Characteristics of Parameters in a Method of Separating fNIRS Signals into Functional and Systemic Components Based on Hemodynamics

Abstract

Functional Near-Infrared Spectroscopy, available for higher time resolution than some other methods like fMRI, is widely used for non-invasive neuroimaging. fNIRS enables us to measure consumption of oxygenation occurred by functional activity as hemoglobin density change. However, observed signal is often contaminated by physiological artifact or systemic blood flow changes. Considering these problems, in this study, we have applied the hemodynamical method introduced by Yamada to the observed signal to separate into two modalities, functional and systemic part. We also modified the method to determine coefficients for functional part dynamically because of significant difference between cortex regions activated or not. The modified method has made some functional parts stable and separated global large changes as the systemic parts. Furthermore, all mutual information has been decreased as compared with prior method. The result of this consideration indicates that ideal functional coefficient may vary depending on region or task.