Noradrenergic Neurons of the Locus Coeruleus Are Phase Locked to Cortical Up-Down States during Sleep

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Cerebral Cortex Advance Access published June 13, 2011 Cerebral Cortex doi:10.1093/cercor/bhr121

Noradrenergic Neurons of the Locus Coeruleus Are Phase Locked to Cortical Up-Down States during Sleep Oxana Eschenko1, Cesare Magri1, Stefano Panzeri2 and Susan J. Sara3 1

Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, 72076 Tu¨bingen, Germany, Department of Robotics, Brain and Cognitive Sciences, Italian Institute of Technology, 16163 Genova, Italy and 3Laboratory of Physiology of Perception and Action, CNRS UMR 7192, Colle`ge de France, F-75005 Paris, France 2

Address correspondence to Susan J. Sara, Colle`ge de France, CNRS, UMR 7152, F-75005 Paris, France. Email: [email protected]

Keywords: locus coeruleus, memory consolidation, neuromodulation, noradrenergic system, prefrontal cortex, sleep, slow oscillations

Introduction Recent years have seen a growing interest in the role of sleep in off-line memory processing (Stickgold 2005; Diekelmann and Born 2010). This interest is due, in part, to the discovery of large-scale changes in cortical and hippocampal neural activity during nonrapid eye movement (NREM) sleep following learning. Learning-related enhanced spindle and ripple activity has been reported in both humans (Gais et al. 2002; Schabus et al. 2004; Clemens et al. 2006; Axmacher et al. 2008; Morin et al. 2008) and rats (Eschenko et al. 2006, 2008; Fogel and Smith 2006; O’Neill et al. 2008; Ramadan et al. 2009). During sleep, the membrane potential of all major types of neocortical neurons fluctuates between depolarized (Up) and hyperpolarized (Down) states; the transitions between these states are reflected in electroencephalography (EEG) as large-amplitude, low-frequency (~1 Hz) slow waves (Steriade et al. 1993a, 1993b; Steriade et al. 2001; Timofeev et al. 2001). Slow oscillations group the faster brain rhythms, spindles in the cortex (Mo¨lle et al. 2002; Steriade 2006), and ripples in the hippocampus (Siapas and Wilson 1998; Sirota et al. 2003; Mo¨lle et al. 2006). In turn, these fast transient oscillations reflect synchronized firing of large neuronal populations during the depolarized state, including the well-documented experience-dependent neuronal

replay in cortex and hippocampus (Kudrimoti et al. 1999; Nadasdy et al. 1999; Johnson et al. 2010). Thus, the slow oscillations are thought to mediate sleep-dependent memory improvements by temporally coordinating other brain rhythms implicated in off-line information processing (Steriade and Timofeev 2003; Diekelmann and Born 2010). Such concerted brain activity may reinforce the neuronal networks being replayed by facilitating communication within and between brain regions and promoting synaptic plasticity (Buzsaki 1996). The noradrenergic (NE) system has been shown to be critically involved in the late phase of memory consolidation (Roullet and Sara 1998; Tronel et al. 2004) that may well take place during NREM sleep. In support of this notion, we previously described a transient increase in activity of NE neurons of the locus coeruleus (LC) during NREM sleep after learning in rats (Eschenko and Sara 2008). A combined EEG and functional magnetic resonance imaging (fMRI) study in humans (Dang-Vu et al. 2008) further revealed that the activity of the LC nucleus is temporally related to slow oscillations. Altogether, these findings challenge the conventional dogma about the relative quiescence of LC neurons during sleep (Hobson et al. 1975; Aston-Jones and Bloom 1981) and suggest an involvement of LC-NE system in modulating cortical activity during NREM sleep. Although the facilitating effects of the LC input on cortical excitability (McCormick et al. 1991), spike timing and synaptic plasticity in cortex (Bouret and Sara 2002; Marzo et al. 2009), and hippocampus (Harley 2007) are well established, the precise temporal relationship between cortical Up/Down states and LC firing has not yet been explored. Our previous investigations in rats under ketamine anesthesia had shown a negative correlation in activity of NE neurons of the LC and prefrontal neurons, when neurons within each region were oscillating at ~1 Hz (Sara and Herve-Minvielle 1995; Lestienne et al. 1997). Therefore, in order to further explore the finescale temporal cortico--coerulear interaction, particularly in the context of potential contribution of the LC-NE system to memory processing during NREM sleep, we recorded unit activity in the LC simultaneously with cortical EEG in the unanaesthetized naturally sleeping rat. Materials and Methods Animals Male Sprague--Dawley rats (Charles River Laboratories, Le GenestSt-Isle, France), weighing 350--400 g were used. They were maintained on a 12:12 h light:dark cycle with free access to food and water. Surgery was performed under pentobarbital anesthesia (40 mg/kg, supplemented as necessary). Rats were allowed 1 week for postsurgical recovery, before being habituated to the recording setup. All procedures followed the 1986 European Community Council Directive

