made some changes and comments to discussion

manuscript.tex

@@ -182,7 +182,7 @@ However the effect of a given channelopathy on different neuronal types across t
 % \textcolor{red}{In the simplest case, the influence on the firing behaviour should correlate with the expression level of the affected gene \textcolor{red}{(cite Niko , other Papers)}. But if a \textcolor{red}{ kinetic parameter} is changed too much, it can have unforseen consequences. }
   The expression level of an affected gene can correlate with firing behaviour in the simplest case \citep{Layer2021} \textcolor{red}{(cite other Papers?)} \notenk{Not sure if Lukas had some in mind}, however if a gating property is altered substantially this can have complex consequences.
 
-For instance, altering relative amplitudes of ionic currents can dramatically influence the firing behaviour and dynamics of neurons \citep{rutecki_neuronal_1992, pospischil_minimal_2008,Kispersky2012, golowasch_failure_2002, barreiro_-current_2012, Noebels2017, Layer2021}, however other properties of ionic currents impact neuronal firing as well. In extreme cases, a mutation can have opposite effects on different neuron types. For example, the R1629H SCN1A mutation is associated which increased firing in interneurons, but decreases pyramidal neuron excitability \citep{Hedrich14874,makinson2016scn1a}
+For instance, altering relative amplitudes of ionic currents can dramatically influence the firing behaviour and dynamics of neurons \citep{rutecki_neuronal_1992, pospischil_minimal_2008,Kispersky2012, golowasch_failure_2002, barreiro_-current_2012, Noebels2017, Layer2021}, however other properties of ionic currents impact neuronal firing as well. In extreme cases, a mutation can have opposite effects on different neuron types. For example, the R1629H SCN1A mutation is associated which increased firing in interneurons, but decreases pyramidal neuron excitability \citep{Hedrich14874,makinson_2016_scn1a}
 
 %However, the effect on the firing behaviour of different neurons is often unclear \textcolor{red}{(and always incomplete)}. Generally, different neuron types have different ionic current compositions and therefore could react in different ways to changes in one ionic current. In the simpler cases, the respective firing behaviour should mostly correlate with expression level of the affected current and scale with it \textcolor{red}{(cite some stuff, cite NikoPaper)}. \textcolor{red}{If the change in gating kinetics is too strong, the firing behaviour can change qualitatively.} Altering the relative current amplitudes in neuronal models leads to dramtic changes in their firing behaviour and dynamics \citep{rutecki_neuronal_1992, pospischil_minimal_2008,Kispersky2012, golowasch_failure_2002, barreiro_-current_2012, Noebels2017}. \textcolor{red}{The same could happen for other parameters too. \citet{Liu2019} reported a drastically slowed inacitvaiton time constant for a mutation in \textcolor{red}{Na$_V$1.6}, which led to huge depolarization plateaus after an action potential, that lasted several 100 milliseconds.} The most drastic example known to us would be the R1629H mutation in \textcolor{red}{SCN2A}. This mutation increases the excitability of interneurons, but decreases it in pyramidal neurons \textcolor{red}{(cite Hedrich2014 and the other paper)}. \textcolor{red}{Some neuron types may be closer to certain transitions between firing states than other, making these observations even more unpredictable \textcolor{red}{(cite some bifurcation stuff?)}.}
 
@@ -340,6 +340,8 @@ Mutations in \Kv are associated with episodic ataxia type~1 (EA1) and have been
 Using a set of diverse conductance-based neuronal models, the effects of changes to properties of ionic currents and conductances on firing were determined to be heterogenous for the AUC of the steady state fI curve but more homogenous for rheobase. For a known channelopathy, episodic ataxia type~1 associated \Kv mutations, the effects on rheobase is consistent across model cell types, whereas the effect on AUC depends on cell type. Our results demonstrate that LoF and GoF on the biophysical level cannot be uniquely transfered to the level of neuronal firing.
 
 \subsection*{Validity of Neuronal Models}
+\notels{should we move this to a less prominent position? How much of this part could be counted as common knowledge and be left out?, for example model complexity in terms of currents and compartments, I just think that this part might be too harsh on the models, even if the criticism doesn't apply for the main points of the paper}
+
 Our findings are based on simulations of a range of single-compartment conductance-based models. Many aspects of these models can be questioned.
 
