Most recent paper

Psychoradiology. 2026 Jun 3;6:kkag020. doi: 10.1093/psyrad/kkag020. eCollection 2026.

ABSTRACT

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder whose core pathological mechanism is deeply rooted in the dysfunction of the cortico-striato-thalamo-cortical circuit. This review summarizes recent advances in magnetic resonance imaging (MRI) studies investigating thalamic abnormalities in children with ADHD, highlighting multidimensional pathological changes within the thalamus. Structurally, children with ADHD exhibit delayed overall thalamic volume development and significant atrophy in specific subregions, such as the ventral anterior nucleus, mediodorsal nucleus, and pulvinar. Regarding white matter microstructure, projection pathways from the thalamus to regions such as the motor cortex and striatum are impaired. Both resting-state and task-fMRI consistently demonstrate weakened cortical connectivity between the thalamus and both the default mode and dorsal attention networks. Furthermore, current evidence suggests that mainstream pharmacological treatments, particularly methylphenidate and atomoxetine, effectively promote structural remodeling and the "normalization" of network functions in the aberrant thalamus. Additionally, multidimensional neuroimaging metrics of the thalamus demonstrate substantial potential as objective biomarkers for assessing genetic risk, classifying clinical subtypes, and predicting treatment outcomes. Ultimately, this review emphasizes that the thalamus is not merely a passive sensory relay station, but an active gatekeeper regulating cognition and behavior. Its structural and functional abnormalities constitute a central hub in the pathogenesis of ADHD. Supported by future large-scale machine learning and longitudinal studies, the thalamus holds promise as a crucial biomarker for the precise diagnosis and personalized targeted intervention of ADHD.

PMID:42328622 | PMC:PMC13280544 | DOI:10.1093/psyrad/kkag020

bioRxiv [Preprint]. 2026 Jun 11:2026.06.10.731401. doi: 10.64898/2026.06.10.731401.

ABSTRACT

Brain regions exhibit dynamic yet highly coordinated activity patterns that form large-scale functional networks measurable through resting-state correlations. While their association with fluctuating activity may intuitively suggest functional networks to be temporally transient and dependent on state, a growing body of literature suggests that they are person-specific and stable across days. If truly person-specific, then functional networks should preserve unique characteristics over extended periods. To test this hypothesis, we collected longitudinal precision fMRI data (≥60 minutes per participant per time point) from 10 healthy young adults across 1-3 year intervals, as well as three adults over 8-13 years. We further replicated findings in the MyConnectome dataset and its 10-year follow-up. Functional network organization-when sufficient per-participant data were collected- remained largely stable within individuals over prolonged periods of up to 13 years, suggesting that individualized brain organization constitutes persistent features of personal identity that may be supported by homeostatic mechanisms.

SIGNIFICANCE: While many aspects of brain function are portrayed as dynamic and malleable, our study provides evidence for the long-term preservation of functional organization of the healthy young adult brain. Whole-brain functional organization exhibited unique individual characteristics that were preserved for years, even over a decade. The stability of such individualized neural architecture suggests that the brain encodes features of personhood that may be invariant across contexts and temporal fluctuations. This observation reframes our understanding of brain resilience and plasticity by offering new insights into the extent that homeostatic mechanisms of brain organization can withstand stressors and environmental changes through time to maintain a constant functional organization. These insights pave the way for a more comprehensive understanding of the neural mechanisms behind this stability, with the possibility of pinpointing critical markers of healthy brain function and its disruptions.

PMID:42327182 | PMC:PMC13277913 | DOI:10.64898/2026.06.10.731401

bioRxiv [Preprint]. 2026 Jun 10:2026.06.05.730513. doi: 10.64898/2026.06.05.730513.

