Purkinje cell: Synaptic activation predicts voltage control of burst-pause (Masoli & D'Angelo 2017)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:239421
"The dendritic processing in cerebellar Purkinje cells (PCs), which integrate synaptic inputs coming from hundreds of thousands granule cells and molecular layer interneurons, is still unclear. Here we have tested a leading hypothesis maintaining that the significant PC output code is represented by burst-pause responses (BPRs), by simulating PC responses in a biophysically detailed model that allowed to systematically explore a broad range of input patterns. BPRs were generated by input bursts and were more prominent in Zebrin positive than Zebrin negative (Z+ and Z-) PCs. Different combinations of parallel fiber and molecular layer interneuron synapses explained type I, II and III responses observed in vivo. BPRs were generated intrinsically by Ca-dependent K channel activation in the somato-dendritic compartment and the pause was reinforced by molecular layer interneuron inhibition. BPRs faithfully reported the duration and intensity of synaptic inputs, such that synaptic conductance tuned the number of spikes and release probability tuned their regularity in the millisecond range. ..."
Reference:
1 . Masoli S, D'Angelo E (2017) Synaptic Activation of a Detailed Purkinje Cell Model Predicts Voltage-Dependent Control of Burst-Pause Responses in Active Dendrites. Front Cell Neurosci 11:278 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Synapse;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum Purkinje GABA cell;
Channel(s): I Potassium; I K,Ca;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Detailed Neuronal Models; Bursting;
Implementer(s): Masoli, Stefano [stefano.masoli at unipv.it];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; I K,Ca; I Potassium;
/
Purkinjecell_2017
mod_files
Cav2_1.mod *
Cav3_1.mod *
Cav3_2.mod *
Cav3_3.mod *
cdp5.mod *
HCN1_Angeloetal2007.mod *
Kca11.mod *
Kca22.mod *
Kca31.mod *
Kir23.mod *
Kv11.mod *
Kv15.mod *
Kv33.mod *
Kv34.mod *
Kv43.mod *
Leak.mod *
Nav16.mod *
PC_Gaba_det_vi_alfa1.mod
PURKINJE_Ampa_det_vi.mod
UBC_TRP.mod
                            
TITLE Calcium dependent potassium channel
: Implemented in Rubin and Cleland (2006) J Neurophysiology
: Parameters from Bhalla and Bower (1993) J Neurophysiology
: Adapted from /usr/local/neuron/demo/release/nachan.mod - squid
:   by Andrew Davison, The Babraham Institute  [Brain Res Bulletin, 2000]

:Suffix from Kca3 to Kca3_1

NEURON {
    THREADSAFE
	SUFFIX Kca3_1
	USEION k READ ek WRITE ik
	USEION ca READ cai
	RANGE gkbar, ik, Yconcdep, Yvdep
	RANGE Yalpha, Ybeta, tauY, Y_inf
}

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(molar) = (1/liter)
	(mM) = (millimolar)
}

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

CONSTANT {
	q10 = 3
}

PARAMETER {
	v (mV)
	dt (ms)
	gkbar= 0.120 (mho/cm2) <0,1e9>
	Ybeta = 0.05 (/ms)
	cai (mM) := 1e-5 (mM)
}


STATE {
	Y
}

ASSIGNED {
	ik (mA/cm2)
	Yalpha   (/ms)
	Yvdep    
	Yconcdep (/ms)
	tauY (ms)
	Y_inf
	ek (mV)

	qt
}

INITIAL {
	rate(v,cai)
	Y = Yalpha/(Yalpha + Ybeta)
	qt = q10^((celsius-37 (degC))/10 (degC))
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	ik = gkbar*Y*(v - ek)
}

DERIVATIVE state {
	rate(v,cai)
	Y' = Yalpha*(1-Y) - Ybeta*Y
}

PROCEDURE rate(v(mV),cai(mM)) {
	vdep(v)
	concdep(cai)
	Yalpha = Yvdep*Yconcdep
	tauY = 1/(Yalpha + Ybeta)
	Y_inf = Yalpha/(Yalpha + Ybeta) /qt
}

PROCEDURE vdep(v(mV)) {
	TABLE Yvdep FROM -100 TO 100 WITH 100
	Yvdep = exp((v*1(/mV)+70)/27)
}

PROCEDURE concdep(cai(mM)) {
	TABLE Yconcdep FROM 0 TO 0.01 WITH 1000
	if (cai < 0.01) {
		Yconcdep = 500(/ms)*( 0.015-cai*1(/mM) )/( exp((0.015-cai*1(/mM))/0.0013) -1 )
	} else {
		Yconcdep = 500(/ms)*0.005/( exp(0.005/0.0013) -1 )
	}
}