Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering

Xian Zhang; Jack Adam Noah; Joyce Hirsch

doi:10.1117/1.NPh.3.1.015004

5 February 2016 Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering

Xian Zhang, Jack Adam Noah, Joyce Hirsch

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Neurophotonics, Vol. 3, Issue 1, 015004 (February 2016). https://doi.org/10.1117/1.NPh.3.1.015004

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.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Xian Zhang, Jack Adam Noah, and Joyce Hirsch "Separation of the global and local components in functional near-infrared spectroscopy signals using principal component spatial filtering," Neurophotonics 3(1), 015004 (5 February 2016). https://doi.org/10.1117/1.NPh.3.1.015004

Published: 5 February 2016

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