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J Integr Neurosci. 2026 Jan 21;25(1):46820. doi: 10.31083/JIN46820.

ABSTRACT

BACKGROUND: Executive dysfunction is the most prominent feature of cognitive impairment in patients with end-stage renal disease (ESRD). The dorsolateral prefrontal cortex (DLPFC) is a central region for the regulation of executive functions. The aim of our study was to examine alterations in neural activity and functional connectivity (FC) of the DLPFC in relation to cognitive assessments and clinical indicators in patients with ESRD using the resting-state functional magnetic resonance imaging (rs-fMRI) technique, and to further predict cognitive-related brain damage in this population.

METHODS: A total of 37 ESRD patients and 35 normal controls received MRI scans and neuropsychological assessments. Inter-group differences in fractional amplitude of low-frequency fluctuations (fALFF) and FC of the DLPFC were compared. Additionally, the relationships between DLPFC abnormalities and cognitive function were analyzed in ESRD patients, along with the clinical characteristics. Finally, we ascertained the potential of DLPFC abnormalities to predict cognitive-related brain damage using receiver operating characteristic (ROC) curve analysis.

RESULTS: ESRD patients exhibited decreased fALFF in the bilateral DLPFC (p < 0.05, false discovery rate [FDR] corrected). These also showed abnormal FC with the frontoparietal cortex, cingulate cortex, cerebellar posterior lobe, inferior temporal gyrus, and rolandic operculum (p < 0.05, FDR corrected). Several alterations in the DLPFC were associated with cognitive assessments (p < 0.05) in ESRD patients, and were also correlated with the levels of uric acid and hemoglobin (p < 0.05). Importantly, ROC curve analysis showed the fALFF value of left DLPFC, and FC between right DLPFC and right middle frontal gyrus effectively predicted cognitive-related brain damage in patients with ESRD.

CONCLUSIONS: This study demonstrated that the DLPFC is an important pathological brain region associated with the cognitive impairment of ESRD patients. Our results provide neuroimaging insights to further understand neural mechanisms of cognitive decline in this population.

PMID:41609046 | DOI:10.31083/JIN46820

Front Psychol. 2026 Jan 13;16:1728241. doi: 10.3389/fpsyg.2025.1728241. eCollection 2025.

ABSTRACT

INTRODUCTION: Previous studies on white matter (WM) in patients with obsessive-compulsive disorder (OCD) have focused primarily on its structural aspects. This study aimed to investigate any abnormal spontaneous WM neural activity in patients with OCD.

METHODS: The study was based on resting-state functional magnetic resonance imaging (fMRI) data from 27 patients with OCD and 24 matched healthy controls (HC). Regional homogeneity (ReHo) and the amplitude of low-frequency fluctuation (ALFF) were used to explore spontaneous neural activity changes in the subjects' WM regions. A two-sample Student's t-test was performed, and correlations between the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD) scores were analyzed.

RESULTS: The ReHo in the left posterior limb of the internal capsule (LPLIC) and right superior corona radiata (RSCR) of the OCD group was significantly higher than those in the HCs (pTFCE-FWE < 0.001). The ALFFs in the right superior longitudinal fasciculus (RSLF) and right cerebral peduncle (RCP) of the OCD group, by contrast, were significantly lower than those in the HCs (pTFCE-FWE < 0.05). There was no correlation between the clinical symptoms of patients with OCD and their abnormal amplitude of low-frequency fluctuation (ALFF) and ReHo values.

DISCUSSION: Abnormal spontaneous WM activity was observed in several brain regions in patients with OCD. This activity may help explain the cognitive inflexibility often observed in this patient group.

PMID:41608182 | PMC:PMC12834757 | DOI:10.3389/fpsyg.2025.1728241

Front Aging Neurosci. 2026 Jan 13;17:1744413. doi: 10.3389/fnagi.2025.1744413. eCollection 2025.

ABSTRACT

INTRODUCTION: Olfactory dysfunction is common in the Alzheimer's Disease continuum, and olfaction may be altered before clinical syndrome onset. The present study aimed at investigating the functional connectivity of the olfactory cortex and its correlation with olfaction performance in a group of patients with Mild Cognitive Impairment (MCI) who subsequently converted or not converted to Alzheimer's Disease (AD) dementia.

