title: Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach.
abstract: We consider the task of inferring causal relations in brain imaging data with latent confounders. Using a priori knowledge that randomized experimental conditions cannot be effects of brain activity, we derive statistical conditions that are sufficient for establishing a causal relation between two neural processes, even in the presence of latent confounders. We provide an algorithm to test these conditions on empirical data, and illustrate its performance on simulated as well as on experimentally recorded EEG data.
authors.affiliation: Empirical Inference Department, Max Planck Institute for Intelligent Systems, Spemannstr. 38, 72076 Tübingen, Germany. Electronic address: moritzgw@tuebingen.mpg.de.
authors.forename: Moritz
authors.initials: M
authors.lastname: Grosse-Wentrup
authors.affiliation: Empirical Inference Department, Max Planck Institute for Intelligent Systems, Spemannstr. 38, 72076 Tübingen, Germany.
authors.forename: Dominik
authors.initials: D
authors.lastname: Janzing
authors.affiliation: Centre for Integrative Neuroscience and MEG Center, Eberhard-Karls Universität Tübingen, Otfried-Müller-Str. 47, 72076 Tübingen, Germany.
authors.forename: Markus
authors.initials: M
authors.lastname: Siegel
authors.affiliation: Empirical Inference Department, Max Planck Institute for Intelligent Systems, Spemannstr. 38, 72076 Tübingen, Germany.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Schölkopf
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000295:instrumentation / Q000379:methods*; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000295:instrumentation / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D058765:Neurofeedback / Q000502:physiology