title: Bayesian inference of structural brain networks.
abstract: Structural brain networks are used to model white-matter connectivity between spatially segregated brain regions. The presence, location and orientation of these white matter tracts can be derived using diffusion-weighted magnetic resonance imaging in combination with probabilistic tractography. Unfortunately, as of yet, none of the existing approaches provide an undisputed way of inferring brain networks from the streamline distributions which tractography produces. State-of-the-art methods rely on an arbitrary threshold or, alternatively, yield weighted results that are difficult to interpret. In this paper, we provide a generative model that explicitly describes how structural brain networks lead to observed streamline distributions. This allows us to draw principled conclusions about brain networks, which we validate using simultaneously acquired resting-state functional MRI data. Inference may be further informed by means of a prior which combines connectivity estimates from multiple subjects. Based on this prior, we obtain networks that significantly improve on the conventional approach.
authors.affiliation: Radboud University Nijmegen, Institute for Computing and Information Sciences, Nijmegen, The Netherlands; Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands. Electronic address: mhinne@cs.ru.nl.
authors.forename: Max
authors.initials: M
authors.lastname: Hinne
authors.affiliation: Radboud University Nijmegen, Institute for Computing and Information Sciences, Nijmegen, The Netherlands.
authors.forename: Tom
authors.initials: T
authors.lastname: Heskes
authors.affiliation: Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
authors.forename: Christian F
authors.initials: CF
authors.lastname: Beckmann
authors.affiliation: Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
authors.forename: Marcel A J
authors.initials: MA
authors.lastname: van Gerven
mesh_terms: D000328:Adult; D001499:Bayes Theorem; D001921:Brain / Q000033:anatomy & histology* / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008297:Male; D009415:Nerve Net / Q000033:anatomy & histology* / Q000502:physiology