Systemic Noise Correction and Integration of Neurophysiological and Behavioral Measures in fNIRS for Enhanced Cognitive Load Analysis

Functional near-infrared spectroscopy (fNIRS) is a valuable neuroimaging technique for studying cognitive processes, offering a non-invasive way to measure hemodynamic responses associated with cortical activity during naturalistic tasks. However, systemic-physiological noise – originating from factors such as respiration, heart rate, and extracerebral tissue – compromises neural signal accuracy and test-retest reliability. To address this, we conducted a comprehensive analysis of noise correction methods across repeated sessions of a passive auditory task. While certain correction approaches reduce reliability metrics by removing global systemic noise, which can artificially bolster reliability, regressing out these artifacts improves the accuracy and interpretability of the auditory-evoked neural response.

Building on these findings, we applied an optimized correction approach to an independent active-listening experiment examining the effects of varying forms of auditory cognitive load on sentence recognition in younger and older adults. Cognitive load was manipulated through two factors: stimulus length and stimulus speed. Behavioral measures included delayed recall task performance, subjective workload ratings, and standardized cognitive assessments, while neurophysiological measures encompassed fNIRS-derived cortical hemodynamics and systemic-physiological signals. Results indicate that task accuracy and physiological responses are differentially modulated by cognitive load type and age, with neural engagement decreasing when cognitive demands exceed an individual’s capacity, particularly in older adults. Additionally, behavioral data suggest age-related differences in the cognitive strategies used to manage these load conditions. These findings contribute to a more nuanced understanding of the relationship between cognitive load, neural processing, and age-related cognitive adaptation in auditory and speech perception.