Arousal and sleep circuits

Jones, Barbara E.

doi:10.1038/s41386-019-0444-2

Cited by 155 publications

(128 citation statements)

References 198 publications

(232 reference statements)

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“…Neurons that comprise arousal-promoting nuclei can either act as local interneurons or project broadly to influence the activity of multiple brain regions, including the neocortex 21 . To assess which of these categories mWAKE DMH neurons belong to, we injected an AAV vector expressing Cre-dependent eGFP (AAV-FLEX-eGFP) into the DMH of mWAKE (Cre/+) mice and imaged the GFP + projections (Fig.…”

Section: Mwake Defines a Novel Clock-regulated Arousal Circuit In Thementioning

confidence: 99%

A Clock-Driven Neural Network Critical for Arousal

Bell

Liu

Kim

et al. 2020

Preprint

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Main The function of WAKE is conserved in mammalsWe previously identified the clock-output molecule WIDE AWAKE (WAKE) from a forward genetic screen in Drosophila 4 . WAKE modulates the activity of arousalpromoting clock neurons at night, in order to promote sleep onset and quality 4,5 . The mammalian proteome contains a single ortholog, mWAKE (also named ANKFN1/Nmf9), with 56% sequence similarity and which is enriched in the core region of the master circadian pacemaker suprachiasmatic nucleus (SCN) 4,6 ( Fig. 1a, Extended Data Fig. 1a). To investigate whether the function of WAKE is conserved in mice, we generated a putative null allele of mWAKE (mWAKE (-) ) by CRISPR/Cas9 insertion of 8 base pairs (containing a stop codon and generating a downstream frameshift) in exon 4, which is predicted to be in all splice isoforms of mWAKE ( Fig. 1b). As expected, mWAKE expression, as assessed by quantitative PCR and in situ hybridization (ISH), was markedly reduced in mWAKE (-/-) mice, likely due to nonsense-mediated decay (Fig. 1c, 1d). Given mWAKE expression in the SCN, we first examined locomotor circadian rhythms and found that mWAKE (-/-) mice exhibit a mild but non-significant decrease in circadian period length (Extended Data Fig. 1b, 1c). These results are similar to findings from fly wake mutants and mice bearing the Nmf9 mutation (a previously identified ENU-generated allele of mWAKE) 4,6 .Because we previously demonstrated that WAKE mediates circadian regulation of sleep timing and quality in fruit flies 4,5 , we next assessed sleep in mWAKE (-/-) mice via electroencephalography (EEG). Under light:dark (L:D) conditions, there was no difference in the amount of wakefulness, non-rapid eye movement (NREM), or REM sleep between mWAKE (-/-) mutants and wild-type (WT) littermate controls (Extended Data Fig. 1d). In constant darkness (D:D), there is a modest main effect of genotype on wakefulness (P<0.05) and NREM sleep (P<0.05), and a mild but significant decrease in REM sleep in mWAKE (-/-) mutants (Fig. 1e). Although the amount of wakefulness did not appreciably differ in mWAKE (-/-) mutants compared to controls, there was a change in the distribution of wakefulness at night; mutants spent more daily time in prolonged wake bouts, and some mutants exhibited dramatically long bouts of wakefulness (Extended Data Fig. 1e, 1f).

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Section: Mwake Defines a Novel Clock-regulated Arousal Circuit In Thementioning

confidence: 99%

A Clock-Driven Neural Network Critical for Arousal

Bell

Liu

Kim

et al. 2020

Preprint

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“…By the middle of the last century, it was increasingly clear that structures in the brainstem have a substantial role in the modulation of cortical states (Jones, 2008(Jones, , 2020. Early experiments of Moruzzi and Magoun (1949) showed that electrical stimulation of the brainstem i.e., the reticular activating system, and other subcortical structures could abolish cortical synchrony in the EEG, replacing it with low amplitude fast activity.…”

