Stability of neocortical synapses across sleep and wake states during the critical period in rats.
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ABSTRACT:
SUBMITTER: Cary BA
PROVIDER: S-EPMC8275129 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesConventional scoring of sleep provides little information about the process of transitioning between vigilance states. We applied the state space technique (SST) using frequency band ratios to follow normal maturation of different sleep/wake states, velocities of movements, and transitions between states of juvenile (postnatal day 34, P34) and young adult rats (P71).Design24-h sleep recordings of eight P34 and nine P71 were analyzed using conventional scoring criteria and SST one week following implantation of telemetric transmitter. SST is a non-categorical approach that allows novel quantitative and unbiased examination of vigilance-states dynamics and state transitions. In this approach, behavioral changes are described in a 2-dimensional state space that is derived from spectral characteristics of the electroencephalography.Measurements and resultsWith maturation sleep intensity declines, the duration of deep slow wave sleep (DSWS) and light slow wave sleep (LSWS) decreases and increases, respectively. Vigilance state determination, as a function of frequency, is not constant; there is a substantial shift to higher ratio 1 in all vigilance states except DSWS. Deep slow wave sleep decreases in adult relative to juvenile animals at all frequencies. P71 animals have 400% more trajectories from Wake to LSWS (p = 0.005) and vice versa (p = 0.005), and 100% more micro-arousals (p = 0.021), while trajectories from LSWS to DSWS (p = 0.047) and vice versa (p = 0.033) were reduced by 60%. In both juvenile and adult animals, no significant changes were found in sleep velocity at all regions of the 2-dimensional state space plot; suggesting that maturation has a partial effect on sleep stability.ConclusionsHere, we present novel and original evidence that SST enables visualization of vigilance-state intensity, transitions, and velocities that were not evident by traditional scoring methods. These observations provide new perspectives in sleep state dynamics and highlight the usefulness of this technique in exploring the development of sleep-wake activity.
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Project description:Slow-wave sleep is characterized by spontaneous alternations of activity and silence in corticothalamic networks, but the causes of transition from silence to activity remain unknown. We investigated local mechanisms underlying initiation of activity, using simultaneous multisite field potential, multiunit recordings, and intracellular recordings from 2 to 4 nearby neurons in naturally sleeping or anesthetized cats. We demonstrate that activity may start in any neuron or recording location, with tens of milliseconds delay in other cells and sites. Typically, however, activity originated at deep locations, then involved some superficial cells, but appeared later in the middle of the cortex. Neuronal firing was also found to begin, after the onset of active states, at depths that correspond to cortical layer V. These results support the hypothesis that switch from silence to activity is mediated by spontaneous synaptic events, whereby any neuron may become active first. Due to probabilistic nature of activity onset, the large pyramidal cells from deep cortical layers, which are equipped with the most numerous synaptic inputs and large projection fields, are best suited for switching the whole network into active state.
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Project description:BackgroundDifferentiating nonwear time from sleep and wake times is essential for the estimation of sleep duration based on actigraphy data. To efficiently analyze large-scale data sets, an automatic method of identifying these three different states is required. Therefore, we developed a classification algorithm to determine nonwear, sleep and wake periods from accelerometer data. Our work aimed to (I) develop a new pattern recognition algorithm for identifying nonwear periods from actigraphy data based on the influence of respiration rate on the power spectrum of the acceleration signal and implement it in an automatic classification algorithm for nonwear/sleep/wake states; (II) address motion artifacts that occur during nonwear periods and are known to cause misclassification of these periods; (III) adjust the algorithm depending on the sensor position (wrist, chest); and (IV) validate the algorithm on both healthy individuals and patients with sleep disorders.MethodsThe study involved 98 participants who wore wrist and chest acceleration sensors for one day of measurements. They spent one night in the sleep laboratory and continued to wear the sensors outside of the laboratory for the remainder of the day. The results of the classification algorithm were compared to those of the reference source: polysomnography for wake/sleep and manual annotations for nonwear/wear classification.ResultsThe median kappa values for the two locations were 0.83 (wrist) and 0.84 (chest). The level of agreement did not vary significantly by sleep health (good sleepers vs. subjects with sleep disorders) (p = 0.348, p = 0.118) or by sex (p = 0.442, p = 0.456). The intraclass correlation coefficients of nonwear total time between the reference and the algorithm were 0.92 and 0.97 with the outliers and 0.95 and 0.98 after the outliers were removed for the wrist and chest, respectively. There was no evidence of an association between the mean difference (and 95% limits of agreement) and the mean of the two methods for either sensor position (wrist p = 0.110, chest p = 0.164), and the mean differences (algorithm minus reference) were 5.11 [95% LoA -15.4-25.7] and 1.32 [95% LoA -9.59-12.24] min/day, respectively, after the outliers were removed.DiscussionWe studied the influence of the respiration wave on the power spectrum of the acceleration signal for the differentiation of nonwear periods from sleep and wake periods. The algorithm combined both spectral analysis of the acceleration signal and rescoring. Based on the Bland-Altman analysis, the chest-worn accelerometer showed better results than the wrist-worn accelerometer.
