SEMINAR UNF SERIES
|Title:||Cluster failure revisited: Impact of first level design and physiological noise on cluster false positive rates.|
|Where:||CRIUGM Room E1910 (http://www.criugm.qc.ca/en/contact.html)|
|When:||Monday August 6th, 13h-14h|
*The seminar will be presented in English
Dr Anders Eklund is a research fellow at Linköping University (Sweden) in the Department of Biomedical Engineering (IMT). His main research interests are within analysis of functional magnetic resonance imaging (fMRI) data, mainly regarding development and testing of statistical algorithms. Other interests include high performance computing using graphics cards, image registration and machine learning.
Methodological research rarely generates a broad interest, yet our work on the validity of cluster inference methods for functional magnetic resonance imaging (fMRI) created intense discussion on both the minutia of our approach and its implications for the discipline. In the present work, we take on various critiques of our work and further explore the limitations of our original work. We address issues about the particular event-related designs we used, considering multiple event types and randomisation of events between subjects. We consider the lack of validity found with one-sample permutation (sign flipping) tests, investigating a number of approaches to improve the false positive control of this widely used procedure. We found that the combination of a two-sided test and cleaning the data using ICA FIX resulted in nominal false positive rates for all datasets, meaning that data cleaning is not only important for resting state fMRI, but also for task fMRI.