|Home | About | Journals | Submit | Contact Us | Français|
During sleep, the mammalian CNS undergoes widespread, synchronized slow wave activity (SWA) that directly varies with prior waking duration (Borbely, 1982;Dijk et al., 1990a). When sleep is restricted, an enhanced SWA response follows in the next sleep period. The enhancement of SWA is associated with improved cognitive performance (Huber et al., 2004c), but it is unclear either how the SWA is enhanced or whether SWA is needed to maintain normal cognitive performance. A conditional, CNS knockout of the adenosine receptor, AdoA1R gene, shows selective attenuation of the SWA rebound response to restricted sleep, but sleep duration is not affected. During sleep restriction, wild phenotype animals, express a rebound SWA response and maintain cognitive performance in a working memory task. However, the knockout animals not only show a reduced rebound SWA response but they also fail to maintain normal cognitive function, although this function is normal when sleep is not restricted. Thus, AdoA1R activation is needed for normal rebound SWA, and when the SWA rebound is reduced, there is a failure to maintain working memory function suggesting a functional role for SWA homeostasis.
The need for recovery of lost sleep, the homeostatic sleep response, is considered one of the universal characteristics of sleep (Mignot, 2008). One commonly used measure of this response is slow wave activity (SWA; Dijk et al., 1990). SWA is measured from the electroencephalogram and results from synchronized, neuronal membrane potential fluctuations of populations of cortical and thalamocortical neurons, with a dominant frequency component in the range of 0.5–4.5 Hz (Amzica and Steriade, 1998). Slow wave activity is present across states, but is predominate in the EEG during slow wave sleep (SWS), also called non-Rapid Eye Movement sleep and in this sense, SWS may be considered permissive to the expression of SWA.
The magnitude of SWA is directly correlated with the time spent awake prior to the SWS episode (Franken et al., 2001a) and may be locally increased in a use-dependent manner (Huber et al., 2004b;Vyazovskiy et al., 2004). Thus, SWA is considered a marker for and is thought to be functionally involved in sleep/waking homeostasis (Daan et al., 1984).
Adenosine has been hypothesized to be involved in sleep/waking homeostasis by modulation of SWA. Converging evidence suggest that this SWA modulation results from A1 adenosine receptor (AdoA1R) activation. Adenosine, acting on the AdoA1R, has been shown to decrease cholinergic neuronal activity and to facilitate, at the single cell level, slow oscillations (Rainnie et al., 1994b;Porkka-Heiskanen et al., 1997e;Benington et al., 1995b;Pape, 1992b). Pharmacological blockade of adenosine A1 and A2 receptors by caffeine results in increased arousal (and decreased sleep) in mammals (Fredholm et al., 2005). In rodents, the increased arousal effect may, in large part, be secondary to increased locomotor activity (Lindskog et al., 2002), mediated by the A2AdoR signaling system in the striatum, that is in itself, arousing. However, an AdoA1R mediated action cannot be ruled out despite the evidence that caffeine’s stimulatory action is less marked acting by AdoA1R’s (Huang et al., 2005). Further, the SWA promoting actions of increased endogenous or exogenous adenosine in the cholinergic nuclei (Porkka-Heiskanen et al., 1997d;Portas et al., 1997a) seems most likely to be mediated by AdoA1R’s since AdoA2aR’s have no electrophysiological activity in the cholinergic nuclei, in contrast to AdoA1R’s (Arrigoni et al., 2001a). Thus, the physiological role of AdoA1R’s to increase SWA remains to be resolved.
We have employed conditional AdoA1R knockout mice, using a CAMKII-promoting Cre transgene, to selectively reduce rebound SWA in response to moderate sleep restriction, as a means of assessing mechanisms responsible for this classic homeostatic sleep response. The conditional knockout approach was justified over either the constitutive knockout or the AAV-mediated Cre induction approaches for the following reasons. First, the constitutive deletion of the AdoA1R gene showed a minimal reduction of SWA in mice during the early part of the circadian day (at lights on) when sleep pressure is most likely to be the greatest (Stenberg et al., 2003c), raising the possibility of developmental compensatory effects. These potential effects would be less of a factor with a conditional gene knockout (Tsien et al., 1996a). Second, although localized increases in adenosine are sufficient to increase SWA (Porkka-Heiskanen et al., 1997c;Portas et al., 1997b), this may require activation of pre-synaptic AdoA1R (Arrigoni et al., 2001b;Arrigoni et al., 2005;Brambilla et al., 2005d). A localized AAV-Cre mediated AdoA1R gene deletion will only affect the neurons within the region of transfection, leaving pre-synaptic AdoA1R’s on terminals originating from neurons outside the transfected region unaffected.
Evidence is provided here suggesting that the normal rebound increase in SWA in response to sleep restirction is modulated by AdoA1Rs and that this modulation is associated with normal working memory performance under sleep restriction conditions.
