A Study on Deep Learning Models for Estimating Brain Activities evoked by Visual Stimuli

Abstract

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 brain 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.