Tahereh Rashnavadi , Raphael F. Casseb , Kristine E. Woodward , Paolo Federico , Bradley Goodyear
{"title":"Motor and default mode network states of rest in frontal lobe epilepsy","authors":"Tahereh Rashnavadi , Raphael F. Casseb , Kristine E. Woodward , Paolo Federico , Bradley Goodyear","doi":"10.1016/j.ynirp.2025.100278","DOIUrl":null,"url":null,"abstract":"<div><div>Frontal lobe epilepsy (FLE), marked by recurrent seizures arising from the frontal lobes, can significantly impair cognitive and motor function, reducing quality of life. Recent studies suggest that epilepsies can involve functional networks throughout the brain that can be identified using resting-state functional magnetic resonance imaging (fMRI). In this study, we aimed to determine whether FLE is associated with a distinct functional network brain states. Using dynamic functional connectivity analysis in combination with <em>k</em>-means clustering, we investigated dynamic connectivity patterns of the somatomotor network (SMN) and default mode network (DMN) of ten right-hemisphere and six left-hemisphere FLE patients, as well as nine healthy controls. We found two distinct states of rest for both the SMN and DMN: a high connectivity state and a lower, more variable connectivity state that was often specific to individual patients. Both FLE groups showed reduced overall connectivity compared to controls, with the greatest differences emerging during the low connectivity state. Right FLE patients and controls exhibited relatively uniform reductions, whereas left FLE patients showed spatially specific disruptions, including reduced lateral-to-medial SMN connectivity and decreased connectivity in posterior and left-lateralized DMN regions. Our findings suggest that dynamic connectivity analysis can uncover the temporal complexity and patient-specific nature of brain network disruption in FLE, supporting the development of personalized diagnostic and treatment strategies. Further research with larger cohorts is necessary to validate these results and explore additional factors affecting brain functional connectivity.</div></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. Reports","volume":"5 3","pages":"Article 100278"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuroimage. Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666956025000467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Neuroscience","Score":null,"Total":0}
引用次数: 0
Abstract
Frontal lobe epilepsy (FLE), marked by recurrent seizures arising from the frontal lobes, can significantly impair cognitive and motor function, reducing quality of life. Recent studies suggest that epilepsies can involve functional networks throughout the brain that can be identified using resting-state functional magnetic resonance imaging (fMRI). In this study, we aimed to determine whether FLE is associated with a distinct functional network brain states. Using dynamic functional connectivity analysis in combination with k-means clustering, we investigated dynamic connectivity patterns of the somatomotor network (SMN) and default mode network (DMN) of ten right-hemisphere and six left-hemisphere FLE patients, as well as nine healthy controls. We found two distinct states of rest for both the SMN and DMN: a high connectivity state and a lower, more variable connectivity state that was often specific to individual patients. Both FLE groups showed reduced overall connectivity compared to controls, with the greatest differences emerging during the low connectivity state. Right FLE patients and controls exhibited relatively uniform reductions, whereas left FLE patients showed spatially specific disruptions, including reduced lateral-to-medial SMN connectivity and decreased connectivity in posterior and left-lateralized DMN regions. Our findings suggest that dynamic connectivity analysis can uncover the temporal complexity and patient-specific nature of brain network disruption in FLE, supporting the development of personalized diagnostic and treatment strategies. Further research with larger cohorts is necessary to validate these results and explore additional factors affecting brain functional connectivity.