METHODS: At baseline, 30 MCI patients were evaluated with the Sniffin' Sticks (threshold, discrimination, and identification) to assess olfactory capacities, and they were followed up over time to identify converter and stable patients. Resting-state fMRI data acquired at baseline were analyzed to assess functional connectivity of left and right olfactory cortex. Beta values were extracted from the stable versus converter contrasts and correlated with olfactory scores.

RESULTS: Functional connectivity of the olfactory cortex was significantly increased with the posterior cingulate cortex, and significantly decreased with middle cingulate cortex, supplementary motor area, and left pre- and postcentral gyri, in converter compared to stable patients. Reduced negative functional connectivity between olfactory cortex and left angular gyrus emerged in converter patients, and a negative correlation was found between angular gyrus and discrimination scores.

DISCUSSION: Our findings indicate alterations of functional connectivity of the olfactory cortex in subjects with MCI at risk of conversion to AD dementia, even at the early stages of the disease. Additionally, the negative correlation between olfactory ability and the angular gyrus functional connectivity, a cerebral region known to be involved in multisensory integration processing, may be considered as a marker of disease progression.

PMID:41607501 | PMC:PMC12835387 | DOI:10.3389/fnagi.2025.1744413

Front Neurosci. 2026 Jan 13;19:1744783. doi: 10.3389/fnins.2025.1744783. eCollection 2025.

ABSTRACT

OBJECTIVE: Postherpetic neuralgia (PHN), a refractory neuropathic pain following herpes zoster reactivation, lacks clear central mechanisms for emerging therapies like short-term spinal cord stimulation (stSCS). This longitudinal study used multimodal neuroimaging to examine the effects of 14-day stSCS on brain function and white matter microstructure in PHN patients, and to identify neural correlates of clinical improvements.

METHODS: In this longitudinal, single-arm, pre-post study, 17 PHN patients received 14 days of continuous stSCS. Clinical outcomes including pain intensity (Numeric Rating Scale, NRS), anxiety and depression (Hospital Anxiety and Depression Scale, HADS), and sleep quality (Pittsburgh Sleep Quality Index, PSQI), were assessed pre-stSCS and 3 days post-stSCS. Resting-state functional MRI (rs-fMRI) and Diffusion Tensor Imaging (DTI) data were acquired at both time points. Longitudinal changes in amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) were analyzed, alongside white matter integrity via TBSS and ROI analysis of key tracts.

RESULTS: Post-stSCS, significant improvements occurred in all clinical outcomes (Wilcoxon signed-rank, all p < 0.001). Neuroimaging showed no DTI microstructural changes but significant fALFF increases in regions including the dorsal striatum. Notably, right medial orbitofrontal cortex (mOFC) fALFF increases correlated with NRS reductions (Spearman's r = 0.71, FDR-corrected p = 0.036). Baseline cingulum integrity (lower FA, higher MD/RD) predicted greater striatal fALFF changes (r = ±0.75, FDR-corrected p < 0.02).

CONCLUSION: These findings suggest that stSCS's early clinical benefits in PHN are mediated by rapid functional reorganization rather than immediate microstructural changes. This reorganization appears prominent within fronto-striatal circuits: specifically, mOFC functional changes correlate with analgesia, while baseline cingulum integrity predicts subsequent striatal plasticity. This provides initial mechanistic insights into stSCS and suggest that baseline brain structure could be explored as a potential biomarker for treatment response, warranting validation in larger, controlled cohorts.

PMID:41607406 | PMC:PMC12835296 | DOI:10.3389/fnins.2025.1744783

Front Neurosci. 2026 Jan 13;19:1695556. doi: 10.3389/fnins.2025.1695556. eCollection 2025.

ABSTRACT

OBJECTIVE: This study aimed to investigate alterations in brain activity due to acute carbon monoxide poisoning (ACOP) and their relationship with clinical manifestations using static and dynamic amplitude of low-frequency fluctuation (ALFF) analyses.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) and clinical data were obtained from 31 ACOP patients and 28 healthy controls. The static ALFF value and dynamic ALFF variability were measured and compared between groups. Partial correlation analysis explored the relationships between changes in ALFF and clinical features in ACOP patients.

