SLEEP | DeepDyve

Abstract Study Objectives: The aim of this study was to examine whether the subthalamic nucleus (STN) plays a role in the transmission of PGO-like waves during REM sleep in humans. Design: Simultaneous recordings from deep brain electrodes to record local field potentials (LFPs), and standard polysomnography to ascertain sleep/wake states. Setting: Main Hospital, department of clinical neurophysiology sleep laboratory. Participants: 12 individuals with Parkinson's disease, with electrodes implanted in the STN; and, as a control for localization purposes, 4 cluster headache patients with electrodes implanted in the posterior hypothalamus. Interventions: All subjects underwent functional neurosurgery for implantation of deep brain stimulation electrodes. Results: Sharp, polarity-reversed LFPs were recorded within the STN during REM sleep in humans. These subthalamic PGO-like waves (2–3 Hz, 80–200 μV, and 300–500 msec) appeared during REM epochs as singlets or in clusters of 3–13 waves. During the pre-REM period, subthalamic PGO-like waves were temporally related to drops in the submental electromyogram and/or onset of muscular atonia. Clusters of PGO-like waves occurred typically before and during the bursts of rapid eye movements and were associated with an enhancement in fast (15–35 Hz) subthalamic oscillatory activity. Conclusion: Subthalamic PGO-like waves can be recorded during pre-REM and REM sleep in humans. Our data suggest that the STN may play an active role in an ascending activating network implicated in the transmission of PGO waves during REM sleep in humans. Basal Ganglia, subthalamic nucleus, REM sleep, PGO waves, fast oscillations, deep brain stimulation RAPID EYE MOVEMENT (REM) SLEEP IN HUMANS IS CHARACTERIZED BY PERIODS OF LOW-VOLTAGE, MIXED-FREQUENCIES ELECTROENCEPHALOGRAM (EEG activation) with occasional sawtooth waves, rapid eye movements (REMs), and muscular atonia.1 In cats, REM sleep is characterized by biphasic, sharp field potentials, called ponto-geniculo-occipital (PGO) waves, which are usually recorded in the lateral geniculate nucleus (LGN) of the thalamus.2 These potentials, which can occur as an isolated event independently of eye movements or in clusters closely related to the bursts of REMs,3 are associated with changes in the electromyogrami (EMG)4, 5 and with synchronized cortical fast oscillations.6, 7 Although the original term “PGO waves” indicated their presence in the feline geniculostriate visual pathway, PGO-like waves largely transcend this sensory system and are disseminated throughout many nuclei and cortical areas of cats, such as other thalamic nuclei, cerebellum, oculomotor nuclei, cingulate gyrus, amygdala, and hippocampus.2 Although the vast majority of evidence regarding the existence of PGO waves comes from experiments in cats, some studies have suggested a human equivalent using a variety of methods: scalp,8 cortical,9 and pontine10 electroencephalographic recordings; dipole tracing11; standardized low resolution brain electromagnetic tomography (sLORETA)12; positron emission tomography (PET)13,14; functional magnetic resonance imaging (fMRI)15,16; and magnetoencephalography (MEG).17 However, studies that have systematically recorded deep brain structures during sleep to directly detect PGO-like waves in humans are lacking. Functional neuroimaging studies of humans in REM sleep have shown a strong activation of the limbic and paralimbic regions of the forebrain, of the basal ganglia, and of the dorsal mesencephalon and pontine tegmentum.18–20 In cats, PGO waves have been shown to originate in the mesopontine tegmentum and the cholinergic neurons of the pedunculopontine tegmental nucleus (PPN), which is located at the junction between the mesencephalon and the pons, representing the final common path for their transfer to thalamocortical systems.2, 21 The PPN and the basal ganglia have reciprocal projections involved in motor control, postural muscle tone, saccadic eye movements, and sleep.22–27 Indeed, the PPN strongly modulates the neuronal activity of the subthalamic nucleus (STN), one of the core nuclei of the basal ganglia.22, 28 Because the basal ganglia participate in an ascending activating network involved in the rostral transmission of PGO waves.18, 29 Renewed interest in deep brain stimulation (DBS) has led to efforts to record neuronal activity, in the form of local field potentials (LFP), directly from the STN in human individuals with Parkinson's disease following implantation of DBS electrodes.30 Using simultaneous polysomnography (PSG) and DBS electrode recordings, the present study was designed to explore the participation of the STN in an ascending activating network involved in the transmission of PGO-like waves during REM sleep in humans. Methods Subjects Twelve patients with PD (6 men, 6 women) implanted with bilateral subthalamic DBS electrodes participated in the present study. Their mean age was 58.1 ± 8.92 years (range 42–73 years), and they had a mean disease duration of 12.5 ± 4.17 years (range 6–20 years), and a mean levodopa (L-dopa) treatment duration of 5.00 ± 2.68 years. These subjects were selected from an initial population of 48 patients of our 2003–2005 surgical period31 who were simultaneously recorded with standard polysomnography (PSG) and DBS electrodes during nighttime sleep after 84 hours of DBS electrode implantation.32 Patients from that group were included in the present study if they showed the following: (1) absence of complications for 6 days after surgical implantation; (2) positive localization of the DBS electrodes within the STN in both hemispheres, as assessed by postsurgical MRI, computed tomography (CT), and neurophysiologic recordings; and (3) an excellent clinical outcome after 1 year of subthalamic DBS. An excellent clinical outcome was defined as a significant reduction in L-dopa dose from the time of surgery to 1-year follow-up (960 ± 259.42 mEq/day vs. 227.27 ± 204.16 mEq/day; t11 = 7.06; P = 0.00004) and a significant increase in the following parameters: quality of life score (20 ± 6.32 vs. 7.08 ± 4.46; t11 = 5.23; P = 0.0003), based on the Unified Parkinson's Disease Rating Scale-part II (UPDRS II); motor disability score, based on the UPDRS III (40.92 ± 7.62 vs. 14.08 ± 6.44; t11 = 12.89; P = 0.00005); Hoehn and Yahr stage (3.33 ± 0.49 vs. 2.17 ± 0.33; t11 = 9.11; P = 0.00002); and scores on the Schwab and England scale (48.18 ± 18.34 vs. 86.82 ± 11.46; t11 = −7.16; P = 0.00003). These requirements for clinical outcome served to ensure the positive bilateral STN positioning of the DBS electrodes and to reduce the interindividual variability in terms of DBS electrode positioning.33 Four patients, who fulfilled these criteria were not selected: 2 did not show REM sleep during the nighttime recording, one asked to abort the sleep recording in the middle of the night, and the EMG for one patient was missing for more than half the PSG recording. The remaining 32 PD patients did not strictly fulfill the above criteria and were excluded from further analyses. Four patients with cluster headache (CH; 3 men and 1 woman) implanted with unilateral DBS electrodes within the posterior hypothalamus during our 2005–2008 surgical period were also recorded with PSG. This allowed us to compare the REM sleep-related PGO-like activity in the STN recordings of PD subjects with recordings made near to, but clearly outside, the STN. The mean age of these subjects was 47.25 ± 2.63 years (range 45–50 years), and they had a mean disease duration of 16.25 ± 16.15 years (range 2–37 years). All subjects provided written informed consent. The study protocol conformed to the Declaration of Helsinki and was approved by the Committee on Clinical Ethics at Hospital Universitario Central de Asturias (Oviedo, Asturias, Spain). Surgical and Neuroimaging Procedures Individual target coordinates for implantation of DBS electrodes in the STN were calculated based on indirect neuroimaging methods combining CT and MRI, and were anatomically defined as 12 mm lateral to the anterior-commissure/posterior-commissure (AC-PC) midline, 2 mm behind the mid-commissural point, and 3 mm below the axial AC-PC plane. In order to improve the localization of the STN, intraoperative monitoring (IOM) of multiunitary neuronal activity was performed. An Ohye's semi-microelectrode was inserted along a pre-defined trajectory through a cranial burr-hole in patients under local anesthesia.34 The insertions were made in steps of 1 mm, and the multiunitary activity was amplified, filtered, and displayed both as crude and 2-sec integrated signals. The latter was displayed over an anatomical atlas plane to indicate the trajectory, which typically was: caudate, thalamic reticularnucleus, internal capsule, top and bottom of the STN, and substantia nigra parsreticulata (SNr).35 The STN was identified by the presence of an abrupt increase in the synchronization of crude multiunitary activity in the 15–35 Hz frequency band36 with occasional discharges of ripples (> 200 Hz). When these activities were indicative of STN, wake subthalamic-related somatotopic responses to passive contralateral movements were performed.36 When IOM showed an atypical STN trajectory, median nerve evoked potentials were performed in order to detect ventroposterolateral thalamic and/or lemniscal activity. In addition, electrical monopolar stimulations through the macro-contact of the semi-microelectrode were used to detect undesirable motor responses, such as tonic or clonic contractions.37 In the 24 hemispheres of the PD subjects, a mean number of 4.25 ± 1.31 trajectories were performed to ensure optimal placement. The best trajectory was used for implanting the DBS electrodes (Model 3389, Medtronic, USA). These electrodes had 4 cylindrical contacts with a length of 1.5 mm, a diameter of 1.5 mm, and a surface area of 6 mm2. The contacts were spaced at a distance of 0.5 mm from one another, and were numbered 0, 1, 2, and 3 starting from the tip of the electrode. To ensure the accurate positioning of contact 2, insertions in steps of 1 mm were monitored using bipolar LFP recording, which was analyzed and displayed as described in the multiunitary detection of the STN. The goal of this approach was to position contact 2 in the dorsolateral area of the STN.38 The final Cartesian coordinates for contact 2 of the DBS electrodes, calculated by integrating immediate postoperative MRI coordinates and intraoperative neurophysiological coordinates39 were 11.96 ± 1.02 mm lateral to the AC-PC midline (X), −60 ± 2.35 mm behind the mid-commissural point (Y) and −49 ± 0.81 mm below the axial AC-PC plane (Z). The same methodology was used for the implantation of unilateral hypothalamic DBS