Skip to main content

The Virtual Brain is an open-source, multi-scale, multi-modal brain simulation platform. In this lesson, you get introduced to brain simulation in general and to The Virtual brain in particular. Prof. Ritter will present the newest approaches for clinical applications of The Virtual brain - that is, for stroke, epilepsy, brain tumors and Alzheimer’s disease - and show how brain simulation can improve diagnostics, therapy and understanding of neurological disease.

Difficulty level: Beginner
Duration: 1:35:08
Speaker: : Petra Ritter

The concept of neural masses, an application of mean field theory, is introduced as a possible surrogate for electrophysiological signals in brain simulation. The mathematics of neural mass models and their integration to a coupled network are explained. Bifurcation analysis is presented as an important technique in the understanding of non-linear systems and as a fundamental method in the design of brain simulations. Finally, the application of the described mathematics is demonstrated in the exploration of brain stimulation regimes.

Difficulty level: Beginner
Duration: 1:49:24
Speaker: : Andreas Spiegler

The simulation of the virtual epileptic patient is presented as an example of advanced brain simulation as a translational approach to deliver improved results in clinics. The fundamentals of epilepsy are explained. On this basis, the concept of epilepsy simulation is developed. 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

A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner
Duration: 1:16:36
Speaker: : Tal Yarkoni

In this presentation by the OHBM OpenScienceSIG, Tom Shaw and Steffen Bollmann cover how containers can be useful for running the same software on different platforms and sharing analysis pipelines with other researchers. They demonstrate how to build docker containers from scratch, using Neurodocker, and cover how to use containers on an HPC with singularity.

 

 

Difficulty level: Beginner
Duration: 01:21:59

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

Difficulty level: Beginner
Duration: 37:51

This module explores sensation in the brain: what organs are involved, sensory pathways, processing centers, and theories of integration. We cover sensory transduction, vision, audition olfaction, gustation, and somatosensation.

Difficulty level: Beginner
Duration: 7:17
Speaker: : Colin Fausnaught

This module covers how the brain interacts with the world through motor movements. Motor movements underlie so much of our functioning, our speech, the opening and closing of our eyes, and the beating of our hearts. We’ll learn about areas of the brain involved in movement and some of its pathways.

Difficulty level: Beginner
Duration: 5:00
Speaker: : Harrison Canning

This module covers the structure and function of the neuron, its components and mechanisms, action potentials, and the many glial cells that support it.

Difficulty level: Beginner
Duration: 8:31
Speaker: : Colin Fausnaught

This module explains how neurons come together to create the networks that give rise to our thoughts. The totality of our neurons and their connection is called our connectome. Learn how this connectome changes as we learn, and computes information. We will also learn about physiological phenomena of the brain such as synchronicity that gives rise to brain waves.

Difficulty level: Beginner
Duration: 7:13
Speaker: : Harrison Canning

Introduction to neurons, synaptic transmission, and ion channels.

Difficulty level: Beginner
Duration: 46:07

Introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.

Difficulty level: Beginner
Duration: 40:32

This lecture covers: integrating information within a network, modulating and controlling networks, functions and dysfunctions of hippocampal networks, and the integrative network controlling sleep and arousal.

Difficulty level: Beginner
Duration: 47:05

This lecture focuses on the comprehension of nociception and pain sensation. It highlights how the somatosensory system and different molecular partners are involved in nociception and how nociception and pain sensation are studied in rodents and humans and the development of pain therapy.

Difficulty level: Beginner
Duration: 28:09
Speaker: : Serena Quarta

This lecture provides an introduction to the study of eye-tracking in humans. 

Difficulty level: Beginner
Duration: 34:05
Speaker: : Ulrich Ettinger

This lecture provides an introduction to the application of genetic testing in neurodevelopmental disorders.

Difficulty level: Beginner
Duration: 37:47

How genetics can contribute to our understanding of psychiatric phenotypes.

Difficulty level: Beginner
Duration: 55:15
Speaker: : Sven Cichon

Introduction to the FAIR Principles and examples of applications of the FAIR Principles in neuroscience. This lecture 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: Beginner
Duration: 55:57

Introduction to reproducible research. The lecture provides an overview of the core skills and practical solutions required to practice reproducible research. This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez

Much like neuroinformatics, data science uses techniques from computational science to derive meaningful results from large complex datasets. In this session, we will explore the relationship between neuroinformatics and data science, by emphasizing a range of data science approaches and activities, ranging from the development and application of statistical methods, through the establishment of communities and platforms, and through the implementation of open-source software tools. Rather than rigid distinctions, in the data science of neuroinformatics, these activities and approaches intersect and interact in dynamic ways. Together with a panel of cutting-edge neuro-data-scientist speakers, we will explore these dynamics

 

This lecture covers the description and brief history of data science and its use in neuroinformatics.

Difficulty level: Beginner
Duration: 11:15
Speaker: : Ariel Rokem