 The \Kv model from \cite{ranjan_kinetic_2019} is based on expression of only \Kv in CHO cells and represents the biophysical properties of \Kv homotetramers and not heteromers. Thus the \Kv model used here neglects the complex reality of these channels \textit{in vivo} including their expression as heteromers and the altered biophyiscal properties of these heteromers \citep{wang__1999, roeper_nip_1998, coleman_subunit_1999, ruppersberg_heteromultimeric_1990, isacoff_evidence_1990, rettig_inactivation_1994}.  Furthermore, dynamic modulation of \Kv channels, although physiologically relevant, is neglected here. For example, \(\textrm{K}_{\textrm{V}}\upbeta\)2 plays a role in \(\textrm{K}_{\textrm{V}}\textrm{1}\) channel trafficking and cell membrane expression \citep{shi_efficacy_2016, campomanes_kv_2002, manganas_identification_2001} and  \Kv phosphorylation increases cell membrane \Kv \citep{jonas_regulation_1996}. It should be noted that the discrete classification of potassium currents into delayed rectifier and A-type is likely not biological, but rather highlights the characteristics of a spectrum of potassium channel inactivation that arises in part due to additional factors such as heteromer composition \citep{stuhmer_molecular_1989, glasscock_kv11_2019}, non-pore forming subunits (e.g. \(\textrm{K}_{\textrm{V}}\upbeta\) subunits) \citep{rettig_inactivation_1994, xu_kv2_1997}, and temperature \citep{ranjan_kinetic_2019} modulating channel properties.
@@ -364,11 +366,15 @@ Variability in ion channel expression often correlates with the expression of ot
 The variability of ion currents and degeneracy of neurons may account, at least in part, for the observation that the effect of toxins within a neuronal type is frequently not constant \citep{khaliq_relative_2006, puopolo_roles_2007, ransdell_neurons_2013}.
 
 \subsection*{Effects of KCNA1 Mutations}
-Moderate changes in delayed rectifier potassium currents change the bifurcation structure of Hodgkin Huxley model, with changes analogous to those seen with \Kv mutations resulting in increased excitability due to reduced thresholds for repetitive firing \citep{hafez_altered_2020}. Although the Hodgkin Huxley delayed rectifier lacks inactivation, the increases in excitability seen are in line with simulation-based predictions of the outcomes of \textit{KCNA1} mutations.  LOF KCNA1 mutations generally increase neuronal excitability, however the different effects of KCNA1 mutations across models on AUC are indicative that a certain cell type specific complexity exists. Increased excitability seen experimentally with \Kv null mice \citep{smart_deletion_1998, zhou_temperature-sensitive_1998}, with pharmacological \Kv block \citep{chi_manipulation_2007, morales-villagran_protection_1996}, by \citet{hafez_altered_2020} and with  simulation-based predictions of KCNA1 mutations. Contrary to these results,  \citet{zhao_common_2020} predicted \textit{in silico} that the depolarizing shifts seen as a result of KCNA1 mutations broaden action potentials and interfere negatively with high frequency action potential firing, however they varied stimulus duration between different models and therefore comparability of firing rates is lacking in this study.     
+Moderate changes in delayed rectifier potassium currents change the bifurcation structure of Hodgkin Huxley model, with changes analogous to those seen with \Kv mutations resulting in increased excitability due to reduced thresholds for repetitive firing \citep{hafez_altered_2020}. Although the Hodgkin Huxley delayed rectifier lacks inactivation, the increases in excitability seen are in line with simulation-based predictions of the outcomes of \textit{KCNA1} mutations.  
+LOF KCNA1 mutations generally increase neuronal excitability, however the varying susceptibility on rheobase and different effects on AUC of KCNA1 mutations across models are indicative that a certain cell type specific complexity exists.
+%LOF KCNA1 mutations generally increase neuronal excitability, however the different effects of KCNA1 mutations across models on AUC are indicative that a certain cell type specific complexity exists. 
+Increased excitability is seen experimentally with \Kv null mice \citep{smart_deletion_1998, zhou_temperature-sensitive_1998}, with pharmacological \Kv block \citep{chi_manipulation_2007, morales-villagran_protection_1996} and by \citet{hafez_altered_2020} with simulation-based predictions of KCNA1 mutations. Contrary to these results,  \citet{zhao_common_2020} predicted \textit{in silico} that the depolarizing shifts seen as a result of KCNA1 mutations broaden action potentials and interfere negatively with high frequency action potential firing, however they varied stimulus duration between different models and therefore comparability of firing rates is lacking in this study.     
+
 Different current properties, such as the difference in \(\textrm{I}_\textrm{A}\) and \IKv in the Cb stellate and STN model families alter the impact of KCNA1 mutations on firing highlighting that knowledge of the biophysical properties of a current and its neuronal expression is vital for holistic understanding of the effects of a given ion channel mutation both at a single cell and network level.
 
