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Psychoradiology. 2025 Oct 13;5:kkaf027. doi: 10.1093/psyrad/kkaf027. eCollection 2025.

ABSTRACT

BACKGROUND: The thalamo-prefrontal white matter (WM) pathway, a core structural element of the frontal-limbic system disrupted in premenstrual syndrome (PMS), remains poorly understood.

METHODS: Diffusion tensor imaging (DTI), functional MRI (fMRI), and serum cytokine levels were collected from 41 PMS participants and 51 healthy controls (HCs), all diagnosed using the Daily Record of Severity of Problems (DRSP) scale. Bilateral thalamic-frontal WM pathways-the anterior thalamic radiations (ATRs)-were reconstructed using probabilistic fiber tracking. Two-sample tests examined group differences in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and amplitude of low-frequency fluctuation (ALFF) within bilateral ATRs. Spearman correlations assessed associations among these MRI metrics, inflammatory cytokines, and DRSP scores. Machine learning models further evaluated the diagnostic and predictive utility of left ATR features combined with inflammatory cytokines.

RESULTS: Compared to HCs, PMS patients exhibited increased MD, AD, RD, and ALFF values in the left ATR, as well as elevated tumor necrosis factor (TNF)-α levels. Correlation analysis revealed that these MRI alterations in the left ATR and TNF-α levels were linked to DRSP scores. Additionally, the machine learning models constructed using the optimal feature subset, involved in MD, AD and ALFF of left ATR as well as TNF-α, demonstrated robust performance in diagnosing PMS and predicting DRSP scores.

CONCLUSION: These findings suggest altered thalamo-frontal WM connectivity and elevated TNF-α in PMS. The left ATR may serve as a biomarker of PMS neuro-mechanisms when combined with multi-MRI and inflammation metrics.

PMID:41200094 | PMC:PMC12586991 | DOI:10.1093/psyrad/kkaf027

AJNR Am J Neuroradiol. 2025 Nov 6. doi: 10.3174/ajnr.A8881. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Visual disturbance is a major complication in nonfunctioning pituitary adenoma (NFPA) due to chiasmal compression. While neuroimaging studies have established brain dysfunction in visually impaired patients from chiasmal compression, the brain dynamic features of spontaneous activity and functional connectivity remain underexplored. This cross-sectional study aims to explore changes in temporal variability of spontaneous activity and connectivity in visually impaired patients with NFPA by resting-state functional MRI.

MATERIALS AND METHODS: Thirty-six patients with NFPA with visual impairment and 36 healthy controls were recruited and underwent resting-state fMRI scans. Dynamic amplitude of low-frequency fluctuation (dALFF) and dynamic functional connectivity (dFC) analyses were performed to assess temporal variability in brain activity and interregional communication. Associations between altered dALFF/dFC and the severity and duration of chiasmal compression, as well as visual field defect severity (quantified by mean deviation), were further evaluated.

RESULTS: Compared with healthy controls, patients with a nonfunctioning pituitary exhibited significantly reduced dALFF in the right lingual gyrus (LING) and bilateral calcarine fissure and surrounding cortex (CAL). Additionally, patients showed a significant reduction in dFC between the right LING and the bilateral precuneus. Our exploratory correlation analyses revealed that the altered dALFF values in the bilateral CAL and right LING were positively correlated with chiasmal volume, and the altered dALFF in the left CAL was negatively correlated with suprasellar extension distance. Additionally, the altered dALFF values in the bilateral CAL were positively correlated with mean deviation.

CONCLUSIONS: Patients with NFPA with visual impairment exhibited decreased temporal variability in brain activity and functional connectivity within visual-related regions, offering new insights into the neuropathologic mechanisms underlying visual disturbance in nonfunctioning pituitary adenoma.

PMID:41198225 | DOI:10.3174/ajnr.A8881

Med Image Anal. 2025 Nov 2;107(Pt B):103861. doi: 10.1016/j.media.2025.103861. Online ahead of print.