A targeted gene insertion, employing a C57BL6 mouse and embryonic stem cells from 129SvJ strain, was made with loxP sites flanking the AdoA1R gene (Scammell et al., 2003b). AdoA1R gene deletion was induced by crossing these mice with another strain (T50 line) containing a transgene expressing the recombinase, Cre, under the control of a CamKinaseII promoter (Tsien et al., 1996b). The genetic background of the Cre cutter line was also C57BL6. The AdoA1R−/− line was backcrossed a minimum of three times prior to use of offspring for experimentation. The promoter provides regional and developmental specificity of the Cre expression, and, as a result, of the AdoA1R gene deletion.
During development from P10 to P60, the expression pattern of the Cre recombinase becomes less restricted (Luikart et al., 2005;Monteggia et al., 2007a) to include forebrain, diencephalon and brainstem of the CNS as indicated by beta-galactosidase expression in ROSA26 reporter mice (Tsien et al., 1996c) crossed with mice containing the CamKII-Cre transgene (Figure 1).
The expression pattern we observed has been previously reported (Monteggia et al., 2007b), using similar histological techniques as employed in our study. Cre expression was not observed in putative interneurons or in the inhibitory nucleus reticularis of the thalamus. At high power magnification, beta-galactosidase staining was clearly apparent in the nuclei of all the thalamocortical (data not shown), despite its apparent absence of expression in the thalamus in low power micrographs (Figure 1, left column). Beta-galactosidase expression was concentrated in the nuclei of cells in the ROSA26 mouse and this appeared especially to be the case for the thalamic neurons.
We used standard autoradiographic techniques to image S35 labeled mRNA probe for the AdoA1R transcript as described previously (Scammell et al., 2003a). The homozygous “floxed” AdoA1R strain (AdoA1Rf/f) has a wildtype expression pattern for AdoA1R message (Figure 1, middle column). The AdoA1R−/− strain (homozygous for the floxed allele, AdoA1Rf and positive for the CamKII-Cre transgene) shows a loss of AdoA1R expression and this loss was restricted to regions that were positive for both Cre and AdoA1R expression (Figure 1, right column).
Quantitative densitometry indicates that the AdoA1R message is reduced in the AdoA1R−/− strain by over 80% in sleep relevant areas that include the following: 1) in the braintstem, the dorsal pontine tegmentum 2) in the diencephalon, the thalamus, with the exception of the inhibitory nucleus reticularis, and the hypothalamus; 3) in the forebrain, the parietal neocortex. Using the identical AdoA1Rf/f strain, we have previously shown that wherever Cre is expressed, there is an associated loss of AdoA1R dependent electrophysiological responses (Scammell et al., 2003c;Arrigoni et al., 2005).
Adult male_AdoA1Rf/f and AdoA1R−/− mice aged 9–16 weeks were housed singly in standard mouse cages with access to food and water ad libitum. Cages were located in a climate controlled environment with a 12/12 hr light/dark schedule with lights on at 8 a.m. In order to determine sleep/waking activity, EEG and EMG electrodes were surgically implanted. Briefly, mice were anesthetized with isoflurane and placed in a Kopf stereotax (Kopf, Tujunga, CA). The scalp was sheared, cleaned, and incised. Four holes were drilled for EEG electrodes, which consisted of a piece of coated wire capped by a gold amphenol pin on one side (Plastics One, Roanoke, VA) and a small screw on the other. Two electrodes were placed bilaterally over the frontal area (AP +1.1mm, ML +/−1.45mm) and two electrodes were placed bilaterally over the parietal area (AP −3.5mm, ML +/− 1.45mm). Two panel EMG electrodes (Plastics One, Roanoke, VA) were placed bilaterally into the nuchal musculature. The electrode caps were threaded into a 6 pin pedestal (Plastics One, Roanoke, VA) and affixed to the skull with dental acrylic (Fisher Scientific, Pittsburgh, PA). Post surgery, the base of the implant was coated with antibiotic to prevent infection and the animals were given buprinex (0.1 ml, IP) for pain relief. Animals were given 10 days to recover from surgery prior to any experimental manipulations. All experimental procedures were approved by the North Texas Veterans Administration Institutional Animal Care and Use Committees.
