Most recent paper

J Magn Reson Imaging. 2026 Oct 9. doi: 10.1002/jmri.70584. Online ahead of print.

ABSTRACT

BACKGROUND: Mounting evidence revealed that the weakened coupling between CSF flow and global brain activity (gBOLD-CSF coupling) is associated with Alzheimer's Disease (AD) pathology and cognitive impairments. However, the mechanisms underlying this weakened coupling remain unclear.

PURPOSE: To investigate the region-specific effects of cerebrovascular reactivity (CVR) on the gBOLD-CSF coupling.

STUDY TYPE: Retrospective.

POPULATION: One hundred ninety-eight cognitively normal controls (70.2 ± 8.7 years; 128 female, 70 male), 115 mild cognitive impairment patients (73.1 ± 7.1 years; 50 female, 65 male), and 24 dementia patients (75 ± 9.3 years; 14 female, 10 male) from ADNI.

FIELD STRENGTH/SEQUENCE: 3 T gradient-echo blood-oxygenation-level-dependent (BOLD).

ASSESSMENT: gBOLD-CSF coupling and CVR maps were respectively derived from resting-state fMRI. The former reflects the temporal coordination between CSF dynamics and global neurovascular fluctuations, while the latter quantifies the capacity of vessels to dilate or constrict. AD-related clinical scales including Aβ-PET, tau-PET, and cognitive assessments were also involved.

STATISTICAL TESTS: Linear regression models were employed to examine the association of gBOLD-CSF coupling with AD-related clinical scales and with CVR of major cerebral arteries. Mediation analyses were employed to investigate the potential pathways linking these metrics. p < 0.05 was considered significant.

RESULTS: gBOLD-CSF coupling was significantly associated with cognitive assessments (CDR Global: β = 0.366; ADAS-Cog: β = 10.613), accumulation of cortical summary Aβ (β = 37.937) and tau in Braak stage ROIs (Braak I-II: β = 0.444; Braak III-IV: β = 0.565; Braak V-VI: β = 0.474). Analysis also revealed the regional differences in the association of gBOLD-CSF coupling with CVR. CVR, especially in posterior cerebral arteries (PCA) region, was significantly associated with gBOLD-CSF coupling (β = -0.313). The gBOLD-CSF coupling, both directly and through its effect on the accumulation of Aβ and tau, mediated the association between CVR and cognition.

DATA CONCLUSION: Data revealed a significant CVR-coupling association in the PCA region and potential pathways linking CVR, gBOLD-CSF coupling, AD pathology, and cognition, providing deeper insights into weakened gBOLD-CSF coupling in AD.

EVIDENCE LEVEL: 3.

TECHNICAL EFFICACY: Stage 2.

PMID:42852594 | DOI:10.1002/jmri.70584

J Magn Reson Imaging. 2026 Oct 9. doi: 10.1002/jmri.70583. Online ahead of print.

ABSTRACT

BACKGROUND: Zero-echo-time (ZTE) imaging detects signals from tissues with extremely short T 2 relaxation times by minimizing echo time. Dead-time gaps and flexible temporal sampling remain challenges for dynamic applications such as functional MRI (fMRI).

PURPOSE: To propose and evaluate ZTE-STAR, a dynamic ZTE framework combining paired-spoke spiral phyllotaxis sampling, algebraic dead-time infilling, and temporal total variation (TTV) reconstruction.

STUDY TYPE: Prospective.

SUBJECTS/PHANTOM: A numerical phantom and eight C57BL/6J mice (one for image quality assessment; seven for resting-state fMRI).

FIELDSTRENGTH/SEQUENCE: 9.4 T; ZTE with a modified Spiral Phyllotaxis Golden Angle trajectory.

ASSESSMENT: Reconstruction quality was assessed using peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), and temporal response using the 90%-10% fall time. In vivo assessment included temporal signal-to-noise ratio (tSNR), rigid-body motion, and exploratory group independent component analysis (ICA).

STATISTICAL TEST: Descriptive statistics were used for PSNR, SSIM, motion, and tSNR. ICA was exploratory, with no inferential statistical testing.

RESULTS: In trajectory-reconstruction ablation at comparable spoke counts, paired spiral phyllotaxis with TTV yielded PSNR 32.12 dB versus 29.75 dB for conventional radial sampling with TTV. ZTE-STAR at 864 spokes yielded PSNR 30.90 dB, SSIM 0.903, and 90%-10% fall time 1.8-2.1 s; at 2880 versus 2948 spokes, fall times were 5.0-5.2 versus 4.9 s. With realistic measurement noise, ZTE-STAR at 864 spokes yielded PSNR 30.12 ± 0.01 dB and SSIM 0.838 ± 0.001 versus 24.79 ± 0.01 dB and 0.604 ± 0.001 for conventional radial sampling at 2948 spokes. Whole-brain tSNR ranged from 26.6 to 30.1. Resting-state ICA yielded an exploratory default mode network-like component.

