FRANÇAIS
A showcase of ÉTS researchers’ publications and other contributions
SEARCH

Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean

Downloads

Downloads per month over past year

Cai, Zhengchen, Machado, Alexis, Chowdhury, Rasheda Arman, Spilkin, Amanda, Vincent, Thomas, Aydin, Ümit, Pellegrino, Giovanni, Lina, Jean-Marc et Grova, Christophe. 2022. « Diffuse optical reconstructions of functional near infrared spectroscopy data using maximum entropy on the mean ». Scientific Reports, vol. 12, nº 1.

[thumbnail of Lina-JM-2022-24046.pdf]
Preview
PDF
Lina-JM-2022-24046.pdf - Published Version
Use licence: Creative Commons CC BY.

Download (3MB) | Preview

Abstract

Functional near-infrared spectroscopy (fNIRS) measures the hemoglobin concentration changes associated with neuronal activity. Diffuse optical tomography (DOT) consists of reconstructing the optical density changes measured from scalp channels to the oxy-/deoxy-hemoglobin concentration changes within the cortical regions. In the present study, we adapted a nonlinear source localization method developed and validated in the context of Electro- and Magneto-Encephalography (EEG/MEG): the Maximum Entropy on the Mean (MEM), to solve the inverse problem of DOT reconstruction. We first introduced depth weighting strategy within the MEM framework for DOT reconstruction to avoid biasing the reconstruction results of DOT towards superficial regions. We also proposed a new initialization of the MEM model improving the temporal accuracy of the original MEM framework. To evaluate MEM performance and compare with widely used depth weighted Minimum Norm Estimate (MNE) inverse solution, we applied a realistic simulation scheme which contained 4000 simulations generated by 250 different seeds at different locations and 4 spatial extents ranging from 3 to 40cm2 along the cortical surface. Our results showed that overall MEM provided more accurate DOT reconstructions than MNE. Moreover, we found that MEM was remained particularly robust in low signal-to-noise ratio (SNR) conditions. The proposed method was further illustrated by comparing to functional Magnetic Resonance Imaging (fMRI) activation maps, on real data involving finger tapping tasks with two different montages. The results showed that MEM provided more accurate HbO and HbR reconstructions in spatial agreement with the main fMRI cluster, when compared to MNE.

Item Type: Peer reviewed article published in a journal
Professor:
Professor
Lina, Jean-Marc
Affiliation: Génie électrique
Date Deposited: 07 Mar 2022 19:06
Last Modified: 10 Mar 2022 18:55
URI: https://espace2.etsmtl.ca/id/eprint/24046

Actions (login required)

View Item View Item