Details

Autor(en) / Beteiligte

• Sanchez, J. C.
• Lytton, W. W.
• Carmena, J. M.
• Principe, J. C.
• Fortes, J.
• Barbour, R. L.
• Francis, J. T.

Titel

Dynamically Repairing and Replacing Neural Networks: Using Hybrid Computational and Biological Tools

Ist Teil von

• IEEE pulse, 2012-01, Vol.3 (1), p.57-59

Ort / Verlag

United States: IEEE

Erscheinungsjahr

2012

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Xplore Digital Library

Beschreibungen/Notizen

• The debilitating effects of injury to the nervous system can have a profound effect on daily life activities of the injured person [1]. In this article, we present a project overview in which we are utilizing computational and biological principles, along with simulation and experimentation, to create a realistic computational model of natural and injured sensorimotor control systems. Through the development of hybrid in silico/biological coadaptive symbiotic systems, the goal is to create new technologies that yield transformative neuroprosthetic rehabilitative solutions and a new test bed for the development of integrative medical devices for the repair and enhancement of biological systems.