Research and Advanced Education
Scientific Research Projects 2009/2010 - Neurosciences Area
Neurophysiological characterisation of sleep spindles and K-complexes in patients with middle cerebral artery stroke and correlation with prognosis
Joana Isaac [1], Ana Rita Peralta [2,3,6] Carla Bentes [2,4,5,6]
Neurology Unit, Neuroscience Department of Santa Maria Hospital
teixeirajoana@campus.ul.pt
[1]: Student in year 3 of the Integrated Master Degree in Medicine of the Faculty of Medicine of Lisbon
[2]: Hospital Assistant, Neurology Unit, Neuroscience Department, Santa Maria Hospital, Northern Lisbon Hospital Centre
[3]: Neurology and Physiology Guest Hospital Assistant, Faculty of Medicine of Lisbon
[4]: Neurology Guest Hospital Assistant, Faculty of Medicine of Lisbon
[5]: Neurophysiologist
[6]: Researcher at the Institute of Molecular Medicine
The present article aims to describe a research project supported by GAPIC (2011) that is being carried out at the EEG/Sono e Unidade de AVCs (EEG/Sleep and Stroke Unit) – Neurology Service, Department of Neuroscience of Santa Maria Hospital by Joana Isaac, a student in year 3 of the medical degree, under the supervision of Ana Rita Peralta and Carla Bentes.
Currently, brain strokes have an incidence rate of 2 to 18 per 1.000 inhabitants. They are the leading cause of disability and the second cause of death worldwide (Jiménez-Conde & Roquer, 2009).
Sleep is markedly affected during the acute stage of stroke. The changes specialists most agreed on include reduced total sleep time, sleep efficiency, stage N2 and N3, increased number of awakenings, of N1 stage and sleep latency (Terzoudi A et al., 2009; Hermann DM et al., 2008). The stroke prognosis correlates positively with the percentage of sleep (Siengsukon & Boyd, 2009).
Changes in sleep microstructure have also been documented, namely with regard to sleep spindles. Sleep spindles correspond to a spontaneous cortical activity originating in the thalamus and which is typical of the N2 stage. Reduced sleep spindles in stroke patients has been demonstrated mostly in strokes of thalamic origin. As for hemispheric strokes, studies are a lot scarcer. Bassetti and Aldrisch (2001) have documented the reduction in the number of sleep spindles ipsilateral to the lesion. A subsequent study confirmed that the power and coherence of the spectral band of sleep spindles had become significantly reduced in the hemisphere ipsilateral to the lesion in hemispheric strokes from distinct arterial regions (Gottselig, Basseti & Achermann, 2002). Urakami (2009) demonstrated that in the hemisphere ipsilateral to deep hemispheric hematomas, the brain sources of these graphoelements present less wide topographic representations located in the frontal, pre and post central, and parietal regions.
The potentiating effect of sleep in consolidating implicit and explicit motor memories has also been demonstrated in stroke patients (Siengsukon & Boyd, 2009). It is possible that part of this memory potentiation, which in stroke patients depends on sleep, is mediated by mechanisms underlying those rhythmic oscillations in the spectral band related to sleep spindles. Accordingly, it is likely that changes in the characteristics of these graphoelements following stroke are important in terms of prognosis. Until now, only one study has suggested that there is indeed a positive correlation between the power and coherence of the spectral band of sleep spindles in the hemisphere ipsilateral to the lesion and the Barthel index done between 2 and 19 months after the stroke (Gottselig, Basseti & Achermann, 2002).
K-complexes are graphoelements of the sleep N2 stage, with wide amplitude, biphasic and which show increased amplitude in bilateral frontal topography (Wennberg, 2010). Their function is unknown, but several studies suggest that they have a sleep protecting role, preventing the occurrence of micro-awakenings (Colrain, 2005). To date, it seems there are no studies that specifically analyse the neurophysiological characteristics and quantify K-complexes following a stroke. In rats, sleep fragmentation causes a larger infarcted area and worse functional recovery following ischemic stroke (Gao et al, 2010). For this reason, it is likely that reducing these sleep protecting elements may have prognostic implications in those patients.
The study of sleep spindles and K-complexes in patients with brain lesion is important because it contributes to our understanding of the cerebral networks involved in the origin of these elements. It also allows improved characterisation of sleep in acute stroke. Sleep classification in these patients is subject to major inter- and intra-observer variability, which makes standardisation of research on this topic difficult. It is necessary to establish the normal sleep pattern of stroke patients. The precise description of microstructural changes is one of the first steps to improve the criteria for classifying the sleep of stroke patients.
Accordingly, the present research aims to characterise, from a neurophysiologic perspective (duration, amplitude, predominant frequency, topography and laterality) the sleep spindles and K-complexes of patients with acute middle cerebral artery stroke and correlate the neurophysiological characteristics of these graphoelements with the functional prognosis 1 week and 1 month after the stroke.
