Most recent paper

Med Image Comput Comput Assist Interv. 2026;15971:109-119. doi: 10.1007/978-3-032-05162-2_11. Epub 2025 Sep 19.

ABSTRACT

We propose a graph information compression framework, called Behavior-Informed Subgroup-consistent Connectome Template (BISCoT), that learns interpretable functional subnetworks from resting-state fMRI (rs-fMRI) connectivity, which simultaneously capture the heterogeneity of a diverse patient cohort. BISCoT uses multidimensional behavioral profiles to guide the decomposition of a rs-fMRI connectivity matrices into sparse yet representative subnetworks that are consistent within behavioral sub-groups. In particular, our framework adopts a graph convolution network to capture local connectivity features and applies a subgroup-informed pooling process to extract the final subnetworks. We evaluate BISCoT on an in-house dataset of individuals with autism spectrum disorder and demonstrate that the learned subnetworks improve the performance of multiple downstream prediction tasks. In addition, BISCoT extracts consistent connectivity "templates" at the subgroup level, which allows for interpretable biomarker identification.

PMID:41987934 | PMC:PMC13078116 | DOI:10.1007/978-3-032-05162-2_11

Hum Brain Mapp. 2026 Apr 1;47(5):e70496. doi: 10.1002/hbm.70496.

ABSTRACT

Autism spectrum disorder (autism) and schizophrenia spectrum disorders (schizophrenia) exhibit overlapping social and neurocognitive impairment and considerable neurobiological heterogeneity. Blood-oxygen-level-dependent (BOLD) signal variability captures the brain's moment-to-moment fluctuations, offering a dynamic marker of neural flexibility that is sensitive to cognitive capacity. This study aimed to examine intra-regional BOLD signal variability during rest and task across schizophrenia, autism, and typically developing controls (TDC) to explore transdiagnostic patterns of brain signal variability and their relationship with cognitive and functional outcomes. Intra-regional BOLD variability, measured by mean squared successive difference (MSSD), was obtained from resting-state and empathic accuracy task fMRI in 176 SSD, 89 autism, and 149 TDC participants. ANCOVAs, controlling for age, sex, and motion, assessed group differences in intra-regional and network-level BOLD variability and dimensional associations with social cognition, neurocognition, social functioning, and symptom severity. Both autism and schizophrenia exhibited lower BOLD signal variability than TDC across rest and task, with reduced variability observed in somatomotor, visual, and auditory networks (pFDR < 0.01). Greater network variability was positively associated with better social cognitive, neurocognitive, and functional scores across the sample. Resting-state variability showed stronger group-based differences and cognitive associations than task-based variability. BOLD signal variability is positively associated with social cognition, neurocognition, and social functioning across groups, suggesting that variability impacts cognitive efficiency and behavior. Reduced variability in autism and schizophrenia may indicate similar patterns of neural rigidity among these related conditions, positioning BOLD variability as a potential biomarker for neural flexibility and a valuable target for future transdiagnostic clinical interventions.

PMID:41987679 | DOI:10.1002/hbm.70496

Brain Behav. 2026 Apr;16(4):e71368. doi: 10.1002/brb3.71368.

ABSTRACT

INTRODUCTION: Patients with chronic kidney disease often exhibit impaired brain function; however, the differences between those with non-diabetic kidney disease (non-DKD) and diabetic kidney disease (DKD) remain poorly understood. This study aimed to investigate alterations in resting-state brain activity in patients with non-DKD and DKD.

METHODS: Thirty non-DKD patients, thirty DKD patients, and twenty-nine healthy controls underwent laboratory examinations and resting-state functional magnetic resonance imaging (rs-fMRI). The brain activity was analyzed using the amplitude of low-frequency fluctuations (ALFF) and seed-based functional connectivity (FC), and correlations between laboratory indicators and FC were examined.

RESULTS: Both non-DKD and DKD groups exhibited reduced ALFF in several brain regions, including the bilateral putamen, alongside elevated ALFF in the left middle occipital gyrus. Seed-based FC analysis revealed decreased connectivity between bilateral putamen and several regions, including decreased FC between the left putamen and left caudate. Compared with the non-DKD group, the DKD group demonstrated reduced ALFF in the left putamen and right precuneus, along with decreased FC between the right putamen and right thalamus. Several biomarkers, including urinary protein-to-creatinine ratio (UPCR), C-reactive protein (CRP), and hemoglobin (HGB), were associated with observed FC alterations.

