Library-based Fast Algorithm for Simulating the Hodgkin-Huxley Neuronal Networks
We present a modified library-based method for simulating the Hodgkin-Huxley (HH) neuronal networks. By pre-computing a high resolution data library during the interval of an action potential (spike), we can avoid evolving the HH equations during the spike and can use a large time step to raise efficiency. The library method can stably achieve at most 10 times of speedup compared with the regular Runge-Kutta method while capturing most statistical properties of HH neurons like the distribution of spikes which data is widely used in the statistical analysis like transfer entropy and Granger causality. The idea of library method can be easily and successfully applied to other HH-type models like the most prominent \textquotedblleft regular spiking\textquotedblright , \textquotedblleft fast spiking\textquotedblright , \textquotedblleft intrinsically bursting\textquotedblright{} and \textquotedblleft low-threshold spike\textquotedblright{} types of HH models.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Design Fast Algorithms For Hodgkin-Huxley Neuronal Networks
The stiffness of the Hodgkin-Huxley (HH) equations during an action potential (spike) limits the use of large time steps. We observe that the neurons can be evolved independently between spikes, $i.e.,$ different neurons…
Learning the Hodgkin-Huxley Model with Operator Learning Techniques
We construct and compare three operator learning architectures, DeepONet, Fourier Neural Operator, and Wavelet Neural Operator, in order to learn the operator mapping a time-dependent applied current to the transmembrane…
Operator learningSodium entry efficiency during action potentials: A novel single-parameter family of Hodgkin-Huxley models
Sodium entry during an action potential determines the energy efficiency of a neuron. The classic Hodgkin-Huxley model of action potential generation is notoriously inefficient in that regard with about 4 times more char…
Towards an Hybrid Hodgkin-Huxley Action Potential Generation Model
Mathematical models for the generation of the action potential can improve the understanding of physiological mechanisms that are consequence of the electrical activity in neurons. In such models, some equations involvin…
Cellular function given parametric variation: excitability in the Hodgkin-Huxley model
How is reliable physiological function maintained in cells despite considerable variability in the values of key parameters of multiple interacting processes that govern that function? Here we use the classic Hodgkin-Hux…