Name
Title | ||
|---|---|---|
Extracting non-linear integrate-and-fire models from experimental data using dynamic I-V curves. |
Abstract | ||
|---|---|---|
The dynamic I-V curve method was recently introduced for the efficient experimental generation of reduced neuron models. The method extracts the response properties of a neuron while it is subject to a naturalistic stimulus that mimics in vivo-like fluctuating synaptic drive. The resulting history-dependent, transmembrane current is then projected onto a one-dimensional current-voltage relation that provides the basis for a tractable non-linear integrate-and-fire model. An attractive feature of the method is that it can be used in spike-triggered mode to quantify the distinct patterns of post-spike refractoriness seen in different classes of cortical neuron. The method is first illustrated using a conductance-based model and is then applied experimentally to generate reduced models of cortical layer-5 pyramidal cells and interneurons, in injected-current and injected- conductance protocols. The resulting low-dimensional neuron models-of the refractory exponential integrate-and-fire type-provide highly accurate predictions for spike-times. The method therefore provides a useful tool for the construction of tractable models and rapid experimental classification of cortical neurons. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/s00422-008-0259-4 | Biological Cybernetics |
Keywords | Field | DocType |
in injected-current and injected- conductance protocols. the resulting low-dimensional neu- ron models—of the refractory exponential integrate-and-fire keywords i-v curve · exponential integrate-and-fire · refractoriness,non-linear integrate-and-fire model,tractable model,rapid experimental classification,v curve method,low-dimensional neuron model,experimental data,reduced neuron model,resulting history-dependent,efficient experimental generation,cortical neuron,refractory exponential integrate-and-fire type,a conductance-based model and is then applied experimen- tallytogeneratereducedmodelsofcorticallayer-5pyramidal cells and interneurons,conductance-based model,iv curve,exponential integrator,action potentials,refractoriness | Nonlinear system,Exponential function,Experimental data,Computer science,Exponential integrate-and-fire,Artificial intelligence,Current–voltage characteristic,Stimulus (physiology),Conductance,Neuron,Machine learning | Journal |
Volume | Issue | ISSN |
99 | 4-5 | 1432-0770 |
Citations | PageRank | References |
15 | 0.86 | 8 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laurent Badel | 1 | 27 | 2.01 |
| Sandrine Lefort | 2 | 15 | 0.86 |
| Thomas K Berger | 3 | 67 | 4.82 |
| Carl C H Petersen | 4 | 19 | 1.30 |
| Wulfram Gerstner | 5 | 2437 | 410.08 |
| Magnus J. E. Richardson | 6 | 87 | 8.24 |