updates from Stephan and Lukas comments

Figures/model_g.py

@@ -125,9 +125,23 @@ def plot_g(ax, df, models, i, let_x, let_y, titlesize=10, letsize=12):
     ax.text(let_x, let_y, string.ascii_uppercase[i], transform=ax.transAxes, size=letsize, weight='bold')
     ax.set_yscale('log')
     ax.set_xlim(-0.5, 9)
+    ymin, ymax = ax.get_ylim()
+    # ax.set_ylim(0.001, df[models[i]].max())
     from matplotlib.ticker import ScalarFormatter
     for axis in [ax.yaxis]:
         axis.set_major_formatter(ScalarFormatter())
+    if i == 1 or i == 4:
+        print(i)
+        ax.set_yticks([0.1,1.0, 10])
+        # ax.yaxis.set_major_formatter(ScalarFormatter())
+
+        # ax.set_yticklabels([0.1,1.0, 10])
+        # ax.set_yscale('log')
+    import matplotlib.ticker
+    # ax.yaxis.set_minor_formatter(matplotlib.ticker.NullFormatter())
+    locmin = matplotlib.ticker.LogLocator(base=10.0, subs=(0.1, 0.2, 0.4, 0.6, 0.8, 1, 2, 4, 6, 8, 10), numticks=100)
+    ax.yaxis.set_minor_locator(locmin)
+    ax.yaxis.set_minor_formatter(matplotlib.ticker.NullFormatter())
     return ax
 
 

Frontiers_manuscript/For_Submission/Koch_frontiers_diff.tex

@@ -1,7 +1,7 @@
 \documentclass[utf8]{FrontiersinHarvard} 
 %DIF LATEXDIFF DIFFERENCE FILE
-%DIF DEL Koch_frontiers.tex           Mon Mar 27 10:08:50 2023
-%DIF ADD Koch_frontiers_revised.tex   Sat Apr 22 11:15:46 2023
+%DIF DEL Koch_Frontiers.tex           Mon Mar 27 10:08:50 2023
+%DIF ADD Koch_Frontiers_revised.tex   Mon Apr 24 09:24:45 2023
 \DeclareUnicodeCharacter{03B2}{\(\beta\)}
 \DeclareUnicodeCharacter{03B1}{\(\alpha\)}
 \DeclareUnicodeCharacter{00C5}{\AA}
@@ -222,7 +222,7 @@ To capture the diversity in neuronal ion channel expression and its relevance in
 
 \subsection{Ionic Current Environments Determine the Effect of Ion Channel Mutations}
 
-To our knowledge, no comprehensive evaluation of how ionic current environment and neuron type affect the outcome of ion channel mutations have been reported. However, comparisons between the effects of such mutations between certain neuron types were described. For instance, the R1648H mutation in \textit{SCN1A} does not alter the excitability of cortical pyramidal neurons, but causes hypoexcitability of adjacent inhibitory GABAergic neurons \citep{Hedrich14874}. In the CA3 region of the hippocampus, the equivalent mutation in \textit{SCN8A}, R1627H, increases the excitability of pyramidal neurons and decreases the excitability of parvalbumin positive interneurons \cite{makinson_scn1a_2016}. Additionally, the L858H mutation in \(\text{Na}_\text{V}\text{1.7}\), 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 \(\text{Na}_\text{V}\text{1.7}\) on firing is dependent on the presence or absence of another sodium channel, namely the \(\text{Na}_\text{V}\text{1.8}\) subunit \citep{Waxman2007, Rush2006}.  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. \DIFaddbegin \DIFadd{However, many differences can exist between neuron types at multiple levels of scale not only in ion channel composition. Despite this complexity, the simulations performed here demonstrate that differential ion channel composition is sufficient to cause neuron type differences in the effects of ion channel mutations.
+To our knowledge, no comprehensive evaluation of how ionic current environment and neuron type affect the outcome of ion channel mutations have been reported. However, comparisons between the effects of such mutations between certain neuron types were described. For instance, the R1648H mutation in \textit{SCN1A} does not alter the excitability of cortical pyramidal neurons, but causes hypoexcitability of adjacent inhibitory GABAergic neurons \citep{Hedrich14874}. In the CA3 region of the hippocampus, the equivalent mutation in \textit{SCN8A}, R1627H, increases the excitability of pyramidal neurons and decreases the excitability of parvalbumin positive interneurons \cite{makinson_scn1a_2016}. Additionally, the L858H mutation in \(\text{Na}_\text{V}\text{1.7}\), associated with \DIFdelbegin \DIFdel{erythermyalgia}\DIFdelend \DIFaddbegin \DIFadd{erythromelalgia}\DIFaddend , 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 \(\text{Na}_\text{V}\text{1.7}\) on firing is dependent on the presence or absence of another sodium channel, namely the \(\text{Na}_\text{V}\text{1.8}\) subunit \citep{Waxman2007, Rush2006}.  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. \DIFaddbegin \DIFadd{However, many differences can exist between neuron types at multiple levels of scale not only in ion channel composition. Despite this complexity, the simulations performed here demonstrate that differential ion channel composition is sufficient to cause neuron type differences in the effects of ion channel mutations.
 }\DIFaddend 
 