electrodes in the 4 CH subjects. First, the coordinates of the anterior border of the left STN were targeted using the same IOM methodology described above. Second, these coordinates were modified by moving 6 mm medially in order to target the left posterior hypothalamus. The final Cartesian coordinates for contact 2 of the DBS electrodes were 5.97 ± 0.63 mm lateral to the AC-PC midline (X), −0.77 ± 0.22 mm behind the mid-commissural point (Y) and −0.92 ± 0.55 mm below the axial AC-PC plane (Z). For a 6-day period following placement of DBS electrodes, the PD subjects remained ON dopaminergic medication and OFF DBS condition (“ON/OFF”), and the leads from each of the 4 contacts of the quadripolar DBS electrode were led out through the scalp and connected to external amplifiers for recording or stimulation purposes. Beginning 84 hours after implantation surgery, recordings of oculomotor, facial and brachial extensor motor responses evoked by subthalamic stimulation and somatosensory evoked potentials were performed. These recordings were used to assess the final positioning of the DBS electrodes with respect to the oculomotor nucleus, posterior thalamus, red nucleus, and cerebral peduncle. Also beginning at 84 hours post-surgery, standard wake video-EEG was performed in order to detect critical phenomena and possible postsurgical complications. The evoked responses and the EEG recordings were made following standard guidelines and methodologies for PD patients.38 Simultaneous Deep Brain and Polysomnographic Recordings Simultaneous standard nighttime PSG and bilateral subthalamic DBS electrode recordings were made the night after these postsurgical neurophysiologic evaluations and were carried out from 22:00 (lights off) until 08:00 (lights on). The behavioral state was monitored by video in real time. All PD subjects were on standard postsurgical medication: L-dopa (750 mg), phenytoin (300 mg), and cefazolin (3 g). Opiate medication was not administered to any of the PD subjects. Standard PSG derivations of EEG (C3-A2, C4-A1, O1-A2, and O2-A1), EOG (E1-A2, E2-A2), submental EMG, EKG, breathing, SpO2, pulse, and body position were recorded in order to allow sleep staging. Subthalamic LFPs were recorded using the contacts of the DBS electrodes as bipolar derivations, numbered 0–1, 1–2, and 2–3. Subthalamic bipolar derivations were preferred, since we wished to ensure that the signals analyzed were as focally generated as possible and thus related to activity within the STN. These recordings were performed with a NicoletOne digital video-electroencephalograph. The PSG and STN signals were obtained by sampling the unfiltered data (DC 1 kHz) at 256 Hz (in recordings made before 2004) and at 512 Hz (in recordings made after 2004). These notch-filtered (50 Hz) records were displayed and scored as discrete 30-s epochs, with a sensitivity deflection of 70 μV/mm for scalp EEG and EOG, 50 μV/mm for EMG, and 20 μV/mm for STN derivations. A vascular artifact was recorded in the STN derivations during sleep; thus in all figures, the EKG and pulse derivations are displayed. Finally, 36 h after the PSG recording, the leads were internalized and connected to a permanently implanted programmable stimulator (Itrel model 3625, Medtronic, USA). This rendered the leads of the DBS electrodes inaccessible until the replacement of the stimulator's battery (after approximately 5 years of DBS). DBS requires adjustment of the most effective DBS electrode contact, as well as modification of stimulation parameters and dopaminergic medication in order to manage possible adverse effects. Therefore, at 1-year follow up, when the subjects' postsurgical clinical courses had stabilized, 2 clinical neurologists performed double-blind, video-based evaluations using the standard clinical scales described above. Based on these evaluations, at 1-year follow-up for the 12 PD subjects studied here, 16 hemispheres were receiving the originally intended monopolar stimulation with contact 2, seven were receiving monopolar stimulation with contact 1, and only one was receiving monopolar stimulation with contact 3. These data confirm that the STN was successfully targeted in the vast majority of hemispheres. Data Analyses Sleep stage scoring was performed blind to the STN traces according to standard methods.36 However, it was difficult to score NREM sleep stage 3 following the standard criteria (i.e., ≥ 20% of a 30-s epoch consisting of waves of peak-to-peak amplitude > 75 μV and 0.5–2 Hz frequency recorded in scalp EEG),40 probably because of the acute postsurgical condition of the subjects (e.g., bilateral frontal burr-holes, contusion, and pneumoencephalus). Thus, 30-s epochs were scored as wake-fulness; NREM stages 1 and 2, with the latter including those epochs that did not strictly fulfill the standard criteria for stage 3; and REM sleep. After scoring sleep stages, 2 researchers visually analyzed the STN traces during all epochs, displaying them with a low band-pass filter of 1 Hz and a high band-pass filter of 100 Hz. For all analyses, the first REM sleep period of the last third of the total sleep time (TST) was selected because REM sleep episodes are longer during the last third of the night.1 We defined pre-REM as the 3 epochs (90 s) preceding the first epoch scored as REM sleep.40 Subthalamic PGO-like waves were analyzed in terms of amplitude, frequency, duration, polarity reversal, organization, density, and length of the inter-potential interval (IPI). To assess the bilateral (inter-hemispheric) synchrony of PGO-like waves, we used the interval between the peak of the left PGO-like wave and that of the right one in each patient (n = 180 intervals) to calculate the mean consecutive difference (MCD). The association between subthalamic PGO-like waves and REMs was analyzed by calculating the incidence of PGO-like waves 500 ms before and after the EOG deflection. Synchronized oscillations in the STN traces were analyzed using digital filtering to group δ (0.5–4 Hz), θ (4–8 Hz), α (8–12 Hz), σ (12–15 Hz), and β (15–35 Hz) frequency bands. While some authors have suggested that there is no reason to split fast oscillations into β (15–30 Hz) and γ (> 30 Hz) categories in order to reflect different functional states,7 studies of the robust β oscillatory activity of the STN in healthy rats, nonhuman primates, and PD patients30 suggest that fast oscillations in the β band are important for motor processing.30, 41–43 In fact, these fast oscillations are considered a hallmark of the STN.30 Thus, the study of fast oscillations in the 15–35 Hz range allowed us to be consistent with previous STN studies,30,,42, 43 to avoid the possible confounder of subthalamic < 15 Hz spindle-like activity,7 and to avoid possible changes in subthalamic > 40 Hz oscillations induced by postsurgical L-dopa treatment.30, 41 Subthalamic β oscillations were analyzed in relation to the clusters of PGO-like waves by displaying the raw subthalamic signal and the filtered one, together with the standard PSG derivations. For visual analyses, low-β (15–25 Hz) and high-β (25–35 Hz) frequency bands were also displayed. The power of subthalamic 15–35 Hz activity before, after, and during the clusters of PGO-like waves was analyzed statistically. Statistical Analyses Paired Student t-tests were used to analyze changes in mean clinical and pharmacological parameters at 1-year follow-up, and changes in the power of the β band before and after the clusters of PGO-like waves. Student t-tests were used to analyze mean differences between subthalamic and hypothalamic subjects in terms of the Cartesian coordinates of contact 2 of the DBS electrodes. A repeated-measures ANOVA with Tukey HSD post hoc multiple comparisons was used to analyze mean changes in β power before, during, and after the PGO-like clusters. Linearity of the increase in β power associated with PGO-like clusters was tested with polynomial analysis. Effect size was measured with the partial eta-squared statistic (pη2). Parametric tests were used because data were normally distributed (Kolmogorov-Smirnov tests, P < 0.10), and because these tests are robust to violations of their assumptions and to the loss of power incurred by the use of the equivalent nonparametric tests. The significance level was set at P ≥ 0.05 (corrected for multiple comparisons). Results PSG Characteristics of the Sample The scoring of standard PSG recordings to ascertain sleep/wake states in the 12 PD subjects showed a mean sleep onset latency of 19.92 ± 19.63 min, and a mean TST of 394.88 ± 87.95 min. The percentages of sleep stages based on TST were 28.92% ± 17.61% for stage 1, 55.78% ± 20.43% for stage 2, and 15.30% ± 7.24% for REM sleep. Stage 3, as defined by current standard criteria,40 was not scored (see Methods). The REM latency was 71.29 ± 79.59 min. The percentage of wakefulness after sleep onset (WASO) based on the time spent in bed was 26.68% ± 16.61%. Although these recordings reflected the well-known disturbed sleep architecture in PD,44 the amount of sleep stages recorded was satisfactory for further analyses. Detection of Subthalamic PGO-like Waves In all 24 hemispheres of the 12 bilaterally implanted subjects, a pattern of subthalamic sharp field potentials was detected during REM sleep (Figure 1). These LFPs were bilaterally synchronous (MCD = 4.06 ms; sampling precision: 1000/256 = 3.906 ms/sample; Figure 1d), showed polarity reversal at different contact levels of the DBS electrodes, and appeared as singlets/doublets or in clusters with a variable number of waves. During periods of WASO with REMs and NREM sleep (outside the pre-REM period), subthalamic PGO-like waves were not detected (data not shown). Figure 1 Open in new tabDownload slide REM sleep related subthalamic activity. (A) A 30-s epoch of simultaneous PSG and bipolar subthalamic recording showing the pattern of PGO-like waves. A 0.5–100 Hz band-pass filter reveals the vascular pulse component in the right 2–3 derivation. (B) Axial MRI view showing DBS electrodes at the level of contact 0. (C) Enlarged section of the pattern of subthalamic PGO-like waves recorded during REM sleep. Figure 1 Open in new tabDownload slide REM sleep related subthalamic activity. (A) A 30-s epoch of simultaneous PSG and bipolar subthalamic recording showing the pattern of PGO-like waves. A 0.5–100 Hz band-pass filter reveals the vascular pulse component in the right 2–3 derivation. (B) Axial MRI view showing DBS electrodes at the level of contact 0. (C) Enlarged section of the pattern of subthalamic PGO-like waves recorded during REM sleep. Characterization of Subthalamic PGO-like Waves Two types of subthalamic sharp field potentials were found during full episodes of REM sleep. The first type (type