title: Further improvement in reducing superficial contamination in NIRS using double short separation measurements.
abstract: Near-Infrared Spectroscopy (NIRS) allows the recovery of the evoked hemodynamic response to brain activation. In adult human populations, the NIRS signal is strongly contaminated by systemic interference occurring in the superficial layers of the head. An approach to overcome this difficulty is to use additional NIRS measurements with short optode separations to measure the systemic hemodynamic fluctuations occurring in the superficial layers. These measurements can then be used as regressors in the post-experiment analysis to remove the systemic contamination and isolate the brain signal. In our previous work, we showed that the systemic interference measured in NIRS is heterogeneous across the surface of the scalp. As a consequence, the short separation measurement used in the regression procedure must be located close to the standard NIRS channel from which the evoked hemodynamic response of the brain is to be recovered. Here, we demonstrate that using two short separation measurements, one at the source optode and one at the detector optode, further increases the performance of the short separation regression method compared to using a single short separation measurement. While a single short separation channel produces an average reduction in noise of 33% for HbO, using a short separation channel at both source and detector reduces noise by 59% compared to the standard method using a general linear model (GLM) without short separation. For HbR, noise reduction of 3% is achieved using a single short separation and this number goes to 47% when two short separations are used. Our work emphasizes the importance of integrating short separation measurements both at the source and at the detector optode of the standard channels from which the hemodynamic response is to be recovered. While the implementation of short separation sources presents some difficulties experimentally, the improvement in noise reduction is significant enough to justify the practical challenges.
authors: Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA. Electronic address: lgagnon@nmr.mgh.harvard.edu.
authors: Louis
authors: L
authors: Gagnon
authors: Meryem A
authors: MA
authors: Yücel
authors: David A
authors: DA
authors: Boas
authors: Robert J
authors: RJ
authors: Cooper
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D002560:Cerebrovascular Circulation / Q000502:physiology; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D005385:Fingers / Q000294:innervation / Q000502:physiology; D059907:Functional Neuroimaging / Q000295:instrumentation / Q000379:methods*; D006454:Hemoglobins / Q000032:analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D009068:Movement / Q000502:physiology; D010100:Oxygen / Q000097:blood; D019265:Spectroscopy, Near-Infrared / Q000295:instrumentation / Q000379:methods*
chemical_list: D006454:Hemoglobins; D010100:Oxygen
keywords: Kalman filtering; Near-Infrared Spectroscopy; Short optode separations; State-space analysis; Systemic interference
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