From 5fd4905b61536e41bd6c4e677a96bc1350511686 Mon Sep 17 00:00:00 2001 From: Jan Benda Date: Wed, 18 May 2022 11:36:53 +0200 Subject: [PATCH] some suggestions --- Makefile | 2 +- gating_table.tex | 16 ++++++++-------- manuscript.tex | 34 ++++++++++++++++------------------ 3 files changed, 25 insertions(+), 27 deletions(-) diff --git a/Makefile b/Makefile index 473cd69..c5f8329 100644 --- a/Makefile +++ b/Makefile @@ -6,7 +6,7 @@ TEXFILE=$(TEXBASE).tex PDFFILE=$(TEXBASE).pdf TXTFILE=$(TEXBASE).txt -REVISION=0691c71d176511c294f39d84c89864fa8c141e4a +REVISION=249fe01cabd4632dee366e26991fe32f4c1286df PDFFIGURES=$(shell sed -n -e '/^[^%].*includegraphics/{s/^.*includegraphics.*{\(.*\)}/\1.pdf/;p}' $(TEXFILE)) diff --git a/gating_table.tex b/gating_table.tex index ad585bc..eb5c536 100644 --- a/gating_table.tex +++ b/gating_table.tex @@ -8,16 +8,16 @@ & Gating & \(V_{1/2}\) [mV]& \(k\) & \(j\) & \(a\) \\ \Xhline{1\arrayrulewidth} %Pospischil - & \(\textrm{I}_{\textrm{Na}}\) activation &-34.33054521 & -8.21450277 & 1.42295686 & --- \\ -RS pyramidal, & \(\textrm{I}_{\textrm{Na}}\) inactivation &-34.51951036 & 4.04059373 & 1 & 0.05 \\ - RS inhibitory, & \(\textrm{I}_{\textrm{Kd}}\) activation &-63.76096946 & -13.83488194 & 7.35347425 & --- \\ - FS & \(\textrm{I}_{\textrm{L}}\) activation &-39.03684525 & -5.57756176 & 2.25190197 & --- \\ - & \(\textrm{I}_{\textrm{L}}\) inactivation &-57.37 & 20.98 & 1 & --- \\ - & \(\textrm{I}_{\textrm{M}}\) activation &-45 & -9.9998807337 & 1 & --- \\ %-45 with 10 mV shift to contributes to resting potential + & \(\textrm{I}_{\textrm{Na}}\) activation &$-34.33054521$ & $-8.21450277$ & $1.42295686$ & --- \\ +RS pyramidal, & \(\textrm{I}_{\textrm{Na}}\) inactivation &$-34.51951036$ & $4.04059373$ & $1$ & $0.05$ \\ + RS inhibitory, & \(\textrm{I}_{\textrm{Kd}}\) activation &$-63.76096946$ & $-13.83488194$ & $7.35347425$ & --- \\ + FS & \(\textrm{I}_{\textrm{L}}\) activation &$-39.03684525$ & $-5.57756176$ & $2.25190197$ & --- \\ + & \(\textrm{I}_{\textrm{L}}\) inactivation &$-57.37$ & $20.98$ & $1$ & --- \\ + & \(\textrm{I}_{\textrm{M}}\) activation &$-45$ & $-9.9998807337$ & $1$ & --- \\ %-45 with 10 mV shift to contributes to resting potential % & & & & &\\ \Xhline{1\arrayrulewidth} - \(\textrm{I}_{\textrm{K}_{\textrm{V}}\textrm{1.1}}\ \) & \(\textrm{I}_{\textrm{K}_{\textrm{V}}\textrm{1.1}}\ \) activation &-30.01851852 & -7.73333333 & 1 & --- \\ - & \(\textrm{I}_{\textrm{K}_{\textrm{V}}\textrm{1.1}}\ \) Inactivation &-46.85851852 & 7.67266667 & 1 & 0.245 \\ + \(\textrm{I}_{\textrm{K}_{\textrm{V}}\textrm{1.1}}\ \) & \(\textrm{I}_{\textrm{K}_{\textrm{V}}\textrm{1.1}}\ \) activation &$-30.01851852$ & $-7.73333333$ & $1$ & --- \\ + & \(\textrm{I}_{\textrm{K}_{\textrm{V}}\textrm{1.1}}\ \) Inactivation &$-46.85851852$ & $7.67266667$ & $1$ & $0.245$ \\ \Xhline{1\arrayrulewidth} diff --git a/manuscript.tex b/manuscript.tex index 62b7e16..2f69158 100644 --- a/manuscript.tex +++ b/manuscript.tex @@ -161,15 +161,13 @@ Ion channels determine neuronal excitability and mutations that alter ion channe \par\null -\notejb{LOF or LoF? GOF or GoF?} \notels{LOF and GoF!!! (I think it is usually all big letters, not 100\% sure though)} - \section*{Introduction (750 Words Maximum - Currently 675)} %\textit{The Introduction should briefly indicate the objectives of the study and provide enough background information to clarify why the study was undertaken and what hypotheses were tested.} -Voltage-gated ion channels are vital in determining neuronal excitability, action potential generation and firing patterns \citep{bernard_channelopathies_2008, carbone_ion_2020}. In particular, the properties and combinations of ion channels and their resulting currents determine the firing properties of the neuron \citep{rutecki_neuronal_1992, pospischil_minimal_2008}. However, ion channel function can be disturbed, resulting in altered ionic current properties and altered neuronal firing behaviour \citep{carbone_ion_2020}. Ion channel mutations are a common cause of such channelopathies and are often associated with hereditary clinical disorders including ataxias, epilepsies, pain disorders, dyskinesias, intellectual disabilities, myotonias, and periodic paralyses among others \citep{bernard_channelopathies_2008, carbone_ion_2020}. +Voltage-gated ion channels are vital in determining neuronal excitability, action potential generation and firing patterns \citep{bernard_channelopathies_2008, carbone_ion_2020}. In particular, the properties and combinations of ion channels and their resulting currents determine the firing properties of a neuron \citep{rutecki_neuronal_1992, pospischil_minimal_2008}. However, ion channel function can be disturbed, resulting in altered ionic current properties and altered neuronal firing behaviour \citep{carbone_ion_2020}. Ion channel mutations are a common cause of such channelopathies and are often associated with hereditary clinical disorders including ataxias, epilepsies, pain disorders, dyskinesias, intellectual disabilities, myotonias, and periodic paralyses among others \citep{bernard_channelopathies_2008, carbone_ion_2020}. \notenk{Are there any obvious citations missing from the following section?} -The effects of channelopathies on ionic current kinetics are frequently assessed by transfection of heterologous expression systems without endogenous currents \citep{Balestrini1044, Noebels2017, Dunlop2008}, and are frequently classified as either a loss of function (LOF) or a gain of function (GOF) with respect to changes in the amount of ionic current \citep{Musto2020, Kullmann2002, Waxman2011, Kim2021}. \notenk{Do you think we need to discuss LOF and GOF more than this?} \notels{LOF and GOF are usually not explained in detail, I would think it's fine} This classification can be used to make rough estimates of the effects on neuronal firing \textcolor{red}{(papers?\citep{Niday2018, Wei2017, Wolff2017}?)}, which in turn is important for understanding the pathophysiology of these disorders and for identification of potential therapeutic targets \citep{Orsini2018, Yang2018}. Genotype-phenotype relationships are complex and the understanding of the relationships between these is still evolving \citep{Wolff2017, johannesen_genotype-phenotype_2021}. Experimentally, the effects of channelopathies on neuronal firing can be assessed using primary neuronal cultures \citep{Scalmani2006, Smith2018, Liu2019} or \textit{in vitro} recordings from transgenic mouse lines \citep{Mantegazza2019, Xie2010,Lory2020, Habib2015, Hedrich2019}. +The effects of channelopathies on ionic current kinetics are frequently assessed by transfection of heterologous expression systems without endogenous currents \citep{Balestrini1044, Noebels2017, Dunlop2008}, and are frequently classified as either a loss of function (LOF) or a gain of function (GOF) with respect to changes in the amount of ionic current \notejb{or: ... changes in the magnitude of ionic currents flowing through the channels ?} \citep{Musto2020, Kullmann2002, Waxman2011, Kim2021}. This classification of the effects on ionic currents is often directly used to predict the effects on neuronal firing \textcolor{red}{(papers?\citep{Niday2018, Wei2017, Wolff2017}?)}, which in turn is important for understanding the pathophysiology of these disorders and for identification of potential therapeutic targets \citep{Orsini2018, Yang2018}. Genotype-phenotype relationships are complex and the understanding of the relationships between these is still evolving \citep{Wolff2017, johannesen_genotype-phenotype_2021}. Experimentally, the effects of channelopathies on neuronal firing can be assessed using primary neuronal cultures \citep{Scalmani2006, Smith2018, Liu2019} or \textit{in vitro} recordings from transgenic mouse lines \citep{Mantegazza2019, Xie2010,Lory2020, Habib2015, Hedrich2019}. %However the effect of a given channelopathy on different neuronal types across the brain is often unclear and not feasible to experimentally obtain. This is especially true when large numbers of distinct mutations are present and personalized medicine approaches are desired. @@ -178,9 +176,9 @@ The effects of channelopathies on ionic current kinetics are frequently assessed %General understanding of the effects of changes in current properties on neuronal firing may help to fill the need to understand the impacts of ion channel mutations on neuronal firing. -However the effect of a given channelopathy on different neuronal types across the brain