Word recognition in <scp>A</scp>lzheimer's disease: Effects of semantic degeneration

Cuetos, Fernando; Arce, Noemí; Martı́nez, Carmen; Ellis, Andrew W.

doi:10.1111/jnp.12077

Cited by 23 publications

(23 citation statements)

References 82 publications

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“…This suggests that people rarely forget words, even when they don’t know the (exact) meaning any more. Indeed, a test in which persons are asked to spot a word among non-words is thought to be a good estimate of premorbid intelligence in elderly people and patients with dementia ( Baddeley et al, 1993 ; Vanderploeg and Schinka, 2004 ; but also see Cuetos et al, 2015 for evidence that dementia patients are deficient at spotting words among non-words, in particular words that are low in frequency, low in imageability, and acquired later in life).…”

Section: Resultsmentioning

confidence: 99%

How Many Words Do We Know? Practical Estimates of Vocabulary Size Dependent on Word Definition, the Degree of Language Input and the Participant’s Age

et al. 2016

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Based on an analysis of the literature and a large scale crowdsourcing experiment, we estimate that an average 20-year-old native speaker of American English knows 42,000 lemmas and 4,200 non-transparent multiword expressions, derived from 11,100 word families. The numbers range from 27,000 lemmas for the lowest 5% to 52,000 for the highest 5%. Between the ages of 20 and 60, the average person learns 6,000 extra lemmas or about one new lemma every 2 days. The knowledge of the words can be as shallow as knowing that the word exists. In addition, people learn tens of thousands of inflected forms and proper nouns (names), which account for the substantially high numbers of ‘words known’ mentioned in other publications.

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Section: Resultsmentioning

confidence: 99%

How Many Words Do We Know? Practical Estimates of Vocabulary Size Dependent on Word Definition, the Degree of Language Input and the Participant’s Age

et al. 2016

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“…Further, speakers who were longer post-diagnosis produced more frequent and strongly collocated combinations. Frequency effects were much stronger at the level of word combinations than they were at the single word level, albeit the analysis did not include a comparison for content words alone, which are usually the focus of studies on lexical processing (Cuetos, Arce, Martínez, & Ellis, 2015;Cuetos, Rodríguez-Ferreiro, Sage, & Ellis, 2012).…”

Section: Introductionmentioning

confidence: 99%

Automated analysis of language production in aphasia and right-hemisphere damage: frequency and collocation strength

et al. 2018

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Background: Reliance on formulaic language, i.e. holistically processed multiword chunks, is claimed to distinguish speakers with aphasia, speakers with right hemisphere damage and neurotypical controls. Frequency and collocation strength of word combinations are indicators of formulaic language. Methods and Procedures: We used computerized methods to investigate spontaneous language in 40 speakers: 10 with fluent aphasia, 10 with non-fluent aphasia, 10 with righthemisphere damage and 10 neurotypical controls. Our analysis focused on frequency and collocation strength of grammatical combinations as markers of formulaic language (using the British National Corpus as reference), but also looked at word frequency, language fluency, proportion of content words, and measures of lexical and combinatorial diversity. Results: Both groups with aphasia differed from neurotypical speakers with regard to lexical features and word combinations. Their language was less fluent, less diverse at word level, and in the non-fluent group, contained a higher proportion of content words. Each aphasic group also differed from controls with increased values on at least one marker of formulaic language. Speakers with right hemisphere damage produced less frequent combinations which were more weakly collocated; however, these effects did not reach statistical significance. Conclusions: Our results show that formulaic language use distinguishes aphasic from other speakers, and that differences can be tracked with an automated, corpus-based script which uses frequency and collocation variables. We present our study in the context of usage-based frameworks of language.

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“…Language processing advantages driven by imageability have been shown in children, who initially acquire [ 14 , 15 , 16 ] and subsequently learn to read [ 17 ] highly imageable words earlier and better. Moreover, concrete and/or highly imaginable word processing is often less severely impaired by clinical disorders like semantic dementia [ 18 , 19 ], dyslexia [ 20 , 21 , 22 , 23 , 24 , 25 ] and Alzheimer’s disease [ 26 ]. Kellogg, et al [ 27 ] showed that a concurrent visual working memory task impaired the performance of healthy young adults in a definition production task for concrete but not abstract words, further supporting the role of imageability in the CE.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Training-Induced Visual Imageability on Electrophysiological Correlates of Novel Word Processing

2018

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The concreteness effect (CE) describes a processing advantage for concrete over abstract words. Electrophysiologically, the CE manifests in higher N400 and N700 amplitudes for concrete words. The contribution of the stimulus-inherent imageability to the electrophysiological correlates of the CE is not yet fully unraveled. This EEG study focused on the role of imageability irrespective of concreteness by examining the effects of training-induced visual imageability on the processing of novel words. In two training sessions, 21 healthy participants learned to associate novel words with pictures of novel objects as well as electron-microscopical structures and were additionally familiarized with novel words without any picture association. During a post-training EEG session, participants categorized trained novel words with or without picture association, together with real concrete and abstract words. Novel words associated with novel object pictures during the training elicited a higher N700 than familiarized novel words without picture-association. Crucially, this training-induced N700 effect resembled the CE found for real words. However, a CE on the N400 was found for real words, but no effect of imageability in novel words. The results suggest that the N400 CE for real words depends on the integration of multiple semantic features, while mere visual imageability might contribute to the CE in the N700 time window.

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Word recognition in Alzheimer's disease: Effects of semantic degeneration

Cited by 23 publications

References 82 publications

How Many Words Do We Know? Practical Estimates of Vocabulary Size Dependent on Word Definition, the Degree of Language Input and the Participant’s Age

How Many Words Do We Know? Practical Estimates of Vocabulary Size Dependent on Word Definition, the Degree of Language Input and the Participant’s Age

Automated analysis of language production in aphasia and right-hemisphere damage: frequency and collocation strength

The Effect of Training-Induced Visual Imageability on Electrophysiological Correlates of Novel Word Processing

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