ICA analysis of optical topography signals for elucidating physiological source

Optical topography (OT) signals are a mixture of neuronal activation-induced hemodynamic changes and systemic blood-circulation changes. For a distinct discussion on an obtained result, it is important to treat these phenomena separately. In this study, we used independent component analysis (ICA) to separate signals related to cerebral hemodynamic changes and systemic blood-circulation changes. The analysis procedure had three stages: first, OT signals were separated into independent components (IO); second, task-related ICs (TR-ICs) were selected from the separated ICs; and third, the TR-ICs were categorized by k-means clustering into TR activation-related ICs (TR-AICs) and TR noise ICs (TR-NICs). We applied this analysis procedure to the OT signals obtained from experiments using one-handed finger tapping tasks. In the averaged waveform of the TR-AICs, a small overshoot can. be seen for a few seconds after the onset of each task and a few seconds after it ends, and the averaged waveforms of the TR-NICs have an N-shaped pattern.