In this lesson, the simulation of a virtual epileptic patient is presented as an example of advanced brain simulation as a translational approach to deliver improved clinical results. You will learn about the fundamentals of epilepsy, as well as the concepts underlying epilepsy simulation. By using an iPython notebook, the detailed process of this approach is explained step by step. In the end, you are able to perform simple epilepsy simulations your own.

Difficulty level: Beginner

Duration: 1:28:53

Speaker: : Julie Courtiol

This lecture presents the Graphical (GUI) and Command Line (CLI) User Interface of TVB. Alongside with the speakers, explore and interact with all means necessary to generate, manipulate and visualize connectivity and network dynamics.

Difficulty level: Beginner

Duration: 1:02:16

Speaker: : Paula Popa & Mihai Andrei

This lecture briefly introduces The Virtual Brain (TVB), a multi-scale, multi-modal neuroinformatics platform for full brain network simulations using biologically realistic connectivity, as well as its potential neuroscience applications (e.g., epilepsy cases).

Difficulty level: Beginner

Duration: 8:53

Speaker: : Petra Ritter

This lecture introduces the theoretical background and foundations that led to the development of TVB, its architecture, and features of its major software components.

Difficulty level: Beginner

Duration: 46:50

Speaker: : Randy McIntosh

This presentation accompanies the paper entitled: *An automated pipeline for constructing personalized virtual brains from multimodal neuroimaging data *(see link below to download publication).

Difficulty level: Beginner

Duration: 4:56

This lecture provides an overview of successful open-access projects aimed at describing complex neuroscientific models, and makes a case for expanded use of resources in support of reproducibility and validation of models against experimental data.

Difficulty level: Beginner

Duration: 1:00:39

Speaker: : Sharon Crook

Course:

This demonstration walks through how to import your data into MATLAB.

Difficulty level: Beginner

Duration: 6:10

Speaker: : MATLAB®

Course:

This lesson provides instruction regarding the various factors one must consider when preprocessing data, preparing it for statistical exploration and analyses.

Difficulty level: Beginner

Duration: 15:10

Speaker: : MATLAB®

Course:

This tutorial outlines, step by step, how to perform analysis by group and how to do change-point detection.

Difficulty level: Beginner

Duration: 2:49

Speaker: : MATLAB®

Course:

This tutorial walks through several common methods for visualizing your data in different ways depending on your data type.

Difficulty level: Beginner

Duration: 6:10

Speaker: : MATLAB®

Course:

This tutorial illustrates several ways to approach predictive modeling and machine learning with MATLAB.

Difficulty level: Beginner

Duration: 6:27

Speaker: : MATLAB®

Course:

This brief tutorial goes over how you can easily work with big data as you would with any size of data.

Difficulty level: Beginner

Duration: 3:55

Speaker: : MATLAB®

Course:

In this tutorial, you will learn how to deploy your models outside of your local MATLAB environment, enabling wider sharing and collaboration.

Difficulty level: Beginner

Duration: 3:52

Speaker: : MATLAB®

Course:

This lesson provides a brief overview of the Python programming language, with an emphasis on tools relevant to data scientists.

Difficulty level: Beginner

Duration: 1:16:36

Speaker: : Tal Yarkoni

Course:

This lecture gives an introduction to the FAIR (findability, accessibility, interoperability, and reusability) science principles and examples of their application in neuroscience research.

Difficulty level: Beginner

Duration: 55:57

Speaker: : Maryann E. Martone

Course:

The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.

Difficulty level: Beginner

Duration: 1:25:17

Speaker: : Fernando Perez

This lecture on model types introduces the advantages of modeling, provide examples of different model types, and explain what modeling is all about.

Difficulty level: Beginner

Duration: 27:48

Speaker: : Gunnar Blohm

This lecture summarizes the concepts introduced in Model Types I and further explains how models can be used answer different scientific questions.

Difficulty level: Beginner

Duration: 32:30

Speaker: : Megan Peters

Course:

This lecture focuses on how to get from a scientific question to a model using concrete examples. We will present a 10-step practical guide on how to succeed in modeling. This lecture contains links to 2 tutorials, lecture/tutorial slides, suggested reading list, and 3 recorded Q&A sessions.

Difficulty level: Beginner

Duration: 29:52

Speaker: : Megan Peters

Course:

This lecture formalizes modeling as a decision process that is constrained by a precise problem statement and specific model goals. We provide real-life examples on how model building is usually less linear than presented in Modeling Practice I.

Difficulty level: Beginner

Duration: 22:51

Speaker: : Gunnar Blohm

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