Our analysis revealed several parameters that proved critical in the expression and control of spike rebounds in DCN neurons. Foremost of these were the values of ECl and the inactivation voltages of rebound currents, since rebounds could only be elicited via synaptic mechanisms if ECl was approaching or negative to the half-inactivation voltages of rebound currents. In neurons, ECl is controlled by the chloride cotransporters NKCC1 and KCC2 (Banke and McBain
2006; Rivera et al.
1999). Hyperpolarizing shifts in ECl occur mostly due to an increase in KCC2, which in many neurons occurs developmentally (Rivera et al.
1999). KCC2 can also be regulated through phosphorylation (Lee et al.
2007) and external potassium concentration (Zhu et al.
2005), and depending on these mechanisms and the density of KCC2 expression ECl can attain a large range of values. The expression of KCC2 and variability of ECl have not been studied in DCN neurons so far, but our modeling study makes a strong prediction that ECl should be relatively hyperpolarized (−75 mV or below) to enable strong rebound spiking. In slices obtained from mature guinea pigs an average reversal of IPSPs was found at −74.3 mV with sharp intracellular recordings (Jahnsen
1986b), a value also supported by a more recent study using perforated patch recordings (Zheng and Raman
2009). Our simulations indicate that this value of ECl is in a critical region where small changes would have a strong influence on rebound strength. Thus, regulation of KCC2 in DCN neurons would have great impact on rebound behavior, and could occur as a mechanism of excitability plasticity. Similar observations hold for the values of activation and inactivation voltages of the rebound conductances. The activation voltage of I
HCN in DCN neurons has been found to be fairly hyperpolarized in juvenile mice (Raman et al.
2000). In our own whole cell data from juvenile rats I
HCN activation is frequently observed when the membrane potential reaches −70 mV (Fig.
3). Discrepancies in HCN measurements could arise from species and age differences, but could also be due to a different level of cAMP and cGMP modulation of HCN channels in different preparations, which can potentially lead to large shifts in activation voltage (Pape
1996). The half-inactivation voltage of I
CaT in thalamus was determined as −80 mV (Destexhe et al.
1998), but again this value can be shifted through modulation (Jagodic et al.
2007; Traboulsie et al.
2006), and may also differ between channel isoforms. The half-inactivation voltage for I
NaP was set to −80 mV in our model as this value matched our own experimental findings on slow rebounds. Previous studies show generally a somewhat more positive half-inactivation voltage of persistent sodium current, with differing values between cell types, however (Aracri et al.
2006). Our simulation data lead to the prediction that I
NaP in DCN neurons may have a more negative half-inactivation voltage than in other cell types.
It is important to note that the model performance is not highly sensitive to the specific value for these parameters chosen in the model. A graded change in model parameters for rebound conductances leads to a graded change in rebound behavior. Thus, our simulation results indicate that different levels of rebound conductances and modulation of activation or inactivation kinetics can account for the cell to cell heterogeneity in the rebound strengths and patterns present in our slice recordings. It is also possible, of course, that additional rebound conductances may exist in DCN neurons that are not currently included in our model. One candidate is the L-type calcium current, which for example in subthalamic nucleus neurons slowly inactivates and can produce rebound behavior (Otsuka et al.
2004). This current is unlikely to be of significant amplitude in DCN neurons, however, as the Na channel blocker TTX removes all post-hyperpolarization plateau potentials (Sangrey and Jaeger
2005).