ABSTRACT

Functional magnetic resonance imaging (fMRI) is a crucial tool in neuroscience for capturing dynamic brain activity across spatial and temporal dimensions. However, fMRI data are high-dimensional, spatiotemporal interdependent, and often noisy, posing significant challenges for representing brain functions and associated applications. To effectively extract spatiotemporal features from fMRI data and map functional brain networks, this study proposes a novel 3D Masked Autoencoder architecture integrated with Spatiotemporal Transformers (MAE-ST). The proposed framework leverages self-supervised learning through partial data masking, enabling efficient spatial feature extraction while mitigating dependence on labeled datasets and enhancing noise robustness. In the MAE-ST encoder, visual transformer (ViT) module and temporal transformer module are employed to extract fMRI spatial features and temporal features respectively, and then the decoder reconstructs fMRI sequence with latent variables that are output by the encoder. After training, the latent variables can be regarded as the temporal features of fMRI data, which are used to estimate functional brain networks by regression analysis. Comprehensive experimental results on HCP task fMRI datasets and ADHD-200 resting state fMRI datasets demonstrated that the proposed MAE-ST model achieves superior performance in mapping both task-evoked networks and resting state networks, compared with the latest deep learning models and traditional methods. Moreover, we construct a classification pipeline based on the MAE-ST model and apply it on ADHD-200 dataset. The MAE-ST model here is used to construct data-driven brain atlas and calculate functional connectivity for classification study. The results indicated that the proposed classification pipeline outperforms several existing methods that used predefined atlases, further demonstrated the effectiveness and superiority of the proposed MAE-ST model. This work highlights the potential of combining masked autoencoders with Transformers for handling global feature extraction in both spatial and temporal dimensions of 4D fMRI data, offering a new framework for functional brain network modeling and brain disorder identification.

PMID:41197226 | DOI:10.1016/j.media.2025.103861

Psoriasis (Auckl). 2025 Oct 31;15:535-543. doi: 10.2147/PTT.S554255. eCollection 2025.

ABSTRACT

PURPOSE: Interleukin-17A (IL-17A) drives psoriasis and central nervous system neuroinflammation, but clinical research on whether IL-17A-targeted biotherapy modulates brain activity to improve neuropsychiatric outcomes in psoriasis is lacking. This study aims to investigate brain functional changes, cognitive impairment, and the effects of IL-17A monoclonal antibody therapy in psoriasis vulgaris.

PATIENTS AND METHODS: Regular secukinumab treatment. Meanwhile, 20 healthy controls (HCs) matched in age and gender were enrolled. The patients underwent functional magnetic resonance imaging (fMRI) before treatment and 48 weeks after treatment. The healthy controls also had fMRI scans. It assessed clinical data, cognition/neuropsych status (MoCA, SDS, SAS), disease severity/quality of Life (PASI/DLQI), and brain function via rs-fMRI (ALFF/ReHo).

RESULTS: Compared to healthy controls, the psoriasis vulgaris patients showed increased ALFF in the frontal lobe, as well as increased frontal ReHo. The treatment group showed signal recovery in some brain regions. Patients before treatment had lower MoCA scores vs controls (P < 0.001)) and higher SAS/SDS scores (SAS, P < 0.0001; SDS, P < 0.05). Patients after treatment showed higher MoCA scores vs before treated (P < 0.05), similar to controls, with lower SAS scores (P < 0.0001) and reduced PASI/DLQI (P < 0.0001).

CONCLUSION: Psoriasis is associated with brain dysfunction and neuropsychiatric symptoms. IL-17A antibody therapy improves skin symptoms, restores brain function, and alleviates neuropsychiatric issues vs untreated patients, supporting multidimensional treatment.

PMID:41195091 | PMC:PMC12584804 | DOI:10.2147/PTT.S554255

Brain Commun. 2025 Oct 14;7(6):fcaf399. doi: 10.1093/braincomms/fcaf399. eCollection 2025.

ABSTRACT

The entorhinal cortex is one of the earliest sites of tau tangle deposition in Alzheimer's disease. Existing connectome studies focus on tau propagation along direct, first-order connections between brain regions, overlooking multi-step, higher-order connections that contribute to the spread of pathology in the brain. We propose a novel quantitative integration of graph theory-based stepwise connectivity with low-dimensional connectome gradient space, which reflects the brain's hierarchical organization. This allows us to elucidate multi-step connectivity between the entorhinal cortex (seed region) and the rest of the brain along the major axes of functional and structural brain organization. In this study, we included 213 participants from the Translational Biomarkers in Aging and Dementia (103 amyloid-negative cognitively normal, 35 amyloid-positive cognitively normal, and 75 cognitively impaired) with diffusion-weighted MRI, resting-state functional MRI, and 18F-MK6240 tau-PET. Through the novel integration between stepwise connectivity and connectome gradients, we observed hypoconnectivity from the entorhinal cortex to the transmodal end of the functional gradient and to the posterior end of the structural gradient. On the other hand, multi-step connections from the entorhinal cortex showed increased connectivity toward both unimodal (e.g. somatomotor) and transmodal (e.g. frontoparietal) networks of the functional gradient as well as anterior ends of the structural gradient, potentially initiating new paths for tau spread. Finally, tau-connectivity correlations shifted spatially within connectome gradient space, moving from the highest-order (default mode network/limbic) cognitive system of the functional gradient in the preclinical stage (amyloid-positive cognitively normal) to the second-highest order (frontoparietal) system in the clinical stage (cognitively impaired). In conclusion, we demonstrate widespread network reorganization of both direct and indirect, multi-step connections that are associated with patterns of tau spread in Alzheimer's disease.

