Redefining the resolution of semantic knowledge in the brain: Advances made by the introduction of models of semantics in neuroimaging

Abstract

The boundaries of our understanding of conceptual representation in the brain have been redrawn since the introduction of explicit models of semantics. These models are grounded in vast behavioural datasets acquired in healthy volunteers. Here, we review the most important techniques which have been applied to detect semantic information in neuroimaging data and argue why semantic models are possibly the most valuable addition to the research of semantics in recent years. Using multivariate analysis, predictions based on patient lesion data have been confirmed during semantic processing in healthy controls. Secondly, this new method has given rise to new research avenues, e.g. the detection of semantic processing outside of the temporal cortex. As a future line of work, the same research strategy could be useful to study neurological conditions such as the semantic variant of primary progressive aphasia, which is characterized by pathological semantic processing.

Keywords: Cross-modal representation; Multivariate analysis; Perirhinal cortex; Primary progressive aphasia; Psycho-experimental norms; Regression-based methods; Representational similarity analysis; Semantic models; Text corpora.