title: Biophysical Insights into How Spike Threshold Depends on the Rate of Membrane Potential Depolarization in Type I and Type II Neurons.
abstract: Dynamic spike threshold plays a critical role in neuronal input-output relations. In many neurons, the threshold potential depends on the rate of membrane potential depolarization (dV/dt) preceding a spike. There are two basic classes of neural excitability, i.e., Type I and Type II, according to input-output properties. Although the dynamical and biophysical basis of their spike initiation has been established, the spike threshold dynamic for each cell type has not been well described. Here, we use a biophysical model to investigate how spike threshold depends on dV/dt in two types of neuron. It is observed that Type II spike threshold is more depolarized and more sensitive to dV/dt than Type I. With phase plane analysis, we show that each threshold dynamic arises from the different separatrix and K+ current kinetics. By analyzing subthreshold properties of membrane currents, we find the activation of hyperpolarizing current prior to spike initiation is a major factor that regulates the threshold dynamics. The outward K+ current in Type I neuron does not activate at the perithresholds, which makes its spike threshold insensitive to dV/dt. The Type II K+ current activates prior to spike initiation and there is a large net hyperpolarizing current at the perithresholds, which results in a depolarized threshold as well as a pronounced threshold dynamic. These predictions are further attested in several other functionally equivalent cases of neural excitability. Our study provides a fundamental description about how intrinsic biophysical properties contribute to the threshold dynamics in Type I and Type II neurons, which could decipher their significant functions in neural coding.
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China.
authors.forename: Guo-Sheng
authors.initials: GS
authors.lastname: Yi
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China.
authors.forename: Jiang
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
authors.forename: Kai-Ming
authors.initials: KM
authors.lastname: Tsang
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China.
authors.forename: Xi-Le
authors.initials: XL
authors.lastname: Wei
authors.affiliation: School of Electrical Engineering and Automation, Tianjin University, Tianjin, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Deng
mesh_terms: D007700:Kinetics; D008564:Membrane Potentials; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology* / Q000378:metabolism; D012964:Sodium / Q000378:metabolism
chemical_list: D012964:Sodium