RESULTS: ACOP patients exhibited increased dynamic ALFF in the bilateral superior frontal gyrus (SFG) and left middle frontal gyrus (MFG) and decreased static ALFF in the left middle occipital gyrus (MOG) compared to controls. Aberrant dynamic ALFF in the left SFG and MFG was negatively correlated with MoCA-B scores (r = -0.430, p = 0.036; r = -0.439, p = 0.032).

CONCLUSION: ACOP patients exhibited abnormal instability in intrinsic brain activity, particularly in prefrontal areas, where temporal variability in local brain activity correlates with cognitive performance. This study highlights the value of combined static and dynamic ALFF approaches in understanding brain disturbances caused by CO exposure, providing new insights into the neuropathological mechanisms of ACOP.

PMID:41607402 | PMC:PMC12835238 | DOI:10.3389/fnins.2025.1695556

J Oral Facial Pain Headache. 2026 Jan;40(1):61-70. doi: 10.22514/jofph.2026.006. Epub 2026 Jan 12.

ABSTRACT

BACKGROUND: Temporomandibular disorders (TMD), particularly pain-related TMD (TMDp), are closely associated with social and psychological factors. However, the neuromechanisms of pain of TMDp are still currently unclear. This study aimed to investigate the altered topological properties of the brain network in the TMDp patients using resting-state functional magnetic resonance imaging (rs-fMRI), and to explore the association between these parameters and emotional and clinical variables of TMDp.

METHODS: A total of 41 TMDp patients and 33 age- and gender-matched healthy controls (NCs) were recruited, and rs-fMRI data were obtained from a 3.0T MR scanner. The topological properties of brain functional networks were calculated based on the rs-fMRI data and were compared between two groups to investigate the altered topological characteristics in TMDp. The correlation analysis was also performed between the abnormal topological characteristics and the clinical variables in TMDp patients.

RESULTS: TMDp patients presented significantly decreased clustering coefficient (Cp) and decreased local efficiency (Eloc) when sparsity threshold was 0.05 and 0.06 compared with NCs (p < 0.05), and the Eloc values when sparsity threshold was 0.06 were positively correlated with depressive (r = 0.319, p = 0.042) and anxious (r = 0.348, p = 0.026) variables in TMDp patients.

CONCLUSIONS: The current study demonstrated the abnormal topological changes of the brain network were observed in TMDp, which could be helpful in understanding the neuromechanisms of pain of TMDp. The topological properties of the brain network based on rs-fMRI could be considered as a new simple tool to monitor the dysfunction network of the brain in TMDp.

PMID:41607323 | DOI:10.22514/jofph.2026.006

Cereb Cortex. 2026 Jan 6;36(1):bhag002. doi: 10.1093/cercor/bhag002.

ABSTRACT

This study introduces a novel oscillatory network model to simulate simultaneous electroencephalography-functional magnetic resonance (EEG-fMRI) data, addressing the reconstruction challenge that arises due to their contrasting spatiotemporal scales. Here, each brain region is modeled by 2 oscillator clusters-a cluster of low-frequency (LFO) and high-frequency Hopf oscillators (HFO) coupled with an innovative power-coupling rule, facilitating cross-frequency interactions. The model is trained in 2 stages: learning oscillators' frequencies and phase relations using a biologically plausible complex-Hebbian rule in the first stage and, followed by a modified complex backpropagation for amplitude approximation, overcoming limitations of poor accuracy and computational complexity in existing models. This framework outperforms current methods in replicating empirical functional connectivity (FC), FC dynamics (FCD), and modularity over disparate spatio-temporal scales. The correlation between the FC of fMRI and the FCs of various EEG frequency bands is reflected in the strengths of the LFO-HFO coupling. Furthermore, in silico structural perturbation studies quantified the effect of pruning of the anatomical connectivity on spatiotemporal dynamics in terms of FC, FCD, modularity, and integration level integrated state of occurrence rate. The model's ability to reconstruct simultaneous EEG-fMRI data showcases significant advancement in understanding the resting-state brain's functionality from multimodal settings and deciphering neurological disorders in diverse spatiotemporal scales.

PMID:41606834 | DOI:10.1093/cercor/bhag002

J Affect Disord. 2026 Jan 26:121273. doi: 10.1016/j.jad.2026.121273. Online ahead of print.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is conceptualized as a disorder of brain circuit function, particularly involving the default mode network (DMN). Repetitive transcranial magnetic stimulation (rTMS) emerged as an effective treatment for major depressive disorder (MDD), while its mechanisms and predictors of response remain poorly understood.

