Browsing BCBL-Publications by Author "Frost, Ram"
Now showing items 1-19 of 19
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Beta-Band Activity Is a Signature of Statistical Learning
Bogaerts, Louisa; Richter, Craig G.; Landau, Ayelet N.; Frost, Ram (The Journal of Neuroscience, 2020)Through statistical learning (SL), cognitive systems may discover the underlying regularities in the environment. Testing human adults (n = 35, 21 females), we document, in the context of a classical visual SL task, ... -
Cross-modal noise compensation in audiovisual words
Baart, Martijn; Armstrong, Blair C.; Martin, Clara D.; Frost, Ram; Carreiras, Manuel (Scientific Reports, 2017)Perceiving linguistic input is vital for human functioning, but the process is complicated by the fact that the incoming signal is often degraded. However, humans can compensate for unimodal noise by relying on simultaneous ... -
Integrating statistical learning into cognitive science
Bogaerts, Louisa; Frost, Ram; Christiansen, Morten H. (Journal of Memory and Language, 2020)Over the last two decades statistical learning (SL) has evolved into a key explanatory mechanism underlying the incidental learning of regularities across different domains of cognition, such as language, visual and ... -
Is the Hebb repetition task a reliable measure of individual differences in sequence learning?
Bogaerts, Louisa; Siegelman, Noam; Ben-Porat, Tali; Frost, Ram (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. ... -
Is there such a thing as a ‘good statistical learner’?
Bogaerts, Louisa; Siegelman, Noam; Christiansen, Morten H.; Frost, Ram (ELSEVIER, 2022)A growing body of research investigates individual differences in the learning of statistical structure, tying them to variability in cognitive (dis)abilities. This approach views statistical learning (SL) as a general ... -
Linguistic entrenchment: Prior knowledge impacts statistical learning performance
Siegelman, Noam; Bogaerts, Louisa; Elazar, Amit; Arciuli, Joanne; Frost, Ram (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 ... -
Measuring individual differences in statistical learning: Current pitfalls and possible solutions
Siegelman, Noam; Bogaerts, Louisa; Frost, Ram (Behavior Research Methods, 2017)Most research in statistical learning (SL) has focused on the mean success rates of participants in detecting statistical contingencies at a group level. In recent years, however, researchers have shown increased interest ... -
Neurobiological signatures of L2 proficiency: Evidence from a bi-directional cross-linguistic study
Brice, Henry; Mencl, William Einar; Frost, Stephen J.; Bick, Atira Sara; Rueckl, Jay G.; Pugh, Kenneth R.; Frost, Ram (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 ... -
Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?
Siegelman, Noam; Bogaerts, Louisa; Kronenfeld, Ofer; Frost, Ram (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 ... -
Sniffing out meaning: Chemosensory and semantic neural network changes in sommeliers
Carreiras, Manuel; Quiñones, Ileana; Chen, H. Alexander; Vázquez-Araujo, Laura; Small, Dana; Frost, Ram (WILEY, 2024)Wine tasting is a very complex process that integrates a combination of sensa-tion, language, and memory. Taste and smell provide perceptual information that,together with the semantic narrative that converts flavor into ... -
Splitting the variance of statistical learning performance: A parametric investigation of exposure duration and transitional probabilities
Bogaerts, Louisa; Siegelman, Noam; Frost, Ram (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 ... -
Statistical Learning and Language Impairments: Toward More Precise Theoretical Accounts
Bogaerts, Louisa; Siegelman, Noam; Frost, Ram (Perspectives on Psychological Science, 2021)Statistical-learning (SL) theory offers an experience-based account of typical and atypical spoken and written language acquisition. Recent work has provided initial support for this view, tying individual differences in ... -
Statistical learning research: A critical review and possible new directions.
Frost, Ram; Armstrong, Blair C.; Christiansen, Morten H. (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 ... -
The long road of statistical learning research: past, present and future
Armstrong, Blair C.; Frost, Ram; Christiansen, Morten H. (Philosophical Transactions of the Royal Society: Biological Sciences, 2017)... -
Towards a theory of individual differences in statistical learning
Siegelman, Noam; Bogaerts, Louisa; Christiansen, Morten H.; Frost, Ram (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 ... -
Tracking second language immersion across time: Evidence from a bi-directional longitudinal cross-linguistic fMRI study
Brice, Henry; Frost, Stephen J.; Bick, Atira Sara; Molfese, Peter J.; Rueckl, Jay G.; Pugh, Kenneth R.; Frost, Ram (Elsevier, 2021)Parallel cohorts of Hebrew speakers learning English in the U.S., and American-English speakers learning Hebrew in Israel were tracked over the course of two years of immersion in their L2. We utilised a functional MRI ... -
What Determines Visual Statistical Learning Performance? Insights From Information Theory
Siegelman, Noam; Bogaerts, Louisa; Frost, Ram (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
Siegelman, Noam; Bogaerts, Louisa; Armstrong, Blair C.; Frost, Ram (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 ... -
When the “Tabula” is Anything but “Rasa:” What Determines Performance in the Auditory Statistical Learning Task?
Elazar, Amit; Alhama, Raquel G.; Bogaerts, Louisa; Siegelman, Noam; Baus, Cristina; Frost, Ram (WILEY, 2022)How does prior linguistic knowledge modulate learning in verbal auditory statistical learning (SL) tasks? Here, we address this question by assessing to what extent the frequency of syllabic co-occurrences in the learners’ ...