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Refining hemodynamic correction in in vivo wide-field fluorescent imaging through linear regression analysis
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Refining hemodynamic correction in in vivo wide-field fluorescent imaging through linear regression analysis
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Refining hemodynamic correction in in vivo wide-field fluorescent imaging through linear regression analysis
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Journal Article
Refining hemodynamic correction in in vivo wide-field fluorescent imaging through linear regression analysis
2024
Overview
•We found that there are non-hemodynamic components in intrinsic optical imaging data.•We found that the non-hemodynamic components result in insufficient substruction of hemodynamic noise from wide-field fluorescent imaging data.•We developed a linear regression method that can calculate the non-hemodynamic components and lead to more precise hemodynamic subtraction.•We demonstrate that the new method works on data from various experiments.
Accurate interpretation of in vivo wide-field fluorescent imaging (WFFI) data requires precise separation of raw fluorescence signals into neural and hemodynamic components. The classical Beer-Lambert law-based approach, which uses concurrent 530-nm illumination to estimate relative changes in cerebral blood volume (CBV), fails to account for the scattering and reflection of 530-nm photons from non-neuronal components leading to biased estimates of CBV changes and subsequent misrepresentation of neural activity. This study introduces a novel linear regression approach designed to overcome this limitation. This correction provides a more reliable representation of CBV changes and neural activity in fluorescence data. Our method is validated across multiple datasets, demonstrating its superiority over the classical approach.
Publisher
Elsevier Inc,Elsevier Limited,Elsevier