METHODS: We retrospectively analyzed 70 patients with MDD received either active (n = 41) or sham (n = 29) rTMS. The resting-state fMRI was performed before and after treatment to assess dynamic functional connectivity. The left dorsal lateral prefrontal cortex (lDLPFC) was selected as the target site for rTMS, based on individualized functional connectivity with the right nucleus accumbens (NAcc) as the seed region. We tested the hypothesis that rTMS remediates depression by increasing modular flexibility, a measure of a brain region's dynamic functional integration and that baseline flexibility would predict clinical outcomes.

RESULTS: Active rTMS produced a significantly greater reduction in Hamilton Depression Rating Scale (HAMD) scores, when compared to sham group (t = -2.70, p = .009). This clinical improvement was paralleled by a significant increase in the modular flexibility of the bilateral medial prefrontal cortex (MPFC), a key DMN hub. The magnitude of this flexibility increase was directly correlated with the degree of symptom reduction in the active group (r = 0.323, p = .045). Importantly, a support vector regression model demonstrated that pre-treatment modular flexibility in DMN nodes significantly predicted post-treatment HAMD scores (r = 0.391, p = .011).

CONCLUSIONS: These findings provide compelling evidence that rTMS exerts its therapeutic effects by remodeling the dynamic architecture of the DMN, enhancing its flexibility. Baseline modular flexibility constitutes a promising, mechanistically inspired biomarker for personalizing rTMS therapy. This work advances a dynamic network model of neuromodulation, shifting the focus from static dysfunction to the restoration of neural adaptability.

PMID:41605354 | DOI:10.1016/j.jad.2026.121273

Neurosci Biobehav Rev. 2026 Jan 26:106579. doi: 10.1016/j.neubiorev.2026.106579. Online ahead of print.

ABSTRACT

Auditory verbal hallucinations (AVH) represent one of the most debilitating symptoms in schizophrenia. The amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF), derived from resting-state fMRI, serve as robust metrics for intrinsic brain activity; however, their network-level and biological correlates of AVH have yet to be systematically elucidated. We conducted a comprehensive systematic review and meta-analysis of ALFF/fALFF studies in schizophrenia with AVH, integrating neurochemical and genetic annotation to provide a multilevel perspective. Across studies, AVH was consistently associated with increased intrinsic activity in auditory and language networks, reward and motivation circuits, and executive control regions, along with decreased activity in sensorimotor network. While alternations within the default mode network were more heterogeneous. Meta-analysis further highlighted the involvement of thalamic-frontal network in distinguishing AVH from non-AVH patients. Spatial correlation analysis demonstrated strong associations between AVH-related activity changes and the distribution of cannabinoid (CB1), dopaminergic (D2), noradrenergic (NAT), and metabotropic glutamate (mGluR5) neurotransmitter systems. Gene enrichment analysis revealed that implicated regions were transcriptionally characterized by pathways related to neurodevelopment, neural circuit formation, and regulation of neural activity. By integrating these multilevel findings, we propose a systems-level model in which early neurodevelopmental and genetic vulnerabilities interact with ongoing neurotransmitter dysregulation and large-scale network dysfunction, ultimately driving the emergence and persistence of AVH in schizophrenia. These findings underscore the importance of developing multidimensional biomarkers and may inform the design of future precision interventions targeting AVH in schizophrenia.

PMID:41605340 | DOI:10.1016/j.neubiorev.2026.106579

Psychiatry Res Neuroimaging. 2026 Jan 21;357:112151. doi: 10.1016/j.pscychresns.2026.112151. Online ahead of print.

