Exploring the feasibility of tensor decomposition for analysis of fNIRS signals: a comparative study with grand averaging method.

ABSTRACT: The analysis of functional near-infrared spectroscopy (fNIRS) signals has not kept pace with the increased use of fNIRS in the behavioral and brain sciences. The popular grand averaging method collapses the oxygenated hemoglobin data within a predefined time of interest window and across multiple channels within a region of interest, potentially leading to a loss of important temporal and spatial information. On the other hand, the tensor decomposition method can reveal patterns in the data without making prior assumptions of the hemodynamic response and without losing temporal and spatial information. The aim of the current study was to examine whether the tensor decomposition method could identify significant effects and novel patterns compared to the commonly used grand averaging method

SUBMITTER: Chan JY 

PROVIDER: S-EPMC10448703 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature