A multilayer cortical model to study seizure propagation across microdomains (Basu et al. 2015)

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Accession:206238
A realistic neural network was used to simulate a region of neocortex to obtain extracellular LFPs from ‘virtual micro-electrodes’ and produce test data for comparison with multisite microelectrode recordings. A model was implemented in the GENESIS neurosimulator. A simulated region of cortex was represented by layers 2/3, 5/6 (interneurons and pyramidal cells) and layer 4 stelate cells, spaced at 25 µm in each horizontal direction. Pyramidal cells received AMPA and NMDA inputs from neighboring cells at the basal and apical dendrites. The LFP data was generated by simulating 16-site electrode array with the help of ‘efield’ objects arranged at the predetermined positions with respect to the surface of the simulated network. The LFP for the model is derived from a weighted average of the current sources summed over all cellular compartments. Cell models were taken from from Traub et al. (2005) J Neurophysiol 93(4):2194-232.
References:
1 . Basu I, Kudela P, Korzeniewska A, Franaszczuk PJ, Anderson WS (2015) A study of the dynamics of seizure propagation across micro domains in the vicinity of the seizure onset zone. J Neural Eng 12:046016 [PubMed]
2 . Basu I, Kudela P, Anderson WS (2014) Determination of seizure propagation across microdomains using spectral measures of causality. Conf Proc IEEE Eng Med Biol Soc 2014:6349-52 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; Neocortex U1 L5B pyramidal pyramidal tract GLU cell; Thalamus reticular nucleus GABA cell; Neocortex spiking low threshold (LTS) neuron; Neocortex spiking regular (RS) neuron; Neocortex layer 2-3 interneuron; Neocortex layer 5 interneuron;
Channel(s): I Na,p; I Na,t; I K; I A; I M; I h; I K,Ca; I A, slow; I L high threshold; I T low threshold; I Calcium;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; GabaA; NMDA;
Gene(s):
Transmitter(s): Glutamate; Gaba; Amino Acids;
Simulation Environment: GENESIS;
Model Concept(s): Activity Patterns; Epilepsy;
Implementer(s): Anderson, WS ; Kudela, Pawel ;
Search NeuronDB for information about:  Thalamus reticular nucleus GABA cell; Neocortex U1 L5B pyramidal pyramidal tract GLU cell; Neocortex U1 L2/6 pyramidal intratelencephalic GLU cell; GabaA; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I h; I K,Ca; I Calcium; I A, slow; Amino Acids; Gaba; Glutamate;
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BasuEtAl2015
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ModelDescription.pdf
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P6RSd_P6RSc.g
P6RSd_P6RSd.g
P6RSd_P6RSd_Gap.g
P6RSd_raninput.g
P6RSd_ST4RS.g
P6RSd_synapsedefs.g
P6RSd_TCR.g
P6RSdcell3Dpk.p
P6RSdchanpk.g
P6RSdprotodefs.g
P6RSsyncond.g
pgenesis_command
protodefs.g
protospikeB23FS.g
protospikeB5FS.g
protospikeC23FS.g
protospikeC5FS.g
protospikeI23LTS.g
protospikeI5LTS.g
protospikenRT.g
protospikeP23FRBa.g
protospikeP23RSa.g
protospikeP23RSb.g
protospikeP23RSc.g
protospikeP23RSd.g
protospikeP5IBa.g
protospikeP5IBb.g
protospikeP5IBc.g
protospikeP5IBd.g
protospikeP5RSa.g
protospikeP6RSa.g
protospikeP6RSb.g
protospikeP6RSc.g
protospikeP6RSd.g
protospikeST4RS.g
protospikeTCR.g
randominputdefs.g
spikedefs.g
ST4RS.g
ST4RS_B23FS.g
ST4RS_B5FS.g
ST4RS_C23FS.g
ST4RS_C5FS.g
ST4RS_I23LTS.g
ST4RS_I5LTS.g
ST4RS_P23FRBa.g
ST4RS_P23RSa.g
ST4RS_P23RSb.g
ST4RS_P23RSc.g
ST4RS_P23RSd.g
ST4RS_P5IBa.g
ST4RS_P5IBb.g
ST4RS_P5IBc.g
ST4RS_P5IBd.g
ST4RS_P5RSa.g
ST4RS_P6RSa.g
ST4RS_P6RSb.g
ST4RS_P6RSc.g
ST4RS_P6RSd.g
ST4RS_raninput.g
ST4RS_ST4RS.g
ST4RS_ST4RS_Gap.g
ST4RS_synapsedefs.g
ST4RScell3Dpk.p
ST4RSchanpk.g
ST4RSprotodefs.g
ST4RSsyncond.g
synapticdelays.g *
synapticprobsTraub.g
synchansB23FS.g *
synchansB5FS.g *
synchansC23FS.g *
synchansC5FS.g *
synchansI23LTS.g *
synchansI5LTS.g *
synchansnRT.g *
synchansP23FRBa.g *
synchansP23RSa.g *
synchansP23RSb.g *
synchansP23RSc.g *
synchansP23RSd.g *
synchansP5IBa.g *
synchansP5IBb.g *
synchansP5IBc.g *
synchansP5IBd.g *
synchansP5RSa.g *
synchansP6RSa.g *
synchansP6RSb.g *
synchansP6RSc.g *
synchansP6RSd.g *
synchansSPIKEs.g *
synchansSPIKEs_base.g
synchansST4RS.g
synchansTCR.g *
syncond.g
syncond2.g
TCR.g
TCR_B23FS.g
TCR_B5FS.g
TCR_C23FS.g
TCR_C5FS.g
TCR_nRT.g
TCR_P23FRBa.g
TCR_P23RSa.g
TCR_P23RSb.g
TCR_P23RSc.g
TCR_P23RSd.g
TCR_P5IBa.g
TCR_P5IBb.g
TCR_P5IBc.g
TCR_P5IBd.g
TCR_P5RSa.g
TCR_P6RSa.g
TCR_P6RSb.g
TCR_P6RSc.g
TCR_P6RSd.g
TCR_raninput.g
TCR_ST4RS.g
TCR_synapsedefs.g
TCRcellpk.p
TCRchanpk.g
TCRprotodefs.g
TCRsyncond.g
                            
