Neuromodulation independently determines correlated channel expression and conductance levels in motor neurons of the stomatogastric ganglion

Abstract

Neuronal identity depends on the regulated expression of numerous molecular components, especially ionic channels, which determine the electrical signature of a neuron. Such regulation depends on at least two key factors, activity itself and neuromodulatory input. Neuronal electrical activity can modify the expression of ionic currents in homeostatic or nonhomeostatic fashion. Neuromodulators typically modify activity by regulating the properties or expression levels of subsets of ionic channels. In the stomatogastric system of crustaceans, both types of regulation have been demonstrated. Furthermore, the regulation of the coordinated expression of ionic currents and the channels that carry these currents has been recently reported in diverse neuronal systems, with neuromodulators not only controlling the absolute levels of ionic current expression but also, over long periods of time, appearing to modify their correlated expression. We hypothesize that neuromodulators may regulate the correlated expression of ion channels at multiple levels and in a cell-type-dependent fashion. We report that in two identified neuronal types, three ionic currents are linearly correlated in a pairwise manner, suggesting their coexpression or direct interactions, under normal neuromodulatory conditions. In each cell, some currents remain correlated after neuromodulatory input is removed, whereas the correlations between the other pairs are either lost or altered. Interestingly, in each cell, a different suite of currents change their correlation. At the transcript level we observe distinct alterations in correlations between channel mRNA amounts, including one of the cell types lacking a correlation under normal neuromodulatory conditions and then gaining the correlation when neuromodulators are removed. Synaptic activity does not appear to contribute, with one possible exception, to the correlated expression of either ionic currents or of the transcripts that code for the respective channels. We conclude that neuromodulators regulate the correlated expression of ion channels at both the transcript and the protein levels.

Rapid Homeostatic Plasticity of Intrinsic Excitability in a Central Pattern Generator Network Stabilizes Functional Neural Network Output

“…Current and voltage traces were sometimes filtered with a lowpass boxcar filter using 7 smoothing points. Most voltage clamps were modified from those used previously in STG preparations (Golowasch and Marder, 1992;Khorkova and Golowasch, 2007;Temporal et al, 2012). High threshold potassium current (I HTK ) magnitude was measured using a leak subtracted TEVC protocol with a holding potential of Ϫ40 mV and 16 voltage steps from Ϫ55 mV to ϩ20 mV (5 mV intervals).…”

“…Compensation in CPG circuits may be inferred from the fact that normal populations of unmanipulated motor neurons of two invertebrate CPGs, the cardiac and stomatogastric ganglia, show correlations in expression levels of mRNAs for ion channels (Schulz et al, 2007;Tobin et al, 2009) and membrane conductances (Khorkova and Golowasch, 2007;Temporal et al, 2012). One relationship detected in previous work (Tobin et al, 2009) is a positive correlation between BKKCa and shaker mRNA levels in neurons of the cardiac ganglion.…”

Modelling the restoration of activity in a biological neural network

“…Taking such correlations between maximal conductance values into consideration reduces the complexity of the search for appropriate parameters for the model of a given STG neuron. At the same time it should be noted that the experimentally determined ranges of conductance parameters of STG neurons are wide [15]. It has also been discovered that the correlations of maximal conductance values depend on the neuromodulatory context of the STG neurons.…”

“…We ran 200 simulations of the network in order to assess the robustness against small random variations of the parameters. We note that conductance parameters can vary in biological STG neurons to a considerable extent and in some cases many folds [14,15]. To analyse the simulations we ran each of them for 150,000 time steps and considered the last 100,000 time steps for the analysis in order to avoid the part of the simulation where the steady state behaviour of the model is not yet reached.…”

Degradation of extracellular chondroitin sulfate delays recovery of network activity after perturbation

“…Changes in intrinsic K ϩ and Ca 2ϩ currents and synaptic efficacy occur after deafferentation to compensate for this loss and restore pyloric activity (Haedo and Golowasch 2006;Khorkova and Golowasch 2007;Thoby-Brisson and Simmers 2002). The driving factor behind these changes is unclear; where some studies suggest activity-dependent or Ca 2ϩ -dependent changes (Golowasch et al 1999), others suggest that the presence or absence of NMs is the only signal required to induce recovery (Khorkova and Golowasch 2007;Temporal et al 2012). However, the time to first bout (t bout ) (suddenly increased frequency) after deafferentation depends on the history of network activity before deafferentation or the application of NMs that alter network activity, suggesting that recovery requires coordinated action of both activity-and NM-dependent pathways (Zhang et al 2009).…”