/* Author: Johannes Luthman
This is the simulation start file, with setting of run-specific variables.
Hoc files called from here:
- DCN_morph.hoc: creates the neuron morphology
- DCN_mechs.hoc: adds ion channels and other biophysics
- DCN_run.hoc: steps through the simulation
- DCN_recording.hoc: contains procedures (called from DCN_run.hoc) for recording
and saving data.
*/
strdef strFilePrefix, strTemp
// Set (optionally) prefix for the output file names. The following will be suffixed
// automatically: compartment recorded from, number of seconds simulated, ".dat".
strFilePrefix = ""
randomiserSeed = 1
runTime = 1000 // ms
/* Set synaptic input rates (Hz). The default of the model is to receive
40 Hz inhibitory and 20 Hz excitatory input.*/
inhibitoryHz = 40
excitatoryHz = 20
// Set whether to record membrane potential and current traces, and if so, during
// which intervals to record. (The somatic spike times are saved by default)
// For each interval, give the number of milliseconds into the simulation to start
// and stop the recording.
// A non-instantiated vector error occurs if nExtraVars = 0, so to not record any
// traces, set tTraceStop[0] = 0.
nStepsSaveTrace = 1
double tTraceStart[nStepsSaveTrace]
double tTraceStop[nStepsSaveTrace]
tTraceStart[0] = 200
tTraceStop[0] = 500
vInit = -70
dt = 0.025
secondorder = 1
// Set the recording interval.
recInterval = 0.100 // ms
// Set the number of excitatory and inhibitory (Purkinje cell) synapses.
EXCSOMASYNAPSES = 50
EXCDENDSYNAPSES = 100
EXCTOTALSYNAPSES = EXCSOMASYNAPSES + EXCDENDSYNAPSES
INHSOMASYNAPSES = 50
INHDENDSYNAPSES = 400
INHTOTALSYNAPSES = INHSOMASYNAPSES + INHDENDSYNAPSES
// Set convergence of Purkinje cells to the DCN.
PCtoDCNconvergence = 450
nDCNsynsPerPC = int(INHTOTALSYNAPSES / PCtoDCNconvergence)
// Set parameters of the synaptic inputs.
// If noise below is set to 0 (to get fully regular inputs), and the number of GABA inputs
// (PCtoDCNconvergence) is set to less than 450, then NEURON sometimes gives this error:
// "internal error: Source delay is > NetCon delay"
// The problem is corrected by setting noise to 1e-19 (1e-20 brings back the
// error).
noiseFractionExcSyn = 1 // max=1
noiseFractionInhSyn = 1 // min=1e-19 if PCtoDCNconvergence<450 (see explanation above), max=1
// Set the gamma distribution of the inputs.
// The default value of 3 for gammaOrderPC is based on the values of 2.8 (for patterns)
// and 3.4 (whole train) in Shin SL, Rotter S, Aertsen A, De Schutter E (2007)
// Stochastic description of complex and simple spike firing in cerebellar Purkinje cells.
// Eur J Neurosci 25:785-794.
gammaOrderExc = 3
gammaOrderPC = 3
// refractory periods of the inputs (ms)
refractoryPeriodExc = 1
refractoryPeriodPC = 2
// set useGABAsyndep to 1 (default) to use mech DCNsynGABA.mod, 0 to use DCNsyn.mod
// to instantiate the GABA synapses, with the former giving short-term
// depression as in Shin et al 2007 (PLOSone issue 5, e485)
useGABAsyndep = 1
// Define the length of the synaptic transmission delay (ms) in the PC-DCN synapse
// and its jitter (standard deviation).
gabaTransDelay = 2
gabaTransDelaySD = 0
// Set the temperature of the simulation. The model has been titrated to reproduce
// in vivo like firing at celsius = 37.0 (default), while the original GENESIS
// DCN model was constructed with temp = 32 deg celsius.
celsius = 37.0
TempOrigDCN = 32.0
// Temperature adjustments
// TempAnchisi = the temperature in the middle of the given range of room temperature
// recording in Anchisi D, Scelfo B, Tempia F (2001) Postsynaptic currents in deep
// cerebellar nuclei. J Neurophysiol 85:323-331.
TempAnchisi = 24.0
Q10channelGating = 3.0 // Middle of experimentally shown range (2-4) of ion channel gating,
// see Hille 3rd ed (2001), p.51.
