
Takashi Kuremoto
Nippon Institute of Technology, JapanPresentation Title:
Multiple-unit firing activity of hippocampal CA1 neurons expresses recent preceding experience
Abstract
The hippocampus plays an important role in the formation of episodic memory. To identify patterns of hippocampal firing activity specific to episodic memory, we performed EEG recognition using deep learning methods. Briefly, adult male rats habituated to the home cage experienced one of four experimental episodic stimuli (restraint stress, contact with a female rat, contact with a male rat, or contact with a novel object) for 10 minutes. Recorded brain spike signals (300–10 kHz) in hippocampal CA1 were classified using machine learning methods such as convolutional neural networks (CNN), support vector machines (SVM), deep learning model VGG16, and combination models composed of VGG16 with SVM or VGG19 with SVM. As a result, VGG19 with SVM successfully detected multiple unit activity (MUA) with ripple firings corresponding to specific episodes, achieving a validation accuracy of 96.79%. The results suggest that the EEG containing ripple firings corresponds to specific episodic memories. By capturing ripple firings, EEG analysis can assess and diagnose memory function, which may help detect various cognitive disorders.
Biography
Takashi Kuremoto received the B.E. degree in System Engineering at University of Shanghai for Science and Technology, China in 1986, and M.E. and Ph.D. degrees at Yamaguchi University, Japan in 1996 and 2014, respectively. He worked as a system engineer at Research Institute of Automatic Machine of Beijing from 1986 to 1992. He was an Academic Visitor of School of Computer Science, The University of Manchester, U.K. in 2008. He was an assistant professor in Division of Information Science and Engineering, Graduate School of Science and Technology for Innovation at Yamaguchi University, Japan, from 1997 to 2021. Currently he is a professor in Department of Information Technology and Media Design, Faculty of Advanced Engineering, Nippon Institute of Technology. His research interests include artificial neural networks, bioinformatics, machine learning, complex systems, time series forecasting and swarm intelligence and with more than 300 publications.