Bayesian inference in FMRI
Bayesian inference has taken FMRI methods research into areas that frequentist statistics have struggled to reach. In this article we will consider some of the early forays into Bayes and what motivated its use. We shall see the impact that Bayes has had on haemodynamic modelling, spatial modelling,...
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| Format: | Journal article |
| Language: | English |
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2012
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| _version_ | 1826262083672473600 |
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| author | Woolrich, M |
| author_facet | Woolrich, M |
| author_sort | Woolrich, M |
| collection | OXFORD |
| description | Bayesian inference has taken FMRI methods research into areas that frequentist statistics have struggled to reach. In this article we will consider some of the early forays into Bayes and what motivated its use. We shall see the impact that Bayes has had on haemodynamic modelling, spatial modelling, group analysis, model selection and brain connectivity analysis; and consider how these advancements have spun-off into related areas of neuroscience and some of the challenges that remain. Bayes has brought to the table inference flexibility, incorporation of prior information, adaptive regularisation and model selection. But perhaps more important than these things, is the ability of Bayes to empower the methods researcher with a mathematically principled framework for inferring on any model. © 2011 Elsevier Inc. |
| first_indexed | 2024-03-06T19:30:45Z |
| format | Journal article |
| id | oxford-uuid:1d6243f6-41a5-4c87-91c0-6f4b24329c90 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:30:45Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oxford-uuid:1d6243f6-41a5-4c87-91c0-6f4b24329c902022-03-26T11:10:31ZBayesian inference in FMRIJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1d6243f6-41a5-4c87-91c0-6f4b24329c90EnglishSymplectic Elements at Oxford2012Woolrich, MBayesian inference has taken FMRI methods research into areas that frequentist statistics have struggled to reach. In this article we will consider some of the early forays into Bayes and what motivated its use. We shall see the impact that Bayes has had on haemodynamic modelling, spatial modelling, group analysis, model selection and brain connectivity analysis; and consider how these advancements have spun-off into related areas of neuroscience and some of the challenges that remain. Bayes has brought to the table inference flexibility, incorporation of prior information, adaptive regularisation and model selection. But perhaps more important than these things, is the ability of Bayes to empower the methods researcher with a mathematically principled framework for inferring on any model. © 2011 Elsevier Inc. |
| spellingShingle | Woolrich, M Bayesian inference in FMRI |
| title | Bayesian inference in FMRI |
| title_full | Bayesian inference in FMRI |
| title_fullStr | Bayesian inference in FMRI |
| title_full_unstemmed | Bayesian inference in FMRI |
| title_short | Bayesian inference in FMRI |
| title_sort | bayesian inference in fmri |
| work_keys_str_mv | AT woolrichm bayesianinferenceinfmri |