A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.

Implicit learning (IL) occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigat...

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Autores principales:	Benjamin G Schultz, Catherine J Stevens, Peter E Keller, Barbara Tillmann
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9f6c058ffcd549a4a8a30a26aa6a8ffb
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spelling	oai:doaj.org-article:9f6c058ffcd549a4a8a30a26aa6a8ffb2021-11-18T08:53:46ZA sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.1932-620310.1371/journal.pone.0075163https://doaj.org/article/9f6c058ffcd549a4a8a30a26aa6a8ffb2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24086461/?tool=EBIhttps://doaj.org/toc/1932-6203Implicit learning (IL) occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigated in temporal pattern learning. Two experiments by Schultz, Stevens, Keller, and Tillmann demonstrated the IL of auditory temporal patterns using a serial reaction-time task and a generation task based on the process dissociation procedure. The generation task demonstrated that learning was implicit in both experiments via motor fluency, that is, the inability to suppress learned information. With the aim to disentangle conscious and unconscious processes, we analyze unreported recognition data associated with the Schultz et al. experiments using the sequence identification measurement model. The model assumes that perceptual fluency reflects unconscious processes and IL. For Experiment 1, the model indicated that conscious and unconscious processes contributed to recognition of temporal patterns, but that unconscious processes had a greater influence on recognition than conscious processes. In the model implementation of Experiment 2, there was equal contribution of conscious and unconscious processes in the recognition of temporal patterns. As Schultz et al. demonstrated IL in both experiments using a generation task, and the conditions reported here in Experiments 1 and 2 were identical, two explanations are offered for the discrepancy in model and behavioral results based on the two tasks: 1) perceptual fluency may not be necessary to infer IL, or 2) conscious control over implicitly learned information may vary as a function of perceptual fluency and motor fluency.Benjamin G SchultzCatherine J StevensPeter E KellerBarbara TillmannPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 9, p e75163 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Benjamin G Schultz Catherine J Stevens Peter E Keller Barbara Tillmann A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.
description	Implicit learning (IL) occurs unconsciously and without intention. Perceptual fluency is the ease of processing elicited by previous exposure to a stimulus. It has been assumed that perceptual fluency is associated with IL. However, the role of perceptual fluency following IL has not been investigated in temporal pattern learning. Two experiments by Schultz, Stevens, Keller, and Tillmann demonstrated the IL of auditory temporal patterns using a serial reaction-time task and a generation task based on the process dissociation procedure. The generation task demonstrated that learning was implicit in both experiments via motor fluency, that is, the inability to suppress learned information. With the aim to disentangle conscious and unconscious processes, we analyze unreported recognition data associated with the Schultz et al. experiments using the sequence identification measurement model. The model assumes that perceptual fluency reflects unconscious processes and IL. For Experiment 1, the model indicated that conscious and unconscious processes contributed to recognition of temporal patterns, but that unconscious processes had a greater influence on recognition than conscious processes. In the model implementation of Experiment 2, there was equal contribution of conscious and unconscious processes in the recognition of temporal patterns. As Schultz et al. demonstrated IL in both experiments using a generation task, and the conditions reported here in Experiments 1 and 2 were identical, two explanations are offered for the discrepancy in model and behavioral results based on the two tasks: 1) perceptual fluency may not be necessary to infer IL, or 2) conscious control over implicitly learned information may vary as a function of perceptual fluency and motor fluency.
format	article
author	Benjamin G Schultz Catherine J Stevens Peter E Keller Barbara Tillmann
author_facet	Benjamin G Schultz Catherine J Stevens Peter E Keller Barbara Tillmann
author_sort	Benjamin G Schultz
title	A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.
title_short	A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.
title_full	A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.
title_fullStr	A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.
title_full_unstemmed	A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.
title_sort	sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/9f6c058ffcd549a4a8a30a26aa6a8ffb
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A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.

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