Izhikevich2004_SpikingNeurons_Class2Excitable
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ABSTRACT:
SUBMITTER: 
Enuo He
PROVIDER: BIOMD0000000142 | BioModels | 2007-07-16
REPOSITORIES: BioModels
Publications
Which model to use for cortical spiking neurons?
IEEE transactions on neural networks 20040901 5
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks. ...[more]
Similar Datasets
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM.
IEEE Trans Neural Netw.2004 Sep;15(5):1063-70.
15484883,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paperWhich Model to Use for Cortical Spiking Neurons? Figure1(S) inhibition-induced spiking has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking NeuronsThe original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events.a=-0.02; b=-1; c=-60; d=8; V=-63.8; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000129 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM.
IEEE Trans Neural Netw.2004 Sep;15(5):1063-70.
15484883,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paperWhich Model to Use for Cortical Spiking Neurons? Figure1(O) threshold variability has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking NeuronsThe original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events.a=0.03; b=0.25; c=-60; d=4; V=-64; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000136 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM.
IEEE Trans Neural Netw.2004 Sep;15(5):1063-70.
15484883,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paperWhich Model to Use for Cortical Spiking Neurons? Figure1(J) subthreshold oscillations has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking NeuronsThe original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events.a=0.05; b=0.26; c=-60; d=0; V=-62; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000135 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM.
IEEE Trans Neural Netw.2004 Sep;15(5):1063-70.
15484883,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paperWhich Model to Use for Cortical Spiking Neurons? Figure1(G) Class 1 excitable has been reproduced by MathSBML. The ODE and the parameters values are originally taken from the a paper Simple Model of Spiking NeuronsThe original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events.a=0.02; b=-0.1; c=-55; d=6; V=-60; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000141 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM. IEEE Trans Neural Netw.
2004 Sep;15(5):1063-70. 15484883
,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paper Which Model to Use for Cortical Spiking Neurons?
Figure1(M) rebound spike has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking Neurons
The original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events.a=0.03; b=0.25; c=-60; d=4; V=-64; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.
For more information see the terms of use
.
To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000132 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM.
IEEE Trans Neural Netw.2004 Sep;15(5):1063-70.
15484883,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paperWhich Model to Use for Cortical Spiking Neurons? Figure1(I) spike latency has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking NeuronsThe original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events. In this model a=0.02; b=0.2; c=-65; d=6; V=-70; u=b*V=0.2*(-70);
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000134 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich, EM
Neural Networks, IEEE Transactions on2004:15(5):1063-1070
15484883,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paperWhich Model to Use for Cortical Spiking Neurons? Figure1(L) integrator has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking NeuronsThe original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948
Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events. a=0.02; b=-0.1; c=-55; d=6; V=-60; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000130 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM. IEEE Trans Neural Netw.
2004 Sep;15(5):1063-70. 15484883
,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paper Which Model to Use for Cortical Spiking Neurons?
Figure1(N) rebound burst has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking Neurons
The original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events. a=0.03; b=0.25; c=-52; d=0;V=-64; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.
For more information see the terms of use
.
To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000131 | BioModels
Project description:This a model from the article:
Which model to use for cortical spiking neurons?
Izhikevich EM. IEEE Trans Neural Netw.
2004 Sep;15(5):1063-70. 15484883
,
Abstract:
We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.
The model is according to the paper Which Model to Use for Cortical Spiking Neurons?
Figure1(K) resonator has been reproduced by MathSBML. The ODE and the parameters values are taken from the a paper Simple Model of Spiking Neurons
The original format of the models are encoded in the MATLAB format existed in the ModelDB with Accession number 39948 Figure1 are the simulation results of the same model with different choices of parameters and different stimulus function or events. a=0.1; b=0.26; c=-60; d=-1; V=-62; u=b*V;
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2010 The BioModels Team.
For more information see the terms of use
.
To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2007-07-16 | BIOMD0000000133 | BioModels
Project description:The neural stem cell decision to self-renew or differentiate is tightly regulated by its microenvironment. Here, we have asked about this microenvironment, focusing on growth factors in the embryonic cortex at a time when it is largely comprised of neural precursor cells (NPCs) and newborn neurons. We show that cortical NPCs secrete factors that promote their maintenance while cortical neurons secrete factors that promote differentiation. To define factors important for these activities, we used transcriptome profiling to identify ligands produced by NPCs and neurons, cell surface mass spectrometry to identify receptors on these cells, and computational modeling to integrate these data. The resultant model predicts a complex growth factor environment with multiple autocrine and paracrine interactions. We tested this communication model, focusing on neurogenesis, and identified IFNγ, Nrtn and glial-derived neurotrophic factor (GDNF) as ligands with unexpected roles in promoting neurogenic differentiation of NPCs in vivo. We prepared E16 cortical neuron, E13 cortical precursor and co-cultured E16 cortical neuron and E13 cortical precursor cultures from three independent biological replicates.
2016-08-23 | E-GEOD-84482 | biostudies-arrayexpress