I) consisted of those appearing in singlets or doublets that were not closely associated with the bursts of REMs, and were typically characterized by a duration of 366.89 ± 52.02 ms, an amplitude of 87.86 ± 27.64 μ V, an IPI of 387.08 ± 64.50 ms, and a frequency of 2.66 ± 0.46 Hz (Figure 2a). The second type (type II) were those that appeared in clusters, with a density of 7.90 ± 2.13 waves/cluster, and that were strongly associated with the bursts of REMs, usually preceding them. These clusters typically had a duration of 366.52 ± 49.78 ms, an amplitude of 96.23 ± 22.57 μV, an IPI of 369.17 ± 61.65 ms, and a frequency of 2.79 ± 0.50 Hz (Figure 2a). Figure 2 Open in new tabDownload slide Sequences of pre-REM and REM sleep. (A) A 90-s REM sleep period showing the clusters of subthalamic PGO-like waves associated with REMs. (B) Fast transition to REM sleep from a pre-REM sleep period where subthalamic PGO-like waves appeared as singlets linked to drops in the EMG and to onset of definite muscular atonia. (C) Transition to REM sleep from a pre-REM sleep period, where a cluster of subthalamic PGO-like waves appeared associated with short-lasting total EMG atonia and instability of the eyes recorded in the EOG. All subthalamic traces band-pass filtered at 1–100 Hz. Figure 2 Open in new tabDownload slide Sequences of pre-REM and REM sleep. (A) A 90-s REM sleep period showing the clusters of subthalamic PGO-like waves associated with REMs. (B) Fast transition to REM sleep from a pre-REM sleep period where subthalamic PGO-like waves appeared as singlets linked to drops in the EMG and to onset of definite muscular atonia. (C) Transition to REM sleep from a pre-REM sleep period, where a cluster of subthalamic PGO-like waves appeared associated with short-lasting total EMG atonia and instability of the eyes recorded in the EOG. All subthalamic traces band-pass filtered at 1–100 Hz. During pre-REM, subthalamic LFPs similar in amplitude, duration, and frequency to those that were found during REM sleep and that were classified as type I also occurred. These occasional pre-REM subthalamic potentials were associated with drops in submental EMG and with the onset of total submental EMG atonia (Figure 2b). Occasionally, clusters of PGO-like waves appeared during pre-REM; when they did, they were associated with the onset of muscular atonia and with certain degree of instability of the eyes recorded in the EOG (Figure 2c). Figure 3 shows the association of type I waves during pre-REM with drops in submental EMG and with onset of muscular atonia (Figure 3a), as well as the association of type II waves with REMs (Figure 3b). There was a higher incidence of PGO-like waves before the EOG deflection, specifically with peaks between −281 ms to −328 ms, between −94 ms and −117 ms, and also around the deflection, between 0 ms and +23 ms (Figure 3b). Since these waves typically last 366 ms and have an IPI of ~370 ms, approximately 2 waves occurred around the EOG deflection. Figure 3 Open in new tabDownload slide Subthalamic PGO-like waves, muscular atonia, and REMs. (A) A 15-s enlarged section of a pre-REM–REM sleep transition showing the close association of subthalamic PGO-like waves with drops in the EMG and the onset of muscular atonia during pre-REM sleep. Subthalamic traces band-pass filtered at 1–100 Hz. (B) Histogram showing the incidence of PGO-like waves 500 ms before and after REMs. The solid line represents the averaged amplitude defection in the EOG (μV), and the dotted lines represent ± SD. Bars represent the incidence (num. = number) of PGO-like waves. Figure 3 Open in new tabDownload slide Subthalamic PGO-like waves, muscular atonia, and REMs. (A) A 15-s enlarged section of a pre-REM–REM sleep transition showing the close association of subthalamic PGO-like waves with drops in the EMG and the onset of muscular atonia during pre-REM sleep. Subthalamic traces band-pass filtered at 1–100 Hz. (B) Histogram showing the incidence of PGO-like waves 500 ms before and after REMs. The solid line represents the averaged amplitude defection in the EOG (μV), and the dotted lines represent ± SD. Bars represent the incidence (num. = number) of PGO-like waves. Location of Subthalamic PGO-like Waves Subthalamic PGO-like waves showed polarity reversal, which is not expected for volume-conducted activity and which indicates a local field origin.7, 30 The specificity of this subthalamic activity was assessed by comparing these recordings with those made in the left posterior hypothalamus of CH subjects. The latter recordings showed sharp, non–polarity-reversed field potentials similar in shape to those found in the STN of PD subjects. Significant differences were detected in the Cartesian coordinates of contact 2 of the DBS electrodes between subthalamic PD subjects and hypothalamic CH subjects [final mediolateral (X), t26 = 7.51; P = 0.00006; dorsoventral (Z), t26 = −6.08; P = 0.0002] (see Methods for mean values). In contrast, no significant difference between these 2 groups was found in the final Cartesian rostrocaudal coordinate (Y) [t26 = 3.71; P = 0.714]. These data indicate that the recorded subthalamic PGO-like potentials had a local field origin within the STN, and that PGO-like waves can be recorded as volume-conducted potentials in the vicinity of the STN. Association of PGO-like Waves with Subthalamic Fast (15–35 Hz) Oscillations Increased subthalamic β (15–35 Hz) activity during and after the clusters of subthalamic PGO-like waves (Figure 4a) was revealed by spectral analyses (Figure 4b). Zooms of subthalamic segments are displayed in Figure 4c to show the polarity reversal of these β oscillations. Figure 4 Open in new tabDownload slide Subthalamic PGO-like clusters and fast (15–35Hz) oscillations. (A) A 15-s REM epoch of simultaneous PSG and STN traces from the period marked in light blue of the hypnogram (top). Subthalamic traces are displayed as raw (1–100 Hz), low-β (15–25 Hz; red) and high-β (25–35 Hz; pink) filtered derivations. Sawtooth waves in C3-A2 are temporally linked to subthalamic PGO-like waves. (B) Display of the fast Fourier transform (FFT) of 1-2R STN traces for different relative powers (μV2) for each second of the epoch: blue = δ (0.5–4 Hz), green = θ (4–8 Hz), yellow = α (8–12 Hz), orange = σ (12–15 Hz), red = low-β (15–25 Hz), pink = high-P (25–35 Hz). (C) Enlarged sections (1 s) of raw subthalamic traces revealing reduced β (15–35 Hz) activity before the clusters (C1), and polarity-reversed β activity (C2) with a higher amplitude after the cluster (C3). (D) Histogram showing the significant increase in beta power after the clusters of subthalamic PGO-like waves. (E) Histogram showing the linear increase in β power during the clusters (see Table 1). Figure 4 Open in new tabDownload slide Subthalamic PGO-like clusters and fast (15–35Hz) oscillations. (A) A 15-s REM epoch of simultaneous PSG and STN traces from the period marked in light blue of the hypnogram (top). Subthalamic traces are displayed as raw (1–100 Hz), low-β (15–25 Hz; red) and high-β (25–35 Hz; pink) filtered derivations. Sawtooth waves in C3-A2 are temporally linked to subthalamic PGO-like waves. (B) Display of the fast Fourier transform (FFT) of 1-2R STN traces for different relative powers (μV2) for each second of the epoch: blue = δ (0.5–4 Hz), green = θ (4–8 Hz), yellow = α (8–12 Hz), orange = σ (12–15 Hz), red = low-β (15–25 Hz), pink = high-P (25–35 Hz). (C) Enlarged sections (1 s) of raw subthalamic traces revealing reduced β (15–35 Hz) activity before the clusters (C1), and polarity-reversed β activity (C2) with a higher amplitude after the cluster (C3). (D) Histogram showing the significant increase in beta power after the clusters of subthalamic PGO-like waves. (E) Histogram showing the linear increase in β power during the clusters (see Table 1). Figure 4d shows the significant enhancement of β (15–35 Hz) power following the clusters of PGO-like waves (1.44 ± 0.90 μV2vs. 13.46 ± 8.12 μV2; t = 5.00; P = 0.0004). Furthermore, the β power of each second after the occurrence of each PGO-like wave of the cluster was analyzed. Since all subjects showed ≥ 6 waves per cluster during the first epoch of the REM episode, subsequent analyses were made on the β power before the cluster, after each wave in the cluster until the fifth wave, and after the cluster (i.e., the 6th wave in 3 subjects, and the 7,th 8th, and 9th in 1, 2, and 6 subjects, respectively). To examine within-subjects differences in β power associated with clusters of PGO-like waves, repeated-measures ANOVA was conducted (F1,11 = 9.93; P = 0.009; pη2 = 0.475). Table 1 shows pairwise comparisons that revealed significant differences in the β power before the clusters and the β power after the third and subsequent PGO-like waves of the clusters. Figure 4e clearly shows a significant linear increase in β power during clusters of PGO-like waves (F1,11 = 32.70; P = 0.0001; pη2 = 0.748), with a peak occurring after the clusters (see Table 1). After we adjusted for age, disease duration, and medication, this increase remained significant, and the mean differences remained similar to those reported in Table 1. Table 1 Enhancement of β (15–35 Hz) Power Associated with Clusters of Subthalamic PGO-like Waves . Beta Power1 . 0. . 1. . 2. . 3. . 4. . 5. . 6. . 0. Before the cluster 1.44 ± 0.26 — 0.9904 0.3910 0.0210 0.0432 0.0002 0.0001 1. After wave 1 2.82 ± 0.42 — — 0.8362 0.1325 0.2276 0.0016 0.0001 2. After wave 2 5.36 ± 0.96 — — — 0.8468 0.9420 0.0771 0.0014 3. After wave 3 7.84 ± 1.77 — — — — 0.9999 0.7060 0.0637 4. After wave 4 7.34 ± 1.21 — — — — — 0.5356 0.0320 5. After wave 5 10.82 ± 1.91 — — — — — — 0.8086 6. After the cluster 13.46 ± 2.34 — — — — — — — . Beta Power1 . 0. . 1. . 2. . 3. . 4. . 5. . 6. . 0. Before the cluster 1.44 ± 0.26 — 0.9904 0.3910 0.0210 0.0432 0.0002 0.0001 1. After wave 1 2.82 ± 0.42 — — 0.8362 0.1325 0.2276 0.0016 0.0001 2. After wave 2 5.36 ± 0.96 — — — 0.8468 0.9420 0.0771 0.0014 3. After wave 3 7.84 ± 1.77 — — — — 0.9999 0.7060 0.0637 4. After wave 4 7.34 ± 1.21 — — — — — 0.5356 0.0320 5. After wave 5 10.82 ± 1.91 — — — — — — 0.8086 6. After the cluster 13.46 ± 2.34 — — — — — — — 1 Values are means ± SEM μV2; 0. = β power 1 s before the first wave of the cluster (i.e., 1.); 1. to 5. = β power 1s after each wave of the cluster in consecutive order; 6. = β power 1 s after the cluster (i.e., the 6th wave in 3 subjects and the 7th, 8th and 9th in 1, 2, and 6 subjects, respectively). Bold P-values are significant at the P < 0.05 level (corrected for multiple comparisons) Open in new tab Table 1 Enhancement of β (15–35 Hz) Power Associated with Clusters of Subthalamic PGO-like Waves . Beta Power1 . 0. . 1. . 2. . 3. . 4. . 5. . 6. . 