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Learn how to create a standard extracellular electrophysiology dataset in NWB using Python.

Difficulty level: Intermediate
Duration: 23:10
Speaker: : Ryan Ly

Learn how to create a standard calcium imaging dataset in NWB using Python.

Difficulty level: Intermediate
Duration: 31:04
Speaker: : Ryan Ly

In this tutorial, you will learn how to create a standard intracellular electrophysiology dataset in NWB using Python.

Difficulty level: Intermediate
Duration: 20:23
Speaker: : Pamela Baker

Learn how to create a standard intracellular electrophysiology dataset in NWB.

Difficulty level: Intermediate
Duration: 20:22
Speaker: : Pamela Baker

This lesson provides an overview of the CaImAn package, as well as a demonstration of usage with NWB.

Difficulty level: Intermediate
Duration: 44:37

This lesson gives an overview of the SpikeInterface package, including demonstration of data loading, preprocessing, spike sorting, and comparison of spike sorters.

Difficulty level: Intermediate
Duration: 1:10:28
Speaker: : Alessio Buccino

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.

Difficulty level: Intermediate
Duration: 47:15
Speaker: : Ben Dichter

This tutorial provides instruction on how to simulate brain tumors with TVB (reproducing publication: Marinazzo et al. 2020 Neuroimage). This tutorial comprises a didactic video, jupyter notebooks, and full data set for the construction of virtual brains from patients and health controls.

Difficulty level: Intermediate
Duration: 10:01

The tutorial on modelling strokes in TVB includes a didactic video and jupyter notebooks (reproducing publication: Falcon et al. 2016 eNeuro).

Difficulty level: Intermediate
Duration: 7:43

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. 

Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke

This tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices. 

Difficulty level: Intermediate
Duration: 1:39:04