Course:

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

Course:

In this tutorial, users learn how to compute and visualize a t-test on experimental condition differences.

Difficulty level: Intermediate

Duration: 17:54

Speaker: : Mike X. Cohen

Course:

This lesson introduces various methods in MATLAB useful for dealing with data generated by calcium imaging.

Difficulty level: Intermediate

Duration: 5:02

Speaker: : Mike X. Cohen

Course:

This tutorial demonstrates how to use MATLAB to generate and visualize animations of calcium fluctuations over time.

Difficulty level: Intermediate

Duration: 15:01

Speaker: : Mike X. Cohen

Course:

This tutorial instructs users how to use MATLAB to programmatically convert data from cells to a matrix.

Difficulty level: Intermediate

Duration: 5:15

Speaker: : Mike X. Cohen

Course:

In this tutorial, users will learn how to identify and remove background noise, or "blur", an important step in isolating cell bodies from image data.

Difficulty level: Intermediate

Duration: 17:08

Speaker: : Mike X. Cohen

Course:

This lesson teaches users how MATLAB can be used to apply image processing techniques to identify cell bodies based on contiguity.

Difficulty level: Intermediate

Duration: 11:23

Speaker: : Mike X. Cohen

Course:

This tutorial demonstrates how to extract the time course of calcium activity from each clusters of neuron somata, and store the data in a MATLAB matrix.

Difficulty level: Intermediate

Duration: 22:41

Speaker: : Mike X. Cohen

Course:

This lesson demonstrates how to use MATLAB to implement a multivariate dimension reduction method, PCA, on time series data.

Difficulty level: Intermediate

Duration: 17:19

Speaker: : Mike X. Cohen

Course:

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

This is the first of two workshops on reproducibility in science, during which participants are introduced to concepts of FAIR and open science. After discussing the definition of and need for FAIR science, participants are walked through tutorials on installing and using Github and Docker, the powerful, open-source tools for versioning and publishing code and software, respectively.

Difficulty level: Intermediate

Duration: 1:20:58

Speaker: : Erin Dickie and Sejal Patel

This is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics.

Difficulty level: Intermediate

Duration: 1:27:18

Speaker: : Dan Felsky

This is a tutorial on using the open-source software PRSice to calculate a set of polygenic risk scores (PRS) for a study sample. Users will also learn how to read PRS into R, visualize distributions, and perform basic association analyses.

Difficulty level: Intermediate

Duration: 1:53:34

Speaker: : Dan Felsky

This is a tutorial introducing participants to the basics of RNA-sequencing data and how to analyze its features using Seurat.

Difficulty level: Intermediate

Duration: 1:19:17

Speaker: : Sonny Chen

Course:

This lesson describes the principles underlying functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), tractography, and parcellation. These tools and concepts are explained in a broader context of neural connectivity and mental health.

Difficulty level: Intermediate

Duration: 1:47:22

Speaker: : Erin Dickie and John Griffiths

Course:

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

Speaker: : Andreea Diaconescu

This lecture provides an introduction to the Brain Imaging Data Structure (BIDS), a standard for organizing human neuroimaging datasets.

Difficulty level: Intermediate

Duration: 56:49

Speaker: : Chris Gorgolewski

This tutorial covers the fundamentals of collaborating with Git and GitHub.

Difficulty level: Intermediate

Duration: 2:15:50

Speaker: : Elizabeth DuPre

Course:

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

- Electroencephalography (EEG) (9)
- Clinical neuroinformatics (4)
- Standards and Best Practices (2)
- Bayesian networks (2)
- (-) Neuroimaging (20)
- Machine learning (1)
- Tools (7)
- Workflows (2)
- Clinical neuroscience (2)
- General neuroscience (5)
- Computational neuroscience (16)
- Statistics (3)
- Computer Science (1)
- Genomics (8)
- Data science (2)
- (-) Open science (4)