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The right superior temporal gyrus plays a role in semantic-rule learning: Evidence supporting a reinforcement learning model

Authors :
Linyan Liu
Dongxue Liu
Tingting Guo
John W. Schwieter
Huanhuan Liu
Source :
NeuroImage, Vol 282, Iss , Pp 120393- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

In real-life communication, individuals use language that carries evident rewarding and punishing elements, such as praise and criticism. A common trend is to seek more praise while avoiding criticism. Furthermore, semantics is crucial for conveying information, but such semantic access to native and foreign languages is subtly distinct. To investigate how rule learning occurs in different languages and to highlight the importance of semantics in this process, we investigated both verbal and non-verbal rule learning in first (L1) and second (L2) languages using a reinforcement learning framework, including a semantic rule and a color rule. Our computational modeling on behavioral and brain imaging data revealed that individuals may be more motivated to learn and adhere to rules in an L1 compared to L2, with greater striatum activation during the outcome phase in the L1. Additionally, results on the learning rates and inverse temperature in the two rule learning tasks showed that individuals tend to be conservative and are reluctant to change their judgments regarding rule learning of semantic information. Moreover, the greater the prediction errors, the greater activation of the right superior temporal gyrus in the semantic-rule learning condition, demonstrating that such learning has differential neural correlates than symbolic rule learning. Overall, the findings provide insight into the neural mechanisms underlying rule learning in different languages, and indicate that rule learning involving verbal semantics is not a general symbolic learning that resembles a conditioned stimulus-response, but rather has its own specific characteristics.

Details

Language :
English
ISSN :
10959572
Volume :
282
Issue :
120393-
Database :
Directory of Open Access Journals
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
edsdoj.730fb908886c420c92a2633e77c55916
Document Type :
article
Full Text :
https://doi.org/10.1016/j.neuroimage.2023.120393