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Proceedings Paper

Data analysis and statistical tests for near-infrared functional studies of the brain
Author(s): Angelo Sassaroli; Yunjie Tong; Christian Benes; Sergio Fantini
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Paper Abstract

We show some limitations of the standard t test when used together with typical data processing methods in functional Near Infrared Spectroscopy of the brain to assess the significance of multiple correlated points. We studied the occurrence of errors type I (that is the occurrence of false positive points) when typical processing methods are applied to time series of normal random numbers and to time series of simulated baseline systemic fluctuations. Since the results of the two studies are very similar we concluded that normal random numbers can be used to assess the occurrence of error type I due to certain algorithms of data processing. In order to decrease the occurrence of false positive points we propose to use some modified stepwise Bonferroni procedures, among which we studied the performance of Dubey/Armitage-Parmar algorithm. The results of the algorithm are shown for both simulated and experimental data.

Paper Details

Date Published: 12 February 2008
PDF: 6 pages
Proc. SPIE 6850, Multimodal Biomedical Imaging III, 685008 (12 February 2008); doi: 10.1117/12.761707
Show Author Affiliations
Angelo Sassaroli, Tufts Univ. (United States)
Yunjie Tong, Tufts Univ. (United States)
Christian Benes, Brooklyn College (United States)
Sergio Fantini, Tufts Univ. (United States)

Published in SPIE Proceedings Vol. 6850:
Multimodal Biomedical Imaging III
Fred S. Azar; Xavier Intes, Editor(s)

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