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

This lecture 1/15 is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 0:40

Speaker: : Florence I. Kleberg

This lecture (2/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:23

Speaker: : Florence I. Kleberg

This lecture (3/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:20

Speaker: : Florence I. Kleberg

This lecture (4/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:08

Speaker: : Florence I. Kleberg

This lecture (5/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:18

Speaker: : Florence I. Kleberg

This lecture (6/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures. Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:26

Speaker: : Florence I. Kleberg

This lecture (7/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 0:42

Speaker: : Florence I. Kleberg

This lecture (8/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 2:40

Speaker: : Florence I. Kleberg

This lecture (9/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 2:54

Speaker: : Florence I. Kleberg

This lecture (10/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:43

Speaker: : Florence I. Kleberg

This lecture (11/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 2:58

Speaker: : Florence I. Kleberg

This lecture (12/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 2:08

Speaker: : Florence I. Kleberg

This lecture (13/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures. Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:58

Speaker: : Florence I. Kleberg

This lecture (14/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 1:40

Speaker: : Florence I. Kleberg

This lecture (15/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate

Duration: 0:37

Speaker: : Florence I. Kleberg

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

Speaker: : Barbara Sperner-Unterweger

Introduction to neurons, synaptic transmission, and ion channels.

Difficulty level: Beginner

Duration: 46:07

Speaker: : Christoph Schwarzer

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

Speaker: : Christine Bandtlow

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

Speaker: : Christoph Schwarzer

- Clinical neuroscience (8)
- Neuroimaging (7)
- Brain networks (1)
- Glia (1)
- Electrophysiology (12)
- Standards and best practices (11)
- Tools (6)
- Neuroanatomy (2)
- (-) Neurobiology (4)
- Workflows (1)
- Neurodegeneration (1)
- Neuroimmunology (1)
- Neuropharmacology (1)
- (-) Neuronal plasticity (15)
- Clinical neuroinformatics (5)
- Computational neuroscience (92)
- Computer Science (5)
- (-) Genomics (1)
- Data science (5)
- Open science (4)
- Project management (6)
- Ethics (11)