Performance comparison of systemic activity correction in functional near-infrared spectroscopy for methods with and without short distance channels

Abstract

Significance: Functional near-infrared spectroscopy (fNIRS) is a promising tool for neurofeedback (NFB) or brain-computer interfaces (BCIs). However, fNIRS signals are typically highly contaminated by systemic activity (SA) artifacts, and, if not properly corrected, NFB or BCIs run the risk of being based on noise instead of brain activity. This risk can likely be reduced by correcting for SA, in particular when short-distance channels (SDCs) are available. Literature comparing correction methods with and without SDCs is still sparse, specifically comparisons considering single trials are lacking.Aim: This study aimed at comparing the performance of SA correction methods with and without SDCs.Approach: Semisimulated and real motor task data of healthy older adults were used. Correction methods without SDCs included a simple and a more advanced spatial filter. Correction methods with SDCs included a regression approach considering only the closest SDC and two GLM-based methods, one including all eight SDCs and one using only two a priori selected SDCs as regressors. All methods were compared with data uncorrected for SA and correction performance was assessed with quality measures quantifying signal improvement and spatial specificity at single trial level.Results: All correction methods were found to improve signal quality and enhance spatial specificity as compared with the uncorrected data. Methods with SDCs usually outperformed methods without SDCs. Correction methods without SDCs tended to overcorrect the data. However, the exact pattern of results and the degree of differences observable between correction methods varied between semisimulated and real data, and also between quality measures.Conclusions: Overall, results confirmed that both Δ½HbO and Δ½HbR are affected by SA and that correction methods with SDCs outperform methods without SDCs. Nonetheless, improvements in signal quality can also be achieved without SDCs and should therefore be given priority over not correcting for SA.

Using preregistration as a tool for transparent fNIRS study design

“…SDCs are generated by placing the source and detector at a distance of <1 cm, and ideally at ∼0.8 cm for adults, 94 to capture the hemodynamic activity from extracerebral tissue only 36 , 126 , 148 – 152 SDC signals can be used for correcting the regular distance channels, for instance, by applying a regression-based approach. If no SDCs are available, it is recommended to apply an alternative method to reduce the extracerebral systemic activity 8 , 19 , 150 , 152 …”

“… – 152 SDC signals can be used for correcting the regular distance channels, for instance, by applying a regression-based approach. If no SDCs are available, it is recommended to apply an alternative method to reduce the extracerebral systemic activity 8 , 19 , 150 , 152 …”

“…If no SDCs are available, it is recommended to apply an alternative method to reduce the extracerebral systemic activity. 8,19,150,152 In any case, the type of algorithm that will be applied for correction should be documented. For instance, for a simple regression, it is possible to use the closest SDC, the SDC with the highest correlation, the average across SDCs, or the first n principal components resulting from a principal component analysis of all SDCs.…”

Successful Modulation of Temporoparietal Junction Activity and Stimulus-Driven Attention by fNIRS-based Neurofeedback – a Randomized Controlled Proof-of-Concept Study

“…However, we took care to keep the contribution of systemic physiological changes in our design to a minimum and assessed the robustness of the online analysis through an additional offline analysis using more stringent preprocessing methods. More state-of-the art online artifact control measures and signal processing methods (Klein and Kranczioch, 2019; Lühmann et al, 2020; Klein et al, 2022; Schroeder et al, 2023) are now available and can be used in future studies to sufficiently rule out the contributions of systemic physiology.…”

Special Section Guest Editorial: Thirty Years of Functional Near-Infrared Spectroscopy

“…fNIRS analysis is particularly sensitive to confounding from systemic physiology and contamination of signal from superficial extracranial tissues. Sophisticated analysis techniques continue to evolve to tackle these issues 12 – 15 …”