This lecture covers different perspectives on the study of the mental, focusing on the difference between Mind and Brain.
This lecture focuses on where and how Jupyter notebooks can be used most effectively for education.
JupyterHub is a simple, highly extensible, multi-user system for managing per-user Jupyter Notebook servers, designed for research groups or classes. This lecture covers deploying JupyterHub on a single server, as well as deploying with Docker using GitHub for authentication.
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.
This lesson introduces the practical usage of The Virtual Brain (TVB) in its graphical user interface and via python scripts. In the graphical user interface, you are guided through its data repository, simulator, phase plane exploration tool, connectivity editor, stimulus generator, and the provided analyses. The implemented iPython notebooks of TVB are presented, and since they are public, can be used for further exploration of TVB.
This lesson provides a brief overview of the Python programming language, with an emphasis on tools relevant to data scientists.
This lesson provides a comprehensive introduction to the command line and 50 popular Linux commands. This is a long introduction (nearly 5 hours), but well worth it if you are going to spend a good part of your career working from a terminal, which is likely if you are interested in flexibility, power, and reproducibility in neuroscience research. This lesson is courtesy of freeCodeCamp.
Overview of Day 2 of this course.
This talk compares various sensors and resolutions for in vivo neural recordings.
This hands-on tutorial explains how to run your own Minion session in the MetaCell cloud using jupityr notebooks.
In this hands-on analysis tutorial, users will mimic a kernel crash and learn the steps to restore inputs in such a case.
This lesson will go through how to extract cells from video that has been cleaned of background noise and motion.
This final hands-on analysis tutorial walks users through the last visualization steps in the cellular data.
This lecture covers infrared LED oblique illumination for studying neuronal circuits in in vitro block-preparations of the spinal cord and brain stem.
This lecture covers the application of diffusion MRI for clinical and preclinical studies.
In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks.
This talk covers the differences between applying HED annotation to fMRI datasets versus other neuroimaging practices, and also introduces an analysis pipeline using HED tags.
This video shows how to use the brainlife.io interface to edit the participants' info file. This file is the ParticipantInfo.json file of the Brain Imaging Data Structure (BIDS).
This quick video presents some of the various visualizers available on brainlife.io
This video demonstrates each required step for preprocessing T1w anatomical data in brainlife.io.