{"id":819595,"date":"2022-02-10T16:01:51","date_gmt":"2022-02-11T00:01:51","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=819595"},"modified":"2022-02-10T16:14:58","modified_gmt":"2022-02-11T00:14:58","slug":"individual-differences-in-the-real-time-neural-dynamics-of-language-comprehension","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/individual-differences-in-the-real-time-neural-dynamics-of-language-comprehension\/","title":{"rendered":"Individual Differences in the Real-Time Neural Dynamics of Language Comprehension"},"content":{"rendered":"

Recordings of\u00a0event-related brain potentials<\/a>\u00a0(ERPs) provide a rich source of information about the cognitive systems supporting real-time language use. However, the interpretation of ERPs can be complicated by individual differences that aren’t reflected in traditional analyses or visualizations. This is problematic, as failure to recognize important and systematic individual differences has in some cases led to inappropriate interpretations of ERP effects, with neurocognitive models of language comprehension sometimes being built on these inappropriate interpretations. In this chapter we review work, largely from our lab, on individual differences in ERP studies\u00a0of language comprehension and discuss the promise of work on individual differences, as well as the challenges. In some cases individual differences in ERPs manifest themselves quantitatively (i.e., systematic differences in effect amplitudes), but in other more complex cases, qualitatively (i.e., different types of effects in different individuals). We will describe work on individual differences in morphosyntactic and\u00a0semantic processing<\/a>\u00a0in both native and nonnative language processing, as<\/span>\u00a0well as multi-modal communication and higher-order pragmatic inferencing. In this last vein we will describe some nascent work done in our lab using unsupervised machine learning algorithms to better understand underlying patterns of qualitative individual differences in the processing of scalar implicatures. We conclude by laying out some challenges and suggestions for future work.<\/p>\n","protected":false},"excerpt":{"rendered":"

Recordings of\u00a0event-related brain potentials\u00a0(ERPs) provide a rich source of information about the cognitive systems supporting real-time language use. However, the interpretation of ERPs can be complicated by individual differences that aren’t reflected in traditional analyses or visualizations. This is problematic, as failure to recognize important and systematic individual differences has in some cases led to 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