 Neuron type specific differences in ionic current properties are important in the effects of ion channel mutations. However, within a neuron 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,OLeary2016}. 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 behavior of a heterogeneous neuron population \citep{verma_computational_2020}. For example, a model derived from the mean conductances in a neuronal sub-population within the stomatogastric ganglion, the so-called "one-spike bursting" neurons fire three spikes instead of one per burst due to an L-shaped distribution of sodium and potassium conductances \citep{golowasch_failure_2002}.  Multiple sets of 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}. The variability in ion channel expression often correlates with the expression of other ion channels \citep{goaillard_ion_2021} and neurons whose behavior is similar may possess correlated variability across different ion channels resulting in stability in the neuronal phenotype \citep{lamb_correlated_2013, soofi_co-variation_2012, taylor_how_2009}. The variability of ionic 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}.
@@ -308,7 +308,7 @@ Changes in firing as characterized by \(\Delta\)AUC and \(\Delta\)rheobase occup
         \centering
         \includegraphics[width=\linewidth]{summary_fig.jpg}
         \linespread{1.}\selectfont
-	\caption[]{\DIFaddFL{Summary of neuron type dependence of channelopathies. The wild type channel (WT, blue) is mutated (Mutant, red) the effects of it in different neuron types (green, orange and grey) each with a unique set of ion channels (see inset axes) determines the effect of firing seen on the right by the shift from the blue wild type fI curve to the red fI curve for the mutated ion channel. Square root functions are used as fI curves for illustration purposes.}}
+	\caption[]{\DIFaddFL{Summary of neuron type dependence of channelopathies. A wild type channel (WT, blue) is mutated (Mutant, red) and expressed in different neuron types (green, orange and grey) each with a unique set of ion channels (see inset axes). The current composition of each neuron determines the effect of firing seen by the shift from the blue wild type fI curve to the red fI curve for the mutated ion channel on the right. Square root functions are used as fI curves for illustration purposes.}}
         \label{fig:summary}
 \DIFaddendFL \end{figure}
 

Frontiers_manuscript/For_Submission/Koch_frontiers_revised.tex

@@ -178,7 +178,7 @@ To capture the diversity in neuronal ion channel expression and its relevance in
 
 \subsection{Ionic Current Environments Determine the Effect of Ion Channel Mutations}
 
