{"title":"基于脑电图的大脑异常功能连接分析:回顾性研究","authors":"Nastaran Khaleghi , Shaghayegh Hashemi , Mohammad Peivandi , Sevda Zafarmandi Ardabili , Mohammadreza Behjati , Sobhan Sheykhivand , Sebelan Danishvar","doi":"10.1016/j.imu.2024.101476","DOIUrl":null,"url":null,"abstract":"<div><p>Several imaging modalities and many signal recording techniques have been used to study the brain activities. Significant advancements in medical device technologies like electroencephalographs have provided conditions for recording neural information with high temporal resolution. These recordings can be used to calculate the connections between different brain areas. It has been proved that brain abnormalities affect the brain activity in different brain regions and the connectivity patterns between them would change as the result. This paper studies the electroencephalogram (EEG) functional connectivity methods and investigates the impacts of brain abnormalities on the brain functional connectivities. The effects of different brain abnormalities including stroke, depression, emotional disorders, epilepsy, attention deficit hyperactivity disorder (ADHD), autism, and Alzheimer's disease on functional connectivity of the EEG recordings have been explored in this study. The EEG-based metrics and network properties of different brain abnormalities have been discussed to have a comparison of the connectivities affected by each abnormality. Also, the effects of therapy and medical intake on the EEG functional connectivity network of each abnormality have been reviewed.</p></div>","PeriodicalId":13953,"journal":{"name":"Informatics in Medicine Unlocked","volume":"47 ","pages":"Article 101476"},"PeriodicalIF":0.0000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352914824000327/pdfft?md5=f4cca409c15776d628c46f1cedf6de45&pid=1-s2.0-S2352914824000327-main.pdf","citationCount":"0","resultStr":"{\"title\":\"EEG-based functional connectivity analysis of brain abnormalities: A review study\",\"authors\":\"Nastaran Khaleghi , Shaghayegh Hashemi , Mohammad Peivandi , Sevda Zafarmandi Ardabili , Mohammadreza Behjati , Sobhan Sheykhivand , Sebelan Danishvar\",\"doi\":\"10.1016/j.imu.2024.101476\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Several imaging modalities and many signal recording techniques have been used to study the brain activities. Significant advancements in medical device technologies like electroencephalographs have provided conditions for recording neural information with high temporal resolution. These recordings can be used to calculate the connections between different brain areas. It has been proved that brain abnormalities affect the brain activity in different brain regions and the connectivity patterns between them would change as the result. This paper studies the electroencephalogram (EEG) functional connectivity methods and investigates the impacts of brain abnormalities on the brain functional connectivities. The effects of different brain abnormalities including stroke, depression, emotional disorders, epilepsy, attention deficit hyperactivity disorder (ADHD), autism, and Alzheimer's disease on functional connectivity of the EEG recordings have been explored in this study. The EEG-based metrics and network properties of different brain abnormalities have been discussed to have a comparison of the connectivities affected by each abnormality. Also, the effects of therapy and medical intake on the EEG functional connectivity network of each abnormality have been reviewed.</p></div>\",\"PeriodicalId\":13953,\"journal\":{\"name\":\"Informatics in Medicine Unlocked\",\"volume\":\"47 \",\"pages\":\"Article 101476\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352914824000327/pdfft?md5=f4cca409c15776d628c46f1cedf6de45&pid=1-s2.0-S2352914824000327-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Informatics in Medicine Unlocked\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352914824000327\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatics in Medicine Unlocked","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352914824000327","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
EEG-based functional connectivity analysis of brain abnormalities: A review study
Several imaging modalities and many signal recording techniques have been used to study the brain activities. Significant advancements in medical device technologies like electroencephalographs have provided conditions for recording neural information with high temporal resolution. These recordings can be used to calculate the connections between different brain areas. It has been proved that brain abnormalities affect the brain activity in different brain regions and the connectivity patterns between them would change as the result. This paper studies the electroencephalogram (EEG) functional connectivity methods and investigates the impacts of brain abnormalities on the brain functional connectivities. The effects of different brain abnormalities including stroke, depression, emotional disorders, epilepsy, attention deficit hyperactivity disorder (ADHD), autism, and Alzheimer's disease on functional connectivity of the EEG recordings have been explored in this study. The EEG-based metrics and network properties of different brain abnormalities have been discussed to have a comparison of the connectivities affected by each abnormality. Also, the effects of therapy and medical intake on the EEG functional connectivity network of each abnormality have been reviewed.
期刊介绍:
Informatics in Medicine Unlocked (IMU) is an international gold open access journal covering a broad spectrum of topics within medical informatics, including (but not limited to) papers focusing on imaging, pathology, teledermatology, public health, ophthalmological, nursing and translational medicine informatics. The full papers that are published in the journal are accessible to all who visit the website.