Hierarchical Optimal Sampling (HOS): a tool for managing and manipulating wide-field imaging datasets - presentation at the Course of International School of Brain Cells and Circuits 'Camillo Golgi' on 'Modelling the Brain'

Presentation on Hierarchical Optimal Sampling: a tool for managing and manipulating wide-field imaging datasets. Powerful recording techniques and increasing anatomical knowledge provided by atlases allow studying the brain at a new level with unprecedented spatial resolution as that achieved with wide-field calcium imaging data. One of the the main issues related to the increase of the spatial resolution is to find the optimal condition which allows to obtain an appropriate signal-to-noise ratio for each channel, relative to the phenomenon of interest. Hierarchical Optimal Sampling (HOS) provides a data-driven inhomogeneous gridding of the field of view with the optimal spatial resolution that preserves and emphasizes the majority of the information from the high number of native signal sources.