On prediction and agreement
(Mikel Santesteban)
Several authors have recently accounted for attraction effects in agreement as a consequence
of similarity-based interference of attractors during cue-based memory retrieval processes
(Badecker & Kuminiak, 2007; Dillon, Mishler, Sloggett, & Phillips, 2013; Wagers et al., 2009).
According to the cue-retrieval mechanism, agreement attraction errors occur due to the
competition between all the elements stored in working memory that have been identified as
possible agreement sources. The cue-retrieval mechanism focuses on the mechanism put to
work once agreement errors are identified. However, to what extent do predictive
mechanisms play a role in agreement encoding? Do listeners make any predictions about the
morphological features the upcoming verb will carry once the features of the agreement
controller are processed? In this study we aim to explore whether prediction plays any role in
agreement encoding.
A wide range of studies have shown that such effects of predictability for specific words affect
both reading times and neural responses (DeLong, Urbach, & Kutas, 2005; Kutas & Hillyard,
1984; Kutas & Federmeier, 2011; Hagoort et al., 2004, Van Berkum, Brown, Zwitserlood,
Kooijman, & Hagoort, 2005; Wicha, Bates, Moreno, & Kutas, 2003). For instance, when
sentence context is highly constrained, any critical word different from the anticipated one
(e.g., beer instead of water) elicits greater N400 ERP amplitude. Similar negative components
are also elicited by agreement violations, as these usually elicit an early negativity (LAN/N400,
see Molinaro, Barber, & Carreiras, 2011 for a discussion) followed by a late positivity (P600).
We will present the design of an experiment that aims to tackle the following questions: To
what extent does morphological integration of predicted morphemes resemble semantic
integration of predicted content words? Is there any interaction between semantic integration
and agreement encoding? Do prediction processes of morphological features (i.e., agreement
features) and content words require similar brain resources?