RT Journal Article
SR Electronic
T1 An Extension of the Fri Framework for Calcium Transient Detection
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 029751
DO 10.1101/029751
A1 Stephanie Reynolds
A1 Caroline S. Copeland
A1 Simon R. Schultz
A1 Pier Luigi Dragotti
YR 2015
UL http://biorxiv.org/content/early/2015/10/23/029751.abstract
AB Two-photon calcium imaging of the brain allows the spatiotemporal activity of neuronal networks to be monitored at cellular resolution. In order to analyse this activity it must first be possible to detect, with high temporal resolution, spikes from the time series corresponding to single neurons. Previous work has shown that finite rate of innovation (FRI) theory can be used to reconstruct spike trains from noisy calcium imaging data. In this paper we extend the FRI framework for spike detection from calcium imaging data to encompass data generated by a larger class of calcium indicators, including the genetically encoded indicator GCaMP6s. Furthermore, we implement least squares model-order estimation and perform a noise reduction procedure (‘pre-whitening’) in order to increase the robustness of the algorithm. We demonstrate high spike detection performance on real data generated by GCaMP6s, detecting 90% of electrophysiologically-validated spikes.Index Terms— Calcium imaging, Calcium transient detection, Finite rate of innovation, GCaMP6s