After 10 days of recovery from surgical procedures, cages were placed in custom wooden boxes. A lightweight cable (Plastics One, Roanoke, VA) was secured to the implant and to a commutator (Plastics One, Roanoke, VA) located on the ceiling of the box. The commutator allows for relatively free movement and prevents the cable from tangling. Animals were given at least 5 days to acclimate to the cable. Next, animals were moved to cages that were bottomless and suspended about 0.125” above a treadmill (Figure 2). While on the treadmill, the lightweight cable was attached to a counterbalanced lever arm (Instech Laboratories, Plymouth Meeting, PA) that allowed for relatively free movement and prevented tangling. Animals were given 2 days to acclimate to the treadmill environment before baseline recording. Baseline sleep/waking activity was measured for 24 hrs, followed by 48 hrs of sleep restriction. For sleep restriction, the treadmill was engaged for 48 more hrs with a cycle of 4 hrs on (TM on) and 2 hrs off (TM off) for a total of 8 complete 6 hr cycles. This treadmill was remotely controlled by a computer programmed to implement the 6 hr cycles. The treadmill speed was set at 3 cm/sec since this was the slowest speed that reliably eliminated sleep (as assessed using EEG and EMG sleep scoring criteria) throughout the 48 hour restricted sleep period. When the treadmill was moving urine and feces were swept under the cage, the feces dropped onto a trash bag under the belt. The treadmill was cleaned between sets of animals. A camera was placed over the treadmill and connected to a monitor in a separate room to allow remote observation.
A Grass Model 15 data acquisition system (Astro-Med, West Warwick, RI) was used to record EEG/EMG activity. An electrode board (Astor-Med, West Warwick, RI) was used to reference the left frontal lead to the left parietal lead, the right frontal lead to the right parietal lead, and the left nuchal lead to the right nuchal lead for 2 channels of EEG and 1 channel of EMG. EEG and EMG signals were fed from the electrode board to an amplifier and then to a PC. Signals were sampled at 128 Hz, filtered between 0.3 and 100 and amplified. After recording was complete, data was copied to CD and scored offline using Rodent Sleep Scorer (Astro-Med, West Warwick, RI). Epochs were scored in 10–15 sec and assigned into one of three sleep/waking states (figure 3). Waking consists of low amplitude, high frequency EEG and high EMG activity, SWS consists of high amplitude, low frequency EEG with little EMG modulation, and REM consists of low amplitude, desynchronized EEG with occasional muscle twitches on a background of low EMG activity. Rodent Sleep Scorer (Astro-Med, West Warwick, RI) also performed an FFT analysis with a Hamming window function for each epoch. Delta power from 3.0–4.5 Hz was defined as slow wave activity and averaged across all epochs and across all SWS sleep epochs for statistical comparisons across conditions. This delta power range was chosen based on Maret and colleagues findings of an altered SWA power frequency band distribution observed in mice with a mutated retinoic acid receptor beta gene during SWS primarily in the 3.0–4.5 Hz range (Maret et al., 2005c).
A standard 8 arm radial maze protocol was used to assess working memory. The mice used for cognitive testing were not tethered to the recording system, but were otherwise treated in a similar manner to the recorded animals. All animals were weighed daily, maintained at or above 85% of their free feeding weight, and were housed on the treadmill (not moving) from training onward. The radial maze is constructed of clear plastic and placed on a table surface with visual cues from the room readily visible.
The task involved obtaining rewards that were hidden from sight in small cups at the end of each arm. Over 2 weeks of training (2 trials/day) all the animals learned to visit each of the 8 arms only once and rarely made mistakes (average <2 mistake/trial). These observations are similar to other assessments of hippocampal-independent working memory (Winocur, 1982) in mice using a similar radial maze protocol (Schmitt et al., 2003b). Control trials in trained animals using un-baited cups, confirmed that olfactory cues obtained from the reward itself were not needed to locate the correct cup.
Mice had two training sessions per day, a morning session at 8 AM and an afternoon session at 2 PM. At the beginning of each training trial, 8 arms were baited with a small piece of chocolate (Hershey’s Hugs, The Hershey Company, Hershey, PA). Mice were placed into the central hub of the maze and allowed to enter any arm. A revisit error was scored if a mouse traversed more than 1/3 of an arm from which they had already retrieved the chocolate. Mice were removed from the maze after successfully retrieving all 8 chocolate pieces or after a maximum of 10 mins. Training continued until animals reached asymptotic performance for 3 days, after which animals began 2 days of testing, followed by 3 days of recall. Testing procedures were the same as training, with the exception that the treadmill was set to the 6 hr cycle (4 hrs ON, 2 hrs OFF). Recall was the same as training (TM off).
The protocol for the paired associated task was the same as what we have previously employed (Rajji et al., 2006a). Briefly, mice were first shaped for 10 days to dig into a sand-filled cup for a chocolate piece buried in the sand. Animals who failed to retrieve the chocolate rewards on day 10 were excluded from the study. Following shaping, animals were given 2 combinations of odor (X or Y; mixed in sand) and contexts (A or B) and trained to associate one odor (X) with reward in one context (room A) and the other odor (Y) with reward in the other context (room B). Animals were given 8 trials (4 for each of 2 contexts) per day across 11 days. Similar to the 8 arm radial maze procedure, animals were housed on the treadmill (not moving) through training and the TM 6 hr cycle began for testing. During testing, animals were given new odor-context cues to learn. Animals were sleep restricted for 6 days and beginning on day 2, were trained for 5 days (using the same protocol as that used for control conditions with new contexts and scent cues) to acquire new paired associates during the sleep restriction.
