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An analytical framework to investigate neuronal synchronization and network oscillations: phase oscillators and beyond


In the first part of my presentation I will talk about the phase-oscillator approximation in neuroscience and its application to studying the formation of synchronized cell assemblies in neuronal networks, as well as two phenomena that are closely related to each other: stochastic synchronization and spike-time reliability. I will also present experimental results verifying some of the theoretical predictions. In the second part of my talk, I will present some recent results from my lab on how network oscillations, like those recorded with EEG or MEG, inform us about the structure of the network. In particular, I will show that networks that generate rhythms like those observed in EEG recordings from healthy individuals have a pronounced hierarchical structure, whereas networks generating rhythms like those observed in EEG from epileptic and, especially, schizophrenic patients are less hierarchical and display lower structural complexity.


Related literature

R. F. Galán (2009). The phase oscillator approximation in neuroscience: An analytical framework to study coherent activity in neural networks. In: Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior. Springer Series in Computational Neuroscience. [Table of contents [1]].
R. F. Galán (2011). Cellular mechanisms underlying spike-time reliability and stochastic synchronization: Insights and predictions from the phase-response curve. In: Phase Response Curves in Neuroscience. Springer Series in Computational Neuroscience. [Table of contents [2]].
G. K. Steinke and R. F. Galán (2011). Brain Rhythms Reveal a Hierarchical Network Organization. PLoS Comput Biol 7(10): e1002207. Available online [3] on October 13th 2011.

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