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Talk by Kaidi Shao

Max-Planck-Institute for Biological Cybernetics

20 Feb 2018 13:00
20 Feb 2018
Building 15.22, E1, Seminar Room 3009

Although sleep is one of the most widespread behavioral state across evolution, its functional role and underlying mechanisms are largely unknown. Interestingly, a variety of transient events, such as hippocampal sharp wave ripples or thalamic spindles, occur during successive sleep stages, coordinating neural activity across brain structures and possibly serving different functions such as memory consolidation. In order to better understand the role played by such events, developing appropriate data analysis techniques to quantify transient interactions across multiples brain structures, as well as neural models accounting for such interactions, is crucial.

In a first part of this talk, I will address the detection of causal interactions during transient events. While a difficulty is that such phenomena are usually very short and non-stationary, the fact that they can be observed repetitively during one experiment can be exploited to better estimate their statistical properties. We proposed to use a time-resolved Granger causality, which is able to reveal the temporal evolution of effective connectivity by taking into account the trial-to-trial variability.

This method was tested on sharp-wave ripples events recorded in monkey hippocampus. Consistent results with the ground truth in both temporal and frequency domain confirms that this method has the potential to overcome the difficulty in analyzing transient events.

In a second part, I will introduce a model for the generation of a key event of Rapid-eyemovement (REM) sleep: Ponto-Geniculo-Occipital (PGO) waves. Apart from REM stage, PGO waves also appear at the transitional stage between Slow Wave Sleep (SWS) and REM sleep (referred to as pre-REM sleep). Importantly, PGO waves in pre-REM and REM stages exhibit two different subtypes, which are hypothesized to contribute differently to memory consolidation during sleep. Therefore, based on a thalamocortical neural mass model and electrophysiological evidence in cats, we constructed a ponto-geniculo-cortical neural mass model to clarify the underlying cellular mechanism involved in producing different PGO subtypes and their interactions with other transient events in the brain.

Simulation results show that this model is able to reproduce several electrophysiological characteristics that qualitatively resemble both subtypes of PGO-related activities. Consistent with experimental findings, the simulated thalamic PGO waves block spindle oscillations during pre-REM stage. By incorporating tonic cholinergic neuromodulation, we were also able to replicate tonic state switches and the slow decreases in multi-unit activities before pre-REM PGO waves observed in anesthetized macaques in our laboratory. Overall, this model paves the way for a better understanding of the interactions between PGO waves and other sleep related event, and may also shed light on how different subtypes of PGO waves affect cortical plasticity across different sleep stages.