Most recent paper

Brain Imaging Behav. 2026 Feb 13;20(1):14. doi: 10.1007/s11682-026-01079-0.

ABSTRACT

The re-organization of brain networks induced by task performance plays a pivotal role for understanding brain mechanisms of function. Studies have demonstrated that functional magnetic resonance imaging (fMRI) data collected during task performance reflects both stimulus-based responses and ongoing intrinsic brain activity that persists even during task performance. However, the state-of-the-art statistical methods for analyzing fMRI signals are not able to extract pure task-evoked brain network activity that is distinguished from ongoing intrinsic brain activity. In order to fill this gap, we propose to use Tensor Component Analysis (TCA) to estimate stimulus evoked brain network responses disentangled from ongoing activity of intrinsic brain networks (ICNs). We conducted numerical simulations and used in-vivo task and resting state fMRI data collected by the Human Connectome Project to evaluate the performance of TCA for this purpose. We also used a subset of the HCP data to demonstrate the ability of TCA for evaluating Theory of Mind related brain networks in individuals with cannabis use disorder. Our findings show that TCA is a promising tool to extract task-evoked dynamic brain networks distinct from intrinsic brain network activity. Compared with dynamic connectivity analyses, task-evoked dynamic brain network estimated with TCA provides a more accurate way to study the brain's response to external stimuli and sheds new light on brain and behavior relationships.

PMID:41686283 | DOI:10.1007/s11682-026-01079-0

Front Neurosci. 2026 Jan 28;20:1766192. doi: 10.3389/fnins.2026.1766192. eCollection 2026.

ABSTRACT

INTRODUCTION: Disruptions in functional connectivity (FC) within the default mode network (DMN) are well established as a key neuropathology underlying cognitive impairment in type 2 diabetes mellitus (T2DM). Subcortical nuclei, including the basal forebrain (BF) and mediodorsal thalamus, play critical roles in regulating DMN-associated cognitive processes and are particularly vulnerable to hyperglycemia and brain insulin resistance. However, the specific FC patterns between these subcortical nuclei and DMN cortical regions in patients with T2DM, as well as their potential associations with cognitive impairment, remain incompletely elucidated.

METHODS: Eighty-two patients with T2DM and 79 healthy controls (HCs) were enrolled in this study. Clinical data, neuropsychological assessments, and resting-state functional magnetic resonance imaging were collected from all participants. Resting-state (rs-FNC) and dynamic (dFNC) functional network connectivity analyses were performed to characterize connectivity between subcortical nuclei and DMN cortical regions. Correlation analyses explored associations between FNC metrics showing significant intergroup differences and participants' clinical and cognitive parameters.

RESULTS: rs-FNC analysis revealed decreased FC between the BF and the dorsomedial prefrontal cortex (dMPFC), the BF and the temporal pole, and the dMPFC and the anteromedial prefrontal cortex in patients with T2DM (network-based statistic correction; edge p < 0.001, component p < 0.05). dFNC analyses indicated increased frequency and prolonged mean dwell time (MDT) of State 1 (high-frequency low-connectivity), as well as decreased frequency and shortened MDT of State 2 (high-frequency high-connectivity) compared with HCs (all p < 0.05). Reduced FC between the dMPFC and BF was positively correlated with Montreal Cognitive Assessment scores (r = 0.353, p = 0.001), whereas frequency (r = -0.434, p < 0.001) and MDT (r = -0.376, p = 0.001) of State 2 were negatively correlated with T2DM disease duration after Bonferroni correction.

CONCLUSION: These findings indicate that T2DM duration correlates with reduced highly efficient DMN connectivity, and that the BF may regulate cognitive function via the dMPFC subsystem. The results reveal temporal and functional specificity in abnormal DMN connectivity in patients with T2DM and enrich the neural atlas of DMN dysfunction in this population.

PMID:41685355 | PMC:PMC12891212 | DOI:10.3389/fnins.2026.1766192

Psychoradiology. 2025 Dec 1;6:kkaf029. doi: 10.1093/psyrad/kkaf029. eCollection 2026.

ABSTRACT

BACKGROUND: There are notable sex differences in the symptoms and treatment response of late-life depression (LLD); however, the underlying static and dynamic abnormalities in brain function that may drive these disparities remain unclear. This study was to investigate sex-specific aberrant brain activity in LLD.

