26.

ABSTRACT

OBJECTIVES: To determine how cytoarchitectonically defined subdivisions of the primary motor cortex, somatosensory cortex, and supplementary motor area (SMA) reorganize their integration with large-scale brain networks during healthy aging. This study investigated the lifespan trajectories of functional connectivity within cytoarchitectonically defined subregions of the primary motor cortex, somatosensory cortex, and supplementary motor area (SMA).

METHODS: We conducted a cross-sectional analysis of resting-state fMRI data from 150 healthy individuals (aged 23-80 years), stratified into young, middle-aged, and older groups. Data were sourced from the Southwest University Adult Lifespan Dataset (SALD) and analyzed between June 2024 and June 2025. Using the Jülich Brain Atlas, we defined seed regions for the M1 (BA4a, BA4p), premotor cortex (6d1-3), PSC (BA1-3), and SMA (pre-SMA, SMA proper). Functional coupling was calculated between these seeds and canonical large-scale networks, including the default mode (DMN), salience, dorsal attention, and frontoparietal systems.

RESULTS: Our analysis identified distinct age-dependent connectivity patterns. While all groups maintained robust motor-somatosensory coupling, older adults exhibited a significant loss of network segregation. Specifically, younger adults displayed strong sensorimotor integration with negative DMN coupling, whereas older adults showed widespread, diffuse positive connectivity across the DMN and frontoparietal networks. Middle-aged participants presented a transitional profile with expanded salience network interactions.

CONCLUSION: Aging is associated with a gradual shift from segregated sensorimotor processing to a more dedifferentiated, globally connected architecture. These findings highlight the importance of analyzing specific cytoarchitectonic subdivisions to detect subtle compensatory neuroplasticity mechanisms.

PMID:42415974 | PMC:PMC13340598 | DOI:10.17712/1658-3183.2804

Hum Brain Mapp. 2026 Jul;47(10):e70590. doi: 10.1002/hbm.70590.

ABSTRACT

Resting-state fMRI (rs-fMRI) is widely used to assess intrinsic brain activity, yet concerns about its test-retest reliability and reproducibility persist. Circadian rhythms strongly influence brain physiology, but their impact on rs-fMRI reliability remains poorly understood. In this study, we scanned 39 healthy young adults six times within a single day (08:00-20:00) under standardized conditions. For each session, we computed four common rs-fMRI metrics, including amplitude of low-frequency fluctuations (ALFF), wavelet-transformed ALFF (wALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo), and assessed reliability using intraclass correlation coefficients (ICCs). ReHo showed relatively higher and more stable reliability across sessions, whereas amplitude-based metrics, particularly fALFF, exhibited greater diurnal variation. Both network-level and region-specific analyses revealed low reliability in the limbic and subcortical structures, with a mid-morning dip at 10:00. Moreover, ICCs for ALFF, wALFF, and fALFF declined with increasing inter-scan intervals, whereas ReHo remained robust. These findings demonstrate diurnal fluctuations in rs-fMRI reliability, with different metrics exhibiting distinct temporal stability profiles. We recommend that scan timing and circadian influences should be explicitly considered in the design, analysis, and interpretation of future rs-fMRI studies.

PMID:42415272 | DOI:10.1002/hbm.70590

Commun Biol. 2026 Jul 7. doi: 10.1038/s42003-026-10599-w. Online ahead of print.

ABSTRACT

Functional brain networks support human cognition, yet how individualized network architecture emerges in early childhood remains poorly understood. Averaging across participants can obscure age-specific organization and person-to-person differences, particularly in slowly developing association cortices. We developed an age-appropriate functional reference that captured common structure across toddlers without averaging away individual variability, enabling estimation of each child's networks from resting-state fMRI. Across cohorts of 8-60-month-old children, we found individualized network organization-including finer-scale subdivisions and emerging language lateralization well before age five. Network layouts showed longitudinal stability, with greater consistency in sensory than association regions. Within-network connectivity was stronger and explained age-related variance when networks were defined using individualized rather than group-consensus topography. Left-lateralization of language networks tracked age-normalized verbal ability, linking early functional architecture to emerging cognition. These findings show that behaviorally relevant brain networks arise far earlier than previously recognized, providing a foundation for studying typical development and early biomarkers.

