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This presentation discusses the impact of data sharing in stroke.

Difficulty level: Intermediate
Duration: 16:33
Speaker: : Valeria Caso

This talks presents an overview of the potential for data federation in stroke research.

Difficulty level: Intermediate
Duration: 21:37
Course:

This talk focuses on the EAN Scientific Panel of Stroke, in particular on the aims and roles of the panel.

Difficulty level: Intermediate
Duration: 18:19
Speaker: : Anna Bersano

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

In this tutorial on simulating whole-brain activity using Python, participants can follow along using corresponding code and repositories, learning the basics of neural oscillatory dynamics, evoked responses and EEG signals, ultimately leading to the design of a network model of whole-brain anatomical connectivity. 

Difficulty level: Intermediate
Duration: 1:16:10
Speaker: : 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

This lecture and tutorial focuses on measuring human functional brain networks. The lecture and tutorial were 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: Intermediate
Duration: 50:44
Speaker: : Caterina Gratton

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and go through both motivation and process involved in moving your research computing to the cloud. 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: Intermediate
Duration: 3:09:12
Speaker: : Amanda Tan

Introduction to stability analysis of neural models

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout

Introduction to stability analysis of neural models

Difficulty level: Intermediate
Duration: 1:25:38
Speaker: : Bard Ermentrout

Oscillations and bursting

Difficulty level: Intermediate
Duration: 1:24:30
Speaker: : Bard Ermentrout

Oscillations and bursting

Difficulty level: Intermediate
Duration: 1:31:57
Speaker: : Bard Ermentrout

Weakly coupled oscillators

Difficulty level: Intermediate
Duration: 1:26:02
Speaker: : Bard Ermentrout

Continuation of coupled oscillators

Difficulty level: Intermediate
Duration: 1:24:44
Speaker: : Bard Ermentrout

Firing rate models.

Difficulty level: Intermediate
Duration: 1:26:42
Speaker: : Bard Ermentrout

Pattern generation in visual system hallucinations.

Difficulty level: Intermediate
Duration: 1:20:42
Speaker: : Bard Ermentrout

Introduction to stability analysis of neural models

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout

Introduction to stability analysis of neural models

Difficulty level: Intermediate
Duration: 1:25:38
Speaker: : Bard Ermentrout

Oscillations and bursting

Difficulty level: Intermediate
Duration: 1:24:30
Speaker: : Bard Ermentrout

Oscillations and bursting

Difficulty level: Intermediate
Duration: 1:31:57
Speaker: : Bard Ermentrout