CONCLUSION: Our findings indicate that DKD patients exhibit distinct patterns of brain activity compared to non-DKD patients, with the putamen potentially acting as a key neural target in the progression of CKD. These functional alterations correlate closely with systemic status, suggesting a significant role in the pathogenesis of neural impairment. Our results may enhance the understanding of neural functional alterations and the underlying mechanisms in non-DKD and DKD patients.

PMID:41987578 | DOI:10.1002/brb3.71368

Zhongguo Zhen Jiu. 2026 Apr 12;46(4):500-506. doi: 10.13703/j.0255-2930.20250924-k0003. Epub 2026 Jan 29.

ABSTRACT

OBJECTIVE: To investigate the regulatory effect of acupuncture bloodletting technique at hand twelve jing-well points on the thalamus-cortex network function in healthy subjects using resting-state functional magnetic resonance imaging (rs-fMRI), so as to analyze the underlying neural mechanism for improving brain functions and promoting brain protection based on multi-dimensional brain function indexes.

METHODS: A within-subject controlled design was employed, involving 30 healthy subjects. After rs-fMRI scanning, the subjects received acupuncture bloodletting technique at hand twelve jing-well points, stimulated from the right hands to the left hands, from the thumb to the small finger, sequentially at Shaoshang(LU11),Shangyang (LI1), Zhongchong (PC9), Guanchong (TE1), Shaochong (HT9) and Shaoze (SI1). After intervention completion, the rs-fMRI scanning was operated again. The amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and whole-brain functional connectivity (FC) with the thalamus as the region of interest, as well as cerebral blood flow (CBF) were analyzed before and after intervention in healthy subjects.

RESULTS: In comparison with the indexes before intervention, ALFF decreased in the bilateral superior temporal gyrus, middle temporal gyrus, precuneus and thalamus after intervention (P<0.05); and ReHo was reduced in the bilateral superior temporal gyrus, middle temporal gyrus and thalamus (P<0.05). In comparison with the indexes before intervention, after intervention, FC of the left thalamus was enhanced with bilateral lingual gyrus, bilateral pericalcarine cortex, left superior occipital gyrus, left fusiform gyrus, bilateral central anterior gyrus, right central sulcus, and bilateral middle temporal gyrus (P<0.05), and it was weakened with the left precuneus (P<0.05); and the enhanced FC of the right thalamus was observed with the bilateral lingual gyrus, bilateral pericalcarine cortex, bilateral middle occipital gyrus, bilateral fusiform gyrus, bilateral superior occipital gyrus, bilateral inferior temporal gyrus, bilateral cuneus, bilateral precentral gyrus, bilateral central sulcus, left superior temporal gyrus, and left inferior frontal triangular gyrus (P<0.05). There was no statistical significance of difference in CBF before and after intervention (P>0.05).

CONCLUSION: Acupuncture bloodletting technique at hand twelve jing-well points may regulate the functional state of the brain by means of inhibiting the excessive activity and abnormal synchronous discharges in the thalamus and higher-order cortical nodes and through reconstructing the functional connection network of the thalamus.

PMID:41987435 | DOI:10.13703/j.0255-2930.20250924-k0003

Eur J Neurosci. 2026 Apr;63(8):e70507. doi: 10.1111/ejn.70507.

ABSTRACT

Brain reserve capacity has recently gained an increasing interest in stroke recovery research to provide a deeper understanding of outcome variability. For instance, global and focal parameters of brain health, such as white matter hyperintensity burden or the structural reserve of the cerebellum, have been linked to recovery. Recently, it was shown that the pre-stroke structural state of key areas of the dopaminergic network might influence outcomes after stroke. We reanalyzed resting-state functional MRI data of 19 severely impaired acute stroke patients and 19 healthy controls and computed amplitudes of low-frequency fluctuations (ALFF) and functional connectivity (FC) in and between eight subcortical and cortical areas of the nigrostriatal and mesocorticolimbic dopaminergic network of the contralesional hemisphere. Linear regression modeling was used to compare patients and controls and combine patients' ALFF and FC data with clinical follow-up data obtained after 3-6 months. The group comparison revealed a significant upregulation of ALFF in the prefrontal cortices, the ventral tegmental area, the nucleus accumbens, and the caudate nucleus. Additionally, for some regions and connections within the nigrostriatal and mesocorticolimbic network, ALFF and FC estimates were significantly linked to global disability and symptom burden at follow-up. These data indicate a link between the pre-stroke functional state of key areas and pathways of the contralesional dopaminergic system and recovery from a severe stroke, thereby adding novel functional insights to recent structural data and promoting the emerging concepts of brain reserve capacity after stroke.