During testing on both tasks animals were moved from the treadmill to the task apparatus and placed back on the treadmill following task completion. All trials occurred during the treadmill ON phase.
Statistical analyses were performed using GraphPad Prism (GraphPad Software Inc, La Holla, CA). Group comparisons of sleep time and SWA were made using a Mann Whitney U test. Data is expressed as mean +/− standard error of the mean. For baseline (undisturbed time) sleep/waking time analyses, percent time in waking, SWS, and REM sleep was calculated from 4, 2 hr blocks (matched to the TM off times – 12–2 pm, 6–8 pm, 12–2 am, 6–8 am). Animals showing greater than 90% waking in any 1 of the baseline hours were eliminated from further analysis. Time in SWS over the 24 hr baseline period was calculated for a subset of mice for comparisons of daily SWS time. For SWA analyses, SWA was averaged in 1 hr bins for baseline and both sleep restriction days. For the 8 arm radial maze, the number of revisit errors and latency to complete the task was averaged for the morning and afternoon session. Comparisons were made between the average performance on the last two training days, sleep restriction days, and recall days, along with weight on each of these days. A Wilcoxon matched pairs test was used to compare error rate between baseline and probe conditions within each group. A Mann Whitney U test was used to compare error rate, latency, and weight between groups. For the paired associates task, percent correct on the new context trials during testing was calculated. A 2 way ANOVA was used to compare genotype (AdoA1Rf/f and AdoA1R−/−) and time (trial 1 and trial 5).
The expression of baseline sleep/waking states were not different between genotypes (Figure 3). The AdoA1R−/− mice had a similar percent time in waking (n=5, 47.2 +/− 9.2 %; Figure 3A), SWS (43.9 +/−, 7.9 %; Figure 3B) and REM sleep (8.2 +/− 2.5 %; data not shown) compared with AdoA1Rf/f mice (n=5, waking mean = 50 +/− 8.4 %, SWS mean = 41.4 +/− 6.4 %, REM mean = 8.6 +/− 2.4 %). As previously reported for AdoA1R constitutive gene deletion mutants (Stenberg et al., 2003b), we did not detect a significant phenotype with respect to the percent of total time spent in any one of the three sleep/waking states.
The loss of AdoA1R expression resulted in a decrease of the average SWA power (frequency range of 3.0–4.5Hz), over the baseline recording period (AdoA1Rf/f SWA, 59.3 +/− 2.2 µV2/epoch; AdoA1R−/− SWA, 49.8 +/− 1.1 µV2/epoch; p<0.001; Figure 3C). This genotype difference in SWA was amplified during SWS, the state in which SWA predominates, (AdoA1Rf/f SWS-SWA, 83.6 +/− 2.8 µV2/epoch, AdoA1R−/− SWS-SWA, 69.5 +/− 2.3 µV2/epoch, p<0.001; Figure 3E) and was absent during waking (AdoA1Rf/f waking-SWA, 40.8 +/− 12.5 µV2/epoch, AdoA1R−/− waking-SWA, 37.2 +/− 8.3 µV2/epoch; Figure 3D). The ability to increase SWA from waking to SWS was significantly attenuated by the loss of AdoA1R expression (AdoA1Rf/f, increased SWA by 110+/−6.22%; AdoA1R−/−, 82.1+/−7.96%, p=0.01; Figure 3F). Thus, even under baseline sleep conditions, SWA expression was attenuated during SWS in animals with disrupted AdoA1R expression.
An altered SWA power frequency band distribution was observed in mice with a mutated retinoic acid receptor beta gene during SWS primarily in the 3.0–4.5 Hz range (Maret et al., 2005b). The frequency specific contribution to the power of EEG signal during SWS was assessed for AdoA1R−/− mutants and AdoA1Rf/f mice. No change in the power distribution in the SWA frequency range of 0.5–15.0Hz between the two groups was apparent (Figure 4).
The reduced SWA in the AdoA1R−/− mice may have resulted from aberrant homeostatic control in relation to waking duration. However, the AdoA1R−/− mice had spontaneous waking periods of similar length as the waking periods of AdoA1Rf/f mice (average duration of waking for AdoA1Rf/f, 2.3 +/− 0.4 min, AdoA1R−/−, 2.1 +/− 0.1 min). They nevertheless expressed significantly less SWA during the ensuing SWS periods (Figure 3E). The magnitude of the SWA power is closely correlated with waking duration (Franken et al., 2001b;Dijk et al., 1990b). If these correlations are causally related, then our observations of the genotype-dependent difference in SWA are consistent with an altered, less effective SWA-inducing feedback.
