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. 

This lesson introduces the practical exercises which accompany the previous lessons on animal and human connectomes in the brain and nervous system. 

This lecture and tutorial focuses on measuring human functional brain networks, as well as how to account for inherent variability within those networks. 

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.

This lecture covers the ethical implications of the use of brain-computer interfaces, brain-machine interfaces, and deep brain stimulation to enhance brain functions and was part of the Neuro Day Workshop held by the NeuroSchool of Aix Marseille University.

This module covers many types of invasive neurotechnology devices/interfaces for the central and peripheral nervous systems. Invasive neurotech devices are crucial, as they often provide the greatest accuracy and long-term use applicability.

This short talk addresses how to use VisuAlign to make nonlinear adjustments to 2D-to-3D registrations generated by QuickNII. 

This talk aims to provide guidance regarding the myriad labelling methods for histological image data. 

This lesson provides a cross-species comparison of neuron types in the rat and mouse brain. 

This lecture concludes the course with an outline of future directions of the field of neuroscientific research data integration. 

This is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics. 

This lesson is an overview of transcriptomics, from fundamental concepts of the central dogma and RNA sequencing at the single-cell level, to how genetic expression underlies diversity in cell phenotypes. 

In this lesson, you will learn about data management within the Open Data Commons (ODC) framework, and in particular, how Spinal Cord Injury (SCI) data is stored, shared, and published. You will also hear about Frictionless Data, an open-source toolkit aimed at simplifying the data experience. 

This talk describes the NIH-funded SPARC Data Structure, and how this project navigates ontology development while keeping in mind the FAIR science principles. 

This talk goes over Neurobagel, an open-source platform developed for improved dataset sharing and searching. 

This video gives a brief introduction to the second session of talks from INCF's Neuroinformatics Assembly 2023. 

This brief video provides an introduction to the third session of INCF's Neuroinformatics Assembly 2023, focusing on how to streamling cross-platform data integration in a neuroscientific context. 

In this talk, you will learn about the standardization schema for data formats among two of the US BRAIN Initiative networks: the Cell Census Network (BICCN) and the Cell Atlas Network (BICAN). 

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.