DATA CONCLUSION: ZTE-STAR enabled shorter retrospective bins while maintaining reconstruction quality at lower spoke counts and supported exploratory resting-state ZTE-fMRI in mice.

TECHNICAL EFFICACY: Stage 1.

EVIDENCE LEVEL: 4.

PMID:42852582 | DOI:10.1002/jmri.70583

Front Pain Res (Lausanne). 2026 Sep 24;7:1794217. doi: 10.3389/fpain.2026.1794217. eCollection 2026.

ABSTRACT

BACKGROUND: Central sensitization involves maladaptive plasticity in ascending nociceptive and descending modulatory pathways. This pilot study was designed with three integrated aims: (1) to characterize baseline thalamocortical and descending control network abnormalities in chronic shoulder pain (CSP) relative to healthy controls; (2) to examine whether these network features change following a standardized course of peripheral myofascial stimulation (PMS); and (3) to explore potential mechanistic pathways linking peripheral intervention to central network reconfiguration. While PMS has been reported anecdotally as effective for musculoskeletal pain, preliminary empirical evidence from randomized controlled trials remains limited, and its central neural mechanisms remain unclear.

METHODS: Twelve patients with CSP underwent longitudinal resting-state fMRI before and after a 10-session PMS intervention. A matched healthy control cohort (n = 18) provided cross-sectional baseline normative data for disease characterization only; no longitudinal data were collected from controls. High-resolution parcellation (HCP-MMP1.0) was used to quantify connectivity in a priori hypothesized networks. Statistical analysis employed a tiered approach combining whole-brain Network-Based Statistics (NBS) and hypothesis-driven Region of Interest (ROI) analyses, rigorously controlled for site effects using ComBat harmonization.

RESULTS: At baseline, patients exhibited trend-level reduced thalamo-somatosensory coupling (Cohen's d = 0.72, p = 0.054) compared to controls, which correlated with disease burden. Following treatment, we observed: (1) a downregulation of ACC-brainstem connectivity at the ROI level (Pre 0.017 ± 0.209, Post -0.149 ± 0.211, Δ = -0.166; Wilcoxon p = 0.012, d = -0.82), which did not survive Bonferroni correction across the eight a priori edges (corrected p = 0.098); and (2) patient-specific change in thalamo-somatosensory connectivity, which was associated with change in present pain intensity (ΔPPI, ρ = -0.73). Control analyses in visual and limbic networks were null; this is compatible with, but does not confirm, anatomical restriction.

CONCLUSIONS: PMS is associated with the reconfiguration of specific bottom-up gating and top-down control circuits in CSP. While the absence of a sham control and the small sample size (n = 12) limit causal inference and generalizability, the large effect sizes and high anatomical specificity suggest these are preliminary biological signals worthy of further investigation. These preliminary findings provide mechanistic targets for future adequately powered randomized controlled trials.

PMID:42851776 | PMC:PMC13646167 | DOI:10.3389/fpain.2026.1794217

Front Endocrinol (Lausanne). 2026 Sep 24;17:1928717. doi: 10.3389/fendo.2026.1928717. eCollection 2026.

ABSTRACT

INTRODUCTION: Patients with diabetes may develop cognitive dysfunction, particularly at advanced stages of the disease, manifested by impairments in learning, memory, language, and judgment. Previous studies have reported abnormal brain functional alterations in patients with diabetic retinopathy (DR), which may be associated with cognitive impairment in diabetes; however, the molecular correlates of these brain alterations remain poorly understood.

METHODS: In this study, we performed a coordinate-based neuroimaging meta-analysis to identify convergent resting-state brain functional alterations in patients with DR. By integrating the meta-analytic imaging phenotype with gene-expression data from the Allen Human Brain Atlas, we further conducted spatial transcriptomic -neuroimaging analyses to identify genes whose normative expression patterns were spatially associated with DR-related brain functional alterations.

RESULTS: The meta-analysis revealed relatively increased resting-state functional measures in the left cerebellum and corpus callosum, whereas relatively decreased measures were observed in the left calcarine fissure, left middle occipital gyrus, two clusters in the right postcentral gyrus, right anterior cingulate cortex, and right middle temporal gyrus. Functional decoding analyses indicated that these regions were associated with cognitive domains involving language, learning, and cognition. In addition, the regional neuroimaging phenotype was spatially associated with the normative expression patterns of 1,101 genes. Functional enrichment analyses indicated that these genes were enriched in processes related to learning, memory, and cognition, as well as biological processes involving metal ion regulation and cell adhesion. Cell- and tissue-specific enrichment analyses further suggested preferential expression patterns involving retinal and cortical neuronal populations.

DISCUSSION: Collectively, these findings demonstrate convergent resting-state brain functional alterations in patients with DR and reveal their spatial correspondence with normative gene-expression patterns, providing potential insights into the molecular and cellular context of cognitive-related brain alterations associated with DR.

SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/, identifier CRD420261292056.

