A Study on Deep Learning Models for Estimating Brain Activities evoked by Visual Stimuli
画像刺激下の脳活動状態推定における深層学習モデルの基礎的考察

Haruka Taguchi, Satoshi Nishida, Shinji Nishida, Ichiro Kobayashi
2021
The purpose of this study is to estimate the state in the human brain when image stimuli are given, and in particular, we will verify the estimation accuracy and visualization results by various deep learning models for image processing as a working model. The human brain activity when images are shown to a subject is observed using fMRI, the same image is input to various deep learning models for image identification, and the representation of those intermediate layers is regressed to the
more » ... activity state. By this, we examine the difference in estimation accuracy for each deep learning model through visualization, and investigate the characteristics of deep learning models when estimating the human brain activity evoked by visual stimuli.
doi:10.14864/fss.37.0_261 fatcat:wfok3yqao5fs7aguklrykcqagi