PMID:41986547 | DOI:10.1111/ejn.70507

Neuroimage. 2026 Apr 13:121923. doi: 10.1016/j.neuroimage.2026.121923. Online ahead of print.

ABSTRACT

We have shown that pregnancy alters brain structure and brain activity, yet its effects on neural dynamics are unknown. This is the first study to investigate the effects of becoming a mother on neural variability, a measure of moment-to-moment fluctuations in brain activity. Longitudinal resting-state functional magnetic resonance imaging data were analyzed of 110 women participating in a prospective pre-conception study, including first-time mothers, second-time mothers and nulliparous control women. Significant differences were observed when comparing pre-to-post pregnancy variability changes in first-time mothers and second-time mothers to those in control women. Control women exhibited widespread reductions in neural variability across all neural networks over time, a pattern that may reflect normative aging and test-retest effects. In contrast, both first-time and second-time mothers showed relative stability in neural variability, diverging from the trajectory observed in controls. Notably, higher neural variability was associated with younger age across all groups, and age was positively associated with changes in attention and frontoparietal networks in first-time mothers. These findings show that pregnancy renders changes in the temporal dynamics of brain activity. Furthermore, becoming a mother alters the trajectory of reductions in neural variability typical for repeated scanning sessions and aging, suggesting compensatory neural adaptations.

PMID:41985852 | DOI:10.1016/j.neuroimage.2026.121923

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Apr 13:111702. doi: 10.1016/j.pnpbp.2026.111702. Online ahead of print.

ABSTRACT

Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neurodevelopmental disorder that often persists into adulthood, leading to extensive functional impairments for individuals with ADHD. However, the predictors for adult functional outcomes of children with ADHD remain unclear. This prospective follow-up study aimed to establish a predictive model using clinical characteristics and multimodal neuroimaging features in children with ADHD for functional outcomes in adulthood. Finally, 104 children with ADHD who accepted baseline magnetic resonance imaging (MRI) scan and clinical assessment completed followed up into adulthood, with a mean follow-up duration of 8.2 years. Functional outcomes assessed in adulthood adopted the Global Assessment of Functioning scale. Random forest models were applied to predict functional outcomes in adults with ADHD, including clinical characteristics, structural MRI (sMRI) and resting state functional MRI (rs-fMRI) as input features. Model performances were evaluated by area under the curve (AUC) and related metrics, with interpretability assessed using SHapley Additive exPlanations (SHAP). The model based on clinical information showed limited predictive performance (AUC = 0.589). Among unimodal models, rs-fMRI outperformed sMRI (AUC = 0.778 vs. 0.611). The multimodal features model demonstrated superior performance (AUC = 0.816). Predictors with the highest predictive value were low-frequency fluctuations (ALFF) in the left middle occipital gyrus, volumes of the right medial orbitofrontal cortex and right supramarginal gyrus, and degree centrality (DC) of the right cerebellum Crus I. Integrating childhood clinical information with multimodal MRI substantially improves prediction of adult functional outcomes in ADHD. Larger prospective study is needed to establish utility for risk stratification.

PMID:41985649 | DOI:10.1016/j.pnpbp.2026.111702

Imaging Neurosci (Camb). 2026 Apr 10;4:IMAG.a.1202. doi: 10.1162/IMAG.a.1202. eCollection 2026.