ABSTRACT

Understanding how functional brain networks in resting state configurations reorganize to perform cognitive tasks is critical for uncovering the nature and mechanisms underlying network dysconnectivity in psychiatric disorders. We applied energy landscape analysis (ELA), a statistical physics-based computational approach, to functional MRI data from 23 adolescent-onset schizophrenia (AOS) and 44 healthy control (HC) subjects, acquired during rest followed by executive function task. ELA maps brain activity into distinct network states and quantifies how the brain transitions among them, capturing differences in stability of network states and transition complexity across conditions. AOS and HC showed markedly different condition-dependent patterns of brain state organization and dynamics. At rest, AOS exhibited reduced dynamical complexity compared to HC (7 vs. 14 stable states) that reversed during the task with more than 2-fold increase in accessible but rarely occupied brain states, while HC showed an opposite pattern. These results suggest that cognitive demands unmask latent fragmentation of the energy landscape, comprising a proliferation of accessible but rarely occupied states not apparent at rest, in AOS. State occupancy analysis revealed a small number of dominant states accounting for the majority of brain activity time, with AOS showing greater persistence in the fully-active DMN state during task performance compared to HC. These findings suggest that the rest-to-task transition features fundamentally different neural dynamics in AOS compared to HC. Combined analysis of resting fMRI and task-induced brain dynamics revealed neural factors that may contribute to cognitive dysfunction and psychiatric symptoms in schizophrenia, with important implications for development of biomarkers and treatment targets.

PMID:42327046 | PMC:PMC13277904 | DOI:10.64898/2026.06.05.730513

Imaging Neurosci (Camb). 2026 Jun 17;4:IMAG.a.1254. doi: 10.1162/IMAG.a.1254. eCollection 2026.

ABSTRACT

Converging evidence from studies on brain network "fingerprinting" and precision functional mapping suggest that brain networks are highly individualized in functionally meaningful ways. Concurrently with a growth in studies on this topic, there has been a rise in interest on dynamics (approximately second-to-second changes) in brain networks within scan sessions. While analyses of traditional static networks have increasingly grown towards emphasizing the importance of individual differences in brain network topology, studies of dynamic networks typically follow methodology that require brain states to be considered at a group level. Recent studies have begun to assess the individuality of recurring dynamic brain "states". In this work, we extend this recent work by exploring the extent to which functional connectivity fingerprinting is feasible at single-frame temporal resolution. We estimate connectivity at individual volumes using phase coherence. We find that the identity of participants can be classified based on single volumes given sufficient database scan data and that having more highly parcellated atlases facilitates identification. Finally, we find that tasks can be identified more readily within subjects than between subjects. We conclude that participant identity may be an important driver of observed single-volume connectivity patterns. Further, the single-volume neural correlates of a task appear to be more consistent within subjects than between subjects. This highlights the importance of considering individual variability in studies of brain network dynamics.

PMID:42326560 | PMC:PMC13277782 | DOI:10.1162/IMAG.a.1254

Front Neurosci. 2026 Jun 4;20:1815703. doi: 10.3389/fnins.2026.1815703. eCollection 2026.

ABSTRACT

Autonomous sensory meridian response (ASMR) is a tingling sensation that originates in the occipital region and spreads along the neck and spine, elicited by specific audiovisual stimuli known as ASMR triggers. The characteristics of ASMR-related changes in brain activity relative to other external stimuli, and whether these changes are specific to ASMR, remain unclear. The aim of this study is to compare changes in functional connectivity during exposure to ASMR triggers and classical music, and to clarify the changes in connectivity that are more strongly associated with ASMR trigger listening. Forty-eight healthy adults without a history of psychiatric disorders underwent functional MRI under three conditions: resting state without auditory stimulation, listening to ASMR triggers, and listening to classical music. Functional connectivity during the ASMR and classical-music conditions was assessed relative to the resting state. As a result, functional connectivity between the medial prefrontal cortex and the right lateral parietal cortex increased during ASMR trigger listening compared to rest. Relative to classical music listening, ASMR trigger listening increased functional connectivity between the medial prefrontal cortex and the right lateral parietal cortex, between the left anterior insula and left supramarginal gyrus, and between the right rostral prefrontal cortex and the anterior cingulate cortex. No significant changes in functional connectivity were observed during classical music listening alone. These findings suggest that, compared with classical music listening, ASMR trigger listening is associated with stronger functional connectivity between specific ROI pairs involved in self-referential/internal evaluative processing and sensory integration.

PMID:42325953 | PMC:PMC13275351 | DOI:10.3389/fnins.2026.1815703

J Neurophysiol. 2026 Jun 21. doi: 10.1152/jn.00238.2026. Online ahead of print.

