Comparative Effects of Event Detection Methods on the Analysis and Interpretation of Ca(2+) Imaging Data

Calcium imaging has gained substantial popularity as a tool to profile the activity of multiple simultaneously active cells at high spatiotemporal resolution. Among the diverse approaches to processing of Ca(2+) imaging data is an often subjective decision of how to quantify baseline fluorescence or F(0). We examine the effect of popular F(0) determination methods on the interpretation of neuronal and astrocyte activity in a single dataset of rats trained to self-administer intravenous infusions of cocaine and compare them with an F(0)-independent wavelet ridgewalking event detection approach. We find that the choice of the processing method has a profound impact on the interpretation of widefield imaging results. All of the dF/F(0) thresholding methods tended to introduce spurious events and fragment individual transients, leading to smaller calculated event durations and larger event frequencies. Analysis of simulated datasets confirmed these observations and indicated substantial intermethod variability as to the events classified as significant. Additionally, most dF/F(0) methods on their own were unable to adequately account for bleaching of fluorescence, although the F(0) smooth approach and the wavelet ridgewalking algorithm both did so. In general, the choice of the processing method led to dramatically different quantitative and sometimes opposing qualitative interpretations of the effects of cocaine self-administration both at the level of individual cells and at the level of cell networks. Significantly different distributions of event duration, amplitude, frequency, and network measures were found across the majority of dF/F(0) approaches. The wavelet ridgewalking algorithm broadly outperformed dF/F(0)-based methods for both neuron and astrocyte recordings. These results indicate the need for heightened awareness of the limitations and tendencies associated with decisions to use particular Ca(2+) image processing pipelines. Both quantification and interpretation of the effects of experimental manipulations are strongly sensitive to such decisions.