Grid cell oscillatory interference with noisy network oscillators (Zilli and Hasselmo 2010)

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Accession:128812
To examine whether an oscillatory interference model of grid cell activity could work if the oscillators were noisy neurons, we implemented these simulations. Here the oscillators are networks (either synaptically- or gap-junction--coupled) of one or more noisy neurons (either Izhikevich's simple model or a Hodgkin-Huxley--type biophysical model) which drive a postsynaptic cell (which may be integrate-and-fire, resonate-and-fire, or the simple model) which should fire spatially as a grid cell if the simulation is successful.
Reference:
1 . Zilli EA, Hasselmo ME (2010) Coupled Noisy Spiking Neurons as Velocity-Controlled Oscillators in a Model of Grid Cell Spatial Firing J. Neurosci. 30(41):13850-13860
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex spiny stellate cell; Abstract integrate-and-fire leaky neuron;
Channel(s): I Na,p; I Na,t; I K; I K,leak; I h;
Gap Junctions: Gap junctions;
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB;
Model Concept(s): Oscillations; Synchronization; Simplified Models; Spike Frequency Adaptation; Grid cell;
Implementer(s): Zilli, Eric [zilli at bu.edu];
Search NeuronDB for information about:  I Na,p; I Na,t; I K; I K,leak; I h;
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ZilliHasselmo2010
README.txt
Acker_sn_FI_n250.mat
fig_RS2sn_filthaftingtraj_n5000_p01_1noise_02res_July13_2D_spikes_0a.txt
fig_RS2sn_filthaftingtraj_n5000_p01_1noise_02res_July13_C_0a.mat
FigS4ABC_izh_simple0b_RS4sn_LIF_oct30_vary_gandncells_1noise_newpost_draft1.txt
FigS4DEF_izh_simple0b_RS4gn_LIF_oct30_vary_gandncells_1noise_newpost_draft1.txt
FigS8_izh_simple0b_RS2gn_LIF_nov08_vary_gandncells_0.125noise_newpost_draft1.txt
FigS8_izh_simple0b_RS2gn_LIF_nov08_vary_gandncells_0.25noise_newpost_draft1.txt
FigS8_izh_simple0b_RS2gn_LIF_nov08_vary_gandncells_0.5noise_newpost_draft1.txt
FigS8_izh_simple0b_RS2gn_LIF_nov08_vary_gandncells_1noise_newpost_draft1.txt
FigS8_izh_simple0b_RS2gn_LIF_nov08_vary_gandncells_2noise_newpost_draft1.txt
FigS8_izh_simple0b_RS2gn_LIF_nov08_vary_gandncells_4noise_newpost_draft1.txt
hafting_trajectory.m
rat_10925.mat
SI_acker_model_2d_grid.m
SI_acker_model_FI_history_dependence.m
SI_acker_model_FI_relations.m
SI_acker_model_stability_vs_params.m
SI_simple_model_2d_grid.m
SI_simple_model_FI_history_dependence.m
SI_simple_model_FI_relation.m
SI_simple_model_stability_vs_params.m
simple_model_RS1_FI_Jan09_n1.mat
simple_model_RS1gn_FI_Jan09_n250.mat
simple_model_RS1n_FI_Jan09_n1.mat
simple_model_RS1sn_FI_Jan09_n250.mat
simple_model_RS2_ext_FI_Jan09_n1.mat
simple_model_RS2_FI_Jan09_n1.mat *
simple_model_RS2gn_FI_Jan09_n250.mat
simple_model_RS2n_FI_Jan09_n1.mat
simple_model_RS2sn_FI_Jan01_n5000.mat
simple_model_RS2sn_FI_Jan01_n5000.txt
simple_model_RS2sn_FI_Jan09_n250.mat *
simple_model_RS2sn_FI_Jul10_n5000.mat
simple_model_RS2sn_FI_Jul10_n5000.txt
simple_model_RS2sn_FI_Jul11_n5000.mat
simple_model_RS2sn_FI_Jul11_n5000.txt
                            
16	1	95.8	0.1	8	25	4.5	0.075	100	-60	-40	0.7	0.03	2	-50	100	35	9.61858	0.182851	0.0472231	0.0868029	43	0.19629	0.196579	0.196728	0.00816826	0.00991212	0.0113116	1.88255	2.45027	3.61219	0
32	1	95.8	0.1	8	25	4.5	0.0375	100	-60	-40	0.7	0.03	2	-50	100	35	5.08206	0.19684	0.00374705	17.1993	40	0.196625	0.196844	0.197015	0.0042276	0.00565574	0.00730328	4.52797	7.54947	13.5475	0
64	1	95.8	0.1	8	25	4.5	0.01875	100	-60	-40	0.7	0.03	2	-50	100	35	5.05542	0.197847	0.00285828	30.0147	40	0.19777	0.197851	0.197908	0.00257084	0.00310326	0.00355801	19.3691	25.4763	37.1002	0
128	1	95.8	0.1	8	25	4.5	0.009375	100	-60	-40	0.7	0.03	2	-50	100	35	5.0297	0.198836	0.00186667	71.4329	39	0.198813	0.198833	0.198854	0.00176836	0.00188364	0.00201963	61.0153	70.1557	79.5963	0
256	1	95.8	0.1	8	25	4.5	0.0046875	100	-60	-40	0.7	0.03	2	-50	100	35	5.01703	0.199328	0.00120393	173.003	39	0.199323	0.199326	0.199331	0.00115894	0.00119647	0.00123133	165.384	175.166	186.697	0
512	1	95.8	0.1	8	25	4.5	0.00234375	100	-60	-40	0.7	0.03	2	-50	100	35	5.01739	0.19931	0.000818469	374.226	39	0.19931	0.19931	0.199315	0.000798945	0.00081557	0.000832496	361.722	376.891	392.74	0

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