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Neurophotonics

Short separation regression improves statistical significance and better localizes the hemodynamic response obtained by near-infrared spectroscopy for tasks with differing autonomic responses
Author(s): Meryem A. Yücel; Juliette Selb; Christopher M. Aasted; Mike P. Petkov; Lino Becerra; David Borsook; David A. Boas
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Paper Abstract

Autonomic nervous system response is known to be highly task-dependent. The sensitivity of near-infrared spectroscopy (NIRS) measurements to superficial layers, particularly to the scalp, makes it highly susceptible to systemic physiological changes. Thus, one critical step in NIRS data processing is to remove the contribution of superficial layers to the NIRS signal and to obtain the actual brain response. This can be achieved using short separation channels that are sensitive only to the hemodynamics in the scalp. We investigated the contribution of hemodynamic fluctuations due to autonomous nervous system activation during various tasks. Our results provide clear demonstrations of the critical role of using short separation channels in NIRS measurements to disentangle differing autonomic responses from the brain activation signal of interest.

Paper Details

Date Published: 11 September 2015
PDF: 10 pages
2(3) 035005 doi: 10.1117/1.NPh.2.3.035005
Published in: Neurophotonics Volume 2, Issue 3
Show Author Affiliations
Meryem A. Yücel, Athinoula A. Martinos Ctr. for Biomedical Imaging (United States)
Juliette Selb, Athinoula A. Martinos Ctr. for Biomedical Imaging (United States)
Christopher M. Aasted, Boston Children’s Hospital (United States)
Mike P. Petkov, Boston Children’s Hospital (United States)
Lino Becerra, Athinoula A. Martinos Ctr. for Biomedical Imaging (United States)
Boston Children’s Hospital (United States)
Harvard Medical School (United States)
David Borsook, Athinoula A. Martinos Ctr. for Biomedical Imaging (United States)
Boston Children’s Hospital (United States)
Harvard Medical School (United States)
David A. Boas, Athinoula A. Martinos Ctr. for Biomedical Imaging (United States)


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