Most recent paper

Neurobiol Dis. 2026 Jan 15:107274. doi: 10.1016/j.nbd.2026.107274. Online ahead of print.

ABSTRACT

BACKGROUND: Essential tremor (ET) is one of the most prevalent neurological diseases and is recognized as a disorder involving multiple neural network dysfunctions. Previous resting-state fMRI studies in ET ignored brain network important dynamic nature. This study aimed to investigate the alterations of dynamic functional connectivity (DFC) and its functional topology in ET.

METHODS: Resting-state fMRI data were collected from 144 ET and 131 normal controls (NC). Sliding-window approach with K-means clustering algorithm was used to identify dynamic functional states and graph theory analysis was performed to explore related topological organization of each state in ET.

RESULTS: Two distinct and switchable DFC states (State 1: "cerebrum-dominant" state, with hyperconnected functional architecture in cerebrum; State 2: "cerebellum-dominant" state, with higher functional independence in cerebellum) were identified. Compared to NC, higher fractional windows and longer mean dwell time of cerebellum-dominant state, and fewer state transitions were observed in ET. Higher fractional windows and longer dwell time of cerebellum-dominant state were correlated with more severe tremor. In the topological analysis, compared to NC, ET demonstrated decreased nodal degree centrality and nodal efficiency in cerebrum regions (e.g., orbital inferior frontal gyrus and temporal pole) within two states, but increased nodal betweenness centrality in cerebellum regions (e.g., Cerebellum Crus 2 and Vermis) within cerebellum-dominant state.

CONCLUSIONS: These findings revealed that ET was characterized by prolonged cerebellum-dominant state and disrupted functional topology within both states, providing novel insights for better understanding the fundamental neurobiological mechanisms in ET.

PMID:41547468 | DOI:10.1016/j.nbd.2026.107274

BMC Gastroenterol. 2026 Jan 16. doi: 10.1186/s12876-026-04615-w. Online ahead of print.

ABSTRACT

BACKGROUND: Crohn's disease (CD) and ulcerative colitis (UC), the two major forms of inflammatory bowel disease (IBD), are associated with emotional disturbances, but their shared and distinct neurobiological substrates remain unclear. This neuroimaging study aimed to characterize shared and distinct patterns of spontaneous neural activity in CD and UC patients using resting-state functional MRI (rs-fMRI).

METHODS: Using cortical surface-based analysis of rs-fMRI data, we compared intrinsic neural activity, measured by amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo), in 248 patients with IBD (180 CD, 68 UC) and 190 healthy controls (HC), controlling for gray matter volume. Demographic, clinical, and neuropsychological data were collected. Group comparisons and correlation analyses were performed.

RESULTS: Compared to HC, both CD and UC patients exhibited reduced ALFF and ReHo in bilateral somatosensory and motor cortices. Disease-specific patterns emerged: CD showed lower ReHo in lateral temporal cortices, while UC demonstrated higher ReHo in medial temporal and superior parietal regions. Correlation analyses revealed that in CD, motor cortex activity was linked to systemic symptoms and emotional function, whereas in UC, it correlated primarily with somatization.

CONCLUSION: This study identifies a common neural signature of sensory-motor dysfunction in IBD, alongside subtype-specific cortical patterns. By directly comparing CD and UC with a multimodal, surface-based approach and controlling for structural differences, our findings provide novel evidence for distinct brain-gut pathophysiology, highlighting neuroimaging as a potential tool for mechanistic insight and patient stratification.

PMID:41545829 | DOI:10.1186/s12876-026-04615-w

Npj Ment Health Res. 2026 Jan 16;5(1):2. doi: 10.1038/s44184-025-00182-2.