ABSTRACT

Exploiting deep learning methods to accelerate the analysis of medical images and the interpretation of pathology results for early diagnosis of Alzheimer's disease (AD) has recently attracted great attention. However, challenges like sub-optimal classifiers and poor image representation hinder their effectiveness. Computer-aided diagnosis (CADx) can improve performance by classifying patterns. Despite the drawbacks of deep networks such as Visual Geometric Group (VGG), including long processing times and performance issues due to data distribution, many CADx systems still rely on VGG classifiers due to their potential for high accuracy when properly trained. To tackle these issues, this paper introduces two novel deep networks, called optimized VGG-16 (OVGG-16) and optimized VGG-19 (OVGG-19), in light of the concepts of transfer learning and dense layers to improve diagnosis performance. The proposed system was developed for the diagnosis of AD employing the OVGG-16 and OVGG-19 networks as classifiers from rs-fMRI images. The results show that the convergence rate of the proposed OVGG-16 and OVGG-19 networks is more rapid than that of the conventional VGG-16 and VGG-19. Moreover, the proposed system, which uses the OVGG-16 network, yielded a high accuracy of 100% and 98.83% for binary and multiclass classification, respectively, which surpasses existing state-of-the-art approaches.

PMID:41604985 | DOI:10.1016/j.pscychresns.2026.112151

Brain Lang. 2026 Jan 27;274:105718. doi: 10.1016/j.bandl.2026.105718. Online ahead of print.

ABSTRACT

Reading ability, a key aspect of verbal skills, is acquired primarily through educational and linguistic experience, whereas non-verbal reasoning is more relevant in problem-solving scenarios that do not depend on language. Both of these two abilities exhibit significant individual differences; however, it remains unclear whether the neural patterns underlying reading and non-verbal reasoning are common or distinct in terms of individual difference. This study utilized resting-state fMRI data from 66 children aged 8.7 to 12.5 years and applied inter-subject representational similarity analysis (IS-RSA) to evaluate three behavioral models-nearest neighbour, convergence, and divergence-in order to determine which model best characterizes the neural patterns underlying individual differences in reading and non-verbal reasoning. Results showed that children with higher reading abilities had greater neural similarity in the reading network (supporting the convergence model), while those with better non-verbal reasoning abilities displayed more neural variability in the non-verbal reasoning network (supporting the divergence model). These findings suggest that cognitive abilities with distinct characteristics (i.e., verbal and non-verbal) may influence their corresponding neural patterns in different ways, leading to distinct patterns of individual differences.

PMID:41605031 | DOI:10.1016/j.bandl.2026.105718

Eur Arch Psychiatry Clin Neurosci. 2026 Jan 28. doi: 10.1007/s00406-026-02198-x. Online ahead of print.

NO ABSTRACT

PMID:41603908 | DOI:10.1007/s00406-026-02198-x

Front Neurol. 2026 Jan 12;16:1684824. doi: 10.3389/fneur.2025.1684824. eCollection 2025.

ABSTRACT

BACKGROUND: Bell's palsy (BP) is an acute facial palsy caused by the inflammation of the facial nerve. Previous research indicates that the striatum may be involved following acute peripheral nerve injury, and acupuncture is a recognized treatment for BP. However, it remains unclear whether the striatum is functionally engaged during the recovery process with acupuncture.

METHOD: Using resting-state functional MRI (fMRI), we investigated striatum-related neural activity in BP patients by measuring two key metrics of local brain function: regional homogeneity (ReHo, reflecting local neural synchrony) and fractional amplitude of low-frequency fluctuations (fALFFs, reflecting the intensity of spontaneous neural activity). We further examined corticostriatal and internal striatal functional connectivity. Patients underwent fMRI scans before and immediately after (15 min following needle withdrawal) an acupuncture treatment session to capture dynamic changes.

RESULTS: The post-treatment scan was associated with significant alterations in both ReHo and fALFFs, including increased fALFFs in the left postcentral gyrus and the precentral gyrus and increased ReHo in the right cerebellum (Crus2). Several striatal subregions also exhibited significantly enhanced internal connectivity.

CONCLUSION: Our results indicate that the striatum undergoes functional alterations during the recovery period, which may provide preliminary insight into neural processes associated with treatment for BP.

PMID:41602988 | PMC:PMC12832370 | DOI:10.3389/fneur.2025.1684824

Front Neurol. 2026 Jan 12;16:1618388. doi: 10.3389/fneur.2025.1618388. eCollection 2025.

