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fMRI Validation of fNIRS Measurements During a Naturalistic Task

fMRI Validation of fNIRS Measurements During a Naturalistic Task

Published on: June 15, 2015

Time-Resolved Information-Theoretic and Spectral Analysis of fNIRS Signals from Multi-Channel Prototypal Device.

Irene Franzone¹, Yuri Antonacci¹, Fabrizio Giuliano¹

¹Department of Engineering, University of Palermo, 90128 Palermo, Italy.

Entropy (Basel, Switzerland)

|July 29, 2025

Summary

Functional near-infrared spectroscopy (fNIRS) reveals how breathing affects brain hemodynamics. Information-theoretic and spectral analyses show significant respiratory modulations in fNIRS signals, enhancing understanding of network physiology.

Keywords:

functional near-infrared spectroscopy information dynamics network physiology power spectral density recursive least-squares time-resolved analysis time-varying autoregressive modeling

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Area of Science:

Neuroscience
Physiology
Biomedical Engineering

Background:

Functional near-infrared spectroscopy (fNIRS) is a non-invasive brain imaging technique.
It measures hemodynamic activity by detecting changes in oxygenated and deoxygenated hemoglobin.
Understanding peripheral influences on fNIRS signals is crucial for accurate brain activity interpretation.

Purpose of the Study:

To comprehensively characterize fNIRS signals during a breath-holding task.
To evaluate the impact of respiratory activity on scalp hemodynamics.
To explore fNIRS signal dynamics within the framework of Network Physiology.

Main Methods:

Utilized a prototypal continuous-wave fNIRS device.
Applied information-theoretic measures (entropy, conditional entropy, information storage) in the time domain.
Employed power spectral density estimation in the frequency domain.

Main Results:

Conditional entropy significantly modulated by respiratory activity.
Distinct informational dynamics observed between breathing and apnea phases.
Significant modulations in oscillation amplitude and frequency, particularly in the respiratory-related high-frequency band.

Conclusions:

Information-theoretic and spectral analyses provide novel insights into fNIRS signal characterization.
Respiratory activity substantially impacts scalp hemodynamics measured by fNIRS.
Enhanced understanding of task-induced peripheral cardiovascular responses on fNIRS hemodynamics.