To test for a genotype-dependent change in the relationship between a controlled waking duration (i.e. forced waking) and SWA, both genotypes of mice (n=7/genotype) were maintained awake on a slowly moving treadmill for a four hour period, followed by a two hour undisturbed period (treadmill was turned off). Figure 5A shows an example of raw EEG signals from both groups during baseline and following enforced waking conditions. Both genotypes responded to the enforced waking with increased SWA during the two hour undisturbed period but the magnitude of the SWA during SWS was significantly greater for the AdoA1Rf/f genotype compared to the AdoA1R−/− group (AdoA1Rf/f, 69 +/− 0.6 µV2/epoch; AdoA1R−/−, 59.3 +/− 3.0 µV2/epoch, p=0.01; Figure 5B). However, there was no difference in percent time in SWS between genotypes (AdoA1Rf/f, 45.5 +/− 4%; AdoA1R−/−, 50.2 +/− 5.8%). This indicates an adenosine mediated role in the rebound SWA response to prolonged waking acts through the AdoA1R.
In mice, four hours of sleep deprivation did not result in any significant change in SWS time but SWA during SWS was greatly enhanced. In order to test whether chronic sleep restriction in mice can be functionally compensated by a rebound SWA increase in an AdoA1R dependent manner, SWS time and SWA were assessed in both genotypes under conditions of chronic sleep restriction.
The opportunity to sleep was restricted to a 2 hr period per 6 hour cycle by enforcing waking for 4 hrs with a slowly moving treadmill. The 6 hr cycle (4hrs TM on & 2hrs TM off) was repeated for 48 hrs (8 complete cycles). Notably, there was no change in SWS time during spontaneous sleep periods (baseline) compared to the same time during TM off for either AdoA1Rf/f mice (n=5; 44.9 +/− 2.3 % baseline; 49.2 +/− 3.2 % restricted sleep TM off) or for AdoA1R−/− mice (n=5; 44.6 +/− 2.2 % baseline; 49.9 +/− 4.6 % restricted sleep TM off), nor was there any difference in SWS time between genotypes. Mice, of either genotype, spent 10.1 hours/day in SWS under baseline conditions, while under the sleep restriction paradigm only 3.5 hrs per day was spent in SWS – a 65% reduction in SWS time.
In contrast to SWS time, SWA recorded during the 2 hour TM off phase, compared to the baseline sleep day (recorded at the same circadian time), showed an increase over baseline magnitude for both genotypes. SWA was significantly lower for the AdoA1R−/− mice on every cycle during the TM off phases (AdoA1R−/− average = 51.3 +/− 2.1 µV2/epoch; average AdoA1Rf/f = 70.8 +/− 2.4 µV2/epoch; p<0.001; Figure 6A,B). Thus, during chronic restricted sleep, SWA, regardless of state, was attenuated in an AdoA1R-dependent manner with no change in SWS time.
Since SWA predominates during SWS, SWA power recorded during SWS during sleep restriction, was compared across genotype. The largest SWA difference between genotypes was observed under these conditions (AdoA1Rf/f = 106.2 +/− 3.4 µV2/epoch; AdoA1R−/− = 65.9 +/−3.2µV2/epoch), showing ~30µV2/epoch difference (p<0.0001; Figure 6 C,D). The percent change in SWA from the TM on phase when the animals were awake to SWS during the TM off phase (calculated as [SWS_SWA TM off – SWA TM on] / SWA TM on) was, for AdoA1Rf/f, 254 +/− 11 %; for AdoA1R−/−, 139 +/− 12.3 %; significant at p<0.0002 (Figure 7A). This suggests the AdoA1R is needed for the full expression of the rebound SWA response during sleep restriction.
These observations suggest that the AdoA1R may be particularly important to the increase in SWA from waking to SWS when sleep time is restricted, as compared to our baseline unrestricted conditions. Indeed, AdoA1Rf/f animals showed a significant increase in SWS SWA following forced waking compared to baseline SWS SWA (baseline = 83.6 +/− 2.8 µV2/epoch, TM off = 106.2 +/− 4.8 µV2/epoch, p<0.001; Figure 3E and and6D),6D), whereas there was no significant increase in SWS SWA in AdoA1R−/− animals (baseline = 69.5 +/− 2.3 µV2/epoch, TM off = 65.9 +/− 3.9 µV2/epoch).
