Bernstein Center Freiburg

Bernstein Seminar

March 9, 2021
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Bernstein Seminar
ALIREZA VALIDAZEH ►

Institute for Advanced Studies in Basic Sciences (IASBS) | Zanjan | Iran

New insights into the oscillatory dynamics of the neuronal networks

Tuesday, March 9, 2021

17:15h

The talk is open to the public.
Guests are cordially invited!

Hosted by Ad Aertsen

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Zoom Meeting
Meeting ID and password will be sent with e-mail invitation
or contact Fiona Siegfried
Fiona Siegfried@bcf.uni-freiburg.de

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Abstract

Brain functions are dependent on the integration of information processed in the different brain regions. It is known that the collective oscillations of the local brain networks provide a means for an efficient and flexible communication between the brain regions. A better understanding of the dynamical properties of the local brain networks and the mechanisms of the generation of the oscillations is crucial to unravel principles of the brain-wide communication. Despite to the extensive studies on the mechanisms of the generation of the collective oscillations in neuronal circuits, many aspects are still unknown. For example it is not well-known how rhythms at multiple frequencies are generated and what determines the inter-relations between the fast and slow oscillations. It is shown that the inhibitory neurons are important in the generation of gamma rhythms through interaction with other inhibitory neurons, or by reciprocal interaction with excitatory neurons. In this study we show that in the inhibitory networks the transition from asynchronous state to synchrony takes place through an extended transition region in the parameter space over which the gamma bursts appear intermittent with the periods of low synchrony. Wax and wane of the gamma bursts introduces a longer time scale into the dynamics of the system which leads to a broadband low-frequency peak in the power-spectrum, with a phase-amplitude coupling between the gamma and the low frequency envelope. We further explore the impact of the external stimuli on the phase and amplitude of such networks. We show that the collective response function of the network is dependent on the level of the synchrony and in the low synchrony level, the response function has a generic form which is independent of the properties of the constituent neurons.

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