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The cross-linguistic finding of greater demands in processing object relatives as compared to subject relatives in individuals with aphasia and non-brain-damaged speakers has been explained within the Relativized Minimality approach. Based on this account, the asymmetry is attributed to an element intervening between the moved element and its extraction site in object relatives, but not in subject relatives. Moreover, it has been proposed that processing of object relatives is facilitated if the intervening and the moved elements differ in their internal feature structure. The present study investigates these predictions in German-speaking individuals with aphasia and a group of control participants by combining the visual world eye-tracking methodology with an auditory referent identification task. Our results provide support for the Relativized Minimality approach. Particularly, the degree of featural distinctness was shown to modulate the occurrence of the effects in aphasia. We claim that, due to reduced processing capacities, individuals with aphasia need a higher degree of featural dissimilarity to distinguish the moved from the intervening element in object relatives to overcome their syntactic deficit. (C) 2017 Elsevier Ltd. All rights reserved.
An English double-embedded relative clause from which the middle verb is omitted can often be processed more easily than its grammatical counterpart, a phenomenon known as the grammaticality illusion. This effect has been found to be reversed in German, suggesting that the illusion is language specific rather than a consequence of universal working memory constraints. We present results from three self-paced reading experiments which show that Dutch native speakers also do not show the grammaticality illusion in Dutch, whereas both German and Dutch native speakers do show the illusion when reading English sentences. These findings provide evidence against working memory constraints as an explanation for the observed effect in English. We propose an alternative account based on the statistical patterns of the languages involved. In support of this alternative, a single recurrent neural network model that is trained on both Dutch and English sentences is shown to predict the cross-linguistic difference in the grammaticality effect.