Implicit Statistical Learning Across Modalities and Its Relationship With Reading in Childhood

Abstract

Implicit statistical learning (ISL) describes our ability to tacitly pick up regularities from our environment therefore, shaping our behavior. A broad understanding of ISL incorporates a great range of possible computations, which render it highly relevant to reading. In the light of this hypothesized relationship, ISL performance was explored in young (M = 8.47 years) typical readers ( N = 31) across three different modalities (i.e., visual, auditory, and tactile) using the Artificial Grammar Learning (AGL) paradigm. Adopting repeated measures and correlational designs, the obtained data revealed modality constraints: (1) above-chance performance was observed on the visual and tactile tasks but not on the auditory task, (2) there was no significant correlation of ISL performance across modalities, and (3) split-half reliability of visual and auditory tasks was reasonably high, yet for the tactile task it was close to zero. Evaluating the relation between ISL ability and language skills, we observed a positive correlation between visual ISL performance and phonological awareness. We discuss these findings in view of current perspectives on the nature of ISL and its potential involvement in mastering successful (i.e., accurate and fluent) reading.

Statistical Learning and Language Impairments: Toward More Precise Theoretical Accounts

“…Testing adult second-language learners, individuals with better visual SL performance were found to better assimilate literacy in Hebrew (Frost, Siegelman, Narkiss, & Afek, 2013). Similar correlations have been reported using the AGL task (e.g., Conway, Bauernschmidt, Huang, & Pisoni, 2010; Misyak & Christiansen, 2012; but see Pavlidou & Bogaerts, 2019).…”

Is there such a thing as a ‘good statistical learner’?

“…to be predictive of the targeted cognitive ability (or disability), be it reading, musicality, or social skills, to name a few. Although results have not been unequivocal [18,[21][22][23], and although effect sizes are often small, most published work has reported significant positive correlations between SL performance and performance in multiple cognitive functions (Table 1). Typically, null effects within this research line have been discussed in terms of insufficient variability in performance [24] and poor task reliability more generally [18,23].…”

“…The main premise of this research is that individuals range from 'good' to 'bad' statistical learners and that 'good' statistical learners are expected to have better skills across the wide range of cognitive functions that require the assimilation of statistical structure (e.g., reading [6][7][8], early language development [9,10], syntactic processing [11,12], object and scene perception [13,14], music [15,16], etc.). Many recent studies, ours included [7,17,18], have consequently assessed correlations between performance in laboratory SL tasks and cognitive abilities in a variety of domains, in normal and special populations. A few studies, in particular those investigating language and literacy acquisition, have tested more narrow and nuanced predictions about the predictive power of individual differences in SL, for example, by linking the sensitivity to orthography-to-phonology regularities to early reading skills [19], or by establishing a relation between infants' knowledge of their native language's sound structure and their vocabulary size [20].…”

Integrating statistical learning into cognitive science

“…As such, the present volume provides a deeper understanding of the range of statistical structures that are embedded in printed texts, and the precise role or SL in assimilating them. We should note that SL abilities have been linked to reading performance through correlational research (e.g., Arciuli & Simpson, 2012;Frost et al, 2013;Misyak & Christiansen, 2012;Pavlidou & Bogaerts, 2019;Qi, Sanchez Araujo, Georgan, Gabrieli, & Arciuli, 2019), and through the study of reading impaired populations (see Bogaerts, Siegelman, & Forst, in press;Schmalz, Altoè, & Mulatti, 2017, for reviews). However, such studies have often been vague regarding the mechanistic underpinning of the revealed associations (see Schmalz, Moll, Mulatti, & Schulte-Körne, 2019;Siegelman et al, 2017;and Bogaerts et al, in press, for discussions).…”