//genesis

float	PI		=	3.14159

// =====================================================================
//                        PHYSIOLOGICAL PARAMETERS
// =====================================================================
// All units in SI  and usually dimensions are given as well 

//                      IONIC EQUILIBRIUM POTENTIALS
float	ENA 		=	 55.0e-3			// V
float	ECL 		=	-65.0e-3			// V
float	EK 		=	-90.0e-3			// V
float	EREST 		=	-70.0e-3			// V
float	I_EREST		=	-70.0e-3			// V

//			ACTIVE COMPARTMENT POTENTIALS
float	EREST_ACT	=	-70.0e-3			// V
float 	ENA_ACT		=	115.0e-3 + EREST_ACT		// V
float	EK_ACT		=	-12.0e-3 + EREST_ACT		// V
float	ELEAK_ACT	=	 10.6e-3 + EREST_ACT		// V


// squid giant axon - Conti et al.(1975),J.Physiol(Lond),248,45-82
// gNa = 4pS
// squid giant axon - Conti and Neher(1980),Nature(Lond),285,140-143
// gK = 18pS
// mouse spinal neurone - Mathers and Barker(1982),Int.Rev.Neurobiol,23,1-34
// gCl = 18pS
//                           UNIT CONDUCTANCES
// 			     (Siemens/channel)
float	UNIT_GNA	=	12.0e-12	// S
float	UNIT_GCL	=	18.0e-12	// S
float	UNIT_GK		=	 4.0e-12	// S
float	SUNIT_GNA	=	 8.0e-12	// S
float	SUNIT_GK	=	 4.0e-12	// S

// squid giant axon - Conti et al.(1975),J.Physiol(Lond),248,45-82
// rhoNa = 330 channels/um^2
// squid giant axon - Conti and Neher(1980),Nature(Lond),285,140-143
// rhoK = 72 channels/um^2
//                           CHANNEL DENSITIES
// 				(channels/m^2)
float	RHO_NA		=	 60.0e12	
float	RHO_CL		=	 30.0e12
float	RHO_K		=	 30.0e12
float	SRHO_NA		=	330.0e12
float	SRHO_K		=	 72.0e12
float	IRHO_NA		=	 10.0e12

//                           SYNAPTIC AREA
// Haberly and Presto(1986),J.Comp.Neurol,248,464-474
// basal spine d = .40um
// distal spine d = .74um
// presynaptic to dendritic spines d = .61
// presynaptic to dendritic shafts d = .89
// presynaptic to initial segment d = .89
//
// using synaptic contact area A = pi*d^2/4 
// 				(m^2/synapse)
float	ASYN_LOCAL_NA	=	0.12e-12
float	ASYN_DISTAL_NA	=	0.43e-12
float	ASYN_CL		=	0.62e-12
float	ASYN_K		=	0.43e-12

float	IASYN_NA	=	0.29e-12

//                      ACTIVE AREA
// fraction of somatic area containing active channels
float	fAC		=	0.1


//                      PEAK CONDUCTANCE
//			(Siemens/synapse)
float	I_GMAX_NA	=	UNIT_GNA * IRHO_NA * IASYN_NA
float	LOCAL_GMAX_NA	=	UNIT_GNA * RHO_NA  * ASYN_LOCAL_NA
float	DISTAL_GMAX_NA	=	UNIT_GNA * RHO_NA  * ASYN_DISTAL_NA
float	GMAX_K		=	UNIT_GK  * RHO_K   * ASYN_K
float	GMAX_CL		=	UNIT_GCL * RHO_CL  * ASYN_CL

float	SGMAX_NA	=	SUNIT_GNA * SRHO_NA		// S/m^2
float	SGMAX_K		=	SUNIT_GK  * SRHO_K		// S/m^2

//                      MEMBRANE PARAMETERS
float	RM		=	0.2		// ohm-m^2
float	RA		=	0.5		// ohm-m
float	CM		=	0.01		// F/m^2

//			TYPICAL CELL DIMENSIONS

float	SOMA_D	=	20.0e-6				// m
float	SOMA_L	=	20.0e-6				// m
float	SOMA_A	=	PI * SOMA_D * SOMA_L		// m^2
float	SOMA_XA	=	PI * SOMA_D * SOMA_D / 4	// m^2
float	DEND_D	=	1.5e-6				// m
float	DEND_L	=	100.0e-6			// m
float	DEND_A	=	PI * DEND_D * DEND_L		// m^2
float	DEND_XA	=	PI * DEND_D * DEND_D / 4	// m^2

/*
** VARIABLES USED BY ACTIVE COMPONENTS
*/
int	EXPONENTIAL	=	1
int	SIGMOID		=	2
int	LINOID		=	3


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