
Functional network activity during errorless and trial‐and‐error color‐name association learning
Author(s) -
Yamashita Madoka,
Shimokawa Tetsuya,
Peper Ferdinand,
Tanemura Rumi
Publication year - 2020
Publication title -
brain and behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.915
H-Index - 41
ISSN - 2162-3279
DOI - 10.1002/brb3.1723
Subject(s) - default mode network , functional magnetic resonance imaging , psychology , association (psychology) , cognition , functional connectivity , neuroscience , artificial intelligence , computer science , cognitive psychology , psychotherapist
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.