Export file:


  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text


  • Citation Only
  • Citation and Abstract

Learning process for identifying different types of communication via repetitive stimulation: feasibility study in a cultured neuronal network

1 Department of Radiology, Graduate School of Medicine, Osaka University, Suita 565-0871, Japan
2 Graduate School of Science Osaka City University, Osaka, 558-8585, Japan
3 Graduate School of Applied Informatics, University of Hyogo, Kobe 650-0044, Japan
4 Department of Integrative Physiology, Graduate School of Medicine, Osaka University, Suita 565-0871, Japan
5 NBL Technovator Co., Ltd., 631 Shindachimakino, Sennan 590-0522, Japan

It is well known that various types of information can be learned and memorized via repetitive training. In brain information science, it is very important to determine how neuronal networks comprising neurons with fluctuating characteristics reliably learn and memorize information. The aim of this study is to investigate the learning process in cultured neuronal networks and to address the question described above. Previously, we reported that the spikes resulting from stimulation at a specific neuron propagate as a cluster of excitation waves called spike wave propagation in cultured neuronal networks. We also reported that these waves have an individual spatiotemporal pattern that varies according to the type of neuron that is stimulated. Therefore, different spike wave propagations can be identified via pattern analysis of spike trains at particular neurons. Here, we assessed repetitive stimulation using intervals of 0.5 and 1.5 ms. Subsequently, we analyzed the relationship between the repetition of the stimulation and the identification of the different spike wave propagations. We showed that the various spike wave propagations were identified more precisely after stimulation was repeated several times using an interval of 1.5 ms. These results suggest the existence of a learning process in neuronal networks that occurs via repetitive training using a suitable interval.
  Article Metrics
Download full text in PDF

Export Citation

Article outline

Copyright © AIMS Press All Rights Reserved