DocumentCode :
2766318
Title :
A Neural Network Model of the Connectivity of the Biological Somatic Sensors
Author :
Rosen, Alan ; Rosen, David
Author_Institution :
Machine Consciousness Inc., Redondo Beach
fYear :
0
fDate :
0-0 0
Firstpage :
299
Lastpage :
306
Abstract :
The connectivity of a neural network model is designed to be similar to the biological connectivity of the somatic body sensors. The model consists of a mechanical robot controlled by a neural network based controller that adheres to three functional characteristics commonly associated with the subjective experience of sensory sensations (modalities of sensors): a) self knowledge, b) a "world space"-coordinate system in a controller, and c) access to information. The robotic controller, called a relational robotic controller (RRC)-circuit, controls the robotic body by reverse engineering the operation of the animal and human body and brain so that the functional operation adheres to those three functional characteristics. The RRC-circuit model may lead to a sensory-motor control system of the somatic motor system and insight into the biological pathways in the brain and the overall functional operation of the human body and brain.
Keywords :
biosensors; neural nets; neurocontrollers; robots; biological somatic sensors connectivity; mechanical robot; neural network; neural network model; relational robotic controller; reverse engineering; robotic controller; somatic motor system; Biological neural networks; Biological system modeling; Biosensors; Control system synthesis; Mechanical sensors; Neural networks; Orbital robotics; Robot control; Robot sensing systems; Sensor phenomena and characterization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.246695
Filename :
1716106
Link To Document :
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