METHODS: We recruited 75 LLD patients and 164 healthy controls (HCs). Static and dynamic metrics of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) were compared across four groups (LLD-female, LLD-male, HC-female, and HC-male). Correlation and moderation analyses were then used to examine whether sex moderated the associations between brain activity, cognitive impairment, and depressive symptoms.

RESULTS: First, significant interaction effects between diagnosis (LLD vs. HCs) and sex were found for ALFF in the left paracentral lobule, ReHo in the right superior temporal gyrus, and static FC (sFC) between the right superior temporal gyrus and left middle frontal gyrus. Second, in LLD-female, ReHo (right superior temporal gyrus) and sFC (right superior temporal gyrus-left middle frontal gyrus) correlated with weight, and ALFF (left paracentral lobule) correlated with visuospatial skills. Third, sex significantly moderated the relationships between ReHo (right superior temporal gyrus) and cognition, ALFF (left paracentral lobule) and depressive symptoms, and sFC (right superior temporal gyrus-left middle frontal gyrus) and depressive symptoms in the LLD group.

CONCLUSION: Our study highlights sex differences in static brain activity related to cognitive impairment and depressive symptoms in LLD, indicating sex-specific neurobiological underpinnings for this disorder.

PMID:41684635 | PMC:PMC12892001 | DOI:10.1093/psyrad/kkaf029

Sci Rep. 2026 Feb 13. doi: 10.1038/s41598-026-37599-4. Online ahead of print.

NO ABSTRACT

PMID:41680306 | DOI:10.1038/s41598-026-37599-4

Magn Reson Imaging. 2026 Feb 10:110640. doi: 10.1016/j.mri.2026.110640. Online ahead of print.

ABSTRACT

Spinal cord functional magnetic resonance imaging (fMRI) has advanced significantly in recent years, revealing insights into the function of somatosensory and motor systems. However, the complex environment of the spinal cord induces unique sources of noise, limiting the quality of spinal fMRI recordings. Various hardware and software solutions have been proposed to address these challenges. Among them, susceptibility-matched padding has gained popularity due its low cost, ease of use, and effectiveness in reducing static B0 field inhomogeneities, which are a major source of artefacts in spinal fMRI. Despite anecdotal evidence, the impact of susceptibility-matched padding on the quality of spinal cord fMRI has not been assessed systematically. We investigated the effects of non-protonated perfluorocarbon liquid-filled padding (SatPad) on B0 field homogeneity and functional echo-planar imaging (EPI) in cervical and lumbar spinal cord in 10 healthy volunteers. Participants underwent two resting-state fMRI scanning sessions, one per cord section. Within each session they were scanned with and without SatPad in a pseudo-randomised order. The use of SatPad increased B0 field homogeneity and improved functional image quality metrics, including temporal signal-to-noise ratio and ghosting artefacts. While both cervical and lumbar cord data benefited from the use of SatPad, greater effects were observed in the cervical cord. These findings provide a compelling basis for integrating susceptibility-matched padding into routine spinal fMRI protocols.

PMID:41679399 | DOI:10.1016/j.mri.2026.110640

PLoS Biol. 2026 Feb 12;24(2):e3003577. doi: 10.1371/journal.pbio.3003577. eCollection 2026 Feb.

ABSTRACT

Systematic identification of global epileptic reorganization and critical seizure-controlling circuits is essential for comprehending epilepsy pathophysiology and for developing network-guided targeted therapies. The piriform cortex (PC) is a recognized epileptogenic region, but how its hyperactivity reshapes whole-brain dynamics and which specific circuits mediate seizures remains unclear. Through multimodal integration of optogenetics, fMRI, electrophysiology, Ca2+ imaging, neural tracing, and circuit-specific manipulation, we mapped the whole-brain dynamics following optogenetic stimulation of PC and identified the fundamental circuit governing piriform seizures. We observed pronounced generalized seizures in mice via repeated optogenetic stimulation of PC Vglut1+ neurons. Optogenetic kindling of PCVglut1 induced widespread blood-oxygen-level-dependent (BOLD) signal hyperactivation and resting-state functional connectivity (rsFC) alterations, notably sustained hyperactivation in the lateral entorhinal cortex (Lent) and enhanced PC-Lent rsFC. Chronic elimination of Lent neurons receiving PC projections significantly decreased the Lent-dentate gyrus (DG) rsFC. Disruption of the PC-Lent or Lent-DG circuit effectively suppressed PC-stimulation-triggered seizures and brain-wide hyperactivation. Our findings demonstrate the dominant role of the PCVglut1-Lentglut-DG circuit in mediating piriform seizures and driving their resulting brain-wide functional reorganization, offering new insights for targeted epilepsy treatments.

