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. 

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

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

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

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.

This lecture presents the Medical Informatic Platform's data federation for Traumatic Brain Injury.

This lecture gives insights into the Medical Informatics Platform's current and future data privacy model.

This lecture explains the concept of federated analysis in the context of medical data, associated challenges. The lecture also presents an example of hospital federations via the Medical Informatics Platform.

This talk discusses what are usually considered successful outcomes of scientific research consortia, and how those outcomes can be translated into lasting impacts. 

In this lesson, you will learn about the BRAIN Initiative Cell Atlas Network (BICAN) and how this project adopts a federated approach to data sharing. 

This talks presents an overview of the potential for data federation in stroke research.

This lecture explains the need for data federation in medicine and how it can be achieved.

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. 

This tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices. 

In this lesson, you will learn about the connectome, the collective system of neural pathways in an organism, with a closer look at the neurons, synapses, and connections of particular species. 

This lesson delves into the human nervous system and the immense cellular, connectomic, and functional sophistication therein. 

In this lesson, you will hear about some of the open issues in the field of neuroscience, as well as a discussion about whether neuroscience works, and how can we know?

The "connectome" is a term, coined in the past decade, that has been used to describe more than one phenomenon in neuroscience. This lecture explains the basics of structural connections at the micro-, meso- and macroscopic scales.

This talk covers the Human Connectome Project, which aims to provide an unparalleled compilation of neural data, an interface to graphically navigate this data, and the opportunity to achieve never before realized conclusions about the living human brain.

EyeWire is a game to map the brain. Players are challenged to map branches of a neuron from one side of a cube to the other in a 3D puzzle. Players scroll through the cube and reconstruct neurons with the help of an artificial intelligence algorithm developed at Seung Lab in Princeton University. EyeWire gameplay advances neuroscience by helping researchers discover how neurons connect to process visual information.