MBExC Lecture

Johannes Friedrich, PhD from the Center for Computational Neuroscience at the Flatiron Institute in New York will talk about “Online methods for real-time analysis of calcium imaging data” during the MBExC Lecture.

Abstract
Calcium imaging methods enable researchers to measure the activity of genetically-targeted large-scale neuronal populations. Previously, a constrained matrix factorization approach (CNMF) has been suggested to extract the activity of neuronal sources imaged using 2-photon microscopy. It has been extended further to handle the very large background fluctuations in 1-photon data (CNMF-E), where microendoscopic lenses and miniaturized microscopes are used to enable deep brain imaging in freely moving mice. However, both approaches rely on offline batch processing of the entire video data and are demanding both in terms of computing and memory requirements, in particular CNMF-E. Moreover, in some scenarios we want to perform experiments in real-time and closed-loop — analyzing data on-the-fly to guide the next experimental steps or to control feedback. Here we address both issues by introducing an online framework for the analysis of streaming calcium imaging data, including i) motion artifact correction, ii) neuronal source extraction, and iii) activity denoising and deconvolution. We first present online adaptations of the CNMF as well as the CNMF-E algorithm, which dramatically reduces memory and computation requirements. Secondly, we propose a new algorithm that uses a convolution-based background model for microendoscopic data. We show that our algorithms yield similar high-quality results as the popular offline approaches, but outperform them with regard to computing time and memory requirements. They enable faster and scalable analysis, and open the door to new closed-loop experiments.

Host: Prof. Dr. Fred Wolf

Location: MPI-NAT City Campus Lecture Hall, Hermann-Rein-Str. 3, 37075 Göttingen

Poster of the talk