We compared the increase in SWA activity from waking to SWS under baseline conditions (Figure 3F) to the increase in SWA from waking to SWS under sleep restricted conditions (Figure 7A). Notably, AdoA1Rf/f mice were able to further increase SWA from waking to SWS in sleep restricted conditions compared to baseline conditions. This further increase was significantly greater than that observed with mice with disrupted AdoA1R activity (AdoA1Rf/f, 42.3 +/− 12.8 %, AdoA1R−/− , 9.81 +/− 7.37 %, p=0.005; Figure 7B). This change was calculated as follows: [increase of SWA_restricted - increase SWA_baseline] / increase of SWA_baseline. The findings are consistent with a ceiling effect on SWA during SWS in AdoA1R−/− mice, suggesting that further enhancement of SWA in sleep restricted conditions requires the AdoA1R.
Finally, we compared the percent change in SWA during SWS from baseline to sleep restriction under acute (1, 6 hr cycle; Figure 5) and chronic (8, 6 hr cycles; Figure 6) sleep restriction. There was no difference in percent change between acute and chronic sleep restriction in either group (data not shown).
These data suggest the AdoA1R is necessary for the compensatory SWS-specific SWA rebound that follows sleep restriction. This may indicate the possibility of functional implications for the compensatory SWA increase.
A recent study suggests that an increase in SWA during SWS follows new learning and improved performance is correlated with this increase in SWA (Huber et al., 2004a). Since the AdoA1R−/− mice show a selective deficit in the SWA response to restricted sleep, we examined their performance on a working memory task in comparison with AdoA1Rf/f mice, before, during and after 48 hours of sleep restriction. Ten animals/genotype were examined on a working memory task. These animals were not connected to the EEG/EMG recording system.
There was no difference in working memory performance between genotypes prior to testing (AdoA1Rf/f = 1.6+/−0.3 revisit errors/trial; AdoA1R−/− = 1.6+/−0.3 revisit errors/trial; Figure 8A). The two genotypes were then sleep restricted on the treadmill with the 4 hr TM on/2 hr TM off protocol for three full cycles (18hr). At the beginning of the 4th cycle, they were tested on the 8-arm maze working memory task (during the time when waking was enforced). They were then returned to the sleep restriction protocol in time to begin the 2 hr TM off phase of the 4th cycle (hour 18–24). Twenty four hours later at the beginning of the 8th cycle, the mice were tested again for the working memory task, then allowed to sleep ad lib for another 24 hours when they were tested again for recovery (Figure 8A). During the sleep restriction the AdoA1R−/− mice showed a significant increase in the number of revisit errors (4.1 +/− 1.3 errors; p<0.05), while the AdoA1Rf/f mice performed at a level of accuracy that was no different from baseline (1.5 +/− 0.2 errors). The difference in revisit error rate was also significant between the two groups (p<0.05; Figure 8A). The significant worsening in the working memory behavior of the AdoA1R−/− mice was associated with an increase in the SEM indicating that not all of the knockout mice were affected to the same degree. Nevertheless, all of the AdoA1Rf/f mice tested either improved in performance or did not change whereas only 4 of 10 AdoA1R−/− mice did not worsen in performance. This difference in performance is not due to a difference in sensory/motor ability or motivation as assessed by latency to complete the task and by weights of the animals (Figure 8 B,C). Thus, the ability to functionally compensate for restricted sleep in a cognitive performance task, requires the AdoA1R gene and is directly associated with enhancement of SWA.
Next, we tested whether hippocampus-dependent learning is affected by the inducible AdoA1R deletion using a task that involves hippocampal-dependent acquisition of paired associates.
AdoA1Rf/f and AdoA1R−/− animals (n=4/genotype) acquired this task under baseline conditions (Figure 9A) with no difference between genotypes (data not shown). Both genotypes were sleep restricted for 6 days and beginning on day 2, were trained for 5 days (using the same protocol as that used for control conditions, except with new contexts and scent cues) to acquire new paired associates during the sleep restriction. Again, no difference was observed between groups or, within groups with respect to learning under baseline conditions compared to learning during sleep restriction. A 2-way ANOVA testing the effect of genotype/condition on trial day response, was not significant (Figure 9A), although, there was an effect of trial day on acquisition (p<0.005; Figure 9B). The hippocampal-dependent task was thus distinguished from the working memory task by the lack of significant effect compared to the significant effect of the AdoA1R gene on working memory task performance when sleep was restricted.
In summary, these findings suggest that AdoA1 receptors mediate a feedback response to restricted sleep comprised of a compensatory enhancement of synchronized SWA. The loss of AdoA1R expression results in a selective attenuation of this homeostatic SWA response. The attenuation of SWA is associated with compromised working memory-dependent performance, indicative of a functional role for AdoA1R-dependent SWA homeostasis in maintaining this cognitive performance when sleep is restricted.
