Sleep-Stage-Specific Regulation of Cortical Excitation and Inhibition

Niethard, Niels; Hasegawa, Masashi; Itokazu, Takahide; Oyanedel, Carlos N.; Born, Jan; Satō, Takashi

doi:10.1016/j.cub.2016.08.035

Cited by 111 publications

(150 citation statements)

References 59 publications

Supporting

Mentioning

120

Contrasting

Order By: Relevance

“…Using standard criteria on ECoG and EMG (Niethard et al, 2016;Oishi et al, 2016;Seibt et al, 2017) states of SWS. IS sleep is a transitional state from NREM to REM sleep, found at the end of a NREM episode and characterized by an increase in sleep spindle frequency, increase in sigma (10)(11)(12)(13)(14)(15)(16) and theta (5-9 Hz) ECoG power and a concomitant decrease in delta (0.5-4 Hz) oscillations (Seibt et al, 2017) ( Figure 1C-E). We excluded microarousals in SWS (Watson et al, 2015) since we aimed to characterize true sleep astrocytic Ca 2+ signals.…”

Section: Resultsmentioning

confidence: 99%

“…Sleep states were identified from filtered ECoG and EMG signals (ECoG 0.5-30 Hz, EMG 100-1000 Hz) based on standard criteria for rodent sleep (Kohtoh et al, 2008;Kreuzer et al, 2015;Niethard et al, 2016;Seibt et al, 2017) (See Figure 1C-D). Non-rapid eye movement (NREM) sleep was defined as high amplitude delta ECoG activity (0.5-4 Hz) and low EMG activity; intermediate state (IS) was defined as an increase in theta (5-9 Hz) and sigma (9-16Hz) ECoG activity, and a concomitant decrease in delta ECoG activity; rapid eye movement (REM) sleep was defined as low amplitude theta ECoG activity with theta/delta ratio >0.5 and low EMG activity.…”

Section: Sleep-wake State Scoringmentioning

confidence: 99%

See 1 more Smart Citation

Ca²⁺signaling in astrocytes is sleep-wake state specific and modulates sleep

Bojarskaite

Bjørnstad

Pettersen

et al. 2019

Preprint

View full text Add to dashboard Cite

and e.a.nagelhus@medisin.uio.no.2 Summary Astrocytic Ca 2+ signaling has been intensively studied in health and disease but remains uncharacterized in sleep. Here, we employed a novel activity-based algorithm to assess astrocytic Ca 2+ signals in the barrel cortex of awake and naturally sleeping mice while monitoring neuronal Ca 2+ activity, brain rhythms and behavior. We discovered that Ca 2+ signaling in astrocytes exhibits distinct features across the sleep-wake cycle and is reduced in sleep compared to wakefulness.Moreover, an increase in astrocytic Ca 2+ signaling precedes transitions from slow-wave sleep to wakefulness, with a peak upon awakening exceeding the levels during whisking and locomotion.Genetic ablation of a key astrocytic Ca 2+ signaling pathway resulted in fragmentation of slow-wave sleep, yet increased the frequency of sleep spindles. Our findings suggest a role for astrocytic Ca 2+ signaling in modulating sleep.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Sleep-wake State Scoringmentioning

confidence: 99%

Ca²⁺signaling in astrocytes is sleep-wake state specific and modulates sleep

Bojarskaite

Bjørnstad

Pettersen

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…2). Unlike in the hippocampus, firing rates increased at the transition from NREM to REM (Evarts, 1964;McCarley and Hobson, 1971;Vyazovskiy et al, 2009;Renouard et al, 2015; but also see Niethard et al, 2016). However, similar to the hippocampus, firing rate distributions widened upon this transition, with higher firing neocortical cells showing relatively larger increases at the transition to REM (Δfiring rate = 24.9±5.4%, 33.3±5.7%, 34.0±4.1%, 53.9±6.7%, and 41.3±3.8%, for each quintile from last 1/3 of NREM to first 1/3 of REM, F (4) = 4.3, p = 0.002, one-way ANOVA; Fig.…”

