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A Critique of a New Analysis Proposed for Functional Neuroimaging
Author(s) -
Frackowiak R. S. J.,
Zeki S.,
Poline J.B.,
Friston K. J.
Publication year - 1996
Publication title -
european journal of neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.346
H-Index - 206
eISSN - 1460-9568
pISSN - 0953-816X
DOI - 10.1111/j.1460-9568.1996.tb01185.x
Subject(s) - false positive paradox , neuroimaging , rendering (computer graphics) , computer science , functional neuroimaging , functional imaging , artificial intelligence , data science , interpretation (philosophy) , machine learning , psychology , cognitive science , neuroscience , programming language
Methods for analysing functional imaging data have evolved rapidly over the last ten years. Standardized techniques based on formal mathematical and statistical theory and rigorous empirical validation have been proposed to facilitate comparisons of biological results between laboratories. This paper examines an image analysis technique that appears to identify unexpectedly large numbers of activated brain areas for the data collected. It concludes that the method may not adequately control for false positives, rendering interpretation of the functional anatomy difficult.