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Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?
(Cognitive Science, 2018)
From a theoretical perspective, most discussions of statistical learning (SL) have focused on
the possible “statistical” properties that are the object of learning. Much less attention has been
given to defining what ...
Is the Hebb repetition task a reliable measure of individual differences in sequence learning?
(QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2018)
The Hebb repetition task, an operationalization of long-term sequence learning through
repetition, is the focus of renewed interest, as it is taken to provide a laboratory analogue for
naturalistic vocabulary acquisition. ...
Linguistic entrenchment: Prior knowledge impacts statistical learning performance
(COGNITION, 2018)
Statistical Learning (SL) is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying statistical regularities in the input. Recent findings, however, show clear differences ...
Neurobiological signatures of L2 proficiency: Evidence from a bi-directional cross-linguistic study
(Journal of Neurolinguistics, 2019)
Recent evidence has shown that convergence of print and speech processing across a network of
primarily left-hemisphere regions of the brain is a predictor of future reading skills in children,
and a marker of fluent ...
What Determines Visual Statistical Learning Performance? Insights From Information Theory
(Cognitive Science. A Multidisciplinary Journal, 2019)
In order to extract the regularities underlying a continuous sensory input, the individual elements constituting the stream have to be encoded and their transitional probabilities (TPs) should be learned. This suggests ...
What exactly is learned in visual statistical learning? Insights from Bayesian modeling
(Cognition, 2019)
It is well documented that humans can extract patterns from continuous input through Statistical Learning (SL) mechanisms. The exact computations underlying this ability, however, remain unclear. One outstanding controversy ...
Statistical learning research: A critical review and possible new directions.
(Psychological Bulletin, 2019)
Statistical learning (SL) is involved in a wide range of basic and higher-order cognitive functions and is
taken to be an important building block of virtually all current theories of information processing. In the
last ...
Splitting the variance of statistical learning performance: A parametric investigation of exposure duration and transitional probabilities
(Psychonomic Bulletin & Review, 2016)
What determines individuals’ efficacy in detecting
regularities in visual statistical learning? Our theoretical
starting point assumes that the variance in performance of
statistical learning (SL) can be split into the ...
The long road of statistical learning research: past, present and future
(Philosophical Transactions of the Royal Society: Biological Sciences, 2017)
Towards a theory of individual differences in statistical learning
(Philosophical Transactions of the Royal Society: Biological Sciences, 2017)
In recent years, statistical learning (SL) research has seen a growing interest in tracking individual performance in SL tasks, mainly as a predictor of linguistic abilities. We review studies from this line of research ...