0. Before the cluster 1.44 ± 0.26 — 0.9904 0.3910 0.0210 0.0432 0.0002 0.0001 1. After wave 1 2.82 ± 0.42 — — 0.8362 0.1325 0.2276 0.0016 0.0001 2. After wave 2 5.36 ± 0.96 — — — 0.8468 0.9420 0.0771 0.0014 3. After wave 3 7.84 ± 1.77 — — — — 0.9999 0.7060 0.0637 4. After wave 4 7.34 ± 1.21 — — — — — 0.5356 0.0320 5. After wave 5 10.82 ± 1.91 — — — — — — 0.8086 6. After the cluster 13.46 ± 2.34 — — — — — — — . Beta Power1 . 0. . 1. . 2. . 3. . 4. . 5. . 6. . 0. Before the cluster 1.44 ± 0.26 — 0.9904 0.3910 0.0210 0.0432 0.0002 0.0001 1. After wave 1 2.82 ± 0.42 — — 0.8362 0.1325 0.2276 0.0016 0.0001 2. After wave 2 5.36 ± 0.96 — — — 0.8468 0.9420 0.0771 0.0014 3. After wave 3 7.84 ± 1.77 — — — — 0.9999 0.7060 0.0637 4. After wave 4 7.34 ± 1.21 — — — — — 0.5356 0.0320 5. After wave 5 10.82 ± 1.91 — — — — — — 0.8086 6. After the cluster 13.46 ± 2.34 — — — — — — — 1 Values are means ± SEM μV2; 0. = β power 1 s before the first wave of the cluster (i.e., 1.); 1. to 5. = β power 1s after each wave of the cluster in consecutive order; 6. = β power 1 s after the cluster (i.e., the 6th wave in 3 subjects and the 7th, 8th and 9th in 1, 2, and 6 subjects, respectively). Bold P-values are significant at the P < 0.05 level (corrected for multiple comparisons) Open in new tab Discussion The main finding of this study was the identification in humans of a bilateral pattern of sharp field potentials within the STN that preceded and accompanied REM sleep and that resembled the PGO waves typically recorded in cats. These subthalamic PGO-like waves appeared as singlets or as clusters (2–3 Hz, 2–8 s, 3–13 waves per cluster) and were associated with drops in the EMG and with total muscular atonia, both during epochs of REM sleep and during epochs preceding it (pre-REM). Furthermore, clusters of subthalamicves were typically associated with the bursts of REMs and with an enhancement of subthalamic fast (15–35 Hz) oscillatory activity. Our data support the role previously proposed18 for the basal ganglia nuclei as part of an ascending activating network involved in the rostral transmission of PGO waves during REM sleep in humans. Many of the features of subthalamic PGO-like waves recorded as LFPs in the present study using DBS electrodes are consistent with those of previous studies in animals. Datta2 has summarized the characteristics of naturally occurring feline PGO waves during REM sleep as biphasic, sharp field potentials that last 60–120 ms and have an amplitude of 200–300 μV. These potentials occur as singlets and as clusters containing a variable number of PGO waves (3–5 waves), with a density ranging from 30 to 60 waves/min. In the rat, pontine PGO-like waves have amplitudes (± 150 μV) and durations (± 100 ms) similar to those of PGO waves recorded in the cat.2 The interspecies variability may be due to morphological differences, or to the type and/or the positioning of the electrodes used relative to the dipole source. Similar to what we observed in humans (Figure 2), PGO waves in the cat precede REM sleep by approximately 30 to 90 s, appearing as singlets that precede the other key signs of REM sleep (i.e., EEG activation, muscular atonia, and REMs), and they continue to occur as clusters throughout REM sleep.2 In the present study, as in studies of feline PGO waves,2, 3 singlet subthalamic PGO-like waves were independent of eye movement (type I), while clusters of PGO-like waves were typically associated with the bursts of REMs during REM sleep (type II). Vanni-Mercier and Debilly45 provided evidence for a parallel anatomical organization of the oculomotor and PGO systems in cats; these authors suggested that an interconnection between the PPN and the caudoventral pontine reticular formation (PRF) may operate as a common generator of REMs and PGO waves during REM sleep.45 Indeed, a network involving the superior colliculus (SC), PPN, SNr, and STN, among other nuclei, has been suggested to generate waking saccades46–48; thus, an association between the subthalamic PGO-like clusters and the bursts of REMs during REM sleep is reasonable. It is possible that we failed to detect subthalamic PGO-like waves during periods of WASO with REMs either because different neurophysiological mechanisms subserve the generation of waking saccades and REM sleep saccades, or because the oculomotor system is in a different state of excitation during these different types of saccades.49 This issue deserves further investigation in humans. We also found that subthalamic PGO-like waves were associated with drops in the submental EMG and/or with the onset of muscle atonia. Previous studies in cats showed that naturally occurring and externally induced PGO waves are associated with the suppression of EMG during pre-REM and REM sleep periods.4,5, 50 Since PGO waves have been proposed to reflect central activation of alerting mechanisms,51–53 a functional link has been suggested between the mechanisms involved in the generation of PGO waves and the inhibitory motoneuron system, which may serve to preserve atonia from potentially disruptive PGO-related influences.5 Thus, it is possible that the same mechanism that in cats induces PGO waves, REMs, and the inhibition of motoneurons during REM sleep, drives the subthalamic PGO-like waves recorded in the present study. Furthermore, cortical PGO waves have been shown to underlie the synchronization of cortical fast oscillations during REM sleep in cats.6,7 During REM sleep in humans, cortical and subcortical fast oscillations are enhanced54–56 and strong subthalamo-cortical coherence is observed in the β range.30, 56 Since PGO waves can not be clearly identified with scalp EEG in humans, studies have corroborated the synchronization of scalp fast oscillations as associated with the bursts of REMs.57 In the present study, clusters of subthalamic PGO-like waves related to the time occurrence of the bursts of REMs were associated with an enhancement of the power of fast subthalamic oscillatory activity in the β (15–35 Hz) range. The linear increase in the power of subthalamic β oscillations provides evidence for the proposed role of PGO-like activity in the progressive synchronization of fast oscillations during REM sleep. Current models of REM sleep posit that activation of the forebrain occurs through ascending activating systems in the brainstem reticular arousal system and the basal forebrain; this activation is aminergically deficient and cholinergically driven,29 and it is modulated by GABAergic and glutamatergic release.58 The cholinergic neurons of the PPN, which are the final common path of brainstem networks for the transfer of PGO waves to thalamocortical systems,12, 21 extensively innervate the STN, which, in turn, sends back glutamatergic projections to the PPN.22–25 The STN is a key component of the basal ganglia and a potent regulator of the basal ganglia-thalamocortical associative and limbic circuits.59 In fact, the output nuclei of the basal ganglia (SNr/ internal Globus Pallidus, GPi), which send projections to the thalamocortical system, are modulated by three pathways: a “direct pathway” (cortico-striatal-SNr/GPi), an “indirect pathway” (cortico-striatal-external GP-STN-SNr/GPi) and a “hyperdirect pathway” (cortico-STN-SNr/GPi).23 In wakefulness, these pathways are thought to be functionally involved in the execution and inhibition of movement, respectively.24,30, 47 Although little is known about how these anatomo-functional pathways operate during REM sleep,25, 60 some studies have reported that the basal ganglia output nuclei may play a role in the modulation of REM sleep phenomena; the precise role depends on their interconnections with the PPN.23,26, 27 Since previous authors have proposed that the PPN-STN projection is a key interface linking the basal ganglia pathways with brainstem systems involved in motor control, sleep, and arousal,22–25,61 it is therefore plausible that, during REM sleep, the PPN drives the pattern of subthalamic PGO-like waves recorded in the present study. PGO waves have been traditionally regarded as a physiological correlate of dreaming29,,62,63 and, recently, of sleep-dependent learning.64 Moreover, changes in subthalamic β oscillations have been shown to be strongly associated with overt and imaginary movement.42, 43 Future studies should therefore examine how the pattern of subthalamic PGO-like waves and fast oscillations during REM sleep relate to these cognitive phenomena. Admittedly, our observations are limited by several factors. First, we studied individuals with PD, a disease known to involve sleep pathology,44 such as decreased REM sleep periods, REM density, and muscle atonia, as well as the presence of REM sleep behavior disorder (RBD). Nevertheless, none of the 12 PD individuals showed complex overt behaviors during REM sleep, and none had been diagnosed with RBD. Moreover, our EOG (E1-A2, E2-A2) montage did not record the complete direction of REMs,40 and in some cases only certain degree of instability of the eyes could be recorded; this may have affected the REM density recorded and thus the association of PGO-like waves with REMs. Second, we recognize that the synchronization in the PGO-like and β bands may reflect the pathological hyperactivity of the STN in PD, which is characterized by an augmented synchrony and a mildly increased firing rate with bursting activity.30 It is therefore possible that PGO-like and β activities are more evident within the STN due to this tendency towards higher neuronal synchrony in PD. However, the fact that we recorded non–polarity-reversed PGO-like waves in the vicinity of the STN of CH patients suggests that our results are valid. Future studies should use other pathological models of the STN and/or multi-target recordings (i.e., PPN+STN; PPN+GPi) in humans and other mammals. Third, the surgical implantation, the acute post-surgical state and/or drug therapy itself may have altered the normal dynamics of the activity within the STN. The neuronal shock and/or the edema may have altered the amplitude of the activities recorded. In fact, changes in L-dopa treatment have been shown to modify the frequencies recorded in the STN; however, these changes attenuate oscillations in the β band and enhance those in higher frequency bands.30, 41 Notwithstanding these limitations, we conclude that subthalamic PGO-like waves can be recorded during pre-REM and REM sleep in humans. These sharp field potentials are associated with muscular atonia, with the bursts of REMs, and with an enhancement of subthalamic fast oscillatory activity. Our findings give further support to animal sleep research exploring the functional significance of PGO waves and its translation to humans. 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journal article