PMID:42851427 | PMC:PMC13645568 | DOI:10.3389/fendo.2026.1928717

Cortex. 2026 Sep 28;205:287-298. doi: 10.1016/j.cortex.2026.09.016. Online ahead of print.

ABSTRACT

Spatial neglect-a disorder characterized by impaired exploration of contralesional space-has only recently been reported following lesions to dorsomedial regions of the right hemisphere. Consequently, the mechanisms underlying the occurrence of neglect in this context remain largely unexplored. Here, we investigated whether alterations in functional connectivity could account for this phenomenon by longitudinally assessing resting-state fMRI in a patient before and after tumor resection. A 71-year-old male underwent resection of an oligodendroglioma involving the right superior frontal gyrus and cingulum. Neuropsychological assessment and resting-state fMRI were acquired before and after surgery. Peripersonal and personal neglect were assessed with two different cancellation tests and the Comb and Razor Test (CRT). System Segregation (SyS), i.e., the balance of within and between network functional connectivity, was computed at both whole-brain and network-specific levels and compared with 20 age-matched healthy controls using Crawford's modified t-test. While no sign of neglect was observed preoperatively, the patient exhibited both peripersonal and personal neglect after surgery. Compared to controls, postoperative data revealed a significant reduction in whole-brain SyS (p < .001). At the network level, the ventral attention network (VAN) showed preserved segregation preoperatively but a marked postoperative decrease (p < .001). These findings show, for the first time, that the clinical manifestation of neglect after right dorsomedial regions may be explained by lesion-induced alterations in large-scale functional connectivity. In particular, reduced VAN segregation may reflect impaired functional differentiation underlying deficits in spatial attention, thereby shedding light on the mechanisms underlying dorsomedial lesions neglect presentation.

PMID:42849102 | DOI:10.1016/j.cortex.2026.09.016

Neuroradiology. 2026 Oct 8. doi: 10.1007/s00234-026-04202-6. Online ahead of print.

ABSTRACT

PURPOSE: To study cerebellar cerebrovascular reactivity (CVR) derived from resting-state (RS) blood oxygen level-dependent (BOLD) as a potential imaging biomarker for crossed cerebellar diaschisis (CCD).

METHODS: Thirty-nine patients with symptomatic unilateral cerebrovascular occlusion and eighteen age-matched healthy subjects underwent a simultaneous PET/MR scan. CCD was diagnosed as a contralateral cerebellar metabolic reduction present on 18F-FDG PET semi-quantitatively. RS BOLD-CVR maps were derived by extracting signals within specific frequency bands of RS BOLD. The cerebellar asymmetry index (CAI) calculated from RS BOLD-CVR and 18F-FDG PET data were compared using receiver operating characteristic and Bland-Altman analysis. Neurological function was determined with NIHSS and mRS.

RESULTS: In our cohort, CCD was diagnosed in 21 of 39 (53.8%) patients on 18F-FDG PET. CCD+ patients exhibited larger infarct volume, more severe supratentorial CVR impairment, and worse functional status than CCD- patients at admission and 3.5 years follow-up. The area under the curve for RS BOLD-CVR CAI was 0.862 (95% confidence interval: 0.747-0.978) with a cutoff value of 8.2%, achieving a sensitivity of 81.0% and a specificity of 83.3% to detect CCD. The Bland-Altman analysis showed no significant proportional bias between PET CAI and CVR CAI (P = 0.848). CVR CAI was correlated with NIHSS (ρ = 0.352, p = 0.033) and mRS (ρ = 0.360, p = 0.029) at admission after adjusted for age and infarct volume.

CONCLUSION: RS BOLD-CVR demonstrates good sensitivity and specificity to detect diaschisis-related cerebellar cerebrovascular reactivity in patients with symptomatic unilateral cerebrovascular occlusion. Furthermore, participants with cerebellar CVR impairment and metabolic reduction tended to have poorer neurological function.

PMID:42848066 | DOI:10.1007/s00234-026-04202-6

Front Med (Lausanne). 2026 Sep 23;13:1915832. doi: 10.3389/fmed.2026.1915832. eCollection 2026.

ABSTRACT

BACKGROUND: Primary dysmenorrhea (PD) is one of the most common gynecological disorders in women of reproductive age and significantly impairs quality of life. Epidemiological data indicate that the cold congestion and blood stasis pattern accounts for a large proportion of PD cases. Tuina, a traditional Chinese external therapy, has unique advantages in pain management; however, its clinical efficacy and central mechanisms for PD remain unclear.

OBJECTIVE: This study aims to conduct an assessor-blind, parallel-group randomized controlled superiority trial, integrating functional magnetic resonance imaging (fMRI), to evaluate the clinical efficacy, safety, and central brain network modulation of Tuina therapy for primary dysmenorrhea with the cold congestion and blood stasis pattern.

