A Simulation Method of Magnetic Treatment to Depressed Brain based on Chaotic Network

DOI

10.2991/icmeit-19.2019.57How to use a DOI?

Keywords

chaotic network; simulation; electromagnetic stimulus; brain region.

Abstract

Chaotic neural network has a wide range of applications, especially in uncertain time-series prediction. Aihara Neural Network takes refractoriness into consideration and shows superiority in solution to TSP. The inspiration was from peers’ work on specifically targeted on deep brain by nanometre materials. We defined a complex system with 16 brain regions related to depression. Based on BOLD signals, we reconstructed the connectivity matrix and the parameters and applied modeled signals as irritation to specific region to provide a model prototype. The comparison between Power Spectral Entropy before and after irritation indicates the relation between physical irritation and curative effect. The results proved the obligation to implement multi-point treatment.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yunchuan Huang
AU  - Yu Zhou
AU  - Huaze Tang
PY  - 2019/04
DA  - 2019/04
TI  - A Simulation Method of Magnetic Treatment to Depressed Brain based on Chaotic Network
BT  - Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SP  - 343
EP  - 348
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.57
DO  - 10.2991/icmeit-19.2019.57
ID  - Huang2019/04
ER  -