Feeding the human brain model

TL;DR

This paper discusses the challenges and necessary neuroinformatics techniques for integrating diverse, incomplete experimental data across multiple scales to enable comprehensive human brain modeling within the Human Brain Project.

Contribution

It reviews new neuroinformatics methods essential for integrating heterogeneous brain data to support large-scale human brain simulation.

Findings

Identification of key data integration challenges

Proposal of neuroinformatics techniques for data harmonization

Highlighting the importance of scalable data infrastructure

Abstract

The goal of the Human Brain Project is to develop during the next decade an infrastructure necessary for running a simulation of the entire human brain constrained by current experimental data. One of the key issues is therefore to integrate and make accessible the experimental data necessary to constrain and fully specify this model. The required data covers many different spatial scales, ranging from the molecular scale to the whole brain and these data are obtained using a variety of techniques whose measurements may not be directly comparable. Furthermore, these data are incomplete, and will remain so at least for the coming decade. Here we review new neuroinformatics techniques that need to be developed and applied to address these issues.