Skip to main content

This talk enumerates the challenges regarding data accessibility and reusability inherent in the current scientific publication system, and discusses novel approaches to these challenges, such as the EBRAINS Live Papers platform. 

Difficulty level: Beginner
Duration: 18:08
Speaker: : Andrew Davison

This brief video gives an introduction to the eighth session of INCF's Neuroinformatics Assembly 2023, focusing on FAIR data and the role of academic journals. 

Difficulty level: Beginner
Duration: 5:57
Speaker: : Jan G. Bjaalie

This talk gives an overview of the perspectives and FAIR-aligned policies of the academic journal Public Library of Science, better known as PLOS. This journal is a nonprofit, open access publisher empowering researchers to accelerate progress in science. 

Difficulty level: Beginner
Duration: 11:53

This talk highlights a set of platform technologies, software, and data collections that close and shorten the feedback cycle in research. 

Difficulty level: Beginner
Duration: 57:52
Speaker: : Satrajit Ghosh

This lecture contains an overview of the China-Cuba-Canada neuroinformatics ecosystem for Quantitative Tomographic EEG Analysis (qEEGt).

Difficulty level: Beginner
Duration: 12:56

This is a tutorial on how to simulate neuronal spiking in brain microcircuit models, as well as how to analyze, plot, and visualize the corresponding data. 

Difficulty level: Intermediate
Duration: 1:39:50
Speaker: : Frank Mazza

This video will document the process of running an app on brainlife, from data staging to archiving of the final data outputs.

Difficulty level: Beginner
Duration: 3:43
Speaker: :

This quick video presents some of the various visualizers available on brainlife.io

Difficulty level: Beginner
Duration: 1:11
Speaker: :

This short video shows how a brainlife.io publication can be opened from the Data Deposition page of the journal Nature Scientific Data.

Difficulty level: Beginner
Duration: 2:25
Speaker: :
Course:

An introduction to data management, manipulation, visualization, and analysis for neuroscience. Students will learn scientific programming in Python, and use this to work with example data from areas such as cognitive-behavioral research, single-cell recording, EEG, and structural and functional MRI. Basic signal processing techniques including filtering are covered. The course includes a Jupyter Notebook and video tutorials.

 

Difficulty level: Beginner
Duration: 1:09:16
Speaker: : Aaron J. Newman