ABSTRACT

Inflammation is associated with detrimental health outcomes including deleterious effects on the brain. We have recently introduced a new measure of brain function reflecting the moment-to-moment change, or turnover, in the resting state blood oxygen level dependent (BOLD) signal, or TBOLD. In previous studies, increase of TBOLD with age was found to be associated with concomitant decrease in brain volume, whereas both changes were absent in individuals carrying the neuroprotective Human Leukocyte Antigen (HLA) allele DRB1*13:02. Given that TBOLD reflects neurovascular coupling and that neuroinflammation is involved in brain aging, we hypothesized that TBOLD could reflect neuroinflammation. Here, we tested this hypothesis by assessing the association of TBOLD with known inflammatory markers in a large sample of 1390 healthy participants from the Human Connectome Project on Aging/Aging Adult Brain Connectome (AABC). We found a highly significant, positive association between TBOLD and the inflammatory marker C reactive protein (CRP). Furthermore, we found a highly significant association between TBOLD and interleukin 6 (IL-6) in a smaller group of 97 participants for whom IL-6 measurements were available. These findings document significant positive associations of TBOD to systemic inflammatory markers, lending support to hypothesis that TBOLD may serve as a proxy for neuroinflammation.

PMID:42324453 | DOI:10.1152/jn.00238.2026

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Jun 20:111800. doi: 10.1016/j.pnpbp.2026.111800. Online ahead of print.

ABSTRACT

Aberrant resting-state functional connectivity (rsFC) within neurocognitive networks is a hallmark of alcohol use disorder (AUD). However, the spatial architecture of the central autonomic network (CAN)-the vital neural substrate governing cardiovascular and homeostatic control-and its association with heart rate variability (HRV) remain poorly characterised. We investigated group differences in CAN-related rsFC and its statistical relationship with HRV metrics in 112 young adults (54 AUD, 58 healthy controls [HC]) using resting-state fMRI and separate, HRV assessments. Seed-based analyses targeted core cortical CAN nodes. Young adults with AUD exhibited a profound pattern of functional connectivity alterations within the CAN compared with HCs. Specifically, the AUD group demonstrated attenuated long-range connectivity between CAN seeds and temporo-frontal regions, alongside heightened, pathologically constrained intra-network connectivity involving the insula and brainstem. In HCs, resting HRV indices correlated positively with rsFC across widely distributed cortical and cerebellar systems, reflecting a robust baseline association between central CAN integrity and autonomic output. Conversely, the AUD group exhibited an attenuated and highly segregated pattern of relationships, where the expected association between CAN network architecture and resting HRV features was markedly diminished. These findings demonstrate that early-stage AUD is characterised by a fundamental spatial reorganization of the CAN and a significant blunting of brain-autonomic relationships. This neuro-autonomic alteration may represent a distinctive neuroimaging trait marker of chronic autonomic dysregulation, highlighting the critical need for early detection and targeted management of AUD in young adults.

PMID:42323184 | DOI:10.1016/j.pnpbp.2026.111800

Brain Behav Immun. 2026 Jun 20:106880. doi: 10.1016/j.bbi.2026.106880. Online ahead of print.

ABSTRACT

Systemic inflammation is increasingly recognised as a key modulator of brain function, yet its impact on large-scale brain network topology remains incompletely understood. In particular, it is unclear whether inflammation alters the balance between functional segregation and integration, as captured by small-world organisation, and whether such effects are better detected using dynamic rather than static connectivity analyses. In this study, we conducted a secondary analysis of a previously collected dataset to examine the effects of experimentally induced inflammation on static and dynamic small-world topology using resting-state fMRI and graph-theoretical methods. Eighteen healthy male participants completed a double-blind, placebo-controlled, randomised crossover trial involving typhoid vaccination, a well-established model of low-grade systemic inflammation. Small-worldness was quantified across a fixed density range for both static and dynamic functional connectivity. No significant differences were observed in static small-worldness between conditions. In contrast, dynamic analyses revealed a significant reduction in mean small-worldness following vaccination. This effect was primarily driven by reduced clustering coefficient, with no change in characteristic path length, indicating a selective alteration in local segregation while preserving global integration. Dynamic state analysis identified two recurring connectivity states with distinct topological profiles. Although differences in fractional occupancy and dwell time were not statistically significant, participants showed a consistent tendency to spend less time in the high small-worldness state following inflammation. These preliminary findings indicate that inflammation modulates the temporal organisation of brain networks in ways not detectable using static approaches and are consistent with a metabolically efficient reconfiguration of network topology under inflammatory challenge.

PMID:42323056 | DOI:10.1016/j.bbi.2026.106880

Biol Psychiatry Cogn Neurosci Neuroimaging. 2026 Jun 20:S2451-9022(26)00180-1. doi: 10.1016/j.bpsc.2026.06.005. Online ahead of print.