ABSTRACT

It has long been established that human brains remain functionally active at rest, as demonstrated with the discovery of resting-state networks (RSNs) underlying spontaneous neural activity. Recent studies suggest that classical RSNs estimated from functional magnetic resonance imaging (fMRI) data using time-domain functional connectivity measures might be driven by recurring point-process events. Due to the slow hemodynamic response, fMRI cannot reveal such point-processes at the timescale of neuronal events while electroencephalography (EEG) holds the promise due to its millisecond temporal resolution and successful reconstruction of fMRI-like RSNs. The present study reported a set of recurring transient (<100 ms) cortical co-activation patterns (CAPs) derived from resting-state EEG using a clustering algorithm with spatial-domain measures (i.e., k-means). Our results indicate that this set of CAPs exhibit strong spatial correspondence with known RSNs, not only those derived from the same EEG data using time-domain measures (i.e., independence), but also those from fMRI literature, covering visual, auditory, motor, limbic, high-order, and default mode networks. CAPs exhibit the properties of hemispheric symmetry, spatially separatable sub-systems, and intersubject variability gradient across functional systems, which have all been observed in classical RSNs. These findings suggest that classical RSNs might be driven by recurring transient neuronal activations captured in CAPs. More importantly, CAPs can reveal the fast dynamics of such brain-wide networked neuronal activations (e.g., different CAPs exhibit significantly different occurrences and lifetimes) and benefit from their intersubject reproducibility, thus underscoring their potential to advance our understanding on neuronal mechanisms of spontaneous large-scale brain activation phenomena.

PMID:41982886 | PMC:PMC13075568 | DOI:10.1162/IMAG.a.1202

BMC Psychol. 2026 Apr 14. doi: 10.1186/s40359-026-04399-4. Online ahead of print.

NO ABSTRACT

PMID:41981693 | DOI:10.1186/s40359-026-04399-4

Complement Ther Med. 2026 Apr 12:103382. doi: 10.1016/j.ctim.2026.103382. Online ahead of print.

ABSTRACT

INTRODUCTION: Tai Chi (TC) combined with transcranial direct current stimulation (tDCS) improves memory function in patients with mild cognitive impairment (MCI), but underlying neurophysiological mechanisms remain unclear. This study aims to explore whether TC and tDCS can independently or interactively regulate spontaneous neural activity in different brain regions and enhance memory function.

METHODS: In a randomized 2×2 factorial trial, 128 MCI patients were assigned to TC, tDCS, TC combined with tDCS, or health education for 12 weeks. Memory performance was assessed using the Chinese Wechsler Memory Scale-Revised (WMS-RC), Auditory Verbal Learning Test (AVLT), and Rey-Osterrieth Complex Figure Test (ROCF). Resting-state functional MRI was performed at baseline and post-intervention.

RESULTS: TC significantly improved WMS-RC memory quotient (P<0.001), AVLT-cued recall (P=0.042), recognition (P=0.005), and increased activity in the middle/inferior temporal gyrus (P<0.05). tDCS significantly enhanced memory quotient (P<0.001), ROCF-recall (P=0.030), AVLT-recognition (P=0.013), and modulated activity in the left postcentral gyrus, lingual gyrus, calcarine fissure, and bilateral frontal regions (P<0.05). TC combined with tDCS significantly interacted with immediate recall (P=0.016) and altered activity across multiple cortical regions (P<0.05), and changes in immediate recall were negatively correlated with the ALFF value of the right orbital part of the middle frontal gyrus (r=-0.263, P=0.011).

CONCLUSIONS: TC and tDCS have distinct yet complementary neural and cognitive effects in MCI, supporting their integration as a promising multimodal strategy to delay cognitive decline.

TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2200059316.

PMID:41980631 | DOI:10.1016/j.ctim.2026.103382

J Clin Med. 2026 Mar 31;15(7):2644. doi: 10.3390/jcm15072644.

ABSTRACT

Background: Navigated repetitive TMS (nrTMS) is widely used for non-invasive mapping of cortical functions. Methodological improvement might be achieved by optimizing coil positioning based on electric-field modeling and augmented reality (AR)-guided neuronavigation to enhance spatial targeting accuracy and stimulation-induced language errors. Therefore, we compared electric-field-optimized, AR-guided nrTMS with conventional nrTMS using manually planned coil positioning. Methods: Twenty-eight healthy subjects underwent two MRI-guided left hemispheric nrTMS language mapping sessions. Each session used 10 Hz stimulation at a 100% resting motor threshold applied for 1.5 s per region of interest (ROI) during a synchronized object naming task. ROIs were defined according to the Corina cortical parcellation system. Manually defined and electric-field-optimized coil placements obtained using SimNIBS (v4.1.0) were applied; the optimized session was assisted by AR goggles. The primary outcome was the quantitative and categorical differences in cortical regions mapped as language-eloquent. Resting-state fMRI was acquired to provide a reference for comparing nrTMS-derived language maps. Outcomes: Electric-field-optimized nrTMS did not result in an increase in positively mapped ROIs. A different distribution of language errors was observed between sessions. Manual mapping roughly followed the extracted resting-state language and motor networks, whereas electric-field-optimized mapping might correspond less. Optimized coil positions were not always practically feasible. AR guidance improved target location accuracy. Conclusions: While AR was a useful addition to the TMS experiment, electric-field optimization did not translate into significant behavioral differences. However, altered distribution of language errors can give insight into underlying neurophysiological processes of rTMS.

