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Functional data analysis view of functional near infrared spectroscopy data.

Zeinab Barati1, Issa Zakeri, Kambiz Pourrezaei

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Summary

Functional data analysis (fDA) transforms discrete fNIRS data into continuous curves. This method enhances the study of tissue oxygenation and hemodynamics, offering deeper insights into physiological responses during tests like the cold pressor test (CPT).

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Physiology

Background:

  • Functional near-infrared spectroscopy (fNIRS) measures tissue oxygenation and hemodynamics.
  • Current fNIRS analysis methods are limited to discrete-time approaches, failing to capture continuous physiological processes.
  • A novel approach is needed to fully leverage the continuous nature of fNIRS data.

Purpose of the Study:

  • To introduce functional data analysis (fDA) as a method for analyzing continuous fNIRS data.
  • To apply fDA to fNIRS data collected during a cold pressor test (CPT).
  • To investigate the interaction between oxyhemoglobin (HbO2) and deoxyhemoglobin (Hb) dynamics using fDA.

Main Methods:

  • Functional data analysis (fDA) was employed to convert discrete fNIRS samples into continuous curves.
  • Functional principal component analysis (fPCA) was used to decompose HbO2 and Hb curves based on inter-subject variability.
  • Functional canonical correlation analysis (fCCA) investigated the relationship between HbO2 and Hb curves.

Main Results:

  • fPCA identified components related to experimental conditions, providing qualitative and quantitative insights into hemodynamic responses.
  • fCCA revealed a positive correlation between Hb and HbO2 variations during the CPT.
  • Specific findings indicated faster and smaller HbO2 variations compared to Hb in certain brain regions.

Conclusions:

  • The fDA platform offers a robust method for analyzing high-dimensional fNIRS data.
  • fDA enhances the study of physiological response dynamics and characterization of evoked responses.
  • This approach has the potential to improve the design and analysis of future fNIRS experiments.