Course:

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

Course:

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

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

This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.

Difficulty level: Beginner

Duration: 1:16:04

Speaker: : Erin Dickie and Sejal Patel

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

This is an in-depth guide on EEG signals and their interaction within brain microcircuits. Participants are also shown techniques and software for simulating, analyzing, and visualizing these signals.

Difficulty level: Intermediate

Duration: 1:30:41

Speaker: : Frank Mazza

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

Course:

This demonstration walks through how to import your data into MATLAB.

Difficulty level: Beginner

Duration: 6:10

Speaker: : MATLAB®

Course:

This lesson provides instruction regarding the various factors one must consider when preprocessing data, preparing it for statistical exploration and analyses.

Difficulty level: Beginner

Duration: 15:10

Speaker: : MATLAB®

Course:

This tutorial outlines, step by step, how to perform analysis by group and how to do change-point detection.

Difficulty level: Beginner

Duration: 2:49

Speaker: : MATLAB®

Course:

This tutorial walks through several common methods for visualizing your data in different ways depending on your data type.

Difficulty level: Beginner

Duration: 6:10

Speaker: : MATLAB®

Course:

This tutorial illustrates several ways to approach predictive modeling and machine learning with MATLAB.

Difficulty level: Beginner

Duration: 6:27

Speaker: : MATLAB®

- Bayesian networks (2)
- Cognitive neuroinformatics (1)
- Neuroimaging (15)
- Machine learning (3)
- Neuromorphic engineering (1)
- Standards and best practices (4)
- Tools (1)
- Animal models (1)
- Brain-hardware interfaces (1)
- Repositories and science gateways (1)
- General neuroscience (7)
- Computational neuroscience (21)
- Statistics (4)
- Computer Science (1)
- Genomics (5)
- Data science (10)
- Open science (4)