PMID:41678438 | DOI:10.1371/journal.pbio.3003577

Eur Arch Psychiatry Clin Neurosci. 2026 Feb 12. doi: 10.1007/s00406-026-02204-2. Online ahead of print.

NO ABSTRACT

PMID:41677825 | DOI:10.1007/s00406-026-02204-2

J Parkinsons Dis. 2026 Feb 12:1877718X261420080. doi: 10.1177/1877718X261420080. Online ahead of print.

ABSTRACT

Parkinson's disease (PD) involves degeneration of dopaminergic neurons and dysfunction across multiple neurotransmitter systems, contributing to both motor and cognitive impairments. Aerobic exercise improves clinical outcomes; however, its underlying neural mechanisms remain unclear. Using conventional resting-state fMRI combined with Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), we examined molecular-enriched motor network changes following six months of supervised aerobic training in PD. Exercise-related connectivity changes were inversely correlated with baseline PD-healthy control differences, reflecting a partial normalization of PD-altered motor networks. Molecular-enriched analyses revealed selective effects on dopaminergic (FDOPA-enriched) and cholinergic (VAChT-enriched) related networks, with no changes observed in networks associated with serotonergic or noradrenergic systems. These findings provide supporting evidence for potential mechanistic links between aerobic exercise and network reorganization in PD, highlight multisystem effects, and illustrate the utility of molecular-enriched fMRI for probing neurotransmitter-specific interventions.

PMID:41677133 | DOI:10.1177/1877718X261420080

bioRxiv [Preprint]. 2026 Feb 7:2026.02.04.703882. doi: 10.64898/2026.02.04.703882.

ABSTRACT

The integration of electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) can be used to characterize temporal and spatial components of neural activity during unfolding mental experience. Here we introduce a multi-session simultaneous EEG-fMRI dataset with measures of continuous behavior and spontaneous mental experience. Data components, organized in Brain Imaging Dataset Structure (BIDS) format, include fMRI, EEG with carbon wire loop sensors for artifact removal, continuous performance task responses, experience sampling ratings, and mental health surveys, from 24 healthy adults. Tasks included the gradual-onset continuous performance task and resting state with intermittent experience sampling of 13 unique thought dimensions (36 repetitions, including 468 total ratings, per participant). The same protocol was completed on two different days, yielding approximately 1.33 hours of simultaneous EEG-fMRI data per individual. The dataset may be used to explore the behavioral and experiential relevance of brain activity during the wakeful resting state. The dataset also provides a means to study the reliability of relationships between fMRI and EEG features across sessions within individuals.

PMID:41676676 | PMC:PMC12889718 | DOI:10.64898/2026.02.04.703882

bioRxiv [Preprint]. 2026 Feb 2:2026.01.30.702883. doi: 10.64898/2026.01.30.702883.

ABSTRACT

The functional network architecture of the aging brain undergoes significant systematic and idiosyncratic changes. Emergent individualized network mapping approaches may yield better or more sensitive explanatory insight about age-related neural and behavioral variability, although most applications have focused on young adults. In the current study, we tested the validity and impact of mapping individual-specific topography in two fMRI datasets comprising 112 young (18-35 years) and 176 older adults (60-92 years). Older adults had more idiosyncratic network topography than young adults. Individualized maps from resting-state fMRI improved network homogeneity and fidelity to task fMRI activations, while also exhibiting intra-individual reliability and inter-individual discriminability over a 2-year interval. Last, traditional group-averaged ( vs . individualized) network mapping had a moderate-to-large impact on individual-level estimates of network segregation, a widely-studied measure of functional brain aging. Therefore, individualized network mapping captures important heterogeneity in older adulthood and may yield more precise characterization of neurocognitive aging.

PMID:41676650 | PMC:PMC12889444 | DOI:10.64898/2026.01.30.702883

bioRxiv [Preprint]. 2026 Feb 6:2026.02.03.703581. doi: 10.64898/2026.02.03.703581.

