Name
Title | ||
|---|---|---|
On the possible use of ICA to identify synaptic inputs from observations of several neurons |
Abstract | ||
|---|---|---|
We consider the problem of separating and determining the time courses of various synaptic input currents from simultaneous recordings of the time courses of membrane potentials, including spikes, of several neurons. Employing a suitable mathematical model, the method involves the differentiation of potentials and the use of ICA to determine the relative strengths of various synaptic inputs. At the same time, the waveforms of these input currents are recovered. We illustrate the application to nonlinear point models with deterministic and stochastic input currents, using a single-component Fitzhugh–Nagumo approximation. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1016/j.neucom.2004.08.008 | Neurocomputing |
Keywords | Field | DocType |
ICA,Synaptic potentials,Separation,Identification | Nonlinear system,Pattern recognition,Waveform,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | ISSN | Citations |
67 | 0925-2312 | 0 |
PageRank | References | Authors |
0.34 | 3 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pando G. Georgiev | 1 | 31 | 3.18 |
| Henry C. Tuckwell | 2 | 49 | 11.37 |