Bin He, Abbas Sohrabpour, Emery Brown, Zhongming Liu
{"title":"电生理源成像:脑动力学的无创窗口。","authors":"Bin He, Abbas Sohrabpour, Emery Brown, Zhongming Liu","doi":"10.1146/annurev-bioeng-062117-120853","DOIUrl":null,"url":null,"abstract":"<p><p>Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.</p>","PeriodicalId":50757,"journal":{"name":"Annual Review of Biomedical Engineering","volume":"20 ","pages":"171-196"},"PeriodicalIF":12.8000,"publicationDate":"2018-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/annurev-bioeng-062117-120853","citationCount":"144","resultStr":"{\"title\":\"Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.\",\"authors\":\"Bin He, Abbas Sohrabpour, Emery Brown, Zhongming Liu\",\"doi\":\"10.1146/annurev-bioeng-062117-120853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.</p>\",\"PeriodicalId\":50757,\"journal\":{\"name\":\"Annual Review of Biomedical Engineering\",\"volume\":\"20 \",\"pages\":\"171-196\"},\"PeriodicalIF\":12.8000,\"publicationDate\":\"2018-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1146/annurev-bioeng-062117-120853\",\"citationCount\":\"144\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annual Review of Biomedical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1146/annurev-bioeng-062117-120853\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2018/3/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Biomedical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1146/annurev-bioeng-062117-120853","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2018/3/1 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.
Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.
期刊介绍:
Since 1999, the Annual Review of Biomedical Engineering has been capturing major advancements in the expansive realm of biomedical engineering. Encompassing biomechanics, biomaterials, computational genomics and proteomics, tissue engineering, biomonitoring, healthcare engineering, drug delivery, bioelectrical engineering, biochemical engineering, and biomedical imaging, the journal remains a vital resource. The current volume has transitioned from gated to open access through Annual Reviews' Subscribe to Open program, with all articles published under a CC BY license.