ABSTRACT

Antidepressant efficacy for major depressive disorder (MDD) remains limited, with the neural mechanisms underlying treatment response poorly understood. The default mode network (DMN), particularly the connectivity between the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC), has been implicated in MDD pathophysiology and may be linked to treatment outcomes. However, its potential as a biomarker for antidepressant response has not been validated. Here, we investigate the relationship between DMN connectivity and antidepressant treatment response in MDD. Resting-state fMRI data from four large MDD cohorts (n = 4271) were analyzed using Granger causality to examine directional effective connectivity (EC) within the DMN. Linear mixed-effects models compared EC between recurrent MDD patients, first-episode drug-naïve patients, and healthy controls. We also examined associations between EC, medication use, illness duration, depressive symptoms, and treatment outcomes. Additionally, Support Vector Machine (SVM) classifiers and support vector regression (SVR) were trained using EC from mPFC to PCC to predict treatment response. Our results revealed that recurrent MDD patients exhibited significantly reduced EC from mPFC to PCC compared to healthy controls and first-episode patients, with this reduction correlating with antidepressant medication use and illness duration. Importantly, DMN connectivity was associated with treatment improvement rather than core depressive symptoms, including suicide, anhedonia, or emotional blunting. Crucially, EC from mPFC to PCC predicted antidepressant treatment response, and SVM classifiers demonstrated high predictive accuracy for therapeutic outcomes. In conclusion, reduced EC from mPFC to PCC may serve as a biomarker for antidepressant treatment response in MDD, offering insights into MDD neurobiology and supporting the clinical potential of DMN connectivity measures for guiding treatment decisions. The SAINT, Xijing_QG, and Xijing_KG datasets were approved by the Ethics Committee of the First Affiliated Hospital, Fourth Military Medical University (approval numbers: KY20202066-F-1, XJLL-KY20222111, and KY20222165-F-1, respectively) and registered with clinicaltrials.gov (identifiers: NCT04653337, NCT05577481, and NCT05544071, respectively).

PMID:41545765 | DOI:10.1038/s44184-025-00182-2

Neuroimage. 2026 Jan 14:121722. doi: 10.1016/j.neuroimage.2026.121722. Online ahead of print.

ABSTRACT

Cognitive control enables individuals to adapt to the ever-changing environmental demands. The dorsal anterior cingulate cortex (dACC) and the dorsolateral prefrontal cortex (dlPFC) are key regions of the cognitive control network, activated during cognitively demanding tasks. In contrast, the entertaining and habitual nature of short-video consumption for leisure shifts neural processing toward emotional engagement and immediate gratification, contributing to excessive use and diminished self-control in some individuals. This raises a critical question: Does short-video viewing suppress cognitive control regions, and what neurochemical factors may underlie individual differences in this process? To address this question, this preregistered study used proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate and γ-aminobutyric acid (GABA) concentrations in the dACC at rest, and employed functional magnetic resonance imaging (fMRI) to examine dACC and dlPFC activity during free viewing of short videos in 56 young adults. We found that both the dACC and the dlPFC exhibited significant deactivation in response to preferred videos that were watched to completion, compared to less-preferred videos that were terminated early. Moreover, resting-state glutamate levels in the dACC were associated with the magnitude of this deactivation, with higher glutamate concentrations associated with less suppression of both dACC and dlPFC activity. Additionally, functional connectivity between the dACC and dlPFC increased during video viewing, particularly for preferred videos. By integrating fMRI with 1H-MRS, our study provides novel evidence that immersive viewing of preferred short videos deactivates the cognitive control network and that individual differences in this deactivation are linked to glutamate metabolism. These findings enhance our understanding of how digital media consumption interacts with neurochemical processes to influence self-regulation. Our study offers new insights into the neural mechanisms underlying short-video engagement and has implications for understanding excessive digital media use.

PMID:41544906 | DOI:10.1016/j.neuroimage.2026.121722

Neuroscience. 2026 Jan 14:S0306-4522(26)00038-2. doi: 10.1016/j.neuroscience.2026.01.014. Online ahead of print.

