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Neuroscience Data Integration Through Use of Digital Brain Atlases

Level
Beginner

Understanding how the brain works is one of the grand challenges in science and requires the integration of huge amounts of heterogeneous and complex data. Numerous research publications present experimental data at various levels of granularity and describe a wide range of structural and functional aspects of the brain. The management of this deluge of data represents a bottleneck for progress, with a main challenge being that the multiple data categories are difficult to compare. In this context, reference atlases of the brain are important tools for assigning anatomical location and (semi-)automatically analyzing data captured with the many methods and instruments used to study the brain. Reference atlases for the brain rank among the most frequently used and highest cited publications in neuroscience. But integration of data through the use of conventional reference atlases has been difficult to achieve.

With a new generation of three-dimensional digital reference atlases, new solutions for integrating and disseminating brain data are being developed. In many ways, future digital reference atlases and the data systems that will be built around them will be similar to current geographical atlases, such as Google Maps and Google Earth, which provide interactive access to huge amounts of high resolution image data, together with additional information (annotations, practical information, photographs) and more detailed visualizations (e.g. "street view") for specific areas. Digital brain atlases play an important role in several large international projects, including the European Union ICT Future Emerging Technologies Flagship project, the Human Brain Project.This course contains an introduction to currently available reference atlases for mouse and rat brain. It will demonstrate how the 3D brain templates for the reference atlases are acquired, how they are used as a basis for delineating the structures of the brain, how they can be enriched by other data modalities, and how they can be used as a basis for assigning location (coordinate based or semantic) to a wide range of structural and functional data collected from the brain. The course will also outline examples of data system employed to organize neuroscience data collections in the context of reference atlases as well as analytical workflows applied to the data, with opportunities for hands-on exploration of selected tools.

Read more about how digital brain atlases are used in the EBRAINS infrastructure at https://ebrains.eu/services/atlases

Course Features
Lectures
Tutorials
Videos
Code / Datasets
Lessons of this Course
1
1
Duration:
14:02

This lesson provides an introduction to the course Neuroscience Data Integration Through Use of Digital Brain Atlases. 

 

 

2
2
Duration:
30:39

Neuroscience data integration through use of digital brain atlases - Concepts for sharing and integration of Neuroscience Research Data

 

 

3
3
Duration:
51:30

Neuroscience data integration through use of digital brain atlases - Brain anatomy in men and mice

Speaker: Nicola Palomero-Gallagher

 

4
4
Duration:
27:45

Neuroscience data integration through use of digital brain atlases - Introduction to EBRAINS atlas services

Speaker: Trygve Brauns Leergaard

 

5
5
Duration:
32:18

Neuroscience data integration through use of digital brain atlases - Assigning location parameters to experimental data

 

 

6
6
Duration:
25:41

Data integration: WHY, WHAT, HOW?

 

 

7
7
Duration:
21:08

The QuickNII approach: mapping customized atlas plates onto serial image data

 

 

8
8
Duration:
17:30
Speaker:

DeepSlice: using deep learning for histology to atlas registration

 

 

9
9
Duration:
08:50

Refining linear atlas registration

 

 

10
11
Duration:
35:20
Speaker:

Approaches to quantifying labelling in images, finding a way through the jungle of methods

 

 

11
12
Duration:
17:16

Quantitative analysis of calbindin and parvalbumin positive neurons across the rat and mouse brain

 

 

12
13
Duration:
09:49

Visions for neuroscience data integration in the future