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The Allen Mouse Brain Atlas is a genome-wide, high-resolution atlas of gene expression throughout the adult mouse brain. This tutorial describes the basic search and navigation features of the Allen Mouse Brain Atlas.

Difficulty level: Beginner
Duration: 6:40

The Allen Developing Mouse Brain Atlas is a detailed atlas of gene expression across mouse brain development. This tutorial describes the basic search and navigation features of the Allen Developing Mouse Brain Atlas.

Difficulty level: Beginner
Duration: 6:35
Speaker: : Unknown

This tutorial demonstrates how to use the differential search feature of the Allen Mouse Brain Atlas to find gene markers for different regions of the brain, as well as to visualize this gene expression in three-dimensional space. Differential search is also available for the Allen Developing Mouse Brain Atlas and the Allen Human Brain Atlas.

Difficulty level: Beginner
Duration: 6:31
Speaker: : Unknown
Course:

The Mouse Phenome Database (MPD) provides access to primary experimental trait data, genotypic variation, protocols and analysis tools for mouse genetic studies. Data are contributed by investigators worldwide and represent a broad scope of phenotyping endpoints and disease-related traits in naïve mice and those exposed to drugs, environmental agents or other treatments. MPD ensures rigorous curation of phenotype data and supporting documentation using relevant ontologies and controlled vocabularies. As a repository of curated and integrated data, MPD provides a means to access/re-use baseline data, as well as allows users to identify sensitized backgrounds for making new mouse models with genome editing technologies, analyze trait co-inheritance, benchmark assays in their own laboratories, and many other research applications. MPD’s primary source of funding is NIDA. For this reason, a majority of MPD data is neuro- and behavior-related.

Difficulty level: Beginner
Duration: 55:36
Speaker: : Elissa Chesler

This lesson provides a demonstration of GeneWeaver, a system for the integration and analysis of heterogeneous functional genomics data.

Difficulty level: Beginner
Duration: 25:53
Speaker: :

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 lecture and tutorial focuses on measuring human functional brain networks, as well as how to account for inherent variability within those networks. 

Difficulty level: Intermediate
Duration: 50:44
Speaker: : Caterina Gratton

This lecture presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.

Difficulty level: Advanced
Duration: 50:28
Speaker: : Pierre Bellec
Course:

Neuronify is an educational tool meant to create intuition for how neurons and neural networks behave. You can use it to combine neurons with different connections, just like the ones we have in our brain, and explore how changes on single cells lead to behavioral changes in important networks. Neuronify is based on an integrate-and-fire model of neurons. This is one of the simplest models of neurons that exist. It focuses on the spike timing of a neuron and ignores the details of the action potential dynamics. These neurons are modeled as simple RC circuits. When the membrane potential is above a certain threshold, a spike is generated and the voltage is reset to its resting potential. This spike then signals other neurons through its synapses.

Neuronify aims to provide a low entry point to simulation-based neuroscience.

Difficulty level: Beginner
Duration: 01:25
Speaker: : Neuronify

This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and goes through both the motivations and processes involved in moving your research computing to the cloud.

Difficulty level: Intermediate
Duration: 3:09:12

As a part of NeuroHackademy 2020, this lecture delves into cloud computing, focusing on Amazon Web Services. 

Difficulty level: Beginner
Duration: 01:43:59

This talk presents an overview of CBRAIN, a web-based platform that allows neuroscientists to perform computationally intensive data analyses by connecting them to high-performance computing facilities across Canada and around the world.

Difficulty level: Beginner
Duration: 56:07
Speaker: : Shawn Brown

Overview of Day 2 of this course.

Difficulty level: Beginner
Duration: 00:03:28
Speaker: : Tristan Shuman

This talk compares various sensors and resolutions for in vivo neural recordings.

Difficulty level: Beginner
Duration: 00:24:03

This lecture introduces neuroscience concepts and methods such as fMRI, visual respones in BOLD data, and the eccentricity of visual receptive fields. 

Difficulty level: Intermediate
Duration: 7:15
Speaker: : Mike X. Cohen

This tutorial walks users through the creation and visualization of activation flat maps from fMRI datasets. 

Difficulty level: Intermediate
Duration: 12:15
Speaker: : Mike X. Cohen

This tutorial demonstrates to users the conventional preprocessing steps when working with BOLD signal datasets from fMRI. 

Difficulty level: Intermediate
Duration: 12:05
Speaker: : Mike X. Cohen

In this tutorial, users will learn how to create a trial-averaged BOLD response and store it in a matrix in MATLAB. 

Difficulty level: Intermediate
Duration: 20:12
Speaker: : Mike X. Cohen

This tutorial teaches users how to create animations of BOLD responses over time, to allow researchers and clinicians to visualize time-course activity patterns.

Difficulty level: Intermediate
Duration: 12:52
Speaker: : Mike X. Cohen

This tutorial demonstrates how to use MATLAB to create event-related BOLD time courses from fMRI datasets. 

Difficulty level: Intermediate
Duration: 13:39
Speaker: : Mike X. Cohen