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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

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

This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.

Difficulty level: Beginner
Duration: 2:24:35

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 lesson is part 1 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner
Duration: 1:45:48
Speaker: : Jonathan Pillow

What is the difference between attention and consciousness? This lecture describes the scientific meaning of consciousness, journeys on the search for neural correlates of visual consciousness, and explores the possibility of consciousness in other beings and even non-biological structures.

Difficulty level: Beginner
Duration: 1:10:01
Speaker: : Christof Koch

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

This talk enumerates the challenges regarding data accessibility and reusability inherent in the current scientific publication system, and discusses novel approaches to these challenges, such as the EBRAINS Live Papers platform. 

Difficulty level: Beginner
Duration: 18:08
Speaker: : Andrew Davison

This lesson aims to define computational neuroscience in general terms, while providing specific examples of highly successful computational neuroscience projects. 

Difficulty level: Beginner
Duration: 59:21
Speaker: : Alla Borisyuk

This lesson covers membrane potential of neurons, and how parameters around this potential have direct consequences on cellular communication at both the individual and population level. 

Difficulty level: Beginner
Duration: 28:08
Speaker: : Carl Petersen

In this lesson you will learn about neurons' ability to generate signals called action potentials, and biophysics of voltage-gated ion channels.

Difficulty level: Beginner
Duration: 27:47
Speaker: : Carl Petersen

This lesson discusses voltage-gating kinetics of sodium and potassium channels.

Difficulty level: Beginner
Duration: 19:20
Speaker: : Carl Petersen

In this lesson, you will learn about the ionic basis of the action potential, including the Hodgkin-Huxley model.

Difficulty level: Beginner
Duration: 28:29
Speaker: : Carl Petersen

This lesson delves into the specifics of how action potentials propagate through individual neurons.

Difficulty level: Beginner
Duration: 23:16
Speaker: : Carl Petersen

This lesson discusses long-range inhibitory connections in the brain, with examples from three different systems.

Difficulty level: Beginner
Duration: 19:05
Speaker: : Carl Petersen
Course:

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

 

Difficulty level: Beginner
Duration: 1:09:16
Speaker: : Aaron J. Newman

This lesson is a general overview of overarching concepts in neuroinformatics research, with a particular focus on clinical approaches to defining, measuring, studying, diagnosing, and treating various brain disorders. Also described are the complex, multi-level nature of brain disorders and the data associated with them, from genes and individual cells up to cortical microcircuits and whole-brain network dynamics. Given the heterogeneity of brain disorders and their underlying mechanisms, this lesson lays out a case for multiscale neuroscience data integration.

Difficulty level: Intermediate
Duration: 1:09:33
Speaker: : Sean Hill

This tutorial demonstrates how to perform cell-type deconvolution in order to estimate how proportions of cell-types in the brain change in response to various conditions. While these techniques may be useful in addressing a wide range of scientific questions, this tutorial will focus on the cellular changes associated with major depression (MDD). 

Difficulty level: Intermediate
Duration: 1:15:14
Speaker: : Keon Arbabi

This lesson explains the fundamental principles of neuronal communication, such as neuronal spiking, membrane potentials, and cellular excitability, and how these electrophysiological features of the brain may be modelled and simulated digitally. 

Difficulty level: Intermediate
Duration: 1:20:42
Speaker: : Etay Hay