Name
Abstract | ||
|---|---|---|
Dynamics of the activity of neuronal networks have been intensively studied from the view point of the nonlinear dynamical system. The neuronal activities are recorded as multivariate time series of the epochs of spike occurrences–the spike trains–which are often effected by intrinsic and measuring noise. The spike trains can be considered as a mixture of a realization of deterministic and stochastic processes. Within this framework we considered several simulated spike trains derived from the Zaslavskii map with additive noise. The ensemble of all preferred firing sequences detected by the pattern grouping algorithm (PGA) in the noisy spike trains form a new time series that retains the dynamics of the original mapping. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11840817_65 | ICANN (1) |
Keywords | Field | DocType |
spike train analysis,neuronal network,multivariate time series,spike train,simulated spike,new time series,dynamical system attractor,zaslavskii map,neuronal activity,noisy spike train,additive noise,spike occurrence,dynamic system,time series,stochastic process | Zaslavskii map,Attractor,Spike train,Computer science,Stochastic process,Algorithm,Nonlinear dynamical systems,Artificial intelligence,Artificial neural network,Deterministic system (philosophy),Dynamical system,Machine learning | Conference |
Volume | ISSN | ISBN |
4131 | 0302-9743 | 3-540-38625-4 |
Citations | PageRank | References |
7 | 0.67 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yoshiyuki Asai | 1 | 30 | 7.56 |
| Takashi Yokoi | 2 | 9 | 1.43 |
| Alessandro E . P. Villa | 3 | 348 | 53.26 |