LitStream Collection

Orexin Neurons Are Necessary for the Circadian Control of REM Sleep

Kantor, Sandor; Mochizuki, Takatoshi; Janisiewicz, Agnieszka M.; Clark, Erika; Nishino, Seiji; Scammell, Thomas E.

2009 SLEEP

doi: 10.1093/sleep/32.9.1127pmid: 19750917

Abstract Study Objectives: The orexin-producing neurons are hypothesized to be essential for the circadian control of sleep/wake behavior, but it remains unknown whether these rhythms are mediated by the orexin peptides or by other signaling molecules released by these neurons such as glutamate or dynorphin. To determine the roles of these neurotransmitters, we examined the circadian rhythms of sleep/wake behavior in mice lacking the orexin neurons (ataxin-3 [Atx] mice) and mice lacking just the orexin neuropeptides (orexin knockout [KO] mice). Design: We instrumented mice for recordings of sleep-wake behavior, locomotor activity (LMA), and body temperature (Tb) and recorded behavior after 6 days in constant darkness. Results: The amplitude of the rapid eye movement (REM) sleep rhythm was substantially reduced in Atx mice but preserved in orexin KO mice. This blunted rhythm in Atx mice was caused by an increase in the amount of REM sleep during the subjective night (active period) due to more transitions into REM sleep and longer REM sleep episodes. In contrast, the circadian variations of Tb, LMA, Wake, non-REM sleep, and cataplexy were normal, suggesting that the circadian timekeeping system and other output pathways are intact in both Atx and KO mice. Conclusions: These results indicate that the orexin neurons are necessary for the circadian suppression of REM sleep. Blunting of the REM sleep rhythm in Atx mice but not in orexin KO mice suggests that other signaling molecules such as dynorphin or glutamate may act in concert with orexins to suppress REM sleep during the active period. Ataxin-3, knock-out, narcolepsy, cataplexy, circadian rhythm, constant darkness, body temperature, REM sleep, REM sleep latency, REM sleep propensity MANY RESEARCHERS HAVE HYPOTHESIZED THAT THE POORLY CONSOLIDATED WAKE AND INAPPROPRIATELY TIMED RAPID EYE MOVEMENT (REM) SLEEP of narcolepsy could be caused by disruption of the circadian rhythms of sleep and wakefulness.1–4 The suprachiasmatic nucleus (SCN) is essential for the timing and consolidation of sleep and wakefulness;5 and squirrel monkeys with SCN lesions lose the circadian rhythms of sleep and wakefulness and are unable to produce long bouts of wakefulness.6 Similarly, people with narcolepsy have difficulty maintaining wakefulness, and their naps often include bouts of REM sleep, regardless of the time of day.1 Most likely, this is not caused by a primary defect in the generation of circadian rhythms because the daily rhythms of body temperature and cortisol are essentially normal.7 Instead, people with narcolepsy may have a specific defect in the circadian control of sleep and wakefulness. Considerable basic research supports this hypothesis. Narcolepsy with cataplexy is caused by a loss of the orexin/hypocretin-producing neurons.8–10 Since the orexin neurons receive both direct and indirect signals from the SCN and send projections to many state-regulatory brain regions, they are anatomically well positioned to mediate the circadian timing of sleep and wakefulness.11–17 Extracellular levels of orexin vary in a circadian pattern, with high levels during the waking period, and lesions of the SCN abolish this rhythm.18–20 Furthermore, nonspecific lesions of the orexin field or of the pathways between the SCN and the orexin neurons disrupt the timing of sleep/wake behavior.12,13,21 We therefore hypothesized that the orexin neurons are an essential relay for the circadian signals that time and consolidate sleep and wake. To determine whether the orexin neurons are necessary for the circadian control of sleep and wakefulness, we examined free-running circadian rhythms in 2 different strains of orexin deficient mice: orexin/ataxin-3 (Atx) mice with an acquired, selective loss of the orexin/hypocretin neurons and orexin peptide knockout (KO) mice.22,23 Materials and Methods All animal experiments were carried out in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals (National Institutes of Health Publication 8023, revised 1978). These studies were approved by the Institutional Animal Care and Use Committees of Beth Israel Deaconess Medical Center and Harvard Medical School. Animals We used 8 male, transgenic orexin/ataxin-3 mice (Atx), 6 orexin peptide knockout (KO) mice, and corresponding wild-type littermates (8 WTAtx and 8 WTKO). The orexin KO mice have a neomycin cassette inserted into the prepro-orexin gene and simply lack orexin-A and –B.22 In Atx mice, the human prepro-orexin promoter drives expression of ataxin-3, a toxic transgene that selectively kills the orexin neurons by around 12 weeks of age.23 Thus, these Atx mice are an excellent model of the loss of the orexin-producing neurons that occurs in people with narcolepsy with cataplexy9,10 and allow one to test the roles of other neurotransmitters (e.g., dynorphin and glutamate) produced in the orexin neurons.8,24 To maximize genetic homogeneity, we backcrossed the Atx and orexin KO lines with C57BL/6J mice for 6–8 generations. Mice were identified by genotyping and immunostaining. PCR was performed on genomic DNA from tail biopsies. Primers used were 5'-CAT GAA GGA AGA AGG TCC TGG and 3'-CCT TGC ACC CAG GAA TCT GG against the orexin/ataxin-3 transgene and 5'-GAC GAC GGC CTC AGA CTT CTT GGG and 3'-TCA CCC CCT TGG GAT AGC CCT TCC against the endogenous mouse prepro-orexin gene. We identified orexin KO mice using a neo primer 5'-TAG TTG CCA GCC ATC TGT TG and a genomic primer 3'-ACT CTC CAC CCA CAG ACA GG. After the polysomnographic recordings, mice were deeply anesthetized and perfused. Immunostaining for orexin-A (1:2500; Santa Cruz Biotechnology, CA, USA, Lot# A2604, catalogue# sc-8070) confirmed a > 95% loss of the hypothalamic orexin neurons in all Atx mice and no orexin immunoreactivity in all KO mice (see17,22,25 for detailed description of immunostaining methods). Surgery and EEG/EMG recordings At the time of surgery, mice were 16–19 weeks old and weighed 35 to 40 g. Under anesthesia with ketamine-xylazine (100 and 10 mg/kg ip), we implanted mice with EEG and electromyogram (EMG) electrodes, as described previously.26 Briefly, stainless steel screw electrodes were implanted epidurally over the left frontal cortex (1.5 mm lateral and 1 mm anterior to bregma) and left parietal cortex (1.5 mm lateral and 1.0 mm anterior to lambda) for frontoparietal EEG recordings. EMG signals were acquired by a pair of multistranded stainless steel wires inserted into the neck extensor muscles. A telemetric body temperature (Tb) and locomotor activity (LMA) transmitter (TA-F20, Data Sciences International, St. Paul, MN) was placed in the peritoneal cavity. Transmitters were factory-calibrated to an accuracy of 0.1°C. One week after surgery, mice were transferred to recording cages in a sound-attenuated chamber with a 12:12 h light-dark (LD) cycle (30 lux daylight-type fluorescent tubes with lights on at 07:00), constant temperature (23 ± 1°C), and with food and water available ad libitum. The recording cable was attached to a low torque commutator, fixed above the cages that allowed free movement. Mice were habituated to the cables for 5 days before the experiments and remained connected throughout the study. After acclimating to the LD cycle for 10 days, baseline sleep/wake behavior was recorded (data not shown). Mice were then kept in constant darkness (DD) for 7 days. On days 6 and 7 of DD, we recorded the polysomnogram (EEG/EMG, infrared video), Tb, and LMA for 48-h and then analyzed 24-h recordings after determining the subjective day onset for each individual animal (see below). The EEG/EMG signals were acquired using Grass Model 12 amplifiers (West Warwick, RI) and digitized at 128 Hz. The signals were digitally filtered (EEG: 0.3–30 Hz, EMG: 5–30 Hz) and scored in 10-s epochs as Wake, non-REM (NREM) sleep, or REM sleep using SleepSign (Kissei Comtec, Matsumoto, Japan). S.K. then visually inspected all scoring and made corrections when appropriate. Behavior was scored as cataplexy using the new consensus definition of murine cataplexy.27 Specifically, an epoch was scored as cataplexy when: (1) the mouse had one or more epochs of EEG θ; activity and muscle atonia immediately preceded and followed by active Wake; (2) at least 40 sec of Wake preceded cataplexy to exclude any REM sleep that might follow a brief awakening;28 and (3) the animal was immobile. Whenever behavior met criterion 1, we examined integrated infrared video recordings (SleepSign) to determine if all criteria were fulfilled.27,29 Priod, Pase, and Amplitude Analysis Tb and LMA were recorded at 5-min intervals by an antenna (RPC-1, Data Sciences International) below the recording cage and digitally acquired (Dataquest, Data Sciences International). Analysis of the Tb rhythm over 7 days showed that mice in all groups had the same phase angle of entrainment in LD. To measure the period of the free-running rhythm, we performed a chi-square periodogram analysis (Circadia, Behavioral Cybernetics, Cambridge, MA) on the Tb data of each mouse over the first week of constant darkness. A subset of mice (5 WTAtx, 4 Atx) continued in DD for a total of 27 days, and their free-running rhythms were very similar to that seen in the first week of DD (data not shown). The onset of subjective night was calculated for each animal based on the period of its free running Tb rhythm: subjective night onset = 19:00 + n*(period of Tb - 24 hr), where n is the number of days after onset of constant darkness.12,13 Sleep/wake rhythms in rodents are clearly not sinusoidal and have multiple peaks and abrupt changes near CT0 and CT12 that hinder analysis using techniques such as cosinor analysis. Thus to measure the amplitudes of circadian rhythms of sleep/wakefulness, we used the circadian index (CI) and the nocturnality ratio.30,31 The CIs of Wake, NREM sleep, REM sleep, LMA and Tb were calculated from the following formula: CI = (meannight - meanday)/mean24hr, where meanday is the average over the subjective day, meannight is the average over the subjective night, and mean24hr is the average over the entire day.12,13 CIs are plotted as positive values in which low values indicate little circadian variation. Nocturnality ratios were defined as the percentage of total amount of a behavior (Wake, NREM sleep, REM sleep, LMA, or Tb) occurring during the subjective night. For the nocturnality analysis of Tb, the values above the daily mean were counted. Thus, high nocturnality ratios represent high incidence of the behavior during the night, while ratios close to 50% indicate behavior evenly distributed between subjective day and night. Analysis of REM Sleep Propensity To measure the propensity for REM sleep, we analyzed REM sleep latency, REM sleep bout durations, and the probability of transitioning into REM sleep from NREM sleep. We defined the sleep cycle as beginning at the onset of NREM sleep and as ending at the offset of REM sleep, allowing for brief awakenings no longer than 10 sec. Cycles were excluded from analysis if 1) they lacked REM sleep; 2) the REM sleep episode was only one epoch long (10 sec), followed by NREM sleep; or 3) the NREM sleep episode prior to REM sleep was shorter than 30 sec.26 REM sleep latency was calculated for each sleep cycle and then averaged for the subjective day and night. To analyze the probability of transitioning into REM sleep as a function of NREM