PMID:42414561 | DOI:10.1038/s42003-026-10599-w

Neuroimage. 2026 Jul 7:122106. doi: 10.1016/j.neuroimage.2026.122106. Online ahead of print.

ABSTRACT

Resting-state functional connectivity (RSFC) and networks (RSNs) provide insight into large-scale brain organization and its disruption in neurological disease. RSNs are most commonly assessed using fMRI, yet its translational use is constrained by high cost, motion sensitivity, and limited feasibility for repeated measurements. Functional near-infrared spectroscopy (fNIRS) offers a portable alternative, but its reliability for RSFC and RSN mapping remains insufficiently established. Near whole-head fNIRS data and fMRI-BOLD signals of corresponding cortical regions were extracted, based on which RSN organization was compared across two independent cohorts of 31 participants each. Cross-modal convergence and divergence were assessed using bivariate and partial correlations across multiple network levels. Edgewise analyses revealed substantial modality differences with bivariate correlations (50-61% of edges), which were markedly reduced using partial correlations (<3%). Group-averaged connectivity patterns showed moderate cross-modal similarity (r ≈ 0.37). At nodal level, net strength, local efficiency, and path-length differed substantially between modalities, while normalized strength and assortativity were largely comparable. Across nodes, graph-metric distributions derived from group-averaged matrices were broadly similar for normalized strength, assortativity, local efficiency, and path length (rho ≈ 0.27-0.5). At network-level, fNIRS-derived modules significantly overlapped with fMRI modules, particularly based on bivariate correlations, identifying default mode, attentional, executive, salience, sensorimotor, and visual networks (Jaccard ≈ 0.27-0.5). Overall, fNIRS captured key features of large-scale RSFC and RSN organization observed with fMRI, supporting meaningful cross-modal correspondence and translational utility. While partial correlations enhanced edge-level agreement, they attenuated nodal and modular recovery, suggesting greater suitability for targeted connectivity analyses rather than whole-network characterization.

PMID:42413889 | DOI:10.1016/j.neuroimage.2026.122106

Neuroimage Clin. 2026 Jul 3;51:104030. doi: 10.1016/j.nicl.2026.104030. Online ahead of print.

ABSTRACT

Aphasia is increasingly understood as a disorder of disrupted language networks rather than damage to isolated language regions. However, most resting-state functional connectivity studies treat people with aphasia as a single group or classify individuals by overall severity, potentially obscuring qualitative differences in network organization across aphasia types. The present study examined how resting-state functional connectivity varies across aphasia types and how aphasia severity relates to network organization following left-hemisphere stroke. Resting-state fMRI data were analyzed from 89 individuals in the chronic stage of recovery drawn from the open-source Aphasia Recovery Cohort dataset. Network-level and ROI-to-ROI functional connectivity analyses were conducted across 32 predefined dorsal and ventral stream language regions. Lesion-overlap analyses were additionally performed to characterize group-level lesion distributions. Network-level analyses revealed relatively limited effects, whereas ROI-to-ROI analyses demonstrated substantial heterogeneity across aphasia subgroups. Broca's aphasia and severe aphasia demonstrated clearer and more spatially convergent connectivity patterns, whereas anomic, mild, and moderate aphasia groups showed greater heterogeneity and limited group-level effects. Groups showing clearer functional connectivity patterns were also characterized by greater convergence in lesion distributions. Within Broca's aphasia, milder impairment was associated with stronger left-hemisphere and interhemispheric connectivity. Overall, aphasia type-based analyses revealed more differentiated connectivity patterns than severity-based groupings alone. These findings suggest that post-stroke language network organization varies across aphasia types characterized by partially shared clinical and lesion features and may not be fully captured by severity measures alone.

PMID:42413174 | DOI:10.1016/j.nicl.2026.104030

Eur Child Adolesc Psychiatry. 2026 Jul 7. doi: 10.1007/s00787-026-03122-3. Online ahead of print.

