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Lecture title:

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
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Part 1 of 2 of a tutorial on statistical models for neural data

Difficulty level: Beginner
Duration: 1:45:48
Speaker: : Jonathan Pillow
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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
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A basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.

Difficulty level: Beginner
Duration: 51:49
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How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.

Difficulty level: Beginner
Duration: 1:08:45
Speaker: : Clay Reid
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JupyterHub is a simple, highly extensible, multi-user system for managing per-user Jupyter Notebook servers, designed for research groups or classes. This lecture covers deploying JupyterHub on a single server, as well as deploying with Docker using GitHub for authentication.

Difficulty level: Beginner
Duration: 1:36:27
Speaker: : Thomas Kluyver.
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This talk highlights a set of platform technologies, software, and data collections that close and shorten the feedback cycle in research. 

Difficulty level: Beginner
Duration: 57:52
Speaker: : Satrajit Ghosh
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Difficulty level: Beginner
Duration: 6:10
Speaker: : MATLAB®
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Difficulty level: Beginner
Duration: 15:10
Speaker: : MATLAB®
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Difficulty level: Beginner
Duration: 2:49
Speaker: : MATLAB®
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Difficulty level: Beginner
Duration: 6:10
Speaker: : MATLAB®
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This tutorial illustrates several ways to approach predictive modeling and machine learning with MATLAB.

Difficulty level: Beginner
Duration: 6:27
Speaker: : MATLAB®
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Difficulty level: Beginner
Duration: 3:55
Speaker: : MATLAB®
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Difficulty level: Beginner
Duration: 3:52
Speaker: : MATLAB®
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A brief overview of the Python programming language, with an emphasis on tools relevant to data scientists. 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: Beginner
Duration: 1:16:36
Speaker: : Tal Yarkoni
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Introduction to the FAIR Principles and examples of applications of the FAIR Principles in neuroscience. This lecture was 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: Beginner
Duration: 55:57
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Tutorial on collaborating with Git and GitHub. This tutorial was 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: 2:15:50
Speaker: : Elizabeth DuPre
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Next generation science with Jupyter. This lecture was 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: 50:28
Speaker: : Elizabeth DuPre
Lecture title:

Introduction to reproducible research. The lecture provides an overview of the core skills and practical solutions required to practice reproducible research. 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: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez
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Neuroethics has been described as containing at least two components - the neuroscience of ethics and the ethics of neuroscience. The first involves neuroscientific theories, research, and neuro-imaging focused on how the brain arrives at moral decisions and actions, which challenge existing descriptive theories of how humans develop moral thinking and make ethical decisions. The second, ethics of neuroscience, involves applying normative theories about what is right, good and fair to ethical questions raised by neuroscientific research and new technologies, such as how to balance the public benefit of “big data” neuroscience while protecting individual privacy and norms of informed consent.

Difficulty level: Beginner
Duration: 38:49