Carmine Gelormini, Lorena Guerrini, Federica Pescaglia, Romain Aubonnet, Halldór Jónsson, Hannes Petersen, Giorgio Di Lorenzo, Paolo Gargiulo
{"title":"利用脑电图微态评估体位控制任务中的脑网络动态。","authors":"Carmine Gelormini, Lorena Guerrini, Federica Pescaglia, Romain Aubonnet, Halldór Jónsson, Hannes Petersen, Giorgio Di Lorenzo, Paolo Gargiulo","doi":"10.1007/s10548-025-01119-w","DOIUrl":null,"url":null,"abstract":"<p><p>The ability to maintain our body's balance and stability in space is crucial for performing daily activities. Effective postural control (PC) strategies rely on integrating visual, vestibular, and proprioceptive sensory inputs. While neuroimaging has revealed key areas involved in PC-including brainstem, cerebellum, and cortical networks-the rapid neural mechanisms underlying dynamic postural tasks remain less understood. Therefore, we used EEG microstate analysis within the BioVRSea experiment to explore the temporal brain dynamics that support PC. This complex paradigm simulates maintaining an upright posture on a moving platform, integrated with virtual reality (VR), to replicate the sensation of balancing on a boat. Data were acquired from 266 healthy subjects using a 64-channel EEG system. Using a modified k-means method, five EEG microstate maps were identified to best model the paradigm. Differences in each microstate maps feature (occurrence, duration, and coverage) between experimental phases were analyzed using a linear mixed model, revealing significant differences between microstates within the experiment phases. The temporal parameters of microstate C showed significantly higher levels in all experimental phases compared to other microstate maps, whereas microstate B displayed an opposite pattern, consistently showing lower levels. This study marks the first attempt to use microstate analysis during a dynamic task, demonstrating the decisive role of microstate C and, conversely, microstate B in differentiating the PC phases. These results demonstrate the utility of microstate technique in studying temporal brain dynamics during PC, with potential applications in the early detection of neurodegenerative diseases.</p>","PeriodicalId":55329,"journal":{"name":"Brain Topography","volume":"38 4","pages":"47"},"PeriodicalIF":2.3000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12133945/pdf/","citationCount":"0","resultStr":"{\"title\":\"Assessing Brain Network Dynamics During Postural Control Task Using EEG Microstates.\",\"authors\":\"Carmine Gelormini, Lorena Guerrini, Federica Pescaglia, Romain Aubonnet, Halldór Jónsson, Hannes Petersen, Giorgio Di Lorenzo, Paolo Gargiulo\",\"doi\":\"10.1007/s10548-025-01119-w\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The ability to maintain our body's balance and stability in space is crucial for performing daily activities. Effective postural control (PC) strategies rely on integrating visual, vestibular, and proprioceptive sensory inputs. While neuroimaging has revealed key areas involved in PC-including brainstem, cerebellum, and cortical networks-the rapid neural mechanisms underlying dynamic postural tasks remain less understood. Therefore, we used EEG microstate analysis within the BioVRSea experiment to explore the temporal brain dynamics that support PC. This complex paradigm simulates maintaining an upright posture on a moving platform, integrated with virtual reality (VR), to replicate the sensation of balancing on a boat. Data were acquired from 266 healthy subjects using a 64-channel EEG system. Using a modified k-means method, five EEG microstate maps were identified to best model the paradigm. Differences in each microstate maps feature (occurrence, duration, and coverage) between experimental phases were analyzed using a linear mixed model, revealing significant differences between microstates within the experiment phases. The temporal parameters of microstate C showed significantly higher levels in all experimental phases compared to other microstate maps, whereas microstate B displayed an opposite pattern, consistently showing lower levels. This study marks the first attempt to use microstate analysis during a dynamic task, demonstrating the decisive role of microstate C and, conversely, microstate B in differentiating the PC phases. These results demonstrate the utility of microstate technique in studying temporal brain dynamics during PC, with potential applications in the early detection of neurodegenerative diseases.</p>\",\"PeriodicalId\":55329,\"journal\":{\"name\":\"Brain Topography\",\"volume\":\"38 4\",\"pages\":\"47\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12133945/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brain Topography\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s10548-025-01119-w\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain Topography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10548-025-01119-w","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Assessing Brain Network Dynamics During Postural Control Task Using EEG Microstates.
The ability to maintain our body's balance and stability in space is crucial for performing daily activities. Effective postural control (PC) strategies rely on integrating visual, vestibular, and proprioceptive sensory inputs. While neuroimaging has revealed key areas involved in PC-including brainstem, cerebellum, and cortical networks-the rapid neural mechanisms underlying dynamic postural tasks remain less understood. Therefore, we used EEG microstate analysis within the BioVRSea experiment to explore the temporal brain dynamics that support PC. This complex paradigm simulates maintaining an upright posture on a moving platform, integrated with virtual reality (VR), to replicate the sensation of balancing on a boat. Data were acquired from 266 healthy subjects using a 64-channel EEG system. Using a modified k-means method, five EEG microstate maps were identified to best model the paradigm. Differences in each microstate maps feature (occurrence, duration, and coverage) between experimental phases were analyzed using a linear mixed model, revealing significant differences between microstates within the experiment phases. The temporal parameters of microstate C showed significantly higher levels in all experimental phases compared to other microstate maps, whereas microstate B displayed an opposite pattern, consistently showing lower levels. This study marks the first attempt to use microstate analysis during a dynamic task, demonstrating the decisive role of microstate C and, conversely, microstate B in differentiating the PC phases. These results demonstrate the utility of microstate technique in studying temporal brain dynamics during PC, with potential applications in the early detection of neurodegenerative diseases.
期刊介绍:
Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.