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Pynapple: a light-weight python package for neural data analysis (Part 1/2)


In systems neuroscience, datasets are multimodal and include data-streams of various origins: multichannel electrophysiology, 1- or 2-p calcium imaging, behavior, etc. Often, the exact nature of data streams are unique to each lab, if not each project. Analyzing these datasets in an efficient and open way is crucial for collaboration and reproducibility. In this combined webinar and tutorial, Adrien Peyrache and Guillaume Viejo will present Pynapple, a Python-based data analysis pipeline for systems neuroscience. Designed for flexibility and versatility, Pynapple allows users to perform cross-modal neural data analysis via a common programming approach which facilitates easy sharing of both analysis code and data.

GitHub resources:

Pynapple Webinar Part 1 - Introduction and Overview

Adrien Peyrache will start with an overview of the historical context that led to the development of  Pynapple. A brief demonstration of Pynapple, as a prelude to the more advanced tutorial session, will cover the main components of the package.