Course:

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 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

Course:

This tutorial is part 1 of 2. It aims to provide viewers with an understanding of the fundamentals of R tool. Note: parts 1 and 2 of this tutorial are part of the same YouTube video; part 1 ends at 17:42.

Difficulty level: Beginner

Duration: 17:42

Speaker: : Edureka

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®

Course:

This brief tutorial goes over how you can easily work with big data as you would with any size of data.

Difficulty level: Beginner

Duration: 3:55

Speaker: : MATLAB®

Course:

In this tutorial, you will learn how to deploy your models outside of your local MATLAB environment, enabling wider sharing and collaboration.

Difficulty level: Beginner

Duration: 3:52

Speaker: : MATLAB®

Course:

This lesson provides a brief overview of the Python programming language, with an emphasis on tools relevant to data scientists.

Difficulty level: Beginner

Duration: 1:16:36

Speaker: : Tal Yarkoni

Course:

This tutorial teaches users how to use Pandas objects to help store and manipulate various datasets in Python.

Difficulty level: Beginner

Duration: 1:21:40

Speaker: : Tal Yarkoni

Course:

In this lesson, users can follow along as a spaghetti script written in MATLAB is turned into understandable and reusable code living happily in a powerful GitHub repository.

Difficulty level: Beginner

Duration: 2:08:19

Speaker: : Agah Karakuzu

Course:

This lesson gives a quick walkthrough the Tidyverse, an "opinionated" collection of R packages designed for data science, including the use of readr, dplyr, tidyr, and ggplot2.

Difficulty level: Beginner

Duration: 1:01:39

Speaker: : Thomas Mock

Course:

This lesson gives a general introduction to the essentials of navigating through a Bash terminal environment. The lesson is based on the Software Carpentries "Introduction to the Shell" and was given in the context of the BrainHack School 2020.

Difficulty level: Beginner

Duration: 1:12:22

Speaker: : Ross Markello

Course:

This lesson covers Python applications to data analysis, demonstrating why it has become ubiquitous in data science and neuroscience. The lesson was given in the context of the BrainHack School 2020.

Difficulty level: Beginner

Duration: 2:38:45

Speaker: : Ross Markello

This lecture discusses how FAIR practices affect personalized data models, including workflows, challenges, and how to improve these practices.

Difficulty level: Beginner

Duration: 13:16

Speaker: : Kelly Shen

In this talk, you will learn how brainlife.io works, and how it can be applied to neuroscience data.

Difficulty level: Beginner

Duration: 10:14

Speaker: : Franco Pestilli

Course:

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

Difficulty level: Beginner

Duration: 01:43:59

Speaker: : Tara Madhyastha, Andrew Crabb, Ariel Rokem

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