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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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Somatic and dendritic voltages during an action potential in the model and currents underlying the spontaneous spike cycle. (a) Somatic voltage (red) shows the waveform of a narrow spike and a subsequent notch followed by a brief depolarizing transient characteristic for DCN neurons (see Section 2). As the spike propagates passively into the dendrite, the spike waveform becomes attenuated, delayed, and broadens. The somatic potential is truncated at −30 mV in order to enhance the y-axis resolution. (b) Somatic currents underlying the spontaneous spike cycle. The notch and depolarizing transient of each spike result from an interaction of delayed rectifier current (blue: fast and slow Kdr combined), HVA calcium current (red), and resurgent axial current flowing back from the dendrites into the soma (orange)
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Fig2: Somatic and dendritic voltages during an action potential in the model and currents underlying the spontaneous spike cycle. (a) Somatic voltage (red) shows the waveform of a narrow spike and a subsequent notch followed by a brief depolarizing transient characteristic for DCN neurons (see Section 2). As the spike propagates passively into the dendrite, the spike waveform becomes attenuated, delayed, and broadens. The somatic potential is truncated at −30 mV in order to enhance the y-axis resolution. (b) Somatic currents underlying the spontaneous spike cycle. The notch and depolarizing transient of each spike result from an interaction of delayed rectifier current (blue: fast and slow Kdr combined), HVA calcium current (red), and resurgent axial current flowing back from the dendrites into the soma (orange)

Mentions: Active properties underlying baseline spiking behavior A plot of the currents underlying the voltage trajectory in the model (Fig. 2) clarifies how the different spike properties of the recorded neurons are matched. As the model lacks NaF and Kdr spike currents in most of its dendrite, action potentials attenuated and broadened as they propagated passively into the dendrite (Fig. 2(a)). The delayed depolarization of the dendrite with respect to the soma resulted in a push–pull mechanism of axial current similar to Purkinje cells (Jaeger and Bower 1999), by which the soma first pushes current into the dendrite during the action potential, but then a substantial current flows back during the AHP and creates the ADP following the fast AHP (Fig. 2(a, b)). These observations in the model lead to the prediction that a dissociated DCN neuron with predominantly a soma remaining would not exhibit the ADP following the AHP.Fig. 2


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)

Somatic and dendritic voltages during an action potential in the model and currents underlying the spontaneous spike cycle. (a) Somatic voltage (red) shows the waveform of a narrow spike and a subsequent notch followed by a brief depolarizing transient characteristic for DCN neurons (see Section 2). As the spike propagates passively into the dendrite, the spike waveform becomes attenuated, delayed, and broadens. The somatic potential is truncated at −30 mV in order to enhance the y-axis resolution. (b) Somatic currents underlying the spontaneous spike cycle. The notch and depolarizing transient of each spike result from an interaction of delayed rectifier current (blue: fast and slow Kdr combined), HVA calcium current (red), and resurgent axial current flowing back from the dendrites into the soma (orange)
© Copyright Policy
Related In: Results  -  Collection

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

Fig2: Somatic and dendritic voltages during an action potential in the model and currents underlying the spontaneous spike cycle. (a) Somatic voltage (red) shows the waveform of a narrow spike and a subsequent notch followed by a brief depolarizing transient characteristic for DCN neurons (see Section 2). As the spike propagates passively into the dendrite, the spike waveform becomes attenuated, delayed, and broadens. The somatic potential is truncated at −30 mV in order to enhance the y-axis resolution. (b) Somatic currents underlying the spontaneous spike cycle. The notch and depolarizing transient of each spike result from an interaction of delayed rectifier current (blue: fast and slow Kdr combined), HVA calcium current (red), and resurgent axial current flowing back from the dendrites into the soma (orange)
Mentions: Active properties underlying baseline spiking behavior A plot of the currents underlying the voltage trajectory in the model (Fig. 2) clarifies how the different spike properties of the recorded neurons are matched. As the model lacks NaF and Kdr spike currents in most of its dendrite, action potentials attenuated and broadened as they propagated passively into the dendrite (Fig. 2(a)). The delayed depolarization of the dendrite with respect to the soma resulted in a push–pull mechanism of axial current similar to Purkinje cells (Jaeger and Bower 1999), by which the soma first pushes current into the dendrite during the action potential, but then a substantial current flows back during the AHP and creates the ADP following the fast AHP (Fig. 2(a, b)). These observations in the model lead to the prediction that a dissociated DCN neuron with predominantly a soma remaining would not exhibit the ADP following the AHP.Fig. 2

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