Literature DB >> 29634990

ERPs differentiate the sensitivity to statistical probabilities and the learning of sequential structures during procedural learning.

Andrea Kóbor1, Ádám Takács2, Zsófia Kardos3, Karolina Janacsek4, Kata Horváth5, Valéria Csépe3, Dezso Nemeth6.   

Abstract

Procedural learning facilitates the efficient processing of complex environmental stimuli and contributes to the acquisition of automatic behaviors. Although earlier findings suggest different temporal trajectories of the multiple learning processes within procedural learning, this has not been clarified at the level of neurocognitive correlates. Therefore, we investigated whether two prominent learning processes - statistical learning and sequence learning - can be distinguished using event-related brain potentials (ERPs) within the same experimental setting. Healthy young adults (N = 40) performed the Alternating Serial Reaction Time task while RTs and ERPs were measured time-locked to the onset of the task's stimuli. Both RT and N2 effects reflected the rapid acquisition of statistical probabilities. At the same time, these effects reflected the gradual learning of sequential structures. The amplitude change of the P3 reflected only gradual sequence learning. The P1 component was sensitive to both learning processes, which did not change as the task progressed. Our results altogether indicate that statistical learning and sequence learning develop differently at the level of both ERPs and overt responses. These findings could provide insight to the dynamic change of multiple parallel learning processes that occur during procedural memory formation.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  N2; P1; P3; Procedural learning; Sequence learning; Statistical learning

Mesh:

Year:  2018        PMID: 29634990     DOI: 10.1016/j.biopsycho.2018.04.001

Source DB:  PubMed          Journal:  Biol Psychol        ISSN: 0301-0511            Impact factor:   3.251


  12 in total

1.  Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data.

Authors:  Noslen Hernández; Aline Duarte; Guilherme Ost; Ricardo Fraiman; Antonio Galves; Claudia D Vargas
Journal:  Sci Rep       Date:  2021-02-10       Impact factor: 4.379

2.  Rational arbitration between statistics and rules in human sequence processing.

Authors:  Maxime Maheu; Florent Meyniel; Stanislas Dehaene
Journal:  Nat Hum Behav       Date:  2022-05-02

3.  Speed and accuracy instructions affect two aspects of skill learning differently.

Authors:  Teodóra Vékony; Claire Pleche; Orsolya Pesthy; Karolina Janacsek; Dezso Nemeth
Journal:  NPJ Sci Learn       Date:  2022-10-22

4.  Different levels of statistical learning - Hidden potentials of sequence learning tasks.

Authors:  Emese Szegedi-Hallgató; Karolina Janacsek; Dezso Nemeth
Journal:  PLoS One       Date:  2019-09-19       Impact factor: 3.240

5.  Tracking the implicit acquisition of nonadjacent transitional probabilities by ERPs.

Authors:  Andrea Kóbor; Kata Horváth; Zsófia Kardos; Ádám Takács; Karolina Janacsek; Valéria Csépe; Dezso Nemeth
Journal:  Mem Cognit       Date:  2019-11

6.  Divided attention does not affect the acquisition and consolidation of transitional probabilities.

Authors:  Kata Horváth; Csenge Török; Orsolya Pesthy; Dezso Nemeth; Karolina Janacsek
Journal:  Sci Rep       Date:  2020-12-31       Impact factor: 4.379

7.  Regularity detection under stress: Faster extraction of probability-based regularities.

Authors:  Eszter Tóth-Fáber; Karolina Janacsek; Ágnes Szőllősi; Szabolcs Kéri; Dezso Nemeth
Journal:  PLoS One       Date:  2021-06-15       Impact factor: 3.240

8.  Deconstructing Procedural Memory: Different Learning Trajectories and Consolidation of Sequence and Statistical Learning.

Authors:  Peter Simor; Zsofia Zavecz; Kata Horváth; Noémi Éltető; Csenge Török; Orsolya Pesthy; Ferenc Gombos; Karolina Janacsek; Dezso Nemeth
Journal:  Front Psychol       Date:  2019-01-09

9.  Not All Words Are Equally Acquired: Transitional Probabilities and Instructions Affect the Electrophysiological Correlates of Statistical Learning.

Authors:  Ana Paula Soares; Francisco-Javier Gutiérrez-Domínguez; Margarida Vasconcelos; Helena M Oliveira; David Tomé; Luis Jiménez
Journal:  Front Hum Neurosci       Date:  2020-09-23       Impact factor: 3.169

10.  Neurophysiological and functional neuroanatomical coding of statistical and deterministic rule information during sequence learning.

Authors:  Ádám Takács; Andrea Kóbor; Zsófia Kardos; Karolina Janacsek; Kata Horváth; Christian Beste; Dezso Nemeth
Journal:  Hum Brain Mapp       Date:  2021-04-02       Impact factor: 5.038

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