Further improvement in reducing superficial contamination in NIRS using double short separation measurements

Abstract

Near-Infrared Spectroscopy (NIRS) allows the recovery of the evoked hemodynamic response to brain activation. In adult human populations, the NIRS signal is strongly contaminated by systemic interference occurring in the superficial layers of the head. An approach to overcome this difficulty is to use additional NIRS measurements with short optode separations to measure the systemic hemodynamic fluctuations occurring in the superficial layers. These measurements can then be used as regressors in the post-experiment analysis to remove the systemic contamination and isolate the brain signal. In our previous work, we showed that the systemic interference measured in NIRS is heterogeneous across the surface of the scalp. As a consequence, the short separation measurement used in the regression procedure must be located close to the standard NIRS channel from which the evoked hemodynamic response of the brain is to be recovered. Here, we demonstrate that using two short separation measurements, one at the source optode and one at the detector optode, further increases the performance of the short separation regression method compared to using a single short separation measurement. While a single short separation channel produces an average reduction in noise of 33% for HbO, using a short separation channel at both source and detector reduces noise by 59% compared to the standard method using a general linear model (GLM) without short separation. For HbR, noise reduction of 3% is achieved using a single short separation and this number goes to 47% when two short separations are used. Our work emphasizes the importance of integrating short separation measurements both at the source and at the detector optode of the standard channels from which the hemodynamic response is to be recovered. While the implementation of short separation sources presents some difficulties experimentally, the improvement in noise reduction is significant enough to justify the practical challenges.

Keywords: Kalman filtering; Near-Infrared Spectroscopy; Short optode separations; State-space analysis; Systemic interference.

Figure 1

NIRS probe. (A) Geometry (B) Sensitivity In order to avoid detector saturation, 200 μm-core fibers were used for the SS detectors (shown in red) and a piece of optical filter (Kodak WRATTEN ND 2.00) was glued at the tips of standard NIRS fibers (shown in green) for the additional sources of the SS measurements.

Figure 2

Overview of the algorithm for data analysis. Both the SS and LS measurements were bandpass filtered at 0.01-1.25 Hz and then used simultaneoulsy as regressors in the Kalman filter. A set of temporal basis functions was used to lower the dimensionality of the problem. The output of the Kalman filter was further low pass filtered at 0.5 Hz to remove any cardiac fluctuations potentially present in the time course and the final estimate of the hemodynamic response was obtained by applying a standard General Linear Model (GLM) procedure.

Figure 3

Construction of synthetic data. Thirty individual evoked responses were added over all 60 LS baseline measurements (5 subjects × 3 runs × 4 LS channels) at random onset times with an inter-stimulus interval taken randomly from a uniform distribution (12-30 sec). We also added an evoked systemic artifact to the HbO signals (LS and SS) that was phase-locked with the stimulus onset. The green box emphasizes a portion of the baseline signal where the Source SS signal resembles the LS signal while the yellow box emphasizes a portion where the Detector SS signal resembles the LS signal.

Figure 4

Averaged recovered HRF across all simulations. The width of the traces represent uncertainty given by one standard deviation taken across all simulations (5 subjects, 3 runs, 4 channels, 30 trials, 30 noise instances). The true simulated HRF is shown with dotted lines in each case.

Figure 5

Quantitative analysis of the 1800 simulations. Bars represent the mean taken across all simulated HRFs and error bars represent the standard error on the mean. Statistical significance at the p<0.05 level (two-tailed paired t-test) is illustrated by black lines over the bars.

Figure 6

HRFs recovered during the experimental finger tapping for a representative subject for a single run. The HRFs for each of the 18 individual trials are shown in red for HbO and blue for HbR. The mean HRF taken across the 18 trials is shown by a black dotted line.

Figure 7

Quantitative analysis of the experimental finger tapping. Bars represent the mean taken across all runs and error bars represent the standard error on the mean. Statistical significance at the p<0.05 level (two-tailed paired t-test) is illustrated by black lines over the bars.