ABSTRACT

Cerebrovascular reactivity (CVR), the ability of cerebral blood vessels to dilate or constrict in response to a vasoactive stimulus, is a clinically meaningful measure of cerebrovascular health. Head motion and other noise sources substantially impact CVR quality, particularly in clinical populations. In this study, we evaluated multi-echo fMRI techniques, including optimal combination of echoes (ME-OC) and multi-echo independent component analysis (ME-ICA), for improving CVR quality relative to single-echo fMRI in participants with stroke. In a breath-hold fMRI dataset, ME-OC significantly improved CVR quality metrics and reduced the percentage of negative CVR values in normal-appearing gray and white matter ( p <0.05). ME-ICA reduced the dependence of BOLD signals on head motion but did not improve CVR quality metrics. In a separate resting-state dataset, ME-OC effects were largely consistent with the breath-hold dataset, but ME-ICA also significantly improved CVR quality metrics and reduced negative CVR values in normal-appearing gray and white matter relative to ME-OC ( p <0.05). These findings demonstrate that multi-echo fMRI can improve CVR estimation in clinical populations, particularly in low signal-to-noise datasets, enhancing the feasibility of CVR analyses in stroke studies and allowing for better visualization of stroke-related CVR deficits.

PMID:41676635 | PMC:PMC12889588 | DOI:10.64898/2026.02.03.703581

bioRxiv [Preprint]. 2026 Feb 3:2026.01.31.703060. doi: 10.64898/2026.01.31.703060.

ABSTRACT

Simultaneous electroencephalography (EEG) and functional MRI (fMRI) offers complementary sensitivity to fast electrophysiological dynamics of EEG and spatially resolved hemodynamics of fMRI, yet previous joint-analysis approaches are confined to fixed task paradigms and struggle with continuous or naturalistic brain states. We FSINC (Fusing Source Imaging based on a Neurovascular Coupling) model, a unified EEG-fMRI source imaging framework that reconstructs cortical activity to simultaneously explain both modalities. FSINC integrates frequency-resolved EEG source activity with fMRI via a data-driven neurovascular coupling model that estimates band-specific coupling coefficients (β) and accommodates a tunable spatial-temporal trade-off through hyperparameters ( λ 2 , λ 3 ). In realistic simulations, FSINC outperformed conventional methods (wMNE, LORETA) in both spatial and temporal accuracy across EEG SNRs (-10 to 10dB) and numbers of concurrent sources (up to five), with optimal performance at λ 2 = 10 2 and λ 3 =1 (e.g., LE: 0.51±0.24mm; SDI: 0.03±0.37mm; temporal accuracy: 0.95 ± 0.05). Applied to simultaneous EEG-fMRI during contrast-reversing visual stimulation (=5.95Hz), FSINC revealed stimulus-locked responses localized to early visual cortex and stimulus-induced modulation of intrinsic alpha oscillations extending into visual and attention networks, patterns that conventional methods failed to capture. Estimated β-weights were broadly consistent with prior reports of negative (theta/alpha) and positive (gamma) BOLD-electrophysiology associations. These findings demonstrate that FSINC enables high-spatiotemporal-resolution source imaging from EEG-fMRI recordings via data-driven hemodynamic modelling, and is expected to be well-suited for continuous and naturalistic brain states (e.g., resting state, natural moving-watching, and narrative listening) that are difficult to interrogate with either modality alone.

PMID:41676576 | PMC:PMC12889465 | DOI:10.64898/2026.01.31.703060

bioRxiv [Preprint]. 2026 Feb 3:2026.02.01.703149. doi: 10.64898/2026.02.01.703149.

ABSTRACT

Resting-state functional MRI (rs-fMRI) is a cornerstone of human brain research, yet its interpretation is complicated by its sensitivity to the slow hemodynamic response that obscures the organization of neural activity across faster time scales. Here we use simultaneous wide-field optical imaging (WOI) and rs-fMRI to directly examine the relationship between neural and hemodynamic functional connectomes across time scales. We show that much of the large-scale spatial structure is preserved across modalities, across time scales, and across frequencies. Although rs-fMRI robustly captures time-averaged neural activity, time-resolved rs-fMRI estimates of functional connectivity exhibit significantly greater variability, which partially reflects sensitivity limitations. Hemodynamic WOI signals maintain greater similarity to neural activity than rs-fMRI, although their fidelity is reduced at high frequencies. Together, our findings demonstrate that the time-averaged spatial structure of neural activity is faithfully represented in hemodynamics and rs-fMRI; provide insight into the reliability of time-resolved rs-fMRI across temporal scales; and establish a multimodal framework for validating features of dynamic brain activity.

