Literature DB >> 25192632

Implicit and explicit statistical learning of tone sequences across spectral shifts.

Tatsuya Daikoku1, Yutaka Yatomi1, Masato Yumoto2.   

Abstract

We investigated how the statistical learning of auditory sequences is reflected in neuromagnetic responses in implicit and explicit learning conditions. Complex tones with fundamental frequencies (F0s) in a five-tone equal temperament were generated by a formant synthesizer. The tones were subsequently ordered with the constraint that the probability of the forthcoming tone was statistically defined (80% for one tone; 5% for the other four) by the latest two successive tones (second-order Markov chains). The tone sequence consisted of 500 tones and 250 successive tones with a relative shift of F0s based on the same Markov transitional matrix. In explicit and implicit learning conditions, neuromagnetic responses to the tone sequence were recorded from fourteen right-handed participants. The temporal profiles of the N1m responses to the tones with higher and lower transitional probabilities were compared. In the explicit learning condition, the N1m responses to tones with higher transitional probability were significantly decreased compared with responses to tones with lower transitional probability in the latter half of the 500-tone sequence. Furthermore, this difference was retained even after the F0s were relatively shifted. In the implicit learning condition, N1m responses to tones with higher transitional probability were significantly decreased only for the 250 tones following the relative shift of F0s. The delayed detection of learning effects across the sound-spectral shift in the implicit condition may imply that learning may progress earlier in explicit learning conditions than in implicit learning conditions. The finding that the learning effects were retained across spectral shifts regardless of the learning modality indicates that relative pitch processing may be an essential ability for humans.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Implicit and explicit learning; Magnetoencephalography; Markov process; Relative pitch; Statistical learning

Mesh:

Year:  2014        PMID: 25192632     DOI: 10.1016/j.neuropsychologia.2014.08.028

Source DB:  PubMed          Journal:  Neuropsychologia        ISSN: 0028-3932            Impact factor:   3.139


  12 in total

1.  Functional connectivity of the cortical network supporting statistical learning in musicians and non-musicians: an MEG study.

Authors:  Evangelos Paraskevopoulos; Nikolas Chalas; Panagiotis Bamidis
Journal:  Sci Rep       Date:  2017-11-24       Impact factor: 4.379

Review 2.  Neurophysiological Markers of Statistical Learning in Music and Language: Hierarchy, Entropy, and Uncertainty.

Authors:  Tatsuya Daikoku
Journal:  Brain Sci       Date:  2018-06-19

3.  When the statistical MMN meets the physical MMN.

Authors:  Vera Tsogli; Sebastian Jentschke; Tatsuya Daikoku; Stefan Koelsch
Journal:  Sci Rep       Date:  2019-04-03       Impact factor: 4.379

4.  Tonality Tunes the Statistical Characteristics in Music: Computational Approaches on Statistical Learning.

Authors:  Tatsuya Daikoku
Journal:  Front Comput Neurosci       Date:  2019-10-02       Impact factor: 2.380

5.  Under the hood of statistical learning: A statistical MMN reflects the magnitude of transitional probabilities in auditory sequences.

Authors:  Stefan Koelsch; Tobias Busch; Sebastian Jentschke; Martin Rohrmeier
Journal:  Sci Rep       Date:  2016-02-02       Impact factor: 4.379

6.  Single, but not dual, attention facilitates statistical learning of two concurrent auditory sequences.

Authors:  Tatsuya Daikoku; Masato Yumoto
Journal:  Sci Rep       Date:  2017-08-31       Impact factor: 4.379

7.  Time-course variation of statistics embedded in music: Corpus study on implicit learning and knowledge.

Authors:  Tatsuya Daikoku
Journal:  PLoS One       Date:  2018-05-09       Impact factor: 3.240

8.  Motor Reproduction of Time Interval Depends on Internal Temporal Cues in the Brain: Sensorimotor Imagery in Rhythm.

Authors:  Tatsuya Daikoku; Yuji Takahashi; Nagayoshi Tarumoto; Hideki Yasuda
Journal:  Front Psychol       Date:  2018-10-02

9.  Musical Creativity and Depth of Implicit Knowledge: Spectral and Temporal Individualities in Improvisation.

Authors:  Tatsuya Daikoku
Journal:  Front Comput Neurosci       Date:  2018-11-13       Impact factor: 2.380

10.  Concurrent Statistical Learning of Ignored and Attended Sound Sequences: An MEG Study.

Authors:  Tatsuya Daikoku; Masato Yumoto
Journal:  Front Hum Neurosci       Date:  2019-04-17       Impact factor: 3.169

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