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Analysis of independent components obtained from functional near infrared data

We analyze statistically independent temporal components in the broadband spectrum of near-infrared data acquired on the human head during breath holding. Breath holding is used to cause strong cerebral hemodynamic changes. The signals from 698 wavelengths of 25-mm long channel and 1289 wavelengths from the 10-mm channel were analyzed using an independent component analysis algorithm. We show that in spite of a very large number of channels only two components with their characteristic optical spectra remain stable across multi-subject analysis. We demonstrate a comparison of fNIRS independent components with simultaneously acquired functional MRI data.