PMID:41676555 | PMC:PMC12889463 | DOI:10.64898/2026.02.01.703149

bioRxiv [Preprint]. 2026 Feb 7:2026.02.04.703913. doi: 10.64898/2026.02.04.703913.

ABSTRACT

White matter (WM) has traditionally been considered structurally important but functionally inert in fMRI research. However, growing evidence indicates that WM exhibits meaningful BOLD fluctuations and participates in functional connectivity. Here, we investigate alterations in WM functional network connectivity (FNC) across the Alzheimers disease (AD) spectrum using resting-state fMRI data from the Alzheimers Disease Neuroimaging Initiative (ADNI 415 cognitively normal (CN), 283 mild cognitive impairment (MCI), 91 AD). We applied a guided independent component analysis (ICA) approach based on a combined multiscale template including 202 intrinsic connectivity networks (ICNs; 97 WM, 105 gray matter (GM)) to estimate subject-specific timecourses and compute static FNC (sFNC). Group differences in WMWM, GMGM, and WMGM connectivity (ADCN, ADMCI, MCICN) were assessed using two-sample t-tests with covariates for age, sex, and motion, with false discovery rate correction. Results showed robust alterations in WMWM and WMGM connectivity in AD, particularly involving WM subcortical, frontal, sensorimotor, and occipitotemporal networks. Several WMGM interactions with cerebellar and hippocampal GM networks were also disrupted, including reduced GMcerebellar:WMfrontal coupling and increased GMhippocampal to WMfrontal connectivity. Notably, MCI already showed WMGM dysconnectivity relative to CN, suggesting that functional disruption of WM circuits emerges prior to overt dementia. These findings provide converging evidence that WM functional connectivity is both measurable and selectively altered across the AD continuum. Our findings support WM sFNC as a complementary candidate biomarker to GM-based measures for staging and monitoring AD. This is, to our knowledge, the first large-scale ADNI study to jointly model WM and GM intrinsic connectivity networks and quantify WMGM dysconnectivity across CN, MCI, and AD.

PMID:41676490 | PMC:PMC12889614 | DOI:10.64898/2026.02.04.703913

Brain Dev. 2026 Feb 10;48(2):104513. doi: 10.1016/j.braindev.2026.104513. Online ahead of print.

ABSTRACT

OBJECTIVE: Preterm birth is associated with an increased risk of functional brain network alterations, which may contribute to long-term motor and neurocognitive deficits. However, the underlying neural mechanisms remain incompletely understood. This study aimed to investigate functional brain activity changes in preterm infants and their correlation with early neurobehavioral development.

METHODS: Fifteen preterm infants and 15 full-term infants underwent scanning using a 3.0T Philips MRI scanner. Three resting-state functional magnetic resonance imaging (rs-fMRI) data-driven approaches, amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and seed-based functional connectivity (FC) were used to comprehensively evaluate functional brain alterations in preterm infants at term-equivalent age (TEA). Correlations between Neonatal Behavioral Neurological Assessment (NBNA) scores and FC values of abnormally connected brain regions were further analyzed in preterm infants at TEA.

RESULTS: Compared with full-term infants, preterm infants exhibited significantly higher ALFF and ReHo values in the left precuneus. Using the left precuneus as a seed region for FC analysis, preterm infants showed reduced FC with the left Rolandic operculum, right putamen, and left hippocampus. Additionally, FC values between the left precuneus and left Rolandic operculum, as well as between the left precuneus and right putamen, were positively correlated with NBNA scores in preterm infants.

CONCLUSIONS: Preterm infants may present early functional connectivity impairments of the left precuneus, which may be a potential neural correlate of neurobehavioral abnormalities. These findings provide insights into the neurodevelopmental mechanisms underlying preterm birth-related deficits and may inform early clinical assessment strategies.

PMID:41671832 | DOI:10.1016/j.braindev.2026.104513

Neuroimage Clin. 2026 Feb 4;49:103958. doi: 10.1016/j.nicl.2026.103958. Online ahead of print.