This work is part of an ongoing project at the same laboratory titled “Electroencephalic monitoring in rtPA stroke patients”, which aims to describe the electroencephalic changes in acute stroke, subject, or not, to intravenous thrombolysis, and correlate the electroencephalic changes with functional prognosis at one week, one month and 6 months after the stroke. This research intends to contribute to the delineation of sleep-wake neurophysiological models with prognostic value for stroke patients, thus making it possible to prepare effective treatment strategies.
__________________________
Bibligraphy
• Bassetti CL, Aldrich MS. (2001). Sleep electroencephalogram changes in acute hemispheric stroke. Sleep Med, 2(3):185-194.
• Colrain. (2005). K-Complex History and Review. SLEEP, Vol. 28, No. 2.
• Gao B, Cam E, Jaeger H, Zunzunegui C, Sarnthein J, Bassetti CL. (2010). Sleep disruption aggravates focal cerebral ischemia in the rat. Sleep, Jul 1; 33(7):879-87.
• Genzel, et al. (2009). Slow Wave and REM Sleep Awakenings and Memory. SLEEP, Vol. 32, No. 3.
• Gottselig JM, Bassetti CL, Achermann P. (2002). Power and coherence of sleep spindle frequency activity following hemispheric stroke. Brain, (2): 373-383.
• Hermann DM, et al. (2008). Evolution of neurological, neuropsychological and sleep-wake disturbances after paramedian thalamic stroke. Stroke, 39(1):62-8.
• Jiménez-Conde J, Roquer J. (2009). Ischemic stroke rhythms: external factors that contribute to modulate the moment of event´s occurrence. Med Clin, 132, 671-6.
• Siengsukon CF, Boyd LA. (2009). Sleep to learn after stroke: implicit and explicit off-line motor learning. Neurosci Lett, Feb 13; 451(1):1-5.
• Terzoudi A, et al. (2009). Sleep architecture in stroke and relation to outcome. Eur Neurol, 61(1):16-22.
• Uramaki Y. (2009). Relationships between sleep spindles and activities of the cerebral cortex after hemispheric stroke as determined by simultaneous EEG and MEG recordings. J Clin Neurophysiol, Aug; 26(4).
• Walker MP. (2008). Cognitive consequences of sleep and sleep loss. Sleep Medicine, 9 Suppl. 1 S29–S34.
• Wennberg. (2010). Intracranial cortical localization of the human K-complex. Clinical Neurophysiology.
Joana Isaac [1], Ana Rita Peralta [2,3,6] Carla Bentes [2,4,5,6]
Neurology Unit, Neuroscience Department of Santa Maria Hospital
teixeirajoana@campus.ul.pt
[1]: Student in year 3 of the Integrated Master Degree in Medicine of the Faculty of Medicine of Lisbon
[2]: Hospital Assistant, Neurology Unit, Neuroscience Department, Santa Maria Hospital, Northern Lisbon Hospital Centre
[3]: Neurology and Physiology Guest Hospital Assistant, Faculty of Medicine of Lisbon
[4]: Neurology Guest Hospital Assistant, Faculty of Medicine of Lisbon
[5]: Neurophysiologist
[6]: Researcher at the Institute of Molecular Medicine
The present article aims to describe a research project supported by GAPIC (2011) that is being carried out at the EEG/Sono e Unidade de AVCs (EEG/Sleep and Stroke Unit) – Neurology Service, Department of Neuroscience of Santa Maria Hospital by Joana Isaac, a student in year 3 of the medical degree, under the supervision of Ana Rita Peralta and Carla Bentes.
Currently, brain strokes have an incidence rate of 2 to 18 per 1.000 inhabitants. They are the leading cause of disability and the second cause of death worldwide (Jiménez-Conde & Roquer, 2009).
Sleep is markedly affected during the acute stage of stroke. The changes specialists most agreed on include reduced total sleep time, sleep efficiency, stage N2 and N3, increased number of awakenings, of N1 stage and sleep latency (Terzoudi A et al., 2009; Hermann DM et al., 2008). The stroke prognosis correlates positively with the percentage of sleep (Siengsukon & Boyd, 2009).
Changes in sleep microstructure have also been documented, namely with regard to sleep spindles. Sleep spindles correspond to a spontaneous cortical activity originating in the thalamus and which is typical of the N2 stage. Reduced sleep spindles in stroke patients has been demonstrated mostly in strokes of thalamic origin. As for hemispheric strokes, studies are a lot scarcer. Bassetti and Aldrisch (2001) have documented the reduction in the number of sleep spindles ipsilateral to the lesion. A subsequent study confirmed that the power and coherence of the spectral band of sleep spindles had become significantly reduced in the hemisphere ipsilateral to the lesion in hemispheric strokes from distinct arterial regions (Gottselig, Basseti & Achermann, 2002). Urakami (2009) demonstrated that in the hemisphere ipsilateral to deep hemispheric hematomas, the brain sources of these graphoelements present less wide topographic representations located in the frontal, pre and post central, and parietal regions.
