moco: Fast Motion Correction for Calcium Imaging

TL;DR

This paper introduces a fast, Fourier-transform-based motion correction algorithm for calcium imaging videos, enabling real-time analysis and targeted stimulation in neuroscience experiments with improved stability and efficiency.

Contribution

It presents a novel, efficient motion correction method combining downsampling and FFT-accelerated computations, suitable for real-time calcium imaging analysis.

Findings

Comparable accuracy to existing algorithms

More stable under large translational motions

Compatible with ImageJ and Java

Abstract

Motion correction is the first in a pipeline of algorithms to analyze calcium imaging videos and extract biologically relevant information, for example the network structure of the neurons therein. Fast motion correction would be especially critical for closed-loop activity triggered stimulation experiments, where accurate detection and targeting of specific cells in necessary. Our algorithm uses a Fourier-transform approach, and its efficiency derives from a combination of judicious downsampling and the accelerated computation of many $L_2$ norms using dynamic programming and two-dimensional, fft-accelerated convolutions. Its accuracy is comparable to that of established community-used algorithms, and it is more stable to large translational motions. It is programmed in Java and is compatible with ImageJ.