Data-driven region-of-interest selection without inflating Type I error rate

Brooks, Joseph L., Zoumpoulaki, Alexia ORCID: https://orcid.org/0000-0002-0810-0319 and Bowman, Howard 2017. Data-driven region-of-interest selection without inflating Type I error rate. Psychophysiology 54 (1) , pp. 100-113. 10.1111/psyp.12682

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Abstract

In ERP and other large multidimensional neuroscience data sets, researchers often select regions of interest (ROIs) for analysis. The method of ROI selection can critically affect the conclusions of a study by causing the researcher to miss effects in the data or to detect spurious effects. In practice, to avoid inflating Type I error rate (i.e., false positives), ROIs are often based on a priori hypotheses or independent information. However, this can be insensitive to experiment-specific variations in effect location (e.g., latency shifts) reducing power to detect effects. Data-driven ROI selection, in contrast, is nonindependent and uses the data under analysis to determine ROI positions. Therefore, it has potential to select ROIs based on experiment-specific information and increase power for detecting effects. However, data-driven methods have been criticized because they can substantially inflate Type I error rate. Here, we demonstrate, using simulations of simple ERP experiments, that data-driven ROI selection can indeed be more powerful than a priori hypotheses or independent information. Furthermore, we show that data-driven ROI selection using the aggregate grand average from trials (AGAT), despite being based on the data at hand, can be safely used for ROI selection under many circumstances. However, when there is a noise difference between conditions, using the AGAT can inflate Type I error and should be avoided. We identify critical assumptions for use of the AGAT and provide a basis for researchers to use, and reviewers to assess, data-driven methods of ROI localization in ERP and other studies.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics Cardiff University Brain Research Imaging Centre (CUBRIC) Psychology
Subjects:	B Philosophy. Psychology. Religion > BF Psychology
Publisher:	Blackwell Publishing
ISSN:	0048-5772
Date of First Compliant Deposit:	7 February 2017
Date of Acceptance:	4 May 2016
Last Modified:	06 May 2023 01:08
URI:	https://orca.cardiff.ac.uk/id/eprint/97667

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