Extraction of cognitive activity-related waveforms from functional near-infrared spectroscopy signals
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We address the problem of prototypical waveform extraction in cognitive experiments using functional near-infrared spectroscopy (fNIRS) signals. These waveform responses are evoked with visual stimuli provided in an oddball type experimental protocol. As the statistical signal-processing tool, we consider the linear signal space representation paradigm and use independent component analysis (ICA). The assumptions underlying ICA is discussed in the light of the signal measurement and generation mechanisms in the brain. The ICA-based waveform extraction is validated based both on its conformance to the parametric brain hemodynamic response (BHR) model and to the coherent averaging technique. We assess the intra-subject and inter-subject waveform and parameter variability.
KeywordsFunctional near-infrared spectroscopy Brain hemodynamic response Independent component analysis
This work has been sponsored in part by funds from the Defense Advanced Research Projects Agency (DARPA) Augmented Cognition Program and the Office of Naval Research (ONR), under agreement numbers N00014-02-1-0524 and N00014-01-1-0986, in part by Boğaziçi University Research Fund, BURF 02S102, DPT 03K120250, and in part by TUBITAK-CNR Grant No. 104E101. The authors would like to thank Drs. Scott Bunce, Banu Onaral, Kambiz Pourrezaei, Meltem Izzetoglu, Britton Chance and Shoko Nioka and Mr Kurtulus Izzetoglu and Hasan Ayaz of Drexel University for sharing their fNIRS data with us.
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