Data Processing of Functional Optical Microscopy for Neuroscience
Image and Video Processing
2022-01-11 v1 Neurons and Cognition
Quantitative Methods
Abstract
Functional optical imaging in neuroscience is rapidly growing with the development of new optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. In this review, we cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.
Cite
@article{arxiv.2201.03537,
title = {Data Processing of Functional Optical Microscopy for Neuroscience},
author = {Hadas Benisty and Alexander Song and Gal Mishne and Adam S. Charles},
journal= {arXiv preprint arXiv:2201.03537},
year = {2022}
}
Comments
33 pages, 5 figures