Dataset Information

Using Psychometric Network Analysis to Examine the Components of Spoken Word Recognition.

ABSTRACT: Using language requires access to domain-specific linguistic representations, but also draws on domain-general cognitive skills. A key issue in current psycholinguistics is to situate linguistic processing in the network of human cognitive abilities. Here, we focused on spoken word recognition and used an individual differences approach to examine the links of scores in word recognition tasks with scores on tasks capturing effects of linguistic experience, general processing speed, working memory, and non-verbal reasoning. 281 young native speakers of Dutch completed an extensive test battery assessing these cognitive skills. We used psychometric network analysis to map out the direct links between the scores, that is, the unique variance between pairs of scores, controlling for variance shared with the other scores. The analysis revealed direct links between word recognition skills and processing speed. We discuss the implications of these results and the potential of psychometric network analysis for studying language processing and its embedding in the broader cognitive system.

SUBMITTER: Hintz F

PROVIDER: S-EPMC10786093 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Using Psychometric Network Analysis to Examine the Components of Spoken Word Recognition.

Hintz Florian F McQueen James M JM Meyer Antje S AS

Journal of cognition 20240110 1

Using language requires access to domain-specific linguistic representations, but also draws on domain-general cognitive skills. A key issue in current psycholinguistics is to situate linguistic processing in the network of human cognitive abilities. Here, we focused on spoken word recognition and used an individual differences approach to examine the links of scores in word recognition tasks with scores on tasks capturing effects of linguistic experience, general processing speed, working memor ...[more]

PMID: 38223231

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Project description:Top-down contextual influences play a major part in speech understanding, especially in hearing-impaired patients with deteriorated auditory input. Those influences are most obvious in difficult listening situations, such as listening to sentences in noise but can also be observed at the word level under more favorable conditions, as in one of the most commonly used tasks in audiology, i.e., repeating isolated words in silence. This study aimed to explore the role of top-down contextual influences and their dependence on lexical factors and patient-specific factors using standard clinical linguistic material. Spondaic word perception was tested in 160 hearing-impaired patients aged 23-88 years with a four-frequency average pure-tone threshold ranging from 21 to 88 dB HL. Sixty spondaic words were randomly presented at a level adjusted to correspond to a speech perception score ranging between 40 and 70% of the performance intensity function obtained using monosyllabic words. Phoneme and whole-word recognition scores were used to calculate two context-influence indices (the j factor and the ratio of word scores to phonemic scores) and were correlated with linguistic factors, such as the phonological neighborhood density and several indices of word occurrence frequencies. Contextual influence was greater for spondaic words than in similar studies using monosyllabic words, with an overall j factor of 2.07 (SD = 0.5). For both indices, context use decreased with increasing hearing loss once the average hearing loss exceeded 55 dB HL. In right-handed patients, significantly greater context influence was observed for words presented in the right ears than for words presented in the left, especially in patients with many years of education. The correlations between raw word scores (and context influence indices) and word occurrence frequencies showed a significant age-dependent effect, with a stronger correlation between perception scores and word occurrence frequencies when the occurrence frequencies were based on the years corresponding to the patients' youth, showing a "historic" word frequency effect. This effect was still observed for patients with few years of formal education, but recent occurrence frequencies based on current word exposure had a stronger influence for those patients, especially for younger ones.

Dataset Information

Using Psychometric Network Analysis to Examine the Components of Spoken Word Recognition.

Publications

Using Psychometric Network Analysis to Examine the Components of Spoken Word Recognition.

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