Common and Segregated Neuronal Networks for Different Languages Revealed Using Functional Magnetic Resonance Adaptation

• Published in: Journal of cognitive neuroscience 2003-01, Vol.15 (1), p.85-97
• Main Authors: Chee, Michael W. L., Soon, Chun Siong, Lee, Hwee Ling
• Format: Article
• Language: English
• Subjects: Adaptation, Psychological - physiology; Adult; Anatomical correlates of behavior; Behavioral psychophysiology; Biological and medical sciences; Brain Mapping; Discrimination (Psychology); Evoked Potentials - physiology; Female; Functional Laterality; Fundamental and applied biological sciences. Psychology; Humans; Languages; Magnetic Resonance Imaging - methods; Male; Multilingualism; Nerve Net - physiology; Neural networks; NMR; Nuclear magnetic resonance; Paired-Associate Learning; Photic Stimulation; Prefrontal Cortex - anatomy & histology; Prefrontal Cortex - physiology; Psychology. Psychoanalysis. Psychiatry; Psychology. Psychophysiology; Reaction Time; Semantics
• ISSN: 0898-929X; 1530-8898
• DOI: 10.1162/089892903321107846

The effect of word repetition within and across languages was studied in English-Chinese bilinguals who read rapidly presented word pairs in a block design and an event-related fMRI study. Relatively less increase in MR signal was observed when the second word in a pair was identical in meaning to the first. This occurred in the English-only and mixed-languages conditions. Repetition-induced reductions in BOLD signal change were found in the left lateral prefrontal and lateral temporal regions in both types of conditions in the block experiment, suggesting that processing in these regions is sensitive to semantic features present in words and characters, and that part of the semantic neuronal networks serving English and Chinese is shared. In addition, these regions showed greater absolute signal change in the mixed-languages trials relative to the English-only trials. These findings were mostly replicated in an event-related experiment. Together, the experiments suggest that while the networks for Chinese and English word processing have shared components, there are also components that may be language specific.