PMID:41194888 | PMC:PMC12585350 | DOI:10.1093/braincomms/fcaf399

Brain Behav. 2025 Nov;15(11):e70975. doi: 10.1002/brb3.70975.

ABSTRACT

OBJECTIVES: This study used resting state functional magnetic resonance imaging (rs-fMRI) technology to explore the characteristics of brain functional activity in migraine patients without aura (MwoA) in middle and high altitude areas during interictal periods through two analysis methods, the regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF).

METHODS: This study was a prospective research that included 41 patients with MwoA in the interictal phase, who visited the Department of Neurology at Qinghai Provincial People's Hospital between January 2023 and January 2024. 39 healthy controls (HCs) matched for age and sex were also recruited.

RESULTS: Compared with HCs group, the ALFF values of right superior temporal gyrus and the right hippocampus in MwoA group at mid-to-high altitude were decreased (voxel level p < 0.001, cluster level p < 0.05, Gaussian random field, GRF corrected). The ReHo values of bilateral rectus gyrus and left cerebellum in MwoA group at mid-to-high altitude were significantly increased, while the ReHo values of left cingulate gyrus, bilateral precuneus and bilateral supplementary motor area were significantly decreased (voxel level p < 0.001, cluster level p < 0.05, GRF corrected). The correlation analysis showed that the duration of disease in MwoA group was negatively correlated with the z-ALFF value of the right hippocampus(r = -0.56, p = 0.004, Bonferroni correction). The HIT-6 score was negatively correlated with the z-ALFF value of the right superior temporal gyrus (r = -0.48, p = 0.001, Bonferroni correction). The SDS score was negatively correlated with the bilateral precuneus z-ReHo values (r = -0.42, p = 0.03, L; r = -0.46, p = 0.01, R, Bonferroni correction).

CONCLUSION: Several brain regions in MwoA patients from mid-to-high altitude areas exhibit abnormal spontaneous neural activity through ALFF and ReHo assessments. These brain regions are closely associated with pain processing, cognitive functions, motor control, attention, and emotional regulation. The functional abnormalities in these regions may be relevant to the pathophysiology of MwoA.

PMID:41194470 | DOI:10.1002/brb3.70975

Magn Reson Imaging. 2025 Nov 3:110556. doi: 10.1016/j.mri.2025.110556. Online ahead of print.

ABSTRACT

PURPOSE: To develop a comprehensive reconstruction pipeline that simultaneously addresses 2D Nyquist and aliasing artifacts in echo-planar imaging (EPI) data acquired using various schemes, including single-shot, multi-shot, parallel, and multi-band EPI.

METHODS: We introduce a novel 2D Nyquist artifact correction method that extends our previously reported phase-search reconstruction approach. A series of phase-corrected images are generated using a range of candidate phase values, and the corresponding coil sensitivity profiles are compared with known profiles to estimate an optimal 2D Nyquist phase correction map. In addition, we propose an integrated reconstruction procedure that corrects aliasing artifacts arising from 2D Nyquist effects, shot-to-shot motion-induced phase variations, and both in-plane and through-plane acceleration schemes. The proposed methods were evaluated using resting-state fMRI data from 30 healthy volunteers.

RESULTS: The proposed method substantially reduced residual artifacts in EPI data, as measured by the ghost-to-signal ratio. The resulting default-mode network maps showed improved correspondence with known reference networks compared to those obtained using conventional 1D Nyquist artifact correction methods.

CONCLUSION: The developed reconstruction pipeline effectively corrects multiple sources of aliasing artifacts in EPI data, offering improved image quality and functional sensitivity across a wide range of EPI acquisition schemes.

PMID:41192812 | DOI:10.1016/j.mri.2025.110556

Neuropsychologia. 2025 Nov 3:109313. doi: 10.1016/j.neuropsychologia.2025.109313. Online ahead of print.

