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The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

Difficulty level: Intermediate
Duration: 5:17
Speaker: : Mike X. Cohen

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

Difficulty level: Intermediate
Duration: 11:37
Speaker: : Mike X. Cohen

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

Difficulty level: Intermediate
Duration: 5:31
Speaker: : Mike X. Cohen

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

Difficulty level: Intermediate
Duration: 13:48
Speaker: : Mike X. Cohen

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

Difficulty level: Intermediate
Duration: 12:16
Speaker: : Mike X. Cohen

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

Difficulty level: Intermediate
Duration: 13:11
Speaker: : Mike X. Cohen

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

Difficulty level: Intermediate
Duration: 8:21
Speaker: : Mike X. Cohen

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

Difficulty level: Intermediate
Duration: 22:01
Speaker: : Mike X. Cohen

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

Difficulty level: Intermediate
Duration: 11:20
Speaker: : Mike X. Cohen

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

Difficulty level: Intermediate
Duration: 20:39
Speaker: : Mike X. Cohen

Explore how to setup an epileptic seizure simulation with the TVB graphical user interface. This lesson will show you how to program the epileptor model in the brain network to simulate a epileptic seizure originating in the hippocampus. It will also show how to upload and view mouse connectivity data, as well as give a short introduction to the python script interface of TVB.

Difficulty level: Intermediate
Duration: 58:06
Speaker: : Paul Triebkorn

Brain network reconstruction from empirical data is of key importance to generate personalized virtual brain models. This lecture will introduce the basic concepts of preprocessing structural, functional and diffusion weighted neuroimages. It highlights the latest methods and pipelines to extract structural as well as functional connectomes according to a multimodal parcellation.

Difficulty level: Intermediate
Duration: 1:17:32
Speaker: : Michael Schirner

This lecture presents two recent clinical case studies using TVB: stroke recovery and dementia (due to Alzheimer’s Disease (AD)). Using a multi-scale neurophysiological model based on empirical multi-modal neuroimaging data, we show how local and global biophysical parameters characterize changes in  individualized patient-specific brain dynamics, predict recovery of motor function for stroke patients, and correlate with individual differences in cognition for AD patients.

Difficulty level: Intermediate
Duration: 32:11
Speaker: : Randy McIntosh

In this lesson, Yaroslav O. Halchenko describes how DataLad allows you to track and mange both your data and analysis code, thereby facilitating reliable, reproducible, and shareable research.

Difficulty level: Intermediate
Duration: 59:34

Tutorial on how to simulate brain tumor brains 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. Authors: Hannelore Aerts, Michael Schirner, Ben Jeurissen, DIrk Van Roost, Eric Achten, Petra Ritter, Daniele Marinazzo

Difficulty level: Intermediate
Duration: 10:01
Speaker: :

The tutorial comprises a didactic video and jupyter notebooks (reproducing publication: Falcon et al. 2016 eNeuro). Contributors: Daniele Marinazzo, Petra Ritter, Paul Triebkorn, Ana Solodkin

Difficulty level: Intermediate
Duration: 7:43
Speaker: :

Tutorial on collaborating with Git and GitHub. This tutorial was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 2:15:50
Speaker: : Elizabeth DuPre

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

Learn how to create a standard intracellular electrophysiology dataset in NWB

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