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Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain.

Antonio Jimenez-Marin^1,2, Ibai Diez^3,4,5, Asier Erramuzpe^1,6

¹Computational Neuroimaging Lab, Biobizkaia HRI, Barakaldo, Spain.

Scientific Data

|February 29, 2024

Summary

This summary is machine-generated.

This study introduces a new open-access dataset and code for analyzing brain connectivity. It aims to improve understanding of brain function and disorders by linking structural and functional networks with genetic data.

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Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Area of Science:

Neuroscience
Network Neuroscience
Computational Neuroscience

Background:

The human brain is a complex network with interconnected structural and functional components operating across various scales.
Understanding the relationship between these multi-scale connections is crucial for deciphering brain function and neurological disorders.
Current research faces limitations due to the scarcity of integrated repositories linking structural and functional brain networks with transcriptomic data.

Purpose of the Study:

To provide an open-access dataset integrating multi-scale structural and functional brain connectivity matrices.
To offer accompanying code for investigating the interrelations between these connectivity matrices.
To facilitate neuro-genetic association studies using module-level network metrics for enhanced biological interpretation.

Main Methods:

Development of an open-access dataset containing derivative matrices of functional and structural connectivity at multiple scales.
Provision of computational code to enable the analysis of interrelations between structural and functional brain networks.
Integration of modular transcriptomic profiles for comprehensive biological interpretation of network metrics.

Main Results:

An integrated, open-access dataset of multi-scale brain connectivity has been established.
Accessible code is provided to facilitate the analysis of structural and functional network relationships.
Resources for exploring neuro-genetic associations at the module level are available, enhancing biological interpretability.

Conclusions:

The created dataset and tools address the need for integrated resources in network neuroscience.
This contribution is expected to advance research into brain function, disorders, and neuro-genetic associations.
The open-access nature of the data and code promotes further investigation and discovery in the field.