TY - JOUR
T1 - Brain decoding in multiple languages
T2 - Can cross-language brain decoding work?
AU - Xu, Min
AU - Li, Duo
AU - Li, Ping
N1 - Funding Information:
Preparation of this article was made possible by grants from the National Science Foundation (BCS-1533625), a Faculty Startup Fund from the Hong Kong Polytechnic University, the Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team (grant no. 2016ZT06S220), National Natural Science Foundation of China (31700951) and Shenzhen Basic Research Scheme (JCYJ20170412164259361).
Funding Information:
Preparation of this article was made possible by grants from the National Science Foundation ( BCS-1533625 ), a Faculty Startup Fund from the Hong Kong Polytechnic University , the Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team (grant no. 2016ZT06S220 ), National Natural Science Foundation of China ( 31700951 ) and Shenzhen Basic Research Scheme ( JCYJ20170412164259361 ).
Publisher Copyright:
© 2021 The Authors
PY - 2021/4
Y1 - 2021/4
N2 - The approach of cross-language brain decoding is to use models of brain decoding from one language to decode stimuli of another language. It has the potential to provide new insights into how our brain represents multiple languages. While it is possible to decode semantic information across different languages from neuroimaging data, the approach's overall success remains to be tested and depends on a number of factors such as cross-language similarity, age of acquisition/proficiency levels, and depth of language processing. We expect to see continued progress in this domain, from a traditional focus on words and concrete concepts toward the use of naturalistic experimental tasks involving higher-level language processing (e.g., discourse processing). The approach can also be applied to understand how cross-modal, cross-cultural, and other nonlinguistic factors may influence neural representations of different languages. This article provides an overview of cross-language brain decoding with suggestions for future research directions.
AB - The approach of cross-language brain decoding is to use models of brain decoding from one language to decode stimuli of another language. It has the potential to provide new insights into how our brain represents multiple languages. While it is possible to decode semantic information across different languages from neuroimaging data, the approach's overall success remains to be tested and depends on a number of factors such as cross-language similarity, age of acquisition/proficiency levels, and depth of language processing. We expect to see continued progress in this domain, from a traditional focus on words and concrete concepts toward the use of naturalistic experimental tasks involving higher-level language processing (e.g., discourse processing). The approach can also be applied to understand how cross-modal, cross-cultural, and other nonlinguistic factors may influence neural representations of different languages. This article provides an overview of cross-language brain decoding with suggestions for future research directions.
KW - Computational modeling
KW - Cross-language brain decoding
KW - Multilingualism
KW - Multivariate pattern analysis
KW - Neural representation
UR - https://www.scopus.com/pages/publications/85100418321
U2 - 10.1016/j.bandl.2021.104922
DO - 10.1016/j.bandl.2021.104922
M3 - Journal article
AN - SCOPUS:85100418321
SN - 0093-934X
VL - 215
JO - Brain and Language
JF - Brain and Language
M1 - 104922
ER -