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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

Lecture on functional brain parcellations and a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation which 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: Advanced
Duration: 50:28
Speaker: : Pierre Bellec

This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network. 

Difficulty level: Beginner
Duration: 1:32:17
Speaker: : Shih-Chii Liu

Presentation of a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Difficulty level: Beginner
Duration: 21:15
Speaker: : Tadashi Yamazaki

Presentation of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Difficulty level: Beginner
Duration: 41:57
Speaker: : Giacomo Indiveri

Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

Difficulty level: Beginner
Duration: 20:39
Speaker: : Giacomo Indiveri

The lecture covers a brief introduction to neuromorphic engineering, some of the neuromorphic networks that the speaker has developed, and their potential applications, particularly in machine learning.

Difficulty level: Intermediate
Duration: 19:57

Introduction to the Mathematics chapter of Datalabcc's "Foundations in Data Science" series.

Difficulty level: Beginner
Duration: 2:53
Speaker: : Barton Poulson

Primer on elementary algebra

Difficulty level: Beginner
Duration: 3:03
Speaker: : Barton Poulson

Primer on linear algebra

Difficulty level: Beginner
Duration: 5:38
Speaker: : Barton Poulson

Primer on systems of linear equations

Difficulty level: Beginner
Duration: 5:24
Speaker: : Barton Poulson

Primer on calculus

Difficulty level: Beginner
Duration: 4:17
Speaker: : Barton Poulson

How calculus relates to optimization

Difficulty level: Beginner
Duration: 8:43
Speaker: : Barton Poulson

Big O notation

Difficulty level: Beginner
Duration: 5:19
Speaker: : Barton Poulson

Basics of probability.

Difficulty level: Beginner
Duration: 7:33
Speaker: : Barton Poulson

This lecture covers describing and characterizing an input-output relationship.

Difficulty level: Beginner
Duration: 1:35:33

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

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

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

Difficulty level: Beginner
Duration: 1:50:31
Speaker: : Jonathan Pillow

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