Data Processing of Functional Optical Microscopy for Neuroscience

2022/01/10 by Benisty, Hadas, Song, Alexander, Mishne, Gal +1 · 1 citation
#FOS: Biological sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Neurons and Cognition (q-bio.NC) #Quantitative Methods (q-bio.QM) #electronic engineering #information engineering

paper · doi:10.48550/arxiv.2201.03537

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.

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• Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data

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