Most recent paper

bioRxiv [Preprint]. 2026 Jan 20:2026.01.18.700221. doi: 10.64898/2026.01.18.700221.

ABSTRACT

High dimensionality of dynamic functional connectivity (dFNC) data representation complicates clinical interpretation and biomarker discovery. We propose a new complementary analytical framework based on dynamic inter-network connectivity entropy (DICE) and its potential use as a biomarker of mental illness. Our framework shows that DICE features extend beyond patient-control discrimination, revealing distinct pathophysiological signatures and differential associations with symptom dimensions. Using resting-state fMRI data from 311 participants, 160 controls, 151 schizophrenia (SZ) patients, we identified 53 intrinsic networks, computed DICE and derived three families of DICE-based metrics: (i) entropy level and range, (ii) distributional shape and temporal organization, (iii) entropy-state repertoire and occupancy. These measures revealed a multidimensional signature of altered entropy dynamics in SZ: (1) elevated baseline entropy with reduced fluctuation magnitude and reduced entropy acceleration; (2) reduced temporal persistence of entropy excursions and entropy distributions closer to Gaussian; and (3) a narrowed repertoire of entropy states, prolonged time in near-baseline entropy configurations. The DICE-based metrics within the SZ group show different associations with symptom dimensions. Reduced fluctuation magnitude and acceleration were associated with greater PANSS general symptom severity (disturbance of volition and preoccupation). Reduced deviation from Gaussianity was associated with higher PANSS positive severity (delusions and hallucinations). Reduced temporal persistence was associated with multiple PANSS positive, negative, and general symptoms. Reduced entropy-state diversity and prolonged dwell time in near-baseline states were associated with depression and PANSS positive/general severity, respectively. The multidimensional pathophysiology revealed through the different entropy patterns may potentially guide biomarker development and personalized treatments.

PMID:41648253 | PMC:PMC12871582 | DOI:10.64898/2026.01.18.700221

bioRxiv [Preprint]. 2026 Jan 24:2026.01.22.701132. doi: 10.64898/2026.01.22.701132.

ABSTRACT

Dynamic connectivity is central to understanding time-varying interactions between brain regions. Despite decades of methodological development, approaches to measuring dynamic connectivity remain fragmented, leading to inconsistent findings, limited comparability across studies, and difficulty attributing observed effects to computational choices. Here we introduce dynamic co-modulation (DyCoM), a compact operator-level framework that expresses dynamic connectivity estimators as compositions of a small set of fundamental signal processing operations. Using simulations and resting-state fMRI data, we show that DyCoM disentangles previously conflated findings by revealing that lower-order sensory and higher-order executive control neurobiological signatures, state-transition sensitivity, and medication-linked clinical associations arise from distinct operator choices within a single unified framework. Together, these results establish DyCoM as a unifying foundation for dynamic interaction analysis, revealing how differences in estimator design give rise to divergent biological interpretations and offering a principled, domain-agnostic framework for coherence, interpretability, and estimator development.

PMID:41648203 | PMC:PMC12871704 | DOI:10.64898/2026.01.22.701132

bioRxiv [Preprint]. 2026 Jan 12:2026.01.11.698919. doi: 10.64898/2026.01.11.698919.

ABSTRACT

Memory athletes can achieve superior performance (e.g., memorizing 339 digits in 5 minutes) with extensive daily training, by converting abstract information into vivid scenes, and placing them along a mental path, that is then retraced at recall (Method of Loci). Understanding the brain mechanisms underlying such training-dependent performance could suggest novel brain-based approaches to improve learning and cognitive performance in other domains. As each memory athlete uses individual-specific, personalized training techniques, it has been challenging to study them at the group level. Fortunately, precision functional mapping (PFM) which uses repeated sampling of resting state functional connectivity and task fMRI, enables detailed study of individual brains. Here, we map the brain organization of a 6-time U.S. Memory Champion (>13 hours fMRI) and compare it to control data. We observe focal functional connectivity differences in the memory champion's retrosplenial, extrastriate visual, and dorsal frontal cortex (area 55b), as well as in the caudate. These suggest additional recruitment of scene and semantic processing in the athlete, alongside a stronger integration of the caudate with memory-related networks. A control rote memorization task elicits typical activation patterns in the athlete, but when using the Method of Loci, his pattern on activation differs: his hippocampal activation was larger during recall than encoding and he recruited regions showing connectivity differences compared to controls. His unique circuit for Method of Loci, incorporates regions typically used for navigation, scene processing, language and associative learning.