sleep bout length, we first calculated the absolute probability of transitioning from NREM into REM sleep for each 10 sec epoch of NREM sleep and calculated the weighted average probability for bins of increasing duration (< 90, 90–180, 180–270, 270–360, and > 360 sec). Statistical Analysis We used ANOVA for repeated measures to analyze changes in each vigilance state as a function of strain (WTAtx, WTKO, Atx, and KO) and time. The same test was used with 2 main factors (strain and day-night cycle) to compare vigilance state parameters. CIs and nocturnality ratios of sleep/wake behavior were compared between strains using unpaired t-tests. To analyze the probability of NREM to REM sleep transitions and the distribution of REM sleep bout durations, we used ANOVA for repeated measures with strain as the between factor and bout length as the repeated measurement. The Bonferroni/Dunn test was used for post hoc comparisons. All results are expressed as means ± SE. Results Impaired Circadian Control of REM Sleep in Atx Mice In constant darkness, the amplitude of the circadian rhythm of REM sleep was much smaller in Atx mice than their WTAtx littermates (t = 3.19, P < 0.01; Figure 2A). Atx mice had nearly half (41%) of their total amount of REM sleep time during the subjective night; a considerably higher proportion than in WTAtx mice (26%) (t = 3.19, P < 0.01; Figure 2B). This reduction in circadian rhythmicity was due to a near doubling in the amount of REM sleep during the subjective night (F =1,14 8.09, P < 0.05; Table 1). This increase was still apparent when REM sleep was viewed as a percentage of total sleep time (TST, F =1,14 15.78, P < 0.01; Figure 3), demonstrating that the increase in REM sleep was not a consequence of more sleep in general. Atx mice had less REM sleep in the first 2 h of the subjective night, compared to the rest of the night, probably due to displacement of REM sleep by the increased amounts of Wake during this interval (Figure 1). Figure 1 Open in new tabDownload slide In constant darkness, the hourly amounts of Wake (A) and NREM sleep (B) are similar in Atx (n = 8) and WTAtx (n = 8) mice. However, Atx mice have more REM sleep (C) than their WTAtx littermates during the subjective night. Nearly all cataplexy (D) occurs during the subjective night in Atx mice. *P < 0.05 compared to WTAtx Figure 1 Open in new tabDownload slide In constant darkness, the hourly amounts of Wake (A) and NREM sleep (B) are similar in Atx (n = 8) and WTAtx (n = 8) mice. However, Atx mice have more REM sleep (C) than their WTAtx littermates during the subjective night. Nearly all cataplexy (D) occurs during the subjective night in Atx mice. *P < 0.05 compared to WTAtx Figure 2 Open in new tabDownload slide Atx mice have little circadian variation in REM sleep rhythm, indicated by low circadian index (A) and a nocturnality ratio (B) close to 50%. In contrast, the circadian rhythms of Wake, NREM sleep, Tb and LMA are preserved in Atx mice. The circadian index is normalized to the mean circadian amplitude of WTAtx mice (100%). **P < 0.01 compared to WTAtx Figure 2 Open in new tabDownload slide Atx mice have little circadian variation in REM sleep rhythm, indicated by low circadian index (A) and a nocturnality ratio (B) close to 50%. In contrast, the circadian rhythms of Wake, NREM sleep, Tb and LMA are preserved in Atx mice. The circadian index is normalized to the mean circadian amplitude of WTAtx mice (100%). **P < 0.01 compared to WTAtx Figure 3 Open in new tabDownload slide During the subjective night, Atx mice have an increased amount of REM sleep as a percentage of total sleep time (TST) (A) demonstrating that more REM sleep in these mice is not a consequence of more sleep in general. The average REM sleep latencies were shorter in both Atx and orexin KO mice than in WT littermates (C, D). **P < 0.01 compared to WTAtx or WTKO. Figure 3 Open in new tabDownload slide During the subjective night, Atx mice have an increased amount of REM sleep as a percentage of total sleep time (TST) (A) demonstrating that more REM sleep in these mice is not a consequence of more sleep in general. The average REM sleep latencies were shorter in both Atx and orexin KO mice than in WT littermates (C, D). **P < 0.01 compared to WTAtx or WTKO. Table 1 Vigilance State Parameters Recorded from Orexin/Ataxin-3 Transgenic (Atx), Orexin Knockout (KO) and their Wild-Type Littermate Control (WT) Mice Variate . Subjective Day . Subjective Night . . . WTAtx . Atx . WTKO . KO . WTAtx . Atx . WTKO . KO . Wake Total time (min) 242.4 ± 14.1 262.5 ± 8.7 302.1 ± 10.6 261.0 ± 9.0 438.7 ± 11.3 433.1 ± 9.8 421.4 ± 16.7 417.2 ± 14.3 Mean duration (sec) 109 ± 9 98 ± 3 152 ± 9 93 ± 6** 248 ± 16 175 ± 10** 252 ± 25 143 ± 12** Number of bouts 134 ± 4 160 ± 5** 121 ± 5 170 ± 6** 108 ± 5 150 ± 7** 104 ± 6 178 ± 10** NREM sleep Total time (min) 429.0 ± 13.1 404.7 ± 9.5 372.7 ± 9.1 401.4 ± 8.8* 263.5 ± 10.1 235.4 ± 7.6* 275.9 ± 14.2 245.5 ± 13.9 Mean duration (sec) 183 ± 5 149 ± 7** 180 ± 7 133 ± 5** 144 ± 8 100 ± 3** 158 ± 8 95 ± 3** Number of bouts 141 ± 4 164 ± 5** 125 ± 5 181 ± 9** 111 ± 6 141 ± 7** 106 ± 7 157 ± 14** REM sleep Total time (min) 48.6 ± 2.8 48.2 ± 2.3 45.2 ± 2.4 49.7 ± 3.7 17.8 ± 2.9 33.8 ± 3.0** 22.7 ± 2.7 23.8 ± 3.7 Mean duration (sec) 59 ± 3 53 ± 2 54 ± 4 36 ± 2** 40 ± 4 49 ± 3 56 ± 5 43 ± 4 Number of bouts 50 ± 3 55 ± 4 51 ± 4 80 ± 4** 26 ± 3 42 ± 4** 24 ± 3 35 ± 7 Cataplexy Total time (min) 0 4.6 ± 1.0 0 8.0 ± 2.3 0 17.7 ± 2.5 0 33.3 ± 5.0 Mean duration (sec) - 68 ± 4 - 80 ± 14 - 67 ± 6 - 78 ± 5 Number of bouts 0 4 ± 1 0 7 ± 2 0 17 ± 3 0 26 ± 4 Tb (°C) 36.3 ± 0.3 35.9 ± 0.1 36.0 ± 0.0 36.0 ± 0.0 37.5 ± 0.2 37.2 ± 0.0 37.0 ± 0.1 37.5 ± 0.0** Variate . Subjective Day . Subjective Night . . . WTAtx . Atx . WTKO . KO . WTAtx . Atx . WTKO . KO . Wake Total time (min) 242.4 ± 14.1 262.5 ± 8.7 302.1 ± 10.6 261.0 ± 9.0 438.7 ± 11.3 433.1 ± 9.8 421.4 ± 16.7 417.2 ± 14.3 Mean duration (sec) 109 ± 9 98 ± 3 152 ± 9 93 ± 6** 248 ± 16 175 ± 10** 252 ± 25 143 ± 12** Number of bouts 134 ± 4 160 ± 5** 121 ± 5 170 ± 6** 108 ± 5 150 ± 7** 104 ± 6 178 ± 10** NREM sleep Total time (min) 429.0 ± 13.1 404.7 ± 9.5 372.7 ± 9.1 401.4 ± 8.8* 263.5 ± 10.1 235.4 ± 7.6* 275.9 ± 14.2 245.5 ± 13.9 Mean duration (sec) 183 ± 5 149 ± 7** 180 ± 7 133 ± 5** 144 ± 8 100 ± 3** 158 ± 8 95 ± 3** Number of bouts 141 ± 4 164 ± 5** 125 ± 5 181 ± 9** 111 ± 6 141 ± 7** 106 ± 7 157 ± 14** REM sleep Total time (min) 48.6 ± 2.8 48.2 ± 2.3 45.2 ± 2.4 49.7 ± 3.7 17.8 ± 2.9 33.8 ± 3.0** 22.7 ± 2.7 23.8 ± 3.7 Mean duration (sec) 59 ± 3 53 ± 2 54 ± 4 36 ± 2** 40 ± 4 49 ± 3 56 ± 5 43 ± 4 Number of bouts 50 ± 3 55 ± 4 51 ± 4 80 ± 4** 26 ± 3 42 ± 4** 24 ± 3 35 ± 7 Cataplexy Total time (min) 0 4.6 ± 1.0 0 8.0 ± 2.3 0 17.7 ± 2.5 0 33.3 ± 5.0 Mean duration (sec) - 68 ± 4 - 80 ± 14 - 67 ± 6 - 78 ± 5 Number of bouts 0 4 ± 1 0 7 ± 2 0 17 ± 3 0 26 ± 4 Tb (°C) 36.3 ± 0.3 35.9 ± 0.1 36.0 ± 0.0 36.0 ± 0.0 37.5 ± 0.2 37.2 ± 0.0 37.0 ± 0.1 37.5 ± 0.0** Total time spent in each state, mean duration, number of bouts and Tb over the subjective day (rest) and night (active) periods. Results shown as mean ± SEM. Significant differences (repeated measures ANOVA) between Atx or KO and their WT littermates are indicated with asterisks * (P < 0.05;) ** (P < 0.01). Open in new tab Table 1 Vigilance State Parameters Recorded from Orexin/Ataxin-3 Transgenic (Atx), Orexin Knockout (KO) and their Wild-Type Littermate Control (WT) Mice Variate . Subjective Day . Subjective Night . . . WTAtx . Atx . WTKO . KO . WTAtx . Atx . WTKO . KO . Wake Total time (min) 242.4 ± 14.1 262.5 ± 8.7 302.1 ± 10.6 261.0 ± 9.0 438.7 ± 11.3 433.1 ± 9.8 421.4 ± 16.7 417.2 ± 14.3 Mean duration (sec) 109 ± 9 98 ± 3 152 ± 9 93 ± 6** 248 ± 16 175 ± 10** 252 ± 25 143 ± 12** Number of bouts 134 ± 4 160 ± 5** 121 ± 5 170 ± 6** 108 ± 5 150 ± 7** 104 ± 6 178 ± 10** NREM sleep Total time (min) 429.0 ± 13.1 404.7 ± 9.5 372.7 ± 9.1 401.4 ± 8.8* 263.5 ± 10.1 235.4 ± 7.6* 275.9 ± 14.2 245.5 ± 13.9 Mean duration (sec) 183 ± 5 149 ± 7** 180 ± 7 133 ± 5** 144 ± 8 100 ± 3** 158 ± 8 95 ± 3** Number of bouts 141 ± 4 164 ± 5** 125 ± 5 181 ± 9** 111 ± 6 141 ± 7** 106 ± 7 157 ± 14** REM sleep Total time (min) 48.6 ± 2.8 48.2 ± 2.3 45.2 ± 2.4 49.7 ± 3.7 17.8 ± 2.9 33.8 ± 3.0** 22.7 ± 2.7 23.8 ± 3.7 Mean duration (sec) 59 ± 3 53 ± 2 54 ± 4 36 ± 2** 40 ± 4 49 ± 3 56 ± 5 43 ± 4 Number of bouts 50 ± 3 55 ± 4 51 ± 4 80 ± 4** 26 ± 3 42 ± 4** 24 ± 3 35 ± 7 Cataplexy Total time (min) 0 4.6 ± 1.0 0 8.0 ± 2.3 0 17.7 ± 2.5 0 33.3 ± 5.0 Mean duration (sec) - 68 ± 4 - 80 ± 14 - 67 ± 6 - 78 ± 5 Number of bouts 0 4 ± 1 0 7 ± 2 0 17 ± 3 0 26 ± 4 Tb (°C) 36.3 ± 0.3 35.9 ± 0.1 36.0 ± 0.0 36.0 ± 0.0 37.5 ± 0.2 37.2 ± 0.0 37.0 ± 0.1 37.5 ± 0.0** Variate . Subjective Day . Subjective Night . . . WTAtx . Atx . WTKO . KO . WTAtx . Atx . WTKO . KO . Wake Total time (min) 242.4 ± 14.1 262.5 ± 8.7 302.1 ± 10.6 261.0 ± 9.0 438.7 ± 11.3 433.1 ± 9.8 421.4 ± 16.7 417.2 ± 14.3 Mean duration (sec) 109 ± 9 98 ± 3 152 ± 9 93 ± 6** 248 ± 16 175 ± 10** 252 ± 25 143 ± 12** Number of bouts 134 ± 4 160 ± 5** 121 ± 5 170 ± 6** 108 ± 5 150 ± 7** 104 ± 6 178 ± 10** NREM sleep Total time (min) 429.0 ± 13.1 404.7 ± 9.5 372.7 ± 9.1 401.4 ± 8.8* 263.5 ± 10.1 235.4 ± 7.6* 275.9 ± 14.2 245.5 ± 13.9 Mean duration (sec) 183 ± 5 149 ± 7** 180 ± 7 133 ± 5** 144 ± 8 100 ± 3** 158 ± 8 95 ± 3** Number of bouts 141 ± 4 164 ± 5** 125 ± 5 181 ± 9** 111 ± 6 141 ± 7** 106 ± 7 157 ± 14** REM sleep Total time (min) 48.6 ± 2.8 48.2 ± 2.3 45.2 ± 2.4 49.7 ± 3.7 17.8 ± 2.9 33.8 ± 3.0** 22.7 ± 2.7 23.8 ± 3.7 Mean duration (sec) 59 ± 3 53 ± 2 54 ± 4 36 ± 2** 40 ± 4 49 ± 3 56 ± 5 43 ± 4 Number of bouts 50 ± 3 55 ± 4 51 ± 4 80 ± 4** 26 ± 3 42 ± 4** 24 ± 3 35 ± 7 Cataplexy Total time (min) 0 4.6 ± 1.0 0 8.0 ± 2.3 0 17.7 ± 2.5 0 33.3 ± 5.0 Mean duration (sec) - 68 ± 4 - 80 ± 14 - 67 ± 6 - 78 ± 5 Number of bouts 0 4 ± 1 0 7 ± 2 0 17 ± 3 0 26 ± 4 Tb (°C) 36.3 ± 0.3 35.9 ± 0.1 36.0 ± 0.0 36.0 ± 0.0 37.5 ± 0.2 37.2 ± 0.0 37.0 ± 0.1 37.5 ± 0.0** Total time spent in each state, mean duration, number of bouts and Tb over the subjective day (rest) and night (active) periods. Results shown as mean ± SEM. Significant differences (repeated measures ANOVA) between Atx or KO and their WT littermates are indicated with asterisks * (P < 0.05;) ** (P < 0.01). Open in new tab To determine whether the reduction in REM sleep rhythmicity was caused by orexin deficiency, we performed the same analyses in orexin KO mice and their WTKO littermates. In contrast to the Atx mice, the amounts and timing of REM sleep in orexin KO mice were very similar to WTKO littermates (Table 1). This was true for the absolute amounts of REM sleep as well as REM sleep as a percent of total sleep time (Figure 3). In contrast, the circadian rhythms of Wake and NREM sleep were undisturbed in Atx and KO mice. The hourly amounts of Wake and NREM sleep were essentially normal, though the duration of Wake and NREM sleep bouts was much shorter in both Atx and KO mice than in WTAtx and WTKO mice, as reported previously.23,32 Cataplexy showed robust circadian variation in both Atx and KO mice, with nearly all cataplexy occurring during the subjective night. This was true for the absolute amounts of cataplexy as well as cataplexy as a percent of Wake time, indicating that circadian timing of cataplexy is not directly linked to the distribution of Wake (Supplemental Figure 1). Increased REM Sleep Propensity in Atx Mice During the Subjective Night To identify factors that contribute to the increase in REM sleep during the dark period, we examined REM sleep architecture in detail. Both Atx and KO mice had REM sleep latencies 30% to 40% shorter than their