title: A short history of causal modeling of fMRI data.
abstract: Twenty years ago, the discovery of the blood oxygen level dependent (BOLD) contrast and invention of functional magnetic resonance imaging (MRI) not only allowed for enhanced analyses of regional brain activity, but also laid the foundation for novel approaches to studying effective connectivity, which is essential for mechanistically interpretable accounts of neuronal systems. Dynamic causal modeling (DCM) and Granger causality (G-causality) modeling have since become the most frequently used techniques for inferring effective connectivity from fMRI data. In this paper, we provide a short historical overview of these approaches, describing milestones of their development from our subjective perspectives.
authors.affiliation: Laboratory for Social and Neural Systems Research, Dept of Economics, University of Zurich, Switzerland. klaasenno.stephan@econ.uzh.ch
authors.forename: Klaas Enno
authors.initials: KE
authors.lastname: Stephan
authors.forename: Alard
authors.initials: A
authors.lastname: Roebroeck
mesh_terms: D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D001931:Brain Mapping / Q000266:history* / Q000379:methods; D049673:History, 20th Century; D049674:History, 21st Century; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000266:history* / Q000379:methods; D008959:Models, Neurological; D008962:Models, Theoretical