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Neurophotonics • Open Access

Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering
Author(s): Xian Zhang; Jack Adam Noah; Joyce Hirsch

Paper Abstract

Global systemic effects not specific to a task can be prominent in functional near-infrared spectroscopy (fNIRS) signals and the separation of task-specific fNIRS signals and global nonspecific effects is challenging due to waveform correlations. We describe a principal component spatial filter algorithm for separation of the global and local effects. The effectiveness of the approach is demonstrated using fNIRS signals acquired during a right finger-thumb tapping task where the response patterns are well established. Both the temporal waveforms and the spatial pattern consistencies between oxyhemoglobin and deoxyhemoglobin signals are significantly improved, consistent with the basic physiological basis of fNIRS signals and the expected pattern of activity associated with the task.

Paper Details

Date Published: 5 February 2016
PDF: 8 pages
3(1) 015004 doi: 10.1117/1.NPh.3.1.015004
Published in: Neurophotonics Volume 3, Issue 1
Show Author Affiliations
Xian Zhang, Yale School of Medicine (United States)
Jack Adam Noah, Yale School of Medicine (United States)
Joyce Hirsch, Yale School of Medicine (United States)
(United States)
(United States)


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