Publications

Abstract

Computational models can reflect the complexity of human behaviour by implementing multiple constraints within their architecture, and/or by taking into account the variety and richness of the environment to which the human is responding. We explore the second alternative in a model of word recognition that learns to map spoken words to visual and semantic representations of the words’ concepts. Critically, we employ a phonological representation utilising coarse-coding of the auditory stream, to mimic early stages of language development that are not dependent on individual phonemes to be isolated in the input, which may be a consequence of literacy development. The model was tested at different stages during training, and was able to simulate key behavioural features of word recognition in children: a developing effect of semantic information as a consequence of language learning, and a small but earlier effect of phonological information on word processing. We additionally tested the role of visual information in word processing, generating predictions for behavioural studies, showing that visual information could have a larger effect than semantics on children’s performance, but that again this affects recognition later in word processing than phonological information. The model also provides further predictions for performance of a mature word recognition system in the absence of fine-coding of phonology, such as in adults who have low literacy skills. The model demonstrated that such phonological effects may be reduced but are still evident even when multiple distractors from various modalities are present in the listener’s environment. The model demonstrates that complexity in word recognition can emerge from a simple associative system responding to the interactions between multiple sources of information in the language learner’s environment.

Abstract

Previous studies show that children do not become adult-like in learning to set the scene and introduce referents in their narrations until 9 years of age and even beyond. However, they investigated spoken languages, thus we do not know much about how these skills are acquired in sign languages, where events are expressed in visually similar ways to the real world events, unlike in spoken languages. The results of the current study demonstrate that deaf children (3;5–9;10 years) acquiring Turkish Sign Language, and hearing children (3;8–9;11 years) acquiring spoken Turkish both acquire scene-setting and referent introduction skills at similar ages. Thus the modality of the language being acquired does not have facilitating or hindering effects in the development of these skills.

Abstract

Language- and speech-related disorders are among the most frequent consequences of developmental and acquired pathologies. While classical approaches to the study of these disorders typically employed the lesion method to unveil one-to-one correspondence between locations, the extent of the brain damage, and corresponding symptoms, recent advances advocate the use of online methods of investigation. For example, the use of electrophysiology or magnetoencephalography—especially when combined with anatomical measures—allows for in vivo tracking of real-time language and speech events, and thus represents a particularly promising venue for future research targeting rehabilitative interventions. In this chapter, we provide a comprehensive overview of language and speech pathologies arising from cortical and/or subcortical damage, and their corresponding neurophysiological and pathological symptoms. Building upon the reviewed evidence and literature, we aim at providing a description of how the neurophysiology of the language network changes as a result of brain damage. We will conclude by summarizing the evidence presented in this chapter, while suggesting directions for future research.