Wavelet-based estimation of the hemodynamic responses in diffuse optical imaging.

Abstract

Diffuse optical imaging uses light to provide a surrogate measure of neuronal activation through the hemodynamic responses. The relative low absorption of near-infrared light enables measurements of hemoglobin changes at depths reaching the first centimeter of the cortex. The rapid rate of acquisition and the access to both oxy and deoxy-hemoglobin leads to new challenges when trying to uncouple physiology from the signal of interest. In particular, recent work provided evidence of the presence of a 1/f noise structure in optical signals and showed that a general linear model based on wavelets can be used to decorrelate the structured noise and provide a superior estimator of response amplitude when compared with conventional techniques. In this work the wavelet techniques are extended to recover the full temporal shape of the hemodynamic responses. A comparison with other models is provided as well as a case study on finger-tapping data.