ABSTRACT

Although numerous studies have primarily associated creativity with spontaneous thought and its corresponding neural networks, effective creativity entails much more than uninhibited ideation. It requires the capacity to filter out irrelevant information, maintain optimal attentional tuning, and strategically regulate and refine innovative outputs. We argue that a robust and adaptive executive control network (ECN), operating in concert with attentional networks, is essential for creativity. Accordingly, we hypothesized that high-creative individuals would exhibit enhanced top-down modulation from both the ECN and attention networks onto other brain networks. To test this hypothesis, we employed resting-state fMRI and Dependency Network Analysis (DEPNA) to examine differences in hierarchical influence patterns across multiple brain regions and networks between individuals with high and low creative abilities. Our analyses revealed that high-creative individuals, relative to their low-creative counterpart, exhibited increased influence of specific brain regions on inter-regional functional connectivity across multiple brain regions. These regions demonstrating augmented influence were predominantly localized within the ECN and ventral attention network (VAN), specifically the bilateral inferior frontal gyrus (IFG), bilateral inferior frontal sulcus (IFS), and right middle frontal gyrus (MFG). Moreover, high-creative individuals displayed significantly greater influence of the ECN and the dorsal attention network (DAN) on other large-scale brain networks. These findings suggest top-down cognitive and attentional control may be crucial in facilitating creativity.

PMID:41192791 | DOI:10.1016/j.neuropsychologia.2025.109313

Conscious Cogn. 2025 Nov 4;136:103957. doi: 10.1016/j.concog.2025.103957. Online ahead of print.

ABSTRACT

Previous research has reported inconsistent findings regarding the relationship between working memory capacity (WMC) and tendencies for future-oriented mind wandering. To address this, the present study incorporated self-relevant elements into probes to further specify self-relevant, future-oriented (self-future) mind wandering, aiming to clarify its relationship with WMC and explore the functional connectivity mediating this association. Ninety-four participants completed the sustained attention to response task (SART) with thought probes, the operation span (OSPAN) task, and the reading span (RSPAN) task. Resting-state functional magnetic resonance imaging (rs-fMRI) data were also collected. The findings demonstrated a significant positive association between WMC and self-future mind wandering. Additionally, functional connectivity between the left lateral prefrontal cortex (LPFC) and the left lateral premotor cortex (LPMC) was positively associated with both WMC and self-future mind wandering. Further analyses revealed that LPFC-LPMC connectivity statistically mediated the relationship between WMC and self-future mind wandering. Conversely, self-future mind wandering also mediated the association between WMC and LPFC-LPMC connectivity. These findings are consistent with the context regulation hypothesis and provide insight into the underlying mechanisms. Specifically, LPFC-LPMC connectivity may link to the integration of motor sequence predictions and anticipated speech and nonverbal communication, whereas the reverse mediation suggests that self-future mind wandering may contribute to shaping neural connectivity associated with executive control.

PMID:41192099 | DOI:10.1016/j.concog.2025.103957

Neuroimage Rep. 2025 Oct 22;5(4):100296. doi: 10.1016/j.ynirp.2025.100296. eCollection 2025 Dec.

ABSTRACT

There is a growing interest in using resting-state functional connectivity (RSFC) to investigate language processing and recovery in post-stroke aphasia due to its limited dependence on an individual's ability to follow directions and perform tasks, or the severity of their aphasia. However, the test-retest reliability of RSFC in people with aphasia has not been established, raising questions about the strength and validity of inferences based on this technique. In this study, we examined the reliability of RSFC at the level of individual edges (i.e., connections) in 14 adults with chronic aphasia due to left-hemisphere stroke. Intraclass correlations (ICCs) between two resting-state scans obtained over a few days were computed for every edge in a whole-brain network and several cognitive and language subnetworks. Based on median ICCs, reliability was fair at longer scan durations (10-12 min) and better in most subnetworks than the whole brain. Reliability was also positively associated with connectivity strength and had a weak negative relationship with inter-node distance (i.e., the distance between the regions that form an edge). Edges in the right hemisphere were more reliable than those in the left hemisphere and between hemispheres, though all three sets of edges were fairly reliable. The results indicate that edge-level RSFC is acceptably reliable for continued use in aphasia research but highlight the need for strategies to ensure that inferences are based on valid results, such as using sufficiently long scans and focusing analyses on established subnetworks, especially in longitudinal contexts.

PMID:41190293 | PMC:PMC12581729 | DOI:10.1016/j.ynirp.2025.100296

Sci Rep. 2025 Nov 4;15(1):38499. doi: 10.1038/s41598-025-21596-0.