ABSTRACT

This study aims to explore the role of the central nervous system network outside the auditory system in the development process of noise - induced central injury. A noise-exposed rat model was established with unilateral narrow-band noise. Auditory brainstem response (ABR) measured hearing thresholds at Click and 8, 16, 24, 32 kHz pre- and post-noise exposure. Experimental rats were split into transcutaneous auricular vagus nerve stimulation (ta-VNS) and sham subgroups for 2-week intervention. Resting-state fMRI (rs-fMRI) was performed on all groups (ta-VNS, sham, control) post-noise exposure and 2 weeks post-intervention. After noise exposure, 22 rats had elevated hearing thresholds at 8, 24, 32 kHz. fMRI revealed increased ALFF/ReHo in the entorhinal cortex, amygdalar cortex, and hippocampus, decreased values in the prelimbic cortex, basal forebrain, striatum, and cingulate cortex, and enhanced cingulate cortex-basal forebrain functional connectivity. The rats were divided into ta-VNS (n = 10) and sham (n = 12) subgroups for 2-week intervention. Compared with the control group (n = 9), both subgroups showed similar brain activation/inhibition in regions like the entorhinal cortex pre- vs. post-intervention. However, the ta-VNS group reversed noise-induced reduced neural activity in the prelimbic cortex and basal forebrain, and significantly enhanced their functional connectivity. Noise exposure increased entorhinal cortex, hippocampus, and amygdala activity in rats, potentially linked to aversive emotions and abnormal auditory memory. The prelimbic cortex-centered network may gate noise-induced aversive perception, with cingulate cortex activity/connectivity disrupted. ta-VNS may alleviate such perception by reversing reduced neural activity in gating-related regions and enhancing their connectivity, plus strengthening brainstem-limbic and brainstem-cerebellum functional links.

PMID:41544840 | DOI:10.1016/j.neuroscience.2026.01.014

J Cereb Blood Flow Metab. 2026 Jan 16:271678X251413924. doi: 10.1177/0271678X251413924. Online ahead of print.

ABSTRACT

Aerobic exercise training promotes cardiovascular, brain and cognitive health. Regular exercise is associated with higher cardiorespiratory fitness, commonly assessed by peak oxygen uptake (VO2peak) during maximal effort testing. Higher cardiorespiratory fitness has been linked to preserved brain health, particularly higher gray matter volume and perfusion. The brain relies heavily on oxidative metabolism, yet the relationship between cardiorespiratory fitness and brain oxidative metabolism remains underexplored. This study investigated the association between VO2peak and two key cerebral metabolic parameters: the cerebral metabolic rate of oxygen consumption (CMRO2) and oxygen extraction fraction (OEF), which represents the balance between cerebral blood flow (CBF) and CMRO2. Thirty-seven healthy adults aged ⩾50 underwent maximal cardiopulmonary exercise testing for VO2peak assessment. Neuroimaging included dual calibrated functional MRI (dc-fMRI) and quantitative susceptibility mapping (QSM). Higher VO2peak correlated positively with higher CBF across whole-brain gray matter but showed no relationship with CMRO2. Conversely, higher VO2peak negatively correlated with lower OEF from both dc-fMRI and QSM. These findings suggest that greater cardiorespiratory fitness enhances cerebral perfusion without changing resting metabolic rate in healthy older adults, resulting in a reduced oxygen extraction. These results are consistent with exercise yielding improved vascular-metabolic coupling, which would reduce the likelihood of transient hypoxic episodes.

PMID:41543005 | DOI:10.1177/0271678X251413924

J Magn Reson Imaging. 2026 Jan 16. doi: 10.1002/jmri.70231. Online ahead of print.

ABSTRACT

BACKGROUND: FDG-PET aids presurgical epilepsy evaluation but is limited by access and radiation exposure.

PURPOSE: To evaluate synthetic FDG-PET generated from T1-weighted imaging and resting-state fMRI metrics.

STUDY TYPE: Retrospective.

POPULATION: 481 participants underwent simultaneous FDG PET/MR. Internal cohort: 311 epilepsy patients split into training/validation/internal test sets (n = 249/31/31; age 18.79 ± 16.33/22.20 ± 11.21/21.65 ± 17.62 years; male/female 145/104, 13/18, 22/9). External cohort: 115 temporal lobe epilepsy patients (age 25.36 ± 10.95 years; male/female 68/47) and 55 healthy controls (age 27.62 ± 5.82 years; male/female 24/31); 92 had surgery with 1-year outcome.

FIELD STRENGTH: Hybrid PET/MR at 3.0 T; gradient-echo T1WI, echo-planar imaging and resting-state BOLD gradient-echo EPI.

ASSESSMENT: Performance was assessed using SSIM, PSNR, MSE, NRMSE, SUVR correlation, and Bland-Altman analysis. Three blinded readers performed visual quality grading and detection of temporal lobe hypometabolism. Hippocampal radiomics was used for classification of hippocampal sclerosis and Engel outcome.

