Can time-resolved NIRS provide the sensitivity to detect brain activity during motor imagery consistently?

Abstract

Previous functional magnetic resonance imaging (fMRI) studies have shown that a subgroup of patients diagnosed as being in a vegetative state are aware and able to communicate by performing a motor imagery task in response to commands. Due to the fMRI's cost and accessibility, there is a need for exploring different imaging modalities that can be used at the bedside. A promising technique is functional near infrared spectroscopy (fNIRS) that has been successfully applied to measure brain oxygenation in humans. Due to the limited depth sensitivity of continuous-wave NIRS, time-resolved (TR) detection has been proposed as a way of enhancing the sensitivity to the brain, since late arriving photons have a higher probability of reaching the brain. The goal of this study was to assess the feasibility and sensitivity of TR fNIRS in detecting brain activity during motor imagery. Fifteen healthy subjects were recruited in this study, and the fNIRS results were validated using fMRI. The change in the statistical moments of the distribution of times of flight (number of photons, mean time of flight and variance) were calculated for each channel to determine the presence of brain activity. The results indicate up to an 86% agreement between fMRI and TR-fNIRS and the sensitivity ranging from 64 to 93% with the highest value determined for the mean time of flight. These promising results highlight the potential of TR-fNIRS as a portable brain computer interface for patients with disorder of consciousness.

Keywords: (120.3890) Medical optics instrumentation; (170.0110) Imaging systems; (170.2655) Functional monitoring and imaging; (170.6920) Time-resolved imaging.

Fig. 1

Optode holder used to collect light from bilateral SMA and PMC and a picture of a participant showing the cap and probe locations for the MI experiment.

Fig. 2

Functional activation data from one subject. (Left) The time courses of all three moments – N (red), <t> (green) and V (blue) – are shown for the same channel. The black line in each graph is the best fit of the GLM model. The grey boxes indicate the periods of MI. (Right) The fMRI activation results were overlaid on the single subject rendered image in SPM with the BOLD time course from one voxel [-20, 0, 68] shown.

Fig. 3

fMRI and fNIRS results for all 15 subjects plotted on a single subject rendered image with the dorsal view shown. The red, green and blue circles indicate significant fNIRS activation detected by N, <t> and V, respectively. ^afMRI results presented are after applying SVC. For display purposes, the results are thresholded at an uncorrected p < 0.001. ^bfNIRS results for subject 2 were only from 3 channels due to a technical issue with the 4th channel during the experiment.

Fig. 4

Median change in concentration (ΔC) of oxy-hemoglobin (red) and deoxy-hemoglobin (blue) across participants that showed activity and averaged across the task cycles. The error bars represent the standard error of the median across subjects.

Fig. 5

Group-wise fMRI results from 11 participants that showed activity at the whole-brain level. The results are plotted on a canonical single subject T1 image. For display purposes, the results are thresholded at an uncorrected p < 0.001 at the whole-brain level.