Frontiers | Predicting Spike Features of Hodgkin-Huxley-Type Neurons With Simple Artificial Neural Network
Hodgkin-Huxley (HH) -type model is the most famous computational model for simulating neural activity. It shows the highest accuracy in capturing neuronal spikes, and its model parameters have definite physiological meanings. However, HH-type models are computationally expensive. To address this problem, a previous study proposed a spike prediction module (SPM) to predict whether a spike will take place 1 ms later based on three voltage values with intervals of 1ms. Although SPM does well, it fails to evaluate the informative features of the spike. In this study, the feature prediction module ...
Source: frontiersin.org