STATISTICAL TESTS: t-tests, chi-square tests, Pearson correlation, Kolmogorov-Smirnov tests, DeLong tests, and false discovery rate correction.

RESULTS: Excellent/Good visual ratings occurred in 82.8% (166/201), with Fleiss' κ = 0.42. SSIM was 0.98 ± 0.01 (internal) and 0.97 ± 0.01 (external); PSNR was 66.66 ± 1.25 and 64.16 ± 1.83, respectively. SUVR correlation with ground-truth PET was r = 0.94 (internal) and r = 0.89 (external); Bland-Altman bias was -0.02 (95% limits of agreement: -0.22 to 0.18) internally and -0.00002 (95% limits: -0.35 to 0.35) externally. Detection accuracy for temporal hypometabolism was 90.3% (internal; κ = 0.735) and 87.1% (external; κ = 0.758). Radiomics AUCs using synthetic PET were 0.72 (95% CI: 0.62-0.83) for hippocampal sclerosis versus healthy controls and 0.77 (95% CI: 0.67-0.87) for Engel IA versus IB-IV; DeLong tests versus ground-truth PET were non-significant (p = 0.56 and p = 0.48).

CONCLUSION: Multisequence MRI-based synthetic PET showed high agreement with ground-truth PET across image-quality and quantitative SUVR metrics, providing a PET-like metabolic surrogate when FDG-PET is unavailable or impractical.

LEVEL OF EVIDENCE: Evidence Level 3.

STAGES OF TECHNICAL EFFICACY: Stage 3.

PMID:41542825 | DOI:10.1002/jmri.70231

medRxiv [Preprint]. 2026 Jan 8:2026.01.06.26343455. doi: 10.64898/2026.01.06.26343455.

ABSTRACT

BACKGROUND: Functional neurological disorder (FND) is associated with alterations in functional brain networks, yet relationships between peripheral autonomic physiology and brain architecture remain poorly characterized. This pilot study examined associations between cardiac autonomic metrics and resting-state functional connectivity (rsFC) in FND.

METHODS: Twenty females with FND and 23 age-matched female psychiatric controls (PCs) completed questionnaires, 10-min resting photoplethysmography recordings, and same-day resting-state fMRI. Interbeat interval (IBI) and heart rate variability (HRV) metrics were extracted. Whole-brain rsFC was quantified using weighted-degree [centrality]. Within-group analyses tested associations between cardiac autonomic metrics and weighted-degree rsFC separately in FND and PC cohorts, adjusting for age, head motion, and antidepressant/β-blocker use - while applying a cluster-wise correction.

RESULTS: Cardiac (IBI and HRV) metrics did not differ between FND and PC cohorts, and these metrics did not correlate with FND symptom severity, somatic symptom burden, affective symptoms, or childhood trauma. In FND, shorter IBI (i.e., faster resting heart rate) correlated with increased weighted-degree rsFC in bilateral supplementary motor area (SMA) and right precentral/superior frontal regions, whereas higher HRV primarily correlated with decreased weighted-degree rsFC in the bilateral SMA, mid-cingulate cortex, and right amygdala, anterior insula, and lateral orbitofrontal cortex. In PCs, autonomic-rsFC associations were more spatially restricted to the anterior/mid-cingulate and SMA.

CONCLUSION: In FND, individual differences in resting autonomic physiology related to the centrality of brain areas that are part of the central autonomic, salience, and allostatic-interoceptive networks. These findings suggest that the relationship between autonomic physiology and network architecture may be important in FND.

PMID:41542673 | PMC:PMC12803374 | DOI:10.64898/2026.01.06.26343455

bioRxiv [Preprint]. 2026 Jan 9:2026.01.08.694967. doi: 10.64898/2026.01.08.694967.

