Variational Bayesian MultimodalEncephaloGraphy (VBMEG): Its Theory and Applications
作者： Taku Yoshioka , Masa-aki Sato
DOI: 10.3902/JNNS.18.214
关键词:
摘要: fMRIは高い空間分解能を持つが時間分解能が低い． 一方，MEGは高い時間分解能を持つが空間分解能が低い． 我々はfMRIとMEGを組み合わせる事により高い時空間分解能で脳活動を推定する階層変分ベイズ推定法（Variational Bayesian MultimodalEncephaloGraphy；VBMEG）を提案した． 本稿ではVBMEGの原理について説明し，実際の応用例を紹介する．
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