METHODS: This study employed a randomized controlled trial design. A total of 54 patients who met the diagnostic criteria were recruited and randomly assigned in a 1:1 ratio to either the treatment or control group. An additional 15 healthy women were included as the healthy group. Participants in the treatment group received standardized manipulation over two consecutive menstrual cycles. For each cycle, treatment began 7 days before menstruation and was administered once daily for 7 consecutive days. Participants in the control group received conventional oral ibuprofen, taken as needed for pain relief. The primary outcome was the change in the Visual Analog Scale score. Secondary outcomes included the COX Menstrual Symptom Scale, Traditional Chinese Medicine pattern score, sleep index, and psychological assessments. All outcomes were evaluated at three time points: baseline, after the first treatment cycle, and after the second treatment cycle. All participants underwent two fMRI sessions-both resting-state and task-state fMRI scans-during days 1-3 of their menstrual cycle: once before enrollment and once after the treatment period. All statistical analyses followed the intention-to-treat principle.

DISCUSSION: This study aims to provide high-level clinical evidence on pain relief, symptom improvement, and brain functional network regulation for the treatment of cold congestion stasis type dysmenorrhea with Tuina therapy, using a randomized controlled trial design combined with functional magnetic resonance imaging.

CLINICAL TRIAL REGISTRATION: https://itmctr.ccebtcm.org.cn, International Traditional Medicine Clinical Trial Registry ITMCTR2026001387.

PMID:42846111 | PMC:PMC13642282 | DOI:10.3389/fmed.2026.1915832

Front Netw Physiol. 2026 Sep 23;6:1881914. doi: 10.3389/fnetp.2026.1881914. eCollection 2026.

ABSTRACT

Tourette syndrome (TS) is a neurodevelopmental disorder characterized by motor and vocal tics that are modulated by internal physiological state and interoceptive state, including premonitory urges and associated changes in short-timescale parasympathetic variability. Since tic expression is thought to be linked to fluctuations in autonomic state, understanding how brain networks integrate physiological signals may provide insight into the neural mechanisms contributing to tic generation and suppression. In recent years, there has been increasing interest in understanding interactions between the brain and autonomic physiology, given their shared central role in shaping cognition, emotion, and behavior. Methodological advances have enabled the study of brain-heart coupling, yet much of this work has focused on static or region-based approaches, limiting insight into how autonomic fluctuations are integrated within dynamic, large-scale brain networks. Here, we examined time-resolved brain-heart interactions using densely sampled resting-state fMRI data and concurrent pulse oximetry in two sibling pairs (n = 4) discordant for Tourette syndrome (TS). Using two targeted network analyses organized around interoceptive/urge awareness and inhibitory control/action regulation processes, we quantified coupling between pulse-derived RMSSD and between-network functional connectivity using sliding-window analyses and Bayesian linear mixed-effects models. We observed marked individual variability in functional network organization and autonomic measures. The most consistent observation was a pattern of opposing coupling directions between individuals with and without TS: those with TS showed positive associations between pulse-derived RMSSD with connectivity between internal-state and attentional networks, as well as among action-related systems, while unaffected siblings showed positive associations along broader integrative pathways linking internal-state and action-control networks. These preliminary findings generate hypotheses regarding individualized patterns of brain-heart coupling in TS and illustrate the potential value of integrating individualized network mapping with time-resolved physiological measures in clinical populations.

PMID:42845759 | PMC:PMC13642012 | DOI:10.3389/fnetp.2026.1881914

bioRxiv [Preprint]. 2026 Aug 13:2026.08.07.743542. doi: 10.64898/2026.08.07.743542.

ABSTRACT

INTRODUCTION: Understanding mid-term test-retest reliability and within-subject variability is important for interpreting changes observed in longitudinal and intervention studies. The reliability of resting-state functional magnetic resonance imaging (rs-fMRI) is known to vary across measures and brain regions. However, how reliability differs across functional networks and connectivity- and amplitude-based measures, and whether multi-echo acquisition and processing modify these patterns, remain incompletely characterized.

METHODS: Twenty-two healthy volunteers underwent two rs-fMRI sessions 15.7 ± 4.0 days apart on a Compact 3T scanner. Multi-echo, middle-echo, and independently acquired single-echo datasets were compared, with multi-echo independent component analysis additionally evaluated as a denoising approach. Functional connectivity (FC) and three amplitude-based measures were evaluated using the Schaefer 400 parcellation. Reliability was systematically assessed using intraclass correlation coefficient (ICC), within-subject standard deviation (wSD), and systematic bias at edge or regional, and network levels.

RESULTS: Acquisition-dependent differences in reliability were generally modest. Multi-echo acquisition and processing increased functional connectivity strength and the magnitude of amplitude-based measures and improved inferior cortical coverage, but these enhancements did not consistently translate into substantially higher ICC or lower wSD. In contrast, reliability showed clear network-dependent differences. FC reliability varied markedly across network pairs and was not explained by connectivity strength alone; pairs involving the default mode and control networks generally showed more favorable profiles than several somatomotor and visual network pairs. Fractional amplitude of low-frequency fluctuations (fALFF) also showed network-dependent reliability, with the most favorable regional reproducibility observed in the default mode and control networks and lower reproducibility in the somatomotor and visual networks.