ABSTRACT

Changes in functional connectivity (FC) strength involving the medial temporal lobe (MTL) and posteromedial cortex (PMC) are related to early Alzheimer's pathology and alterations in episodic memory performance in cognitively unimpaired older adults, but their dynamics remain unclear. We examined how longitudinal changes in FC involving MTL and PMC during resting-state, episodic memory encoding, and retrieval relate to subsequent amyloid- and tau-PET burden, longitudinal episodic memory performance, and the APOE4 genotype in 152 cognitively unimpaired older adults from the PREVENT-AD cohort. We found APOE4- and fMRI paradigm-dependent associations of change in FC strength with pathology burden and change in episodic memory performance. Decreasing FC over time, or "hypoconnectivity", within PMC during rest in APOE4 carriers and during retrieval in APOE4 non-carriers was related to more amyloid and tau, respectively. Conversely, increasing FC over time, or "hyperconnectivity", within MTL during encoding in APOE4 carriers and between MTL and PMC during retrieval independent of APOE4 status was related to more tau. Further, increasing FC between MTL and PMC during rest, unlike during encoding, was beneficial for episodic memory. Our study highlights that pathology-related episodic memory network changes manifest differently during rest and task and have differential implications for episodic memory trajectories.

PMID:41188354 | DOI:10.1038/s41598-025-21596-0

Brain Struct Funct. 2025 Nov 4;230(8):169. doi: 10.1007/s00429-025-03038-9.

ABSTRACT

Social phobia (SP) adversely affects individual as it often drives lower positive affect (PA) in social situations. This study aims to investigate the role of Lack of Control (LC) and its neural underpinnings in this process. We recruited 268 participants who completed measurements of SP tendency, LC, and PA at baseline (T1) and after two years (T2). All underwent a resting-state fMRI scan at T1. Findings revealed bidirectional associations among LC, SP tendency and PA, and the mediating effect of LC. Specifically, the LC at T1 was associated with SP tendency (β = 0.164) and PA (β = -0.191) at T2, while SP tendency (β = 0.103) and PA (β = -0.175) at T1 were associated with LC at T2. Additionally, Functional connectivity (FC) analyses and brain-behavior models further demonstrated that: (1) SP tendency at T1 was associated with LC at T2 through the FC networks involving the bilateral angular gyrus and left middle occipital gyrus (point estimate = -0.045, 95% CI [-0.070, -0.019]), and (2) LC at T2 was associated with PA at T2 via the FC networks of the left lingual gyrus, right cuneus and fusiform gyrus (point estimate = 0.040, 95% CI [0.007, 0.058]). This elucidates the cognitive and neural correlates through which SP tendency negatively affects PA, emphasizing the crucial role of LC in this relationship. Unraveling this mechanism offers a potential path for clinical interventions aimed at improving the mental health of individuals high in SP tendency.

PMID:41186751 | DOI:10.1007/s00429-025-03038-9

Brain Struct Funct. 2025 Nov 4;230(8):168. doi: 10.1007/s00429-025-03041-0.

NO ABSTRACT

PMID:41186746 | DOI:10.1007/s00429-025-03041-0

Nat Neurosci. 2025 Nov 3. doi: 10.1038/s41593-025-02099-7. Online ahead of print.

ABSTRACT

High-amplitude coactivation patterns are sparsely present during resting-state functional magnetic resonance imaging (fMRI), yet they drive functional connectivity and resemble task activation patterns. However, little research has characterized the remaining majority of the resting-state signal. Here, we introduce caricaturing, a method for projecting resting-state data onto a subspace orthogonal to a manifold of coactivation patterns estimated from task fMRI data. This removes linear combinations of these coactivation patterns from resting-state data to create caricatured connectomes. We used task data from two large-scale neuroimaging datasets to construct a manifold of task coactivation patterns and created caricatured connectomes. These connectomes exhibit lower between-individual similarity and higher identifiability and could be used to predict phenotypic measures, representing individual differences in behavior, often to a greater degree than standard connectomes. Our results show that there is a useful signal beyond the dominant coactivations that drive resting-state functional connectivity, which may better characterize the brain's intrinsic functional architecture.

PMID:41184631 | DOI:10.1038/s41593-025-02099-7

J Neurotrauma. 2025 Oct 23. doi: 10.1177/08977151251377469. Online ahead of print.

