FN400 amplitudes reveal the differentiation of semantic inferences within natural vs. artificial domains

Category-based inferences allow inductions about novel properties based on categorical memberships (e.g., knowing all trout have genes [premise] allows us to infer that all fish have genes [conclusion]). Natural (N) and artificial (A) domains are the most obvious and traditional distinctions in categorization. The distinct event-related potential (ERP) responses for N and A domains have not yet been examined during category-based inferences. In this study, the differences between ERP inference parameters within N and A domains were measured during inductive decision processing, while controlling the premise−conclusion similarity and premise typicality between those two domains. Twenty-two adults were asked to make a decision on whether a conclusion was definitely weak, possibly weak, possibly strong, or definitely strong, based on a premise. The behavioral results showed that semantic inferences within the N domain shared similar inductive strength, similar “correct” response rates, and similar reaction times with that within the A domain. However, the ERP results showed that semantic inferences elicited smaller frontal-distributed N400 (FN400) amplitudes within the N domain than within the A domain, which suggested that knowledge of the ontological domain of a category affects category-based inferences, and underlaid the increased categorical coherence and homogeneity in the N as compared to the A categories. Therefore, we have distinguished the cognitive course of semantic inferences between N and A domains.