Brief introduction to Research Resource Identifiers (RRIDs), persistent and unique identifiers for referencing a research resource. 

Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (e.g., antibodies, model organisms, and software projects) in biomedical literature to improve the transparency of research methods.

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

The Allen Mouse Brain Atlas is a genome-wide, high-resolution atlas of gene expression throughout the adult mouse brain. This tutorial describes the basic search and navigation features of the Allen Mouse Brain Atlas.

The Allen Developing Mouse Brain Atlas is a detailed atlas of gene expression across mouse brain development. This tutorial describes the basic search and navigation features of the Allen Developing Mouse Brain Atlas.

This tutorial demonstrates how to use the differential search feature of the Allen Mouse Brain Atlas to find gene markers for different regions of the brain, as well as to visualize this gene expression in three-dimensional space. Differential search is also available for the Allen Developing Mouse Brain Atlas and the Allen Human Brain Atlas.

Longitudinal Online Research and Imaging System (LORIS) is a web-based data and project management software for neuroimaging research studies. It is an open source framework for storing and processing behavioural, clinical, neuroimaging and genetic data. LORIS also makes it easy to manage large datasets acquired over time in a longitudinal study, or at different locations in a large multi-site study.

In this workshop talk, you will receive a tour of the Code Ocean ScienceOps Platform, a centralized cloud workspace for all teams. 

This talk describes approaches to maintaining integrated workflows and data management schema, taking advantage of the many open source, collaborative platforms already existing.

This video will document how to run a correlation analysis between the gray matter volume of two different structures using the output from brainlife app-freesurfer-stats.

KnowledgeSpace is a community-based encyclopedia that links brain research concepts to data, models, and literature. It provides users with access to anatomy, gene expression, models, morphology, and physiology data from over 15 different neuroscience data/model repositories, such as Allen Institute for Brain Science and the Human Brain Project.

This lesson outlines NeuroMorpho.org, a centrally curated inventory of digitally reconstructed neurons, which contrains contributions from dozens of laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. 

This module explores sensation in the brain: what organs are involved, sensory pathways, processing centers, and theories of integration.

This module covers how the brain interacts with the world through motor movements. Motor movements underlie so much of our functioning, our speech, the opening and closing of our eyes, and the beating of our hearts.

This lesson provides an overview of the structure and function of the neuron, its components and mechanisms, action potentials, and the many glial cells that support it.

This module explains how neurons come together to create the networks that give rise to our thoughts. The totality of our neurons and their connection is called our connectome. Learn how this connectome changes as we learn, and computes information.

This lesson provides an introduction to the DataLad, a free and open source distributed data management system that keeps track of your data, creates structure, ensures reproducibility, supports collaboration, and integrates with widely used data infrastructure.

This lesson introduces several open science tools like Docker and Apptainer which can be used to develop portable and reproducible software environments. 

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks. 

This lecture provides a detailed description of how to incorporate HED annotation into your neuroimaging data pipeline.