ABSTRACT

Abundant resting-state fMRI studies have shown altered brain activation and functional connectivity (FC) in children and adolescents with Attention Deficit Hyperactivity Disorder (ADHD) compared with typically developing (TD) subjects, with specific disruptions in brain networks associated with attention and cognitive control. Most prior meta-analyses have focused on populations across all ages, leaving a significant gap in understanding how these alterations unfold during childhood and adolescence. The current meta-analysis reviewed 36 studies (1867 subjects, 989 with ADHD, 878 TD), including 20 seed-based connectivity (SBC) studies and 16 non-seed-based connectivity (Non-SBC) studies, with a particular focus on FC within and between seven major brain networks. Activation Likelihood Estimation (ALE) analyses were conducted separately for the SBC and Non-SBC datasets. In the SBC analysis, we found significant reductions in FC between the Default Mode Network (DMN) and the Dorsal Attention Network (DAN), as well as between the Somatomotor Network (SMN) and the Ventral Attention Network (VAN) in the ADHD group, whereas no significant alterations were identified in the Non-SBC analysis. Our findings are consistent with aspects of two theoretical frameworks, the DMN interference hypothesis and the multi-network model of ADHD, suggesting that weakened inter-network connectivity may contribute to the core cognitive and attentional difficulties observed in ADHD. These findings contribute to a better understanding of the network-level neural features of ADHD and may provide a basis for future studies on early intervention.

PMID:42412230 | DOI:10.1007/s00787-026-03122-3

Psychol Med. 2026 Jul 7;56:e217. doi: 10.1017/S0033291726104899.

ABSTRACT

BACKGROUND: Cognitive difficulties, including problems with attention and executive processing, are common in major depressive disorder (MDD), and strongly predict psychosocial and occupational functioning. Impairment in sustained attention contributes to increased intra-individual variability (IIV) in reaction times observed during cognitive tasks. Understanding brain network changes associated with IIV could guide novel neuromodulation strategies targeting cognitive difficulties.

METHODS: We analyzed baseline resting-state fMRI data from 209 patients with moderate-to-severe treatment-resistant MDD who participated in the BRIGhTMIND neuromodulation trial. Following a preregistered analytic protocol, we examined associations between: functional connectivity across three core brain networks (executive control, ECN; default mode, DMN; and salience network, SN); components of IIV derived from a choice reaction time task (using a three-parameter ex-Gaussian model); and functioning.

RESULTS: Greater IIV was linked to increased ECN-DMN functional connectivity. The ECN supports top-down control and externally directed cognition, while the DMN supports internal mentation and rumination. ECN-DMN connectivity was modulated by the SN, which prioritizes salient internal and external stimuli. Higher SN-ECN connectivity was associated with lower ECN-DMN connectivity and with faster mean reaction times. Both IIV and mean reaction time predicted functioning, with poorer functioning related to a slowed and inflexible response pattern.

CONCLUSIONS: Distinct components of reaction time variability are associated with specific patterns of brain network connectivity, largely independent of mood severity. Connectivity between the salience and executive control networks may represent a promising target for neuromodulation interventions focused on cognitive deficits in MDD.

PMID:42410874 | DOI:10.1017/S0033291726104899

Eur J Nucl Med Mol Imaging. 2026 Jul 6. doi: 10.1007/s00259-026-08053-4. Online ahead of print.

ABSTRACT

PURPOSE: Dopaminergic signalling and glucose metabolism have been implicated in autism spectrum disorder (ASD), yet in vivo evidence in the human brain remains largely unexplored. This study examined subcortical dopamine D2 receptor availability and glucose metabolism in ASD to assess their clinical relevance.

METHODS: In this dual-tracer PET/MR case-control study, 30 autistic and 30 neurotypical adults (age-, sex-, body mass index-, and IQ-matched) underwent [11C]raclopride PET to assess dopamine D2 receptor availability, [1⁸F]FDG PET to measure glucose metabolism and resting-state fMRI to evaluate functional connectivity.

