Revolutionizing Brain Signal Analysis: Innovative Study Uncovers Hidden Neural Patterns with Tensor Decomposition Method

Recently, researchers from the Center for SMART Health, including Teresa Wilcox, Ph.D. (an affiliate of the center), Behnaz Ghoraani, Ph.D. (co-director of the center), and Murtadha Hssayeni, Ph.D. (former Ph.D. student of Dr. Ghoraani, graduated in Summer 2022), collaborated on a study with Jasmine Chan, M.A., a current Ph.D. Candidate in the Department of Psychology at the FAU Charles E. Schmidt College of Science. The study is titled "Exploring the Feasibility of Tensor Decomposition for Analysis of fNIRS Signals: A Comparative Study with Grand Averaging Method."

Jasmine's research aims to analyze brain recordings without compressing information, a novel approach in the field. The study focuses on functional near-infrared spectroscopy (fNIRS), a relatively new neuroimaging technique, to examine differences in brain activity over time. Unlike more popular methods, the team’s proposed analysis method does not reduce participant information into a single value, allowing for a more effective brain signal analysis.

The research utilized tensor decomposition on brain measurements from multiple participants and compared the results with the grand averaging method. The proposed method not only supported brain patterns identified with the grand averaging method but also revealed additional patterns that the latter missed due to information collapsing.

This research holds critical implications for identifying neurodivergent individuals and will be extended to adult recordings in future studies, providing more robust data. The paper's co-authors include Murtadha Hssayeni, Ph.D., a research scientist for the University of Technology in Iraq and FAU's College of Engineering and Computer Science; Teresa Wilcox, Ph.D., a professor in FAU's Department of Psychology and an affiliate of the Center for SMART Health; and Behnaz Ghoraani, Ph.D., an associate professor in FAU's Department of Electrical Engineering and Computer Science, co-director of the Center for SMART Health, and faculty fellow for the Institute for Sensing and Embedded Network Systems Engineering (I-SENSE).

Chan, J. Y. T., Hssayeni, M. D., Wilcox, T., & Ghoraani, B. Exploring the Feasibility of Tensor Decomposition for Analysis of fNIRS Signals: A Comparative Study with Grand Averaging Method. Frontiers in Neuroscience, 17, 1180293. https://doi.org/10.3389/fnins.2023.1180293 
 
https://www.frontiersin.org/articles/10.3389/fnins.2023.1180293/abstract