Q10synapseGating = 2.0 // (Silver et al., 1996; Otis and Mody, 1992) Synaptic Q10s are given
// for GABA and excitatory synapses in Otis and Mody (1992), and Silver et al. (1996),
// respectively (full references below), with both giving Q10s in the region of 2.
Q10conductances = 1.4 // The middle of the range (1.2-1.5) given in Hille 3rd ed (2001)
// for ion channel conductances (p.51). Also, eg Milburn et al (1995)
// Receptors Channels 3:201-211: “The conductance increases steeply with temperature,
// with Q10 ranging from 1.4 to 1.5”. However, also note Cao XJ, Oertel D (2005)
// J Neurophysiol 94:821-832. They get the results that some conductances have a
// Q10 of 2 while other channel conductances don’t change at all by changing
// temp (Q10=1).
Q10CaConc = 2.0 // Guesswork: I assume that calcium concentration changes due to a
// combination of diffusion (Q10 of ca 1.4) and pumping action (Q10 of enzymatic
// reactions = ca 3)
QdTsynapseTausAnchisi = Q10synapseGating^((celsius - TempAnchisi) / 10.0)
QdTconductanceAnchisi = Q10conductances^((celsius - TempAnchisi) / 10.0)
QdTchannelGating = Q10channelGating^((celsius - TempOrigDCN) / 10.0)
QdTsynapseTaus = Q10synapseGating^((celsius - TempOrigDCN) / 10.0)
QdTconductances = Q10conductances^((celsius - TempOrigDCN) / 10.0)
QdTCaConc = Q10CaConc^((celsius - TempOrigDCN) / 10.0)
// Synaptic conductances
gGABA = 1600e-6*QdTconductances
tauRiseGABA = 0.25 / QdTsynapseTaus // From Dieter Jaeger's code cn6c_const_dj4.g
tauFallGABA = 5.1 / QdTsynapseTaus // Telgkamp P, Padgett DE, Ledoux VA, Woolley CS, Raman IM (2004)
// Maintenance of high-frequency transmission at purkinje to cerebellar nuclear
// synapses by spillover from boutons with multiple release sites. Neuron 41:113-126.
// For the following excitatory synaptic conductances, I'm using the high input gain
// level of Steuber, V., N. W. Schultheiss, et al. (2010). "Determinants of synaptic
// integration and heterogeneity in rebound firing explored with data-driven models of
// deep cerebellar nucleus cells." J Comput Neurosci.
// [= AMPA 200 pS, NMDA peak conductance (fast + slow) 172 pS (114+57)]
// The time constants are from Anchisi D, Scelfo B, Tempia F (2001) Postsynaptic currents
// in deep cerebellar nuclei. J Neurophysiol 85:323-331.
gAMPA = 200e-6*QdTconductanceAnchisi
tauRiseAMPA = 0.5 / QdTsynapseTausAnchisi
tauFallAMPA = 7.1 / QdTsynapseTausAnchisi
gfNMDA = 114e-6*QdTconductanceAnchisi
tauRisefNMDA = 5 / QdTsynapseTausAnchisi
tauFallfNMDA = 20.2 / QdTsynapseTausAnchisi
MgFactorfNMDA = 0.002
gammafNMDA = 0.109
gsNMDA = 57e-6*QdTconductanceAnchisi
tauRisesNMDA = 5 / QdTsynapseTausAnchisi
tauFallsNMDA = 136.4 / QdTsynapseTausAnchisi
MgFactorsNMDA = 0.25
gammasNMDA = 0.057
// Passive electrical parameters.
RA = 235.3 // ohm * cm
CM = 1.57 // microfarad / cm2
CMMYEL = CM/100
PASSCOND = 2.81e-5*QdTconductances // S/cm2 passive conductance
PASSCONDMYEL = PASSCOND / 2.81 // passive conductance of the axon
SHELLTHICK = 0.2 // micrometers, the thickness of the calcium-containing shell
// defined by CaConc.mod.
