Neural impact of native language literacy on the processing of non-native languages. Evidence from Chinese-English-Japanese and Vietnamese-English-Japanese trilinguals

2020 Fiscal Year Research-status Report

• Project/Area Number: 18K00687
• Research Institution: Kyoto University
• Principal Investigator: ディン ティ 京都大学, 医学研究科, 研究員 (30602073)
• Co-Investigator(Kenkyū-buntansha): 中村 仁洋 国立障害者リハビリテーションセンター(研究所), 研究所 脳機能系障害研究部, 主任研究官 (40359633) ; 藤本 晃司 京都大学, 医学研究科, 特定准教授 (10580110) ; 岡田 知久 京都大学, 医学研究科, 特定准教授 (30321607)
• Project Period (FY): 2018-04-01 – 2022-03-31
• Keywords: fMRI / 7T MRI / denoising / bilingual

Outline of Annual Research Achievements

This year, we mainly analyzed the data for investigating the optimized acquisition parameters at our 7T MRI. Head motion during the acquisition of fMRI data is well known as a significantly contaminated noise, we firstly applied ICA technique to denoise our data and investigated the influence of head motion on the output of ICA-based denoising. We also clarified the relationships between the ICA output with the framewise displacement (FD) variable, a well-known cut-off threshold for excluding high motion-related fMRI datasets. Our results, for the first time, showed that there was a strong correlation between the number of total ICA components with head motion and FD. We believe that the number of ICA components can be used as a new index for detecting high motion-related fMRI datasets.

Current Status of Research Progress

3: Progress in research has been slightly delayed.

Reason

Because the ultra high field 7T-MRI scanner is a very new device in the MRI research field. Although it is well known that the signal-to-noise ratio (SNR) is increasing at 7T MRI, the sensitivity to temporal fluctuation (i.e., noise) is also increasing which can easily induce the false positive activation. Therefore, denoising fMRI datasets obtained at 7T-MRI scanner has become an initial and critical step for data analysis. Unfortunately, there are few references on the denoising issue for the data obtained at 7T-MRI with different acquisition parameters as in our study. Therefore, as the pilot study in this field, finding out appropriate methods for denoising analysis took longer time than we initially planned.

Strategy for Future Research Activity

Because we could successfully denoised our data, we will continue to finish the data analysis for comparing the brain activation patterns of the different acquisition parameters in order to decide the best acquisition parameter set for obtaining the fMRI data at 7T-MRI. Then after, we will recruit the bilingual subjects for our main experiments. The recruitment will be conducted at universities in Kyoto, Osaka or Kansai areas for collecting high-qualified bilingual subjects (Chinese or Vietnamese native speakers who can speak Japanese and English fluently). The bilingual MRI experiment will be done in 2021 year.

Causes of Carryover

This year we mainly performed the data analysis, therefore, the amount of the money which was planned to be used for MRI using fee and compensation fee for participants were not completely used as initially planned.