ABSTRACT

BACKGROUND: In early development autism can be stratified into subtypes differentiated by non-core language, intellectual, motor, and adaptive functioning features. In toddlerhood, these subtypes show different genomic patterning effects on brain structure and function that follow early primary axes of neurodevelopmental organization. This leads to the hypothesis that early cortical patterning differences may continue to be evident between subtypes in later development within hierarchical organization along the sensorimotor-association (S-A) axis.

METHODS: Standardized phenotypic measures from the National Institute of Mental Health Data Archive (NDA; n=419) were used in unsupervised data-driven clustering analyses to build a phenotypic stratification model based on language, intellectual, and adaptive functioning (LIAF) features. This stratification model was then applied to independent multi-site resting state fMRI (rsfMRI) datasets (autism n=174; typically-developing (TD) n = 185) to test for subtype differences in global functional connectivity. Mass univariate and multivariate patterning analyses were used to test for differences between TD and autism subtypes.

RESULTS: Clustering revealed 2 phenotypically distinct autism subtypes (high versus low) in late childhood to adulthood that generalize in independent data with 92% accuracy. Autism was associated with hyper-connectivity in association areas alongside hypo-connectivity in sensorimotor areas. However, these differences were most pronounced in the TD versus autism low LIAF group comparison and resemble patterning effects that follow the S-A axis.

CONCLUSIONS: These findings suggest that cortical patterning of global functional connectivity along the S-A axis is different in autism relative to TD and may be relatively more pronounced in autism with low LIAF features.

PMID:42323050 | DOI:10.1016/j.bpsc.2026.06.005

Psychiatry Res Neuroimaging. 2026 Jun 15;362:112274. doi: 10.1016/j.pscychresns.2026.112274. Online ahead of print.

ABSTRACT

Individuals with schizophrenia (SZ) experience significantly greater obesity rates compared to the general population. The underlying biological mechanisms, however, remain poorly understood. Although brain functional connectivity (FC) has been associated with obesity in the general population, its role in obesity in SZ is largely unexplored. As such, this study examined FC contributions to adiposity in participants with SZ (n = 46) and an adiposity-matched comparison group without SZ (n = 46) as they completed resting-state functional magnetic resonance imaging in fasted and fed states. A machine learning approach identified FC patterns associated with adiposity (percent body fat), with model performance evaluated on an independent test set. In both fasted and fed states, brain regions involved in reward and eating behaviors contributed to adiposity prediction in both groups. While fasted, predictive connections in SZ largely involved limbic and sensorimotor networks, whereas comparison group networks were more varied. In the fed state, SZ predictive features included visual, default mode, and executive control networks, while comparison group connections involved limbic, sensorimotor, salience, and executive control networks. Findings may suggest shared, as well as diagnosis- and state-specific, FC patterns associated with adiposity in SZ, which may help inform future development of obesity-related interventions in this high-risk population.

PMID:42322676 | DOI:10.1016/j.pscychresns.2026.112274

Geroscience. 2026 Jun 20. doi: 10.1007/s11357-026-02333-5. Online ahead of print.

ABSTRACT

Alzheimer's disease (AD) involves early disruptions in brain connectivity, yet how AD risk markers relate to resting-state dynamic functional connectivity (rs-dFC) remains unclear. We examined associations of AD pathology, genetic risk, and blood-based biomarkers (BBMs) of neurodegeneration with local and distant rs-dFC in cognitively normal older adults and explored links with cognitive performance. Baseline data from 86 cognitively normal older adults in the AGUEDA trial (NCT05186090) were analyzed. Participants underwent amyloid-beta (Aβ)-PET, APOE4 genotyping, and plasma BBM quantification (Aβ42/40, BD-tau, GFAP, NfL, p-tau181, and p-tau217). rs-fMRI was used to compute voxel-wise local and distant rs-dFC using a stepwise connectivity framework. Models tested associations between AD markers and rs-dFC adjusting for age, sex, and education; secondary models examined extracted cluster values and six cognitive domains. Aβ-positive individuals and APOE4 carriers showed lower local connectivity in frontal regions. APOE4 carriers also exhibited higher distant connectivity in the superior motor area, inferior frontal gyrus, and anterior insula. Among BBMs, only NfL was associated with both lower local (insula and cingulate) and higher distant (precuneus, putamen, thalamus, supramarginal, and superior motor area) connectivity. Secondary analyses suggested additional cluster-cognition associations. Across AD risk markers, higher risk (Aβ-positivity, APOE4 carriage, and higher NfL) converged on a consistent rs-dFC signature characterized by reduced local and increased distant connectivity. This local-to-distant shift may serve as a candidate functional marker of early AD-related network vulnerability in cognitively normal aging and could support risk monitoring and stratification pending longitudinal validation.

