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Front. Neurosci., 21 January 2014 | http://dx.doi.org/10.3389/fnins.2014.00001

Misconceptions in the use of the General Linear Model applied to functional MRI: a tutorial for junior neuro-imagers

  • Brain Research Imaging Centre, Imaging Sciences, University of Edinburgh, Edinburgh, UK

This tutorial presents several misconceptions related to the use the General Linear Model (GLM) in functional Magnetic Resonance Imaging (fMRI). The goal is not to present mathematical proofs but to educate using examples and computer code (in Matlab). In particular, I address issues related to (1) model parameterization (modeling baseline or null events) and scaling of the design matrix; (2) hemodynamic modeling using basis functions, and (3) computing percentage signal change. Using a simple controlled block design and an alternating block design, I first show why “baseline” should not be modeled (model over-parameterization), and how this affects effect sizes. I also show that, depending on what is tested; over-parameterization does not necessarily impact upon statistical results. Next, using a simple periodic vs. random event related design, I show how the hemodynamic model (hemodynamic function only or using derivatives) can affects parameter estimates, as well as detail the role of orthogonalization. I then relate the above results to the computation of percentage signal change. Finally, I discuss how these issues affect group analyses and give some recommendations.

Keywords: GLM, modeling, baseline, derivatives, percentage signal change, fMRI

Citation: Pernet CR (2014) Misconceptions in the use of the General Linear Model applied to functional MRI: a tutorial for junior neuro-imagers. Front. Neurosci. 8:1. doi: 10.3389/fnins.2014.00001

Received: 03 June 2013; Accepted: 03 January 2014;
Published online: 21 January 2014.

Edited by:

Bertrand Thirion, Institut National de Recherche en Informatique et Automatique, France

Reviewed by:

Matthew Brett, University of Cambridge, UK
Arnaud Delorme, Centre de Recherche Cerveau et Cognition, France

Copyright © 2014 Pernet. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Cyril R. Pernet, Brain Research Imaging Centre, Division of Clinical Neurosciences, Western General Hospital, Crewe Road, EH4 2XU, Edinburgh, UK e-mail: cyril.pernet@ed.ac.uk