Welcome to the first pynapple-fastplotlib-nemos workshop, which will run from June 23 to 24, 2024, right before the FENS Forum! This workshop will teach attendees how to use open source python libraries developed by the NeuroRSE Group at the Flatiron Institute's Center for Computational Neuroscience to explore, manipulate, visualize, and analyze their systems neuroscience data.
pynapple is a light-weight python library for neurophysiological data analysis. The goal is to offer a versatile set of tools to study typical data in the field, i.e. time series (spike times, behavioral events, etc.) and time intervals (trials, brain states, etc.). It also provides users with generic functions for neuroscience such as tuning curves and cross-correlograms.
Next-gen plotting library built using the pygfx rendering engine that can utilize modern GPUs so it is very fast! It is an expressive plotting library that enables rapid prototyping for large scale explorative scientific visualization.
A statistical modeling framework for systems neuroscience. Nemos, our latest software package, specializes in GPU-accelerated optimizations. Its current core functionality includes the implementation of the Generalized Linear Model (GLM) for spike train analysis.
Workshop contents
Through a combination of theoretical presentations and hands-on tutorials, attendees will learn how to:
- Use pynapple to stream publicly available datasets following the Neurodata Without Borders (NWB) standard.
- Use pynapple to manipulate time series and perform standard system neuroscience analyses such as tuning curves, cross-correlograms and more.
- Use fastplotlib to build efficient and powerful GPU-accelerated visualizations.
- Use nemos to fit Generalized Linear Models (GLM) in order to gain insight into neural responses.
To learn more and apply, click here.