PMID:42322546 | DOI:10.1007/s11357-026-02333-5

Radiol Med. 2026 Jun 20. doi: 10.1007/s11547-026-02245-6. Online ahead of print.

ABSTRACT

BACKGROUND: Brain tumors impair brain function both locally and across distant regions by disrupting network connectivity, contributing to cognitive deficits and triggering compensatory plasticity. Traditional resting-state fMRI methods average brain activity over time, missing transient, dynamic events critical to cognition. Co-Activation Pattern (CAP) analysis captures these brief brain states, enabling quantification of state engagement and duration.

PURPOSE: To investigate alterations in transient brain states in patients with brain tumors using CAP analysis of resting-state fMRI, and to assess whether these changes reflect modified engagement of cognitive states compared to healthy controls.

MATERIALS AND METHODS: This retrospective cross-sectional study included 106 patients with left-hemispheric brain tumors (72 high-grade gliomas, 19 low-grade gliomas, 15 metastases; mean age 61.15 ± 8.95 years; 43 women) and 100 age-matched healthy controls. Resting-state fMRI data were analyzed using a seed-free clustering method (TbCAPs toolbox) to extract CAPs. CAPs were first identified in controls and then matched to patients via spatial similarity. Each CAP was assigned to a canonical brain network using the GIFT toolbox. Dynamic metrics computed included: persistence (duration of a CAP), transitions (switching frequency), in-degree, and out-degree. Group comparisons used two-tailed t-tests with Benjamini-Hochberg correction (p < 0.05).

RESULTS: Six CAPs were identified. Compared to controls, patients showed significantly increased transitions, in-degree, and out-degree, and decreased persistence in CAPs linked to the default mode and executive control networks (all p < 0.01), suggesting more frequent but less stable engagement. Visuospatial network CAPs demonstrated lower transition, in/out-degree and persistence in patients (p < 0.05). No significant differences were observed among tumor types.

CONCLUSION: Patients with brain tumors display altered CAP dynamics involving higher-order cognitive networks and perceptual networks. These alterations may reflect the combined effects of tumor-related network damage and potential adaptive reorganization, with potential implications for functional preoperative planning and prognosis. However, in the absence of direct clinical or neuropsychological correlations, these interpretations remain hypothesis-generating. The findings are also limited by the retrospective cross-sectional design preventing causal or longitudinal interpretation, and the restriction to left-hemispheric tumors. Future studies integrating CAP dynamics with cognitive and clinical outcomes will be necessary to determine whether these changes reflect compensatory functional reorganization in brain tumor patients.

PMID:42322516 | DOI:10.1007/s11547-026-02245-6

J Headache Pain. 2026 Jun 19. doi: 10.1186/s10194-026-02427-7. Online ahead of print.

ABSTRACT

BACKGROUND: Chronic migraine (CM) carries high disability, yet interictal MRI phenotypes that distinguish CM from episodic migraine (EM), particularly in medication-overuse headache (MOH)-inclusive cohorts, remain incompletely characterized. We tested whether periventricular diffusivity (PVeD), an indirect MRI marker of tissue-water properties at the ventricular-parenchymal interface, is associated with CM and headache burden.

METHODS: In this cross-sectional 3.0-T multimodal MRI study, 289 adults with complete structural MRI, diffusion MRI, and resting-state fMRI were analyzed: 67 healthy controls, 162 EM, and 60 CM. MOH was diagnosed and retained in the CM group. MRI was acquired during verified interictal evening sessions; participants with headache within 24 hours before or after MRI were excluded. The primary contrast was age- and sex-adjusted CM versus EM for PVeD. Secondary analyses examined MOH strata, headache-frequency strata, partial Spearman correlations, Firth logistic regression for CM status, and HIT-6 models.

