Abstract

Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive brain imaging technique which measures brain activity via local changes in blood hemoglobin concentration. Since brain activity decreases as a function of age, it is expected that aging adults will demonstrate less hemodynamic changes and therefore, indicate less cortical activation compared to younger adults. To test the stated relationships, this study involves using the Near Infra-Red Optimal Tomography (NIROT) workflow with Maximum Entropy on the Mean (MEM), using personalized fNIRS and local 3D reconstruction to assess the hemodynamic response elicited during simultaneous walking and arithmetic tasks in healthy young and older adults. Personalized fNIRS consisted of following the Optimal Montage algorithm, which maximizes the positions of fNIRS sensors to increase sensitivity to two targeted brain regions: the Inferior Frontal Gyrus (IFG) and Middle Frontal Gyrus (MFG) which are both involved in performing mental arithmetic and shown to demonstrate compensatory behaviors in single task (mental arithmetic only) when compared to dual task (walking while performing mental arithmetic).
Single and dual tasks were considered for five younger adults and two older adults. Subject-specific optimal montages were calculated to ensure maximum light sensitivity to the target ROI and sufficient spatial overlap between sensors, allowing local 3D reconstruction of [HbO] and [HbR] response along the underlying cortical surface. Single task consisted of a block design arithmetic task (Serial-Sevens: sequential subtraction. For dual task, the same arithmetic task was performed, while participants were walking on a treadmill. NIRSTORM software package was used for channel space analysis of fNIRS signal, motion correction, modified Beer Lambert Law and block averaging. Reconstruction in 3D using Maximum Entropy on the Mean (MEM) was calculated using the same number of trials for each subject.
In addition to answering questions encompassing brain activity as a function of age and balancing a cognitive task during gait, the study provided data for investigating trends around motion artifacts and testing the effectiveness of an accelerometer during simultaneous gait and fNIRS acquisitions. Due to restrictions during the Covid-19 pandemic, this study serves as a proof of concept and methods in improving the quality of data.