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Updated: Nov 27, 2025

Automated Analysis of Dynamic Ca2+ Signals in Image Sequences
Published on: June 16, 2014
Computational Analysis of PER2::LUC Imaging Data
1Department of Mathematics and Statistics, Amherst College, Amherst, MA, USA. tleise@amherst.edu.
Abstract:
Advances in imaging technology, combined with the development of bioluminescent reporters for core clock genes, has enabled the observation of spatiotemporal patterns of circadian rhythms in the suprachiasmatic nuclei (SCN). In particular, the PERIOD2::luciferase (PER2::LUC) knockin mouse has led to novel approaches for studying the heterogeneous circadian network in the SCN. This chapter describes how to automate the processing of PER2::LUC imaging data from SCN slices for generating spatiotemporal maps of circadian parameters like phase, period, and amplitude. These maps can be aligned and averaged to produce composite maps displaying common features across multiple slices. In addition, we describe a method for automated detection of cell-like regions of interest, to support the study of the neural network in the SCN.
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