The impact of Hodgkin–Huxley models on dendritic research

Abstract

For the past seven decades, the Hodgkin–Huxley (HH) formalism has been an invaluable tool in the arsenal of neuroscientists, allowing for robust and reproducible modelling of ionic conductances and the electrophysiological phenomena they underlie. Despite its apparent age, its role as a cornerstone of computational neuroscience has not waned. The discovery of dendritic regenerative events mediated by ionic and synaptic conductances has solidified the importance of HH‐based models further, yielding new predictions concerning dendritic integration, synaptic plasticity and neuronal computation. These predictions are often validated through in vivo and in vitro experiments, advancing our understanding of the neuron as a biological system and emphasizing the importance of HH‐based detailed computational models as an instrument of dendritic research. In this article, we discuss recent studies in which the HH formalism is used to shed new light on dendritic function and its role in neuronal phenomena.

A novel non-invasive brain stimulation technique: “Temporally interfering electrical stimulation”

“…Mirzakhalili et al (2020) established an axon model for analysis using the standard Hodgkin-Huxley formula. As a cornerstone in the field of computational neuroscience, Hodgkin-Huxley formula can be used to investigate the neuronal function and further provide accurate reflection of single neuron (Petousakis et al, 2022). The findings indicated that TI stimulation necessitates an ion-channel-mediated signal rectification process in order to extract low-frequency envelope waveforms and activate neural activity.…”

Can neuron modeling constrained by ultrafast imaging data extract the native function of ion channels?

“…For ion channels, the biophysical behavior of the model can be initially established from experiments where the channel is expressed in a host system. Each channel can be modeled as deterministic (Petousakis et al, 2022 ) or stochastic (Goldwyn et al, 2011 ) Hodgkin-Huxley function. From this background, the modeler can optimize the parameters of ion channels and of the other molecules so that the results of the computer simulation match the set of experimental V m signals.…”

Data-driven estimation of spatial electrical property of multi-compartment models with neuronal morphology by replica exchange Monte Carlo method

“…In order to extract spatiotemporal neuronal dynamics, it is necessary to establish data-driven framework for estimating spatial electrical properties from membrane potentials. Prior works have proposed framework for estimating parameters of neuron models that ignore spatial structure of neurons [11][12][13], such as the Hodgkin-Huxley model [14] and Izhikevich model [15]. In contrast, estimating spatial electrical properties that reproduce nonlinear spatiotemporal electrical activity in neurons has been difficult due to 1) morphological characteristics, where dendrites of neurons have complicated shapes; 2) complex energy structure, where incorrect properties are estimated because of being stuck in local optima; 3) incomplete observation data, where membrane potentials are partially observable and noisy.…”