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