Thalamic reticular control of local sleep in mouse sensory cortex

Fernandez, Laura M. J.; Vantomme, Gil; Osorio-Forero, Alejandro; Cardis, Romain; Béard, Elidie; Lüthi, Anita

doi:10.7554/elife.39111

Cited by 74 publications

(154 citation statements)

References 86 publications

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“…Interestingly, oscillatory activity in Drosophila R5 neurons is reminiscent of up-and down-states occurring at the level of mammalian cortical networks during deep sleep [36]. We thus hypothesize that the oscillations observed here are comparable to sleep-regulating thalamocortical oscillations [37][38][39] as well as network-specific oscillations observed during sleep deprivation in vertebrates (local sleep) [2,40,41]. Thus, the R5 network could be functionally analogous to the thalamus, as network-specific synchronization of slowwave activity within the thalamus plays a crucial role in maintaining sleep [37][38][39] and sensory gating [42].…”

Section: Discussionsupporting

confidence: 58%

Network-Specific Synchronization of Electrical Slow-Wave Oscillations Regulates Sleep Drive in Drosophila

et al. 2019

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Graphical Abstract Highlights d Drosophila R5 network exhibits sleep-regulating compound slow-wave oscillations d Activation of circadian pathways mediates R5 multi-unit synchronization d Synchronization and compound delta oscillations require NMDAR coincidence detection d Eliminating NMDAR coincidence detection in R5 disrupts sleep In Brief Raccuglia et al. discover sleep-regulatory compound delta oscillations within the Drosophila R5 network. NMDAR coincidence detection mediates singleunit synchronization, which is the mechanistic basis for generating compound delta oscillations. Eliminating NMDAR coincidence detection, and thus compound oscillations, disrupts sleep and facilitates wakening. SUMMARYSlow-wave rhythms characteristic of deep sleep oscillate in the delta band (0.5-4 Hz) and can be found across various brain regions in vertebrates. Across phyla, however, an understanding of the mechanisms underlying oscillations and how these link to behavior remains limited. Here, we discover compound delta oscillations in the sleep-regulating R5 network of Drosophila. We find that the power of these slowwave oscillations increases with sleep need and is subject to diurnal variation. Optical multi-unit voltage recordings reveal that single R5 neurons get synchronized by activating circadian input pathways. We show that this synchronization depends on NMDA receptor (NMDAR) coincidence detector function, and that an interplay of cholinergic and glutamatergic inputs regulates oscillatory frequency. Genetically targeting the coincidence detector function of NMDARs in R5, and thus the uncovered mechanism underlying synchronization, abolished network-specific compound slow-wave oscillations. It also disrupted sleep and facilitated light-induced wakening, establishing a role for slow-wave oscillations in regulating sleep and sensory gating. We therefore propose that the synchronization-based increase in oscillatory power likely represents an evolutionarily conserved, potentially ''optimal,'' strategy for constructing sleep-regulating sensory gates.

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Section: Discussionsupporting

confidence: 58%

Network-Specific Synchronization of Electrical Slow-Wave Oscillations Regulates Sleep Drive in Drosophila

et al. 2019

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“…Indeed, local aspects of spindles at the thalamic level is further supported by the possible occurrence of local spindles within the mouse TRN itself (Fernandez et al . 2018).…”

Section: Discussionmentioning

confidence: 99%

“…Fernandez et al . (2017, 2018) have recently shown in mice that cells in the TRN sector corresponding to auditory cortex had less repetitive bursting capacities than cells in other TRN sectors (reviewed by Vantomme et al . 2019).…”

