title: Causal interpretation rules for encoding and decoding models in neuroimaging.
abstract: Causal terminology is often introduced in the interpretation of encoding and decoding models trained on neuroimaging data. In this article, we investigate which causal statements are warranted and which ones are not supported by empirical evidence. We argue that the distinction between encoding and decoding models is not sufficient for this purpose: relevant features in encoding and decoding models carry a different meaning in stimulus- and in response-based experimental paradigms.We show that only encoding models in the stimulus-based setting support unambiguous causal interpretations. By combining encoding and decoding models trained on the same data, however, we obtain insights into causal relations beyond those that are implied by each individual model type. We illustrate the empirical relevance of our theoretical findings on EEG data recorded during a visuo-motor learning task.
authors.affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany. Electronic address: sweichwald@tuebingen.mpg.de.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Weichwald
authors.affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany. Electronic address: tmeyer@tuebingen.mpg.de.
authors.forename: Timm
authors.initials: T
authors.lastname: Meyer
authors.affiliation: Sabancı University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey. Electronic address: oozdenizci@sabanciuniv.edu.
authors.forename: Ozan
authors.initials: O
authors.lastname: Özdenizci
authors.affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany. Electronic address: bs@tuebingen.mpg.de.
authors.forename: Bernhard
authors.initials: B
authors.lastname: Schölkopf
authors.affiliation: Bernstein Center Freiburg, University of Freiburg, Freiburg, Germany. Electronic address: tonio.ball@uniklinik-freiburg.de.
authors.forename: Tonio
authors.initials: T
authors.lastname: Ball
authors.affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany. Electronic address: moritzgw@tuebingen.mpg.de.
authors.forename: Moritz
authors.initials: M
authors.lastname: Grosse-Wentrup
mesh_terms: D000328:Adult; D000465:Algorithms; D001931:Brain Mapping / Q000379:methods; D015984:Causality; D004569:Electroencephalography; D056228:Feedback, Sensory; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007858:Learning / Q000502:physiology; D008297:Male; D008959:Models, Neurological; D016571:Neural Networks, Computer; D059906:Neuroimaging / Q000379:methods* / Q000706:statistics & numerical data*; D010363:Pattern Recognition, Automated; D011597:Psychomotor Performance / Q000502:physiology; D055815:Young Adult
keywords: Causal inference; Decoding models; Encoding models; Interpretation; Pattern recognition