RESULTS: Age- and sex-adjusted PVeD was lower in CM than EM (adjusted difference, -0.011; 95% CI, -0.017 to -0.006; standardized difference, -0.71; p < 0.001) and healthy controls (-0.014; 95% CI, -0.021 to -0.007; standardized difference, -0.88; p < 0.001), with no EM-control difference. Both CM participants with and without MOH had lower PVeD than EM. In migraine participants, lower PVeD correlated with higher headache frequency, HIT-6, and MIDAS and with larger choroid plexus volume and smaller thalamic, nucleus accumbens, and putaminal volumes. In the expanded clinical-plus-MRI Firth model, each 1-SD higher PVeD was associated with lower CM odds (OR, 0.59; 95% CI, 0.38 to 0.89; p = 0.011). Higher PVeD was associated with lower HIT-6 after adjustment for headache frequency or MOH.

CONCLUSIONS: CM was associated with lower PVeD at the ventricular-parenchymal interface, and lower PVeD was linked to patient-centered burden in this MOH-inclusive cohort. PVeD is not yet a diagnostic or treatment-selection biomarker, but may help define an MRI phenotype for future chronification-risk and treatment-response studies after longitudinal and external validation.

PMID:42321653 | DOI:10.1186/s10194-026-02427-7

Int Psychogeriatr. 2026 Jun 19:100233. doi: 10.1016/j.inpsyc.2026.100233. Online ahead of print.

ABSTRACT

BACKGROUND: Working memory impairment has been reported in older adults with sleep disorders and MCI, with the frontoparietal network playing a central role in working memory. The key question is whether integrating Tai Chi with rTMS improves working memory, and whether such improvements result from the modulation of frontoparietal networks plasticity.

METHODS: Seventy-one participants with sleep disorders and MCI were assigned to the experimental group (Tai Chi + 1-Hz rTMS, n = 37) or sham group (Tai Chi + sham rTMS, n = 34). They completed 6 weeks of Tai Chi combined with neuronavigated rTMS targeted the right DLPFC and underwent fMRI scans. Outcomes included Numerical N-back task, digit span task，Pittsburgh Sleep Quality Index (PSQI), Montreal Cognitive Assessment (MoCA). Task fMRI measured N-back activation patterns, and seed-based resting-state functional connectivity (rsFC) was assessed. Correlations between the activation/rsFC and N-back task performance were explored.

RESULTS: Seventy-one participants (mean age 67.6 ± 4.6 years; 30 male [42%], 41 female [58%]) were included. After 6 weeks, the experimental group showed significant improvements versus shams in PSQI, MoCA, 0-back and 2-back task accuracy, 0-back reaction time, and forward digit span (all p < 0.05). The 2-back accuracy was negatively correlated with right precuneus activation (r = -0.381, p = 0.034) and positively correlated with right precuneus connectivity to the left SMA (r = 0.367, p = 0.042).

CONCLUSION: Adjunctive neuronavigated rTMS delivered in addition to Tai Chi training may enhance working memory rehabilitation in older adults with sleep disorders and MCI, with frontoparietal network modulation as a potential neural basis.

TRIAL REGISTRATION: Clinical trial registration no. ChiCTR 2200063274.

PMID:42321075 | DOI:10.1016/j.inpsyc.2026.100233

Neuroimage. 2026 Jun 19:122071. doi: 10.1016/j.neuroimage.2026.122071. Online ahead of print.

ABSTRACT

Presbycusis, a bilateral, symmetric, and progressive neural hearing loss, is closely associated with cognitive decline, yet its underlying white-matter (WM) network mechanisms remain unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), this study investigated WM functional network reorganization and its relationship with cognitive performance in 81 patients with presbycusis and 77 healthy controls. Patients exhibited significant WM functional connectivity (FC) alterations, characterized by decreased intra-network functional integrity within the left corticospinal tract (CST) and reduced inter-network FC between the body of the corpus callosum (BCC) and the bilateral posterior limbs of the internal capsule (PLIC) as well as the left medial lemniscus (ML). These disrupted FC patterns were significantly correlated with global cognitive impairment, attentional deficits, and poorer auditory verbal memory. Furthermore, a support vector machine (SVM) classifier with a radial basis function (RBF) kernel, implemented with a nested feature selection and repeated 5-fold cross-validation scheme, achieved stable discriminative performance (accuracy = 60.65%, AUC = 0.64, precision = 61.70%, sensitivity = 62.62%). These findings indicate that reorganization of WM functional networks is associated with cognitive impairment in presbycusis, suggesting that WM FC metrics may serve as potential imaging indicators to assist in the clinical assessment of cognitive risk, offering preliminary network-level evidence consistent with the auditory deprivation hypothesis.

