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 20:417-426 [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; 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;
/
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
                            
__author__ = 'milsteina'
from function_lib import *
import sys

if len(sys.argv) > 1:
    syn_type = str(sys.argv[1])
if len(sys.argv) > 2:
    seed = int(sys.argv[2])
if len(sys.argv) > 3:
    condition = int(sys.argv[3])

file_list, rec_filenames = {}, {}
for this_syn_type in ['i_AMPA', 'i_NMDA', 'i_GABA']:
    for parameter in file_list, rec_filenames:
        parameter[this_syn_type] = {}
        for this_seed in range(5):
            parameter[this_syn_type][this_seed] = {}

file_list['i_AMPA'][0]['modinh0'] = ['output060820161304-pid47126-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_0',
 'output060820161303-pid47756-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_1',
 'output060920161653-pid100108-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_2',
 'output060920161653-pid15101-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_3',
 'output060820161303-pid47758-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_4',
 'output061020161207-pid20403-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_5',
 'output060820161303-pid26172-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_6',
 'output060820161303-pid26171-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_7',
 'output060820161303-pid26175-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_8',
 'output060920161654-pid58898-seed0-e3200-i600-subtr_mod_inh0-i_AMPA_9']
file_list['i_AMPA'][0]['modinh3'] = ['output061020161207-pid839-seed0-e3200-i600-subtr_mod_inh3-i_AMPA_20',
 'output060820161303-pid19190-seed0-e3200-i600-subtr_mod_inh3-i_AMPA_21',
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file_list['i_AMPA'][1]['modinh0'] = ['output060820161304-pid39439-seed1-e3200-i600-subtr_mod_inh0-i_AMPA_30',
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file_list['i_AMPA'][1]['modinh3'] = ['output060820161303-pid32514-seed1-e3200-i600-subtr_mod_inh3-i_AMPA_50',
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file_list['i_AMPA'][2]['modinh0'] = ['output060920161708-pid125840-seed2-e3200-i600-subtr_mod_inh0-i_AMPA_60',
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file_list['i_AMPA'][2]['modinh3'] = ['output060820161303-pid17744-seed2-e3200-i600-subtr_mod_inh3-i_AMPA_80',
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file_list['i_AMPA'][3]['modinh0'] = ['output060820161304-pid29822-seed3-e3200-i600-subtr_mod_inh0-i_AMPA_90',
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file_list['i_AMPA'][3]['modinh3'] = ['output060920161651-pid4611-seed3-e3200-i600-subtr_mod_inh3-i_AMPA_110',
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file_list['i_AMPA'][4]['modinh0'] = ['output060820161304-pid20342-seed4-e3200-i600-subtr_mod_inh0-i_AMPA_120',
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file_list['i_AMPA'][4]['modinh3'] = ['output060820161304-pid28407-seed4-e3200-i600-subtr_mod_inh3-i_AMPA_140',
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 'output060920161653-pid58516-seed4-e3200-i600-subtr_mod_inh3-i_AMPA_149']

file_list['i_NMDA'][0]['modinh0'] = ['output060920161654-pid30570-seed0-e3200-i600-subtr_mod_inh0-i_NMDA_0',
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file_list['i_NMDA'][0]['modinh3'] = ['output060920161649-pid42227-seed0-e3200-i600-subtr_mod_inh3-i_NMDA_20',
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file_list['i_NMDA'][1]['modinh0'] = ['output060820161303-pid34488-seed1-e3200-i600-subtr_mod_inh0-i_NMDA_30',
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file_list['i_NMDA'][1]['modinh3'] = ['output060920161650-pid109542-seed1-e3200-i600-subtr_mod_inh3-i_NMDA_50',
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file_list['i_NMDA'][2]['modinh0'] = ['output060920161711-pid5516-seed2-e3200-i600-subtr_mod_inh0-i_NMDA_60',
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file_list['i_NMDA'][2]['modinh3'] = ['output061020161207-pid32361-seed2-e3200-i600-subtr_mod_inh3-i_NMDA_80',
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file_list['i_NMDA'][3]['modinh0'] = ['output060820161303-pid36168-seed3-e3200-i600-subtr_mod_inh0-i_NMDA_90',
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file_list['i_NMDA'][3]['modinh3'] = ['output060820161303-pid30931-seed3-e3200-i600-subtr_mod_inh3-i_NMDA_110',
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file_list['i_NMDA'][4]['modinh0'] = ['output060920161734-pid28704-seed4-e3200-i600-subtr_mod_inh0-i_NMDA_120',
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file_list['i_NMDA'][4]['modinh3'] = ['output060920161653-pid43177-seed4-e3200-i600-subtr_mod_inh3-i_NMDA_140',
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file_list['i_GABA'][0]['modinh0'] = ['output060820161304-pid47117-seed0-e3200-i600-subtr_mod_inh0-i_GABA_0',
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file_list['i_GABA'][0]['modinh3'] = ['output060920161649-pid44728-seed0-e3200-i600-subtr_mod_inh3-i_GABA_20',
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file_list['i_GABA'][1]['modinh0'] = ['output060820161304-pid39425-seed1-e3200-i600-subtr_mod_inh0-i_GABA_30',
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file_list['i_GABA'][1]['modinh3'] = ['output060920161649-pid36121-seed1-e3200-i600-subtr_mod_inh3-i_GABA_50',
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file_list['i_GABA'][2]['modinh0'] = ['output060820161304-pid47573-seed2-e3200-i600-subtr_mod_inh0-i_GABA_60',
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file_list['i_GABA'][2]['modinh3'] = ['output060920161649-pid12049-seed2-e3200-i600-subtr_mod_inh3-i_GABA_80',
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file_list['i_GABA'][3]['modinh0'] = ['output060920161649-pid146376-seed3-e3200-i600-subtr_mod_inh0-i_GABA_90',
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 'output060820161304-pid20315-seed3-e3200-i600-subtr_mod_inh0-i_GABA_99']
file_list['i_GABA'][3]['modinh3'] = ['output060920161649-pid7706-seed3-e3200-i600-subtr_mod_inh3-i_GABA_110',
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file_list['i_GABA'][4]['modinh0'] = ['output060920161649-pid112082-seed4-e3200-i600-subtr_mod_inh0-i_GABA_120',
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file_list['i_GABA'][4]['modinh3'] = ['output060820161304-pid28402-seed4-e3200-i600-subtr_mod_inh3-i_GABA_140',
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 'output060820161304-pid47127-seed4-e3200-i600-subtr_mod_inh3-i_GABA_149']

rec_filenames['i_AMPA'][0]['modinh0'] = 'output060916 - cell141 - e3200-i600-subtr_0-i_AMPA-inh0 - 10 trials'
rec_filenames['i_AMPA'][0]['modinh3'] = 'output060916 - cell141 - e3200-i600-subtr_0-i_AMPA-inh3 - 10 trials'
rec_filenames['i_AMPA'][1]['modinh0'] = 'output060916 - cell143 - e3200-i600-subtr_1-i_AMPA-inh0 - 10 trials'
rec_filenames['i_AMPA'][1]['modinh3'] = 'output060916 - cell143 - e3200-i600-subtr_1-i_AMPA-inh3 - 10 trials'
rec_filenames['i_AMPA'][2]['modinh0'] = 'output060916 - cell144 - e3200-i600-subtr_2-i_AMPA-inh0 - 10 trials'
rec_filenames['i_AMPA'][2]['modinh3'] = 'output060916 - cell144 - e3200-i600-subtr_2-i_AMPA-inh3 - 10 trials'
rec_filenames['i_AMPA'][3]['modinh0'] = 'output060916 - cell145 - e3200-i600-subtr_3-i_AMPA-inh0 - 10 trials'
rec_filenames['i_AMPA'][3]['modinh3'] = 'output060916 - cell145 - e3200-i600-subtr_3-i_AMPA-inh3 - 10 trials'
rec_filenames['i_AMPA'][4]['modinh0'] = 'output060916 - cell146 - e3200-i600-subtr_4-i_AMPA-inh0 - 10 trials'
rec_filenames['i_AMPA'][4]['modinh3'] = 'output060916 - cell146 - e3200-i600-subtr_4-i_AMPA-inh3 - 10 trials'