ABSTRACT

Right temporal lobe epilepsy (rTLE) is associated with disruptions in functional brain networks and structural connectivity, yet underlying mechanisms remain unclear. This study investigated the alterations in modular interactions, connector hub (CH) topology, and related structural changes in rTLE patients. It included 30 rTLE patients and 30 matched healthy controls (HCs), all of whom underwent resting-state functional MRI (rs-fMRI), diffusion-weighted imaging (DWI), and volumetric MRI (vMRI). Functional networks were analyzed by assessing modular interactions, functional connectivity (FC), and CH topological properties. White matter microstructural differences were examined using tract-based spatial statistics (TBSS), while cortical morphometry was evaluated in key CH regions. Compared with HCs, rTLE patients showed reduced modularity (Q), small-world index (σ), and clustering coefficient (γ), along with enhanced modular interactions, particularly between the supplementary motor area (SMA) and inferior temporal gyrus (ITG). CHs exhibited increased participation coefficient (PC), within-module degree z-score (WMD), and local efficiency. Structural analyses revealed reduced fractional anisotropy (FA) and increased radial diffusivity (RD) in the corpus callosum, as well as cortical thinning in the ITG and SMA. We confirmed that rTLE is characterized by disrupted modular architecture and CH topology, leading to network reorganization and associated structural abnormalities. These findings offer new insights into rTLE pathophysiology.

PMID:41602986 | PMC:PMC12832528 | DOI:10.3389/fneur.2025.1618388

Front Neurol. 2026 Jan 12;16:1738198. doi: 10.3389/fneur.2025.1738198. eCollection 2025.

ABSTRACT

INTRODUCTION: Cognitive impairment is a common complication of chronic kidney disease (CKD), but its underlying mechanisms are not fully understood. This study aims to investigate the glymphatic system function in CKD patients with and without cognitive impairment (CI) by analyzing the coupling between the global blood oxygen level-dependent (gBOLD) signal and the cerebrospinal fluid (CSF) signal using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: Twenty-nine patients with CKD were enrolled (19 with CI and 10 without), along with 22 healthy controls (HCs). All patients underwent high-resolution structural MRI and rs-fMRI scans. The gBOLD-CSF coupling was quantified by calculating the maximum negative correlation within a predefined time-lag range between the gBOLD signal and the fourth ventricular CSF signal. The gBOLD-CSF coupling was compared between the CKD and HC groups using analysis of covariance (ANCOVA), adjusting for age, sex, education, and mean framewise displacement (FD). The difference between patients with CKD with and without CI was assessed using ANCOVA, after adjusting for age, sex, education, hypertension, diabetes, and mean FD. Partial correlation analysis was performed to explore the associations between gBOLD-CSF coupling and clinical indicators, such as estimated glomerular filtration rate (eGFR), Montreal Cognitive Assessment (MoCA) scores, and other laboratory data.

RESULTS: After adjusting for covariates, gBOLD-CSF coupling was significantly lower in the CKD group than in the HC group (β = -0.178, p = 0.003). This finding remained robust in sensitivity analyses adjusting for hypertension and diabetes. Within the CKD group, patients with CI had significantly lower gBOLD-CSF coupling than those without CI (β = -0.135, p = 0.040). Correlation analyses revealed that gBOLD-CSF coupling tended to be positively associated with hemoglobin, MoCA score, and eGFR, and negatively associated with blood urea and creatinine; however, none of these correlations reached statistical significance after false discovery rate correction (all q > 0.05).

CONCLUSION: Patients with CKD exhibit impaired glymphatic system function, manifested as reduced gBOLD-CSF coupling, which is associated with the severity of CI. These findings support the hypothesis that impaired glymphatic clearance may contribute to cognitive decline in CKD via the kidney-brain axis. Larger longitudinal studies are needed to validate its clinical significance.

PMID:41602980 | PMC:PMC12832948 | DOI:10.3389/fneur.2025.1738198

IBRO Neurosci Rep. 2024 Dec 4;19:1128-1140. doi: 10.1016/j.ibneur.2024.11.014. eCollection 2025 Dec.

ABSTRACT

Mapping consistent longitudinal intrinsic connectivity networks (ICNs) is crucial for understanding brain functional development over various life stages. However, achieving consistent longitudinal ICNs has been challenging due to the lack of methodologies that maintain temporal consistency. To address this gap, we introduce an innovative approach named Longitudinal Sparse Dictionary Learning (LSDL). This method utilizes an additional Frobenius norm to bridge gaps between consecutive ICNs, facilitating the continuous transfer of the learned feature matrix to subsequent stages. Moreover, Matrix Backpropagation (MBP) is employed to effectively mitigate potential accumulative errors. Our validation results demonstrate that LSDL can successfully extract 21 consistent longitudinal ICNs in macaque brains. In comparative empirical evaluations with established methodologies, Fast Independent Component Analysis (FICA) and Sparse Dictionary Learning (SDL), LSDL showcases superior efficacy in modeling longitudinal functional Magnetic Resonance Imaging (fMRI) data. This approach opens new avenues for research into developmental brain dynamics and neurodegenerative disorders, providing a robust framework for tracking the evolution of brain connectivity over time.