-To our knowledge, no comprehensive evaluation of how ionic current environment and neuron type affect the outcome of ion channel mutations have been reported. However, comparisons between the effects of such mutations between certain neuron types were described. For instance, the R1648H mutation in \textit{SCN1A} does not alter the excitability of cortical pyramidal neurons, but causes hypoexcitability of adjacent inhibitory GABAergic neurons \citep{Hedrich14874}. In the CA3 region of the hippocampus, the equivalent mutation in \textit{SCN8A}, R1627H, increases the excitability of pyramidal neurons and decreases the excitability of parvalbumin positive interneurons \cite{makinson_scn1a_2016}. Additionally, the L858H mutation in \(\text{Na}_\text{V}\text{1.7}\), 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 \(\text{Na}_\text{V}\text{1.7}\) on firing is dependent on the presence or absence of another sodium channel, namely the \(\text{Na}_\text{V}\text{1.8}\) subunit \citep{Waxman2007, Rush2006}.  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. However, many differences can exist between neuron types at multiple levels of scale not only in ion channel composition. Despite this complexity, the simulations performed here demonstrate that differential ion channel composition is sufficient to cause neuron type differences in the effects of ion channel mutations.
+To our knowledge, no comprehensive evaluation of how ionic current environment and neuron type affect the outcome of ion channel mutations have been reported. However, comparisons between the effects of such mutations between certain neuron types were described. For instance, the R1648H mutation in \textit{SCN1A} does not alter the excitability of cortical pyramidal neurons, but causes hypoexcitability of adjacent inhibitory GABAergic neurons \citep{Hedrich14874}. In the CA3 region of the hippocampus, the equivalent mutation in \textit{SCN8A}, R1627H, increases the excitability of pyramidal neurons and decreases the excitability of parvalbumin positive interneurons \cite{makinson_scn1a_2016}. Additionally, the L858H mutation in \(\text{Na}_\text{V}\text{1.7}\), associated with erythromelalgia, 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 \(\text{Na}_\text{V}\text{1.7}\) on firing is dependent on the presence or absence of another sodium channel, namely the \(\text{Na}_\text{V}\text{1.8}\) subunit \citep{Waxman2007, Rush2006}.  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. However, many differences can exist between neuron types at multiple levels of scale not only in ion channel composition. Despite this complexity, the simulations performed here demonstrate that differential ion channel composition is sufficient to cause neuron type differences in the effects of ion channel mutations.
 
 Neuron type specific differences in ionic current properties are important in the effects of ion channel mutations. However, within a neuron 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,OLeary2016}. 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 behavior of a heterogeneous neuron population \citep{verma_computational_2020}. For example, a model derived from the mean conductances in a neuronal sub-population within the stomatogastric ganglion, the so-called "one-spike bursting" neurons fire three spikes instead of one per burst due to an L-shaped distribution of sodium and potassium conductances \citep{golowasch_failure_2002}.  Multiple sets of 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}. The variability in ion channel expression often correlates with the expression of other ion channels \citep{goaillard_ion_2021} and neurons whose behavior is similar may possess correlated variability across different ion channels resulting in stability in the neuronal phenotype \citep{lamb_correlated_2013, soofi_co-variation_2012, taylor_how_2009}. The variability of ionic 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}.
 
@@ -259,7 +259,7 @@ Changes in firing as characterized by \(\Delta\)AUC and \(\Delta\)rheobase occup
         \centering
         \includegraphics[width=\linewidth]{summary_fig.jpg}
         \linespread{1.}\selectfont
-	\caption[]{Summary of neuron type dependence of channelopathies. The wild type channel (WT, blue) is mutated (Mutant, red) the effects of it in different neuron types (green, orange and grey) each with a unique set of ion channels (see inset axes) determines the effect of firing seen on the right by the shift from the blue wild type fI curve to the red fI curve for the mutated ion channel. Square root functions are used as fI curves for illustration purposes.}
+	\caption[]{Summary of neuron type dependence of channelopathies. A wild type channel (WT, blue) is mutated (Mutant, red) and expressed in different neuron types (green, orange and grey) each with a unique set of ion channels (see inset axes). The current composition of each neuron determines the effect of firing seen by the shift from the blue wild type fI curve to the red fI curve for the mutated ion channel on the right. Square root functions are used as fI curves for illustration purposes.}
         \label{fig:summary}
 \end{figure}
 