PMID:41648109 | PMC:PMC12871203 | DOI:10.64898/2026.01.11.698919

Imaging Neurosci (Camb). 2026 Feb 3;4:IMAG.a.1121. doi: 10.1162/IMAG.a.1121. eCollection 2026.

ABSTRACT

Research on biomarkers for predicting psychiatric disorders from resting-state functional connectivity (FC) is advancing. While the focus has primarily been on the discriminative performance of biomarkers by machine learning, identification of abnormal FCs in psychiatric disorders has often been treated as a secondary goal. However, it is crucial to investigate the effect size and robustness of the selected FCs because they can be used as potential targets of neurofeedback training or transcranial magnetic stimulation therapy. Here, we incorporated approximately 5,000 runs of resting-state functional magnetic resonance imaging from six datasets, including individuals with three different psychiatric disorders (major depressive disorder [MDD], schizophrenia [SCZ], and autism spectrum disorder [ASD]). We demonstrated that a PCA-based feature selection method can robustly extract FCs related to psychiatric disorders compared with other conventional supervised feature selection methods. We found that our proposed method robustly extracted FCs with larger effect sizes from the validation dataset compared with different types of feature selection methods based on supervised learning for MDD (Cohen's d = 0.40 vs. 0.25), SCZ (0.37 vs. 0.28), and ASD (0.17 vs. 0.16). We found 78, 69, and 81 essential FCs for MDD, SCZ, and ASD, respectively, and these FCs were mainly thalamic and motor network FCs. The current study showed that the PCA-based feature selection method robustly identified abnormal FCs in psychiatric disorders consistently across datasets. The discovery of such robust FCs will contribute to understanding neural mechanisms as abnormal brain signatures in psychiatric disorders.

PMID:41647267 | PMC:PMC12869322 | DOI:10.1162/IMAG.a.1121

Front Endocrinol (Lausanne). 2026 Jan 21;16:1629157. doi: 10.3389/fendo.2025.1629157. eCollection 2025.

ABSTRACT

INTRODUCTION: Patients with concurrent obesity, type 2 diabetes, and depression experience high disease severity and prevalence. This triad of conditions compromises quality of life and treatment adherence, further exacerbating disease progression. Therapeutic strategies for such patients must address both glycemic control and psychological well-being. Liraglutide, a glucagon-like peptide-1 receptor agonist (GLP-1RA), offers benefits beyond glucose-lowering and weight reduction, with emerging evidence suggesting it may also alleviate depressive symptoms. Therefore, liraglutide represents a promising intervention for managing depression in patients with obesity and diabetes.

OBJECTIVES: This study aims to assess the therapeutic efficacy of liraglutide in overweight or obese patients with type 2 diabetes and comorbid depression, with a specific focus on its antidepressant effects.

METHODS: This is a randomized, double-blind, placebo-controlled pilot trial. Sixty eligible participants will be randomly assigned (1:1) to receive either liraglutide (initiated at 0.6 mg/day, titrated weekly to a maximum of 1.8 mg/day) or a matched placebo, as an adjunct to standard care for 12 weeks. The primary endpoints include blood glucose levels, glycated hemoglobin, body mass index, Hamilton Depression Rating Scale score, and metrics derived from resting-state functional magnetic resonance imaging (resting-state fMRI). Secondary endpoints will assess changes in inflammatory biomarkers (tumor necrosis factor-α, interleukin-6), oxidative stress indicators (superoxide dismutase, malondialdehyde), homeostasis model assessment of insulin resistance, insulin sensitivity index, and homeostasis model assessment of β-cell function.

CONCLUSIONS: This trial will provide preliminary data on the effects of liraglutide on depressive symptoms in overweight/obese patients with type 2 diabetes. The findings are expected to provide a basis and reference for subsequent large-scale clinical research.

PMID:41647109 | PMC:PMC12867914 | DOI:10.3389/fendo.2025.1629157

medRxiv [Preprint]. 2026 Jan 30:2026.01.27.26344860. doi: 10.64898/2026.01.27.26344860.

ABSTRACT

BACKGROUND: Clinical trajectories in functional neurological disorder (FND) are variable, and the mechanisms underlying this heterogeneity remain poorly understood.

OBJECTIVE: This longitudinal study examined resting-state functional connectivity predictors and mechanisms of symptom change in FND.

METHODS: Thirty-two adults with FND (motor and/or seizure phenotypes) completed baseline questionnaires and a functional MRI (fMRI) session, followed by naturalistic treatment for 6.8±0.8 months. All participants completed follow-up questionnaires; 28 individuals completed a follow-up fMRI. At each timepoint, three graph-theory network metrics of functional connectivity were computed: weighted-degree (centrality), integration ( between-network connectivity), and segregation ( within-network connectivity). Analyses adjusted for age, sex, anti-depressants, head motion, time between sessions, and baseline score-of-interest, with cluster-wise correction. Results were contextualized against 50 age-, sex-, and head motion-matched healthy controls (HCs).

RESULTS: Based on patient-reported Clinical Global Impression of Improvement, 59.4% improved, 31.3% were unchanged, and 9.3% worsened. Psychometric scores of core FND symptoms and non-core physical symptoms showed variable trajectories, with no group-level changes. Greater improvement in core FND symptoms was associated with higher baseline between-network integrated connectivity and reduced integration longitudinally within salience, frontoparietal, and default mode network regions. Right anterior insula integration emerged as a prognostic marker and mechanistic site of reorganization, with the most improved participants showing elevated baseline integration compared to HCs. Increased baseline within-network segregated connectivity in dorsal attention network regions correlated with non-core physical symptom improvement. Findings remained significant adjusting for FND phenotype.

CONCLUSIONS: This study identified large-scale network interactions as potential prognostic and mechanistically-relevant sites of reorganization related to symptom change in FND.

PMID:41646801 | PMC:PMC12870675 | DOI:10.64898/2026.01.27.26344860

medRxiv [Preprint]. 2026 Jan 15:2026.01.13.26344039. doi: 10.64898/2026.01.13.26344039.

ABSTRACT

Sleep problems and sensory over-responsivity (SOR) are common, co-occurring, and early-emerging features of Autism Spectrum Disorder (ASD). Yet, the early neural mechanisms underlying this relationship remain unclear. Here, we used resting-state fMRI data from the Infant Brain Imaging Study (IBIS) to examine how brain connectivity at 6 months may relate to parent-reported measures of sleep-onset problems and SOR in infants at varying familial likelihood for ASD. The right anterior insula was used in seed-based analyses to investigate Salience Network (SN) connectivity to cortical and cerebellar regions of interest previously implicated in sleep disruption, sensory processing challenges, and ASD. Infants at high (HL) and low (LL) likelihood for ASD displayed divergent patterns of SN connectivity with sensorimotor cortex, as well as cerebellar regions involved in sensorimotor processing and higher-order functions. Furthermore, stronger SN connectivity with sensorimotor cortices and cerebellar regions was associated with worse sleep-onset problems and SOR in HL infants. In contrast, stronger SN-cerebellar connectivity was related to fewer sleep-onset problems and SOR in LL infants. Our findings indicate that altered SN connectivity may result in over-attribution of attention to sensory stimuli and highlight aberrant sensory prediction learning, which may underlie worse sleep problems and higher SOR in HL infants.

PMID:41646728 | PMC:PMC12870681 | DOI:10.64898/2026.01.13.26344039

medRxiv [Preprint]. 2026 Jan 30:2026.01.28.26345061. doi: 10.64898/2026.01.28.26345061.

