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nonlinearbaseline.tex
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@ -544,7 +544,7 @@ Electric fish possess an additional electrosensory system, the passive or ampull
\subsection{Model-based estimation of the second-order susceptibility}
In the example recordings shown above (\figsrefb{fig:punit} and \fref{fig:ampullary}), we only observe nonlinear responses where the sum of the two stimulus frequencies matches the neuron's baseline firing rate, but not where either og the frequencies alone matches the baseline rate. In the following, we investigate this discrepancy to the theoretical expectations \citep{Voronenko2017,Franzen2023}.
In the example recordings shown above (\figsrefb{fig:punit} and \fref{fig:ampullary}), we only observe nonlinear responses where the sum of the two stimulus frequencies matches the neuron's baseline firing rate, but not where either of the frequencies alone matches the baseline rate. In the following, we investigate this discrepancy to the theoretical expectations \citep{Voronenko2017,Franzen2023}.
\begin{figure*}[p]
\includegraphics[width=\columnwidth]{noisesplit}
@ -577,7 +577,9 @@ The SI($r$) correlates with the CVs of the cell's baseline interspike intervals
\subsection{Weakly nonlinear interactions vanish for higher stimulus contrasts}
As pointed out above, the weakly nonlinear regime can only be observed for sufficiently weak stimuli. In the model cells we estimated second-order susceptibilities for RAM stimuli with a contrast of 1, 3, and 10\,\%. The estimates for 1\,\% contrast (\figrefb{fig:modelsusceptcontrasts}\,\panel[ii]{E}) were quite similar to the estimates from the noise-split method, corresponding to a stimulus contrast of 0\,\% ($r=0.97$, $p\ll 0.001$). Thus, RAM stimuli with 1\,\% contrast are sufficiently small to not destroy weakly nonlinear interactions by their linearizing effect. At this low contrast, 51\,\% of the model cells have an SI($r$) value greater than 1.2.
\notebl{As pointed out above, the weakly nonlinear regime can only be observed for sufficiently weak \notejb{noise} stimuli: strong \notejb{noise} simuli act as a linearizing background noise and thus shift the neural signal transmission into a regime free of nonlinearities. What exactly constitutes a 'strong' stimulus causing an effective increase of the background noise, also depends on all the other cellular properties of the neuron, or on the parameters in our leaky integrate-and-fire neuron. This is what we explore now by varying the contrast of RAM stimuli driving our model cells.}
In the model cells we estimated second-order susceptibilities for RAM stimuli with a contrast of 1, 3, and 10\,\%. The estimates for 1\,\% contrast (\figrefb{fig:modelsusceptcontrasts}\,\panel[ii]{E}) were quite similar to the estimates from the noise-split method, corresponding to a stimulus contrast of 0\,\% ($r=0.97$, $p\ll 0.001$). Thus, RAM stimuli with 1\,\% contrast are sufficiently small to not destroy weakly nonlinear interactions by their linearizing effect. At this low contrast, 51\,\% of the model cells have an SI($r$) value greater than 1.2.
At a RAM contrast of 3\,\% the SI($r$) values become smaller (\figrefb{fig:modelsusceptcontrasts}\,\panel[iii]{E}). Only 7 cells (18\,\%) have SI($r$) values exceeding 1.2. Finally, at 10\,\% the SI($r$) values of all cells drop below 1.2, except for three cells (8\,\%, \figrefb{fig:modelsusceptcontrasts}\,\panel[iv]{E}). The cell shown in \subfigrefb{fig:modelsusceptcontrasts}{A} is one of them. At 10\,\% contrast the SI($r$) values are no longer correlated with the ones in the noise-split configuration ($r=0.32$, $p=0.05$). To summarize, the regime of distinct nonlinear interactions at frequencies matching the baseline firing rate extends in this set of P-unit model cells to stimulus contrasts ranging from a few percents to about 10\,\%.