Frontiers_manuscript/For_Submission/Koch_reviewer_comments.tex

@@ -63,7 +63,6 @@
 
 \section{Reviewer 1}
 
-
 \textit{Although the proposed study for publication presents an up-to-date approach, it does not bring any innovation beyond the previous studies (Hedrich et al., 2014; Makinson et al., 2016; Waxman, 2007; Rush et al., 2006).}
 
 We thank the reviewer for their comments. Although previous studies (Hedrich et al., 2014; Makinson et al., 2016; Waxman, 2007; Rush et al., 2006) referred to by the reviewer and discussed in our manuscript investigate differences in outcomes of ion channel mutations in different neuronal types, these studies have addressed specific instances in which this is the case. For instance, Waxman, 2007 and Rush et al., 2006 demonstrate the dependence of Nav1.7 mutations on the presence/absence of Nav1.8. However whether the outcome of the mutation is graded with different levels of Nav1.8 or whether this effect is modulated by other channels is not investigated nor known. In this context, our work furthers the current knowledge that certain ion channel mutations can have different effects on firing in specific contexts (i.e. cell types) by generalizing this viewpoint to demonstrate that the effects of any ion channel mutation will depend in the neuron-type and its ion channel composition. This suggests that holistic understanding of the effects of ion channel mutations likely requires a more specific neuron-type dependent level of understanding than is generally used currently.  Although many differences can exist between neuron types, this study demonstrates that different ion channel composition alone is sufficient to cause neuron type specific ion channel mutation firing effects. The ``Ionic Current Environments Determine the Effect of Ion Channel Mutations'' section of the discussion has been updated to clarify this.
@@ -82,7 +81,7 @@ We thank the reviewer for their question. The complexity noted in the reviewers
 
 \textit{Failure to analyze the effects of the obtained data on living organisms casts a shadow over the reliability of the results. The study would be much more valuable if the authors could at least support their results with animal experiments. Otherwise, it will not go beyond being an evaluation study based on already known mutations. This limits the originality of the study.}
 
-Although we agree that data obtained from animal experiments is invaluable in the investigation of channelopathies and in neuroscience and neurology generally, the modelling and simulation in this study serves to provide a theoretical framework (Figures 3 and 4) to explain why neuron-type level investigation is important in understanding of ion channel mutations. Furthermore, efforts to reduce animal experimentation are ongoing and modelling approaches such as that presented in this study enables the reduction of animal experimentation. Previous experimental studies (Hedrich et al., 2014; Makinson et al., 2016; Waxman, 2007; Rush et al., 2006) have demonstrated neuron-type specific effects of ion channel mutations. Therefore, experimental efforts should be focused on validation and investigation of specific cases rather than accumulation of evidence for the general neuron-type dependence. Although we recognize the importance and value in the discovery of new mutations, further investigation and analysis of known mutations and their effects is also valuable and essential for understanding the effects of ion channel mutations at multiple levels of scale. This has been added to the Modelling limitations section of the discussion.
+Although we agree that data obtained from animal experiments is invaluable in the investigation of channelopathies and in neuroscience and neurology generally, the modelling and simulation in this study serves to provide a theoretical framework (Figures 3 and 4) to explain why neuron-type level investigation is important in understanding of ion channel mutations. Furthermore, efforts to reduce animal experimentation are ongoing and modelling approaches such as that presented in this study enables the reduction of animal experimentation. Previous experimental studies (Hedrich et al., 2014; Makinson et al., 2016; Waxman, 2007; Rush et al., 2006) have demonstrated neuron-type specific effects of ion channel mutations. Therefore, experimental efforts should be focused on validation and investigation of specific cases rather than accumulation of evidence for the general neuron-type dependence. Furthermore, the development of neuron type specific models enables informed hypothesis generation for such electrophysiological experimentation and enables testing of hypotheses that are difficult to test experimentally. Although we recognize the importance and value in the discovery of new mutations, further investigation and analysis of known mutations and their effects is also valuable and essential for understanding the effects of ion channel mutations at multiple levels of scale. This has been added to the Modelling limitations section of the discussion.
 
 
 \section{Reviewer 2}