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  Neural mass modeling of the Ponto-Geniculo-Occipital wave and its neuromodulation

Shao, K., Logothetis, N., & Besserve, M. (2019). Neural mass modeling of the Ponto-Geniculo-Occipital wave and its neuromodulation. Poster presented at 28th Annual Computational Neuroscience Meeting (CNS*2019), Barcelona, Spain. doi:10.1186/s12868-019-0538-0.

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Shao, K1, 2, Author              
Logothetis, NK1, 2, Author              
Besserve, M1, 2, Author              
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1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: As a prominent feature of Rapid Eye Movement (REM) sleep and the transitional stage from Slow Wave Sleep to REM sleep (the pre-REM stage), Ponto-Geniculo-Occipital (PGO) waves are hypothesized to play a critical role in dreaming and memory consolidation [1]. During pre-REM and REM stages, PGO waves appear in two subtypes differing in number, amplitude and frequency. However, the mechanisms underlying their generation and propagation across multiple brain structures, as well as their functions, remains largely unexplored. In particular, contrary to the multiple phasic events occurring during non-REM sleep (slow waves, spindles and sharpwave ripples), computational modeling of PGO waves has to the best of our knowledge not yet been investigated. Based on experimental evidence in cats, the species were most extensively studied, we elaborated an existing thalamocortical model operating in the pre-REM stage [2], and constructed a pontothalamo- cortical neural mass model consisting of 6 rate-coded neuronal populations interconnected via biologically-verified synapses (Fig. 1A). Transient PGO-related activities are elicited by a single or multiple brief pulses, modelling the input bursts that PGO-triggering neurons send to cholinergic neurons in the pedunculopontine tegmentum nucleus (PPT). The effect of acetylcholine (ACh), as the primarily-affecting neuromodulator during the SWS-to-REM transition, was also modelled by tuning several critical parameters with tonically-varying ACh concentration. Our simulations are able to reproduce deflections in local field potentials (LFPs), as well as other electrophysiological characteristics consistent in many respects with classical electrophysiological studies (Fig. 1B). For example, the duration of both subtypes of thalamic PGO waves matches that of the PGO recordings with a similar waveform comprised of a sharp negative peak and a slower positive peak. The bursting duration of TC and RT neurons (10ms, 25ms) falls in the range reported by experimental papers (7-15ms, 20-40ms). Consistent with experimental findings, the simulated PGO waves block spindle oscillations that occur during pre-REM stage. By incorporating tonic cholinergic neuromodulation to mimic the SWS-to-REM transition, we were also able to replicate the electrophysiological differences between the two PGO subtypes with an ACh-tuned leaky potassium conductance in TC and RT neurons (Fig. 1C). These results help clarify the cellular mechanisms underlying thalamic PGO wave generation, e.g., the nicotinic depolarization of LGin neurons, whose role used to be under debate, is shown to be critical for the generation of the negative peak. The model elucidates how ACh modulates state transitions throughout the wake-sleep cycle, and how this modulation leads to a recently-reported difference of transient change in the thalamic multi-unit activities. The simulated PGO waves also provides us a biologically-plausible framework to investigate how they take part in the multifaceted brain-wide network phenomena occurring during sleep and the enduring effects they may induce through plasticity.

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 Dates: 2019-072019-11
 Publication Status: Published in print
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 Identifiers: DOI: 10.1186/s12868-019-0538-0
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Title: 28th Annual Computational Neuroscience Meeting (CNS*2019)
Place of Event: Barcelona, Spain
Start-/End Date: 2019-07-13 - 2019-07-17

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Title: BMC Neuroscience
Source Genre: Journal
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Publ. Info: BioMed Central
Pages: - Volume / Issue: 20 (Supplement 1) Sequence Number: P19 Start / End Page: 21 Identifier: ISSN: 1471-2202
CoNE: https://pure.mpg.de/cone/journals/resource/111000136905018