Name
Title | ||
|---|---|---|
Sequential Estimation Of Gating Variables From Voltage Traces In Single-Neuron Models By Particle Filtering |
Abstract | ||
|---|---|---|
This paper addresses the problem of inferring voltage traces and ionic channel activity from noisy intracellular recordings in a neuron. A particle filtering method with optimal importance density is proposed to that aim, with the benefits of on-line estimation methods and Bayesian filtering theory. The method is applied to an inaccurate Morris-Lecar neuron model without loss of generality. Simulation results show the validity of the approach, where it is observed that theoretical estimation bounds are attained. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICASSP.2013.6637853 | 2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) |
Keywords | Field | DocType |
Neuroscience, dynamical systems, particle filtering | Biological neuron model,Computer science,Particle filter,Theoretical computer science,Without loss of generality,Artificial intelligence,Gating,Pattern recognition,Neurophysiology,Voltage,Algorithm,Communication channel,Sequential estimation | Conference |
ISSN | Citations | PageRank |
1520-6149 | 0 | 0.34 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Closas, P. | 1 | 236 | 30.31 |
| Antoni Guillamon | 2 | 21 | 4.51 |