Literature DB >> 21574745

Learning across senses: cross-modal effects in multisensory statistical learning.

Aaron D Mitchel1, Daniel J Weiss.   

Abstract

It is currently unknown whether statistical learning is supported by modality-general or modality-specific mechanisms. One issue within this debate concerns the independence of learning in one modality from learning in other modalities. In the present study, the authors examined the extent to which statistical learning across modalities is independent by simultaneously presenting learners with auditory and visual streams. After establishing baseline rates of learning for each stream independently, they systematically varied the amount of audiovisual correspondence across 3 experiments. They found that learners were able to segment both streams successfully only when the boundaries of the audio and visual triplets were in alignment. This pattern of results suggests that learners are able to extract multiple statistical regularities across modalities provided that there is some degree of cross-modal coherence. They discuss the implications of their results in light of recent claims that multisensory statistical learning is guided by modality-independent mechanisms. (c) 2011 APA, all rights reserved.

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Year:  2011        PMID: 21574745      PMCID: PMC4041380          DOI: 10.1037/a0023700

Source DB:  PubMed          Journal:  J Exp Psychol Learn Mem Cogn        ISSN: 0278-7393            Impact factor:   3.051


  32 in total

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Review 3.  Multisensory integration: current issues from the perspective of the single neuron.

Authors:  Barry E Stein; Terrence R Stanford
Journal:  Nat Rev Neurosci       Date:  2008-04       Impact factor: 34.870

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Review 5.  Benefits of multisensory learning.

Authors:  Ladan Shams; Aaron R Seitz
Journal:  Trends Cogn Sci       Date:  2008-11       Impact factor: 20.229

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Journal:  Curr Opin Neurobiol       Date:  1998-04       Impact factor: 6.627

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Journal:  Child Dev       Date:  2005 May-Jun

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Authors:  Juan M Toro; Scott Sinnett; Salvador Soto-Faraco
Journal:  Cognition       Date:  2005-04-18

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Authors:  Nicholas B Turk-Browne; Phillip J Isola; Brian J Scholl; Teresa A Treat
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2008-03       Impact factor: 3.051

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  18 in total

Review 1.  Domain generality versus modality specificity: the paradox of statistical learning.

Authors:  Ram Frost; Blair C Armstrong; Noam Siegelman; Morten H Christiansen
Journal:  Trends Cogn Sci       Date:  2015-01-24       Impact factor: 20.229

2.  Task-irrelevant auditory metre shapes visuomotor sequential learning.

Authors:  Alexis Deighton MacIntyre; Hong Ying Josephine Lo; Ian Cross; Sophie Scott
Journal:  Psychol Res       Date:  2022-06-12

3.  Anchors aweigh: The impact of overlearning on entrenchment effects in statistical learning.

Authors:  Federica Bulgarelli; Daniel J Weiss
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2016-03-07       Impact factor: 3.051

4.  Visual speech segmentation: using facial cues to locate word boundaries in continuous speech.

Authors:  Aaron D Mitchel; Daniel J Weiss
Journal:  Lang Cogn Process       Date:  2014

5.  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

6.  Multimodal integration in statistical learning: evidence from the McGurk illusion.

Authors:  Aaron D Mitchel; Morten H Christiansen; Daniel J Weiss
Journal:  Front Psychol       Date:  2014-05-16

7.  Differential Gaze Patterns on Eyes and Mouth During Audiovisual Speech Segmentation.

Authors:  Laina G Lusk; Aaron D Mitchel
Journal:  Front Psychol       Date:  2016-02-02

8.  Smaller = denser, and the brain knows it: natural statistics of object density shape weight expectations.

Authors:  Megan A K Peters; Jonathan Balzer; Ladan Shams
Journal:  PLoS One       Date:  2015-03-13       Impact factor: 3.240

9.  Cross-Domain Statistical-Sequential Dependencies Are Difficult to Learn.

Authors:  Anne M Walk; Christopher M Conway
Journal:  Front Psychol       Date:  2016-02-25

10.  Learning predictive statistics from temporal sequences: Dynamics and strategies.

Authors:  Rui Wang; Yuan Shen; Peter Tino; Andrew E Welchman; Zoe Kourtzi
Journal:  J Vis       Date:  2017-10-01       Impact factor: 2.240

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