| Presentation | 2019-06-17 Meta-analysis fMRI data helps robust source reconstruction of MEG measurements Keita Suzuki, Okito Yamashita, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) are the major recording means of brain activity. FMRI records brain activity with high spatial resolution but its temporal resolution is low due to slow hemodynamic responses to neural activity. Conversely, MEG has characteristics that the temporal resolution is high but spatial resolution is low. One of the solution is combining both records of fMRI and MEG so that we can estimate high spatio-temporal brain activity. However, taking into consideration the measurement cost and the burden on the subject, it is difficult to obtain high quality measurement data of both modalities. Therefore, we propose combining MEG data with meta-analysis fMRI instead of measured one. And also, we developed realistic simulation framework to evaluate our proposal. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | MEG / source reconstruction / variational Bayesian / meta-analysis |
| Paper # | NC2019-5 |
| Date of Issue | 2019-06-10 (NC) |
| Conference Information | |
| Committee | NC / IBISML / IPSJ-MPS / IPSJ-BIO |
|---|---|
| Conference Date | 2019/6/17(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Institute of Science and Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Neurocomputing, Machine Learning Approach to Biodata Mining, and General |
| Chair | Hayaru Shouno(UEC) / Hisashi Kashima(Kyoto Univ.) / Masakazu Sekijima(Tokyo Tech) / Hiroyuki Kurata(Kyutech) |
| Vice Chair | Kazuyuki Samejima(Tamagawa Univ) / Masashi Sugiyama(Univ. of Tokyo) / Koji Tsuda(Univ. of Tokyo) |
| Secretary | Kazuyuki Samejima(NAIST) / Masashi Sugiyama(NTT) / Koji Tsuda(Nagoya Inst. of Tech.) / (AIST) / (Nagoya Univ.) |
| Assistant | Takashi Shinozaki(NICT) / Ken Takiyama(TUAT) / Tomoharu Iwata(NTT) / Shigeyuki Oba(Kyoto Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on Infomation-Based Induction Sciences and Machine Learning / IPSJ Special Interest Group on Mathematical Modeling and Problem Solving / IPSJ Special Interest Group on Bioinformatics and Genomics |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Meta-analysis fMRI data helps robust source reconstruction of MEG measurements |
| Sub Title (in English) | |
| Keyword(1) | MEG |
| Keyword(2) | source reconstruction |
| Keyword(3) | variational Bayesian |
| Keyword(4) | meta-analysis |
| 1st Author's Name | Keita Suzuki |
| 1st Author's Affiliation | Nara Institute of Science and Technology(NAIST) |
| 2nd Author's Name | Okito Yamashita |
| 2nd Author's Affiliation | Advanced Telecommunications Research Institute International(ATR) |
| Date | 2019-06-17 |
| Paper # | NC2019-5 |
| Volume (vol) | vol.119 |
| Number (no) | NC-88 |
| Page | pp.pp.21-25(NC), |
| #Pages | 5 |
| Date of Issue | 2019-06-10 (NC) |