ABSTRACT

Exposure is considered the most active element of cognitive behavioral therapy (CBT) for pediatric anxiety, and its efficacy is theorized to depend on cognitive control and its supporting neural substrates (e.g., central executive [CEN], salience [SN], and default mode networks [DMN]). However, little work has identified how CBT, or exposure specifically, modulates intrinsic connectivity of these networks. Progress may be limited by heterogeneity in network connectivity in anxiety, which may obscure treatment-related effects in group-averaged analyses. This randomized clinical trial (RCT) leverages person-specific network modeling to test how exposure-focused CBT (EF-CBT) influences resting-state connectivity of cognitive control networks in pediatric anxiety, relative to an active control (relaxation mentorship training; RMT). Youth aged 7-18 years with an anxiety disorder (N = 104) or low/no anxiety (L/NA; N = 37) completed resting-state fMRI scans before being randomized to EF-CBT or RMT. Resting-state connectivity was reassessed following treatment (or commensurate time L/NA youth) in 113 participants. Changes in within-CEN, CEN-SN, and CEN-DMN density were examined using Group Iterative Multiple Model Estimation, which yields sparse, person-specific networks capturing both shared and individual connectivity structure. At baseline, anxious youth exhibited lower density within-CEN, between CEN-SN, and between CEN-DMN than L/NA youth. Treatment effects differed by intervention: EF-CBT selectively increased (i.e., normalized) CEN-SN density, whereas RMT increased within-CEN density. These findings demonstrate dissociable effects of exposure and relaxation on cognitive control network organization in pediatric anxiety. Exposure-focused CBT uniquely strengthens coordination between control and salience systems, consistent with a mechanism supporting top-down control of threat-related signals during exposure. Network-based measures of cognitive control may help identify mechanistic targets for optimizing and personalizing treatment.

CLINICAL TRIAL NUMBER: NCT02810171.

PMID:41646716 | PMC:PMC12870638 | DOI:10.64898/2026.01.28.26345061

medRxiv [Preprint]. 2026 Jan 13:2026.01.10.26343837. doi: 10.64898/2026.01.10.26343837.

ABSTRACT

BACKGROUND: Auditory hallucinations are among the most disabling symptoms in individuals with schizophrenia (SZ) and are linked to aberrant signaling within deep-striatal circuits, such as the nucleus accumbens (NAc) and caudate head (CH). However, causal tests of striatal involvement have been limited by the inaccessibility of these structures using noninvasive neuromodulatory techniques. Low-intensity focused ultrasound (LIFU) provides millimeter-scale precision capable of modulating deep-brain circuits, but its feasibility and impact on hallucinations in SZ remain unknown.

METHODS: SZ participated in a within-subject cross-over feasibility trial including two active LIFU sessions (NAc, CH) and one sham control (unfocused sonication), spaced one-week apart. Resting-state fMRI and hallucination symptoms were acquired at baseline and immediately post-sonication.

RESULTS: LIFU was delivered safely and well-tolerated in all patients. Acoustic simulations show consistent engagement of both striatal targets across subjects. Clinically, SZ demonstrated significant reductions in hallucination severity following active LIFU to NAc and CH, relative to baseline. Mechanistically, SZ exhibited abnormally high striatal-superior temporal cortex (STC) connectivity at baseline. Immediately after sonication, active LIFU to NAc and CH produced robust reductions in striatal-STC coupling in SZ.

CONCLUSIONS: This first-in-human study demonstrates that deep striatal LIFU is safe, feasible, and produces functional-connectivity changes accompanied by hallucination severity reductions in SZ. The convergence of symptom improvement with reduced striatal-STC coupling provides mechanistic proof-of-concept evidence that this circuit provides a promising biomarker and therapeutic LIFU target in psychosis and motivates larger sham-controlled trials to test the causal role of striatal circuitry in hallucination generation in SZ.

PMID:41646697 | PMC:PMC12870488 | DOI:10.64898/2026.01.10.26343837

Childs Nerv Syst. 2026 Feb 5;42(1):61. doi: 10.1007/s00381-026-07150-x.

ABSTRACT

BACKGROUND: Accurate localization and lateralization of language areas are essential in the preoperative evaluation of children with drug-resistant epilepsy (DRE) to minimize postoperative neurological deficits. Traditional invasive methods such as the Wada test and electrocortical stimulation remain gold standards but present significant limitations, especially in pediatric populations. Noninvasive techniques leveraging blood oxygen level-dependent (BOLD) signal fluctuations, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), offer interesting and convenient alternatives, but clinical evidence is limited. This narrative review aims to synthesize current knowledge on noninvasive BOLD-based imaging techniques, specifically task-based and resting-state fMRI and fNIRS, for language mapping in children with epilepsy.

METHODS: A comprehensive literature search was conducted using PubMed, focusing on studies employing fMRI and fNIRS for language mapping in pediatric epilepsy and cross-referencing. Special consideration was given to higher-impact studies, frequently cited publications, and works by leading experts in the field.