ABSTRACT

BACKGROUND: Schizophrenia is associated with widespread functional dysconnectivity, but the spatial scale and structural correlates of these alterations remain unclear. While relevant to local dysfunction, short-range connectivity is not well captured by standard approaches due to methodological constraints.

METHODS: We applied a vertex-wise, distance-dependent analysis of functional connectivity strength (FCS) to resting-state fMRI data from 86 schizophrenia patients and 99 healthy controls across two datasets. FCS was partitioned by geodesic distance on the cortical surface and analyzed by cortical hierarchy. We also assessed two proxies of intracortical microstructure: T1/T2 ratio and a novel signal-detection-based measure of individualized data-driven functional connectivity density (idFCD).

RESULTS: Schizophrenia patients exhibited reductions in short-range FCS within the dorsal primary somatosensory cortex. These functional alterations colocalized with abnormalities in both microstructural proxies and were not evident in global FCS analysis. In contrast, longer-range FCS was increased in transmodal regions, particularly the precuneus, without associated microstructural differences. Hierarchical analysis confirmed this dissociation, with structure-function disruption in primary networks and increased relative FCS in transmodal regions without microstructural association.

CONCLUSIONS: Our findings support two distinct patterns of cortical dysconnectivity in schizophrenia: short-range reductions in primary sensory areas that colocalize with microstructural abnormalities, and longer-range increases in transmodal regions that appear structurally decoupled at the local level. By integrating distance-dependent functional measures with independent proxies of intracortical microstructure, this study highlights the role of short-range connectivity disruptions in primary areas and provides a complementary framework to conventional approaches based on regional or global analyses and diffusion-weighted imaging.

PMID:41671792 | DOI:10.1016/j.nicl.2026.103958

Psychiatry Res Neuroimaging. 2026 Feb 3;358:112165. doi: 10.1016/j.pscychresns.2026.112165. Online ahead of print.

ABSTRACT

BACKGROUND: Delusions are a core symptom of schizophrenia and schizoaffective disorder (SCZ/SZA), yet their neural mechanisms remain incompletely understood. Contemporary models emphasize dysfunctional network-level interactions, particularly between subcortical and cortical regions.

OBJECTIVE: To characterize resting-state functional connectivity (rsFC) alterations specifically associated with prominent delusions in SCZ/SZA, with emphasis on cortico-subcortical and cerebellar networks.

METHODS: High-resolution ROI-to-ROI rsFC analyses were conducted in 20 SCZ/SZA patients with prominent delusions and 20 matched healthy controls. Functional connectivity was calculated across 164 regions using the Harvard-Oxford atlas. Statistical significance was assessed with threshold-free cluster enhancement (TFCE) and family-wise error (FWE) correction at p < 0.05.

RESULTS: Twenty significant connectivity clusters were identified, encompassing both hyper- and hypoconnectivity. Increased connectivity was observed between basal ganglia structures (putamen, pallidum) and cortical regions of the default mode network (DMN), frontal executive networks, and limbic areas, consistent with aberrant salience attribution and disrupted integration of internal and external signals.

CONCLUSION: Delusions in SCZ/SZA may stem from widespread dysconnectivity anchored in evolutionarily older subcortical and cerebellar regions, impairing sensorimotor, emotional, and cognitive integration. These findings support a network-based model of delusion formation and may inform potential targets for neuromodulatory intervention.

PMID:41671697 | DOI:10.1016/j.pscychresns.2026.112165

Auton Neurosci. 2026 Feb 5;264:103389. doi: 10.1016/j.autneu.2026.103389. Online ahead of print.

ABSTRACT

The vagus nerve connects the brain and the heart, allowing communication between the body and the mind. Studies have strengthened the meaning of the brain to control heart rate variability (HRV), however, brain research has largely overlooked the effects of age on the association between phasic changes in HRV and resting state functional brain connectivity. To close this gap, we studied a large open data set of 69 old and 134 young participants with two consecutive fMRI resting state scans in combination with the corresponding physiological HRV data assessed via photoplethysmography (PPG). We quantified spontaneous HRV changes from one resting state to the other and studied the unique information about the relationship between changes in functional coupling between brain areas and spontaneous HRV changes. Using a fc-MVPA, we identified functional brain coupling patterns associated with changes in HRV within brain networks, including the anterior cingulate cortex (ACC), the cerebellum, the brainstem, and the temporal lobe. These patterns were not significantly different between the two age groups - indicating age invariance of brain heart communication. Post hoc seed-to-voxel analyses indicated a stronger functional coupling of these identified clusters with brain regions such as the insula, the opercular cortex, the superior frontal gyrus, and the cerebellum when HRV increased. This pattern of findings is in accordance with prominent theories and provides further insights into the neural mechanisms underlying brain-heart communication.

