LinkRbrain: Multi-scale data integrator of the brain

Salma Mesmoudi (1) , Mathieu Rodic , Claudia Cioli (2) , Jean-Philippe Cointet (3) , Tal Yarkoni (4) , Yves Burnod (2)

1 UP1 - Université Paris 1 Panthéon-Sorbonne
2 LIB - Laboratoire d'Imagerie Biomédicale [Paris]
3 SenS - Sciences en Société
4 Department of Psychology

Background LinkRbrain is an open-access web platform for multi-scale data integration and visualization of human brain data. This platform integrates anatomical, functional, and genetic knowledge produced by the scientific community. New method The linkRbrain platform has two major components: (1) a data aggregation component that integrates multiple open databases into a single platform with a unified representation; and (2) a website that provides fast multi-scale integration and visualization of these data and makes the results immediately available. Results LinkRbrain allows users to visualize functional networks or/and genetic expression over a standard brain template (MNI152). Interrelationships between these components based on topographical overlap are displayed using relational graphs. Moreover, linkRbrain enables comparison of new experimental results with previous published works. Comparison with existing methods Previous tools and studies illustrate the opportunities of data mining across multiple tiers of neuroscience and genetic information. However, a global systematic approach is still missing to gather cognitive, topographical, and genetic knowledge in a common framework in order to facilitate their visualization, comparison, and integration. Conclusions LinkRbrain is an efficient open-access tool that affords an integrative understanding of human brain function.

Keywords: Platform; Multi-scale; Open databases; Genetics; Integrative; Anatomo-functional; Complex systems

Domains: Neurons and Cognition [q-bio.NC]

Salma Mesmoudi, Mathieu Rodic, Claudia Cioli, Jean-Philippe Cointet, Tal Yarkoni, et al.. LinkRbrain: Multi-scale data integrator of the brain. Journal of Neuroscience Methods, 2015, 241, pp.44 - 52. ⟨10.1016/j.jneumeth.2014.12.008⟩. ⟨hal-01110246⟩