Several studies indicate that the expression of SWA is under genetic control (Franken et al., 1998;Franken et al., 2001c;Wisor et al., 2002;Maret et al., 2005a), but the specific molecular, neurochemical, and physiological mechanisms responsible for this control remain largely uncharacterized. At the cellular level, AdoA1Rs mediate an increase in GIRK channel currents and a decrease in hyperpolarization activated currents, both of which facilitate the oscillations that underlie SWA (Pape, 1992a). In addition, activation of AdoA1Rs on presynaptic terminals reduces synaptic glutamate release, thereby reducing excitatory drive (Brambilla et al., 2005c) and allowing electrophysiological relaxation of neurons towards a more hyperpolarized membrane potential needed for the emergence of endogenously generated SWA oscillations (McCormick and Pape, 1990). Application of exogenous adenosine and AdoA1R agonists either systemically or locally to the diencephalon increases SWS (Radulovacki, 1985) and SWA recorded from the surface EEG (Benington et al., 1995a;Benington and Heller, 1995).
An indirect AdoA1R mediated mechanism to increase SWS and SWA in response to waking may result from a local increase in extracellular adenosine in cholinergic arousal centers. Increased glutamate-mediated excitatory input to neurons of these centers, associated with prolonged waking, increases AdoA1R activation (Arrigoni et al., 2001c;Brambilla et al., 2005b;Rainnie et al., 1994a). This activation reduces arousal center activity, acting at both pre- and post-synaptic inhibitory AdoA1Rs (Rainnie et al., 1994; Arrigoni et al., 2001) and accordingly, decreases cholinergic tone in these centers’ target sites, including the thalamocortical system. The decrease in cholinergic tone facilitates SWA as observed when adenosine reuptake is blocked (increasing endogenous adenosine concentration) in the cholinergic basal forebrain (Porkka-Heiskanen et al., 1997b). Thus, AdoA1R mediated actions can potentially facilitate the increase in SWA by two complimentary mechanisms during prolonged waking (Arrigoni et al., 2001d;Porkka-Heiskanen et al., 1997a;Portas et al., 1997c;Rainnie et al., 1994c). However, the requirement for AdoA1R mediated increase in homeostatic SWA has not previously been demonstrated.
Adenosine is the endogenous ligand for the AdoA1R and its extracellular concentration increases whenever the ratio of metabolite availability to metabolite demand decreases (Greene and Haas, 1991;Dunwiddie and Masino, 2001;McIlwain and Poll, 1986). An AdoA1R mediated inhibitory tone, present under physiological conditions, is positively modulated with a slow time constant in response to maintained increases in excitatory synaptic glutamate release as occurs with maintained waking (Brambilla et al., 2005a). Since extracellular adenosine concentration reflects the intracellular concentration that is maintained in equilibrium with ATP/ADP ratio by adenosine kinase (Muchmore et al., 2006) in both glia and neurons (Studer et al., 2006b), the AdoA1R inhibitory tone reflects the intracellular metabolic state of nervous tissue. Accordingly, intracellular metabolic state can modulate the functionally relevant enhancement of synchronized SWA during the SWS state. Although the loss of AdoA1R’s in the conditional gene deletion employed in this study are exclusively neuronal (Tsien et al., 1996d), the source of the adenosine may include both neurons and glia (Pascual et al., 2005;Studer et al., 2006a) and reflect the metabolic state both kinds of neural tissue.
The data presented here suggest that under physiological conditions during sleep restriction, AdoA1R activation is needed for the full expression of a homeostatic increase of SWA. Nevertheless, SWA still predominates during SWS in the absence of AdoA1R activation since it was clearly observed in AdoA1R−/− mice. Furthermore, in a mutant mouse with constitutive deletion of the AdoA1R gene, SWA was not altered in spontaneously sleeping mice and mice sleep deprived by gentle handling (Stenberg et al., 2003a). These findings are most consistent with a modulatory role for AdoA1R activation in SWA expression.
Additionally, the working memory deficits seen in the AdoA1R−/− mice under sleep restriction may be due to factors other than the decreased SWA, such as stress or changes in other frequency bands. It is unlikely that a stress effect would only appear in the knockout animals since all mice had the same amount of forced waking at the same belt speed. We cannot rule out differences in other frequency bands in the AdoA1R−/− animals, however, the greatest changes in frequency during SWS following sleep restriction are in the SWA frequency band (Borbély et al., 1984). Thus, is it reasonable to conclude that the working memory effects seen by knocking out the AdoA1 receptor are most likely due the concurrent changes in SWA.
The effect of the inducible deletion of the AdoA1R gene in CNS was remarkably selective for an attenuated rebound response in SWA to sleep restriction. SWA was only slightly attenuated in baseline conditions and the percent of time spent in SWS in either baseline or during sleep restriction, was not affected by the gene deletion. This selectivity offered an experimental opportunity to dissociate changes in SWA from changes in SWS time since AdoA1R−/− mice had an attenuated homeostatic SWA response but, an unchanged SWS time in our sleep restriction paradigm. The ability to further increase SWA expressed during SWS under baseline conditions to the larger amplitude of SWA expressed during SWS under the sleep restriction conditions was marked in the AdoA1Rf/f mice and almost completely absent in the AdoA1R−/− mice (a >40% compared to <10% further increase). This suggests an AdoA1R-dependent compensatory increase in SWA.