RESULTS: Task-based fMRI remains the clinical standard for language mapping but is frequently compromised by poor task compliance in children. Resting-state fMRI provides a task-free alternative with high sensitivity but often yields broader, bilateral networks that complicate precise lateralization. fNIRS offers a portable and child-friendly option with excellent tolerability but is limited by its spatial resolution and depth penetration. Further standardization of the various data-processing methods used for these modalities is required.

CONCLUSION: BOLD-based noninvasive imaging techniques represent promising advancements in the preoperative evaluation of pediatric epilepsy surgery candidates. Future multicenter studies and the development of pediatric-specific tools are essential to establish standardized clinical use.

PMID:41644798 | DOI:10.1007/s00381-026-07150-x

Sci Rep. 2026 Feb 5. doi: 10.1038/s41598-026-38807-x. Online ahead of print.

ABSTRACT

End-stage renal disease (ESRD) is associated with an increased risk. This study investigates associations between cognitive decline, resting-state networks (RSNs), and biochemical indicators in ESRD patients pre-/post-hemodialysis. 20 hemodialysis (HD) patients and 22 healthy controls underwent resting-state fMRI (rs-fMRI) and neuropsychological assessments. Resting-state networks (RSNs) were extracted via independent component analysis (ICA), with functional connectivity strength compared between pre-/post-HD patients and controls. Correlations between connectivity strength and biochemical indicators were analyzed. Compared to HCs, the post-HD group exhibited significantly decreased FC between the auditory-somatomotor network (t = - 5.120, P < 0.001) and the visual-somatomotor network (t = - 4.199, P < 0.001). In contrast, FC between the default mode and dorsal attention networks was significantly increased (t = 2.908, P = 0.006). While serum electrolytes and iron metabolism markers remained stable post-HD (all P > 0.05), phosphorus levels decreased (P = 0.046), with significant improvements in renal function: eGFR increased from 4.560 ± 1.650 to 16.980 ± 6.428 mL/min, urea, creatinine, and PTH levels decreased (all P < 0.001). Elevated baseline chloride levels were associated with reduced post-HD attention network connectivity (r = -0.758, P < 0.001), while cognitive improvement correlated inversely with baseline connectivity (r = -0.619, P = 0.004) and positively with connectivity plasticity (r = 0.513, P = 0.021). Immediate post-HD changes in resting-state network connectivity were associated with biochemical status and cognitive performance, suggesting potential neural substrates of cognitive dysfunction in ESRD.

PMID:41644743 | DOI:10.1038/s41598-026-38807-x

Psychiatry Res Neuroimaging. 2026 Jan 30;358:112156. doi: 10.1016/j.pscychresns.2026.112156. Online ahead of print.

ABSTRACT

BACKGROUND: Functional connectivity (FC) has been used to identify brain disorders. The present study aimed to identify brain disorders by FC across multiple timescales.

METHODS: We first segmented the resting-state fMRI signals to construct multiple timescale functional connectivity (mFC) between brain regions. Next, we developed a deep multiple instance learning (MIL) approach, namely the Two-stage Multi-stream Network (TMN), to capture spatio-temporal patterns from the mFC. We evaluated the TMN in the ABIDE I dataset and the REST-Meta-MDD dataset. Furthermore, we proposed using the inputXgrad to explain the important features in the model.

RESULTS: We achieved the best performance using the TMN model with mFC. Our findings indicated that mFC outperformed both static FC and the combination of static and dynamic FC in identification tasks. The model's explanation revealed that FC across all timescales contributed to the identification of brain disorders and highlighted the important FC that are strongly associated with these conditions.

LIMITATIONS: The techniques used for data preprocessing can influence the model's performance, and this study requires further validation with a larger patient cohort and a broader range of brain disorders.

CONCLUSIONS: The experimental results demonstrate that brain disorders can be effectively identified using the proposed TMN with mFC.

PMID:41643285 | DOI:10.1016/j.pscychresns.2026.112156

Proc Natl Acad Sci U S A. 2026 Feb 10;123(6):e2526799123. doi: 10.1073/pnas.2526799123. Epub 2026 Feb 5.

