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Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells.

Steuber V, Schultheiss NW, Silver RA, De Schutter E, Jaeger D - J Comput Neurosci (2010)

Bottom Line: Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than -70 mV to allow de-inactivation of rebound currents.Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current.Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum.

View Article: PubMed Central - PubMed

Affiliation: Science and Technology Research Institute, University of Hertfordshire, Hatfield Herts, AL10 9AB, UK.

ABSTRACT
Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than -70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum.

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Rebound rates and latencies for different current injection amplitudes and durations in simulations of Neuron 1. (a) Rebound rate profiles for 0.5 and 0.0625 s duration current injections of varying amplitude. For the longest current injection, even this low density of GNaP leads to a prolonged rebound period from 12.1 Hz baseline to 23.2 Hz after −250 pA current injection (rate averaged over 500 ms). (b) For all durations of current injection, the rebound spike rate increases with the amplitude of injected current. (c) The relationship between current amplitude and rebound latency is more complex. While lowering the amplitude of injected current increases the rebound latency for long current injections, the relationship is reversed for short current injections. This effect is due to IHCN (see Section 3 and Fig. 5)
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Fig8: Rebound rates and latencies for different current injection amplitudes and durations in simulations of Neuron 1. (a) Rebound rate profiles for 0.5 and 0.0625 s duration current injections of varying amplitude. For the longest current injection, even this low density of GNaP leads to a prolonged rebound period from 12.1 Hz baseline to 23.2 Hz after −250 pA current injection (rate averaged over 500 ms). (b) For all durations of current injection, the rebound spike rate increases with the amplitude of injected current. (c) The relationship between current amplitude and rebound latency is more complex. While lowering the amplitude of injected current increases the rebound latency for long current injections, the relationship is reversed for short current injections. This effect is due to IHCN (see Section 3 and Fig. 5)

Mentions: The effect of stimulus amplitude was preserved for different stimulus durations, but stimulus duration had important additional effects. Because the de-inactivation time constant of ICaT was much shorter than that of INaP (101 vs 483 ms at −80 mV), a fast rebound could develop already after short hyperpolarizing stimuli of 62.5 ms, whereas it took stimuli of at least 125 ms duration to evoke a strong prolonged rebound (Figs. 7, 8).Fig. 7


Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells.

Steuber V, Schultheiss NW, Silver RA, De Schutter E, Jaeger D - J Comput Neurosci (2010)

Rebound rates and latencies for different current injection amplitudes and durations in simulations of Neuron 1. (a) Rebound rate profiles for 0.5 and 0.0625 s duration current injections of varying amplitude. For the longest current injection, even this low density of GNaP leads to a prolonged rebound period from 12.1 Hz baseline to 23.2 Hz after −250 pA current injection (rate averaged over 500 ms). (b) For all durations of current injection, the rebound spike rate increases with the amplitude of injected current. (c) The relationship between current amplitude and rebound latency is more complex. While lowering the amplitude of injected current increases the rebound latency for long current injections, the relationship is reversed for short current injections. This effect is due to IHCN (see Section 3 and Fig. 5)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3108018&req=5

Fig8: Rebound rates and latencies for different current injection amplitudes and durations in simulations of Neuron 1. (a) Rebound rate profiles for 0.5 and 0.0625 s duration current injections of varying amplitude. For the longest current injection, even this low density of GNaP leads to a prolonged rebound period from 12.1 Hz baseline to 23.2 Hz after −250 pA current injection (rate averaged over 500 ms). (b) For all durations of current injection, the rebound spike rate increases with the amplitude of injected current. (c) The relationship between current amplitude and rebound latency is more complex. While lowering the amplitude of injected current increases the rebound latency for long current injections, the relationship is reversed for short current injections. This effect is due to IHCN (see Section 3 and Fig. 5)
Mentions: The effect of stimulus amplitude was preserved for different stimulus durations, but stimulus duration had important additional effects. Because the de-inactivation time constant of ICaT was much shorter than that of INaP (101 vs 483 ms at −80 mV), a fast rebound could develop already after short hyperpolarizing stimuli of 62.5 ms, whereas it took stimuli of at least 125 ms duration to evoke a strong prolonged rebound (Figs. 7, 8).Fig. 7

Bottom Line: Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than -70 mV to allow de-inactivation of rebound currents.Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current.Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum.

View Article: PubMed Central - PubMed

Affiliation: Science and Technology Research Institute, University of Hertfordshire, Hatfield Herts, AL10 9AB, UK.

ABSTRACT
Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than -70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum.

Show MeSH
Related in: MedlinePlus