CONCLUSION: These findings provide practical mid-term reliability benchmarks for rs-fMRI on a Compact 3T scanner and show that measurement stability varies more clearly across measures and functional networks than across acquisition approaches.

PMID:42845319 | PMC:PMC13640555 | DOI:10.64898/2026.08.07.743542

bioRxiv [Preprint]. 2026 Aug 14:2026.08.09.743708. doi: 10.64898/2026.08.09.743708.

ABSTRACT

Two decades of functional connectivity research have established schizophrenia as a disorder of distributed dysconnectivity, with a robust thalamocortical signature: reduced prefrontal and increased sensory coupling. A fundamental issue is that functional connectivity is undirected, operates at a single slow timescale, and cannot reveal causal direction. Moreover, the mismatch between BOLD sampling speed and neural dynamics can hide edges, fabricate spurious ones, and reverse the apparent orientation of causal relationships. To overcome these limitations, we introduce a general framework for estimating directed causal graphs from fMRI that explicitly accounts for temporal undersampling. We apply RnR, a causal discovery method built on the rate-agnostic RASL framework, to resting-state fMRI from the multi-site FBIRN cohort. Rather than returning a single directed graph, RnR recovers an equivalence class of directed graphs consistent with the observed data, each annotated with the sampling rate that would produce it and classifies each estimated orientation by its stability across inferred rates. This provides a principled basis for distinguishing directed interpretations that are safe to trust from those that are timescale-contingent. Benchmarking against five single-timescale estimators on schizophrenia data, RnR recovered substantially more group-differentiating directed edges, reproducing the field's most replicated finding in directed form: a sensory-to-visual hyperconnectivity hub oriented from the post-central gyrus component to primary visual cortex. Through simulation, we show that coarse spatial resolution has shielded single-timescale methods from the full effects of undersampling, whereas finer parcellations will require explicit undersampling modeling. This work reframes fMRI effective connectivity estimation by treating undersampling as a fundamental property of the measurement, enabling directed interpretations that are grounded in the data-generating process.

PMID:42845316 | PMC:PMC13640626 | DOI:10.64898/2026.08.09.743708

Neuropsychologia. 2026 Oct 7:109601. doi: 10.1016/j.neuropsychologia.2026.109601. Online ahead of print.

ABSTRACT

Attention-Deficit/Hyperactivity Disorder (ADHD) has been associated with altered integration across large-scale brain networks. Temporal fluctuations in functional organization and differences between acquisition centers complicate classification based on resting-state functional magnetic resonance imaging (rs-fMRI). This study used BrainNetCNN as the reference architecture to examine how region-of-interest (ROI) dimensionality, connectivity representation, network design, window configuration and acquisition site influence ADHD discrimination. The sample included 465 participants from four ADHD-200 centers: New York University (NYU; n = 177), Peking University (Peking; n=183), NeuroIMAGE (n=39) and Oregon Health & Science University (OHSU; n=66). Functional connectivity was derived from regional blood-oxygen-level-dependent (BOLD) time series using prespecified 12, 18, 39 and 116-ROI panels from the Automated Anatomical Labeling atlas (AAL116). The reference window was 120 s with an approximately 12-s step. Within each center, classification was assessed through participant-level stratified 10-fold cross-validation repeated five times, with area under the receiver operating characteristic curve (AUC) as the primary metric. BrainNetCNN was configured using NYU data and then kept fixed for evaluation at the remaining centers. Across site-by-ROI combinations, AUC ranged from 50.1% to 64.5%. The 12-ROI configuration reached 63.6% in both NYU and Peking, while the strongest panel differed across centers. Comparisons involving static connectivity, long short-term memory (LSTM), gated recurrent unit (GRU), DeepSets, logistic regression and alternative window settings revealed no consistent advantage. Leave-one-site-out analyses yielded AUCs from 44.4% to 63.9%, with 14 of 16 pointwise 95% confidence intervals including 0.50. Overall, the models showed modest site-dependent discrimination and limited cross-site transportability.

PMID:42843755 | DOI:10.1016/j.neuropsychologia.2026.109601

Neuroimage. 2026 Oct 7:122279. doi: 10.1016/j.neuroimage.2026.122279. Online ahead of print.

ABSTRACT

Allocentric spatial navigation declines with age, but the underlying neural mechanisms remain unclear. The posterior cingulate/retrosplenial cortex (PCC/RSC) is an integrative navigation hub and is also among the earliest regions affected by aging. We investigated whether the PCC/RSC is organized along continuous functional connectivity gradients, and how these gradients relate to age and spatial navigation ability. Using an adult-lifespan sample from the Southwest University Adult Lifespan Dataset (SALD; n = 479; age range = 19-80 years), we characterized functional connectivity gradients within the PCC/RSC complex and examined their associations with age. Two dominant functional connectivity gradients (G1 and G2) were identified within the PCC/RSC complex. The ranges of both gradients decreased significantly with age. In an independent navigation sample comprising 19 younger and 19 older adults, participants underwent resting-state fMRI and task-based fMRI while performing an allocentric object-location memory task. We examined whether age-related gradient compression was also evident in this independent navigation sample and whether gradient range was associated with navigation performance. Older adults showed smaller task-state left G1, task-state right G2, and resting-state right G2 ranges, with the largest reduction in task-state left G1 (approximately 65%). Among older adults, greater task-state left G1 range was associated with lower drop error. These findings provide novel evidence that age-related compression of PCC/RSC functional organization is behaviorally relevant to allocentric navigation decline.

