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Poster C106

Factors affecting signal quality of functional near-infrared spectroscopy measurements of neural activity

Poster Session C - Sunday, April 14, 2024, 5:00 – 7:00 pm EDT, Sheraton Hall ABC

Brian Kent1 (, Zahra Bassiri1, Maggie Logan1, Adrienne Hildenbrand1, Caleb Simon1, Taye Allred1, Hannah Apostolou1, Dario Martelli2, Ian McDonough3; 1The University of Alabama, 2Medstar, 3Binghamton University

Functional Near-Infrared Spectroscopy (fNIRS) has emerged as a useful technique in the investigation of the neural mechanisms of cognitive processes. fNIRS is substantially more cost effective and allows for a greater level of mobility during measurement when compared to other commonly utilized neural activity recording techniques, such as functional magnetic resonance imaging. While these attributes of fNIRS enable novel study methodologies, the use of near-infrared light causes fNIRS measurements to suffer from lower spatial resolution and shallower penetration depth into brain tissue. Therefore, it is pertinent that nuisance factors affecting the quality of fNIRS signal be quantified to allow for more effective study designs or implementation of new technology to solve these challenges. This study measured the signal quality of fNIRS measurements in frontal and parietal regions in young adults (N = 76) during a memory task. Overall, signal quality was better in the frontal than parietal cortex. Among the factors assessed, signal quality was significantly higher in non-Hispanic White adults than ethnoracial minorities (African American and Hispanic) in both frontal and parietal. Darker hair was associated with poorer signal quality in the parietal but not in the frontal cortex. Greater hair density was not related to signal quality. Hair color mediated the effects of ethnoracial group on signal quality suggesting that hair rather than skin pigment impacts signal quality. Spending more time making sure hair is completely removed from the optodes might reduce these signal quality impairments.

Topic Area: METHODS: Neuroimaging


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April 13–16  |  2024