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22 October 2013 Spatiotemporal and time-frequency analysis of functional near infrared spectroscopy brain signals using independent component analysis
Zhen Yuan
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Journal of Biomedical Optics, Vol. 18, Issue 10, 106011 (October 2013). https://doi.org/10.1117/1.JBO.18.10.106011
Abstract
Functional near infrared spectroscopy (fNIRS) is a noninvasive method to capture brain activities according to the measurements of changes in both oxyhemoglobin and deoxyhemoglobin concentrations. However, fNIRS recordings are the hemodynamic signals that come from the latent neural sources that are spatially and temporally mixed across the brain. The purpose of this work is to extract the temporal and frequency characteristics as well as the spatial activation patterns in the brains using independent component analysis (ICA). In this study, the filtered fNIRS recordings were processed and the time-frequency and spatiotemporal domain independent components (ICs) were identified by ICA. We found that multiple task-related components can be separated by ICA in time-frequency domain, and distinct spatial patterns of brain activity can be derived from ICs that are well correlated with the specific neural events, such as finger tapping tasks.
© 2013 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2013/$25.00 © 2013 SPIE
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Zhen Yuan "Spatiotemporal and time-frequency analysis of functional near infrared spectroscopy brain signals using independent component analysis," Journal of Biomedical Optics 18(10), 106011 (22 October 2013). https://doi.org/10.1117/1.JBO.18.10.106011
Published: 22 October 2013
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Cited by 31 scholarly publications.
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KEYWORDS
Independent component analysis
Brain
Time-frequency analysis
Functional near infrared spectroscopy
Signal processing
Chromophores
Principal component analysis
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