AdoA1R−/− mice could perform a working memory cognitive task normally under baseline conditions but performance was compromised under conditions of sleep restriction. This deficit in performance was associated with the deficit in the compensatory SWA response and the deficit was recovered when sleep was no longer restricted. Thus, loss of AdoA1R function compromises working memory performance but only under conditions involving the reduction of rebound SWA, consistent with a role for rebound SWA in cognitive performance.
Notably, attenuated SWA did not affect a hippocampal-dependent, paired associates, learning task involving acquisition and next day improvement in performance. This task was employed for several reasons. First, the paradigm is sensitive to loss of only 10–30% of CA3 NMDA receptors (Rajji et al., 2006), indicating its sensitivity to intact hippocampal, NMDA receptor function including NMDAR receptor-dependent synaptic plasticity. Second, it does not require working memory to perform, since all the needed cues are always present. Third, attentional processes may be less critical for this task’s performance for the same reason, i.e. all cues are always present, a condition that contrasts with the 8-arm working memory task. Our observations suggest that the neural processes involved in hippocampal-dependent learning and episodic memory (Rajji et al., 2006b), are less sensitive, or even, insensitive to the AdoA1R loss of function and the attenuated SWA as compared to those required for normal working memory capacity. It is conceivable that any negative effect of the disrupted rebound SWA response was opposed by the loss of AdoA1R inhibitory tone in the hippocampus, although these same speculated opposing effects ought to apply to the neural mechanisms involved in performance of the working memory task as well, and this was not the case. Synaptic plasticity responsible for the acquisition, retention and consolidation involved in the paired associate task was less sensitive than the neural mechanism(s) needed to perform the 8 arm maze working memory task.
With respect to the mechanisms responsible for performance of the working memory task, the observed reversibility of the sleep restriction induced deficit in AdoA1R−/− mice suggests that synaptic plasticity and/or consolidation processes were not involved. A similar kind of selective loss of function of working memory compared to reference memory has been described as resulting from the deletion of the GluR1 subunit of the AMPA receptor (Schmitt et al., 2003a) consistent with a greater sensitivity of working memory to perturbations of glutamatergic function rather than mechanisms directly related to synaptic plasticity. A major difference in neuronal function with respect to working memory performance compared to episodic memory is that the former requires sustained, selective, circuit activity of the prefrontal cortical circuits (Wang et al., 2004;Constantinidis et al., 2002;Lee and Kesner, 2003). The loss of AdoA1R function and the associated rebound SWA may be one of the factors that selectively compromise the more metabolically demanding activities such as those involved in sustained circuit activity under conditions that produce rebound SWA like restricted sleep, and thus affect working memory performance.
The nature of sleep function remains enigmatic (Greene and Siegel, 2004), especially as the molecular mechanisms controlling a homeostatic increase in SWA are not well understood. It has been suggested that sleep function is involved in the consolidation of learning (Stickgold and Walker, 2005;Walker and Stickgold, 2004) or in the global homeostasis of synaptic plasticity of learning and memory (Vyazovskiy et al., 2008), based on observations of performance with or without intervening episodes of sleep. Nevertheless, whether these sleep dependent changes are due to a direct modulation of synaptic plasticity or to an indirect outcome from some other process that impinges upon synaptic plasticity remains to be established. Indeed, there is considerable evidence consistent with a role in metabolism, feeding and sleep based on known modulators of sleep that involve metabolism and feeding, including NPAS2 (Dudley et al., 2003;Rutter et al., 2001), clock (Turek et al., 2005;Naylor et al., 2000), leptin (Laposky et al., 2006), orexin/hypocretin (Chemelli et al., 1999;Willie et al., 2001;Lin et al., 1999) and adenosine (Brambilla et al., 2005e).
Taken together our findings suggest that metabolically associated feedback signals of waking, involving AdoA1R activation, influence homeostatic sleep functions in the CNS. The homeostatic sleep function requires rebound synchronized SWA, as suggested by the observation that loss of AdoA1R function and the selective attenuation of this homeostatic sleep response reduces working memory capacity.
We gratefully acknowledge the scientific direction and oversight of Dr. Margaret Thompson in the generation of the AdoA1Rf/f mice, the technical assistance of To Thai, Lehong Nguyen and Dr. Gerald Marks. We also acknowledge the grant and resource support from the Department of Veterans Affairs and NIH, RO1 MH 06777.