ABSTRACT

Functional MRI-based graph theory has provided profound insights into the brain's functional organization, yet the neuroenergetic meaning of widely used graph-theoretical metrics remains poorly understood. Although resting-state research suggests a positive coupling between network topology and glucose metabolism, it remains unclear whether this relationship reflects a general principle of brain organization or a state-specific phenomenon. Here, we test the neuroenergetic interpretability of nodal graph-theoretical metrics by linking complex network topology to cerebral glucose consumption across diverse brain states. Leveraging simultaneous functional PET-MRI, we directly compare state-dependent fluctuations in glucose consumption and network topology during sensory, cognitive, and arousal conditions. We further assess metabolic-topological couplings in disease through a meta-analysis of resting-state FDG-PET and fMRI studies involving Alzheimer's disease, Parkinson's disease, major depressive disorder, and schizophrenia. Our results show that nodal graph-theoretical metrics exhibit state- and network-dependent metabolic associations, with coupling patterns diverging across experimental and disease contexts. Notably, frontoparietal and attentional networks show more conserved metabolic-topological coupling than other large-scale networks across states. These findings underscore a dynamic, complex interplay between metabolic demand and complex network organization, highlighting the need for a nuanced interpretation of the energetic underpinnings of nodal graph-theoretical metrics in health and disease.

PMID:41542587 | PMC:PMC12803132 | DOI:10.64898/2026.01.08.694967

bioRxiv [Preprint]. 2026 Jan 5:2026.01.05.697753. doi: 10.64898/2026.01.05.697753.

ABSTRACT

Brain regions perform distinct computations, and their signals propagate through the whole-brain white matter network. Yet, mathematical models that describe this signal propagation via purely passive diffusion can predict a considerable amount of the observed functional connectivity between regions. This raises a critical question: if so much functional connectivity can be explained by a passive process, how can we isolate the active process? Here, we calculate in closed-form an estimate for such an active signal in functional MRI by spatially deconvolving the effect of passive signal spread over the brain's structural connectivity using a higher-order network diffusion (HONeD) model. Across 770 Human Connectome Project subjects, we show that the resulting HONeD-innovation (HONeD-in) signal 1) sparsifies functional connectivity while retaining a well-connected network, 2) remodels resting-state networks (RSNs), 3) mixes the unimodal--multimodal hierarchical organization of RSNs into a circle with no clear hierarchy, and 4) deblurs task-activation maps. Together, our results highlight HONeD deconvolution as a generalizable new way to study resting-state and task fMRI brain signals.

PMID:41542509 | PMC:PMC12803073 | DOI:10.64898/2026.01.05.697753

bioRxiv [Preprint]. 2026 Jan 9:2025.12.22.695992. doi: 10.64898/2025.12.22.695992.

ABSTRACT

Discrimination is a chronic stressor linked to adverse health outcomes, particularly in racial and ethnic minorities. Understanding associations between early discrimination and the brain in childhood may help identify mechanisms through which discrimination impacts future health. Data from 4512 children (ages 9-11) and a subsample of Black, Indigenous, and People of Color (BIPOC; N = 1567) from the Adolescent Brain and Cognitive Development (ABCD) Study® was used to create linear mixed-effects models that evaluated associations between Perceived Discrimination (PD) and amygdala resting-state fMRI connectivity (AC) to the salience network (SN), default mode network (DMN), and thalamus. PD was measured using the youth self-reported PD Scale. Results indicated that greater PD significantly predicted greater AC to the right thalamus in our full sample. In secondary analyses, environmental and behavioral factors were evaluated as potential moderators for associations significant at least at a trend level in both our full sample and BIPOC subsample. In our BIPOC subsample, traumatic events experienced moderated the relationship between PD and AC to the anterior cingulate cortex (ACC; SN), such that greater traumatic experiences predicted stronger positive associations between PD and this connection. Results suggest PD impacts neural connections in early life, highlighting the need to consider the impact of discrimination on risk for psychopathology.

PMID:41542413 | PMC:PMC12803270 | DOI:10.64898/2025.12.22.695992

Nat Ment Health. 2025 Nov;3(11):1407-1416. doi: 10.1038/s44220-025-00525-0. Epub 2025 Oct 20.

