Parameter estimation for Hodgkin-Huxley based models of cortical neurons (Lepora et al. 2011)


Simulation and fitting of two-compartment (active soma, passive dendrite) for different classes of cortical neurons. The fitting technique indirectly matches neuronal currents derived from somatic membrane potential data rather than fitting the voltage traces directly. The method uses an analytic solution for the somatic ion channel maximal conductances given approximate models of the channel kinetics, membrane dynamics and dendrite. This approach is tested on model-derived data for various cortical neurons.

Model Type: Neuron or other electrically excitable cell

Cell Type(s): Neocortex L5/6 pyramidal GLU cell; Neocortex L2/3 pyramidal GLU cell; Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron

Currents: I Na,t; I L high threshold; I T low threshold; I K; I M

Model Concept(s): Parameter Fitting; Simplified Models; Parameter sensitivity

Simulation Environment: GENESIS; MATLAB

Implementer(s): Lepora, Nathan [n.lepora at shef.ac.uk]

References:

Lepora NF, Overton PG, Gurney K. (2012). Efficient fitting of conductance-based model neurons from somatic current clamp. Journal of computational neuroscience 32 [PubMed]