is often unclear and not feasible to experimentally obtain. Different neuron types differ in their composition of ionic currents \citep{yao2021taxonomy, Cadwell2016, BICCN2021, Scala2021} and therefore likely respond differently to changes in the properties of one ionic current. +However the effect of a given channelopathy on firing behavior of different neuronal types across the brain is often unclear and not feasible to experimentally obtain. Different neuron types differ in their composition of ionic currents \citep{yao2021taxonomy, Cadwell2016, BICCN2021, Scala2021} and therefore likely respond differently to changes in the properties of a single ionic current. % \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. + 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 gating kinetics are affected 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,makinson_scn1a_2016} @@ -221,8 +219,7 @@ All modelling and simulation was done in parallel with custom written Python 3.8 % Linux 3.10.0-123.e17.x86_64. \subsection*{Different Cell Models} - A group of neuronal models representing the major classes of cortical and thalamic neurons including regular spiking pyramidal (RS pyramidal), regular spiking inhibitory (RS inhibitory), and fast spiking (FS) cells were used \citep{pospischil_minimal_2008}. To each of these models, a \Kv current (\IKv; \citealt{ranjan_kinetic_2019}) was added. A cerebellar stellate cell model from \citet{alexander_cerebellar_2019} is used (Cb stellate). This model was also used with a \Kv current \citep{ranjan_kinetic_2019} in addition to the A-type potassium current (Cb stellate +\Kv) or replacing the A-type potassium current (Cb stellate \(\Delta\)\Kv). A subthalamic nucleus neuron model as described by \citet{otsuka_conductance-based_2004} are used (STN) and with a \Kv current (\IKv; \citealp{ranjan_kinetic_2019}) in addition to the A-type potassium current (STN +\Kv) or replacing the A-type potassium current (STN \(\Delta\)\Kv). The properties and conductances of each model are detailed in \Cref{tab:g} and the gating properties are unaltered from the original Cb stellate and STN models. For comparability to typical electrophysiological data fitting reported and for ease of further gating curve manipulations, a Boltzmann function - \notels{is this still a Boltzmann function?}\notenk{I'm not sure, we could always say ``a Boltzmann function raise to a power''} + A group of neuronal models representing the major classes of cortical and thalamic neurons including regular spiking pyramidal (RS pyramidal), regular spiking inhibitory (RS inhibitory), and fast spiking (FS) cells were used \citep{pospischil_minimal_2008}. To each of these models, a \Kv current (\IKv; \citealt{ranjan_kinetic_2019}) was added. A cerebellar stellate cell model from \citet{alexander_cerebellar_2019} is used (Cb stellate). This model was also used with a \Kv current \citep{ranjan_kinetic_2019} in addition to the A-type potassium current (Cb stellate +\Kv) or replacing the A-type potassium current (Cb stellate \(\Delta\)\Kv). A subthalamic nucleus neuron model as described by \citet{otsuka_conductance-based_2004} are used (STN) and with a \Kv current (\IKv; \citealp{ranjan_kinetic_2019}) in addition to the A-type potassium current (STN +\Kv) or replacing the A-type potassium current (STN \(\Delta\)\Kv). The properties and conductances of each model are detailed in \Cref{tab:g} and the gating properties are unaltered from the original Cb stellate and STN models. For comparability to typical electrophysiological data fitting reported and for ease of further gating curve manipulations, a modified Boltzmann function \begin{equation}\label{eqn:Boltz} x_\infty = {\left(\frac{1-a}{1+{\exp\left[{\frac{V-V_{1/2}}{k}}\right]}} +a\right)^j} \end{equation} @@ -276,20 +273,20 @@ The code/software described in the paper is freely available online at [URL reda To examine the role of cell-type specific ionic current environments on the impact of altered ion channel properties on firing behaviour a set of neuronal models was used and properties of channels common across models were altered systematically one at a time. The effects of a set of episodic ataxia type~1 associated \Kv mutations on firing was then examined across different neuronal models with different ionic current environments. \subsection*{Firing Characterization} -\begin{figure}[ht!] +\begin{figure}[tp] \centering \includegraphics[width=0.5\linewidth]{Figures/firing_characterization.pdf} \\\notejb{Nils, can you put the python script of this figure into the git? I have some ideas I would like to try.