Abstract
.Significance: Functional near-infrared spectroscopy (fNIRS) uses surface-placed light sources and detectors to record underlying changes in the brain due to fluctuations in hemoglobin levels and oxygenation. Since these measurements are recorded from the surface of the scalp, the mapping from underlying regions-of-interest (ROIs) in the brain space to the fNIRS channel space measurements depends on the registration of the sensors, the anatomy of the head/brain, and the sensitivity of these diffuse measurements through the tissue. However, small displacements in the probe position can change the distribution of recorded brain activity across the fNIRS measurements.Aim: We propose an approach using either individual or atlas-based brain-space anatomical information to define ROI-based statistical hypotheses to test the null involvement of specific regions, which allows us to test the analogous ROI across subjects while adjusting for fNIRS probe placement and sensitivity differences due to head size variations without a localizer task.Approach: We use the optical forward model to project the underlying brain-space ROI into a tapered contrast vector, which defines the relative weighting of the fNIRS channels contributing to the ROI and allows us to test the null hypothesis of no brain activity in this region during a functional task. We demonstrate this method through simulation and compare the sensitivity-specificity of this approach to other conventional methods.Results: We examine the performance of this method in the scenario where head size and probe registration are both an accurately known parameters and where this is subject to unknown experimental errors. This method is compared with the performance of the conventional method using 364 different simulation parameter combinations.Conclusion: The proposed method is always recommended in ROI-based analysis, since it significantly improves the analysis performance without a localizer task, wherever the fNIRS probe registration is known or unknown.
Highlights
Functional near-infrared spectroscopy is a noninvasive neuroimaging technique that uses low levels of red to near-infrared light to measure changes in the optical absorption due NeurophotonicsDownloaded From: https://www.spiedigitallibrary.org/journals/Neurophotonics on 02 Nov 2021 Terms of Use: https://www.spiedigitallibrary.org/terms-of-useJul–Sep 2020 Vol 7(3)Zhai, Santosa, and Huppert: Using anatomically defined regions-of-interest. . .to hemoglobin in the brain
We examine the performance of this method in the scenario where head size and probe registration are both an accurately known parameters and where this is subject to unknown experimental errors
The proposed method is always recommended in ROI-based analysis, since it significantly improves the analysis performance without a localizer task, wherever the Functional near-infrared spectroscopy (fNIRS) probe registration is known or unknown
Summary
Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of red to near-infrared light to measure changes in the optical absorption due NeurophotonicsDownloaded From: https://www.spiedigitallibrary.org/journals/Neurophotonics on 02 Nov 2021 Terms of Use: https://www.spiedigitallibrary.org/terms-of-useJul–Sep 2020 Vol 7(3)Zhai, Santosa, and Huppert: Using anatomically defined regions-of-interest. . .to hemoglobin in the brain. Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of red to near-infrared light to measure changes in the optical absorption due Neurophotonics. Light is sent into the tissue from source positions on the scalp This light diffuses through the tissue, and a small fraction of the light is detected at a discrete set of optical detector positions placed several centimeters from the originating source position. These channel-space measurements are sensitive to changes in the optical properties of the tissue along this diffuse volume between the light source and detector. The ability to noninvasively record brain activity without participant immobilization or a specialized dedicated scanner environment (cf. magnetic resonance imaging; MRI) makes this technique well suited for studies in pediatric populations (reviewed in Refs. 1 and 5–7)
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