PMID:41601563 | PMC:PMC12834029 | DOI:10.1016/j.ibneur.2024.11.014

Front Neurosci. 2026 Jan 12;19:1686273. doi: 10.3389/fnins.2025.1686273. eCollection 2025.

ABSTRACT

BACKGROUND: Patients with active ulcerative colitis (UC) frequently exhibit emotional disturbances and cognitive deficits. However, the neurobiological basis of these manifestations remains poorly understood. This study investigates neurostructural and functional alterations in UC patients using multimodal MRI to identify potential neural correlates.

METHODS: We enrolled 45 active-stage UC patients and 48 healthy controls, all of whom underwent structural MRI, resting-state functional MRI (rs-fMRI), neurocognitive testing, and clinical assessments. Regional neural activity was evaluated using fractional amplitude of low-frequency fluctuations (fALFF), while gray matter volume (GMV) was analyzed to assess structural differences. Brain regions showing significant abnormalities were further examined for correlations with cognitive performance and clinical scale results.

RESULTS: Compared to the healthy control group, the UC patient group exhibited higher scores in PSQI, PSS, SAS, and SDS. Furthermore, the UC patient group displayed varying degrees of impairment in attention, working memory, and executive function. The GMV of the bilateral thalamus in UC patients decreased, while the fALFF values in bilateral posterior cingulate gyrus (PCG) and left lingual gyrus increased. Conversely, the fALFF values in multiple brain regions, including bilateral frontal lobes, the right temporal lobe, and the right inferior parietal lobule, were decreased. Multiple brain regions with reduced activity in the bilateral frontal lobes are closely related to emotions and executive control, while the increased activity in the bilateral PCG is strongly correlated with stress and anxiety. The reduction GMV in bilateral thalamic is associated with working memory and attention.

CONCLUSION: Cognitive impairment and emotional abnormalities in UC are associated with the functional activity and structure of multiple brain regions, particularly in the bilateral frontal lobes, PCG and thalamus. These findings provide potential neuroimaging evidence for the activation of the gut-brain axis due to chronic inflammation, and that certain brain regions may be considered as key targets for predicting cognitive impairment for UC patients.

PMID:41601538 | PMC:PMC12832693 | DOI:10.3389/fnins.2025.1686273

Front Neurosci. 2026 Jan 12;19:1714446. doi: 10.3389/fnins.2025.1714446. eCollection 2025.

ABSTRACT

PURPOSE: Herpes simplex encephalitis (HSE) is a severe neurological condition associated with significant cognitive impairment and structural brain changes. This study aimed to investigate microstructural and functional connectivity (FC) alterations in HSE patients and their association with cognitive function, cerebrospinal fluid (CSF) parameters, and inflammatory markers.

METHODS: A single-center cohort study was conducted with 73 HSE patients and 76 cognitively unimpaired controls. Voxel-based morphometry (VBM) and resting-state functional MRI (rs-fMRI) were used to assess VBM grey matter volume (GMV) and FC. Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA). CSF pressure, protein levels, and proinflammatory cytokines (IL-6, IL-1β, IL-2, IL-4, IL-5, IL-10) were measured. Statistical analyses included group comparisons and multivariable regression adjusted for age, gender, and hypertension.

RESULTS: HSE patients exhibited significant GMV reductions in the right hippocampal gyrus, left precuneus, and left posterior cingulate gyrus (all p < 0.001). Enhanced FC was observed between the left hippocampus and medial prefrontal cortex (mPFC), while weakened connectivity was noted between the left precuneus, posterior cingulate gyrus, and mPFC in controls. Cognitive scores (MoCA) were lower in HSE patients (p < 0.001) and positively correlated with GMV and FC metrics (p < 0.05). Elevated CSF pressure, protein, and proinflammatory cytokines (particularly IL-6) were negatively associated with cerebral metrics (p < 0.001). A significant interaction between IL-6 and cerebral metrics further influenced cognitive outcomes (p < 0.05).