} - \notenk{Should already be in \path{./Figures}, specifically file: \path{./Figures/firing_characterization.py}} + \notenk{Should already be in \path{./Figures}, specifically file: \path{./Figures/firing_characterization.py}}\notejb{Ok, thanks. plotstyle.py is missing in the repository. Can you please add it?} \linespread{1.}\selectfont \caption[]{Characterization of firing with AUC and rheobase. (A) The area under the curve (AUC) of the repetitive firing frequency-current (fI) curve. (B) Changes in firing as characterized by \(\Delta\)AUC and \(\Delta\)rheobase occupy 4 quadrants separated by no changes in AUC and rheobase. Representative schematic fI curves in blue with respect to a reference fI curve (black) depict the general changes associated with each quadrant.} \label{fig:firing_characterizaton} \end{figure} -Neuronal firing is a complex phenomenon and a quantification of firing properties is required for comparisons across cell types and between conditions. Here we focus on two aspects of firing: rheobase (smallest injected current at which the cell fires an action potential) and the initial shape of the frequency-current (fI) curve as quantified by the area under the curve (AUC) for input currents above rheobase (\Cref{fig:firing_characterizaton}A). The characterization of firing with AUC and rheobase enables determination of general increases or decreases in firing based on current-firing relationships. The upper left quadrant (+\(\Delta\)AUC and -\(\Delta\)rheobase) indicates a increased firing whereas the bottom right quadrant (-\(\Delta\)AUC and +\(\Delta\)rheobase) indicates decreased firing (\Cref{fig:firing_characterizaton}B). In the lower left (-\(\Delta\)AUC and -\(\Delta\)rheobase) and upper right (+\(\Delta\)AUC and +\(\Delta\)rheobase) quadrants, the effects on firing are less clear-cut and cannot easily be described as a gain or loss of excitability. +Neuronal firing is a complex phenomenon and a quantification of firing properties is required for comparisons across cell types and between conditions. Here we focus on two aspects of firing: rheobase (smallest injected current at which the cell fires an action potential) and the initial shape of the frequency-current (fI) curve as quantified by the area under the curve (AUC) for input currents above rheobase (\Cref{fig:firing_characterizaton}A). The characterization of firing with AUC and rheobase enables determination of general increases or decreases in firing based on current-firing relationships. The upper left quadrant (\(+\Delta\)AUC and \(-\Delta\)rheobase) indicates an increased firing whereas the bottom right quadrant (\(-\Delta\)AUC and \(+\Delta\)rheobase) indicates decreased firing (\Cref{fig:firing_characterizaton}B). In the lower left (\(-\Delta\)AUC and \(-\Delta\)rheobase) and upper right (\(+\Delta\)AUC and \(+\Delta\)rheobase) quadrants, the effects on firing are less clear-cut and cannot uniquely be described as a gain or loss of excitability. -\begin{figure}[ht!] +\begin{figure}[tp] \centering \includegraphics[width=\linewidth]{Figures/diversity_in_firing.pdf} \linespread{1.}\selectfont @@ -301,11 +298,12 @@ Neuronal firing is a complex phenomenon and a quantification of firing propertie Neuronal firing is heterogenous across the CNS and a set of neuronal models with heterogenous firing due to different ionic currents is desirable to reflect this heterogeneity. The set of neuronal models used here has considerable diversity as evident in the variability seen across neuronal models both in spike trains and their fI curves (\Cref{fig:diversity_in_firing}). The models chosen all fire tonically and do not exhibit bursting. Some models, such as Cb stellate and RS inhibitory models, display type I firing whereas others such as Cb stellate \(\Delta\)\Kv and STN models have type II firing. Type I firing is characterized by continuous fI curve (i.e. firing rate increases from 0 in a continuous fashion) generated through a saddle-node on invariant cycle bifurcation. Type II firing is characterized by a discontinuity in the fI curve (i.e. a jump occurs from no firing to firing at a certain frequency) due to sub-critical Hopf bifurcation \cite{ERMENTROUT2002, ermentrout_type_1996}. The other models used here lie on a continuum between these prototypical firing classifications. Most neuronal models exhibit hysteresis with ascending and descending ramps eliciting spikes with different thresholds, however the STN +\Kv, STN \(\Delta\)\Kv, and Cb stellate \(\Delta\)\Kv models have large hysteresis (\Cref{fig:diversity_in_firing}, \Cref{fig:ramp_firing}). \subsection*{Sensitivity Analysis} -Sensitivity analyses are used to understand how input model parameters contribute to determining the output of a model \citep{Saltelli2002}. In other words, sensitivity analyses are used to understand how sensitive the output of a model is to a change in input or model parameters. One-factor-a-time sensitivity analyses involve altering one parameter at a time and assessing the impact of this parameter on the output. This approach enables the comparison of given alterations in parameters of ionic currents across models. Changes in gating \(V_{1/2}\) and slope factor \(k\) as well as the maximum conductance affect AUC (\Cref{fig:AUC_correlation} A, B and C). Heterogeneity in the correlation between gating and conductance changes and AUC occurs across models for most ionic currents. In these cases some of the models display non-monotonic relationships or no relationship (i.e. \( |\text{Kendall} \tau | \approx 0\)\notejb{is this right?} \notenk{Yes, although it is perhaps a bit misleadingly written as this is not the only situation in which the Kendall \(\tau \approx 0\). Kendall \(\tau\) is a measure of monotonic relationships so if there is no relationship or the relationship is completely non-monotonic (i.e. a parabola) then the Kendall \(\tau\) is zero. I added ``or no relationship'' to make this clearer}). However, shifts in A-current activation \(V_{1/2}\), changes in \Kv activation \(V_{1/2}\) and slope factor \(k\), and changes in A-current conductance display consistent monotonic relationships across models. The impact of a similar change in \(V_{1/2}\), slope factor \(k\), or conductance of different currents will impact firing behaviour dfferently not just within and between models. +Sensitivity analyses are used to understand how input model parameters contribute to determining the output of a model \citep{Saltelli2002}. In other words, sensitivity analyses are used to understand how sensitive the output of a model is to a change in input or model parameters. One-factor-a-time sensitivity analyses involve altering one parameter at a time and assessing the impact of this parameter on the output. This approach enables the comparison of given alterations in parameters of ionic currents across models. Changes in gating \(V_{1/2}\) and slope factor \(k\) as well as the maximum conductance affect AUC (\Cref{fig:AUC_correlation} A, B and C). Heterogeneity in the correlation between gating and conductance changes and AUC occurs across models for most ionic currents. In these cases some of the models display non-monotonic relationships or no relationship (\( |\text{Kendall} \tau | \approx 0\)). However, shifts in A-current activation \(V_{1/2}\), changes in \Kv activation \(V_{1/2}\) and slope factor \(k\), and changes in A-current conductance display consistent monotonic relationships across models (\( |\text{Kendall} \tau | \ne 0\)). The impact of a similar change in \(V_{1/2}\), slope factor \(k\), or conductance of different currents will impact firing behaviour differently not just within and between models \notejb{something is wrong with `` not just within and between models'', I do not understand what the message should be}. -\begin{figure}[ht!] +\begin{figure}[tp] \centering \includegraphics[width=\linewidth]{Figures/AUC_correlation.pdf} + \\\notejb{tick labels too small!} \linespread{1.