ABSTRACT

Predicting outcome for patients with acute severe traumatic brain injury (TBI) is imprecise, relying on neurological examination, structural neuroimaging, and resting-state electroencephalography (EEG) to serve as proxies for brain function. We implemented a multimodal assessment protocol to determine whether detection of consciousness using advanced tools, including standardized behavioral evaluation, advanced EEG, and functional magnetic resonance imaging (fMRI), is associated with functional outcome in patients with acute severe TBI admitted to the intensive care unit (ICU). We tested the association between 6-month Disability Rating Scale (DRS) scores and acute level of consciousness on the Coma Recovery Scale-Revised (CRS-R); responses to active-motor-imagery and passive-language EEG and fMRI; and resting-state fMRI default mode network (DMN) connectivity. We consecutively enrolled 55 patients with acute severe TBI. Six-month outcome was available in 45 (45.2 ± 20.7 years old, 70% male), of whom 10 died, all due to withdrawal of life-sustaining treatment (WLST). All deaths occurred in participants who were not behaviorally following commands. Lower (i.e., better) 6-month DRS scores were observed in participants who were younger (ρ = 0.401; 95% confidence interval [CI: 0.078, 0.649]; p = 0.006]) and who were conscious (median DRS score difference [95% CI]: -11 [-20, -2]; p = 0.003) or following commands (-9 [-20, -1]; p = 0.011) on CRS-R assessment in the ICU. Evidence of command-following on EEG or fMRI did not strengthen this relationship. In participants without command-following on the CRS-R, we detected responses to active-motor-imagery (i.e., cognitive motor dissociation [CMD]) in 6/34 (18%) of participants on EEG and 8/24 (33%) participants on fMRI. We detected responses to passive-language stimuli (i.e., covert cortical processing [CCP]) in 30/33 (91%) of participants on EEG and 18/24 (75%) on fMRI. However, neither CMD nor CCP was associated with outcome on the DRS or several secondary outcome measures (e.g., dichotomous DRS, Glasgow Outcome Scale-Extended), an unexpected result that may reflect the modest sample size and high rate of WLST. In exploratory analyses, an intact DMN and the magnitude of DMN connectivity were associated with 6-month outcome on secondary outcome measures. Collectively, our results suggest that the level of consciousness in the ICU, assessed with a standardized behavioral measure, may predict recovery from severe TBI. Further research, conducted at multiple sites and with larger samples, is required to determine whether integrating behavioral, EEG, and fMRI biomarkers of consciousness is more predictive than behavioral assessment alone.

PMID:41182259 | DOI:10.1177/08977151251377469

Brain Commun. 2025 Oct 15;7(6):fcaf404. doi: 10.1093/braincomms/fcaf404. eCollection 2025.

ABSTRACT

There have been reports of altered functional connectivity in Alzheimer's disease, which is associated with the buildup of pathogenic proteins in the brain, including neurofibrillary tau tangles and amyloid-beta plaques. It is believed that the tau aggregates are the main driver of functional disconnection and resulted in cognitive decline in Alzheimer's disease. Tau propagates through connected neurons, a phenomenon often described as the 'prion-like' properties of tau, which can locally result in functional connectivity disruption. Apolipoprotein E gene allele 4 status and amyloid-beta are accelerating factors for tau-related pathological changes in Alzheimer's disease. However, the potential role of apolipoprotein E gene allele 4 and amyloid-beta in mediating the tau-related functional disconnection is not clear. I aimed to investigate the mediating effect of apolipoprotein E gene allele 4 and amyloid-beta on the local association of tau spreading on functional connections. I analysed follow-up resting-state functional MRI (fMRI) (non-baseline visit) and longitudinal tau-PET data from 211 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and 138 healthy elderly individuals from the Harvard Aging Brain Study (HABS). The follow-up resting-state fMRI (non-baseline visit) was studied in order to study the time needed effect of tau pathology. The top 10 regions with the highest probability-weighted SUVR values using Gaussian mixture models were selected as individual-level tau-PET epicentres. I looked at how the relationship between functional connectivity to epicentres and individualized connectivity-related tau spreading was mediated by amyloid-beta status and the apolipoprotein E gene allele 4 genotype. Higher rates of tau aggregation accumulation were seen in areas with stronger connectedness (shorter distance-based connectivity) to the baseline-defined tau epicentres. Moreover, the association between functional connectivity to epicentres and tau spreading through functional connections was mediated by apolipoprotein E gene allele 4 and amyloid-beta status in both dataset's participants. Tau aggregates spread through functional connections and locally disrupt connectivity between tau epicentre and non-epicentre regions, which is mediated in apolipoprotein E gene allele 4 carriers and amyloid-beta-positive participants. These findings have implications for trial designs, proposing that apolipoprotein E gene allele 4 carriers and amyloid-beta-positive participants might need earlier intervention to attenuate tau spreading and tau relative functional disconnection.

