[2B1] [General Session] 1. Basis / Theory

[2B1-03] Creating Artificial Brain Activity Data Based on Mutual Data Transformation between Different Subjects

〇Kaei Cho¹, Ichiro Kobayashi¹, Shinji Nishimoto², Satoshi Nishida², Hideki Asoh³ (1. Ochanomizu University, 2. National Institute of Information and Communications Technology, 3. National Institute of Advanced Industrial Science and Technology)

Keywords:Brain Science

Quantitative analysis of human brain activity has been actively studied in brain and neuroscience. In the analysis, there has recently been getting many opportunities that deep leaning is applied to deal with brain activity data observed with fMRI. Whereas, it costs expensive to collect such data and this always causes the lack of enough data to train a model in deep learning framework. With this background, we aim to artificially increase the number of such data and apply them to a caption generation task with deep learning for raising the accuracy of the model.