Locus Coeruleus Activity during Wake Is Associated with Rapid Eye Movement Sleep Intensity
Poster No:
2577
Submission Type:
Abstract Submission
Authors:
Nasrin Mortazavi1, Ekaterina Koshmanova1, Roya Sharifpour1, Alexandre Berger2,3, Elise Beckers1,4, Islay Campbell1, Ilenia Paparella1, Fermin Aizpurua1, Laurent Lamalle1, Puneet Talwar1, Siya Sherif1, Gilles Vandewalle1
Institutions:
1Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège, Liège, Belgium, 2Institute of Neuroscience (IoNS), Université Catholique de Louvain (UCLouvain), Brussels, Belgium, 3Synergia Medical SA, Mont-Saint-Guibert, Belgium, 4Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, Netherlands
First Author:
Nasrin Mortazavi
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Co-Author(s):
Ekaterina Koshmanova
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Roya Sharifpour
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Alexandre Berger
Institute of Neuroscience (IoNS), Université Catholique de Louvain (UCLouvain)|Synergia Medical SA
Brussels, Belgium|Mont-Saint-Guibert, Belgium
Institute of Neuroscience (IoNS), Université Catholique de Louvain (UCLouvain)|Synergia Medical SA
Brussels, Belgium|Mont-Saint-Guibert, Belgium
Elise Beckers
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège|Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University
Liège, Belgium|Maastricht, Netherlands
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège|Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University
Liège, Belgium|Maastricht, Netherlands
Islay Campbell
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Ilenia Paparella
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Fermin Aizpurua
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Laurent Lamalle
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Puneet Talwar
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Siya Sherif
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Gilles Vandewalle
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Sleep and Chronobiology Lab, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège
Liège, Belgium
Introduction:
The locus coeruleus (LC) is the main source of norepinephrine in the brain (Szabadi, 2013). The LC contributes to the transition between sleep and wakefulness, and between slow wave sleep (SWS) and rapid eye movement sleep (REMS) (Cirelli et al., 2005). It is tightly linked to the oscillatory modes found during sleep, such as sleep spindles and slow waves in animals (Eschenko et al., 2012). While the LC appears to be an important structure for sleep, only a few imaging studies evaluated whether the LC is related to sleep variability due to the difficulty of imaging such a small size nucleus in vivo (Keren et al., 2009).
We aimed to investigate the link between LC activity during wakefulness assessed by 7-Tesla MRI and electroencephalogram (EEG) features of sleep. To trigger a response of the LC, we used a visual perceptual rivalry task and an auditory attentional task. Subjects saw an ambiguous stimulus which could trigger spontaneous switches between two perceptions of the same image (Blake et al., 2002). Switches are considered to recruit the LC (Einhauser et al., 2008; Murphy et al., 2014). Participants also did an auditory oddball task, which can activate LC (Murphy et al., 2014).
We aimed to investigate the link between LC activity during wakefulness assessed by 7-Tesla MRI and electroencephalogram (EEG) features of sleep. To trigger a response of the LC, we used a visual perceptual rivalry task and an auditory attentional task. Subjects saw an ambiguous stimulus which could trigger spontaneous switches between two perceptions of the same image (Blake et al., 2002). Switches are considered to recruit the LC (Einhauser et al., 2008; Murphy et al., 2014). Participants also did an auditory oddball task, which can activate LC (Murphy et al., 2014).
Methods:
52 healthy volunteers, including 33 young (22.3 ± 3.2 y; 28 women) and 19 late middle-aged (61.05 ± 5.3 y; 14 women) individuals completed the protocol. They first underwent a structural 7T MRI session, which allowed collecting high-resolution whole-brain T1-weighted images as well as magnetization transfer-weighted turbo-flash (MT-TFL) sequence over a 6 cm slab placed around the LC. The latter was used to create an individual LC-mask in the brain space of each participant. All individual LC-masks were gathered into a probabilistic LC-mask in a standardized group brain space.
Following 1 week of regular sleep times, participants completed an fMRI session in the morning, 2h to 3h after wake-up time, during which they were administered the perceptual rivalry task and oddball task (TR= 2.34s; voxel size 1.4x1.4x1.4 mm³). Participant's habitual and baseline sleep was recorded in-lab under EEG to extract 4 sleep features of interest depicting some of the most canonical characteristics of sleep (i.e., cumulated power of the theta frequency band during REMS, slow wave energy (SWE), sleep onset latency, and REMS percentage).
