Literature DB >> 31580089

Statistical learning research: A critical review and possible new directions.

Ram Frost1, Blair C Armstrong2, Morten H Christiansen3.   

Abstract

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 2 decades, a large and continuously growing research community has therefore focused on the ability to extract embedded patterns of regularity in time and space. This work has mostly focused on transitional probabilities, in vision, audition, by newborns, children, adults, in normal developing and clinical populations. Here we appraise this research approach and we critically assess what it has achieved, what it has not, and why it is so. We then center on present SL research to examine whether it has adopted novel perspectives. These discussions lead us to outline possible blueprints for a novel research agenda. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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Year:  2019        PMID: 31580089     DOI: 10.1037/bul0000210

Source DB:  PubMed          Journal:  Psychol Bull        ISSN: 0033-2909            Impact factor:   17.737


  26 in total

1.  Long-term implicit memory for sequential auditory patterns in humans.

Authors:  Roberta Bianco; Peter Mc Harrison; Mingyue Hu; Cora Bolger; Samantha Picken; Marcus T Pearce; Maria Chait
Journal:  Elife       Date:  2020-05-18       Impact factor: 8.140

2.  Beta-Band Activity Is a Signature of Statistical Learning.

Authors:  Louisa Bogaerts; Craig G Richter; Ayelet N Landau; Ram Frost
Journal:  J Neurosci       Date:  2020-08-21       Impact factor: 6.167

3.  Learning words without trying: Daily second language podcasts support word-form learning in adults.

Authors:  Elise Alexander; Stephen C Van Hedger; Laura J Batterink
Journal:  Psychon Bull Rev       Date:  2022-09-29

4.  Detecting non-adjacent dependencies is the exception rather than the rule.

Authors:  Laure Tosatto; Guillem Bonafos; Jean-Baptiste Melmi; Arnaud Rey
Journal:  PLoS One       Date:  2022-07-14       Impact factor: 3.752

5.  Individual differences in learning the regularities between orthography, phonology and semantics predict early reading skills.

Authors:  Noam Siegelman; Jay G Rueckl; Laura M Steacy; Stephen J Frost; Mark van den Bunt; Jason D Zevin; Mark S Seidenberg; Kenneth R Pugh; Donald L Compton; Robin D Morris
Journal:  J Mem Lang       Date:  2020-06-07       Impact factor: 3.059

6.  Cross-situational statistical learning in younger and older adults.

Authors:  Federica Bulgarelli; Daniel J Weiss; Nancy A Dennis
Journal:  Neuropsychol Dev Cogn B Aging Neuropsychol Cogn       Date:  2020-05-05

7.  Statistical language learning in infancy.

Authors:  Jenny R Saffran
Journal:  Child Dev Perspect       Date:  2020-01-19

8.  Statistical Learning and Language Impairments: Toward More Precise Theoretical Accounts.

Authors:  Louisa Bogaerts; Noam Siegelman; Ram Frost
Journal:  Perspect Psychol Sci       Date:  2020-11-02

9.  When the "Tabula" is Anything but "Rasa:" What Determines Performance in the Auditory Statistical Learning Task?

Authors:  Amit Elazar; Raquel G Alhama; Louisa Bogaerts; Noam Siegelman; Cristina Baus; Ram Frost
Journal:  Cogn Sci       Date:  2022-02

10.  Neural correlates of sequence learning in children with developmental dyslexia.

Authors:  Martina Hedenius; Jonas Persson
Journal:  Hum Brain Mapp       Date:  2022-04-18       Impact factor: 5.399

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