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Duman, Tuba Yarbay; Bastiaanse, Roelien – Brain and Language, 2009
This study tested the production of tensed finite verbs and participles referring to the past and future in agrammatic speakers of Turkish. The agrammatic speakers did not make more time reference errors in tensed verbs than in participles. This is interesting because tense in general cannot therefore be the main problem, since time reference for…
Descriptors: Verbs, Turkish, Neurolinguistics, Aphasia
Bormann, Tobias; Kulke, Florian; Wallesch, Claus-W.; Blanken, Gerhard – Brain and Language, 2008
Within a discrete two-stage model of lexicalization, semantic errors and errors of omission are assumed to be independent events. In contrast, cascading and interactive models allow for an influence of word form on lexical selection and thus for an inherent relationship in accounting for both error types. A group of 17 aphasic patients was…
Descriptors: Semantics, Aphasia, Patients, Semiotics
Van Lancker Sidtis, Diana – Brain and Language, 2007
Neurolinguistic research has been engaged in evaluating models of language using measures from brain structure and function, and/or in investigating brain structure and function with respect to language representation using proposed models of language. While the aphasiological strategy, which classifies aphasias based on performance modality and a…
Descriptors: Diagnostic Tests, Neurolinguistics, Neurological Organization, Models
Sidtis, Diana Van Lancker – Brain and Language, 2006
Neurolinguistic research has been engaged in evaluating models of language using measures from brain structure and function, and/or in investigating brain structure and function with respect to language representation using proposed models of language. While the aphasiological strategy, which classifies aphasias based on performance modality and a…
Descriptors: Diagnostic Tests, Neurolinguistics, Neurological Organization, Models
Guenther, Frank H.; Ghosh, Satrajit S.; Tourville, Jason A. – Brain and Language, 2006
This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and…
Descriptors: Syllables, Models, Computer Simulation, Acoustics