Issue is that gbar is named haphazardly across different channels, when comparing with super models, we override it by renaming the maximum conductance to gbar for the sake of convenience and as a global setting.
This creates issues when comparing the model to supermodel one to one, as it seems like the models with ICG protocols are sensitive to gbar max vals.
Maybe resolved using the following trick
from neuron import h all_attributes = dir(h)
Now search among these attributes via g+_SUFFIX in all the attributes. And call for its set value using h.soma(0.5).g+_SUFFIX. In case of multiple entries available for gbar-like entries - manual intervention is warranted.
This would also potentially fix the issue of comparing channels at different gbar's - instead we will then stick to the original gbar values as intended.
Issue is that gbar is named haphazardly across different channels, when comparing with super models, we override it by renaming the maximum conductance to gbar for the sake of convenience and as a global setting.
This creates issues when comparing the model to supermodel one to one, as it seems like the models with ICG protocols are sensitive to gbar max vals.
Maybe resolved using the following trick
from neuron import h all_attributes = dir(h)
Now search among these attributes via g+_SUFFIX in all the attributes. And call for its set value using h.soma(0.5).g+_SUFFIX. In case of multiple entries available for gbar-like entries - manual intervention is warranted.