CONCLUSION: HSE is associated with distinct microstructural and functional connectivity changes that are correlated with cognitive impairment and neuroinflammation. Our findings suggest a potential interaction between IL-6 levels, cerebral alterations, and cognitive dysfunction, which may inform the exploration of neuroimaging and inflammatory biomarkers in personalized therapeutic strategies. However, these represent observational associations, and further prospective studies are needed to validate these findings and establish causal relationships.

PMID:41601536 | PMC:PMC12833072 | DOI:10.3389/fnins.2025.1714446

Front Neurosci. 2026 Jan 12;19:1629305. doi: 10.3389/fnins.2025.1629305. eCollection 2025.

ABSTRACT

OBJECTIVE: This review aimed to summarize neuroimaging evidence on the effects of acupuncture in post-ischemic stroke cognitive impairment (PISCI) and to explore its potential neural mechanisms.

METHODS: A systematic search was conducted across multiple databases, including China National Knowledge Infrastructure (CNKI), SinoMed (China Biology Medicine Disc), the Chinese Scientific Journal Database (VIP), Wanfang Data, PubMed, the Cochrane Library, Embase, and Web of Science. Studies were selected according to inclusion and exclusion criteria. Risk of bias was assessed for all eligible studies.

RESULTS: Eight studies met the inclusion criteria. These studies utilized resting-state functional magnetic resonance imaging (rs-fMRI) and magnetic resonance spectroscopy (MRS) to investigate the effects of acupuncture on brain activity and metabolic changes. The neuroimaging findings showed that all studies focused on the sustained effects of acupuncture on brain functional activity.

CONCLUSIONS: This review provides preliminary neuroimaging evidence supporting the potential benefits of acupuncture for PISCI. The findings suggest that the possible mechanisms of acupuncture for PISCI involve changes in the activity and enhanced functional connectivity of cognition-related brain regions. Additionally, acupuncture may influence brain networks and regulate neurochemical metabolites within cognition-related regions. However, as this field remains in its early stages, further validation is needed. Future studies should focus on well-designed, multicenter randomized controlled trials (RCTs) with large sample sizes and incorporate multiple neuroimaging techniques to better clarify and verify the neural mechanisms of acupuncture in PISCI.

SYSTEMATIC REVIEW REGISTRATION: PROSPERO, identifier: CRD420250652194.

PMID:41601528 | PMC:PMC12832758 | DOI:10.3389/fnins.2025.1629305

Sensors (Basel). 2026 Jan 21;26(2):716. doi: 10.3390/s26020716.

ABSTRACT

Independent vector analysis (IVA) has emerged as a powerful tool for fusing and analyzing functional magnetic resonance imaging (fMRI) data. Applying IVA to multi-task fMRI data enhances analytical power by capturing the relationships across different tasks in order to discover their underlying multivariate relationship to one another. Incorporation of prior information into IVA enhances the separability and interpretability of estimated components. In this paper, we demonstrate successful fusion of multi-task fMRI feature data under two settings: constrained IVA and constrained transposed IVA (tIVA). We show that using these methods for fusing multi-task fMRI feature data offers novel ways to improve the quality and interpretability of the analysis. While constrained IVA extracts components linked to distinct brain networks, tIVA reverses the roles of spatial components and subject profiles, enabling flexible analysis of behavioral effects. We apply both methods to a multi-task fMRI dataset of 247 subjects. We demonstrate that for task-based fMRI, structural MRI (sMRI) references provide a better match for task data than resting-state fMRI (rs-fMRI) references, and using sMRI priors improves identification of group differences in task-related networks, such as the sensory-motor network during the Auditory Oddball (AOD) task. Additionally, constrained tIVA allows for targeted investigation of the effects of behavioral variables by applying them individually during the analysis. For instance, by using the letter number sequence subtest, a measure of working memory, as a behavioral constraint in tIVA, we observed significant group differences in the auditory and sensory-motor networks during the AOD task. Results show that the use of two constrained approaches, guided by well-aligned structural and behavioral references, enables a more comprehensive analysis of underlying brain function as modulated by task.

PMID:41600509 | DOI:10.3390/s26020716