| 1 |
Do individual differences in face recognition ability moderate the other ethnicity effect?
|
|
|
|
BASE
|
|
Show details
|
|
|
| 2 |
Can Machines Find the Bilingual Advantage? Machine Learning Algorithms Find No Evidence to Differentiate Between Lifelong Bilingual and Monolingual Cognitive Profiles
|
|
|
|
In: Front Hum Neurosci (2021)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
Prefixes repel stress in reading aloud : evidence from surface dyslexia
|
|
|
|
BASE
|
|
Show details
|
|
|
| 7 |
Recognition memory in developmental prosopagnosia: electrophysiological evidence for abnormal routes to face recognition
|
|
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Intranasal inhalation of oxytocin improves face processing in developmental prosopagnosia
|
|
|
|
BASE
|
|
Show details
|
|
|
| 10 |
The Influence of Psycholinguistic Variables on Articulatory Errors in Naming in Progressive Motor Speech Degeneration
|
|
|
|
BASE
|
|
Show details
|
|
|
| 11 |
The Influence of Psycholinguistic Variables on Articulatory Errors in Naming in Progressive Motor Speech Degeneration
|
|
|
|
BASE
|
|
Show details
|
|
|
| 13 |
Computational modelling of the effects of semantic dementia on visual word recognition
|
|
|
|
Abstract:
Rogers, Lambon Ralph, Hodges, and Patterson (2004) studied two-alternative forced-choice visual lexical decision performance in patients with semantic dementia. With item pairs where the target word was more “typical” (i.e., higher in bigram and trigram frequency) than the foil (all foils were pseudohomophones), lexical decision performance was good and was unaffected by word frequency. With item pairs where the target word was less “typical” (i.e., lower in bigram and trigram frequency) than the foil, lexical decision performance was worse and was affected by word frequency, being particularly inaccurate when the word targets were low in frequency. We show (using as materials all the monosyllabic items used by Rogers and colleagues) that the same pattern of results occurs in the lexical decision performance of the DRC (dual-route cascaded) computational model of reading when the model is lesioned by probabilistic deletion of low-frequency words from its orthographic lexicon. We consider that the PDP (parallel distributed processing) computational model of reading used by Woollams, Plaut, Lambon Ralph, and Patterson (2007) to simulate reading in semantic dementia is not capable of simulating this lexical decision result. We take this, in conjunction with previous work on computational modelling of reading aloud in surface dyslexia, phonological dyslexia, and semantic dementia using the DRC and PDP reading models, to indicate that the DRC model does a better job than the PDP model in accounting for what is known about the various forms of acquired dyslexia. ; 14 page(s)
|
|
Keyword:
110900 Neurosciences; computational modelling; reading; semantic dementia; visual word recognition
|
|
URL: http://hdl.handle.net/1959.14/129309
|
|
BASE
|
|
Hide details
|
|
|
| 14 |
Computational modeling of reading in semantic dementia : comment on Woollams, Lambon Ralph, Plaut, and Patterson (2007)
|
|
|
|
BASE
|
|
Show details
|
|
|
| 15 |
Dysgraphia in dementia: a systematic investigation of graphemic buffer features in a case series
|
|
|
|
BASE
|
|
Show details
|
|
|
| 17 |
Computational modelling of phonological dyslexia : how does the DRC model fare?
|
|
|
|
BASE
|
|
Show details
|
|
|
|
|
