Information theoretic approaches to deciphering the neural code with functional fluorescence imaging

Information theoretic metrics have proven highly useful to quantify the relationship between behaviorally relevant parameters and neuronal activity with relatively few assumptions. However, such metrics are typically applied to action potential recordings and were not designed for the slow timescales and variable amplitudes typical of functional fluorescence recordings (e.g. calcium imaging). Therefore, the power of information theoretic metrics has yet to be fully exploited by the neuroscience community due to a lack of understanding for how to apply and interpret the metrics with such fluorescence traces. Here, we used computational methods to create mock action potential traces with known amounts of information and from them generated fluorescence traces to examine the ability of different information metrics to recover the known information values. We provide guidelines for the use of information metrics when applied to functional fluorescence and demonstrate their appropriate application to GCaMP6f population recordings from hippocampal neurons imaged during virtual navigation.