PMID:42320610 | DOI:10.1016/j.neuroimage.2026.122071

BMC Psychiatry. 2026 Jun 19. doi: 10.1186/s12888-026-08307-3. Online ahead of print.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) has been associated with large-scale functional dysconnectivity, yet it remains unclear whether these abnormalities differ as a function of anatomical distance. We investigated distance-related functional connectivity strength (FCS) alterations in first-episode, drug-naïve MDD and examined whether their spatial distribution corresponds to atlas-based neurotransmitter receptors/transporters profiles.

METHODS: Resting-state functional MRI data were acquired from 191 patients with first-episode, drug-naïve MDD and 130 healthy controls. Whole-brain global, long-range, and short-range FCS were quantified voxel-wise. Distance-constrained seed-based connectivity analyses were performed to characterize the circuit-level contributions underlying abnormal FCS findings. To provide a molecular context, regional maps of FCS abnormalities were compared with neurotransmitter receptors/transporters distributions derived from a publicly available positron emission tomography atlas.

RESULTS: Compared with healthy controls, patients with MDD showed reduced long-range FCS in the left orbital superior frontal gyrus and left medial superior frontal gyrus, together with increased short-range FCS in the right inferior parietal lobule. Seed-based analyses indicated that reduced long-range FCS was mainly related to weaker long-range connectivity between the left orbital superior frontal gyrus and right inferior temporal gyrus, and between the left medial superior frontal gyrus and right hippocampus. Increased short-range FCS in the right inferior parietal lobule was associated with stronger short-range connectivity with the right inferior frontal operculum, right superior temporal gyrus, and left paracentral lobule. The spatial pattern of FCS abnormalities showed significant correspondence with atlas-based neurotransmitter receptors/transporters distributions; short-range abnormalities spatially covaried with an atlas-derived regional excitation-inhibition balance.

CONCLUSIONS: First-episode, drug-naïve MDD is characterized by a distance-related pattern of reduced long-range prefrontal connectivity and increased short-range parietal connectivity. Atlas-based molecular mapping provides a biologically informed, population-level spatial context for these macroscale functional abnormalities.

PMID:42321709 | DOI:10.1186/s12888-026-08307-3

Brain Imaging Behav. 2026 Jun 19;20(4):100. doi: 10.1007/s11682-026-01164-4.

ABSTRACT

Post-stroke cognitive impairment (PSCI) significantly impacts patients' quality of life following a stroke. Its effects on white matter functional networks remain unclear. This study used resting-state functional MRI to examine alterations in white matter functional connectivity and spontaneous activity in this condition. Resting-state functional MRI data were acquired from PSCI (n = 21), non-PSCI (PSNCI, n = 16), and healthy subjects (HSs, n = 29). A clustering analysis was employed to identify white matter functional networks. Functional connectivity and the amplitude of low-frequency fluctuation within these networks were compared across groups. Correlation analyses assessed their relationships with neuropsychological scores. Sixteen stable white matter networks were identified. Both patient groups showed reduced functional connectivity between the inferior longitudinal fasciculus and anterior cingulum compared to HSs. PSCI patients also exhibited decreased functional connectivity between the anterior and posterior cingulum compared to HSs. Furthermore, the amplitude of low-frequency fluctuation in the posterior cingulum was lower in PSCI group than in PSNCI group. These altered metrics showed correlations with neuropsychological performance across multiple cognitive domains. This study identified alterations in functional connectivity and spontaneous activity within specific WM networks in PSCI, which were associated with cognitive performance. These findings suggest that white matter functional abnormalities may be involved in the neural mechanisms underlying PSCI and could inform future research on early identification.

PMID:42319649 | DOI:10.1007/s11682-026-01164-4

Neuroimage Rep. 2026 Jun 10;6(3):100372. doi: 10.1016/j.ynirp.2026.100372. eCollection 2026 Sep.

ABSTRACT

Fatigue is common in patients with chronic pain, but the neural underpinning of this symptom is still poorly understood. In this study, we aimed to investigate resting state connectivity correlates of pain and fatigue in patients with chronic pain. Twenty-four women with chronic pain, and 22 age-matched healthy controls underwent resting state functional magnetic resonance imaging (fMRI), performed a 20-min fatiguing attention task, and underwent an additional resting state fMRI examination. Patients with chronic pain reported a higher degree of both fatigue (p < 0.001) and pain (p < 0.001) than healthy controls. Significant group differences in connectivity to the lateral visual network, the salience network, the auditory network, the executive control network, and especially in regions within the default mode network were detected before the task. After the task, these differences were no longer statistically detectable, and only differences in connectivity between the basal ganglia network and the prefrontal areas between groups were observed. While differences in functional connectivity related to pain were present before performance of the task, only differences related to fatigue were found after the task. This finding indicates that processing of fatigue might overshadow processing of pain after performance of a fatiguing attention task in patients with chronic pain.

