It normalizes the intensity data during stimulus window by calculating an average Fo before stimulus, and then dviding the fluorescence values in this window by the background Fo.
1 | quantF_Fo(data, conditions, averageWindow)
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Normalizing first by an averaged background (Fo) right before stimulus corrects for photobleaching/drift.
Inputs: Data = Dataframe containing fluorescence intensity data Conditions = vectory of integers indicating when averageWindow = the window to use prior to stimulus for calculating Fo
i = odd index of conditions (corresponds of start of new condition) j = index of response
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