{"title":"统计参数映射:认知神经科学的催化剂。","authors":"Klaas Enno Stephan","doi":"10.1093/cercor/bhaf239","DOIUrl":null,"url":null,"abstract":"<p><p>Statistical Parametric Mapping (SPM) is a statistical framework and open source software package for neuroimaging data analysis. Originally created by Karl Friston in the early 1990s, it has been used by a vast number of scientific studies over the last three decades. SPM has not only revolutionized the analysis of neuroimaging data but also catalyzed the development of cognitive neuroscience. This short commentary reflects on key principles that have made SPM so enormously influential and successful: (i) the introduction of a principled general framework for statistical inference that applied to all neuroimaging modalities, (ii) the emphasis on open source code, transparency, and collaboration, and (iii) constant evolution over three decades, from a frequentist mass-univariate framework to generative models of neuroimaging, electrophysiological, magnetoencephalographic, and behavioral data.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"35 8","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical parametric mapping: a catalyst for cognitive neuroscience.\",\"authors\":\"Klaas Enno Stephan\",\"doi\":\"10.1093/cercor/bhaf239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Statistical Parametric Mapping (SPM) is a statistical framework and open source software package for neuroimaging data analysis. Originally created by Karl Friston in the early 1990s, it has been used by a vast number of scientific studies over the last three decades. SPM has not only revolutionized the analysis of neuroimaging data but also catalyzed the development of cognitive neuroscience. This short commentary reflects on key principles that have made SPM so enormously influential and successful: (i) the introduction of a principled general framework for statistical inference that applied to all neuroimaging modalities, (ii) the emphasis on open source code, transparency, and collaboration, and (iii) constant evolution over three decades, from a frequentist mass-univariate framework to generative models of neuroimaging, electrophysiological, magnetoencephalographic, and behavioral data.</p>\",\"PeriodicalId\":9715,\"journal\":{\"name\":\"Cerebral cortex\",\"volume\":\"35 8\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cerebral cortex\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/cercor/bhaf239\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cerebral cortex","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/cercor/bhaf239","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Statistical parametric mapping: a catalyst for cognitive neuroscience.
Statistical Parametric Mapping (SPM) is a statistical framework and open source software package for neuroimaging data analysis. Originally created by Karl Friston in the early 1990s, it has been used by a vast number of scientific studies over the last three decades. SPM has not only revolutionized the analysis of neuroimaging data but also catalyzed the development of cognitive neuroscience. This short commentary reflects on key principles that have made SPM so enormously influential and successful: (i) the introduction of a principled general framework for statistical inference that applied to all neuroimaging modalities, (ii) the emphasis on open source code, transparency, and collaboration, and (iii) constant evolution over three decades, from a frequentist mass-univariate framework to generative models of neuroimaging, electrophysiological, magnetoencephalographic, and behavioral data.
期刊介绍:
Cerebral Cortex publishes papers on the development, organization, plasticity, and function of the cerebral cortex, including the hippocampus. Studies with clear relevance to the cerebral cortex, such as the thalamocortical relationship or cortico-subcortical interactions, are also included.
The journal is multidisciplinary and covers the large variety of modern neurobiological and neuropsychological techniques, including anatomy, biochemistry, molecular neurobiology, electrophysiology, behavior, artificial intelligence, and theoretical modeling. In addition to research articles, special features such as brief reviews, book reviews, and commentaries are included.