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This hands-on tutorial explains how to run your own Minion session in the MetaCell cloud using jupityr notebooks.

Difficulty level: Beginner
Duration: 01:28:03

This is an in-depth guide on EEG signals and their interaction within brain microcircuits. Participants are also shown techniques and software for simulating, analyzing, and visualizing these signals.

Difficulty level: Intermediate
Duration: 1:30:41
Speaker: : Frank Mazza

In this tutorial on simulating whole-brain activity using Python, participants can follow along using corresponding code and repositories, learning the basics of neural oscillatory dynamics, evoked responses and EEG signals, ultimately leading to the design of a network model of whole-brain anatomical connectivity. 

Difficulty level: Intermediate
Duration: 1:16:10
Speaker: : John Griffiths

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks. 

Difficulty level: Beginner
Duration: 58:05

This lesson contains practical exercises which accompanies the first few lessons of the Neuroscience for Machine Learners (Neuro4ML) course. 

Difficulty level: Intermediate
Duration: 5:58
Speaker: : Dan Goodman

This lesson introduces some practical exercises which accompany the Synapses and Networks portion of this Neuroscience for Machine Learners course. 

Difficulty level: Intermediate
Duration: 3:51
Speaker: : Dan Goodman

This lesson introduces the practical exercises which accompany the previous lessons on animal and human connectomes in the brain and nervous system. 

Difficulty level: Intermediate
Duration: 4:10
Speaker: : Dan Goodman

In this lesson, you will learn how to train spiking neural networks (SNNs) with a surrogate gradient method. 

Difficulty level: Intermediate
Duration: 11:23
Speaker: : Dan Goodman

This video briefly goes over the exercises accompanying Week 6 of the Neuroscience for Machine Learners (Neuro4ML) course, Understanding Neural Networks.

Difficulty level: Intermediate
Duration: 2:43
Speaker: : Marcus Ghosh

In this tutorial, you will learn how to use TVB-NEST toolbox on your local computer.

Difficulty level: Beginner
Duration: 2:16

This tutorial provides instruction on how to perform multi-scale simulation of Alzheimer's disease on The Virtual Brain Simulation Platform.

Difficulty level: Beginner
Duration: 29:08

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

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 a hands-on, Jupyter-notebook-based tutorial to apply machine learning in Python to brain-imaging data.

Difficulty level: Beginner
Duration: 02:13:53
Speaker: : Jake Vogel

This lesson from freeCodeCamp introduces Scikit-learn, the most widely used machine learning Python library.

Difficulty level: Beginner
Duration: 02:09:22
Speaker: :
Course:

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

 

Difficulty level: Beginner
Duration: 1:09:16
Speaker: : Aaron J. Newman