2018
DOI: 10.1111/infa.12274
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Second‐Order Correlation Learning of Dynamic Stimuli: Evidence from Infants and Computational Modeling

Abstract: We present two habituation experiments that examined 20‐ and 26‐month‐olds’ ability to engage in second‐order correlation learning for static and dynamic features, whereby learned associations between two pairs of features (e.g., P and Q, P and R) are generalized to the features that were not presented together (e.g., Q and R). We also present results from an associative learning mechanism that was implemented as an autoencoder parallel distributed processing (PDP) network in which second‐order correlation lea… Show more

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Cited by 10 publications
(6 citation statements)
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References 47 publications
(92 reference statements)
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“…Power analysis using G*power software (Faul, Erdfelder, Buchner, & Lang, 2009) revealed that 20 infants per condition would provide sufficient power (>.80) to detect a significant Pearson correlation between looking time at familiarization and test with a moderate effect size (see also Rakison & Benton, 2019). However, there were no significant correlations between the percent of time infants attended to the block tower or builder during the familiarization trials and later novelty preferences, either within or across conditions (all ps>.44).…”
Section: Resultsmentioning
confidence: 95%
“…Power analysis using G*power software (Faul, Erdfelder, Buchner, & Lang, 2009) revealed that 20 infants per condition would provide sufficient power (>.80) to detect a significant Pearson correlation between looking time at familiarization and test with a moderate effect size (see also Rakison & Benton, 2019). However, there were no significant correlations between the percent of time infants attended to the block tower or builder during the familiarization trials and later novelty preferences, either within or across conditions (all ps>.44).…”
Section: Resultsmentioning
confidence: 95%
“…We chose to implement our account in a connectionist network for two reasons. First, these models make minimal assumptions about the starting state of the infant and have shown that knowledge once taken to be innate can be learned based on experience with structured input and sufficient information-processing capacities (e.g., Rakison & Benton, 2019;Yermolayeva & Rakison, 2016). Second, we wished to demonstrate that an associative-learning mechanism can account for apparent sociomoral evaluation in preverbal infants.…”
Section: Mechanisms Of Infant Social Evaluationmentioning
confidence: 99%
“…Children's developing information-processing abilities may also explain why secondorder correlation learning emerges at different ages in studies on this topic (e.g., Rakison & Benton, 2018;Yermolayeva & Rakison, 2016). For example, in Cuevas et al's (2006) study, 6month-olds showed second-order correlation learning but only after extended exposure to the stimuli.…”
Section: Discussionmentioning
confidence: 99%