added comment from discussion with Lukas

manuscript.tex

@@ -397,7 +397,8 @@ To our knowledge, no comprehensive evaluation of how ionic current environment a
 % mutations in the SCN1A gene encoding \(\textrm{Na}_{\textrm{V}}\textrm{1.1}\) result in epileptic phenotypes by selective hypoexcitability of inhibitory but not excitatory neurons in the cortex resulting in circuit hyperexcitability 
  \citep{Hedrich14874}. In CA3 of the hippocampus, the equivalent mutation in SCN8A, R1648H, increases excitability of pyramidal neurons and decreases excitability of parvalbumin positive interneurons
 % mutation of \(\textrm{Na}_{\textrm{V}}\textrm{1.6}\) similarly results in increased excitability of pyramidal neurons and decreased excitability of parvalbumin positive interneurons 
- \cite{makinson_scn1a_2016}. Additionally, the L858H mutation in \(\textrm{Na}_\textrm{V}\textrm{1.7}\), associated with erythermyalgia, has been shown to cause hypoexcitability in sympathetic ganglion neurons and hyperexcitability in dorsal root ganglion neurons \citep{Waxman2007, Rush2006}. The differential effects of L858H \(\textrm{Na}_\textrm{V}\textrm{1.7}\) on firing is dependent on the presence or absence of another sodium channel \(\textrm{Na}_\textrm{V}\textrm{1.8}\) \citep{Waxman2007, Rush2006}. In a modelling study, it was found that altering the sodium conductance in 2 stomatogastric ganglion neuron models from a population models decreases rheobase in both models, however the initial slope of the fI curves (proportional to AUC of the fI-curve) is increased in one model and decreased in the other suggesting that the magnitude of other currents in these models (such as \(\textrm{K}_\textrm{d}\)) determines the effect of a change in sodium current \citep{Kispersky2012} \notels{I don't see this in the paper. As far as I understood, they start with one model type and then only work with the other and state that they behave qualitatively the same} \notenk{Yes you are right. I looked at the paper again and I'm not sure why I wrote that. I think the key thing I was trying to get at is that the effect of an increase in sodium conductan on the fI curve can be different at different parts of the fI curve, because at higher firing rates \(\textrm{K}_\textrm{d}\) plays a role. As such changes or heterogeneity in \(\textrm{K}_\textrm{d}\)  could alter the effect of such an increase in sodium conductance at these higher firing rates.}. \notenk{Do you think that this is a more accurate representation? ``In a modelling study, it was found that altering the sodium conductance in 2 stomatogastric ganglion neuron models from a population models decreases rheobase in both models, however the shape of the fI curves especially at high firing rates is altered due other currents in these models such as \(\textrm{K}_\textrm{d}\) \citep{Kispersky2012}.''} These findings, in concert with our findings emphasize that the ionic current environment in which a channelopathy occurs is vital in determining the outcomes of the channelopathy on firing.
+ \cite{makinson_scn1a_2016}. Additionally, the L858H mutation in \(\textrm{Na}_\textrm{V}\textrm{1.7}\), associated with erythermyalgia, has been shown to cause hypoexcitability in sympathetic ganglion neurons and hyperexcitability in dorsal root ganglion neurons \citep{Waxman2007, Rush2006}. The differential effects of L858H \(\textrm{Na}_\textrm{V}\textrm{1.7}\) on firing is dependent on the presence or absence of another sodium channel \(\textrm{Na}_\textrm{V}\textrm{1.8}\) \citep{Waxman2007, Rush2006}. In a modelling study, it was found that altering the sodium conductance in 2 stomatogastric ganglion neuron models from a population models decreases rheobase in both models, however the initial slope of the fI curves (proportional to AUC of the fI-curve) is increased in one model and decreased in the other suggesting that the magnitude of other currents in these models (such as \(\textrm{K}_\textrm{d}\)) determines the effect of a change in sodium current \citep{Kispersky2012} \notels{I don't see this in the paper. As far as I understood, they start with one model type and then only work with the other and state that they behave qualitatively the same} \notenk{Yes you are right. I looked at the paper again and I'm not sure why I wrote that. I think the key thing I was trying to get at is that the effect of an increase in sodium conductan on the fI curve can be different at different parts of the fI curve, because at higher firing rates \(\textrm{K}_\textrm{d}\) plays a role. As such changes or heterogeneity in \(\textrm{K}_\textrm{d}\)  could alter the effect of such an increase in sodium conductance at these higher firing rates.}. \notenk{Do you think that this is a more accurate representation? ``In a modelling study, it was found that altering the sodium conductance in 2 stomatogastric ganglion neuron models from a population models decreases rheobase in both models, however the shape of the fI curves especially at high firing rates is altered due other currents in these models such as \(\textrm{K}_\textrm{d}\) \citep{Kispersky2012}.''} \notenk{Could move this to methods as a justification as to why we use rheobase and AUC as measures for firing}
+These findings, in concert with our findings emphasize that the ionic current environment in which a channelopathy occurs is vital in determining the outcomes of the channelopathy on firing.
 
 Cell type specific differences in ionic current properties are important in the effects of ion channel mutations, however within a cell type heterogeneity in channel expression levels exists and it is often desirable to generate a population of neuronal models and to screen them for plausibility to biological data in order to capture neuronal population diversity \citep{marder_multiple_2011}. The models we used here are originally generated by characterization of current gating properties and by fitting of maximal conductances to experimental data \citep{pospischil_minimal_2008, ranjan_kinetic_2019, alexander_cerebellar_2019, otsuka_conductance-based_2004}. This practice of fixing maximal conductances based on experimental data is limiting as it does not reproduce the variability in channel expression and neuronal firing behaviour of a heterogeneous neuron population \citep{verma_computational_2020}. For example, a model derived from the mean conductances in a sub-population of stomatogastric ganglion "one-spike bursting" neurons fires 3 spikes instead of 1 per burst due to an L shaped distribution of sodium and potassium conductances \citep{golowasch_failure_2002}.  
 Multiple sets of current conductances can give rise to the same patterns of activity also termed degeneracy and differences in neuronal dynamics may only be evident with perturbations \citep{marder_multiple_2011, goaillard_ion_2021}.