Scale Invariance in fNIRS as a Measurement of Cognitive Load

Zhuang, Chu; Meidenbauer, Kimberly L.; Kardan, Omid; Stier, Andrew J.; Choe, Kyoung Whan; Cardenas-Iniguez, Carlos; Huppert, Theodore J.; Berman, Marc G. · 2021 · Crossref

DOI: 10.1101/2021.08.31.458427

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Summary

This study investigates whether scale invariance, quantified by the Hurst exponent (H), can serve as a reliable neural marker for cognitive load using functional near-infrared spectroscopy (fNIRS). While scale invariance has been validated as an indicator of cognitive effort in fMRI and EEG studies, its applicability to fNIRS—a portable, motion-robust neuroimaging technique suitable for real-world settings—had not previously been established. The authors hypothesized that H values would decrease as cognitive load increased, mirroring findings from other modalities. The researchers analyzed data from 52 adult participants who performed an N-back working memory task with varying difficulty levels (1-back, 2-back, and 3-back) while fNIRS data were recorded. The fNIRS system measured changes in oxygenated (HbO) and deoxygenated (HbR) hemoglobin concentrations across 33 channels covering the bilateral frontal cortex. Data preprocessing involved converting raw light intensity to optical density and then to concentration changes. The Hurst exponent was calculated using Detrended Fluctuations Analysis (DFA) on 20-second segments of both task and rest periods. To ensure data quality, the authors excluded noisy channels and participants based on the Structured Noise Index (SNI) and regressed SNI from H values to control for systematic noise. Motion artifacts were also evaluated to confirm they did not drive the results. The results demonstrated that scale-invariance analysis significantly differentiated between task and rest periods, with higher H values observed during rest than during task performance. Furthermore, H values were higher during the less demanding 1-back task compared to the more difficult 2-back task, supporting the hypothesis that scale invariance decreases with increased cognitive load. These effects were more pronounced in H values derived from HbR signals than from HbO signals, likely due to HbR’s tighter coupling with the BOLD response. Although the 3-back condition did not show significant differences from other task levels, this was attributed to participant disengagement and poor performance at that difficulty level. Multivariate partial least squares analysis replicated these findings, confirming that H is sensitive to task difficulty. These findings establish that scale invariance in fNIRS data, particularly from deoxyhemoglobin signals, is a valid measure of cognitive load. By validating this metric in fNIRS, the study opens avenues for monitoring cognitive fatigue and load in ecologically valid, real-life settings such as driving, education, and clinical environments, where traditional neuroimaging methods are impractical.

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• neuro workload indices
• workload measurement

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• Empirical Findings: physiological data