Exploring the variability induced by different configurations in the neuroimaging analytical space

Abstract

In this talk, I will present myself and my starting thesis, entitled “Exploring the variability induced by different configurations in the neuroimaging analytical space”. Neuroimaging is a research field aiming at providing in-vivo measures of the humain brain to better understand its strutures, networks and functions. A large set of softwares, versions, algorithms, parameters, … is available to the neuroimaging researcher to build their analysis pipelines. The lack of ground truth and community consensus on pipeline configuration poses issues of variability, validity and reproducibility in the field. The goal of this thesis is to model this vast analytical space, and explore it to investigate the main sources of variability. For this, we will derives methodologies drawn from the field of software variability engineering.