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Chunking improves symbolic sequence processing and relies on working memory gating mechanisms

Chunking, namely the grouping of sequence elements in clusters, is ubiquitous during sequence processing, but its impact on performance remains debated. Here, we found that participants who adopted a consistent chunking strategy during symbolic sequence learning showed a greater improvement of their...

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Detalles Bibliográficos
Autores principales: Solopchuk, Oleg, Alamia, Andrea, Olivier, Etienne, Zénon, Alexandre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4755266/
https://www.ncbi.nlm.nih.gov/pubmed/26884228
http://dx.doi.org/10.1101/lm.041277.115
Descripción
Sumario:Chunking, namely the grouping of sequence elements in clusters, is ubiquitous during sequence processing, but its impact on performance remains debated. Here, we found that participants who adopted a consistent chunking strategy during symbolic sequence learning showed a greater improvement of their performance and a larger decrease in cognitive workload over time. Stronger reliance on chunking was also associated with higher scores in a WM updating task, suggesting the contribution of WM gating mechanisms to sequence chunking. Altogether, these results indicate that chunking is a cost-saving strategy that enhances effectiveness of symbolic sequence learning.