 \subsection*{Loss or Gain of Function Characterizations Do Not Fully Capture Ion Channel Mutation Effects on Firing}
-The effects of changes in current properties depend in part on the neuronal model in which they occur and can be seen in the variance of correlations (especially in AUC) across models for a given current property change. Therefore, relative conductances and gating properties of currents in the ionic current environment in which an alteration in current properties occurs plays an important role in determining the outcome on firing. The use of loss of function (LOF) and gain of function (GOF) is useful at the level of ion channels and whether a mutation results in more or less ionic current, however the extension of this thinking onto whether mutations induce LOF or GOF at the level of neuronal firing based on the ionic current LOF/GOF is problematic due to the dependency of neuronal firing changes on the ionic current environment. Thus the direct leap from current level LOF/GOF characterizations to effects on firing without experimental or modelling-based evidence, although tempting, should be refrained from and viewed with caution when reported. This is especially relevant in the recent development of personalized medicine for channelopathies, where a patients specific channelopathy is identified and used to tailor treatments \citep{Weber2017, Ackerman2013, Helbig2020, Gnecchi2021, Musto2020, Brunklaus2022}. However, the effects of specific ion channel mutations are often characterized in expression systems and classified as LOF or GOF to aid in treatment decisions \citep{johannesen_genotype-phenotype_2021, Brunklaus2022, Musto2020}.  Interestingly, both LOF and GOF \(\textrm{Na}_{\textrm{V}}\textrm{1.1}\) mutations can benefit from treatment with sodium channel blockers \citep{johannesen_genotype-phenotype_2021}, suggesting that the relationship between effects at the level of ion channels and effects at the level of firing and therapeutics is not linear or evident without further contextual information. Therefore, this approach must be used with caution and the cell type which expressed the mutant ion channel must be taken into account. Experimental assessment of the effects of a patients specific ion channel mutation \textit{in vivo} is not feasible at a large scale due to time and cost constraints, modelling of the effects of patient specific channelopathies is a desirable approach.
+The effects of changes in current properties depend in part on the neuronal model in which they occur and can be seen in the variance of correlations (especially in AUC) across models for a given current property change. Therefore, relative conductances and gating properties of currents in the ionic current environment in which an alteration in current properties occurs plays an important role in determining the outcome on firing. The use of loss of function (LOF) and gain of function (GOF) is useful at the level of ion channels and whether a mutation results in more or less ionic current, however the extension of this thinking onto whether mutations induce LOF or GOF at the level of neuronal firing based on the ionic current LOF/GOF is problematic due to the dependency of neuronal firing changes on the ionic current environment. Thus the direct leap from current level LOF/GOF characterizations to effects on firing without experimental or modelling-based evidence, although tempting, should be refrained from and viewed with caution when reported. This is especially relevant in the recent development of personalized medicine for channelopathies, where a patients specific channelopathy is identified and used to tailor treatments \citep{Weber2017, Ackerman2013, Helbig2020, Gnecchi2021, Musto2020, Brunklaus2022}. However, the effects of specific ion channel mutations are often characterized in expression systems and classified as LOF or GOF to aid in treatment decisions \citep{johannesen_genotype-phenotype_2021, Brunklaus2022, Musto2020}.  Interestingly, both LOF and GOF \(\textrm{Na}_{\textrm{V}}\textrm{1.6}\) mutations can benefit from treatment with sodium channel blockers \citep{johannesen_genotype-phenotype_2021}, suggesting that the relationship between effects at the level of ion channels and effects at the level of firing and therapeutics is not linear or evident without further contextual information. Therefore, this approach must be used with caution and the cell type which expressed the mutant ion channel must be taken into account. Experimental assessment of the effects of a patients specific ion channel mutation \textit{in vivo} is not feasible at a large scale due to time and cost constraints, modelling of the effects of patient specific channelopathies is a desirable approach.
 Accordingly, for accurate modelling and predictions of the effects of mutations on neuronal firing, information as to the type of neurons containing the affected channel, and the properties of the affected and all currents in the affected neuronal type is needed. When modelling approaches are sought out to overcome the limitations of experimental approaches, care must be taken to account for model dependency and the generation of relevant cell-type or cell specific populations of models should be standard in assessing the effects of mutations in specific neurons.
 \par\null
 

ref.bib

@@ -1620,18 +1620,18 @@ SIGNIFICANCE: Bromide is most effective and is a well-tolerated drug among DS pa
 }
 
 
-@article{makinson2016scn1a,
-  title={An Scn1a epilepsy mutation in Scn8a alters seizure susceptibility and behavior},
-  author={Makinson, Christopher D and Dutt, Karoni and Lin, Frank and Papale, Ligia A and Shankar, Anupama and Barela, Arthur J and Liu, Robert and Goldin, Alan L and Escayg, Andrew},
-  journal={Experimental neurology},
-  volume={275},
-  pages={46--58},
-  year={2016},
-  publisher={Elsevier},
-  language = {en},
-  url={https://doi.org/10.1016/j.expneurol.2015.09.008},
-  doi={10.1016/j.expneurol.2015.09.008}
-}
+%@article{makinson2016scn1a,
+%  title={An Scn1a epilepsy mutation in Scn8a alters seizure susceptibility and behavior},
+%  author={Makinson, Christopher D and Dutt, Karoni and Lin, Frank and Papale, Ligia A and Shankar, Anupama and Barela, Arthur J and Liu, Robert and Goldin, Alan L and Escayg, Andrew},
+%  journal={Experimental neurology},
+%  volume={275},
+%  pages={46--58},
+%  year={2016},
+%  publisher={Elsevier},
+%  language = {en},
+%  url={https://doi.org/10.1016/j.expneurol.2015.09.008},
+%  doi={10.1016/j.expneurol.2015.09.008}
+%}
 
  
 @Article{Waxman2011,