This lesson demonstrates how to use MATLAB to implement a multivariate dimension reduction method, PCA, on time series data.
This is a tutorial introducing participants to the basics of RNA-sequencing data and how to analyze its features using Seurat.
This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).
This lesson corresponds to slides 65-90 of the PDF below.
This tutorial provides instruction on how to interact with and leverage Python packages to get the most out of Python's suite of available tools for the manipulation, management, analysis, and visualization of neuroscientific data.
This lesson provides an overview of the CaImAn package, as well as a demonstration of usage with NWB.
This lesson gives an overview of the SpikeInterface package, including demonstration of data loading, preprocessing, spike sorting, and comparison of spike sorters.
In this lesson, users will learn about the NWBWidgets package, including coverage of different data types, and information for building custom widgets within this framework.