DocumentCode :
3684816
Title :
Bidirectional neural interface: Closed-loop feedback control for hybrid neural systems
Author :
Zane Chou;Jeffrey Lim;Sophie Brown;Melissa Keller;Joseph Bugbee;Frédéric D. Broccard;Massoud L. Khraiche;Gabriel A. Silva;Gert Cauwenberghs
Author_Institution :
University of California San Diego, 92092 USA
fYear :
2015
Firstpage :
3949
Lastpage :
3952
Abstract :
Closed-loop neural prostheses enable bidirectional communication between the biological and artificial components of a hybrid system. However, a major challenge in this field is the limited understanding of how these components, the two separate neural networks, interact with each other. In this paper, we propose an in vitro model of a closed-loop system that allows for easy experimental testing and modification of both biological and artificial network parameters. The interface closes the system loop in real time by stimulating each network based on recorded activity of the other network, within preset parameters. As a proof of concept we demonstrate that the bidirectional interface is able to establish and control network properties, such as synchrony, in a hybrid system of two neural networks more significantly more effectively than the same system without the interface or with unidirectional alternatives. This success holds promise for the application of closed-loop systems in neural prostheses, brain-machine interfaces, and drug testing.
Keywords :
"Artificial neural networks","Neurons","Biological neural networks","Real-time systems","Testing","Prosthetics"
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
ISSN :
1094-687X
Electronic_ISBN :
1558-4615
Type :
conf
DOI :
10.1109/EMBC.2015.7319258
Filename :
7319258
Link To Document :
بازگشت