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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

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

Learn how to create a standard extracellular electrophysiology dataset in NWB using Python

Difficulty level: Intermediate
Duration: 45:46
Speaker: : Ryan Ly

Learn how to create a standard calcium imaging dataset in NWB using Python

Difficulty level: Intermediate
Duration: 31:04
Speaker: : Ryan Ly

Learn how to create a standard intracellular electrophysiology dataset in NWB

Difficulty level: Intermediate
Duration: 20:23
Speaker: : Pamela Baker

Learn how to use the icephys-metadata extension to enter meta-data detailing your experimental paradigm

Difficulty level: Intermediate
Duration: 27:18
Speaker: : Oliver Ruebel

Learn how to create a standard extracellular electrophysiology dataset in NWB using MATLAB

Difficulty level: Intermediate
Duration: 45:46
Speaker: : Ben Dichter

Learn how to create a standard calcium imaging dataset in NWB using MATLAB

Difficulty level: Intermediate
Duration: 39:10
Speaker: : Ben Dichter

Learn how to create a standard intracellular electrophysiology dataset in NWB

Difficulty level: Intermediate
Duration: 20:22
Speaker: : Pamela Baker

Overview of the Braintorm package for analyzing extracellular electrophysiology, including preprocessing, spike sorting, trial alignment, and spectrotemporal decomposition

Difficulty level: Intermediate
Duration: 47:47

Overview of the CaImAn package, and demonstration of usage with NWB

Difficulty level: Intermediate
Duration: 44:37

Overview of the SpikeInterface package, including demonstration of data loading, preprocessing, spike sorting, and comparison of spike sorters

Difficulty level: Intermediate
Duration: 1:10:28
Speaker: : Alessio Buccino

Overview of the NWBWidgets package, including coverage of different data types, and information for building custom widgets within this framework

Difficulty level: Intermediate
Duration: 47:15
Speaker: : Ben Dichter

This lecture 1/15 is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate
Duration: 0:40

This lecture (2/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate
Duration: 1:23


This lecture (3/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate
Duration: 1:20

This lecture (4/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate
Duration: 1:08

This lecture (5/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate
Duration: 1:18

This lecture (6/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures. Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate
Duration: 1:26

This lecture (7/15) is part of the Computational Modeling of Neuronal Plasticity Course that aims to teach users how to build a mathematical model of a neuron, its inputs, and its neuronal plasticity mechanisms, by writing your own Python program. This lecture provides users with a brief video introduction to the concepts that serves as a companion to the lecture notes and solution figures.

Authors: Florence I. Kleberg and Prof. Jochen Triesch.

Difficulty level: Intermediate
Duration: 0:42