Techniques to identify and temporally correlate calcium transients between multiple regions of interest in vertebrate neural circuits.

Calcium imaging is commonly used to record dynamic changes in excitability from axons or cell bodies in the nervous system of vertebrates. These recordings often reveal discrete calcium transients that have variable amplitudes, durations, and rates of rise and decay, all of which can arise from an unstable or "noisy" baseline. This often leads to considerable ambiguity about how to discriminate and quantify calcium transients. We describe an analytical methodology that objectively identifies multiple calcium transients from multiple recording sites and quantifies the degree of temporal synchrony between each event. The methodology consists of multiple steps. The first step involves baselining, to either preserve the underlying shape of calcium transients or remove unwanted frequency components and transform the peaks of calcium transients into more easily detectable patterns. The second step is the application of at least one of two different spike detection algorithms, one based on a gradient estimate and the other on template matching. The third step is the quantification of synchrony between pairs of recordings using at least one of two time lag correlation measures. The fourth step is the identification of statistically significant coincident firing patterns. This allows discrimination of neuronal firing patterns between different sites that appear to occur simultaneously and that statistically could not be attributed to chance. The analytical methods we have demonstrated can be applied not only to calcium imaging but also to many other physiological recordings, where discrimination and temporal correlation of biological signals from multiple sites is required, particularly when arising from unstable baselines, with variable signal-to-noise ratios.