A Study of Intrinsic Excitability for the Hodgkin-Huxley Neuron Model
Session Number
IND STUDY 06 CMPS
Advisor(s)
Dr. Ashwin Mohan, Illinois Mathematics and Science Academy
Discipline
Independent Study
Start Date
17-4-2025 11:10 AM
End Date
17-4-2025 11:25 AM
Abstract
Computational models have commonly been used to study neuropathologies, allowing for a realistic interpretation of behavior. This study investigates the single-cell Hodgkin-Huxley model to develop a richer understanding of the neuron’s resting state during cognitive activity. Using the Simulator for Neural Networks and Action Potentials (SNNAP) computer program, sodium and potassium conductance are modulated from a quiescent state until observed excitability, becoming an underexplored study in micro-instabilities. The model neuron was quiescent under normal membrane conductances (gNa = 120 mS/cm², gK = 36 mS/cm²) with no external current injection. However, a conductance change as small as 0.001 affected the excitability of the neuron. Therefore, given the goal to locate these conductance thresholds, this study looked at various SNNAP parameters, including the membrane voltage (V), its time derivative (dV/dt), and the voltage dependence of ionic currents (Ivd) for both Na and K ionic channels. This study found significant differences in excitability after the incremental change in sodium conductance and the comparable decrement in potassium conductance. Altogether, these findings show how small modifications in conductance parameters can lead to action potentials without current injection, informing researchers of the realistic thresholds that larger neural networks should maintain in computational neuroscience.
A Study of Intrinsic Excitability for the Hodgkin-Huxley Neuron Model
Computational models have commonly been used to study neuropathologies, allowing for a realistic interpretation of behavior. This study investigates the single-cell Hodgkin-Huxley model to develop a richer understanding of the neuron’s resting state during cognitive activity. Using the Simulator for Neural Networks and Action Potentials (SNNAP) computer program, sodium and potassium conductance are modulated from a quiescent state until observed excitability, becoming an underexplored study in micro-instabilities. The model neuron was quiescent under normal membrane conductances (gNa = 120 mS/cm², gK = 36 mS/cm²) with no external current injection. However, a conductance change as small as 0.001 affected the excitability of the neuron. Therefore, given the goal to locate these conductance thresholds, this study looked at various SNNAP parameters, including the membrane voltage (V), its time derivative (dV/dt), and the voltage dependence of ionic currents (Ivd) for both Na and K ionic channels. This study found significant differences in excitability after the incremental change in sodium conductance and the comparable decrement in potassium conductance. Altogether, these findings show how small modifications in conductance parameters can lead to action potentials without current injection, informing researchers of the realistic thresholds that larger neural networks should maintain in computational neuroscience.