ABSTRACT

Rumination, or perseverative negative self-referential thinking, is a hallmark of depression. In adults, a dynamic resting-state fMRI model of trait rumination was recently identified through predictive modelling. In adolescents, a development period during which rumination and depression increase, the neurobiological correlates of ruminative thinking are less clear. In the current preregistered study, we examine dynamic connectivity correlates of self-reported rumination in the largest sample of adolescents to date (n = 443, containing clinical and non-clinical individuals). Notably, the adult model failed to generalize to our sample. In addition, linear models trained on default-mode network (DMN) connectivity, as well as whole-brain connectome models, failed to generalize to held-out data. In an exploratory random forest analysis, we found significant prediction performance of a model where increased variability between DMN-cerebellum, DMN-dorsal attention network, and DMN-DMN connections was nominally associated with higher rumination. However, the model did not generalize to an external sample with lower rumination scores and a distinct scanner protocol. Our findings illustrate the difficulty of characterizing the neurodevelopment of risk factors for depression.

PMID:41541224 | PMC:PMC12803745 | DOI:10.1038/s44220-025-00525-0

Imaging Neurosci (Camb). 2026 Jan 13;4:IMAG.a.1065. doi: 10.1162/IMAG.a.1065. eCollection 2026.

ABSTRACT

Recent advancements in connectome analyses have enabled more precise measurements of brain network integrity. Identifying neural measures that can operate as mechanisms of cognitive reserve is integral for the study of individual variability in age-related cognitive changes. In the present study, we tested the hypothesis that network resilience, or the network's ability to maintain functionality when facing internal or external perturbations that cause damage or error, can function as a cognitive reserve (CR) candidate, modifying the relationship between cognitive and brain changes in a lifespan cohort of cognitively healthy adults. One hundred cognitively healthy older adults from the Reference Ability Neural Network (RANN) longitudinal lifespan cohort (50-80 years) underwent resting-state fMRI and neuropsychological testing at baseline and 5-year follow-up. Using undirected weighted adjacency matrices created from the Schaefer et al. (2018) 400-parcellation atlas and 19 additional subcortical regions (419 nodes in total), whole-brain network resilience was assessed through a targeted attack approach, where nodes were sequentially removed by nodal strength and resilience defined as the iteration of the steepest slope in the largest connected component (LCC) decay. We observed that network resilience moderated the effect of cortical thickness (CT) changes on longitudinal changes in Fluid Reasoning performance, even after adjusting for baseline differences, demographic factors, and the initial LCC of the unlesioned matrix, indicating that individuals with greater resilience were less sensitive to the effect of cortical thickness changes on changes in cognition. These findings support the use of targeted attack as a measure of cognitive reserve, suggesting that higher network resilience may allow individuals with reduced brain integrity to better cope with structural loss and maintain cognitive function.

PMID:41541057 | PMC:PMC12801055 | DOI:10.1162/IMAG.a.1065

Appetite. 2026 Jan 13:108456. doi: 10.1016/j.appet.2026.108456. Online ahead of print.

ABSTRACT

Eating less in response to negative emotions, called emotional undereating (EUE), is common in children, but research on the etiology of these behaviors is in its infancy. 91 children (aged 9-12, 46 females) completed EUE subscale of Children Eating Behavior Questionnaire and underwent resting-state fMRI. Of these, 43 participants also completed arrow task and 78 were followed up one year later. Compared to children with low-EUE, those with high-EUE exhibited fewer errors but longer reaction times, indicating over-control and reduced flexibility. Additionally, children with high-EUE revealed decreased resting-state functional connectivity (rsFC) within the prefrontal cortex and altered connectivity of insula. Notably, the rsFC between the insula and the temporal lobe could mediate the relationship between EUE and arrow task performance and positively predicted the performance one year later. These findings identify a potential stable neural marker of impaired cognitive control in children with EUE and provide new insights into the neurobiological basis of emotional undereating in childhood.

PMID:41539532 | DOI:10.1016/j.appet.2026.108456

Bone. 2026 Jan 13:117774. doi: 10.1016/j.bone.2025.117774. Online ahead of print.

