Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Aims: Motor abnormalities have been identified as one common symptom in patients with generalized tonic-clonic seizures (GTCS) inspiring us to explore the disease in a motor execution condition, which might provide novel insight into the pathomechanism.
Methods: Resting-state and motor-task fMRI data were collected from 50 patients with GTCS, including 18 patients newly diagnosed without antiepileptic drugs (ND_GTCS) and 32 patients receiving antiepileptic drugs (AEDs_GTCS). Motor activation and its association with head motion and cerebral gradients were assessed. Whole-brain network connectivity across resting and motor states was further calculated and compared between groups.
Results: All patients showed over-activation in the postcentral gyrus and the ND_GTCS showed decreased activation in putamen. Specifically, activation maps of ND_GTCS showed an abnormal correlation with head motion and cerebral gradient. Moreover, we detected altered functional network connectivity in patients within states and across resting and motor states by using repeated-measures analysis of variance. Patients did not show abnormal connectivity in the resting state, while distributed abnormal connectivity in the motor-task state. Decreased across-state network connectivity was also found in all patients.
Conclusion: Convergent findings suggested the over-response of activation and connection of the brain to motor execution in GTCS, providing new clues to uncover motor susceptibility underlying the disease.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11033329 | PMC |
| http://dx.doi.org/10.1111/cns.14672 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Unravelling the molecular network structure of biohybrid hydrogels.
Mater Today Bio
October 2025
Leibniz Institute of Polymer Research Dresden, Division Polymer Biomaterials Science, Max Bergmann Center of Biomaterials Dresden, 01069, Dresden, Germany.
Glycosaminoglycan-based biohybrid hydrogels represent a powerful class of cell-instructive materials with proven potential in tissue engineering and regenerative medicine. Their biomedical functionality relies on a nanoscale polymer network that standard microscopy techniques cannot resolve. Here, we introduce an advanced analytical approach that integrates transmission electron microscopy, X-ray scattering, and computer simulations to directly and quantitatively characterize the nanoscale molecular network structure of these hydrogels.
View Article and Find Full Text PDFFully-connected network-based prediction model for lymph node metastasis in clinical early-stage endometrial cancer: development and validation in two centers.
Front Oncol
August 2025
Department of Gynecology, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Objective: The risk of lymph node metastasis significantly influences the choice of surgical strategy for patients with early-stage endometrial cancer. While sentinel lymph node dissection can be considered in clinically early-stage endometrial cancer, lymph node evaluation might be omitted in patients with very low risk of lymph node metastasis. This study aims to develop a predicting model for lymph node metastasis in these patients, identifying potential metastases as thoroughly as possible to provide clinicians with a preoperative reference that helps in decisions about surgical procedures and treatments.
View Article and Find Full Text PDFHybrid two-stage CNN for detection and staging of periodontitis on panoramic radiographs.
J Oral Biol Craniofac Res
August 2025
Neura Integrasi Solusi, Jl. Kebun Raya No. 73, Rejowinangun, Kotagede, Yogyakarta, 55171, Indonesia.
Background: Periodontal disease is an inflammatory condition causing chronic damage to the tooth-supporting connective tissues, leading to tooth loss in adults. Diagnosing periodontitis requires clinical and radiographic examinations, with panoramic radiographs crucial in identifying and assessing its severity and staging. Convolutional Neural Networks (CNNs), a deep learning method for visual data analysis, and Dense Convolutional Networks (DenseNet), which utilize direct feed-forward connections between layers, enable high-performance computer vision tasks with reduced computational demands.
View Article and Find Full Text PDFIndoor Air Quality Conditions and Respiratory Virus Detections in Elementary Schools-Kansas City, Missouri, February-March 2023.
Indoor Air
January 2025
National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Background/objectives: Respiratory viruses circulate year-round and can spread indoors via inhalation of airborne particles. Effective ventilation and filtration may reduce transmission, particularly in school settings where children and staff spend significant time. This study examines the impact of indoor air quality (IAQ) and ventilation in schools on respiratory virus detection.
View Article and Find Full Text PDFBrain network of athletes in motor imagery and action anticipation: an ALE meta-analysis and MACM analysis.
Front Sports Act Living
August 2025
Faculty of Physical Education, China West Normal University, Nanchong, China.
Understanding how athletes mentally simulate and anticipate actions provides key insights into experience-driven brain plasticity. While previous studies have investigated motor imagery and action anticipation separately, little is known about how their underlying neural mechanisms converge or diverge in expert performers. This study conducted a meta-analysis using activation likelihood estimation (ALE) and meta-analytic connectivity modeling (MACM) to compare brain activation patterns between athletes and non-athletes across both tasks.
View Article and Find Full Text PDF