Computational model of cerebellar tDCS (Zhang et al., 2021)

 Download zip file 
Help downloading and running models
Accession:267189
This archive contains models used in (Zhang et al. 2021) and simulates Purkinje cell, granule cell, and deep cerebellar neuron activities under cerebellar tDCS (transcranial direct current stimulation).
Reference:
1 . Zhang X, Hancock R, Santaniello S (2021) Transcranial Direct Current Stimulation of Cerebellum Alters Spiking Precision in Cerebellar Cortex: A Modeling Study of Cellular Responses. PLoS Comp Biol 17(12):e1009609 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum Purkinje GABA cell; Cerebellum interneuron granule GLU cell; Cerebellum deep nucleus neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s):
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; Cerebellum interneuron granule GLU cell;
// Simulate Purkinje cell (Masoli et al.,2015) activity under mossy fiber inputs
// Establish the state for the first 20 seconds
// (c) Xu (Shawn) Zhang, UConn
// xu.3.zhang@uconn.edu

load_file("nrngui.hoc")
load_file("Purkinje.hoc")

cvode.active(0)

dt = 0.025
celsius = 37
tstop = 20000
v_init = -58

numsyn_exc = 1000
numsyn_inh = 100
numsyn_all = numsyn_exc+numsyn_inh

objref f_tDCSparams
f_tDCSparams = new File()
ampparam = 0
synparam = 0

// Poisson process inputs to PYNs
objref rngdendns
rngdendns = new Random(111)
rngdendns.normal(1,0.16)
objref rngdendnsseed
rngdendnsseed = new Random(222)
rngdendnsseed.uniform(100,999)
objref rngdendnsstart
rngdendnsstart = new Random(333)
rngdendnsstart.normal(250,100)

// Excitatory synapses
objref f_dendname
strdef tmpdendname
f_dendname = new File()
f_dendname.ropen("dend_train/dendnames_delayedonset.txt")
strdef straccessdend, strtmpsyn, strtmpns, strtmpnsnc
objref dend_syn_exc[numsyn_exc], dendns[numsyn_exc], dendnsnc[numsyn_exc]

objref rec_event_dend[numsyn_all]
tmpseed = rngdendnsseed.repick()
	
for i = 0,numsyn_exc-1 {
	f_dendname.scanstr(tmpdendname)
	
	sprint(strtmpns,"%s%s",tmpdendname," dendns[i] = new NetStim(0.25)")
	execute(strtmpns)
	
	sprint(strtmpsyn,"%s%s",tmpdendname," dend_syn_exc[i] = new NoisyExp2Syn(0.5)")
	execute(strtmpsyn)
	
	dendns[i].number=1e4
	dendns[i].interval=100
	dendns[i].start=200
	dendns[i].noise=1
	tmpseed = rngdendnsseed.repick()
	
	dendns[i].seed(tmpseed)
	
	dend_syn_exc[i].tau1 = 0.6 // (ms)
	dend_syn_exc[i].tau2 = 1 // (ms)
	dend_syn_exc[i].e = 0
	
	sprint(straccessdend,"%s%s","access ",tmpdendname)
	execute(straccessdend)
	
	sprint(strtmpnsnc,"%s%s",tmpdendname," dendnsnc[i] = new NetCon(dendns[i], dend_syn_exc[i], 0, 0, 0*synparam)")
	execute(strtmpnsnc)
	
	rec_event_dend[i] = new Vector()
	dendnsnc[i].record(rec_event_dend[i])
}
f_dendname.close()

// Inhibitory synapses
objref f_dendname_inh
strdef tmpdendname_inh
f_dendname_inh = new File()
f_dendname_inh.ropen("dend_train/dendnames_inh_delayedonset.txt")
strdef straccessdend_inh, strtmpsyn_inh, strtmpns_inh, strtmpnsnc_inh
objref dend_syn_inh[numsyn_inh], dendns_inh[numsyn_inh], dendnsnc_inh[numsyn_inh]

for i = 0,numsyn_inh-1 {
	f_dendname_inh.scanstr(tmpdendname_inh)
	
	sprint(strtmpsyn_inh,"%s%s",tmpdendname_inh," dend_syn_inh[i] = new NoisyExp2Syn(0.5)")
	execute(strtmpsyn_inh)
	
	sprint(strtmpns_inh,"%s%s",tmpdendname_inh," dendns_inh[i] = new NetStim(0.75)")
	execute(strtmpns_inh)
	
	soma dendns_inh[i] = new NetStim(0.75)
	dendns_inh[i].number=1e4
	dendns_inh[i].interval=35.7
	dendns_inh[i].start=200
	dendns_inh[i].noise=1
	dendns_inh[i].seed(rngdendnsseed.repick())
	
	dend_syn_inh[i].tau1 = 1 // (ms)
	dend_syn_inh[i].tau2 = 5 // (ms)
	dend_syn_inh[i].e = -80 // (mV)
	
	
	sprint(straccessdend_inh,"%s%s","access ",tmpdendname_inh)
	execute(straccessdend_inh)
	
	sprint(strtmpnsnc_inh,"%s%s",tmpdendname_inh," dendnsnc_inh[i] = new NetCon(dendns_inh[i], dend_syn_inh[i], 0, 0, 0)")
	execute(strtmpnsnc_inh)
	
	rec_event_dend[i+numsyn_exc] = new Vector()
	dendnsnc_inh[i].record(rec_event_dend[i+numsyn_exc])
}
f_dendname_inh.close()

forall {
  insert extracellular
  insert xtrau
}

load_file("interpxyzu.hoc")	// only interpolates sections that have xtrau
load_file("calcrxcu.hoc")	// computes transfer r between segments and recording electrodes
load_file("calcd.hoc")	// computes scale factor used to calculate extracellular potential
			            //   produced by a uniform electrical field
load_file("setpointersu.hoc")	// automatically calls grindaway() in interpxyzu.hoc
load_file("zapstimu_DC.hoc")		// extracellular stimulus

setstim(0, 1e6, 0) // Positive: hyperpolarizing soma
changefield(0, 90, 100)

access soma

// Record soma
objref rec_v_soma
rec_v_soma = new Vector()
rec_v_soma.record(&soma.v(0.5))

run()

objref ss,f_ss
ss = new SaveState()
f_ss = new File()
ss.save()
f_ss.wopen("currentState.dat")
ss.fwrite(f_ss)
f_ss.close()

quit()

Loading data, please wait...