2021
DOI: 10.1037/xlm0000955
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Structural priming is supported by different components of nondeclarative memory: Evidence from priming across the lifespan.

Abstract: Structural priming is the tendency to repeat syntactic structure across sentences and can be divided into short-term (prime to immediately following target) and long-term (across an experimental session) components. This study investigates how nondeclarative memory could support both the transient, short-term and the persistent, long-term structural priming effects commonly seen in the literature. We propose that these characteristics are supported by different subcomponents of nondeclarative memory: Perceptua… Show more

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Cited by 15 publications
(24 citation statements)
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References 75 publications
(150 reference statements)
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“…It could be that older adults are more vulnerable to being biased towards infrequent syntactic structures. A similar trend was found in the performance of older adults in a statistical learning task (serial reaction time task; Heyselaar et al, 2020), suggesting that this effect could be due to their declining implicit memory system and may not be language-specific. Patients with amnesia also show a more robust passive priming magnitude after a single session (Heyselaar et al, 2017).…”
Section: Discussionsupporting
confidence: 60%
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“…It could be that older adults are more vulnerable to being biased towards infrequent syntactic structures. A similar trend was found in the performance of older adults in a statistical learning task (serial reaction time task; Heyselaar et al, 2020), suggesting that this effect could be due to their declining implicit memory system and may not be language-specific. Patients with amnesia also show a more robust passive priming magnitude after a single session (Heyselaar et al, 2017).…”
Section: Discussionsupporting
confidence: 60%
“…For the analysis, we used a generalized additive mixed model (GAMM), using the mgcv package (version 1.8-22; Wood, 2017) as previous experiments have shown that cumulative priming mirrors a growth-curve more than a linear correlation over the length of the experimental session (Heyselaar et al, 2015(Heyselaar et al, , 2020Segaert et al, 2016). Unlike ANOVAs or generalized mixed-effects regression (GLMER), GAMM does not assume linearity (although it can find a linear form if supported by the data).…”
Section: Experiments 1 -Resultsmentioning
confidence: 99%
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