PMID:41976945 | DOI:10.3390/jcm15072644

PLoS Biol. 2026 Apr 13;24(4):e3003738. doi: 10.1371/journal.pbio.3003738. Online ahead of print.

ABSTRACT

Cognitive flexibility supports efficient switching between mental sets and contributes to the preservation of general cognition in aging. It relies on the integration between brain functional dynamics and structural architecture. However, how this structure-function integration changes with age and contributes to cognitive flexibility decline in older adults remains unclear. In this study, we investigated longitudinal aging-related changes in multimodal structure-function integration, quantified as functional signal alignment (i.e., coupling) versus liberality (i.e., decoupling) relative to individual structural connectomes, which represent distinct spectral components, and tested their longitudinal associations with cognitive flexibility. Resting-state fMRI signals were decomposed based on diffusion MRI-derived structural networks using a graph signal processing framework. We focused on subnetworks within three core large-scale cognitive systems: the executive control network (ECN), default mode network (DMN), and salience network (SN). Across two independent datasets, the task-positive SN-A subnetwork, which includes core SN regions such as the anterior insula and dorsal anterior cingulate cortex, exhibited decreased coupling and increased decoupling with aging. Importantly, these changes were associated with a greater decline in cognitive flexibility (measured by the Trail Making Test and Color Trails Test) over time. In contrast, task-negative DMN-A (centered in the medial prefrontal and posterior cingulate cortex) showed aging-related changes in the opposite direction, with increased coupling and decreased decoupling over time. Together, these findings reveal network-specific trajectories of intrinsic structure-function integration in normal aging and indicate that preserved structure-function integration within the SN may be particularly important for maintaining cognitive flexibility in older adults.

PMID:41973732 | DOI:10.1371/journal.pbio.3003738

Pain. 2026 Apr 7. doi: 10.1097/j.pain.0000000000003984. Online ahead of print.

ABSTRACT

Chronic pain is associated with maladaptive reorganization of brain networks, particularly in the anterior cingulate cortex (ACC), contributing to the affective dimension of pain. Although peripheral capsaicin administration relieves neuropathic pain in clinics, its effects on central pain networks remain unclear. In this study, we determined the resting-state functional connectivity of ACC (ACC FC) rearrangement after infraorbital nerve chronic constriction injury (ION-CCI) and subsequent peripheral administration of capsaicin through longitudinal resting-state functional magnetic resonance imaging (fMRI) in male rats. We also conducted functional silencing of the ACC using inhibitory chemogenetic receptors to determine ACC networks commonly reversed by peripheral capsaicin and chemogenetic silencing. Infraorbital nerve chronic constriction injury produced orofacial mechanical allodynia accompanied by ACC FC changes compared to sham. A single injection of capsaicin into the maxillary skin decreased mechanical allodynia. Five days after capsaicin injection, CCI-enhanced ACC FC was significantly reduced compared to the time point before the injection in the same rats or to the rats with vehicle injection. Subsequent chemogenetic silencing of ACC in the previously vehicle-treated CCI rats reduced mechanical allodynia and suppressed CCI-enhanced ACC FC. Peripheral capsaicin and chemogenetic inhibition of ACC commonly reversed approximately one-third of the CCI-enhanced ACC FC. Affected regions included the bilateral cingulate areas, primary and secondary somatosensory cortex, primary and secondary auditory areas, hippocampus, and temporal association cortex. We conclude that peripheral capsaicin administration reverses maladaptive ACC networks in male rats with nerve injury and that peripheral nociceptors contribute to the maintenance chronic pain and peripherally targeted treatment can produce long-lasting analgesia.

