Veronica M Zarr, Jyun-You Liou, Edward M Merricks, Tyler S Davis, Kyle Thomson, Bradley Greger, Paul A House, Ronald G Emerson, Robert R Goodman, Guy M McKhann, Sameer A Sheth, Catherine A Schevon, John D Rolston, Elliot H Smith
{"title":"从高时空分辨率人体电生理记录中检测和分析非振荡行波的方案。","authors":"Veronica M Zarr, Jyun-You Liou, Edward M Merricks, Tyler S Davis, Kyle Thomson, Bradley Greger, Paul A House, Ronald G Emerson, Robert R Goodman, Guy M McKhann, Sameer A Sheth, Catherine A Schevon, John D Rolston, Elliot H Smith","doi":"10.1016/j.xpro.2025.103659","DOIUrl":null,"url":null,"abstract":"<p><p>Innovations in electrophysiological recordings and computational analytic techniques enable high-resolution analysis of neural traveling waves. Here, we present a protocol for the detection and analysis of traveling waves from multi-day microelectrode array human electrophysiological recordings through a multi-linear regression statistical approach using point estimator data. We describe steps for traveling wave detection, feature characterization, and propagation pattern analysis. This protocol may improve our understanding of the coordination of neurons during non-oscillatory neural dynamics. For complete details on the use and execution of this protocol, please refer to Smith et al.<sup>1</sup>.</p>","PeriodicalId":34214,"journal":{"name":"STAR Protocols","volume":"6 1","pages":"103659"},"PeriodicalIF":1.3000,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Protocol for detecting and analyzing non-oscillatory traveling waves from high-spatiotemporal-resolution human electrophysiological recordings.\",\"authors\":\"Veronica M Zarr, Jyun-You Liou, Edward M Merricks, Tyler S Davis, Kyle Thomson, Bradley Greger, Paul A House, Ronald G Emerson, Robert R Goodman, Guy M McKhann, Sameer A Sheth, Catherine A Schevon, John D Rolston, Elliot H Smith\",\"doi\":\"10.1016/j.xpro.2025.103659\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Innovations in electrophysiological recordings and computational analytic techniques enable high-resolution analysis of neural traveling waves. Here, we present a protocol for the detection and analysis of traveling waves from multi-day microelectrode array human electrophysiological recordings through a multi-linear regression statistical approach using point estimator data. We describe steps for traveling wave detection, feature characterization, and propagation pattern analysis. This protocol may improve our understanding of the coordination of neurons during non-oscillatory neural dynamics. For complete details on the use and execution of this protocol, please refer to Smith et al.<sup>1</sup>.</p>\",\"PeriodicalId\":34214,\"journal\":{\"name\":\"STAR Protocols\",\"volume\":\"6 1\",\"pages\":\"103659\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-02-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"STAR Protocols\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.xpro.2025.103659\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"STAR Protocols","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.xpro.2025.103659","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
Protocol for detecting and analyzing non-oscillatory traveling waves from high-spatiotemporal-resolution human electrophysiological recordings.
Innovations in electrophysiological recordings and computational analytic techniques enable high-resolution analysis of neural traveling waves. Here, we present a protocol for the detection and analysis of traveling waves from multi-day microelectrode array human electrophysiological recordings through a multi-linear regression statistical approach using point estimator data. We describe steps for traveling wave detection, feature characterization, and propagation pattern analysis. This protocol may improve our understanding of the coordination of neurons during non-oscillatory neural dynamics. For complete details on the use and execution of this protocol, please refer to Smith et al.1.