title: Logic as Marr's Computational Level: Four Case Studies.
abstract: We sketch four applications of Marr's levels-of-analysis methodology to the relations between logic and experimental data in the cognitive neuroscience of language and reasoning. The first part of the paper illustrates the explanatory power of computational level theories based on logic. We show that a Bayesian treatment of the suppression task in reasoning with conditionals is ruled out by EEG data, supporting instead an analysis based on defeasible logic. Further, we describe how results from an EEG study on temporal prepositions can be reanalyzed using formal semantics, addressing a potential confound. The second part of the article demonstrates the predictive power of logical theories drawing on EEG data on processing progressive constructions and on behavioral data on conditional reasoning in people with autism. Logical theories can constrain processing hypotheses all the way down to neurophysiology, and conversely neuroscience data can guide the selection of alternative computational level models of cognition.
authors.affiliation: Brain and Language Laboratory, Neuroscience Area, SISSA International School for Advanced Studies; Language Acquisition and Language Processing Lab, Department of Language and Literature, Norwegian University of Science and Technology.
authors.forename: Giosuè
authors.initials: G
authors.lastname: Baggio
authors.forename: Michiel
authors.initials: M
authors.lastname: van Lambalgen
authors.forename: Peter
authors.initials: P
authors.lastname: Hagoort
mesh_terms: D001321:Autistic Disorder / Q000503:physiopathology*; D000066494:Cognitive Neuroscience / Q000379:methods*; D056344:Executive Function / Q000502:physiology*; D006801:Humans; D008128:Logic; D008962:Models, Theoretical; D012660:Semantics; D013850:Thinking / Q000502:physiology*
keywords: Cognitive neuroscience; EEG; Language; Logic; Reasoning; Semantics