PMID:41973718 | DOI:10.1097/j.pain.0000000000003984

Quant Imaging Med Surg. 2026 Apr 1;16(4):309. doi: 10.21037/qims-2025-1771. Epub 2026 Feb 25.

ABSTRACT

BACKGROUND: Cognitive impairment (CI) is an under-recognized yet clinically important complication in patients with non-dialysis chronic kidney disease (CKD). Despite its significance, predictive and evaluative frameworks remain underdeveloped, limiting opportunities for timely management. We investigated the utility of multimodal functional magnetic resonance imaging (MRI) in predicting CI in patients with non-dialysis CKD.

METHODS: A prospective study of 60 patients with non-dialysis CKD was conducted using conventional MRI sequences and three-dimensional T1-weighted scans. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) scale, and patients were stratified into a CI group (MoCA score <26) and a non-cognitive impairment (NCI) group (MoCA score ≥26). Group differences in brain structure and function were examined using voxel-based morphometry (VBM) and blood oxygenation level-dependent (BOLD) analyses. The associations between brain structural metrics [gray matter volume (GMV); gray matter volume fraction (GMVF)] and CI were further evaluated with binary logistic regression and receiver operating characteristic (ROC) analysis.

RESULTS: Compared to the NCI group, patients with CKD with CI showed substantially reduced brain GMV (572.56±39.70 vs. 621.30±62.12 cm3, P=0.001). VBM analysis indicated substantially reduced GMV in the right amygdala (t=5.0291), left insula (t=5.3287), and right middle temporal gyrus (t=4.4031) in the cognitively impaired group. BOLD analysis indicated reduced amplitude of low-frequency fluctuations in the left posterior central gyrus and right supplementary motor area, and reduced regional homogeneity in the bilateral postcentral gyri (all P<0.001). After adjustment for age, education, and estimated glomerular filtration rate (eGFR), GMV remained independently associated with visuospatial/executive impairment [odds ratio per 1-cm3 decrease =0.970, 95% confidence interval (95% CI): 0.975-0.997, P=0.028]. GMV demonstrated predictive value for CI, with an area under the ROC curve of 0.729 (95% CI: 0.561-0.879, P=0.01), yielding a sensitivity of 94.7% and specificity of 53.3% at a cut-off of 619.9 cm3.

CONCLUSIONS: Patients with non-dialysis CKD and CI exhibited reduced GMV and impaired functional connectivity in specific brain regions. These structural and functional alterations were strongly associated with CI. GMV demonstrated high sensitivity in differentiating between patients with and without CI. These findings indicate the potential of multimodal MRI techniques in the early diagnosis and intervention planning in cognitive decline associated with non-dialysis CKD.

PMID:41972076 | PMC:PMC13066838 | DOI:10.21037/qims-2025-1771

Neurobiol Lang (Camb). 2026 Mar 26;7:NOL.a.225. doi: 10.1162/NOL.a.225. eCollection 2026.

ABSTRACT

The visual word form area (VWFA) has been consistently identified as a crucial structure in word reading, and its function differs across subregions. Nevertheless, the functional roles of its subregions and their functional origins remain controversial. Here, we adopted multimodal neuroimaging techniques (i.e., task-state fMRI, resting-state fMRI, and diffusion MRI) combined with representational similarity analysis to investigate the functional role of VWFA subregions and the brain circuitry supporting their function in two experiments. Results revealed respective roles of the posterior and anterior VWFA subregions in visual and semantic processing, which is consistent with their respective connectivity to orthographic and semantic networks. In addition, processing demands modulated the neural representations of high-level linguistic information in the VWFAs. These convergent findings elucidated the local neural computations in the VWFAs and their cooperative mechanism with distant brain regions related to language processing, jointly providing multimodal neuroimaging evidence for the connectivity-biased hypothesis.

PMID:41971749 | PMC:PMC13065096 | DOI:10.1162/NOL.a.225

Front Public Health. 2026 Mar 27;14:1762620. doi: 10.3389/fpubh.2026.1762620. eCollection 2026.

ABSTRACT

BACKGROUND: Chronic smoking has well-documented impacts on brain structure. Voxel-based morphometry (VBM) investigations have revealed diverse regional gray matter (GM) changes in chronic smokers, hindering a unified understanding of smoking-induced neuropathology. To reconcile these findings, this study aimed to identify common intrinsic functional networks underlying these structural alterations using a functional connectivity network mapping (FCNM) approach. We further explored potential exposure-dependent variations to characterize how brain network architecture relates to cumulative smoking dose.