PMID:42843612 | DOI:10.1016/j.neuroimage.2026.122279

Biomed Phys Eng Express. 2026 Oct 7. doi: 10.1088/2057-1976/aeb128. Online ahead of print.

ABSTRACT

OBJECTIVE: Clinical autism spectrum disorder (ASD) relies on subjective scales and neuroimaging, with traditional approaches suffering from high subjectivity and insufficient feature extraction, increasing misdiagnoses risk.

APPROACH: To improve the diagnostic accuracy, we propose a multimodal ASD prediction network (APN) that integrates resting-state functional magnetic resonance imaging (rs-fMRI) with non-imaging data. Algorithmically, we first introduce a novel cumulative distribution divergence score (CDDS) feature selection method based on the multi-atlas functional connectivity, which quantifies statistical distributional differences between positive and negative samples, effectively addressing the limitations of the traditional F-score in overlapping or weakly discriminative features. Building upon this, we adapt existing deep learning paradigms to construct a deep neural architecture (VAEA), combining a variational autoencoder (VAE), a denoising autoencoder (DAE), and a multilayer perceptron (MLP). The combination of these modules is non-trivial: the novel CDDS first purifies the high-dimensional feature space, enabling the VAEA to learn robust latent probabilistic representations via unsupervised pre-training without suffering from the curse of dimensionality. This is followed by the supervised fine-tuning to optimize parameters. We further incorporate demographic factors including age, full-scale intelligence quotient (FIQ), and gender via a late-fusion strategy to prevent them from being overshadowed by imaging features, thereby enhancing the discriminability. Functional connectivity features from three atlases including AAL, CC400, and Dosenbach160 are weighted and integrated to achieve the effective multi-source fusion.

MAIN RESULTS: We conduct 10-fold cross-validations on the Autism Brain Imaging Data Exchange (ABIDE) dataset, and the proposed APN achieves 81.63% accuracy, 81.89% sensitivity and 81.46% specificity, significantly outperforming state-of-the-art methods. Interpretability analysis identifies hippocampus, amygdala, and cingulate gyrus as strongly ASD-associated regions, offering neural mechanistic insights.

SIGNIFICANCE: This study provides an efficient, objective, and interpretable multimodal deep learning framework for ASD assisted diagnosis, with substantial clinical application and neuroscience value.

PMID:42843381 | DOI:10.1088/2057-1976/aeb128

Schizophr Bull. 2026 Aug 20;52(5):sbag138. doi: 10.1093/schbul/sbag138.

ABSTRACT

BACKGROUND AND HYPOTHESIS: Air pollution exposure has been associated with altered neurodevelopment and increased risk of schizophrenia. Individuals at high genetic risk may be more vulnerable to these effects. Here, we examined how air pollution relates to brain structure and functional connectivity in adolescents, and we tested for the first time whether genetic risk for schizophrenia exacerbates these effects.

STUDY DESIGN: We included n = 1580 individuals with information on genetic risk for schizophrenia, air pollution at 9-10 years, and structural and resting-state functional magnetic resonance imaging at 13-14 years from the Adolescent Brain Cognitive Development Study. We used linear mixed-effects models to examine the association between air pollution (ambient particulate matter (PM₂.5), nitrogen dioxide (NO₂), and ozone (O₃)) and brain measures, and test whether genetic risk for schizophrenia moderated these effects.

STUDY RESULTS: Higher PM₂.5 was associated with smaller right frontal pole surface area (p-FDR = 0.039). Individuals with low polygenic risk scores for schizophrenia (PRS-SCZ) and medium PM₂.5 had smaller left caudate volumes compared with those with medium PRS-SCZ and medium PM₂.5 (p-FDR = 0.019). In individuals with low PRS-SCZ, higher PM₂.5 was associated with larger left (p-FDR = 0.019) and right (p-FDR = 0.018) caudate volumes. Higher NO₂ was associated with stronger negative functional connectivity between default mode and dorsal attention networks (p-FDR = 0.034) and weaker positive functional connectivity between dorsal attention and frontoparietal networks (p-FDR = 0.034).

CONCLUSIONS: Air pollution and its interplay with genetic risk for schizophrenia are associated with structural and functional changes in areas implicated in schizophrenia pathophysiology. This underscores the potential of lowering air pollution during critical periods of neurodevelopment and informing proactive environmental policies.

