Literature DB >> 32716372

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques.

Julie M Schneider1, Anqi Hu2, Jennifer Legault2, Zhenghan Qi3.   

Abstract

Statistical learning, a fundamental skill to extract regularities in the environment, is often considered a core supporting mechanism of the first language development. While many studies of statistical learning are conducted within a single domain or modality, recent evidence suggests that this skill may differ based on the context in which the stimuli are presented. In addition, few studies investigate learning as it unfolds in real-time, rather focusing on the outcome of learning. In this protocol, we describe an approach for identifying the cognitive and neural basis of statistical learning, within an individual, across domains (linguistic vs. non-linguistic) and sensory modalities (visual and auditory). The tasks are designed to cast as little cognitive demand as possible on participants, making it ideal for young school-aged children and special populations. The web-based nature of the behavioral tasks offers a unique opportunity for us to reach more representative populations nationwide, to estimate effect sizes with greater precision, and to contribute to open and reproducible research. The neural measures provided by the functional magnetic resonance imaging (fMRI) task can inform researchers about the neural mechanisms engaged during statistical learning, and how these may differ across individuals on the basis of domain or modality. Finally, both tasks allow for the measurement of real-time learning, as changes in reaction time to a target stimulus is tracked across the exposure period. The main limitation of using this protocol relates to the hour-long duration of the experiment. Children might need to complete all four statistical learning tasks in multiple sittings. Therefore, the web-based platform is designed with this limitation in mind so that tasks may be disseminated individually. This methodology will allow users to investigate how the process of statistical learning unfolds across and within domains and modalities in children from different developmental backgrounds.

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Mesh:

Year:  2020        PMID: 32716372      PMCID: PMC7425813          DOI: 10.3791/61474

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  36 in total

Review 1.  Combining fMRI and behavioral measures to examine the process of human learning.

Authors:  Elisabeth A Karuza; Lauren L Emberson; Richard N Aslin
Journal:  Neurobiol Learn Mem       Date:  2013-09-25       Impact factor: 2.877

2.  Age and experience shape developmental changes in the neural basis of language-related learning.

Authors:  Kristin McNealy; John C Mazziotta; Mirella Dapretto
Journal:  Dev Sci       Date:  2011-09-15

3.  Timing is everything: changes in presentation rate have opposite effects on auditory and visual implicit statistical learning.

Authors:  Lauren L Emberson; Christopher M Conway; Morten H Christiansen
Journal:  Q J Exp Psychol (Hove)       Date:  2011-02-22       Impact factor: 2.143

4.  Psychophysics in a Web browser? Comparing response times collected with JavaScript and Psychophysics Toolbox in a visual search task.

Authors:  Joshua R de Leeuw; Benjamin A Motz
Journal:  Behav Res Methods       Date:  2016-03

5.  The long road of statistical learning research: past, present and future.

Authors:  Blair C Armstrong; Ram Frost; Morten H Christiansen
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-01-05       Impact factor: 6.237

6.  Statistical learning as an individual ability: Theoretical perspectives and empirical evidence.

Authors:  Noam Siegelman; Ram Frost
Journal:  J Mem Lang       Date:  2015-05-01       Impact factor: 3.059

7.  The curse of knowledge: first language knowledge impairs adult learners' use of novel statistics for word segmentation.

Authors:  Amy S Finn; Carla L Hudson Kam
Journal:  Cognition       Date:  2008-06-03

8.  Statistical learning in children with specific language impairment.

Authors:  Julia L Evans; Jenny R Saffran; Kathryn Robe-Torres
Journal:  J Speech Lang Hear Res       Date:  2009-04       Impact factor: 2.297

9.  Do current statistical learning tasks capture stable individual differences in children? An investigation of task reliability across modality.

Authors:  Inbal Arnon
Journal:  Behav Res Methods       Date:  2020-02

10.  Statistical learning across development: flexible yet constrained.

Authors:  Lauren Krogh; Haley A Vlach; Scott P Johnson
Journal:  Front Psychol       Date:  2013-01-11
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  1 in total

1.  Which Cognitive Factors Predict L2 Grammar Learning: Cognitive Control, Statistical Learning, Working Memory, or Attention?

Authors:  Yao Chen; Li Li; Mengxing Wang; Ruiming Wang
Journal:  Front Psychol       Date:  2022-07-14
  1 in total

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