• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2018 Fiscal Year Final Research Report

Empirical proof of multiplex communication identification in cultured neuronal network

Research Project

  • PDF
Project/Area Number 16K12524
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeMulti-year Fund
Research Field Life / Health / Medical informatics
Research InstitutionOsaka University

Principal Investigator

Tamura Shinichi  大阪大学, その他部局等, 名誉教授 (30029540)

Project Period (FY) 2016-04-01 – 2019-03-31
Keywords神経回路網 / 多重通信 / 機械学習 / スパイク波 / 神経の揺らぎ / リレーニューロン / 培養神経回路網 / シミュレーション
Outline of Final Research Achievements

As an intermediate level approach between AI and neuroscience, behaviors of artificial neural network have been elucidated. However, since functions of the neural network have not been enough elucidated, we are studying the intermediate level function of the neural network focused on signal transmission or communication function. In 25×25 mesh neural network simulation, we have confirmed it is possible to set asynchronous multiplex communication channel such as 9:9. Corresponding to these, we showed we can set communication channels such as 3:n in wet experiments on cultured neuronal networks. That is, several receiving neurons (group) away from the stimulated neurons (group) could classify/recognize what kind of stimulation was added based on the arrived spike waves. Both of the simulation in artificial neural networks and the experiment in cultured neuronal networks support the multiplex communication scheme in the brain.

Free Research Field

医用画像解析,人工知能,情報科学

Academic Significance and Societal Importance of the Research Achievements

脳神経回路について,マクロ的視点からは,AIや深層学習の研究が進んできた.ミクロ的視点からは,神経自体の特性や動作,また中間レベルの神経回路網の特性や振る舞いについてもよく研究されてきた.しかしながら神経回路網の機能については十分研究されていない.本研究は,情報伝達・通信の視点から,シミュレーションと,培養神経回路の対応を取りつつ,神経回路網の機能について研究を行ってきたものである.
その結果,神経回路網では空間的多重通信が行われているであろうことが結論された.これはシミュレーションと培養神経における実験の両面から,神経回路網内の多重通信原理を指摘・解明した最初の研究である.

URL: 

Published: 2020-03-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi