Dr. Kachi Odoemene Profile

Dr. Kachi Odoemene

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Proceedings Article | 5 March 2021 Presentation + Paper

Evaluation of neural information content from the phase component of a 32-channel frequency-domain fNIRS system

Clara Scholl, Jeremiah Wathen, Michael Fitch, Griffin Milsap, Margaret Thompson, Marisel Villafañe-Delgado, Kachi Odoemene, Adam Eggebrecht, Zachary Markow, Edward Richter, Jason Trobaugh, Joseph Culver, David Blodgett, Scott Hendrickson

Proceedings Volume 11629, 116292H (2021) https://doi.org/10.1117/12.2581851

KEYWORDS: Tissues, Principal component analysis, Human subjects, Head, Avalanche photodiodes

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We present a 32-transmitter, 32-receiver dual-wavelength frequency-domain (FD) fNIRS system comprised of commercially available avalanche photodiodes, laser drivers and laser mounts. The custom frequency domain (FD) fNIRS system is used to interrogate cerebral tissue with optodes positioned at the posterior occipital region of the head. Data are collected from human subjects watching movie scenes with no sound. We applied cross-validated PCA to identify the number of dimensions retained in the neural signal recorded using FD-fNIRS for the magnitude, phase, and FD (magnitude and phase combined) components of the recorded signal. Importantly, a comparison of the cross-validation error for each signal allows us quantify the dimensionality of the linear subspace spanned by each data type. The number of principal components producing the minimum cross-validation error for the held-out test runs represents the number of orthogonal signal dimensions preserved across training and held-out test data runs. We find that the FD signal captures a higher dimensional space compared to the magnitude or phase signals in isolation. Previous theoretical and empirical work suggest that signals extracted using FD-fNIRS contain higher fidelity neural information than CW-fNIRS in isolation. The findings reported here further support this hypothesis and extend beyond the findings reported in the literature, demonstrating that a higher dimension linear subspace is covered by FD-fNIRS above and beyond the baseline signal captured using traditional CW-fNIRS, assuming other optical performance metrics such as optical dynamic range, noiseequivalent power and cross-talk are comparable. This work was funded by a research contract under Facebook’s Sponsored Academic Research Agreement.

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