Why the study?
Significant hemoglobin-absorption artifacts in brain fiber-photometry data can be misinterpreted as sensor activity changes, impeding recording accuracy.
Spectral fiber-photometry combined with computational methods can accurately correct hemoglobin-absorption artifacts in fluorescent sensor activity in vivo.
Summary Fiber-photometry is an emerging technique for recording fluorescent sensor activity in the brain. However, significant hemoglobin-absorption artifacts in fiber-photometry data may be misinterpreted as sensor activity changes. Because hemoglobin exists in nearly every location in the brain and its concentration varies over time, such artifacts could impede the accuracy of many photometry recording results. Here we present a novel use of spectral photometry technique and propose computational methods to quantify photon absorption effects by using activity-independent fluorescence signals, which can be used to derive oxy- and deoxy-hemoglobin concentration changes. Following time-locked neuronal activation in vivo , we observed that a 20% increase in CBV contributes to about a 4% decrease in green fluorescence signal and a 2% decrease in red fluorescence signal. While these hemoglobin concentration changes are often temporally delayed than the fast-responding fluorescence spikes, we found that erroneous interpretation may occur when examining pharmacology-induced sustained activity changes, and in some cases, hemoglobin-absorption could flip the GCaMP signal polarity. We provided hemoglobin-based correction methods to restore fluorescence signals across spectra and compare our results against the commonly used regression approach. We also demonstrated the utility of spectral fiber-photometry for delineating brain regional differences in hemodynamic response functions. Highlights Hemoglobin-absorption compromises fiber-photometry recording in vivo Spectral photometry allows quantification of hemoglobin concentration changes for correction The proposed platform allows measuring regional differences in neurovascular transfer function
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Zhang et al. (2021) studied this question.
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