// Reversal potentials in mV
SodiumRevPot = 71
PotassiumRevPot = -90
GABARevPot = -75
ExcitSynRevPot = 0
hRevPot = -45
TNCrevPot = -35
// Non-synaptic channel conductances
gNaFsoma = 2.5e-2*QdTconductances
gNaFaxHill = 2*gNaFsoma
gNaFaxIniSeg = 2*gNaFsoma
gNaFpDend = 0.4*gNaFsoma
gNaPsoma = 8e-4*QdTconductances
gfKdrsoma = 1.5e-2*QdTconductances
gfKdraxHill = 2*gfKdrsoma
gfKdraxIniSeg = 2*gfKdrsoma
gfKdrpDend = 0.6*gfKdrsoma
gsKdrsoma = 1.25e-2*QdTconductances
gsKdraxHill = 2*gsKdrsoma
gsKdraxIniSeg = 2*gsKdrsoma
gsKdrpDend = 0.6*gsKdrsoma
gSKsoma = 2.2e-4*QdTconductances
gSKpDend = 0.3*gSKsoma
gSKdDend = 0.3*gSKsoma
permCaLVAsoma = 1.77e-5*QdTconductances
permCaLVAdend = 2*permCaLVAsoma
permCaHVAsoma = 7.5e-6*QdTconductances
permCaHVAdend = permCaHVAsoma / 1.5
tauCaConcSoma = 70/QdTCaConc
kCaCaConcSoma = 3.45e-7
kCaCaConcDend = 1.04e-6
gHsoma = 2e-4*QdTconductances
gHpDend = 2*gHsoma
gHdDend = 3*gHsoma
gTNCsoma = 3e-5*QdTconductances
gTNCaxHill = 3.5e-5*QdTconductances
gTNCaxIniSeg = 3.5e-5*QdTconductances
gTNCpDend = 0.2*gTNCsoma
load_file("DCN_morph.hoc")
load_file("DCN_mechs.hoc")
load_file("DCN_run.hoc")
//quit()
/* /////////////////////////////////////////////////////
/// REFERENCES ///
////////////////////////////////////////////////////////
@@@ Excitatory inputs @@@
(Gauck and Jaeger, 2003) say:
"The mean activation rate of excitatory inputs was set to 20 Hz
in accordance with in vivo recordings (Eccles et al., 1972; Cazin et al.,
1980; van Kan et al., 1993; Gamlin and Clarke, 1995; Matsuzaki and
Kyuhou, 1997). No difference between mossy and climbing fiber inputs
has been described in the DCN, and we simulate only one homogenous
group of excitatory inputs."
@@@ Inhibitory inputs (from Purkinje cells) @@@
(Savio and Tempia, 1985): spontaneous firing of single spikes = 36.15/s (± 17.04 SD)
in awake rats. (wistar 180-240 grams, a size I believe corresponds to almost adult size
(Stratton et al., 1988) gives a spontaneous simple spike firing rate of normal awake
rats of 35 ± 5.1 spikes/sec, (with SE), and “average complex spike rate, 1.3 spikes/sec”. The age was P20-28.
(LeDoux and Lorden, 2002) give a mean of ca 41 Hz SS frequency in 19.5±0.8 days old awake rats.
Max PC firing rate: 260 Hz in axonal recordings:
Monsivais P, Clark BA, Roth A, Hausser M (2005) Determinants of action potential propagation
in cerebellar Purkinje cell axons. J Neurosci 25:464-472.
@@@ Other references in the code @@@
Gauck V, Jaeger D (2003) The contribution of NMDA and AMPA conductances to the control
of spiking in neurons of the deep cerebellar nuclei. J Neurosci 23:8109-8118.
LeDoux MS, Lorden JF (2002) Abnormal spontaneous and harmaline-stimulated Purkinje cell
activity in the awake genetically dystonic rat. Exp Brain Res 145:457-467.
Savio T, Tempia F (1985) On the Purkinje cell activity increase induced by suppression
of inferior olive activity. Exp Brain Res 57:456-463.
Stratton SE, Lorden JF, Mays LE, Oltmans GA (1988) Spontaneous and harmaline-stimulated
Purkinje cell activity in rats with a genetic movement disorder. J Neurosci 8:3327-3336.
Otis TS, Mody I (1992) Modulation of decay kinetics and frequency of GABAA
receptor-mediated spontaneous inhibitory postsynaptic currents in hippocampal
neurons. Neuroscience 49:13-32.
Silver RA, Colquhoun D, Cull-Candy SG, Edmonds B (1996) Deactivation and
desensitization of non-NMDA receptors in patches and the time course of EPSCs
in rat cerebellar granule cells. J Physiol 493:167-173.
