Collectively, N400 sentence processing data point to a language comprehension system that makes use of all the information it can as soon as it can in order to deal with a rapid, noisy input stream. Such data helped to compel a shift away from models that treat word recognition as a relatively isolated, data-driven process and also led to a reconsideration of the “postlexical” view of the N400. With that, came a surge of interest in using the measure to examine aspects of word recognition, including the nature and influence of orthographic and phonological levels of structure, and the representation and processing of morphology. The results lined up well with interactive views, revealing highly intertwined and sometimes multiple effects of many lexical variables (reviewed in Barber & Kutas 2007). Furthermore, the fact that not only words but also pseudowords (e.g., GORP) and even illegal strings (e.g., NKL) were subject to the processing reflected in the N400 (Laszlo & Federmeier, 2009) and similarly sensitive to language-relevant variables (such as orthographic neighborhood size) suggests that the process of categorizing inputs as lexically represented or even orthographically regular occurs in parallel with attempts at meaning access.
