Neural representations of the concepts in simple sentences: Concept activation prediction and context effects

Abstract

Although it has been possible to identify individual concepts from a concept’s brain activation pattern, there have been significant obstacles to identifying a proposition from its fMRI signature. Here we demonstrate the ability to decode individual prototype sentences from readers’ brain activation patterns, by using theory-driven regions of interest and semantic properties. It is possible to predict the fMRI brain activation patterns evoked by propositions and words which are entirely new to the model with reliably above-chance rank accuracy. The two core components implemented in the model that reflect the theory were the choice of intermediate semantic features and the brain regions associated with the neurosemantic dimensions. This approach also predicts the neural representation of object nouns across participants, studies, and sentence contexts. Moreover, we find that the neural representation of an agent-verb-object proto-sentence is more accurately characterized by the neural signatures of its components as they occur in a similar context than by the neural signatures of these components as they occur in isolation.

When words burn – language processing differentially modulates pain perception in typical and chronic pain populations

“…On this view, we expected language to modulate the perception of pain evoked by noxious stimulation. Second, in agreement with previous language comprehension literature (Cosentino, Baggio, Kontinen, & Werning, 2017; Just, Wang, & Cherkassky, 2017; Knoeferle, Urbach, & Kutas, 2011; Maguire, Frith, & Morris, 1999), we expected the degree of pain modulation to be influenced by the semantic context. We manipulated such context by using sentences describing pain experiences either in a metaphoric or in a literal fashion.…”

The revolution will not be controlled: natural stimuli in speech neuroscience

“…Many experiments use isolated sentences as stimuli (Anderson et al, 2016;Hamilton, Edwards, & Chang, 2018;Just, Wang, & Cherkassky, 2017;Mesgarani, Cheung, Johnson, & Chang, 2014). These stimuli are often drawn from real-world sources, so they clearly pass the first criterion.…”

Predicting the brain activation pattern associated with the propositional content of a sentence: Modeling neural representations of events and states

“…The addends that were used to generate sentence representations may be sentence‐context‐sensitive. Elsewhere, we demonstrate systematic interactions or context effects among the NPSFs of the concepts of a proposition [Just et al, , under review].…”