{"title":"大数据和开放科学时代的功能神经影像学:现代概述","authors":"N. Lazar","doi":"10.1002/wics.1609","DOIUrl":null,"url":null,"abstract":"In the past 30 years, the statistical analysis of functional neuroimaging data has made much progress, and spurred many new research directions. At the same time, problems with reproducibility and replicability have plagued the field, owing in part to small sample sizes, a plethora of choices at the data preprocessing stage, and overall lack of transparency in reporting. The latter two in particular pose barriers to statisticians who want to become involved in the area. Recent efforts by some in the neuroimaging community to address these problems represent a turning point. This article highlights the current landscape and provides an introduction to some of the relevant resources in “open neuroimaging.”","PeriodicalId":47779,"journal":{"name":"Wiley Interdisciplinary Reviews-Computational Statistics","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Functional neuroimaging in the era of Big Data and Open Science: A modern overview\",\"authors\":\"N. Lazar\",\"doi\":\"10.1002/wics.1609\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the past 30 years, the statistical analysis of functional neuroimaging data has made much progress, and spurred many new research directions. At the same time, problems with reproducibility and replicability have plagued the field, owing in part to small sample sizes, a plethora of choices at the data preprocessing stage, and overall lack of transparency in reporting. The latter two in particular pose barriers to statisticians who want to become involved in the area. Recent efforts by some in the neuroimaging community to address these problems represent a turning point. This article highlights the current landscape and provides an introduction to some of the relevant resources in “open neuroimaging.”\",\"PeriodicalId\":47779,\"journal\":{\"name\":\"Wiley Interdisciplinary Reviews-Computational Statistics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2023-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wiley Interdisciplinary Reviews-Computational Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1002/wics.1609\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews-Computational Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/wics.1609","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Functional neuroimaging in the era of Big Data and Open Science: A modern overview
In the past 30 years, the statistical analysis of functional neuroimaging data has made much progress, and spurred many new research directions. At the same time, problems with reproducibility and replicability have plagued the field, owing in part to small sample sizes, a plethora of choices at the data preprocessing stage, and overall lack of transparency in reporting. The latter two in particular pose barriers to statisticians who want to become involved in the area. Recent efforts by some in the neuroimaging community to address these problems represent a turning point. This article highlights the current landscape and provides an introduction to some of the relevant resources in “open neuroimaging.”