Auditory cortex layer IV network model (Beeman 2013)

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Accession:150678
"... The primary objective of this modeling study was to determine the effects of axonal conduction velocity (often neglected, but significant), as well as synaptic time constants, on the ability of such a network to create and propagate cortical waves. ... The model is also being used to study the interaction between single and two-tone input and normal background activity, and the effects of synaptic depression from thalamic inputs. The simulation scripts have the additional purpose of serving as tutorial examples for the construction of cortical networks with GENESIS. The present model has fostered the development of the G-3 Python network analysis and visualization tools used in this study... It is my hope that this short tutorial and the example simulation scripts can provide a head start for a graduate student or postdoc who is beginning a cortical modeling project. "
Reference:
1 . Beeman D (2013) A modeling study of cortical waves in primary auditory cortex BMC Neuroscience 14(Supl 1):P23
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Auditory cortex;
Cell Type(s): Neocortex V1 pyramidal corticothalamic cell; Neocortex V1 basket intratelencephalic cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: GENESIS;
Model Concept(s): Activity Patterns; Tutorial/Teaching;
Implementer(s): Beeman, Dave;
Search NeuronDB for information about:  Neocortex V1 pyramidal corticothalamic cell; Neocortex V1 basket intratelencephalic cell;
  
// protodefs.g - Definition of prototype elements for Auditory Cortex Cells

/* Included files are in genesis/Scripts/neurokit/prototypes */

float EREST_ACT = -0.07       // resting membrane potential (volts)
float ENA   = 0.045           // sodium equilibrium potential
float EK    = -0.082          // potassium equilibrium potential

/* file for standard compartments */
include compartments

// include the definitions for the functions to create channels
include  pyrchans.g

// Make a "library element" to hold the prototypes, which will be used
// by the cell reader to add compartments and channels to the cell.

if (!{exists /library})     // But, only if it doesn't already exist
    create neutral /library
end

// We don't want the library to try to calculate anything, so we disable it
disable /library

// To ensure that all subsequent elements are made in the library
pushe /library

/* Make a prototype compartment.  The internal fields will be set by
   the cell reader, so they do not need to be set here.  The
   make_cylind_compartment function is defined in compartments.g.
*/

make_cylind_compartment

/* makes "symcompartment", if needed */
// make_cylind_symcompartment

/* Make the pyramidal cell channels.  

   Note that pyrchans.g changes some global variables.  Different
   values could be added here.
*/

/* the values in pyrchans.g are
float EREST_ACT = -0.060 // hippocampal cell resting potl
float ENA = 0.115 + EREST_ACT // 0.055
float EK = -0.015 + EREST_ACT // -0.075
float ECA = 0.140 + EREST_ACT // 0.080
*/

make_Na_hip_traub91 Na_pyr
make_Kdr_hip_traub91 Kdr_pyr
// slow down the firng by doubling Kdr_pyr
scaletabchan Kdr_pyr X tau 1.0 2.0 0.0 0.0

make_Ca_hip_traub91  // This needs to keep the name Ca_hip_traub91
make_Kahp_hip_traub91 Kahp_pyr
/* The original traub91 Kahp tau had a max of 1 sec at [Ca]=0, dropping
   to 0.2 when [Ca]=200, and 0.1 at higher values.  This scaling makes the
   typical range 10-50 msec, which is roughly the time for adaptation in
   neocortical pyramidal cells.
*/
scaletabchan Kahp_pyr Z tau 1.0 0.05 0.0 0.0

make_Ca_hip_conc Ca_conc
/* The original Ca_conc tau was 0.0133 sec.  A value of 0.05 sec gives
    [Ca] more time to decay.
*/
setfield Ca_conc tau 0.1

/* Make the synaptically activated channels */
make_AMPA_pyr AMPA_pyr /* synchan with Ek = 0.0, tau1 = tau2 = 3 msec */
make_GABA_pyr GABA_pyr /* synchan with Ek = -0.080, tau1 = 3, tau2 = 8 msec */

/* make a spike generator */
create spikegen spike
setfield spike  thresh 0.00  abs_refract 1.0e-3  output_amp 1

/* Make the Fast Spiking basket cell channels.  */
include FSchans.g

/*   Note that FSchans.g changes some global variables.  Different
     values could be added here, before creating the channels.
*/

/* the values in baskchans.g are
float   EREST_ACT = -0.063  // value for vtraub in Destexhe et al. (2001)
float   ENA       =  0.050
float   EK        = -0.090
*/

make_Na_traub_mod Na_bask
make_K_traub_mod  Kdr_bask
// speed them up by scaling the activation time constants by 0.5
scaletabchan Na_bask X tau 1.0 0.5  0.0 0.0
scaletabchan Na_bask Y tau 1.0 0.5  0.0 0.0
scaletabchan Kdr_bask X tau 1.0 0.5 0.0 0.0

/* Make the synaptically activated channels */
// Presently, AMPA_bask and GABA_bask are the same as AMPA_pyr and GABA_pyr

make_AMPA_bask AMPA_bask // synchan with Ek = 0.0, tau1 = tau2 = 3 msec */
copy AMPA_bask AMPA_bask_drive // make a similar channel for Ex drive input
make_GABA_bask GABA_bask // synchan with Ek = -0.080, tau1 = 3, tau2 = 8 msec

pope // Return to the original place in the element tree

Beeman D (2013) A modeling study of cortical waves in primary auditory cortex BMC Neuroscience 14(Supl 1):P23

References and models cited by this paper

References and models that cite this paper

Cornelis H, Coop AD, Bower JM (2012) A federated design for a neurobiological simulation engine: the CBI federated software architecture. PLoS One 7:e28956 [PubMed]

Rodriguez AL, Cornelis H, Beeman D, Bower JM (2012) Multiscale modeling with GENESIS 3, using the G-shell and Python BMC Neuroscience 13(Supl 1):P176

(2 refs)