WTAtx and WTKO littermates (F1,14= 29.07, P < 0.01 and F1,12= 42.22, P < 0.01, respectively; Figure 3). In addition, Atx mice were more likely to transition into REM sleep than WTAtx, WTKO, or orexin KO mice. In WTAtx and WTKO mice, the probability of entering REM sleep gradually rose across the duration of NREM sleep, but Atx mice had a much higher probability of entering REM sleep at any time during a NREM sleep episode (F1,14 = 8.30, P < 0.05; Figure 4). Interestingly, orexin KO mice had generally normal probabilities of entering REM sleep, suggesting that the frequent transitions into REM sleep in Atx mice are not simply due to orexin deficiency. Figure 4 Open in new tabDownload slide In contrast to orexin KO mice (B, D), Atx mice have a generally higher probability of entering REM sleep (A) and have longer bouts of REM sleep (C) than their wild-type littermates during the subjective night (active period) suggesting that the orexin neurons may control the initiation and maintenance of REM sleep during the active period. *P < 0.05, **P < 0.01 compared to WTAtx or WTKO. Figure 4 Open in new tabDownload slide In contrast to orexin KO mice (B, D), Atx mice have a generally higher probability of entering REM sleep (A) and have longer bouts of REM sleep (C) than their wild-type littermates during the subjective night (active period) suggesting that the orexin neurons may control the initiation and maintenance of REM sleep during the active period. *P < 0.05, **P < 0.01 compared to WTAtx or WTKO. Atx mice also produced more bouts and longer bouts of REM sleep. During the subjective night, Atx mice had about twice as many long bouts (> 20–30 sec) of REM sleep as WTAtx littermates (F1,12 = 6.95, P < 0.05; Figure 4), and the mean duration of REM sleep bouts was increased by about 20% (Table 1). In contrast, the durations of REM sleep bouts appeared roughly normal in KO mice, with no increase in long REM sleep bouts and a slightly reduced mean duration of REM sleep bouts. These findings demonstrate that two main factors contribute to the increased REM sleep of Atx mice: a higher probability of entering REM sleep, and better maintenance of REM sleep bouts than WTAtx mice. Preserved Fundamental Circadian Rhythmicity in DD To determine whether this reduction in the circadian rhythm of REM sleep was caused by a general decrease in circadian rhythmicity, we analyzed the periods of the Tb rhythms. Both WTAtx and Atx mice had robust free-running circadian Tb rhythms in DD with periods significantly shorter than 24.0 h (t = 3.7, P < 0.01; t = 2.6, P < 0.05, respectively). The mean periods of the Tb rhythms (23.92 ± 0.02 vs. 23.88 ± 0.05; t = 0.67, P = 0.5), as well as the amplitudes of the circadian rhythms of Tb (t = 0.69, P = 0.5) and LMA (t = 0.35, P = 0.7) were very similar in WTAtx and Atx mice, suggesting that even in the absence of the orexin neurons, fundamental circadian rhythmicity is preserved. In mice with mutations in clock regulatory genes, it can take several weeks for rhythms to fully disappear,33 so we maintained a subset of mice (5 WTAtx, 4 Atx) in DD for 27 days. Their sleep/wake behavior and free-running rhythms were very similar to that seen after 6 days of DD (data not shown). Discussion These results indicate that the orexin neurons are necessary for the circadian suppression of REM sleep during the active period. Specifically, we found that in constant darkness, Atx mice lacking the orexin neurons had much less circadian variation in REM sleep than their WTAtx littermates whereas orexin ligand KO mice had a normal rhythm of REM sleep. The reduction in the REM sleep rhythm in Atx mice was due to a near doubling in the amount of REM sleep during the subjective night related to a higher probability of transitioning into REM sleep and longer bouts of REM sleep. Since the circadian rhythms of Tb, LMA, and Wake were normal, it is likely that the circadian clock itself and the clock effector mechanisms responsible for timing wakefulness are intact in both Atx and KO mice. Our results are in accord with and build upon prior studies of narcoleptic rodents and humans. The first studies of Atx and orexin KO mice as well as orexin deficient Atx rats described an increase in REM sleep during the dark (active) period,22,23,32,34,35 but these studies were limited in that they did not distinguish between REM sleep and cataplexy. A recent, detailed analysis that scored REM sleep and cataplexy separately revealed that Atx mice had twice the normal number of NREM to REM sleep transitions during the night and slightly longer REM sleep bouts.32 However, light/dark cycles can influence sleep patterns and mask any underlying defects in circadian regulation,36,37 and no prior studies examined orexin neuron deficient animals under free running conditions. In a study of people with narcolepsy, Dantz and colleagues examined the circadian control of sleep using a forced desynchrony protocol in which subjects had an opportunity to sleep for 30 minutes every 90 minutes over a 3-day period.1 They found that narcoleptic subjects had much less circadian variation in REM sleep than controls, but with such a short sleep period, many control subjects had difficulty obtaining enough REM sleep and had substantial rebound REM sleep on the subsequent recovery day. Despite these limitations, these studies, along with our new observations suggest that the orexin neurons are necessary for the circadian control of REM sleep. REM sleep is clearly under strong circadian and homeostatic control, but the nature of this control is controversial.1,38–44 Specifically, it is unclear whether the circadian variation in REM sleep is due to active promotion of REM sleep during the rest period; inhibition of REM sleep during the active period; or passive gating of REM sleep by competing arousal states. Wurts and colleagues hypothesized that REM sleep is actively promoted by the SCN during the rest period because SCN-lesioned rats made fewer attempts to enter REM sleep after REM sleep deprivation than unlesioned controls.43 One might expect that less active promotion would result in less REM sleep overall, but the SCN-lesioned rats had normal amounts of REM sleep during baseline recordings.43 In our study, orexin neuron deficiency resulted in an increased amount of REM sleep during the active period with no change in REM sleep during the rest period. Therefore, we propose that circadian regulation of REM sleep is achieved, at least in part, by suppression of REM sleep during the active period by the orexin neurons. This hypothesis is supported by the anatomic observations that orexin neurons receive direct and indirect projections from the SCN and send projections to many state-regulatory nuclei of the brain including many regions that suppress REM sleep.11–16 Furthermore, the orexin neurons are most active during wakefulness and relatively silent during sleep45–48 and selective stimulation of the orexin neurons is sufficient to trigger awakenings from NREM and REM sleep.49 These data together with our results suggest that the orexin neurons mediate the circadian timing of REM sleep by suppressing REM sleep during the active period, though it remains possible that other mechanisms promote REM sleep during the rest period. In contrast to Atx mice, we found that orexin KO mice had normal circadian rhythms of REM sleep, as reported previously.26 This difference suggests that the impaired circadian control of REM sleep in Atx mice is not simply due to orexin deficiency. The orexin neurons produce other signaling molecules including glutamate and dynorphin,8,24,50 and even in the absence of orexin, these neurotransmitters may still relay circadian timing signals that suppress REM sleep during the active period. The synergistic effects of orexin and dynorphin have been demonstrated in the wake-promoting neurons of the tuberomammillary nucleus (TMN): orexin directly excites TMN neurons and dynorphin disinhibits TMN neurons by presynaptically inhibiting GABAergic inputs.50 Similarly, brain regions that inhibit REM sleep (including the ventrolateral periaqueductal grey, lateral pontine tegmentum, locus coeruleus and dorsal raphe) receive excitatory inputs from the orexin neurons and inhibitory inputs from sleep-promoting neurons in the ventrolateral preoptic area.51–53 We speculate that orexins excite neurons that inhibit REM sleep, and dynorphin may enhance this effect by inhibiting GABAergic inputs from sleep-promoting brain sites. Together, the synergistic effects of these neuropeptides would strongly suppress REM sleep during the active period. These mice provide novel perspectives on the circadian control of sleep and wakefulness, but some aspects of their behavior leave open other interpretations. First, KO mice lack orexin throughout development, and they may have more opportunity for developmental compensation than Atx mice in which the orexin neurons are lost postnatally. These compensatory changes may contribute to the milder REM sleep phenotype in orexin KO mice. In addition, it is possible that both Atx and KO mice have poor circadian suppression of REM sleep during the active period, but orexin KO mice express this as partial transitions into cataplexy whereas Atx mice are more prone towards complete transitions into REM sleep. Last, disinhibition of REM sleep in Atx mice could mask the REM sleep rhythm. Though this could be caused by abnormal REM sleep homeostasis, this seems unlikely as Atx mice had normal amounts of REM sleep during the subjective day. Additional studies, perhaps using selective REM sleep deprivation in narcoleptic patients, may help clarify whether the homeostatic control of REM sleep is abnormal in narcolepsy. In addition to promoting wakefulness and regulating REM sleep, the orexin neurons increase autonomic tone, boost metabolism, and enhance feeding, reward-seeking and other motivated behaviors.23,54–58 In fact, many researchers view the orexin neurons as playing a central role in coordinating these functions so that an animal is alert and energetic when engaged in the active behaviors of wakefulness.59,60 Our finding that the orexin neurons are necessary for the circadian control of REM sleep fits well with this perspective. An animal would certainly be exposed to attack or injury during the atonia and unconsciousness of REM sleep, and by suppressing REM sleep during the active period, the orexin neurons may help ensure that this vulnerable state does not intrude into wakefulness. Acknowledgments This research was made possible by grants from Takeda Pharmaceuticals North America and the National Institute of Health (NS055367, HL60292). Elizabeth Clain provided invaluable help with data analysis. We are grateful for the insightful comments and suggestions provided by Elizabeth Klerman, Ralph Mistlberger, Janet Mullington, and David Weaver. References 1. Dantz B , Edgar DM, Dement WC Circadian rhythms in narcolepsy: studies on a 90 minute day . Electroencephalogr Clin Neurophysiol 1994 ; 90 : 24 – 35 . Google Scholar Crossref Search ADS PubMed WorldCat 2. Selbach O , Haas HL Hypocretins: the timing of sleep and waking . Chronobiol Int 2006 ; 23 : 63 – 70 . Google Scholar Crossref Search ADS PubMed WorldCat 3. Broughton R , Krupa S, Boucher B, Rivers M, Mullington J Impaired circadian waking arousal in narcolepsy-cataplexy . Sleep Res Online 1998 ; 1 : 159 – 65 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 4. 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Cholinergic Modulation of GABAergic and Glutamatergic Transmission in the Dorsal Subcoeruleus: Mechanisms for REM Sleep Control