METHODS: We utilized coordinate-based FCNM to quantitatively integrate heterogeneous findings from previous VBM studies. We systematically reviewed VBM studies reporting GM differences between chronic smokers and non-smokers. We identified peak coordinates from 27 studies, encompassing 36 contrasts with 1,336 smokers and 1803 non-smokers. Resting-state fMRI from 1,093 healthy participants (Human Connectome Project) were utilized to create individual functional connectivity maps based on seed coordinates. Maps were combined to identify a shared alteration network and evaluated for spatial overlap with established canonical brain networks. Sensitivity analysis were conducted with different seed radii. Crucially, subgroup analysis stratified studies into higher-exposure and lower-exposure groups to investigate exposure-dependent mechanisms.

RESULTS: Functional connectivity network mapping identified a widespread network linked to smoking-induced GM changes. Key nodes included the supramarginal gyrus, insula, anterior cingulate cortex, caudate nucleus, putamen, and superior temporal gyrus. Spatial overlap analysis revealed predominant involvement of the posterior Salience Network (51.59%), anterior Salience Network (32.15%), basal ganglia network (31.52%), and auditory network (24.19%). Sensitivity analysis confirmed the robustness of these findings. Subgroup analysis revealed exposure-dependent patterns: while the Salience and basal ganglia networks were consistently affected in both groups, the auditory network and ventral Default Mode Network showed markedly greater involvement in the higher-exposure group, largely spared in the lower-exposure group.

CONCLUSION: This FCNM approach identified consistent brain networks, predominantly the Salience, basal ganglia, and auditory networks, associated with chronic smoking-related GM alterations. These findings offer network-level insight into the structural effects of smoking, helping to resolve discrepancies and potentially guiding tailored interventions. Furthermore, the findings suggest a progressive neuropathological expansion, characterized by the concurrent recruitment of sensory (auditory) and high-order cognitive systems (ventral Default Mode Network) with cumulative smoking exposure.

PMID:41971270 | PMC:PMC13066286 | DOI:10.3389/fpubh.2026.1762620

Neuroimage. 2026 Apr 10:121919. doi: 10.1016/j.neuroimage.2026.121919. Online ahead of print.

ABSTRACT

Brain entropy (BEN) quantifies the irregularity of regional brain activity and serves as an index of neural complexity, yet how BEN co-varies with large-scale brain connectivity remains unclear. Given the brain's dynamic nature, this study examined how whole-brain connectivity patterns co-vary with recurring BEN states. Using a large resting-state fMRI data dataset (N = 812), we applied a sliding-window approach and k-means clustering to derive dynamic BEN states and their corresponding connectivity patterns. Four distinct BEN states were identified, each showing unique functional and cognitive relevance. A low-BEN state (State 1) was associated with a strongly segregated, weakly integrated organization and negative cognitive relevance, while a high-BEN state (State 4) showed a highly integrated but weakly segregated organization and neutral cognitive relevance. Two intermediate-BEN states differed in regional entropy and connectivity: State 2, with low entropy in the default mode (DMN), executive control (ECN), and salience (SAN) networks, showed positive cognitive relevance and balanced integration-segregation; State 3, with low entropy in sensorimotor (SMN) and visual networks (VN), showed no significant cognitive relevance. Moreover, BEN-connectivity correlations were significantly negative and varied across states, being strongest in the cognitively relevant states. These findings demonstrate that the relationship between BEN and brain connectivity is dynamic and state-dependent, advancing BEN as a marker of the brain's complex, state-dependent functional organization.

PMID:41967787 | DOI:10.1016/j.neuroimage.2026.121919

J Affect Disord. 2026 Apr 9:121770. doi: 10.1016/j.jad.2026.121770. Online ahead of print.

ABSTRACT

BACKGROUND: Facial emotion recognition (FER), an essential component of emotion processing that influences social functioning and interpersonal relationship satisfaction, plays a key role in major depressive disorder (MDD). This study aimed to investigate the heterogeneity of FER performance within individuals with MDD and its relationship with whole-brain functional connectivity (FC) using multivariate methods.

