Additive Effects of Repetition and Predictability during Comprehension: Evidence from Event-Related Potentials

Abstract

Previous research has shown that neural responses to words during sentence comprehension are sensitive to both lexical repetition and a word’s predictability in context. While previous research has often contrasted the effects of these variables (e.g. by looking at cases in which word repetition violates sentence-level constraints), little is known about how they work in tandem. In the current study we examine how recent exposure to a word and its predictability in context combine to impact lexical semantic processing. We devise a novel paradigm that combines reading comprehension with a recognition memory task, allowing for an orthogonal manipulation of a word’s predictability and its repetition status. Using event-related brain potentials (ERPs), we show that word repetition and predictability have qualitatively similar and additive effects on the N400 amplitude. We propose that prior exposure to a word and predictability impact lexical semantic processing in an additive and independent fashion.

A new insight into sentence comprehension: The impact of word associations in sentence processing as shown by invasive EEG recording

“…In the scalp EEG recording of patient P2, we observed only the effect of SC and no effects of WA or SC × WA interaction in both time-windows. This observation is in line with some of the previous studies (Coulson et al, 2000;Khachatryan et al, 2017), while other studies did observe an effect of WA independent of or in interaction with the effect of SC (Camblin et al, 2007;Chow et al, 2014, for review see, Ledoux, Camblin, Swaab, & Gordon, 2006). The difference between these results is probably due to the use of stimuli with different levels of semantic constraints.…”

“…However, it is unclear whether word predictability, reflected by CP, played any role in the modulation of N400 amplitude, as Van Petten did not report whether she controlled her stimuli for CP. Recently, another study (Chow et al, 2014) suggested that low-level lexical manipulations such as word repetitions and high-level sentence processing such as word predictability can have an additive effect on N400 amplitude. This was also suggested by a number of eye-tracking studies evaluating the interaction between sentence context and word frequency (for a review of these studies, see Staub, 2015).…”

Hyper-active gap filling

“…Critically, a non-predictive account must assume that access to the contents of lexical information is ordered, such that category information is accessed earlier than the subcategorization property of the verb. However, as yet there is little evidence to support such ordered access to category vs. other contents of a verb ( Farmer et al, 2006 is one rare case, but see Staub et al, 2009 for a counterargument), whereas there is an abundance of psycholinguistic and neurolinguistic research demonstrating extremely fast access to all aspects of lexical content (e.g., Federmeier et al, 2000 ; Dambacher et al, 2006 ; Hauk et al, 2006 ; Staub and Rayner, 2007 ; Tanenhaus, 2007 ; Almeida and Poeppel, 2013 ; Chow et al, 2014 ). Moreover, there has been a recent surge of empirical work demonstrating that structure building processes can proceed predictively based on various types of top–down linguistic and contextual information, as discussed above (e.g., Konieczny, 2000 ; Kamide et al, 2003 ; DeLong et al, 2005 ; Van Berkum et al, 2005 ; Lau et al, 2006 ; Staub and Clifton, 2006 ; Levy and Keller, 2013 ; Yoshida et al, 2013 ; Yoshida, unpublished doctoral dissertation), including access to transitivity information ( Arai and Keller, 2013 ).…”

Spatiotemporal Signatures of Lexical–Semantic Prediction

“…Another mechanism that can sometimes result in activation of representations ahead of bottom-up input is automatic spreading activation, which has been proposed to explain the facilitation observed in classic semantic priming paradigms. The relationship between this kind of "passive" priming and sentential prediction and the extent to which they draw on common underlying mechanisms has long been debated (e.g., Neely 1991;Van Petten 1993;Camblin et al 2007;Chow et al 2014). What most would agree on, however, is that predictive contexts lead to larger effects on semantic facilitation than passive priming during sentence comprehension (e.g., Van Petten 1993), and that this can offer significant advantages during real-time comprehension: not only does it allow preactivation of stored representations ahead of the bottom-up input, it can also allow these stored representations to be added to the current representation of context such that it is updated in advance of the actual input.…”