This lesson gives a presentation on computationally demanding studies of synaptic plasticity on the molecular level.

Difficulty level: Advanced

Duration: 15:44

Speaker: : Kim "Avrama" Blackwell

Course:

This talk presents several computationally demanding studies of synaptic plasticity on the molecular level.

Difficulty level: Advanced

Duration: 15:44

Speaker: : Kim "Avrama" Blackwell

In this lesson you will hear about several computationally demanding studies of synaptic plasticity on the molecular level.

Difficulty level: Advanced

Duration: 15:44

Speaker: : Kim "Avrama" Blackwell

Course:

This lecture presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.

Difficulty level: Advanced

Duration: 50:28

Speaker: : Pierre Bellec

Course:

This lesson provides an introduction to biologically detailed computational modelling of neural dynamics, including neuron membrane potential simulation and F-I curves.

Difficulty level: Intermediate

Duration: 8:21

Speaker: : Mike X. Cohen

Course:

In this lesson, users learn how to use MATLAB to build an adaptive exponential integrate and fire (AdEx) neuron model.

Difficulty level: Intermediate

Duration: 22:01

Speaker: : Mike X. Cohen

Course:

In this lesson, users learn about the practical differences between MATLAB scripts and functions, as well as how to embed their neuronal simulation into a callable function.

Difficulty level: Intermediate

Duration: 11:20

Speaker: : Mike X. Cohen

Course:

This lesson teaches users how to generate a frequency-current (F-I) curve, which describes the function that relates the net synaptic current (I) flowing into a neuron to its firing rate (F).

Difficulty level: Intermediate

Duration: 20:39

Speaker: : Mike X. Cohen

This talk gives an overview of the Human Brain Project, a 10-year endeavour putting in place a cutting-edge research infrastructure that will allow scientific and industrial researchers to advance our knowledge in the fields of neuroscience, computing, and brain-related medicine.

Difficulty level: Intermediate

Duration: 24:52

Speaker: : Katrin Amunts

This lecture gives an introduction to the European Academy of Neurology, its recent achievements and ambitions.

Difficulty level: Intermediate

Duration: 21:57

Speaker: : Paul Boon

Course:

This lesson describes the principles underlying functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), tractography, and parcellation. These tools and concepts are explained in a broader context of neural connectivity and mental health.

Difficulty level: Intermediate

Duration: 1:47:22

Speaker: : Erin Dickie and John Griffiths

Course:

This tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices.

Difficulty level: Intermediate

Duration: 1:39:04

Speaker: : Erin Dickie and John Griffiths

This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment.

This lesson corresponds to slides 1-64 in the PDF below.

Difficulty level: Intermediate

Duration: 1:28:14

Speaker: : Andreea Diaconescu

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

This lesson corresponds to slides 65-90 of the PDF below.

Difficulty level: Intermediate

Duration: 1:15:04

Speaker: : Daniel Hauke

Course:

This lesson provides an introduction to modeling single neurons, as well as stability analysis of neural models.

Difficulty level: Intermediate

Duration: 1:26:06

Speaker: : Bard Ermentrout

Course:

This lesson continues a thorough description of the concepts, theories, and methods involved in the modeling of single neurons.

Difficulty level: Intermediate

Duration: 1:25:38

Speaker: : Bard Ermentrout

Course:

In this lesson you will learn about fundamental neural phenomena such as oscillations and bursting, and the effects these have on cortical networks.

Difficulty level: Intermediate

Duration: 1:24:30

Speaker: : Bard Ermentrout

Course:

This lesson continues discussing properties of neural oscillations and networks.

Difficulty level: Intermediate

Duration: 1:31:57

Speaker: : Bard Ermentrout

Course:

In this lecture, you will learn about rules governing coupled oscillators, neural synchrony in networks, and theoretical assumptions underlying current understanding.

Difficulty level: Intermediate

Duration: 1:26:02

Speaker: : Bard Ermentrout

Course:

This lesson provides a continued discussion and characterization of coupled oscillators.

Difficulty level: Intermediate

Duration: 1:24:44

Speaker: : Bard Ermentrout

- Clinical neuroinformatics (13)
- Bayesian networks (3)
- Brain-computer interface (1)
- Digital brain atlasing (5)
- Neuroimaging (22)
- EBRAINS RI (6)
- Machine learning (1)
- Neuromorphic engineering (2)
- Ontologies (1)
- Standards and best practices (15)
- Tools (12)
- Workflows (1)
- Clinical neuroscience (22)
- General neuroscience (6)
- (-) Computational neuroscience (72)
- Statistics (3)
- Computer Science (4)
- Genomics (8)
- Data science
(9)
- Open science (5)
- Education (1)
- Neuroethics (5)