Heister, David S.; Hayar, Abdallah; Garcia-Rill, Edgar

2009 SLEEP

doi: 10.1093/sleep/32.9.1135pmid: 19750918

AbstractStudy Objectives:Dorsal subcoeruleus (SubCD) neurons are thought to promote PGO waves and to be modulated by cholinergic afferents during REM sleep. We examined the differential effect of the cholinergic agonist carbachol (CAR) on excitatory and inhibitory postsynaptic currents (PSCs), and investigated the effects of CAR on SubCD neurons during the developmental decrease in REM sleep.Design:Whole-cell patch clamp recordings were conducted on brain-stem slices of 7- to 20-day-old rats.Measurements and Results:CAR acted directly on 50% of SubCD neurons by inducing an inward current, via both nicotinic and muscarinic M1 receptors. CAR induced a potassium mediated outward current via activation of M2 muscarinic receptors in 43% of SubCD cells. Evoked stimulation established the presence of NMDA, AMPA, GABA, and glycinergic PSCs in the SubCD. CAR was found to decrease the amplitude of evoked EPSCs in 31 of 34 SubCD cells, but decreased the amplitude of evoked IPSCs in only 1 of 13 SubCD cells tested. Spontaneous EPSCs were decreased by CAR in 55% of cells recorded, while spontaneous IPSCs were increased in 27% of SubCD cells. These findings indicate that CAR exerts a predominantly inhibitory role on fast synaptic glutamatergic activity and a predominantly excitatory role on fast synaptic GABAergic/glycinergic activity in the SubCD.Conclusion:We hypothesize that during REM sleep, cholinergic “REM-on” neurons that project to the SubCD induce an excitation of inhibitory interneurons and inhibition of excitatory events leading to the production of coordinated activity in SubCD projection neurons. The coordination of these projection neurons may be essential for the production of REM sleep signs such as PGO waves.

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Excessive Muscle Activity Increases Over Time in Idiopathic REM Sleep Behavior Disorder

Iranzo, Alex; Ratti, Pietro Luca; Casanova-Molla, Jordi; Serradell, Mónica; Vilaseca, Isabel; Santamaría, Joan

2009 SLEEP

doi: 10.1093/sleep/32.9.1149pmid: 19750919

AbstractStudy Objectives:Rapid eye movement (REM) sleep behavior disorder (RBD) is characterized by excessive electromyographic (EMG) activity due to dysfunction of the brainstem structures modulating REM sleep atonia. Patients with idiopathic RBD often develop a neurodegenerative disease, such as Parkinson disease, over the years, suggesting progression of an underlying pathologic process in the brainstem. It is unknown if the excessive EMG activity in REM sleep changes over time in patients with idiopathic RBD.Setting:University hospital sleep disorders center.Participants:Eleven patients with idiopathic RBD who were studied at baseline and after a mean follow-up of 5 years.Interventions:NA.Measurements and Results:Eleven patients with idiopathic RBD underwent polysomnography (PSG) at the moment of the diagnosis of RBD (PSG1) and after a mean follow-up of 5 years (PSG2). Tonic EMG activity in PSG1 and PSG2 was blindly quantified and compared in the mentalis muscle during REM sleep. Phasic EMG activity in PSG1 and PSG2 was blindly quantified and compared in the mentalis muscle, both biceps brachii, and both anterior tibialis during REM sleep. Patients were 9 men and 2 women with a mean age of 73.2 ± 5.4 years and a mean RBD duration of 10.7 ± 5.3 years at PSG2. In each of the 5 muscles and combination of muscles evaluated, phasic EMG activity was significantly greater in PSG2 than in PSG1 (P < 0.022 in all muscles studied). Mentalis tonic EMG activity increased from 30% to 54% (P = 0.013). No correlation was found between age of the patients and quantity of EMG activity at PSG1 (tonic; P = 0.69, phasic P = 0.89) and at PSG2 (tonic; P = 0.16, phasic; P = 0.42).Conclusion:Excessive tonic and phasic EMG activity during REM sleep increases over time in subjects with idiopathic RBD. This finding suggests that, in subjects with idiopathic RBD, there is an underlying progressive pathologic process damaging the brainstem structures that modulate REM sleep.

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Breast Cancer Patients have Progressively Impaired Sleep-Wake Activity Rhythms during Chemotherapy

Savard, Josée; Liu, Lianqi; Natarajan, Loki; Rissling, Michelle B.; Neikrug, Ariel B.; He, Feng; Dimsdale, Joel E.; Mills, Paul J.; Parker, Barbara A.; Sadler, Georgia Robins; Ancoli-Israel, Sonia

2009 SLEEP

doi: 10.1093/sleep/32.9.1155

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Brain Activation Changes Before and After PAP Treatment in Obstructive Sleep Apnea

Castronovo, Vincenza; Canessa, Nicola; Ferini, Luigi Strambi; Aloia, Mark S.; Consonni, Monica; Marelli, Sara; Iadanza, Antonella; Bruschi, Alice; Falini, Andrea; Cappa, Stefano F.

2009 SLEEP

doi: 10.1093/sleep/32.9.1161pmid: 19750921

journal article

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Upper Airway Collapsibility During REM Sleep in Children with the Obstructive Sleep Apnea Syndrome

Huang, Jingtao; Karamessinis, Laurie R.; Pepe, Michelle E.; Glinka, Stephen M.; Samuel, John M.; Gallagher, Paul R.; Marcus, Carole L.

2009 SLEEP

doi: 10.1093/sleep/32.9.1173pmid: 19750922

AbstractStudy Objectives:In children, most obstructive events occur during rapid eye movement (REM) sleep. We hypothesized that children with the obstructive sleep apnea syndrome (OSAS), in contrast to age-matched control subjects, would not maintain airflow in the face of an upper airway inspiratory pressure drop during REM sleep.Design:During slow wave sleep (SWS) and REM sleep, we measured airflow, inspiratory time, inspiratory time/total respiratory cycle time, respiratory rate, tidal volume, and minute ventilation at a holding pressure at which flow limitation occurred and at 5 cm H2O below the holding pressure in children with OSAS and in control subjects.Setting:Sleep laboratory.Participants:Fourteen children with OSAS and 23 normal control subjects.Results:In both sleep states, control subjects were able to maintain airflow, whereas subjects with OSAS preserved airflow in SWS but had a significant decrease in airflow during REM sleep (change in airflow of 18.58 ± 12.41 mL/s for control subjects vs −44.33 ± 14.09 mL/s for children with OSAS, P = 0.002). Although tidal volume decreased, patients with OSAS were able to maintain minute ventilation by increasing the respiratory rate and also had an increase in inspiratory time and inspiratory time per total respiratory cycle time.Conclusion:Children with OSAS do not maintain airflow in the face of upper-airway inspiratory-pressure drops during REM sleep, indicating a more collapsible upper airway, compared with that of control subjects during REM sleep. However, compensatory mechanisms exist to maintain minute ventilation. Local reflexes, central control mechanisms, or both reflexes and control mechanisms need to be further explored to better understand the pathophysiology of this abnormality and the compensation mechanism.

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Sleep Duration and Obesity in Children: Is the Association Dependent on Age and Choice of the Outcome Parameter?

Bayer, Otmar; Rosario, Angelika Schaffrath; Wabitsch, Martin; von Kries, Rüdiger

2009 SLEEP

doi: 10.1093/sleep/32.9.1183pmid: 19750923

AbstractStudy Objectives:To assess the association between sleep duration in children and different markers of body fat by age and weight status.Design:Nation-wide health survey. Measurement of BMI and body fat percentage (KFA) calculated from weight, height, skin fold thickness, age, and sex. Sleep duration and potential confounding variables were assessed in a parent questionnaire.Setting:N/AParticipants:7767 German resident children from 3 to 10 years of age.Interventions:N/AMeasurements and Results:Prolongation of sleep duration from the lowest to the highest percentile accounted for a similar mean decrease in BMI (−0.235, 95%-CI −0.321; −0.149) and KFA (−0.182, 95% CI −0.271; −0.092) z-scores. The given association is adjusted for confounding variables and did not show a systematic age dependency. The greatest effects of sleep duration were seen for the upper tails of the BMI and KFA distributions, which were about four as high as the lower tails.Conclusions:The association between sleep duration and weight status is of similar size through ages 3 to 10 years. The sleep-associated changes in BMI are likely to be a consequence of higher body fat and primarily affect children whose BMI or KFA is already elevated. These findings favor hormonal pathways nurturing adipose tissue playing a key role in the underlying physiological mechanisms.

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