Title :
A biological-based neural network model of leech reflexive behaviors
Author :
Coulston, Chris ; Pakzad, Simin
Author_Institution :
Dept. of Electr. & Comput. Eng., Pennsylvania State Univ., University Park, PA, USA
Abstract :
An artificial neural network is built and trained to model the local bending reflex of the leech Hirudo Medicinalis. The model is validated by the data provided from physiological experiments. The training data and topology of the neural network is based on data gathered from physiological experiments. A graphical representation of the leech is constructed as a high level interface to the artificial neural network. This interface is used to determine the appropriateness of responses to different stimulus patterns. The artificial neural network is tested to see if it can generalize its repertoire of behaviors to untrained stimulus patterns. The leech provides the authors with a simple neurostructure that can be understood with today´s technologies
Keywords :
brain; learning (artificial intelligence); neural nets; neurophysiology; physiological models; biological-based neural network model; graphical representation; high level interface; leech Hirudo Medicinalis; leech reflexive behaviors; local bending reflex; neurostructure; physiological experiments; stimulus patterns; training data; Artificial neural networks; Biological neural networks; Biological system modeling; Head; Humans; Information processing; Neural networks; Neurons; Tail; Testing;
Conference_Titel :
Developing and Managing Intelligent System Projects, 1993., IEEE International Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-3730-7
DOI :
10.1109/DMISP.1993.248639