A Cortical Surface-Based Meta-Analysis (BMACS)
We developed a new meta-analysis method called Bayesian meta-analysis of the cortical surface (BMACS). BMACS offers a fast, accurate, and accessible inference of the spatial patterns of cognitive processes from peak brain activations across studies by applying spatial point processes to the cortical surface. We hope surface-based meta-analysis will be facilitated by BMACS, bringing more profound knowledge of various cognitive processes.
Project Lead: Minho Shin
A multifaceted verification of a MNI targeting protocol for neuronavigated TMS (in progress)
For transcranial magnetic stimulation (TMS), researchers conduct conventional MRI-guided neuronavigation by creating a “virtual link” between individuals’ heads and either their T1-weighted MR images (i.e., T1 protocol) or the standard MNI image (i.e., MNI protocol). The MNI protocol has been widely used as a convenient alternative to the T1 protocol when individuals’ T1 images are unavailable. However, its targeting accuracy and the compatibility between the T1 and MNI protocols remain unanswered. Therefore, we currently scrutinize the possibility of the interchangeability between the T1 and MNI protocols with multifauceted verification.
Project Lead: Hee Dong Yoon