PMID:42842776 | DOI:10.1093/schbul/sbag138

Imaging Neurosci (Camb). 2026 Oct 5;4:IMAG.a.1314. doi: 10.1162/IMAG.a.1314. eCollection 2026.

ABSTRACT

Recent neuromodulation studies suggest that theta burst stimulation (TBS) applied to the dorsolateral prefrontal cortex (dlPFC) can influence neural circuits involved in cognitive control and emotion-related processing, with relevance for psychiatric disorders. However, large-scale datasets characterizing variability, reliability, and multimodal neural responses to TBS remain limited. To address this gap, we established the Philadelphia Theta Burst Project, a dataset of 100 healthy participants who completed 4 fMRI sessions following cumulatively increasing doses of intermittent or continuous TBS, with participants randomized to one protocol or the other. Each session includes multiband, multi-echo resting-state (16 minutes) and task-based fMRI (16 minutes) during a Sternberg working memory paradigm. TMS targeting was guided by task-evoked activation in the left dlPFC. Structural T1-weighted, T2-weighted, and diffusion-weighted imaging were also acquired. Here, we describe the dataset design, acquisition protocol, and data characteristics, and report initial measures of data quality and reliability. The completed dataset can be accessed at https://openneuro.org/datasets/ds008893, providing an open resource for future investigations of TBS mechanisms and individualized neuromodulation strategies.

PMID:42841045 | PMC:PMC13641012 | DOI:10.1162/IMAG.a.1314

Adv Sci (Weinh). 2026 Oct 6:e78190. doi: 10.1002/advs.78190. Online ahead of print.

ABSTRACT

Rotator cuff injury (RCI) is frequently accompanied by psychological comorbidities, particularly anxiety-related symptoms, which predict poor functional recovery, yet the central mechanisms linking affective disturbance to impaired tendon-bone healing remain unclear. Here, by integrating clinical neuroimaging, imaging transcriptomics, and mechanistic animal experiments, we identify hypothalamic paraventricular nucleus (PVN) oxytocinergic (OXT) neurons as a critical central node coordinating emotional regulation and bone-tendon interface (BTI) repair. In patients with RCI, resting-state fMRI (rs-fMRI) revealed reduced hypothalamic spontaneous activity that was inversely correlated with anxiety severity. Imaging transcriptomic analyses further linked these functional alterations to spatially concordant gene expression programs enriched in oxytocin signaling. In mouse models, retrograde viral tracing and spatial transcriptomics identified PVNOXT neurons as the predominant labeled population within a polysynaptic PVN-IML-SCG sympathetic pathway connected to the subchondral bone region of the rotator cuff enthesis. In vivo local field potential recordings confirmed a reduction in PVN neuronal activity that peaked at four weeks post-injury and recovered thereafter, paralleling the behavioral time course. Chemogenetic inhibition of PVNOXT neurons induced anxiety-like behaviors and impaired BTI healing, whereas their activation alleviated anxiety and enhanced structural and biomechanical recovery. Together, these findings support a working model in which a PVNOXT-sympathetic-shoulder axis links anxiety dysregulation to musculoskeletal healing through a hypothalamic-sympathetic pathway, providing a framework for integrated neuromodulatory and tissue-targeted interventions in RCI.

PMID:42839625 | DOI:10.1002/advs.78190

Psychol Med. 2026 Oct 7;56:e320. doi: 10.1017/S0033291726105959.

ABSTRACT

BACKGROUND: The excitation-inhibition (E/I) imbalance is a major pathological characteristic of major depressive disorder (MDD). However, whether/how electroconvulsive therapy (ECT) modulates neuronal homeostasis or E/I balance in MDD and its molecular basis is still largely unknown.

METHODS: In this study, longitudinal rs-fMRI data from 46 patients with MDD receiving ECT and 46 healthy controls were included. The Hurst index was used to characterize the E/I balance, and mixed-effects model was constructed to assess the interactive effects of ECT on the Hurst index and functional connectivity (FC). Moreover, spatial correlation analyses were conducted by integrating cortical myelination pattern, glucose metabolism distribution, neurotransmitter density maps, and transcriptomic data to reveal the underlying molecular basis.

RESULTS: ECT significantly reduces the Hurst index in the middle cingulate cortex (MCC) and induces functional decoupling between the MCC and the posterior cingulate cortex. Furthermore, changes in the Hurst index were closely associated with cortical myelination, glucose metabolism, and the distribution maps of dopamine and histamine. Spatial transcriptomic association analysis revealed that genes regulating the effects of ECT on Hurst index or FC are specifically enriched in cell types such as excitatory neurons, astrocytes, and oligodendrocytes, and are primarily involved in biological processes including synaptic signal transduction, neuronal projection regulation, and glutamatergic synapses.

CONCLUSION: These findings suggest that ECT may regulate the processes of myelin remodelling through neurons and glial cells by influencing the expression levels of relevant genes, thereby modulating the E/I balance and functional network activity in a synergistic manner to improve depressive symptoms.

