A Hodgkin-Huxley Type Neuron Model That Learns Slow Non-Spike Oscillations

Kenji Doya, Allen I. Selverston, Peter F. Rowat
1993 Neural Information Processing Systems  
Peter F. Rowat A gradient descent algorithm for parameter estimation which is similar to those used for continuous-time recurrent neural networks was derived for Hodgkin-Huxley type neuron models. Using membrane potential trajectories as targets, the parameters (maximal conductances, thresholds and slopes of activation curves, time constants) were successfully estimated. The algorithm was applied to modeling slow non-spike oscillation of an identified neuron in the lobster stomatogastric
more » ... n. A model with three ionic currents was trained with experimental data. It revealed a novel role of A-current for slow oscillation below -50 mY.
dblp:conf/nips/DoyaSR93 fatcat:st3nzlmgung73dinekqdankumm