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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 lesson discusses FAIR principles and methods currently in development for assessing FAIRness.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

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

This lesson provides an overview of Neurodata Without Borders (NWB), an ecosystem for neurophysiology data standardization. The lecture also introduces some NWB-enabled tools. 

Difficulty level: Beginner
Duration: 29:53
Speaker: : Oliver Ruebel

This lecture provides an introduction to Plato’s concept of rationality and Aristotle’s concept of empiricism, and the enduring discussion between rationalism and empiricism to this day.

Difficulty level: Beginner
Duration: 1:13:45

This lecture goes into further detail about the hard problem of developing a scientific discipline for subjective consciousness.

Difficulty level: Beginner
Duration: 58:03

This opening lecture from INCF's Short Course in Neuroinformatics provides an overview of the field of neuroinformatics itself, as well as laying out an argument for the necessity for developing more sophisticated approaches towards FAIR data management principles in neuroscience. 

Difficulty level: Beginner
Duration: 1:19:14
Speaker: : Maryann Martone

This lesson provides a thorough description of neuroimaging development over time, both conceptually and technologically. You will learn about the fundamentals of imaging techniques such as MRI and PET, as well as how the resultant data may be used to generate novel data visualization schemas. 

Difficulty level: Beginner
Duration: 1:43:57
Speaker: : Jack Van Horn

This lesson contains the first part of the lecture Data Science and Reproducibility. You will learn about the development of data science and what the term currently encompasses, as well as how neuroscience and data science intersect. 

Difficulty level: Beginner
Duration: 32:18
Speaker: : Ariel Rokem

This lesson gives a brief introduction to the course Neuroscience for Machine Learners (Neuro4ML). 

Difficulty level: Beginner
Duration: 1:25
Speaker: : Dan Goodman

This lesson covers the history of neuroscience and machine learning, and the story of how these two seemingly disparate fields are increasingly merging. 

Difficulty level: Beginner
Duration: 12:25
Speaker: : Dan Goodman

In this lesson, you will learn about the current challenges facing the integration of machine learning and neuroscience. 

Difficulty level: Beginner
Duration: 5:42
Speaker: : Dan Goodman

This module explores sensation in the brain: what organs are involved, sensory pathways, processing centers, and theories of integration.

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.

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

This lesson provides an overview of 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.

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

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

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

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

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