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Sonderforschungsbereich 910An analytical framework to investigate neuronal synchronization and network oscillations: phase oscillators and beyond

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

Held by Roberto Fernández Galán, PhD (Case Western Reserve University, USA)

 

Abstract:
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.

For further information, http://www.case.edu/med/galanlab.

 

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].
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].
G. K. Steinke and R. F. Galán (2011). Brain Rhythms Reveal a Hierarchical Network Organization. PLoS Comput Biol 7(10): e1002207. Available online on October 13th 2011.

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