ABSTRACT

Electroacupuncture has demonstrated established efficacy in treating postmenopausal osteoporosis, yet the central mechanisms underlying its action via the brain-bone axis remain incompletely understood. This study employed multimodal resting-state functional magnetic resonance imaging to investigate neurofunctional changes induced by electroacupuncture in a rat model of postmenopausal osteoporosis. Twenty-four female Sprague-Dawley rats were randomly allocated to electroacupuncture, sham, and model (ovariectomized) groups. The electroacupuncture group received an 8-week intervention at acupoints GB30, GB34, and GB39. We assessed brain function through amplitude of low-frequency fluctuation, regional homogeneity, and region-of-interest functional connectivity, while simultaneously measuring serum bone turnover markers via enzyme-linked immunosorbent assay. Our results demonstrated that electroacupuncture significantly improved bone microstructure and reduced bone resorption marker levels. Neuroimaging revealed enhanced cerebellar neural activity which correlated negatively with bone resorption, alongside decreased neural synchronization in the entorhinal cortex. Furthermore, strengthened functional connectivity between entorhinal and visual cortices positively correlated with bone formation markers, while weakened somatosensory-cerebellar connectivity correlated with reduced bone resorption. Bayesian mediation analysis provided strong statistical evidence for the role of the entorhinal-visual pathway involvement in bone formation regulation and cerebellar mediation of bone resorption suppression. These findings systematically reveal the association between electroacupuncture-induced brain functional reorganization and bone metabolic improvements, offering new insights into the role of the brain-bone axis in osteoporosis management.

PMID:41539419 | DOI:10.1016/j.bone.2025.117774

Imaging Neurosci (Camb). 2026 Jan 12;4:IMAG.a.1092. doi: 10.1162/IMAG.a.1092. eCollection 2026.

ABSTRACT

To improve the clinical utility of resting-state fMRI (rs-fMRI), enhancing its interpretability is paramount. Establishing links with electrophysiological activities remains the benchmark for understanding the neuronal basis of rs-fMRI signals. Existing research, while informative, suffers from inconsistencies and a limited scope of rs-fMRI metrics (e.g., seed-based functional connectivity). Phenotypic variables like sex and age are suspected to obscure reliable fMRI-electroencephalography (EEG) associations. A major contributing factor to these inconsistencies may be the neglect of macrovascular correction in rs-fMRI metrics. Given that macrovascular contributions can inflate rs-fMRI connectivity and power, they may lead to misleading fMRI-EEG associations that do not reflect genuine neuronal underpinnings. In this study, we addressed this by applying macrovascular correction and performing a systematic, inter-participant analysis of multiple rs-fMRI and EEG metrics. Our key findings are: (1) macrovascular correction enhances the relationship between EEG and rs-fMRI metrics and improves model fit in many instances; (2) sex significantly modulates EEG-fMRI associations; and (3) EEG complexity is significantly associated with resting-state functional activity (RSFA). This research provides crucial insights into the interplay between rs-fMRI and EEG, ultimately improving the interpretability of rs-fMRI measurements and building upon our prior work linking fMRI and metabolism.

PMID:41537053 | PMC:PMC12797145 | DOI:10.1162/IMAG.a.1092

Imaging Neurosci (Camb). 2026 Jan 12;4:IMAG.a.1091. doi: 10.1162/IMAG.a.1091. eCollection 2026.

ABSTRACT

Understanding how the older adult brain sustains cognitive flexibility remains a central question in aging research. Here, we analyzed resting-state fMRI data from the population-based CamCAN database (N = 628; age 18-88) and applied structural balance theory to measure functional network energy, a graph-theoretical proxy of network flexibility. In line with the SENECA model, our findings highlight midlife as a critical transition period: network energy is redistributed along the sensory-transmodal hierarchy, shifting from higher-level networks (DMN-FPN) to lower-level networks (SMN, CON, Auditory, Visual, Language). This reorganization (i) helps preserve the global wiring economy across the lifespan, hinting at an allostatic mechanism (i.e., stability through change) regulated by anti-correlated dynamics; and (ii) may support embodied semantic strategies in older adulthood, leveraging more predictive processing to sustain cognitive flexibility at lower costs. Taken together, our study reframes healthy neurocognitive aging as an allostatic process and provides a reference for extending the SENECA model to metabolism and neuropathology.

PMID:41537050 | PMC:PMC12797148 | DOI:10.1162/IMAG.a.1091

Netw Neurosci. 2026 Jan 8;10(1):80-92. doi: 10.1162/NETN.a.504. eCollection 2026.