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Project description:BackgroundPrevious studies demonstrated a short-term relationship between infant sleep-wake states and oral feeding performance, with state being an indication of infants' neurobehavioral readiness for feeding. However, the relationship between sleep-wake states and feeding skills has not been evaluated longitudinally during hospitalization.ObjectivesThe purpose of this study was to examine preterm infants' sleep-wake state developmental trajectories and their associations with feeding progression during hospitalization.MethodsThis descriptive and exploratory study was a secondary analysis using data from a longitudinal two-group, randomized controlled trial evaluating the effects of early and late cycled light on health and developmental outcomes among extremely preterm infants who were born ≤28 weeks of gestational age. Sleep-wake states were assessed for two 2-hour interfeeding periods per day (day and night hours), 30 weeks postmenstrual age, and every 3 weeks until discharge. Occurrences of active sleep, quiet sleep, and waking were recorded every 10 seconds. Feeding progression was assessed based on an infant's postmenstrual age at five milestones: first enteral feeding, full enteral feeding, first oral feeding, half oral feeding, and full oral feeding. Trajectory analyses were used to describe developmental changes in sleep-wake states, feeding progression patterns, and associations between feeding progression and sleep-wake trajectories.ResultsActive sleep decreased while waking, and quiet sleep increased during hospitalization. Two distinct feeding groups were identified: typical and delayed feeding progression. In infants with delayed feeding progression, rates of active and quiet sleep development during the day were delayed compared to those with typical feeding progression. We also found that infants with delayed feeding progression were more likely to be awake more often during the night compared to infants with typical feeding progression.DiscussionsFindings suggest that delays in sleep-wake state development may be associated with delays in feeding progression during hospitalization. Infants with delayed feeding skill development may require more environmental protection to further support their sleep development.
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Project description:In the mouse, Period-2 (Per2) expression in tissues peripheral to the suprachiasmatic nuclei (SCN) increases during sleep deprivation and at times of the day when animals are predominantly awake spontaneously, suggesting that the circadian sleep-wake distribution directly contributes to the daily rhythms in Per2. We found support for this hypothesis by recording sleep-wake state alongside PER2 bioluminescence in freely behaving mice, demonstrating that PER2 bioluminescence increases during spontaneous waking and decreases during sleep. The temporary reinstatement of PER2-bioluminescence rhythmicity in behaviorally arrhythmic SCN-lesioned mice submitted to daily recurring sleep deprivations substantiates our hypothesis. Mathematical modeling revealed that PER2 dynamics can be described by a damped harmonic oscillator driven by two forces: a sleep-wake-dependent force and an SCN-independent circadian force. Our work underscores the notion that in peripheral tissues the clock gene circuitry integrates sleep-wake information and could thereby contribute to behavioral adaptability to respond to homeostatic requirements.
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Project description:During critical periods, all cortical neural circuits are refined to optimize their functional properties. The prevailing notion is that the balance between excitation and inhibition determines the onset and closure of critical periods. In contrast, we show that maturation of silent glutamatergic synapses onto principal neurons was sufficient to govern the duration of the critical period for ocular dominance plasticity in the visual cortex of mice. Specifically, postsynaptic density protein-95 (PSD-95) was absolutely required for experience-dependent maturation of silent synapses, and its absence before the onset of critical periods resulted in lifelong juvenile ocular dominance plasticity. Loss of PSD-95 in the visual cortex after the closure of the critical period reinstated silent synapses, resulting in reopening of juvenile-like ocular dominance plasticity. Additionally, silent synapse-based ocular dominance plasticity was largely independent of the inhibitory tone, whose developmental maturation was independent of PSD-95. Moreover, glutamatergic synaptic transmission onto parvalbumin-positive interneurons was unaltered in PSD-95 KO mice. These findings reveal not only that PSD-95-dependent silent synapse maturation in visual cortical principal neurons terminates the critical period for ocular dominance plasticity but also indicate that, in general, once silent synapses are consolidated in any neural circuit, initial experience-dependent functional optimization and critical periods end.
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Project description:Heightened neural excitability in infancy and childhood results in increased susceptibility to seizures. Such early-life seizures are associated with language deficits and autism that can result from aberrant development of the auditory cortex. Here, we show that early-life seizures disrupt a critical period (CP) for tonotopic map plasticity in primary auditory cortex (A1). We show that this CP is characterized by a prevalence of "silent," NMDA-receptor (NMDAR)-only, glutamate receptor synapses in auditory cortex that become "unsilenced" due to activity-dependent AMPA receptor (AMPAR) insertion. Induction of seizures prior to this CP occludes tonotopic map plasticity by prematurely unsilencing NMDAR-only synapses. Further, brief treatment with the AMPAR antagonist NBQX following seizures, prior to the CP, prevents synapse unsilencing and permits subsequent A1 plasticity. These findings reveal that early-life seizures modify CP regulators and suggest that therapeutic targets for early post-seizure treatment can rescue CP plasticity.
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