Extraction of cognitive activity related waveforms from functional near infrared signals

We address the problem of prototypical waveform extraction from functional near infrared spectroscopy (fNIRS) signals in cognitive experiments. Extracted waveforms represent the brain hemodynamic response (BHR) to visual stimuli provided in an oddball type experimental protocol. We use and evaluate two statistical signal processing tools, namely independent component analysis (ICA) and waveform clustering, in a comparative manner. Based on the conformance to a parametric BHR model, we determine that the ICA waveform extraction method is superior. We measure and comment on the intra-subject and inter-subject waveform and parameter variability.