RESULTS: Autistic individuals demonstrated increased D2 receptor availability in the thalamus, with additional increases in the nucleus accumbens and putamen among autistic males compared to neurotypical males. Glucose metabolism was elevated in the thalamus and globus pallidus in ASD relative to NT, and this pattern persisted within both autistic males and autistic females in sex‑stratified comparisons. Globus pallidus and thalamic glucose metabolism correlated positively with social and communication difficulties. Resting-state fMRI analyses revealed diagnosis- and sex-dependent correlations between thalamic D2 receptor availability and functional connectivity.

CONCLUSIONS: This study provides in vivo evidence of elevated subcortical D2R availability and glucose metabolism in autistic adults, a pattern observed across sexes. We also show that D2R availability is tightly linked to glucose metabolism and that D2R-functional connectivity coupling is altered in ASD, both relative to neurotypical adults and between autistic males and females. These findings highlight dopaminergic mechanisms as potential biomarkers and therapeutic targets in ASD.

PMID:42406073 | DOI:10.1007/s00259-026-08053-4

Neuromodulation. 2026 Jun 15:S1094-7159(26)00618-5. doi: 10.1016/j.neurom.2026.06.460. Online ahead of print.

ABSTRACT

OBJECTIVES: Transcranial focused ultrasound stimulation (TUS) is an emerging neuromodulatory technique capable of modulating cortical and subcortical brain regions with high spatial precision. However, its effects on large-scale functional brain networks and their temporal evolution remain incompletely understood. This study investigated whether brief theta burst TUS induces target-specific alterations in functional brain network topology over the first hour after stimulation.

MATERIALS AND METHODS: A total of 22 healthy participants were randomly assigned to receive TUS targeting either the right inferior frontal cortex (IFC) or the right thalamus. Resting-state functional magnetic resonance imaging was acquired at baseline and at three minutes post stimulation intervals spaced 15 minutes apart. Graph-theoretical analyses quantified four centrality metrics (strength, expected influence, betweenness, and closeness) across 86 brain regions. Global network organization was assessed using small-worldness.

RESULTS: IFC stimulation produced progressive reductions in regional network integration, initially affecting visual cortices and subsequently extending to right prefrontal and temporal regions, the insula, and the putamen, with peak effects occurring approximately 45 minutes post stimulation. IFC stimulation also increased global small-worldness, indicating a shift toward a more randomized network configuration. In contrast, thalamic stimulation resulted in a spatially circumscribed and temporally stable reduction in betweenness centrality within the left precuneus without widespread network alterations.

CONCLUSIONS: Brief theta burst TUS induces target-dependent and temporally evolving changes in large-scale functional brain organization. Cortical stimulation of the IFC produced distributed and progressive network reconfiguration, whereas thalamic stimulation yielded a focal and stable effect. These findings suggest that the magnitude and spatial extent of TUS-induced network modulation depend on the connectivity profile and topologic embedding of the stimulated structure.

PMID:42405921 | DOI:10.1016/j.neurom.2026.06.460

JIMD Rep. 2026 Jul 3;67(4):e70108. doi: 10.1002/jmd2.70108. eCollection 2026 Jul.

ABSTRACT

In early-treated adults with phenylketonuria (PKU), the effects of elevated phenylalanine (Phe) on functional brain networks remain poorly understood. While subacute structural brain changes have been reported, their functional significance remains unclear. Executive and attentional functions have been shown to be particularly sensitive to metabolic control in PKU. In this double-blind, randomized, placebo-controlled crossover trial, we investigated the effects of a 4-week high-Phe period on resting-state functional connectivity using seed-based analyses of the dorsal attention and frontoparietal networks, which are critically involved in executive and attentional functions. Twenty-three adults with PKU (median age 35.3 years [IQR 12.0]; 43% female) were included. When baseline connectivity was considered, no significant differences in functional connectivity were observed between the Phe and placebo periods. Without baseline adjustment, exploratory analyses revealed increased functional connectivity of the right frontal eye field within the dorsal attention network with frontal regions. Changes in functional connectivity were neither associated with changes in metabolite concentrations nor in working memory, attention, or executive function. These findings suggest that subacute increases in Phe may induce subtle and potentially transient changes in functional brain networks, although their functional relevance and persistence over longer exposure periods remain unclear.

