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 and 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.
The chair of the workshop is giving an introduction and a motivating argument.
Since their introduction in 2016, the FAIR data principles have gained increasing recognition and adoption in global neuroscience. FAIR defines a set of high-level principles and practices for making digital objects, including data, software, and workflows, Findable, Accessible, Interoperable, and Reusable. But FAIR is not a specification; it leaves many of the specifics up to individual scientific disciplines to define. INCF has been leading the way in promoting, defining, and implementing FAIR data practices for neuroscience. We have been bringing together researchers, infrastructure providers, industry, and publishers through our programs and networks. In this session, we will hear some perspectives on FAIR neuroscience from some of these stakeholders who have been working to develop and use FAIR tools for neuroscience. We will engage in a discussion on questions such as: how is neuroscience doing with respect to FAIR? What have been the successes? What is currently very difficult? Where does neuroscience need to go?
This lecture covers FAIR atlases, from their background, their construction, and how they can be created in line with the FAIR principles.
This lesson introduces concepts and practices surrounding reference atlases for the mouse and rat brains. Additionally, this lesson provides discussion around examples of data systems employed to organize neuroscience data collections in the context of reference atlases as well as analytical workflows applied to the data.
Enabling multi scale data integration: Turning data to knowledge - EBRAINS Research Infrastructure
Enabling multi scale data integration: Turning data to knowledge - Integrating multimodal data in a unifying brain model
Enabling multi scale data integration: Turning data to knowledge - Multi-scale co-simulation of a brain model
Enabling multi-scale data integration: Turning data to knowledge - Tools and services for research data management in neuroscience
Enabling multi-scale data integration: Turning data to knowledge - Research Data Management, Hosting, and Sharing
This lesson provides an introduction to the course Neuroscience Data Integration Through Use of Digital Brain Atlases.
Neuroscience data integration through use of digital brain atlases - Concepts for sharing and integration of Neuroscience Research Data
Neuroscience data integration through use of digital brain atlases - Brain anatomy in men and mice
Speaker: Nicola Palomero-Gallagher
Neuroscience data integration through use of digital brain atlases - Introduction to EBRAINS atlas services
Speaker: Trygve Brauns Leergaard
Neuroscience data integration through use of digital brain atlases - Assigning location parameters to experimental data
Data integration: WHY, WHAT, HOW?
The QuickNII approach: mapping customized atlas plates onto serial image data
DeepSlice: using deep learning for histology to atlas registration
Overview of the content for Day 1 of this course.
Overview of Day 2 of this course.
Best practices: the tips and tricks on how to get your Miniscope to work and how to get your experiments off the ground.