bertram_2002

Original status:

Model coded with reaction elements

Work done on model:

Rebuilt model using differential equations. Contacted author Richard Bertram regarding definition of variable x_infinity - 14/05/07

Reply:

x_infinity = alphax/(alphax+betax)

where:

alphax = 0.2 * (v + 40) / (1 - exp (-(v + 40)/10)) betax = 8 * exp(-(v+65)/18)

In fact this information is supplied in a previous paper that is referenced. Units were not given by Bertram, assumption made that the units are the same as for alpha_n and beta_n. That is, dimensionless.

Units for C1, C2, C3 etc. made dimensionless as they represent a probability of the channel being in that state, as a fraction of 1. Used value of 4mM for T_, which corresponds to a superthreshold response of the post-synaptic cell. Also, changed values (from Catherine's model,) of kG?_minus, starting with a value of 0.00025, which corresponds tothe beta1-gamma2 G-protein. Applied rule in paper: kG2_minus = kG_minus * 64, kG3_minus = kG2_minus * 64. kG_minus values for other G-proteins are: beta2-gamma2: 0.001, beta3-gamma2: 0.0005, beta4-gamma2: 0.01.

Model still doesn't integrate. Need to work on Markov model of channel, since this will be repeated in many other models. Could try looking at some ephys models curated by Penny.

Curation Status:

Partially curated - 1 standard star - maths mostly represented.

Future work required:

Need to fix Markov model within model. Need to build postsynaptic cell and connect network of neurons using cellml 1.1

Return to PMR Curation Wiki