PMID:42404601 | PMC:PMC13330130 | DOI:10.1002/jmd2.70108

bioRxiv [Preprint]. 2026 Jun 28:2026.06.23.734045. doi: 10.64898/2026.06.23.734045.

ABSTRACT

This paper presents a framework for modelling the topography of whole-brain connectivity in resting-state functional MRI. The aim is to disentangle functional segregation, which manifests as abrupt changes in connectivity, from so-called gradients, i.e., smooth variations in connectivity across the brain. Our core assumption is that functional segregation leads to low-rank structure in the dense (point-to-point) connectome, whereas connectivity gradients imply a sparse and non-low-rank structure in the dense connectome. Our method thus decomposes the connectome into low-rank and sparse components, enabling the integration of local-nonlinear and global-linear embedding strategies. We show that this hybrid model approximates the empirical dense connectome more effectively than purely low-rank or purely gradient approaches. We also find that connectivity gradients derived from this model exhibit strong correspondence with task-based topographic maps. We hope that this approach can provide insight into the organisational principles of brain regions where gradients remain poorly characterised.

PMID:42395476 | PMC:PMC13320991 | DOI:10.64898/2026.06.23.734045

Res Sq [Preprint]. 2026 Jun 28:rs.3.rs-9557211. doi: 10.21203/rs.3.rs-9557211/v1.

ABSTRACT

Neuroimaging studies rarely test whether the variance structure is equivalent across population subgroups. Here, in 4,736 participants from the Adolescent Brain Cognitive Development (ABCD) cohort, we examine racialized heteroscedasticity (i.e., differences in variance across racialized groups) in neuroimaging and behavioral data and test how these differences in variance propagate into predictive modeling. Across neuroimaging modalities, behaviors, and predictive frameworks, variance differences exhibited consistent patterns, indicating that variance structure is a stable property across domains within the dataset. Simulation analyses demonstrated that such differences directly induce subgroup disparities in prediction error and reliability, even in the absence of mean differences. Across neuroimaging modalities, multiple measures demonstrated greater variance in Black participants, particularly in functional imaging modalities. Similar variance patterns were observed in behavioral measures, and predictive models exhibited greater residual dispersion and prediction variance in Black participants even when overall performance metrics were comparable. These findings position variance structure, rather than central tendency, as a critical determinant of model performance, generalizability, and reliability across diverse populations.

PMID:42396488 | PMC:PMC13321234 | DOI:10.21203/rs.3.rs-9557211/v1

Res Sq [Preprint]. 2026 Jun 25:rs.3.rs-9773701. doi: 10.21203/rs.3.rs-9773701/v1.

ABSTRACT

Major Depressive Disorder (MDD) involves large-scale brain network disruption at rest. Canonical zero-lag functional connectivity methods often miss temporal offsets (or "lags") in interactions. Lag-adjusted functional connectivity captures intrinsic neural timescales (INTs) and directional signaling, offering a more sensitive framework to characterize network-level alterations. Here, we applied the NeuroMark framework to resting-state scans from 235 MDD and 284 healthy controls, identifying 105 intrinsic connectivity networks (ICNs) and their time series. To enable sub-TR estimation, time series were upsampled to 100 ms resolution. Lag-adjusted connectivity was computed as the maximal cross-correlation for each ICN pair within a ±2s window sampled at 0.1s intervals. Group differences were assessed using a regression model. Significant differences emerged between groups (p<0.05). Specifically, MDD revealed hyperconnectivity in salience-sensorimotor and sensorimotor-temporoinsular networks, alongside hypoconnectivity in salience-higher cognitive temporal and frontal networks and temporoparietal-visual systems, indicating altered coordination among sensory, emotional, and cognitive processes. An exploration of the lags revealed a non-random bias in the temporal ordering of networks operating at different INTs. This was characterized by earlier relative cortical coupling in MDD, suggesting compressed inter-network timing. These findings underscore the utility of lag-adjusted approaches for detecting impaired neural coordination, beyond alterations in connectivity strength.

PMID:42396482 | PMC:PMC13321241 | DOI:10.21203/rs.3.rs-9773701/v1