 The Authors 2011. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Downloaded from at University of Pennsylvania Library on June 14, 2011

Nonrapid eye movement (NREM) sleep is characterized by periodic changes in cortical excitability that are reflected in the electroencephalography (EEG) as high-amplitude slow oscillations, indicative of cortical Up/Down states. These slow oscillations are thought to be involved in NREM sleep-dependent memory consolidation. Although the locus coeruleus (LC) noradrenergic system is known to play a role in off-line memory consolidation (that may occur during NREM sleep), cortico--coerulear interactions during NREM sleep have not yet been studied in detail. Here, we investigated the timing of LC spikes as a function of sleep-associated slow oscillations. Cortical EEG was monitored, along with activity of LC neurons recorded extracellularly, in nonanesthetized naturally sleeping rats. LC spike-triggered averaging of EEG, together with phase-locking analysis, revealed preferential firing of LC neurons along the ascending edge of the EEG slow oscillation, correlating with Down-to-Up state transition. LC neurons were locked best when spikes were shifted forward ~50 ms in time with respect to the EEG slow oscillation. These results suggest that during NREM sleep, firing of LC neurons may contribute to the rising phase of the EEG slow wave by providing a neuromodulatory input that increases cortical excitability, thereby promoting plasticity within these circuits.

and the French Ministe`re de l’Agriculture et de la Foret, Commission Nationale de l’Experimentation Animal decree 87848.

Signal Processing and Event Detection Unit Isolation After online detection, the stored spike shapes were further isolated from electrical noise offline with template matching complemented by cluster analysis based on principal components and specific wave form measurements, using Spike2 software. A representative example of the isolated LC spike shapes is shown on Supplementary Figure 1B. The recording technique and spike sorting method did not allow an unambiguous single unit isolation, and therefore, the LC, non-LC, and

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Eschenko et al.

Sleep Scoring NREM sleep episodes were detected by the presence of a high-amplitude slow activity ( >200 lV), predominance of delta (1--4 Hz), and absence of theta (6--9 Hz) frequencies in the power spectrum and regular appearance of sleep spindles in the EEG. To identify the sleep spindles, the EEG signal was band-pass filtered using finite impulse response (FIR) of 12--15 Hz; an automatic spindle detection algorithm was then applied (Eschenko et al. 2006). REM sleep was characterized by dominant theta activity, low-voltage fast activity, and a sleep posture monitored by online video recording. A representative pattern of EEG and LC activity across awake/sleep stages is illustrated on Supplementary Figure 1D. Detection of Slow Oscillations A high-pass filter in the majority of analog amplifiers designed for extracellular recording (including the one used in the present study) introduces a systematic frequency-dependent phase shift that is appreciable for low frequencies. We corrected for this phase delay by filtering the EEG signal backward in time using a second-order Butterworth low-pass filter with a cutoff frequency of 0.11 Hz. The order of the filter was determined from the technical specifications of the amplifier while the cutoff frequency was selected after inspecting the output of the amplifier to controlled inputs. This procedure, which is detailed fully in Supplementary Methods and illustrated on Supplementary Figure 3, enabled a more accurate detection of the timing of slow oscillation events and a precise determination of their phase. Slow oscillation cycles were then identified by peaks of negativity of the EEG signal during NREM sleep episodes, as follows. The EEG signal was first low-pass filtered using FIR of 4 Hz. Then, the largest negative half-waves during NREM sleep episodes were detected using a standard algorithm (Mo¨lle et al. 2002). Negative half-waves satisfying the following criteria were selected for further analyses: 1) 2 successive zero-crossings of the low-pass filtered signal separated from each other by at least 0.2 s; 2) maximum amplitude between both zero-crossings exceeding --100 lV; and 3) a negative-to-positive peakto-peak amplitude >120 lV. Validity of this algorithm for detection of cortical Up and Down states using EEG was previously assessed by calculation of an even...

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