PMID:42839296 | DOI:10.1017/S0033291726105959

Neuroimage. 2026 Oct 6:122283. doi: 10.1016/j.neuroimage.2026.122283. Online ahead of print.

ABSTRACT

Clinical adoption of new biomedical techniques depends on establishing reference values against which individual patients can be compared. In resting-state functional MRI (rsfMRI), most biomarker research has relied on the case-control paradigm, whose underlying assumptions are often invalid as diseases are frequently heterogeneous, limiting biomarker generalizability. Normative modeling offers a complementary alternative by characterizing individual deviations against a reference population. However, in rsfMRI, normative modeling remains comparatively limited relative to case-control studies and has been applied almost exclusively to functional connectivity. We address these gaps by developing a spatial normative model of four rsfMRI metrics that capture complementary features of the blood-oxygen-level-dependent (BOLD) signal across age and sex. Aggregating five public datasets yielded a sample of 1,978 participants aged 10-30 years. For each of 110 grey matter regions, we computed amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and Hurst exponent. A machine-learning model based on hierarchical Bayesian regression with a non-Gaussian likelihood was fitted per metric, modeling non-linear age effects, sex, head motion parameters, and multi-site acquisition. Models were well calibrated across all four metrics, with fALFF showing the strongest predictive performance and Hurst exponent the weakest. Normative trajectories varied regionally: while the median of each distribution stayed bounded across regions, the spread was more variable. All four metrics showed predominantly negative slopes with age, indicating a decline over the age window. This work provides a normative reference across four rsfMRI metrics capturing distinct BOLD signal features, complementing the case-control paradigm and supporting individual-level inference.

PMID:42838427 | DOI:10.1016/j.neuroimage.2026.122283

Neurotoxicol Teratol. 2026 Oct 6:107723. doi: 10.1016/j.ntt.2026.107723. Online ahead of print.

ABSTRACT

AIM: Cannabis use during pregnancy has increased, raising concerns about potential effects on offspring brain development. The objective of this systematic review was to evaluate MRI-based evidence on the association between prenatal cannabis exposure (PCE) and offspring brain development across structural, diffusion, resting-state functional, and task-based functional MRI.

METHODS: Following PRISMA guidelines, PubMed, Web of Science, and Embase were searched through September 4, 2026, for MRI studies comparing prenatally exposed offspring with non-exposed controls across any modality. Study quality was assessed using Joanna Briggs Institute tools, and certainty of evidence was evaluated using the GRADE framework.

RESULTS: Eighteen studies (2004-2026) met inclusion criteria, with participants ranging from the fetal period to young adulthood. Structural MRI showed no consistent global brain-volume reductions, although some studies reported region-specific differences, particularly in frontal regions and intracranial-volume trajectories. Diffusion MRI identified alterations in selected white-matter pathways, including frontolimbic and corticostriatal tracts, but findings were inconsistent and not uniformly replicated. Resting-state functional MRI studies showed heterogeneous connectivity differences across hippocampal, salience, thalamic, and auditory networks, and task-based functional MRI studies reported variable reward- and executive-control activation, including some null findings. Overall certainty of evidence was low to very low because of risk of bias, inconsistency, imprecision, residual confounding, and methodological heterogeneity.

INTERPRETATION: PCE may be associated with subtle, regionally specific differences in brain structure, microstructure, and function rather than consistent global abnormalities. However, structural MRI showed no consistent global abnormalities, diffusion MRI findings were inconsistent, and resting-state and task-based fMRI findings were heterogeneous. Causal interpretation remains limited by confounding, cohort overlap, exposure assessment, and methodological heterogeneity.

PMID:42838292 | DOI:10.1016/j.ntt.2026.107723

Cereb Cortex. 2026 Oct 6;36(10):bhag091. doi: 10.1093/cercor/bhag091.

ABSTRACT

Why is human music rhythmically structured the way it is? One hypothesis is that the human brain is intrinsically wired to favor specific rhythmic organizations. To test this, we collected diffusion and resting-state functional MRI (fMRI) data from musically untrained participants and, weeks later, asked them to imitate randomly generated drumming sequences using finger taps. These imitations exhibited systematic biases toward temporal structures widespread in human music: predictable patterns characterized by isochronous organization (1:1) and other small integer ratios (2:1 and 3:1). Functional connectome analyses linked the increased rhythmic predictability of reproduced rhythms to intrinsic interactions between networks implicated in auditory timing (auditory basal ganglia) and executive control (task-positive and task-negative networks). Notably, the tendency toward isochrony-a feature highly conserved across species-was selectively associated with increased fiber density within a cortico-basal ganglia-thalamo-cortical network previously implicated in the perception and production of a metronomic pulse from music (the "beat"). Our findings reveal how stable neural architecture predisposes humans to produce rhythmically structured patterns. This evidence links intrinsic brain circuitry to individual cultural expressions, supporting the account of human symbolic systems, including music, as biocultural hybrids.

PMID:42837292 | DOI:10.1093/cercor/bhag091