# Data Processing of Functional Optical Microscopy for Neuroscience

arXiv: https://arxiv.org/abs/2201.03537 · HTML: https://mlsanity.com/paper/2201.03537/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jan 2022.

## Built on by (most cited first, 2 of 2)

- [Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data](https://mlsanity.com/paper/2509.18507/) (2025)
- [Deep and shallow data science for multi-scale optical neuroscience](https://mlsanity.com/paper/2402.08811/) (2024)

## Abstract (arXiv)

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.