Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technique measuring oxy- and de-oxy hemoglobin concentration changes.
• fNIRS offers good temporal resolution, making it suitable for brain-computer interface applications.
• Despite advancements, a standardized method for fNIRS data analysis remains elusive.

Purpose of the Study:

• To provide a comprehensive review of existing methodologies for modeling and analyzing fNIRS signals.
• To offer an overview of techniques for extracting meaningful information from fNIRS data.
• To summarize current challenges in fNIRS signal analysis.

Main Methods:

• Review of pre-processing steps for fNIRS data.
• Analysis of the impact of differential path length factor (DPF).
• Examination of hemodynamic response function (HRF) variations and attributes.
• Methods for evoked response extraction and physiological/environmental noise removal.
• Assessment of resting/activation state functional connectivity.

Main Results:

• Identified various established and emerging methods for fNIRS data analysis.
• Highlighted the importance of accounting for DPF and HRF characteristics.
• Discussed techniques for noise reduction and functional connectivity assessment.
• Summarized the limitations and challenges in current fNIRS analysis.

Conclusions:

• The review consolidates diverse fNIRS analysis approaches, aiding researchers in selecting appropriate methods.
• Standardization of fNIRS data analysis is crucial for improving reproducibility and comparability.
• Further research is needed to address remaining challenges in signal processing and interpretation.