We computed a general linear model by the Statistical Parametric Mapping 12 package (SPM12) over the entire brain in individual space. Subject level maps were normalized to MNI space for group statistic visualization. We then extracted the activity estimates over individual LC masks and then conducted generalized linear mixed models (GLMMs) to test for associations between the activity of the LC during both tasks and EEG features of sleep, including age, sex, BMI, and total sleep time as covariates.
Following 1 week of regular sleep times, participants completed an fMRI session in the morning, 2h to 3h after wake-up time, during which they were administered the perceptual rivalry task and oddball task (TR= 2.34s; voxel size 1.4x1.4x1.4 mm³). Participant's habitual and baseline sleep was recorded in-lab under EEG to extract 4 sleep features of interest depicting some of the most canonical characteristics of sleep (i.e., cumulated power of the theta frequency band during REMS, slow wave energy (SWE), sleep onset latency, and REMS percentage).
We computed a general linear model by the Statistical Parametric Mapping 12 package (SPM12) over the entire brain in individual space. Subject level maps were normalized to MNI space for group statistic visualization. We then extracted the activity estimates over individual LC masks and then conducted generalized linear mixed models (GLMMs) to test for associations between the activity of the LC during both tasks and EEG features of sleep, including age, sex, BMI, and total sleep time as covariates.
Results:
Inspection of whole brain group data identified increased activation within the left LC group template associated with perceptual switches (uncorrected p<0.001; t > 3.27) and the detection of the target sound of the oddball task (uncorrected p<0.001; t >3.26) (Figure 1).
This supported the extraction of individual LC activity in the individual space to associate with sleep EEG metrics. GLMMs on the LC activity and sleep EEG metrics revealed a positive association between the left LC activity during perceptual rivalry task and EEG cumulated power of the theta frequency band (4-8Hz) during REMS (p = 0.004, t=3.02), which reflects the intensity of REMS. A negative association was found between the left LC activity during oddball task and this sleep metric in the older (p = 0.024, t = -2.33) but not in the younger group.
This supported the extraction of individual LC activity in the individual space to associate with sleep EEG metrics. GLMMs on the LC activity and sleep EEG metrics revealed a positive association between the left LC activity during perceptual rivalry task and EEG cumulated power of the theta frequency band (4-8Hz) during REMS (p = 0.004, t=3.02), which reflects the intensity of REMS. A negative association was found between the left LC activity during oddball task and this sleep metric in the older (p = 0.024, t = -2.33) but not in the younger group.
Conclusions:
The results suggest that maybe there is an inverted U-shape relationship between LC activity during wakefulness and REMS intensity. These results contribute to the understanding of sleep physiology.
Funding: FNRS Belgium, ULiège, FEDER, Alzheimer Foundation (SAO-FRA), Wallonia-Brussels federation
Funding: FNRS Belgium, ULiège, FEDER, Alzheimer Foundation (SAO-FRA), Wallonia-Brussels federation
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 2
EEG/MEG Modeling and Analysis
Perception, Attention and Motor Behavior:
Sleep and Wakefulness 1
Keywords:
Brainstem
Electroencephaolography (EEG)
FUNCTIONAL MRI
NORMAL HUMAN
Sleep
1|2Indicates the priority used for review
Provide references using author date format
Einhauser, W. (2008) ‘Pupil dilation reflects perceptual selection and predicts subsequent stability in perceptual rivalry’, Proceedings of the National Academy of Sciences, vol. 105, no. 5, pp. 1704–1709.
Eschenko, O. (2012) ‘Noradrenergic neurons of the locus coeruleus are phase locked to cortical up-down states during sleep’, Cerebral Cortex, vol. 22, no. 2, pp. 426–435.
Keren, N.I. (2009) ‘In vivo mapping of the human locus coeruleus’, NeuroImage, vol. 47, no. 4, pp. 1261–1267.
Murphy, P.R. (2014) ‘Pupil diameter covaries with BOLD activity in human locus coeruleus’, Human Brain Mapping, vol. 35, no. 8, pp. 4140–4154.
Szabadi, E. (2013) ‘Functional neuroanatomy of the central noradrenergic system’, Journal of Psychopharmacology, vol. 27, no. 8, pp. 659–693.