PMID:42318321 | PMC:PMC13273879 | DOI:10.1016/j.ynirp.2026.100372

Neuroimage Rep. 2026 Jun 11;6(3):100370. doi: 10.1016/j.ynirp.2026.100370. eCollection 2026 Sep.

ABSTRACT

Adjuvant therapies in aphasia rehabilitation may help reduce the cost and clinical resources required for intensive speech-language interventions. We conducted a proof-of-principle pilot study to evaluate whether transcranial direct current stimulation (tDCS) paired with a shortened course of phonomotor treatment (sPMT)-targeting sounds and nonwords but not real words-enhances phonological production in chronic post-stroke aphasia, and to examine the neural mechanisms underlying this approach. Using a double-blind, parallel-group design, participants received 30 h of sPMT combined with 1 mA tDCS (anode/cathode over left/right inferior frontal gyrus) delivered at the start of each intervention session. Here, we report data from six older male participants matched on aphasia severity (active: n = 3; sham: n = 3). Phonological production and confrontation naming were assessed at baseline, immediately post-intervention, and at 3-month follow-up. Structural and resting-state functional MRI (rs-fMRI) were acquired at baseline and post-intervention. Repeated-measures ANOVA revealed a significant group-by-time interaction for phonological production, with the active tDCS + sPMT group showing gains from baseline to post-intervention that were maintained at 3 months, whereas the sham group showed no significant improvement. Confrontation naming showed no significant effects of time or group. MRI-based estimates of current density (J) indicated that J varied systematically with lesion volume and inter-electrode distance, underscoring the importance of individualized electrode placement. rs-fMRI analyses demonstrated significant group-by-time interactions, with greater connectivity increases in the active versus sham group across domain-specific and domain-general networks. These preliminary findings suggest that active tDCS may enhance the effects of sPMT on phonological production and provide mechanistic support for individualized, network-informed neuromodulatory approaches in post-stroke aphasia rehabilitation.

PMID:42318320 | PMC:PMC13273797 | DOI:10.1016/j.ynirp.2026.100370

Neuropsychiatr Dis Treat. 2026 Jun 13;22:601136. doi: 10.2147/NDT.S601136. eCollection 2026.

ABSTRACT

PURPOSE: Alzheimer's disease (AD) is increasingly prevalent, yet how acupuncture modulates cognitive brain networks remains unclear. We used resting-state fMRI (rs-fMRI) to examine whether acupuncture prescription regulates effective connectivity within the frontoparietal network (FPN) in AD.

PATIENTS AND METHODS: Sixty AD patients were randomized to donepezil alone (drug group) or acupuncture plus donepezil (acupuncture group) for 6 weeks (n=30/group). Seven healthy controls were scanned once. Global cognition was assessed with MoCA-B. Independent component analysis identified the FPN, and Granger causality analysis quantified directed effective connectivity before and after treatment.

RESULTS: Both interventions improved MoCA-B (P<0.05), with larger gains in the acupuncture group (P<0.05). Relative to controls, AD showed FPN disruption with compensatory reorganization. Decreased connectivity was observed from the left middle temporal gyrus (MTG) to the right inferior parietal lobule (IPL), and from the left median cingulate/paracingulate gyri (P<0.05). Increased connectivity emerged from the right IPL and left cingulate/paracingulate to the left MTG, and from the right IPL to the left medial frontal gyrus (orbital part) (P<0.05). The right IPL and left MTG were core FPN nodes. Post-treatment, the drug group showed reduced right IPL→left orbital medial frontal connectivity, whereas the acupuncture group showed reduced right IPL→left MTG connectivity (P<0.05). Between-group comparisons indicated acupuncture-specific modulation of right insula→left MTG and left precuneus→left MTG connectivity (P<0.05).

CONCLUSION: Acupuncture combined with donepezil provides superior cognitive benefits and selectively reshapes directed FPN interactions, supporting a network-level mechanism involving frontal-parietal-temporal integration.

PMID:42318047 | PMC:PMC13274761 | DOI:10.2147/NDT.S601136