Title :
A learning algorithm for Hodgkin-Huxley type neuron models
Author :
Doya, Kenji ; Selverston, Allen I.
Author_Institution :
Dept. of Biol., California Univ., San Diego, La Jolla, CA, USA
Abstract :
A learning algorithm for conductance-based neuron models is derived in a similar way as those for continuous-time neural networks. The algorithm was used for estimating a region in the parameter space that reproduces a set of oscillation patterns at different levels of current injection.
Keywords :
brain models; learning (artificial intelligence); neural nets; neurophysiology; Hodgkin-Huxley type neuron models; conductance-based neuron models; continuous-time neural networks; current injection; learning algorithm; oscillation patterns; parameter space; Biological system modeling; Biomembranes; Circuits; Computational biology; Differential equations; Nerve fibers; Neural networks; Neurons; Steady-state; Voltage;
Conference_Titel :
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN :
0-7803-1421-2
DOI :
10.1109/IJCNN.1993.716709
