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Section DYNAMICS IN LIFE SCIENCES, NEUROSCIENCE APPLICATIONS WORKSHOP
However, unlike the model discussed in [7], our model provides an explicit analytical description of the linear response function in (3) and, therefore, allows performing analytical stability analysis of the CW solutions. Apart from FDML lasers the approach discussed here can be applied to study the dynamics of mode-locked photonic crystal [7] and other types of multimode lasers.
Acknowledgements
We gratefully acknowledge useful discussions with Julien Javaloyes, Svetlana Gurevich, Svetlana Slepneva, and Shal-va Amiranashvili. A.G.V. and A.P. acknowledge the support of SFB 787 of the DFG. A.G.V. acknowledges the support of the grant 14-41-00044 of Russian Scientific Foundation.
References
1. H. A. Haus, IEEE J. Sel. Top. Quantum Electron., 2000, 6(6), 1173-1185.
2. U. Bandelow, M. Radziunas, J. Sieber, and M. Wolfrum, IEEE J. Quantum Electron., 2001, 37, 183-188.
3. A. G. Vladimirov and D. Turaev, Phys. Rev. A, 2005, 72, 033808.
4. S. Slepneva, B. Kelleher, B. O'Shaughnessy, S. Hegarty, A. G. Vladimirov, and G. Huyet, Opt. Express, 2013, 21(16), 19240-19251.
5. S. Slepneva, B. O'Shaughnessy, B. Kelleher, S. Hegarty, A. G. Vladimirov, H. Lyu, K. Karnowski, M. Wojtkowski, and G. Huyet, Opt. Express, 2014, 22(15), 18177-18185.
6. S. Yanchuk and M. Wolfrum, SIAM J. Appl. Dyn. Syst., 2010, 9, 519-535.
7. M. Heuck, S. Blaaberg, and J. Mark, Opt. Express, 2010, 18(17), 18003-18014.
OM&P
Optimal Extraction of Collective Rhythmicity from Unreliable EEG Channels
Justus Schwabedal*
Max-Planck-Institute for the Physics of Complex Systems,Germany. * Presenting e-mail: jschwabedal@gmail.com
I present a novel data-processing method that facilitates the detection and analysis of the irregular-oscillatory dynamics. The method is particularly useful to EEG analysis, as I will demonstrate in polysomnographic EEG recordings. By design, the method copes well with unreliable recordings showing fluctuating signal amplitude, phase offsets, and substantial amounts of measurement noise. Under such relatively general conditions, I will show that the method optimally enhances a rhythm of interest, and demonstrate its use by the detection and analysis of EEG sleep spindles.
Active Wireless Networks for Experimental Study in Neuroscience
AS. Dmitriev*, R.Y. Emelyanov, M.Yu. Gerasimov
Institute of Radio Engineering and Electronics. VA Kotelnikov RAS, Moscow Institute of Physics and Technology * Presenting e-mail: chaos@cplire.ru
The report examines the active wireless network, which can serve as an experimental tool in the study of various objects in neurodynamics. The network combines the nodes on which digital or analog neuron model (if necessary this may be living neurons), and programmable connections between them, which are implemented through wireless channels can be implemented. The latter circumstance allows the implementation of any type of connection (Linear. Non-linear, with delay, etc.) with any desired topology As an example, the modeling of the phenomenon of chimeras in the system of coupled oscillators is presented.
Chimeras - a popular and interesting phenomenon in the oscillator system [1], which are mainly studying by computer simulation. Experimental study of chimeras, in particular, in small ensembles requires special experimental setups. The active wireless network [2] is used as such experimental equipment in the report. Experiments were carried out with small ensemble of coupled oscillators. Ensemble of six phase oscillators [3] was using as the study system:
Opera Med Physiol 2016 Vol. 2 (S1) 43