PMID:41180953 | PMC:PMC12576542 | DOI:10.1093/braincomms/fcaf404

Front Neurol. 2025 Oct 17;16:1683552. doi: 10.3389/fneur.2025.1683552. eCollection 2025.

ABSTRACT

BACKGROUND: Current evidence suggests that repetitive transcranial magnetic stimulation (rTMS), repetitive peripheral magnetic stimulation (rPMS), and their combined application can all enhance upper limb functional recovery after stroke. However, their comparative therapeutic profiles, including relative advantages and limitations, have not been systematically characterized.

OBJECTIVES: To compare rTMS, rPMS, and combined protocols for post-stroke upper limb recovery, analyzing both functional outcomes and neural mechanisms to guide therapeutic selection.

METHODS: Fifty-one stroke patients were randomly divided into an rTMS group, rPMS group, or a combined group. Before and after 3 weeks of intervention, all patients were assessed with the Fugl-Meyer assessment for the upper limb (FMA-UL), the Thumb Localizing Test (TLT), modified Barthel index (MBI), and resting-state functional magnetic resonance imaging (rs-fMRI).

RESULTS: The ΔFMA-UL and ΔMBI scores of the combined group were significantly better than the rTMS group and rPMS group. The ΔTLT scores of the combined group and rPMS were significantly better than the rTMS group, but there was no statistically significant difference in ΔTLT scores between rPMS and the combined group. Compared to the rTMS group, the rPMS group showed increased amplitude of low-frequency fluctuation (ALFF) in the ipsilesional superior frontal gyrus, cerebellum_8 area, and contralesional cerebellum_crus1; the combined group showed increased ALFF in the ipsilesional cerebellum_8 area, superior medial frontal gyrus, and contralesional cerebellum_crus2 area. Compared with the rPMS group, the combined group showed increased ALFF in the ipsilesional paracentral lobule, supplementary motor area, precentral gyrus, and superior medial frontal gyrus.

CONCLUSION: Compared with rTMS, rPMS has certain advantages in improving proprioception after stroke, and combination therapy improves both motor and proprioception. Therefore, combination therapy is recommended to better promote the recovery of brain and limb function.

CLINICAL TRIAL REGISTRATION: http://chictr.org.cn, Identifier ChiCTR2200065871.

PMID:41180535 | PMC:PMC12576412 | DOI:10.3389/fneur.2025.1683552

Front Comput Neurosci. 2025 Oct 16;19:1616472. doi: 10.3389/fncom.2025.1616472. eCollection 2025.

ABSTRACT

INTRODUCTION: Understanding the cognitive process of thinking as a neural phenomenon remains a central challenge in neuroscience and computational modeling. This study addresses this challenge by presenting a biologically grounded framework that simulates adaptive decision making across cognitive states.

METHODS: The model integrates neuronal synchronization, metabolic energy consumption, and reinforcement learning. Neural synchronization is simulated using Kuramoto oscillators, while energy dynamics are constrained by multimodal activity profiles. Reinforcement learning agents-Q-learning and Deep Q-Network (DQN)-modulate external inputs to maintain optimal synchrony with minimal energy cost. The model is validated using real EEG and fMRI data, comparing simulated and empirical outputs across spectral power, phase synchrony, and BOLD activity.

RESULTS: The DQN agent achieved rapid convergence, stabilizing cumulative rewards within 200 episodes and reducing mean synchronization error by over 40%, outperforming Q-learning in speed and generalization. The model successfully reproduced canonical brain states-focused attention, multitasking, and rest. Simulated EEG showed dominant alpha-band power (3.2 × 10-4 a.u.), while real EEG exhibited beta-dominance (3.2 × 10-4 a.u.), indicating accurate modeling of resting states and tunability for active tasks. Phase Locking Value (PLV) ranged from 0.9806 to 0.9926, with the focused condition yielding the lowest circular variance (0.0456) and a near significant phase shift compared to rest (t = -2.15, p = 0.075). Cross-modal validation revealed moderate correlation between simulated and real BOLD signals (r = 0.30, resting condition), with delayed inputs improving temporal alignment. General Linear Model (GLM) analysis of simulated BOLD data showed high region-specific prediction accuracy (R 2 = 0.973-0.993, p < 0.001), particularly in prefrontal, parietal, and anterior cingulate cortices. Voxel-wise correlation and ICA decomposition confirmed structured network dynamics.