ABSTRACT

Deficits in dopamine function cause alterations in episodic memory. Converging evidence implicates dopamine in postencoding hippocampal mechanisms inferred to support long-term memory, though there is a lack of direct evidence in humans. We address this gap using pharmacological functional MRI (fMRI) and positron emission tomography (PET). Using a motivated reward encoding task on and off oral methylphenidate, we tested whether individual differences in baseline dopamine ([11C]raclopride PET D2/3 receptor density) relate to drug-induced changes in hippocampal postencoding processes. Our study focused on healthy older adults, who are among those most vulnerable to memory decline and may benefit from pharmacologically enhancing dopamine. We found that methylphenidate administration was associated with improved memory performance relative to placebo for both high and low reward conditions. Older adults with high receptor density showed greater persistence of hippocampal multivoxel patterns into postencoding rest and stronger hippocampus-midbrain resting-state connectivity following encoding while on methylphenidate. These findings support the view that enhanced dopaminergic tone, verified through PET, directly modulates hippocampal postencoding dynamics in humans. Substantial variation in neurobiological effects was associated with individual differences in baseline dopamine function as older adults with high dopamine receptor density profiles showed preferential benefit of drug on hippocampal function, though these insights are qualified by null associations between memory performance and postencoding hippocampal activity. Individuals with lower dopamine receptor profiles showed preferential benefit of reward incentives suggesting altered sensitivity to extrinsic motivational factors depending on endogenous dopamine function.

PMID:41642987 | DOI:10.1073/pnas.2526799123

Hum Brain Mapp. 2026 Feb 1;47(2):e70465. doi: 10.1002/hbm.70465.

ABSTRACT

Non-primary motor areas, including dorsal premotor cortex (PMd), ventral premotor cortex (PMv), and posterior parietal cortex (PPC), contribute to movement planning, but how these regions differentially shape kinematic features of goal-directed movements, and how this specialization is associated with functional connectivity within the frontoparietal network, remains of interest, particularly in relation to recovery after stroke. We used functional magnetic resonance imaging (fMRI), transcranial magnetic stimulation (TMS), and kinematic assessments to explore how these areas influence reaching performance in neurologically intact adults. Participants performed a goal-directed planar reaching task using the KINARM exoskeleton robot. Brief TMS pulse trains were initiated before movement onset to perturb cortical activity at subthreshold and suprathreshold intensities targeting bilateral PMd, PMv, and dorsomedial superior parietal lobule (SPL) within PPC. Resting-state fMRI quantified functional connectivity among these regions to assess whether connectivity explains stimulation-induced kinematic changes. Relative to the control target within the postcentral sulcus (PCS), subthreshold stimulation of contralateral PMd and PMv reduced reach efficiency and smoothness, while suprathreshold stimulation of contralateral PPC increased deviation error and reduced smoothness. Among ipsilateral targets, PMd showed consistent TMS-induced effects, and was the only target where resting-state connectivity predicted behavioral response. Stronger interhemispheric connectivity in the primary motor cortex and weaker interhemispheric PPC connectivity were associated with greater reductions in straightness and smoothness during subthreshold ipsilateral PMd stimulation. We found that perturbation of premotor and parietal targets led to distinct kinematic effects that varied by site, intensity, and laterality, with premotor stimulation showing the most consistent disruptions at subthreshold intensity and bilateral effects, whereas parietal effects were observed primarily for contralateral stimulation at suprathreshold intensity, and differences in network organization explain variability in behavioral response. Identifying contributions of cortical areas and connectivity patterns may help personalize interventions after stroke. Trial Registration: This study was registered at ClinicalTrials.gov under ID NCT04286516.

PMID:41641924 | DOI:10.1002/hbm.70465

Chin Med J (Engl). 2026 Feb 5. doi: 10.1097/CM9.0000000000004040. Online ahead of print.

ABSTRACT

BACKGROUND: Visual input supports locomotion through sensorimotor integration. However, the neural mechanisms underlying how the brain adapts to degraded vision are not well understood. This study investigated the effects of visual occlusion on interactions between regions within the sensorimotor network.

METHODS: Twelve healthy young adults (8 males, 4 females; mean age 24.0 ±2.1 years) were recruited from the Department of Ophthalmology at Peking University Third Hospital between December 2024 and September 2025. Pattern-reversal visual evoked potentials were recorded under both normal vision and visual occlusion condition (Snellen 20/60 acuity). We acquired resting-state functional magnetic resonance imaging (rs-fMRI) data to calculate the amplitude of low-frequency fluctuations (ALFF) and seed-based functional connectivity (FC) focused on visuomotor integration regions. A one-way repeated-measures analysis of variance was conducted with three within-subject conditions: seated rest, level walking with normal vision, and level walking with visual occlusion.

