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  1. Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?Noam Siegelman, Louisa Bogaerts, Ofer Kronenfeld & Ram Frost - 2018 - Cognitive Science 42 (S3):692-727.
    From a theoretical perspective, most discussions of statistical learning have focused on the possible “statistical” properties that are the object of learning. Much less attention has been given to defining what “learning” is in the context of “statistical learning.” One major difficulty is that SL research has been monitoring participants’ performance in laboratory settings with a strikingly narrow set of tasks, where learning is typically assessed offline, through a set of two-alternative-forced-choice questions, which follow a brief visual or auditory familiarization (...)
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  • Statistical Learning Impairments as a Consequence of Stroke.Albulena Shaqiri, James Danckert, Lauren Burnett & Britt Anderson - 2018 - Frontiers in Human Neuroscience 12.
  • Explicit pre-training instruction does not improve implicit perceptual-motor sequence learning.Daniel J. Sanchez & Paul J. Reber - 2013 - Cognition 126 (3):341-351.
  • Statistical learning of tone sequences by human infants and adults.Jenny R. Saffran, Elizabeth K. Johnson, Richard N. Aslin & Elissa L. Newport - 1999 - Cognition 70 (1):27-52.
  • Implicit learning and tacit knowledge.Arthur S. Reber - 1989 - Journal of Experimental Psychology: General 118 (3):219-235.
    I examine the phenomenon of implicit learning, the process by which knowledge about the rule-governed complexities of the stimulus environment is acquired independently of conscious attempts to do so. Our research with the two seemingly disparate experimental paradigms of synthetic grammar learning and probability learning, is reviewed and integrated with other approaches to the general problem of unconscious cognition. The conclusions reached are as follows: Implicit learning produces a tacit knowledge base that is abstract and representative of the structure of (...)
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  • Implicit learning and statistical learning: One phenomenon, two approaches.Pierre Perruchet & Sebastien Pacton - 2006 - Trends in Cognitive Sciences 10 (5):233-238.
  • Fading out of the rule vs. no-rule.Pierre Perruchet & Sebastien Pacton - 2006 - Trends in Cognitive Sciences 10 (5):233-238.
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  • Musicians’ Online Performance during Auditory and Visual Statistical Learning Tasks.Pragati R. Mandikal Vasuki, Mridula Sharma, Ronny K. Ibrahim & Joanne Arciuli - 2017 - Frontiers in Human Neuroscience 11.
  • Visual statistical learning in infancy: evidence for a domain general learning mechanism.Natasha Z. Kirkham, Jonathan A. Slemmer & Scott P. Johnson - 2002 - Cognition 83 (2):B35-B42.
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  • Surface features can deeply affect artificial grammar learning.Luis Jiménez, Helena Mendes Oliveira & Ana Paula Soares - 2020 - Consciousness and Cognition 80:102919.
  • Changing Structures in Midstream: Learning Along the Statistical Garden Path.Andrea L. Gebhart, Richard N. Aslin & Elissa L. Newport - 2009 - Cognitive Science 33 (6):1087-1116.
    Previous studies of auditory statistical learning have typically presented learners with sequential structural information that is uniformly distributed across the entire exposure corpus. Here we present learners with nonuniform distributions of structural information by altering the organization of trisyllabic nonsense words at midstream. When this structural change was unmarked by low‐level acoustic cues, or even when cued by a pitch change, only the first of the two structures was learned. However, both structures were learned when there was an explicit cue (...)
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  • Neurocognitive mechanisms of statistical-sequential learning: what do event-related potentials tell us?Jerome Daltrozzo & Christopher M. Conway - 2014 - Frontiers in Human Neuroscience 8.
  • Implicit Statistical Learning: A Tale of Two Literatures.Morten H. Christiansen - 2019 - Topics in Cognitive Science 11 (3):468-481.
    In this review article, Christiansen provides a historical perspective on the two research traditions, implicit learning and statistical learning, thus nicely setting the scene for this special issue of Topics in Cognitive Science. In this “tale of two literatures”, he first traces the history of both literatures before sketching a framework that provides a basis for understanding implicit learning and statistical learning as a unified phenomenon.
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  • Visual statistical learning in the newborn infant.Hermann Bulf, Scott P. Johnson & Eloisa Valenza - 2011 - Cognition 121 (1):127-132.
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  • Visual statistical learning in children and young adults: how implicit?Julie Bertels, Emeline Boursain, Arnaud Destrebecqz & Vinciane Gaillard - 2014 - Frontiers in Psychology 5.
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  • Understanding the Neural Bases of Implicit and Statistical Learning.Laura J. Batterink, Ken A. Paller & Paul J. Reber - 2019 - Topics in Cognitive Science 11 (3):482-503.
    This article provides a much‐needed review of the neural bases of implicit statistical learning. Batterink, Paller and Reber focus on the neural processes that underpin performance in experimental paradigms employed in implicit learning and statistical learning research. An important insight is that learning across all paradigms is supported by interactions between the declarative and nondeclarative memory systems of the brain. They conclude with a helpful discussion of future directions of research.
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  • Statistical learning under incidental versus intentional conditions.Joanne Arciuli, Janne von Koss Torkildsen, David J. Stevens & Ian C. Simpson - 2014 - Frontiers in Psychology 5.
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  • Statistical Learning Is Related to Reading Ability in Children and Adults.Joanne Arciuli & Ian C. Simpson - 2012 - Cognitive Science 36 (2):286-304.
    There is little empirical evidence showing a direct link between a capacity for statistical learning (SL) and proficiency with natural language. Moreover, discussion of the role of SL in language acquisition has seldom focused on literacy development. Our study addressed these issues by investigating the relationship between SL and reading ability in typically developing children and healthy adults. We tested SL using visually presented stimuli within a triplet learning paradigm and examined reading ability by administering the Wide Range Achievement Test (...)
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  • A cortical network for semantics: (de)constructing the N400.E. Lau, C. Phillips & D. Poeppel - 2008 - Nature Reviews Neuroscience 9:920-933.
    Measuring event-related potentials (ERPs) has been fundamental to our understanding of how language is encoded in the brain. One particular ERP response, the N400 response, has been especially influential as an index of lexical and semantic processing. However, there remains a lack of consensus on the interpretation of this component. Resolving this issue has important consequences for neural models of language comprehension. Here we show that evidence bearing on where the N400 response is generated provides key insights into what it (...)
     
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  • Comparing direct and indirect measures of sequence learning.Axel Cleeremans - unknown
    Comparing the relative sensitivity of direct and indirect measures of learning is proposed as the best way to provide evidence for unconscious learning when both conceptual and operative definitions of awareness are lacking. This approach was first proposed by Reingold & Merikle (1988) in the context of subliminal perception. In this paper, we apply it to a choice reaction time task in which the material is generated based on a probabilistic finite-state grammar (Cleeremans, 1993). We show (1) that participants progressively (...)
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  • Implicit learning of artificial grammars.Arthur S. Reber - 1967 - Journal of Verbal Learning and Verbal Behavior 6:855-863.
  • Implicit probabilistic sequence learning is independent of explicit awareness.Sunbin Song, Howard Jr, James H. & Darlene V. Howard - 2007 - Learning and Memory 14 (1-6):167-176.