Section: Neuromodulation and The Hypothalamusmentioning

confidence: 99%

“…We now understand that many of the deep structures in the brainstem, midbrain, and hypothalamus are part of a large, interconnected neuromodulatory network that acts both directly and indirectly on the cortex to change brain states ( Figure 1B). Collectively, these structures, which include the locus coeruleus, pedunculopontine nucleus, tuberomammillary nucleus, and others constitute the reticular activating system (reviewed in Jones, 2008Jones, , 2020. Each structure is associated with a particular neuromodulatory transmitter, and stimulation of each of these structures can induce cortical state changes.…”

Section: Neuromodulation and The Hypothalamusmentioning

confidence: 99%

Perspective on the Multiple Pathways to Changing Brain States

Tantirigama

Zolnik

Judkewitz

et al. 2020

Front. Syst. Neurosci.

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In this review article, we highlight several disparate ideas that are linked to changes in brain state (i.e., sleep to arousal, Down to Up, synchronized to de-synchronized). In any discussion of the brain state, we propose that the cortical pyramidal neuron has a central position. EEG recordings, which typically assess brain state, predominantly reflect the activity of cortical pyramidal neurons. This means that the dominant rhythmic activity that characterizes a particular brain state ultimately has to manifest globally across the pyramidal neuron population. During state transitions, it is the long-range connectivity of these neurons that broadcast the resultant changes in activity to many subcortical targets. Structures like the thalamus, brainstem/hypothalamic neuromodulatory systems, and respiratory systems can also strongly influence brain state, and for many decades we have been uncovering bidirectional pathways that link these structures to state changes in the cerebral cortex. More recently, movement and active behaviors have emerged as powerful drivers of state changes. Each of these systems involve different circuits distributed across the brain. Yet, for a system-wide change in brain state, there must be a collaboration between these circuits that reflects and perhaps triggers the transition between brain states. As we expand our understanding of how brain state changes, our current challenge is to understand how these diverse sets of circuits and pathways interact to produce the changes observed in cortical pyramidal neurons.

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“…Furthermore, source distributions might change drastically during recording time. For instance, dominant sources alter drastically during the transition from wake state to sleep (Steriade, 2003) and during sleep cycles (Pace-Schott and Hobson, 2002; Steriade, 2003; Dang-Vu et al, 2010; Brown et al, 2012; Jones, 2019). Even the much longer circadian rhythm (Dijk and Czeisler, 1995; Pace-Schott and Hobson, 2002; Brown et al, 2012) is regulated by specific neuronal circuits.…”

Section: Introductionmentioning

confidence: 99%

The Influence of EEG References on the Analysis of Spatio-Temporal Interrelation Patterns

et al. 2019

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The characterization of the functional network of the brain dynamics has become a prominent tool to illuminate novel aspects of brain functioning. Due to its excellent time resolution, such research is oftentimes based on electroencephalographic recordings (EEG). However, a particular EEG-reference might cause crucial distortions of the spatiotemporal interrelation pattern and may induce spurious correlations as well as diminish genuine interrelations originally present in the dataset. Here we investigate in which manner correlation patterns are affected by a chosen EEG reference. To this end we evaluate the influence of 7 popular reference schemes on artificial recordings derived from well controlled numerical test frameworks. In this respect we are not only interested in the deformation of spatial interrelations, but we test additionally in which way the time evolution of the functional network, estimated via some bi-variate interrelation measures, gets distorted. It turns out that the median reference as well as the global average show the best performance in most situations considered in the present study. However, if a collective brain dynamics is present, where most of the signals get correlated, these schemes may also cause crucial deformations of the functional network, such that the parallel use of different reference schemes seems advisable.

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Arousal and sleep circuits

Cited by 155 publications

References 198 publications

A Clock-Driven Neural Network Critical for Arousal

A Clock-Driven Neural Network Critical for Arousal

Perspective on the Multiple Pathways to Changing Brain States

The Influence of EEG References on the Analysis of Spatio-Temporal Interrelation Patterns

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