PMID:41671693 | DOI:10.1016/j.autneu.2026.103389

J Neurol. 2026 Feb 11;273(2):139. doi: 10.1007/s00415-026-13665-9.

ABSTRACT

BACKGROUND: Abnormalities in large-scale brain functional networks are implicated in multiple sclerosis (MS) and linked to clinical impairments, but reported findings remain heterogeneous due to methodological and sample variations.

METHODS: Based on 25 resting-state functional magnetic resonance (rsfMRI) imaging studies (1,524 MS patients and 886 healthy controls (HCs)), in which the independent component analysis (ICA) method was used to evaluate the resting-state functional connectivity (rsFC) changes in default mode (DMN), sensorimotor (SMN), salience (SN), and visual (VN) networks, a meta-analysis was performed using the anisotropic effect size seed mapping (AES-SDM) software to quantify the differences between MS patients and HCs. The heterogeneity was assessed, and a meta-regression analysis was conducted on age, disease duration, Expanded Disability Status Scale scores, and T2-hyperintense lesion volume.

RESULTS: Compared with HCs, MS exhibited increased rsFC in left anterior cingulate/paracingulate gyri and right superior frontal gyrus (DMN), bilateral precentral gyrus and right postcentral gyrus (SMN), right angular gyrus (SN), whereas hypoconnectivity was observed in left posterior cingulate gyrus (DMN), right supplementary motor region and left precentral gyrus (SMN), right insula (SN), and left superior parietal gyrus (VN). The Meta-regression analysis revealed no significant correlation between these altered rsFC and clinical variables.

DATA CONCLUSIONS: This study demonstrates widespread and complex rsFC abnormalities in several neural networks in MS, particularly within core regions of the DMN, SMN, VN, and SN. Together with a descriptive synthesis of additional RSNs, these rsFC disruptions and reorganizations may represent intrinsic neuropathological alterations in MS, which further elucidate the pathophysiological mechanisms of functional abnormalities in MS at a large-scale level.

PMID:41670734 | DOI:10.1007/s00415-026-13665-9

Quant Imaging Med Surg. 2026 Feb 1;16(2):163. doi: 10.21037/qims-24-2442. Epub 2026 Jan 14.

ABSTRACT

BACKGROUND: Static functional networks of the brain are disrupted in minimal hepatic encephalopathy (MHE), but their dynamic alterations are unknown. This observational study utilized multilayer network analysis to investigate dynamic network characteristics in hepatitis B cirrhosis (HBC) with or without MHE and assess their association with neurocognitive function (registry: https://ctms.xyeyy.com/iit/project/index; trial registration number: LYF20240134; date: 2024-07-31).

METHODS: A total of 33 HBC patients [15 non-MHE (NMHE; HBC patients without MHE) and 18 MHE individuals], as well as 36 matched healthy controls (HCs), underwent neurocognitive assessments, resting-state functional magnetic resonance imaging (rs-fMRI), and clinical examinations. Dynamic network variations were quantified using network switching rates, and their relationships with clinical and neurocognitive parameters were evaluated.

RESULTS: Both HBC patients with and without MHE status exhibited a range of altered network switching rates compared to HCs. Specifically, differences were observed in subnetworks including somatomotor network (SMN), dorsal attention network (DAN), ventral attention network (VAN), frontoparietal network (FPN), and subcortical network (SUB), as well as in nodal regions such as the right precentral gyrus (rPrG), left fusiform gyrus (lFuG), left inferior parietal lobule (lIPL), and right hippocampus (rHipp). Furthermore, altered global level and lFuG switching rates positively correlated with Psychometric Hepatic Encephalopathy Score (PHES) (r=0.341, 0.339; P=0.004, 0.004, respectively, Bonferroni corrected).

CONCLUSIONS: This study firstly revealed that HBC patients exhibited imbalanced functional dynamics in subnetworks and nodes, suggesting a potential mechanism underlying cerebral dysfunction in MHE.

PMID:41669485 | PMC:PMC12883493 | DOI:10.21037/qims-24-2442