Cargando…

Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach

Functional magnetic resonance imaging (fMRI) is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a general linear model (GLM) approach to separate stimulus induced signals from noise. Crucially, this approach relies on a...

Descripción completa

Detalles Bibliográficos
Autor principal: Monti, Martin M.
Formato: Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3062970/
https://www.ncbi.nlm.nih.gov/pubmed/21442013
http://dx.doi.org/10.3389/fnhum.2011.00028
_version_ 1782200750470856704
author Monti, Martin M.
author_facet Monti, Martin M.
author_sort Monti, Martin M.
collection PubMed
description Functional magnetic resonance imaging (fMRI) is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a general linear model (GLM) approach to separate stimulus induced signals from noise. Crucially, this approach relies on a number of assumptions about the data which, for inferences to be valid, must be met. The current paper reviews the GLM approach to analysis of fMRI time-series, focusing in particular on the degree to which such data abides by the assumptions of the GLM framework, and on the methods that have been developed to correct for any violation of those assumptions. Rather than biasing estimates of effect size, the major consequence of non-conformity to the assumptions is to introduce bias into estimates of the variance, thus affecting test statistics, power, and false positive rates. Furthermore, this bias can have pervasive effects on both individual subject and group-level statistics, potentially yielding qualitatively different results across replications, especially after the thresholding procedures commonly used for inference-making.
format Text
id pubmed-3062970
institution National Center for Biotechnology Information
language English
publishDate 2011
publisher Frontiers Research Foundation
record_format MEDLINE/PubMed
spelling pubmed-30629702011-03-25 Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach Monti, Martin M. Front Hum Neurosci Neuroscience Functional magnetic resonance imaging (fMRI) is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a general linear model (GLM) approach to separate stimulus induced signals from noise. Crucially, this approach relies on a number of assumptions about the data which, for inferences to be valid, must be met. The current paper reviews the GLM approach to analysis of fMRI time-series, focusing in particular on the degree to which such data abides by the assumptions of the GLM framework, and on the methods that have been developed to correct for any violation of those assumptions. Rather than biasing estimates of effect size, the major consequence of non-conformity to the assumptions is to introduce bias into estimates of the variance, thus affecting test statistics, power, and false positive rates. Furthermore, this bias can have pervasive effects on both individual subject and group-level statistics, potentially yielding qualitatively different results across replications, especially after the thresholding procedures commonly used for inference-making. Frontiers Research Foundation 2011-03-18 /pmc/articles/PMC3062970/ /pubmed/21442013 http://dx.doi.org/10.3389/fnhum.2011.00028 Text en Copyright © 2011 Monti. http://www.frontiersin.org/licenseagreement This is an open-access article subject to an exclusive license agreement between the authors and Frontiers Media SA, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
spellingShingle Neuroscience
Monti, Martin M.
Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
title Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
title_full Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
title_fullStr Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
title_full_unstemmed Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
title_short Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach
title_sort statistical analysis of fmri time-series: a critical review of the glm approach
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3062970/
https://www.ncbi.nlm.nih.gov/pubmed/21442013
http://dx.doi.org/10.3389/fnhum.2011.00028
work_keys_str_mv AT montimartinm statisticalanalysisoffmritimeseriesacriticalreviewoftheglmapproach