ABSTRACT

Decades of neuroimaging have revealed that the functional organization of the brain is roughly consistent across individuals, and at rest, it resembles group-level task-evoked networks. A fundamental assumption in the field is that the functional specialization of a brain region arises from its connections to the rest of the brain, but limitations in the amount of data that can be feasibly collected in a single individual leave open the following question: Is the association between task activation and connectivity consistent across the brain and many cognitive tasks? To answer this question, we fit ridge regression models to activation maps from 33 cognitive domains (generated with NeuroQuery) using resting-state functional connectivity data from the Human Connectome Project as the predictor. We examine how well functional connectivity fits activation and find that all regions and all cognitive domains have a very robust relationship between brain activity and connectivity. The tightest relationship exists for higher order, domain-general cognitive functions. These results support the claim that connectivity is a general organizational principle of brain function by comprehensively testing this relationship in a large sample of individuals for a broad range of cognitive domains and provide a reference for future studies engaging in individualized predictive models.

PMID:41536424 | PMC:PMC12798649 | DOI:10.1162/NETN.a.504

Psychiatry Res Neuroimaging. 2026 Jan 8;357:112139. doi: 10.1016/j.pscychresns.2026.112139. Online ahead of print.

ABSTRACT

BACKGROUND: Opioid use disorder (OUD) is characterized by intense cue-induced craving and high relapse risk. This longitudinal fMRI study investigated whether oral naltrexone (50mg/day) (oral-NTX) modulates neural and behavioral responses to opioid cues, as well as resting-state brain connectivity.

METHODS: Thirty male patients with moderate-severe OUD underwent fMRI during an opioid-versus-neutral image task at baseline and after 2 weeks of oral-NTX treatment. The DDQ and OCDUS were administered for craving assessment. Task fMRI data was analyzed with linear mixed-effects models (3dLME). Resting-state fMRI was analyzed for ROI-to-ROI functional connectivity changes in key craving-related regions.

RESULTS: Oral_NTX significantly reduced both DDQ and OCDUS scores (p<0.01). Task-based fMRI revealed significant reductions in cue-induced activation in the anterior cingulate cortex (ACC) and cerebellum (whole-brain p<0.05, cluster-corrected). ROI analyses confirmed pre-to-post decreases in ACC and cerebellar activation (t>3.5, p<0.05). Larger craving reductions correlated with greater left superior temporal deactivation (t≈1.97, p<0.05). Resting-state connectivity analysis showed significant attenuation of intrinsic functional coupling between ACC-insula, nucleus accumbens (NAc)-amygdala, and cerebellum-hippocampus (p<0.05). These decreases complement task findings, indicating widespread dampening of salience and reward network interactions following oral-NTX.

CONCLUSION: Oral-NTX reduces cue-driven activation in cortical and cerebellar regions while dampening resting-state connectivity within craving circuits.

PMID:41534246 | DOI:10.1016/j.pscychresns.2026.112139

Diabetes Obes Metab. 2026 Jan 14. doi: 10.1111/dom.70476. Online ahead of print.

ABSTRACT

AIMS: Obesity involves both metabolic and neural dysfunction, yet the temporal dynamics of brain connectivity remain unclear. This study applied dynamic functional network connectivity (dFNC) analysis to reveal time-varying brain network patterns in obesity.

MATERIALS AND METHODS: Eighty-three individuals with obesity and 40 normal-weight controls underwent resting-state functional magnetic resonance imaging. After preprocessing and group independent component analysis, dFNC was estimated using a sliding-window approach and clustered into distinct connectivity states. Temporal metrics (fraction time, dwell time and transitions) were compared between groups, and correlations with clinical characteristics were analysed.

RESULTS: Three recurring connectivity states were identified. Compared with controls, individuals with obesity showed enhanced coupling among the default mode, attention and visual networks, with reduced network flexibility-manifested as prolonged dwell time and fewer transitions. Uncontrolled eating correlated positively with time spent in maladaptive states, whereas cognitive restraint was negatively associated with participation in integrative states.

CONCLUSIONS: Obesity is characterised by state-dependent reorganisation of large-scale brain networks and diminished temporal flexibility. These dynamic connectivity alterations are closely related to eating behaviour and metabolic characteristics, suggesting that dFNC provides a valuable neuroimaging framework for understanding impaired self-regulation in obesity and for guiding future intervention studies.

PMID:41532333 | DOI:10.1111/dom.70476