Tracking competition and cognitive control during language comprehension with multi-voxel pattern analysis

Abstract

To successfully comprehend a sentence that contains a homonym, readers must select the ambiguous word’s context-appropriate meaning. The outcome of this process is influenced both by top-down contextual support and bottom-up, word-specific characteristics. We examined how these factors jointly affect the neural signatures of lexical ambiguity resolution. We measured the similarity between multi-voxel patterns evoked by the same homonym in two distinct linguistic contexts: once after subjects read sentences that biased interpretation toward each homonym’s most frequent, dominant meaning, and again after interpretation was biased toward a weaker, subordinate meaning. We predicted that, following a subordinate-biasing context, the dominant yet inappropriate meaning would nevertheless compete for activation, manifesting in increased similarity between the neural patterns evoked by the two word meanings. In left anterior temporal lobe (ATL), degree of within-word pattern similarity was positively predicted by the association strength of each homonym’s dominant meaning. Further, within-word pattern similarity in left ATL was negatively predicted by item-specific responses in a region of left ventrolateral prefrontal cortex (VLPFC) sensitive to semantic conflict. These findings have implications for psycholinguistic models of lexical ambiguity resolution, and for the role of left VLPFC function during this process. Moreover, these findings demonstrate the utility of item-level, similarity-based analyses of fMRI data for our understanding of competition between co-activated word meanings during language comprehension.

The Neural Time Course of Semantic Ambiguity Resolution in Speech Comprehension

“…However, source localization results from MEG/EEG suggest that frontal and temporal regions play a coordinated role both in the initial interpretation of ambiguous words presented in neutral sentence contexts and subsequently when interpretations need to be revised. This proposal could be taken to challenge traditional divisions between temporal lobe contributions to semantic representation and frontal contributions to working memory or selection (see Musz & Thompson-Schill, 2017, for a recent statement along these lines).…”

“…With regard to the anatomical questions that motivated this study, our source localization provides evidence that frontal and temporal lobe regions are activated both in response to ambiguous words in a neutral context (before presentation of disambiguating information; Figure 5) and subsequently in response to a disambiguating word that resolves the ambiguity to a subordinate meaning (Figure 7). Previous fMRI evidence has similarly demonstrated the involvement of frontotemporal regions in ambiguity resolution (Musz & Thompson-Schill, 2017;Vitello et al, 2014;Rodd et al, 2005Rodd et al, , 2012Rodd, Longe, et al, 2010;Mason & Just, 2007;Zempleni et al, 2007). However, unlike in fMRI, timing information from MEG/ EEG allows us to confidently attribute our ambiguity and disambiguation responses specifically to initial processing of the ambiguous word and also to subsequent reinterpretation of the ambiguous word.…”

Barking up the right tree: Univariate and multivariate fMRI analyses of homonym comprehension

“…Only one previous fMRI study has investigated neural representation of homonyms in the ventral ATL. Musz and Thompson-Schill (2017) presented participants with homonyms in sentences that primed their dominant or their subordinate meanings. They then compared the neural patterns elicited by the same homonym in the two different contexts.…”

Evidence of semantic processing impairments in behavioural variant frontotemporal dementia and Parkinson's disease

“…This increased semantic diversity means that abstract nouns are more ambiguous, with more competing interpretations than concrete nouns, and may thus rely more on the surrounding linguistic context to facilitate meaning selection and efficient processing [39]. Because of high processing demands, abstract concept knowledge is thought to be supported in part by the LIFG [40 ▪ ]; the LIFG has been shown to facilitate semantic selection amongst competing alternatives [22,41,42], as well as in the unification of a lexical item with its surrounding context [43,44]. The role of the LIFG in abstract noun processing is further supported by functional imaging studies, which show increased activation of the LIFG when healthy individuals are presented with abstract nouns, compared with concrete [23,45].…”