Computer models of corticospinal neurons replicate in vitro dynamics (Neymotin et al. 2017)

 Download zip file 
Help downloading and running models
Accession:195615
"Corticospinal neurons (SPI), thick-tufted pyramidal neurons in motor cortex layer 5B that project caudally via the medullary pyramids, display distinct class-specific electrophysiological properties in vitro: strong sag with hyperpolarization, lack of adaptation, and a nearly linear frequency-current (FI) relationship. We used our electrophysiological data to produce a pair of large archives of SPI neuron computer models in two model classes: 1. Detailed models with full reconstruction; 2. Simplified models with 6 compartments. We used a PRAXIS and an evolutionary multiobjective optimization (EMO) in sequence to determine ion channel conductances. ..."
Reference:
1 . Neymotin SA, Suter BA, Dura-Bernal S, Shepherd GM, Migliore M, Lytton WW (2017) Optimizing computer models of corticospinal neurons to replicate in vitro dynamics. J Neurophysiol 117:148-162 [PubMed]
Citations  Citation Browser
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: Neocortex;
Cell Type(s): Neocortex M1 L5B pyramidal pyramidal tract GLU cell; Neocortex primary motor area pyramidal layer 5 corticospinal cell;
Channel(s): I A; I h; I_KD; I K,Ca; I L high threshold; I Na,t; I N; Ca pump; Kir;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Parameter Fitting; Activity Patterns; Active Dendrites; Detailed Neuronal Models; Simplified Models;
Implementer(s): Suter, Benjamin ; Neymotin, Sam [samn at neurosim.downstate.edu]; Dura-Bernal, Salvador [salvadordura at gmail.com]; Forzano, Ernie ;
Search NeuronDB for information about:  Neocortex M1 L5B pyramidal pyramidal tract GLU cell; I Na,t; I L high threshold; I N; I A; I h; I K,Ca; I_KD; Ca pump; Kir;
/
spidemo
data
readme.html
cadad.mod
cal2.mod
can_mig.mod
h_kole.mod
kap_BS.mod
kBK.mod
kdmc_BS.mod
kdr_BS.mod
misc.mod *
nax_BS.mod
savedist.mod
vecst.mod *
archfig.py
axonMorph.py
BS0284.ASC
BS0409.ASC
conf.py
Fig6.py
figure_1.png
misc.h
morph.py
mosinit.py
PTcell.BS0284.cfg *
PTcell.BS0409.cfg
PTcell.cfg *
sim.py
SPI6.cfg
SPI6.py
utils.py
                            
: $Id: cadad.mod,v 1.4 2002/11/08 15:42:37 billl Exp $
TITLE Fast mechanism for submembranal Ca++ concentration (cai)
:
: Takes into account:
:
:	- increase of cai due to calcium currents
:	- extrusion of calcium with a simple first order equation
:
: This mechanism is compatible with the calcium pump "cad" and has the 
: same name and parameters; however the parameters specific to the pump
: are dummy here.
:
: Parameters:
:
:	- depth: depth of the shell just beneath the membran (in um)
:	- cainf: equilibrium concentration of calcium (2e-4 mM)
:	- taur: time constant of calcium extrusion (must be fast)
:	- kt,kd: dummy parameters
:
: Written by Alain Destexhe, Salk Institute, 1995
:

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

NEURON {
  SUFFIX cadad
  USEION ca READ ica, cai WRITE cai
  RANGE depth,kt,kd,cainf,taur
}

UNITS {
  (molar) = (1/liter)			: moles do not appear in units
  (mM)	= (millimolar)
  (um)	= (micron)
  (mA)	= (milliamp)
  (msM)	= (ms mM)
}

CONSTANT {
  FARADAY = 96489		(coul)		: moles do not appear in units
  :	FARADAY = 96.489	(k-coul)	: moles do not appear in units
}

PARAMETER {
  depth	= 1	(um)		: depth of shell
  taur	= 5	(ms)		: rate of calcium removal
  cainf	= 2.4e-4	(mM)
  kt	= 0	(mM/ms)		: dummy
  kd	= 0	(mM)		: dummy
}

STATE {
  cai		(mM) 
}

INITIAL {
  cai = cainf
}

ASSIGNED {
  ica		(mA/cm2)
  drive_channel	(mM/ms)
}
	
BREAKPOINT {
  SOLVE state METHOD cnexp
}

DERIVATIVE state { 
  drive_channel =  - (10000) * ica / (2 * FARADAY * depth)
  if (drive_channel <= 0.) { drive_channel = 0. }	: cannot pump inward
  cai' = drive_channel + (cainf-cai)/taur
}