The potentiating effect of sleep in consolidating implicit and explicit motor memories has also been demonstrated in stroke patients (Siengsukon & Boyd, 2009). It is possible that part of this memory potentiation, which in stroke patients depends on sleep, is mediated by mechanisms underlying those rhythmic oscillations in the spectral band related to sleep spindles. Accordingly, it is likely that changes in the characteristics of these graphoelements following stroke are important in terms of prognosis. Until now, only one study has suggested that there is indeed a positive correlation between the power and coherence of the spectral band of sleep spindles in the hemisphere ipsilateral to the lesion and the Barthel index done between 2 and 19 months after the stroke (Gottselig, Basseti & Achermann, 2002).
K-complexes are graphoelements of the sleep N2 stage, with wide amplitude, biphasic and which show increased amplitude in bilateral frontal topography (Wennberg, 2010). Their function is unknown, but several studies suggest that they have a sleep protecting role, preventing the occurrence of micro-awakenings (Colrain, 2005). To date, it seems there are no studies that specifically analyse the neurophysiological characteristics and quantify K-complexes following a stroke. In rats, sleep fragmentation causes a larger infarcted area and worse functional recovery following ischemic stroke (Gao et al, 2010). For this reason, it is likely that reducing these sleep protecting elements may have prognostic implications in those patients.
The study of sleep spindles and K-complexes in patients with brain lesion is important because it contributes to our understanding of the cerebral networks involved in the origin of these elements. It also allows improved characterisation of sleep in acute stroke. Sleep classification in these patients is subject to major inter- and intra-observer variability, which makes standardisation of research on this topic difficult. It is necessary to establish the normal sleep pattern of stroke patients. The precise description of microstructural changes is one of the first steps to improve the criteria for classifying the sleep of stroke patients.
Accordingly, the present research aims to characterise, from a neurophysiologic perspective (duration, amplitude, predominant frequency, topography and laterality) the sleep spindles and K-complexes of patients with acute middle cerebral artery stroke and correlate the neurophysiological characteristics of these graphoelements with the functional prognosis 1 week and 1 month after the stroke.
This work is part of an ongoing project at the same laboratory titled “Electroencephalic monitoring in rtPA stroke patients”, which aims to describe the electroencephalic changes in acute stroke, subject, or not, to intravenous thrombolysis, and correlate the electroencephalic changes with functional prognosis at one week, one month and 6 months after the stroke. This research intends to contribute to the delineation of sleep-wake neurophysiological models with prognostic value for stroke patients, thus making it possible to prepare effective treatment strategies.
__________________________
Bibligraphy
• Bassetti CL, Aldrich MS. (2001). Sleep electroencephalogram changes in acute hemispheric stroke. Sleep Med, 2(3):185-194.
• Colrain. (2005). K-Complex History and Review. SLEEP, Vol. 28, No. 2.
• Gao B, Cam E, Jaeger H, Zunzunegui C, Sarnthein J, Bassetti CL. (2010). Sleep disruption aggravates focal cerebral ischemia in the rat. Sleep, Jul 1; 33(7):879-87.
• Genzel, et al. (2009). Slow Wave and REM Sleep Awakenings and Memory. SLEEP, Vol. 32, No. 3.
• Gottselig JM, Bassetti CL, Achermann P. (2002). Power and coherence of sleep spindle frequency activity following hemispheric stroke. Brain, (2): 373-383.
• Hermann DM, et al. (2008). Evolution of neurological, neuropsychological and sleep-wake disturbances after paramedian thalamic stroke. Stroke, 39(1):62-8.
• Jiménez-Conde J, Roquer J. (2009). Ischemic stroke rhythms: external factors that contribute to modulate the moment of event´s occurrence. Med Clin, 132, 671-6.
• Siengsukon CF, Boyd LA. (2009). Sleep to learn after stroke: implicit and explicit off-line motor learning. Neurosci Lett, Feb 13; 451(1):1-5.
• Terzoudi A, et al. (2009). Sleep architecture in stroke and relation to outcome. Eur Neurol, 61(1):16-22.
• Uramaki Y. (2009). Relationships between sleep spindles and activities of the cerebral cortex after hemispheric stroke as determined by simultaneous EEG and MEG recordings. J Clin Neurophysiol, Aug; 26(4).
• Walker MP. (2008). Cognitive consequences of sleep and sleep loss. Sleep Medicine, 9 Suppl. 1 S29–S34.
• Wennberg. (2010). Intracranial cortical localization of the human K-complex. Clinical Neurophysiology.
