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Projects source: E-CRIS

Neurobiology of sleep in aging and disease - electroencephalographic markers and modeling in the estimation of disorder

Research activity

Code Science Field
B470  Biomedical sciences  Physiology 
B540  Biomedical sciences  Respiratory system 
B640  Biomedical sciences  Neurology, neuropsychology, neurophysiology 
Keywords
sleep, aging, neurodegenerative disease, cholinergic neurons, electroencephalographic markers
Organisations (3)
0097  University of Belgrade, Institute for Biological Research "Siniša Stanković" - National Institute of the Republic of Serbia
0018  University of Belgrade, Faculty of Medicine
0106  University of Belgrade, Institute for Multidisciplinary Research
Abstract
On the base of hypothesis that basal forebrain cholinergic system plays an important role in the etiology of the most common neurodegenerative diseases of elderly, the lesion of the nucleus basalis in the rat presents the most utilized “in vivo” animal model to study disorders of cortical cholinergic innervation, and its impact on higher central nervous system functions. In this research we will use the rat models of unilateral or bilateral lesion of the nucleus basalis-a (NB; the main cortical cholinergic nucleus), and nucleus pedunculopontine tegmentum, (PPT; the main cholinergic nucleus of the brainstem - pons), by stereotaxically guided microinfusion of the excitotoxin in a nanoliter volume. The main objective of this research project is to investigate at the electroencephalographic (EEG) level the impact of two functionally distinct brain cholinergic systems (NB versus PPT): on changes in sleep/wake states distribution, NREM/REM sleep cycling, sleep/wake state related alteration of all conventional EEG frequency bands and characteristic oscillations during progression of the neurodegenerative disease versus healthy aging. The main goal of this research project is to determine all characteristic EEG markers of sleep disturbance in rat caused by healthy aging or neurodegenerative disease using the linear and nonlinear data analysis methods and modeling, and to apply them on the human signals for detection, follow-up and estimation of the disease.
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