Abstract
We present cointegration analysis as a method to infer the network structure of a linearly phase coupled oscillating system. By defining a class of oscillating systems with interacting phases, we derive a data generating process where we can specify the coupling structure of a network that resembles biological processes. In particular we study a network of Winfree oscillators, for which we present a statistical analysis of various simulated networks, where we conclude on the coupling structure: the direction of feedback in the phase processes and proportional coupling strength between individual components of the system. We show that we can correctly classify the network structure for such a system by cointegration analysis, for various types of coupling, including uni-/bi-directional and all-to-all coupling. Finally, we analyze a set of EEG recordings and discuss the current applicability of cointegration analysis in the field of neuroscience.
| Original language | English |
|---|---|
| Journal | Journal of Mathematical Biology |
| Volume | 75 |
| Issue number | 4 |
| Pages (from-to) | 845–883 |
| Number of pages | 39 |
| ISSN | 0303-6812 |
| DOIs | |
| Publication status | Published - 1 Oct 2017 |
Keywords
- Cointegration
- Coupled oscillators
- EEG signals
- Interacting dynamical system
- Phase process
- Synchronization
- Winfree oscillator