Semantic prediction in language comprehension: evidence from brain potentials

Figures & data

Table 1. Example stimuli.

COND	Example sentence	Mean CP (SD)
High-Cor	Der Torhüter behauptet, dass der rutschige Ball einfach zu fangen war. The goalkeeper claims, that the slick ball easy to catch was. “The goalkeeper claims that the slick ball was easy to catch”.	79.3% (11.4)
High-Inc	Der Torhüter behauptet, dass der rutschige Ball einfach zu *fängst war. The goalkeeper claims, that the slick ball easy to *catches was. “The goalkeeper claims that the slick ball was easy to *catches”.
Low-Cor	Die Kinder prahlten, dass das junge Pferd einfach zu satteln war. The children boasted, that the young horse easy to saddle was. “The children boasted that the young horse was easy to saddle”.	2.5% (0.0)
Low-Inc	Die Kinder prahlten, dass das junge Pferd einfach zu *sattelst war. The children boasted, that the young horse easy to *saddles was. “The children boasted that the young horse was easy to *saddles”.

Cor, correct; CP, cloze probability; Inc, incorrect.

Notes: Example sentence for all conditions in German, literal English, and analogous English translations, with mean cloze-values (standard deviations in brackets). Critical words are underlined.

Figure 1. Cor = Correct, Inc = Incorrect. A. Grand average ERPs from selected midline electrodes. Time zero marks the onset of the critical words (bold in the examples given). Note that the example sentences are literal translations (for analogues translation, see Table 1). Negativity is plotted upwards. B. Differences maps from the two time-windows used for ERP-analyses.

Figure 2. Grand average ERPs from all electrodes. Time zero corresponds to the onset of the critical words. Negativity is plotted upwards.