Section: Discussionmentioning

confidence: 99%

Local sleep spindles in the human thalamus

Bastuji

Lamouroux

Villalba

et al. 2020

The Journal of Physiology

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Key points Sleep spindles have recently been shown to occur not only across multiple neocortical regions but also locally in restricted cortical areas. Here we show that local spindles are indeed present in the human posterior thalamus. Thalamic local spindles had lower spectral power than non‐local ones. While non‐local thalamic spindles had equal local and non‐local cortical counterparts, local thalamic spindles had significantly more local cortical counterparts (i.e. occurring in a single cortical site). The preferential association of local thalamic and cortical spindles supports the notion of thalamocortical loops functioning in a modular way. Abstract Sleep spindles are believed to subserve many sleep‐related functions, from memory consolidation to cortical development. Recent data using intracerebral recordings in humans have shown that they occur across multiple neocortical regions but may also be spatially restricted to specific brain areas (local spindles). The aim of this study was to characterize spindles at the level of the human posterior thalamus, with the hypothesis that, besides the global thalamic spindling activity usually observed, local spindles could also be present in the thalamus. Using intracranial, time‐frequency EEG recordings in 17 epileptic patients, we assessed the distribution of thalamic spindles during natural sleep stages N2 and N3 in six thalamic nuclei. Local spindles (i.e. spindles present in a single pair of recording contacts) were observed in all the thalamic regions explored, and compared with non‐local spindles in terms of intrinsic properties and cortical counterparts. Thalamic local and non‐local spindles did not differ in density, frequency or duration, but local spindles had lower spectral power than non‐local ones. Each thalamic spindle had a cortical counterpart. While non‐local thalamic spindles had equal cortical local and non‐local counterparts, local thalamic spindles had significantly more local cortical counterparts (i.e. occurring in a single cortical site). The preferential association of local thalamic and cortical spindles supports the notion of thalamocortical loops functioning in a modular way.

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“…Applied to the mouse, the SO (or δ1) upper demarcation might be as high as 2.5Hz, as others have already assumed due to other considerations (Binder et al, 2012, Fernandez et al, 2018. Accordingly, the δ1 population of SWs we identified, could represent the SO while δ2 SWs could represent δ, albeit with species-specific lower and upper frequency boundaries.…”

Section: Two Populations Of Swsmentioning

confidence: 58%

“…For instance, cortical UP-states synchronize thalamic δoscillations (Steriade et al, 1991), which might contribute to the prominent nesting we observed of δ2-waves at δ1 onset, while excitatory thalamocortical input to the cortex can trigger cortical UP-state initiation and removing thalamic input reduces cortical SO period and synchrony (David et al, 2013, Lemieux et al, 2014, Gent et al, 2018a. Moreover, thalamic neurons are intrinsically capable of generating rhythmic oscillations at <1Hz frequencies (Blethyn et al, 2006, Crunelli et al, 2018, Fernandez et al, 2018, Halasz et al, 2014, Herrera et al, 2016 that could aid the strengthening of the cortical SO. These and other observations demonstrate that SWs must be regarded as an emerging property of the thalamocortical network acting as a single unit (Crunelli et al, 2015).…”

Section: Neuronal Substrates Of δ1 and δ2mentioning

confidence: 86%

Reassessing the validity of slow-wave dynamics as a proxy for NREM sleep homeostasis

Hubbard

Gent

Hoekstra

et al. 2019

Preprint

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Sleep-wake driven changes in NREM sleep (NREMS) EEG delta (δ: ~0.75-4.5Hz) power are widely used as proxy for a sleep homeostatic process. We noted frequency increases in δ-waves in sleep-deprived (SD) mice, prompting us to re-evaluate how slow-wave characteristics relate to prior sleep-wake history. We discovered two types of δ-waves; one responding to SD with high initial power and fast, discontinuous decay (δ2: ~2.5-3.5Hz) and another unrelated to time-spentawake with slow, linear decays (δ1: ~0.75-1.75Hz). Human experiments confirmed this δ-band heterogeneity. Similar to SD, silencing of centromedial thalamus neurons boosted δ2-waves, specifically. δ2-dynamics paralleled that of temperature, muscle tone, heart-rate, and neuronal UP/DOWN state lengths, all reverting to characteristic NREMS levels within the first recovery hour. Thus, prolonged waking seems to necessitate a physiological recalibration before typical NREMS can be reinstated. These short-lasting δ2-dynamics challenge accepted models of sleep regulation and function based on the merged δ-band as sleep-need proxy.

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Thalamic reticular control of local sleep in mouse sensory cortex

Cited by 74 publications

References 86 publications

Network-Specific Synchronization of Electrical Slow-Wave Oscillations Regulates Sleep Drive in Drosophila

Network-Specific Synchronization of Electrical Slow-Wave Oscillations Regulates Sleep Drive in Drosophila

Local sleep spindles in the human thalamus

Reassessing the validity of slow-wave dynamics as a proxy for NREM sleep homeostasis

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