DISCUSSION: These findings demonstrate that the framework captures both electrophysiological and spatial aspects of brain activity, respects neuroenergetic constraints, and adaptively regulates brain-like states through reinforcement learning. The model offers a scalable platform for simulating cognition and developing biologically inspired neuroadaptive systems.

CONCLUSION: This work provides a novel and testable approach to modeling thinking as a biologically constrained control problem and lays the groundwork for future applications in cognitive modeling and brain-computer interfaces.

PMID:41180117 | PMC:PMC12571814 | DOI:10.3389/fncom.2025.1616472

Front Med (Lausanne). 2025 Oct 17;12:1657241. doi: 10.3389/fmed.2025.1657241. eCollection 2025.

ABSTRACT

OBJECTIVES: Non-specific low back pain (NSLBP) is a prevalent disorder with significant global health impacts. This systematic review and meta-analysis assessed acupuncture's clinical effectiveness for NSLBP and explored its brain mechanisms using fMRI.

METHODS: A comprehensive search of multiple databases (PubMed, Embase, Cochrane Library, Web of Science, Science Direct, China National Knowledge Infrastructure, Wanfang Data, Chinese Technical Periodicals Database, and Chinese Biomedical Literature Database) was conducted from inception to July 11th, 2024. We included randomized controlled trials (RCTs) or non-RCTs resting-state functional magnetic resonance imaging to observe the effect of acupuncture on NSLBP. GingerALE 3.0.2 was used as the meta-analysis tool, and meta-analysis was performed in the Montreal Neurological Institute coordinate space.

RESULTS: The review synthesized evidence from ten studies involving 358 participants. Subgroup analyses indicated that acupuncture significantly reduced pain scores compared to sham acupuncture in both acute NSLBP (WMD = -1.04, 95% CI: -1.72 to -0.36, p = 0.003) and chronic NSLBP (WMD = -0.78, 95% CI: -1.25 to -0.31, p < 0.001). Neuroimaging analyses revealed distinct brain activation patterns: acute NSLBP showed positive activation in the right sub-lobar insula, inferior parietal lobule, medial frontal gyrus, and cingulate gyrus, while chronic NSLBP demonstrated positive activation in bilateral sub-lobar insula and negative activation in motor and prefrontal regions.

CONCLUSION: Acupuncture shows significant efficacy for NSLBP, modulating pain processing through the insula and limbic system. While these results suggest therapeutic potential for both acute and chronic NSLBP, higher-quality research is needed to validate these mechanisms.

SYSTEMATIC REVIEW REGISTRATION: Prospero registration number: CRD42022342438, URL: https://www.crd.york.ac.uk/PROSPERO/view/CRD42022342438.

PMID:41179904 | PMC:PMC12575243 | DOI:10.3389/fmed.2025.1657241

Front Hum Neurosci. 2025 Oct 17;19:1624489. doi: 10.3389/fnhum.2025.1624489. eCollection 2025.

ABSTRACT

BACKGROUND: Functional constipation (FCon) is frequently accompanied by psychological disorders, implicating the interaction between the gastrointestinal symptom and brain dysfunction in FCon. Recent studies combining electrogastrogram and resting-state functional magnetic resonance imaging (fMRI) have reported a novel gastric network. Besides, the fMRI activity of the gastric network was also coupled with the insular fMRI signal. However, little is known about the connection between the gastric network and the insula in FCon.

METHODS: Based on rs-fMRI, functional connectivity (FC) using a large sample of 652 healthy subjects identified the insular cortex as the most closely linked to the gastric network. Then, seed-based FC and dynamic functional connectivity of the gastric network and the gastric-related insular cortex were calculated and compared in 35 patients with FCon and 36 healthy controls. Constipation symptoms were measured using the Patient Assessment of Constipation Symptom Scale (PAC-SYM) and the Wexner Constipation Scale. Their relationships with alterations in the gastric network-insula subregion were investigated.

RESULTS: The posterior insular cortex presented a strong connection with the gastric network with large-scale resting-state fMRI data sets of healthy participants. FCon patients had significantly decreased FC (t = -2.19, p = 0.032) in the left posterior insula and gastric network compared to healthy controls and were significantly negatively correlated with PAC-SYM (r = -0.407, p = 0.015) and Wexner Constipation Scale (r = -0.483, p = 0.003) scores.

CONCLUSION: The abnormality of the connection between the posterior insula and the gastric network may be the prominent neuroimaging feature on FCon, which sheds light on a new perspective on the pathophysiology of FCon.

PMID:41179259 | PMC:PMC12575236 | DOI:10.3389/fnhum.2025.1624489