2021
DOI: 10.1080/02687038.2021.1907292
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Psycholinguistic variables influencing word retrieval in Persian speaking people with aphasia

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Cited by 4 publications
(5 citation statements)
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“…These findings confirm the stability of lexical frequency as a robust predictor for word recognition and retrieval throughout the lifespan, including advanced aging. As mentioned in the Introduction, the lexical frequency effect is explained by the differing levels of semantic representation and familiarity presented by words, which impact the speed and accuracy of the processing [ 18 , 26 ]. Moreover, our data show that the difference in RT between low- and high-frequency words increases exponentially with aging in all experiments (see Table 1 ).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…These findings confirm the stability of lexical frequency as a robust predictor for word recognition and retrieval throughout the lifespan, including advanced aging. As mentioned in the Introduction, the lexical frequency effect is explained by the differing levels of semantic representation and familiarity presented by words, which impact the speed and accuracy of the processing [ 18 , 26 ]. Moreover, our data show that the difference in RT between low- and high-frequency words increases exponentially with aging in all experiments (see Table 1 ).…”
Section: Discussionmentioning
confidence: 99%
“…Moreover, several studies on lexical access have shown that some lexical variables play a facilitating or inhibiting role in the recognition and/or retrieval processes [ 25 ]. For example, high-frequency words, compared to low-frequency words, reduce the RT and increase the accuracy in lexical access tasks, since they have greater semantic representation and familiarity [ 26 ]. They also form more interconnected networks between sub-lexical units, thereby having a greater potential to be recognized, which facilitates their activation and subsequent selection [ 25 ].…”
Section: Introductionmentioning
confidence: 99%
“…Pictures are a valuable tool in cognitive science and kindred disciplines. They are employed both in experimental research to understand the nuances of various cognitive processes (e.g., language, attention, memory; for review, see Souza et al, 2020) and in various clinical populations (for instance, in dementia: e.g., Cuetos et al, 2005Cuetos et al, , 2012Moayedfar et al, 2021;Silagi et al, 2015;and in aphasia: e.g., Alyahya et al, 2020;Bemani et al, 2022;Bose & Schafer, 2017;Brysbaert & Ellis, 2016;Cuetos et al, 2002;Nickels, 1995;Nickels & Howard, 1995). For all such purposes, pictures need to be carefully developed and evaluated in terms of various (psycholinguistic) attributes that are known to influence their processing across tasks.…”
Section: Introductionmentioning
confidence: 99%
“…Word properties (or psycholinguistic variables) are characteristics of words that can be extracted using corpora (e.g., frequency ratings as found in collections of books, subtitles, and spoken language), running questionnaires to healthy individuals (e.g., how familiar they are with the word; how concrete is the word; when they think they learned the word), and by measuring physical characteristics of the words (e.g., number of graphemes or phonemes). The study of word properties of language tasks is relevant because it may indicate impairments at specific language levels (e.g., Whitworth et al, 2014 ; Rofes et al, 2019 ; Alyahya et al, 2020 ; Bemani et al, 2021 ).…”
Section: Introductionmentioning
confidence: 99%
“…For the comparison between animal and unconstrained fluency, we expect no differences; (c) total number of correct words in animal fluency and unconstrained fluency to be better explained by word properties that are typically related to lexical-semantic processes (i.e., age of acquisition, concreteness, familiarity, frequency, imageability, arousal, valence). Also, we expect variables that are typically related to the (phonological/orthographic) output lexica and buffer to explain the total number of words in letter fluency (i.e., age of acquisition, frequency, length in graphemes, and orthographic/phonologic neighborhood) (e.g., Whitworth et al, 2014 ; Rofes et al, 2019 ; Alyahya et al, 2020 ; Bemani et al, 2021 ). We expect cluster size and number of switches to be relevant to explain fluency tasks.…”
Section: Introductionmentioning
confidence: 99%