METHODS: A total of 202 patients with MDD and 202 healthy controls (HCs) were included in the study and completed FER assessments. Among them, 158 patients with MDD and 128 HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Data-driven clustering was employed to identify FER-based clusters within the MDD group based on recognition performance. Group differences in FC were explored at both the edge and large-scale network levels. Partial least squares (PLS) correlation analysis was then applied to investigate the association between whole-brain FC patterns and FER performance.

RESULTS: Clustering analysis identified three MDD subgroups characterized by progressively decreasing FER performance, accompanied by a corresponding stepwise reduction in overall network connectivity strength. Comparisons between subgroups highlighted the crucial involvement of hippocampal and prefrontal regions, as well as subcortical and visual systems. The PLS results revealed a distinctive FC pattern associated with FER performance.

CONCLUSIONS: Our findings suggest that multilevel neural alterations, including disrupted connectivity within the hippocampal-prefrontal-limbic circuitry and abnormal coupling between large-scale information integration and sensory-motor networks, may collectively impair affective information processing and contribute to individual differences in FER observed among individuals with MDD.

PMID:41966228 | DOI:10.1016/j.jad.2026.121770

Neuroimage Clin. 2026 Apr 7;50:103990. doi: 10.1016/j.nicl.2026.103990. Online ahead of print.

ABSTRACT

PURPOSE: The exact mechanisms underlying the distinct neurological outcomes between Traumatic Brain Injury (TBI) and Hemorrhagic Stroke (HS) remain unclear. Our objective is to assess distinct features of neurologic state between comatose patients with TBI and HS during the stage of acute disorder of consciousness (aDoC) and to identify the correlation of neurologic features with prognosis.

METHODS: Data were analyzed from TBI and HS patients examined by positron emission tomography (PET) and resting-state functional magnetic resonance imaging (rs-fMRI) simultaneously. Primary clinical outcomes consisted of the state of consciousness and neurological prognosis. The regional neural activity was assessed by the amplitude of fractional low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) on rs-fMRI scans. The standardized uptake value (SUV) on PET scans quantified neural metabolism. Functional connectivity (FC) and graph theoretic approach (GTA) were employed to compare the FC patterns between TBI and HS. Correlations of PET/rs-fMRI indicators with the prognosis of HS and TBI were identified.

RESULTS: Muti-modal PET/rs-fMRI analysis showed more active local neurological state in TBI patients than HS patients, specifically in the right precentral gyrus (PreCG.R), right postcentral gyrus (PoCG.R), right superior temporal gyrus (STG.R) and right middle temporal gyrus (MTG.R). TBI patients demonstrated significantly higher clustering coefficient and nodal efficiency of the sensorimotor network (SMN) along with lower connectivity and network efficiency in the default network (DMN) compared to HS patients. PET/rs-fMRI indicators significantly correlated with the neurological prognosis of TBI and HS.

CONCLUSIONS: This study elucidated the underlying mechanisms contributing to the distinct neurologic prognosis between comatose TBI and HS patients, and may contribute to the development of early targeted intervention strategies for specific diseases.

PMID:41965151 | DOI:10.1016/j.nicl.2026.103990

Commun Biol. 2026 Apr 10;9(1):520. doi: 10.1038/s42003-025-09444-3.

ABSTRACT

The brain's functional activity is shaped by the complex architecture of its fibers. Yet, the lack of a direct one-to-one mapping between functional and structural connections makes this relationship elusive. To date, most studies on structure-function coupling (SFC) have conceptualized function in terms of resting-state functional Magnetic Resonance Imaging (fMRI) connectivity. Here, we extend this framework to neurophysiological data by examining how magnetoencephalography (MEG) activity relates to the structural connectome, leveraging its rich spectral content and direct sensitivity to neuronal population dynamics. We show that the decoupling of MEG activity from structure is strongly associated with the expression levels of synaptic plasticity markers, pointing to a link between flexible functional reconfiguration and the molecular mechanisms of plasticity. Moreover, regions with greater decoupling exhibit higher neurotransmitter receptor diversity, underscoring neuromodulatory heterogeneity as a substrate for functional flexibility. This association is especially pronounced for slow-acting metabotropic receptors, whose diffuse and prolonged signaling may facilitate functional reorganization atop the structural connectome.

PMID:41963461 | DOI:10.1038/s42003-025-09444-3