CA1 pyr cell: Inhibitory modulation of spatial selectivity+phase precession (Grienberger et al 2017)

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Accession:225080
Spatially uniform synaptic inhibition enhances spatial selectivity and temporal coding in CA1 place cells by suppressing broad out-of-field excitation.
Reference:
1 . Grienberger C, Milstein AD, Bittner KC, Romani S, Magee JC (2017) Inhibitory suppression of heterogeneously tuned excitation enhances spatial coding in CA1 place cells. Nat Neurosci [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Realistic Network;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s):
Gap Junctions:
Receptor(s): NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Active Dendrites; Detailed Neuronal Models; Place cell/field; Synaptic Integration; Short-term Synaptic Plasticity; Spatial Navigation; Feature selectivity;
Implementer(s): Milstein, Aaron D. [aaronmil at stanford.edu];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; NMDA;
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GrienbergerEtAl2017
morphologies
readme.txt
ampa_kin.mod *
exp2EPSC.mod
exp2EPSG.mod
exp2EPSG_NMDA.mod
gaba_a_kin.mod *
h.mod
kad.mod *
kap.mod *
kdr.mod *
km2.mod
nas.mod
nax.mod
nmda_kin2.mod
nmda_kin3.mod
nmda_kin5.mod *
pr.mod *
vecevent.mod *
batch_EPSP_attenuation.sh
batch_place_cell_r_inp.sh
batch_place_cell_record_i_syn.sh
batch_place_cell_single_compartment.sh
batch_place_cell_subtr_inh.sh
batch_place_cell_subtr_inh_shifted.sh
batch_place_cell_subtr_inh_vclamp.sh
batch_process_i_syn_files.sh
batch_rinp.sh
batch_spine_attenuation_ratio.sh
build_expected_EPSP_reference.sh
build_expected_EPSP_reference_controller.py
build_expected_EPSP_reference_engine.py
consolidate_i_syn_files.py
consolidate_tracked_spine_data.py
fit_parameter_exponential_distribution.py
function_lib.py
optimize_AMPA_KIN.py
optimize_dendritic_excitability_020416.py
optimize_GABA_A_KIN.py
optimize_NMDA_KIN2.py
parallel_branch_cooperativity.sh
parallel_branch_cooperativity_no_nmda.sh
parallel_clustered_branch_cooperativity_nmda_controller_110315.py
parallel_clustered_branch_cooperativity_nmda_engine_110315.py
parallel_EPSP_attenuation_controller.py
parallel_EPSP_attenuation_engine.py
parallel_EPSP_i_attenuation_controller.py
parallel_EPSP_i_attenuation_engine.py
parallel_expected_EPSP_controller.py
parallel_expected_EPSP_engine.py
parallel_optimize_branch_cooperativity.sh
parallel_optimize_branch_cooperativity_nmda_kin3_controller.py
parallel_optimize_branch_cooperativity_nmda_kin3_engine.py
parallel_optimize_EPSP_amp_controller.py
parallel_optimize_EPSP_amp_engine.py
parallel_optimize_pr.sh
parallel_optimize_pr_controller_020116.py
parallel_optimize_pr_engine_020116.py
parallel_rinp_controller.py
parallel_rinp_engine.py
parallel_spine_attenuation_ratio_controller.py
parallel_spine_attenuation_ratio_engine.py
plot_channel_distributions.py
plot_NMDAR_kinetics.py
plot_results.py
plot_spine_traces.py
plot_synaptic_conductance_facilitation.py
process_i_syn_files.py
record_bAP_attenuation.py
simulate_place_cell_no_precession.py
simulate_place_cell_single_compartment.py
simulate_place_cell_single_compartment_no_nmda.py
simulate_place_cell_subtr_inh.py
simulate_place_cell_subtr_inh_add_noise.py
simulate_place_cell_subtr_inh_add_noise_no_na.py
simulate_place_cell_subtr_inh_no_na.py
simulate_place_cell_subtr_inh_no_nmda_no_na.py
simulate_place_cell_subtr_inh_r_inp.py
simulate_place_cell_subtr_inh_rec_i_syn.py
simulate_place_cell_subtr_inh_shifted.py
simulate_place_cell_subtr_inh_silent.py
simulate_place_cell_subtr_inh_vclamp.py
specify_cells.py
                            
TITLE CA1 KM channel from Mala Shah
: M. Migliore June 2006
: option to have faster activation than inactivation kinetics based on Chen & Johnston, 2004.

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
}

PARAMETER {
	gkmbar 	= .0001 	(mho/cm2)
    vhalfl 	= -40   	(mV)
	kl 		= -7
    vhalft 	= -42   	(mV)
    a0t_f 	= 0.009     (/ms)
	a0t_s 	= 0.036
    zetat 	= 7    		(1)
    gmt 	= .4   		(1)
	q10 	= 5
	t0_f 	= 15
	t0_s 	= 60
	st 		= 1
}

NEURON {
	SUFFIX km2
	USEION k READ ek WRITE ik
    RANGE  gkmbar,ik,inf,tau
}

STATE {
    m
}

ASSIGNED {
    v 	    (mV)
	ek
	celsius (degC)
	ik      (mA/cm2)
    inf
	tau
    tau_f
	tau_s
}

INITIAL {
	rate(v)
	m=inf
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	ik = gkmbar*m^st*(v-ek)
}

FUNCTION alpt(v(mV)) {
    alpt = exp(0.0378*zetat*(v-vhalft))
}

FUNCTION bett(v(mV)) {
    bett = exp(0.0378*zetat*gmt*(v-vhalft))
}

DERIVATIVE state {
    rate(v)
	if (m<inf) {tau=tau_s} else {tau=tau_f}
    :if (m<inf) {tau=tau_f} else {tau=tau_s}
	:tau=tau_s
	m' = (inf - m)/tau
}

PROCEDURE rate(v (mV)) { :callable from hoc
    LOCAL a,qt
    qt=q10^((celsius-35)/10)
    inf = (1/(1 + exp((v-vhalfl)/kl)))
    a = alpt(v)
    tau_f = t0_f + bett(v)/(a0t_f*(1+a))
    tau_s = t0_s + bett(v)/(a0t_s*(1+a))
}