Sun Mi Park1,
Francesca Branzoli2, Misun Kim1, Hyerin Lim1,
Matthias J.P. van Osch2, Itamar Ronen2, Dae-Shik Kim1
1Department
of Electrical Engineering, Korea Advanced Institute of Science and
Technology, Daejeon, Korea; 2C. J. Gorter Center for High-field MRI,
Department of Radiology, Leiden University Medical Center, Leiden,
Netherlands
Although Multi-voxel pattern analysis (MVPA) has been widely studied to classify recognizing object categories, the signal characteristic of distributed patterns on the human ventral stream remains elusive. Ultra-high field MRI enables imaging at higher spatial resolution and improved localization, thereby potentially leading to improved discrimination between different neuronal patterns. Our results showed that the distributed patterns of 7T BOLD fMRI were better to distinguish each object category than 3T despite equal spatial resolution to provide fair comparison. It has been hypothesized that improving SNR and signal localization at 7T BOLD fMRI resulted in improved discrimination in MVPA methods.