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Functional network activity during errorless and trial‐and‐error color‐name association learning

INTRODUCTION: In cognitive rehabilitation, errorless (EL) and trial‐and‐error (T&E) learning are well‐known methods, but their neural mechanisms are not well known. In this study, we investigated functional magnetic resonance imaging data for healthy adults during EL and T&E learning. METHOD...

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Detalles Bibliográficos
Autores principales: Yamashita, Madoka, Shimokawa, Tetsuya, Peper, Ferdinand, Tanemura, Rumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7428483/
https://www.ncbi.nlm.nih.gov/pubmed/32558312
http://dx.doi.org/10.1002/brb3.1723
Descripción
Sumario:INTRODUCTION: In cognitive rehabilitation, errorless (EL) and trial‐and‐error (T&E) learning are well‐known methods, but their neural mechanisms are not well known. In this study, we investigated functional magnetic resonance imaging data for healthy adults during EL and T&E learning. METHODS: Participants memorized color‐name associations in both methods using Japanese traditional colors which were unfamiliar to study participants. A functional network analysis was conducted by applying graph theory. We focused on two major cognitive networks: the default mode network (DMN) and the fronto‐parietal network (FPN). Also, we used “within‐network connectivity” and “between‐network connectivity” graph metrics. The former represents the functional connectivity strength of a subnetwork, namely the within‐DMN connectivity and within‐FPN connectivity, while the latter represents the number of links between the DMN and FPN. RESULTS: The within‐DMN connectivity in T&E learning was significantly higher than in EL learning. The difference between the memory scores of EL and T&E learning weakly correlated with the between‐network connectivity differences between both learning tasks. CONCLUSIONS: Our results suggest that within‐DMN connectivity is important in T&E learning and that the learning benefit differences between EL and T&E approaches potentially relate to the functional integration strength between the DMN and FPN.