rec_filenames['i_NMDA'][0]['modinh0'] = 'output060916 - cell141 - e3200-i600-subtr_0-i_NMDA-inh0 - 10 trials'
rec_filenames['i_NMDA'][0]['modinh3'] = 'output060916 - cell141 - e3200-i600-subtr_0-i_NMDA-inh3 - 10 trials'
rec_filenames['i_NMDA'][1]['modinh0'] = 'output060916 - cell143 - e3200-i600-subtr_1-i_NMDA-inh0 - 10 trials'
rec_filenames['i_NMDA'][1]['modinh3'] = 'output060916 - cell143 - e3200-i600-subtr_1-i_NMDA-inh3 - 10 trials'
rec_filenames['i_NMDA'][2]['modinh0'] = 'output060916 - cell144 - e3200-i600-subtr_2-i_NMDA-inh0 - 10 trials'
rec_filenames['i_NMDA'][2]['modinh3'] = 'output060916 - cell144 - e3200-i600-subtr_2-i_NMDA-inh3 - 10 trials'
rec_filenames['i_NMDA'][3]['modinh0'] = 'output060916 - cell145 - e3200-i600-subtr_3-i_NMDA-inh0 - 10 trials'
rec_filenames['i_NMDA'][3]['modinh3'] = 'output060916 - cell145 - e3200-i600-subtr_3-i_NMDA-inh3 - 10 trials'
rec_filenames['i_NMDA'][4]['modinh0'] = 'output060916 - cell146 - e3200-i600-subtr_4-i_NMDA-inh0 - 10 trials'
rec_filenames['i_NMDA'][4]['modinh3'] = 'output060916 - cell146 - e3200-i600-subtr_4-i_NMDA-inh3 - 10 trials'

rec_filenames['i_GABA'][0]['modinh0'] = 'output060916 - cell141 - e3200-i600-subtr_0-i_GABA-inh0 - 10 trials'
rec_filenames['i_GABA'][0]['modinh3'] = 'output060916 - cell141 - e3200-i600-subtr_0-i_GABA-inh3 - 10 trials'
rec_filenames['i_GABA'][1]['modinh0'] = 'output060916 - cell143 - e3200-i600-subtr_1-i_GABA-inh0 - 10 trials'
rec_filenames['i_GABA'][1]['modinh3'] = 'output060916 - cell143 - e3200-i600-subtr_1-i_GABA-inh3 - 10 trials'
rec_filenames['i_GABA'][2]['modinh0'] = 'output060916 - cell144 - e3200-i600-subtr_2-i_GABA-inh0 - 10 trials'
rec_filenames['i_GABA'][2]['modinh3'] = 'output060916 - cell144 - e3200-i600-subtr_2-i_GABA-inh3 - 10 trials'
rec_filenames['i_GABA'][3]['modinh0'] = 'output060916 - cell145 - e3200-i600-subtr_3-i_GABA-inh0 - 10 trials'
rec_filenames['i_GABA'][3]['modinh3'] = 'output060916 - cell145 - e3200-i600-subtr_3-i_GABA-inh3 - 10 trials'
rec_filenames['i_GABA'][4]['modinh0'] = 'output060916 - cell146 - e3200-i600-subtr_4-i_GABA-inh0 - 10 trials'
rec_filenames['i_GABA'][4]['modinh3'] = 'output060916 - cell146 - e3200-i600-subtr_4-i_GABA-inh3 - 10 trials'

compress_i_syn_rec_files(file_list[syn_type][seed]['modinh'+str(condition)])
combine_output_files(file_list[syn_type][seed]['modinh'+str(condition)],
                     rec_filenames[syn_type][seed]['modinh'+str(condition)])