Computational reconstruction of pacemaking and intrinsic electroresponsiveness in cerebellar golgi cells

Abstract

The Golgi cells have been recently shown to beat regularly in vitro (Forti et al., 2006. J. Physiol. 574, 711-729). Four main currents were shown to be involved, namely a persistent sodium current (I Na-p ), an h current (I h ), an SK-type calcium-dependent potassium current (I K-AHP ), and a slow M-like potassium current (I K-slow ). These ionic currents could take part, together with others, also to different aspects of neuronal excitability like responses to depolarizing and hyperpolarizing current injection. However, the ionic mechanisms and their interactions remained largely hypothetical. In this work, we have investigated the mechanisms of Golgi cell excitability by developing a computational model. The model predicts that pacemaking is sustained by subthreshold oscillations tightly coupled to spikes. I Na-p and I K-slow emerged as the critical determinants of oscillations. I h also played a role by setting the oscillatory mechanism into the appropriate membrane potential range. I K-AHP , though taking part to the oscillation, appeared primarily involved in regulating the ISI following spikes. The combination with other currents, in particular a resurgent sodium current (I Na-r ) and an A-current (I K-A ), allowed a precise regulation of response frequency and delay. These results provide a coherent reconstruction of the ionic mechanisms determining Golgi cell intrinsic electroresponsiveness and suggests important implications for cerebellar signal processing, which will be fully developed in a companion paper (Solinas et al., .

Parallelization of a Computational Model of a Biophysical Neuronal Circuitry of Rat Cerebellum

“…Model details are already reported in a previous study [13]. We used the biophysical neuron models of a detailed multi-compartmental granule cell [4] and cerebellar Golgi cell [16][17] to generate a large scale detailed network of granular layer that reconstructed center-surround excitation patterns. Our aim was to understand the best parallelization approach for large-scale biophysically detailed neuron circuit models.…”

Golgi Neurons

“…The Golgi cell firing frequency is linearly related to the intensity of their depolarizing drive and a detailed electrophysiological analysis of the Golgi cell active conductances in vitro, coupled to modeling, suggested that I h /I Na-p /I K-AHP / I K-slow can interact to generate slow pacemaking (Forti 2006;Solinas et al 2007a). The same approach revealed that the phase of the regular Golgi cell firing can be reset by spikes evoked by phasic inputs (Solinas et al 2007b; Kanichay and Silver 2008), as observed in vivo.…”

Understanding Cerebellum Granular Layer Network Computations through Mathematical Reconstructions of Evoked Local Field Potentials

“…The biophysical model consisting of cerebellar Golgi neuron consisted of a soma, 3 dendrites and an axon with ion channels mechanisms was used [11] . Synaptic information processing was modelled through AMPA, NMDA and GABA receptor mechanisms implemented as described in [12] .…”

“…Electrophysiological recordings have been translated to detailed biophysical models of neuronal cells [10,11] to develop biologically realistic mathematical models of microcircuit and to study the molecular and cellular mechanisms underlying cerebellar function [12] . Reconstructions also assist in elaborating animal models for the study of several neurological disorders [9] .…”