}\selectfont \caption[]{The Kendall rank correlation (Kendall \(\tau\)) coefficients between shifts in \(V_{1/2}\) and AUC, slope factor k and AUC as well as current conductances and AUC for each model are shown on the right in (A), (B) and (C) respectively. The relationships between AUC and \(\Delta V_{1/2}\), slope (k) and conductance (g) for the Kendall \(\tau\) coefficients highlights by the black box are depicted in the middle panel. The fI curves corresponding to one of the models are shown in the left panels.} \label{fig:AUC_correlation} @@ -313,7 +311,7 @@ Sensitivity analyses are used to understand how input model parameters contribut Alterations in gating \(V_{1/2}\) and slope factor \(k\) as well as the maximum conductance also play a role in determining rheobase (\Cref{fig:rheobase_correlation} A, B and C). Shifts in half activation of gating properties are similarly correlated with rheobase across models, however Kendall \(\tau\) values departing from \(-1\) indicate non-monotonic or no relationships between K-current \(V_{1/2}\) and rheobase in some models (\Cref{fig:rheobase_correlation}A). Changes in Na-current inactivation, \Kv-current inactivation, and A-current activation affect rheobase with positive and negative correlations in different models (\Cref{fig:rheobase_correlation}B). Departures from monotonic relationships occur in some models as a result of K-current activation, \Kv-current inactivation, and A-current activation in some models. Maximum conductance affects rheobase similarly across models (\Cref{fig:rheobase_correlation}C). However, identical changes in current gating properties such as activation or inactivation \(V_{1/2}\) or slope factor \(k\) can have differing effects on firing depending on the model in which they occur. -\begin{figure}[ht!] +\begin{figure}[tp] \centering \includegraphics[width=\linewidth]{Figures/rheobase_correlation.pdf} \\\notejb{Oben rechts: linebreak in ``A inactivation'' is weird} @@ -326,7 +324,7 @@ Alterations in gating \(V_{1/2}\) and slope factor \(k\) as well as the maximum \subsection*{\Kv Mutations} Mutations in \Kv are associated with episodic ataxia type~1 (EA1) and have been characterized biophysically \citep{lauxmann_therapeutic_2021}. They are used here as a case study in the effects of various ionic current environments on neuronal firing and on the outcomes of channelopathies. The changes in AUC and rheobase from wild type values for reported EA1 associated \Kv mutations are heterogenous across models containing \Kv, but generally show decreases in rheobase (\Cref{fig:simulation_model_comparision}A-I). Pairwise non-parametric Kendall \(\tau\) rank correlations between the simulated effects of these \Kv mutations on rheobase are highly correlated across models (\Cref{fig:simulation_model_comparision}J) indicating that EA1 associated \Kv mutations generally decrease rheobase across diverse cell-types. However, the effects of the \Kv mutations on AUC are more heterogenous as reflected by both weak and strong positive and negative pairwise correlations between models (\Cref{fig:simulation_model_comparision}K), suggesting that the effects of ion-channel variant on super-threshold neuronal firing depend on the specific composition of ionic currents in a given neuron. -\begin{figure}[ht!] +\begin{figure}[tp] \centering \includegraphics[width=\linewidth]{Figures/simulation_model_comparison.pdf} \linespread{1.}\selectfont @@ -337,7 +335,7 @@ Mutations in \Kv are associated with episodic ataxia type~1 (EA1) and have been \section*{Discussion (3000 Words Maximum - Currently 2145)} % \textit{The discussion section should include a brief statement of the principal findings, a discussion of the validity of the observations, a discussion of the findings in light of other published work dealing with the same or closely related subjects, and a statement of the possible significance of the work. Extensive discussion of the literature is discouraged.}\\ -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. +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} @@ -449,7 +447,7 @@ Accordingly, for accurate modelling and predictions of the effects of mutations \captionof{Extended Data}{TODO: Caption for code in zip file.} \beginsupplement -\begin{figure}[ht!]%described +\begin{figure}[tp]%described \centering \includegraphics[width=\linewidth]{Figures/ramp_firing.pdf} \linespread{1.}\selectfont