RESULTS: Stimuli consisted of checkerboard patterns with large (1°) and small (15') checks. Under 1° visual stimulation, visual occlusion prolonged binocular P100 latency (117.00 ± 8.55 ms vs. 111.81 ± 5.12 ms; 116.78 ± 9.79 ms vs. 110.96 ± 4.28 ms; all P <0.05) and reduced N75-P100 amplitude (5.798 ± 2.372 μV vs. 8.613 ± 3.949 μV; 6.230 ± 2.459 μV vs. 7.453 ± 2.692 μV, all P <0.05). For 15' stimulation, occlusion decreased both binocular N75-P100 (5.935 ± 3.500 μV vs. 10.794 ± 5.249 μV; 3.991 ± 1.585 μV vs. 10.361 ± 3.143 μV, all P <0.001) and P100-N135 amplitudes (6.218 ± 3.516 μV vs. 12.499 ± 4.236 μV; 4.427 ± 2.218 μV vs. 10.767 ± 4.904 μV, all P <0.001). Rs-fMRI analysis showed reduced ALFF in the right paracentral lobule after walking (peak Montreal Neurological Institute (MNI) coordinates: 3, -39, 66; P <0.001, F = 14.009). Walking activated multiple visuomotor pathways (all P <0.001), including the bilateral calcarine and middle temporal gyri, the right calcarine and middle frontal gyri, the bilateral supplementary motor area and right cuneus, and the bilateral precentral gyrus and right cerebellar lobule VI. The visual occlusion strengthened FC between the right precentral and the right middle frontal gyri (peak MNI: 27, 57, 27; F = 16.456, P <0.001).

CONCLUSIONS: Basic visuomotor pathways demonstrate consistent activation to maintain locomotion. Increased functional connectivity between the right precentral and middle frontal gyri serves as a compensatory mechanism for reduced visual input.

PMID:41641583 | DOI:10.1097/CM9.0000000000004040

Front Neurol. 2026 Jan 20;17:1688307. doi: 10.3389/fneur.2026.1688307. eCollection 2026.

ABSTRACT

OBJECTIVE: To investigate electroacupuncture (EA)-induced reorganization of voxel-mirrored homotopic connectivity (VMHC) and its association with motor recovery in a rat model of ischemic stroke.

METHODS: Twenty-four female Sprague-Dawley rats were randomized into Sham group, stroke model group and EA group. The EA group received 1-week treatment (2/15 Hz sparse-dense wave, 2 mA, 30 min/day) at GV20. Neurological deficits were assessed using the modified neurological severity score. And resting-state functional magnetic resonance imaging was acquired pre-post-intervention for VMHC analysis. Group differences and VMHC-behavior correlations were evaluated.

RESULTS: EA significantly increased VMHC in subcortical motor regions (p = 0.001, alphasim correction) but decreased VMHC in somatosensory cortex versus untreated stroke. Model group showed progressive VMHC reductions in hippocampus, hypothalamus, and somatosensory cortex. Enhanced internal capsule VMHC correlated with improved Longa scores in EA rats (r 2 = 0.206, p = 0.009).

CONCLUSION: EA promotes motor recovery through frequency-specific bidirectional VMHC modulation. This study elucidates EA's inter-hemispheric connectivity level therapeutic mechanism for stroke rehabilitation.

PMID:41641330 | PMC:PMC12864109 | DOI:10.3389/fneur.2026.1688307

Sci Data. 2026 Feb 4. doi: 10.1038/s41597-026-06734-1. Online ahead of print.

ABSTRACT

We present a new dataset consisting of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) collected from 39 healthy adults in their twenties to forties while performing cognitive tasks (visual oddball and N-back tasks) in addition to resting state. These tasks took place both inside and outside an MR scanner (i.e., simultaneous EEG-fMRI and EEG-only, respectively), enabling direct comparisons across the different recording environments. Moreover, a subset of the participants was in two different MRI scanners, allowing for traveling-subject analyses. In both scanners, we used EEG caps equipped with carbon wire loops to measure motion and ballistocardiogram artifacts for their subsequent removal from raw EEG signals, resulting in a dataset of superior quality compared to previous studies. All the raw data are publicly available for facilitating multimodal neuroimaging research.