Section: Differential Effects Of Rem and Nrem On Higher-and Lower-firmentioning

confidence: 98%

Neuronal firing rates diverge during REM and homogenize during non-REM

Miyawaki

Watson

Diba

2016

Preprint

View full text Add to dashboard Cite

Neurons fire at highly variable innate rates and recent evidence suggests that low and high firing rate neurons display different plasticity and dynamics. Furthermore, recent publications imply possibly differing rate-dependent effects in hippocampus versus neocortex, but those analyses were carried out separately and with possibly important differences. To more effectively synthesize these questions, we analyzed the firing rate dynamics of populations of neurons in both hippocampal CA1 and frontal cortex under one framework that avoids pitfalls of previous analyses and accounts for regression-to-the-mean. We observed remarkably consistent effects across these regions. While rapid eye movement (REM) sleep was marked by decreased hippocampal firing and increased neocortical firing, in both regions firing rates distributions widened during REM due to differential changes in high-firing versus low-firing cells in parallel with increased interneuron activity. In contrast, upon non-REM (NREM) sleep, firing rate distributions narrowed while interneuron firing decreased. Interestingly, hippocampal interneuron activity closely followed the patterns observed in neocortical principal cells rather than the hippocampal principal cells, suggestive of long-range interactions. Following these undulations in variance, the net effect of sleep was a decrease in firing rates. These decreases were greater in lower-firing hippocampal neurons but higher-firing frontal cortical neurons, suggestive of greater plasticity in these cell groups. Our results across two different regions and with statistical corrections indicate that the hippocampus and neocortex show a mixture of differences and similarities as they cycle between sleep states with a unifying characteristic of homogenization of firing during NREM and diversification during REM. Significance StatementMiyawaki and colleagues analyze firing patterns across low-firing and high-firing neurons in the hippocampus and the frontal cortex throughout sleep in a framework that accounts for regression-to-the-mean. They find that in both regions REM sleep activity is relatively dominated by high-firing neurons and increased inhibition, resulting in a wider distribution of firing rates. On the other hand, NREM sleep produces lower inhibition, and results in a more homogenous distribution of firing rates. Integration of these changes across sleep results in net decrease of firing rates with largest drops in low-firing hippocampal pyramidal neurons and high-firing neocortical principal neurons. These findings provide insights into the effects and functions of different sleep stages on cortical neurons.

show abstract

“…As a result, the statistical power of SANC analysis would increase significantly by ~100 fold. In addition, calcium imaging is another emerging technique for measuring large-scale activity of neuronal populations, which has been successfully used for chronic recordings from the rodent hippocampus [82–85] and cortex [86]. Since calcium signals are merely indirect measurements of neuronal spiking, the precise relationship between calcium signals and spiking is not fully identifiable and is also susceptible to biophysical variations.…”

Section: Future Directionsmentioning

confidence: 99%

Deciphering Neural Codes of Memory during Sleep

Chen

Wilson

2017

Trends in Neurosciences

View full text Add to dashboard Cite

Memories of experiences are stored in the cerebral cortex. Sleep is critical for consolidating hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms on memory consolidation, and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here, we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches for analyzing sleep-associated neural codes (SANC). We focus on two analysis paradigms for sleep-associated memory, and propose a new unsupervised learning framework (“memory first, meaning later”) for unbiased assessment of SANC.

show abstract

Sleep-Stage-Specific Regulation of Cortical Excitation and Inhibition

Cited by 111 publications

References 59 publications

Ca²⁺signaling in astrocytes is sleep-wake state specific and modulates sleep

Ca²⁺signaling in astrocytes is sleep-wake state specific and modulates sleep

Neuronal firing rates diverge during REM and homogenize during non-REM

Deciphering Neural Codes of Memory during Sleep

Contact Info

Product

Resources

About

Sleep-Stage-Specific Regulation of Cortical Excitation and Inhibition

Cited by 111 publications

References 59 publications

Ca2+signaling in astrocytes is sleep-wake state specific and modulates sleep

Ca2+signaling in astrocytes is sleep-wake state specific and modulates sleep

Neuronal firing rates diverge during REM and homogenize during non-REM

Deciphering Neural Codes of Memory during Sleep

Contact Info

Product

Resources

About

Ca²⁺signaling in astrocytes is sleep-wake state specific and modulates sleep

Ca²⁺signaling in astrocytes is sleep-wake state specific and modulates sleep