PMID:41639123 | DOI:10.1038/s41597-026-06734-1

Neuroimage. 2026 Feb 2:121772. doi: 10.1016/j.neuroimage.2026.121772. Online ahead of print.

ABSTRACT

OBJECTIVES: Chronic ankle instability (CAI) is not only associated with those peripheral neuromuscular impairments but also with the functional changes in the supraspinal regions. Nevertheless, the characteristics of the cortical elements in CAI remain poorly understood. This study aimed to examine the dynamics of resting-state BOLD and ankle-related functional performance in recreational athletes with CAI, as well as explore the associations between neural fluctuations and ankle functional performance.

METHODS: This cross-sectional design study recruited 82 participants, comprising 41 active recreational athletes with CAI (CAI group) and 41 active recreational athletes without CAI (Control group). Data on joint position sense, one-leg standing balance, and resting-state fMRI were collected from both groups. A two-sample t-test was used to determine the difference in amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) between the two groups. Linear regression analysis evaluated the associations between functional performance and dynamics of resting-state BOLD in the two groups.

RESULTS: Compared with control group, athletes with CAI had lower ALFF values in the bilateral supplementary motor area and reduced ReHo values in the right precentral gyrus and postcentral gyrus, while higher ALFF and ReHo values in the right cerebellum. Moreover, athletes with CAI had lower fALFF values in the left superior frontal gyrus and the right superior frontal gyrus than controls. The sway velocities of center of pressure in the one-leg standing with eyes closed condition were negatively associated with ALFF and ReHo values in the right cerebellum cluster.

CONCLUSIONS: Athletes with severely right-sided CAI had different neural fluctuations compared with controls. Elevated ALFF and ReHo values in the right cerebellum cluster were associated with balance control, suggesting that high ipsilateral cerebellar activity and homogeneity may compensate for balance control in athletes with CAI.

PMID:41638415 | DOI:10.1016/j.neuroimage.2026.121772

Neuroimage. 2026 Feb 2:121769. doi: 10.1016/j.neuroimage.2026.121769. Online ahead of print.

ABSTRACT

Sleep deprivation (SD) significantly impacts brain function, particularly through disruption of the glymphatic system, an essential mechanism for cerebral metabolic waste clearance dependent on cerebrospinal fluid (CSF) dynamics. Recent advances link CSF flow to global brain activity, measurable via global blood-oxygenation-level-dependent (gBOLD) signals. However, how gBOLD-CSF coupling changes during prolonged wakefulness remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we investigated how 36-hour sleep deprivation affects gBOLD-CSF coupling in healthy participants. We observed a significant transient increase in gBOLD-CSF coupling strength as sleep deprivation progressed, peaking after approximately 30 hours of wakefulness. Importantly, changes in coupling strength correlated quantitatively with heightened subjective sleep pressure but not with vigilance performance. Furthermore, SD induced a temporary phase shift in CSF signal timing relative to gBOLD, indicating disrupted temporal coordination. These results suggest that SD triggers both a transient enhancement and a temporal instability in neuro-fluid coupling, reflecting a biphasic modulation of brain-CSF coupling linked to glymphatic-related dynamics. Our findings reveal novel compensatory adjustments within the glymphatic system during prolonged wakefulness, advancing our understanding of the physiological underpinnings linking sleep loss, metabolic clearance, and brain function, with potential implications for cognitive health and neurodegenerative disease risk.

PMID:41638414 | DOI:10.1016/j.neuroimage.2026.121769

Brain Lang. 2026 Feb 3;275:105720. doi: 10.1016/j.bandl.2026.105720. Online ahead of print.

ABSTRACT

Speech disorders are highly prevalent among patients with Parkinson's disease (PD). Although insights into the neural substrates of these disorders have been achieved since the introduction of functional magnetic resonance imaging (fMRI), the evidence has never been analyzed altogether. This review aims to summarize and discuss the findings from the two most common approaches of fMRI: task-based and resting-state. We grouped the evidence into four statements: (i) speech disorders in patients with PD are linked with functional changes in the speech production network (SPN), (ii) PD alters the SPN even before the onset of speech disorders, (iii) levodopa have a discrete effect on the SPN functioning, and (iv) speech therapy in patients with PD can induce changes on the activity of the SPN. Limitations of current evidence and future directions in the field are also discussed.

PMID:41638063 | DOI:10.1016/j.bandl.2026.105720