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Grant: Discovery Grants Program - Individual

École de technologie supérieure

$33,000.00

QuantSLEEP: A numerical toolbox for a graph signal processing of the rhythmic and arrhythmic components of sleep EEG recordings.

FY 2024-25

Summary
A third of human life is spent sleeping. Far from being a resting state, sleep is a particularly important state during which the brain generates and processes information, and undergoes a plastic reorganization of synaptic connections to be more efficient during the forthcoming awake time. In terms of signal processing, sleep is a pristine `laboratory' in which electric measurements of spontaneous brain activity give a clear signature of the ability of the brain to cope with, and to respond to adverse threats during the previous periods of wakefulness. Today, our understanding of this activity is mostly a matter of sequences of interactions between various processes. In addition to the possible coupling of bursts of oscillations, the brain bioelectrical activity also shows interactions between short-lived functional networks that organize the co-activated remote brain areas involved in the neuronal processes. Our research program will focus on the development of numerical methods for the integration of advanced signal processing specific to electro-encephalography (EEG) measurements of the sleeping brain. More specifically, this research program aims at developing an innovative software to provide the time-resolved interactions between the networks involved during sleep. The networks will be obtained from different components of the EEG signals, from the characteristic transient rhythmic oscillations observable in the background of an arrhythmic component, to the more recent `microstates' events that happen to sample the stable co-activation of remote brain regions. The main outcome of this proposal is a numerical tool that integrates innovative approaches to decode EEG signals in order to provide the inventory and the dynamical interactions of the functional networks associated with the fundamental biomarkers of the `sleeping brain'. This innovative description of the sleep EEG recordings will be evaluated in various contexts, from the early maturation of the brain during childhood to clinical applications in epilepsy and other neuro-degenerative diseases.
Program
Discovery Grants Program - Individual
Location
Quebec, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2022-05351
Name nom
Lina, Jean-Marc
Department département
Génie électrique
Organization id
53
Institution établissement
École de technologie supérieure
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2022
Award amount
33000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
1201
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Life sciences (including biotechnology)
Area of application fr
Sciences de la vie (y compris biotechnologie)
Research subject code
1900
Research subject group en
Biomedical engineering
Research subject group fr
Génie biomédical
Research subject en
Biomedical engineering
Research subject fr
Génie biomédical
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
QuantSLEEP: A numerical toolbox for a graph signal processing of the rhythmic and arrhythmic components of sleep EEG recordings.
Keywords
traitement des signaux/signal processing; électroencéphalographie/electroencephalography; sommeil/sleep; problèmes inverses/inverse problems; ondelettes analytiques/analytical wavelets; analyse spectrale/spectral analysis; analyse multifractale/multifractal analysis; connectivité fonctionnelle/functional connectivity
Application summary
A third of human life is spent sleeping. Far from being a resting state, sleep is a particularly important state during which the brain generates and processes information, and undergoes a plastic reorganization of synaptic connections to be more efficient during the forthcoming awake time. In terms of signal processing, sleep is a pristine `laboratory' in which electric measurements of spontaneous brain activity give a clear signature of the ability of the brain to cope with, and to respond to adverse threats during the previous periods of wakefulness. Today, our understanding of this activity is mostly a matter of sequences of interactions between various processes. In addition to the possible coupling of bursts of oscillations, the brain bioelectrical activity also shows interactions between short-lived functional networks that organize the co-activated remote brain areas involved in the neuronal processes. Our research program will focus on the development of numerical methods for the integration of advanced signal processing specific to electro-encephalography (EEG) measurements of the sleeping brain. More specifically, this research program aims at developing an innovative software to provide the time-resolved interactions between the networks involved during sleep. The networks will be obtained from different components of the EEG signals, from the characteristic transient rhythmic oscillations observable in the background of an arrhythmic component, to the more recent `microstates' events that happen to sample the stable co-activation of remote brain regions. The main outcome of this proposal is a numerical tool that integrates innovative approaches to decode EEG signals in order to provide the inventory and the dynamical interactions of the functional networks associated with the fundamental biomarkers of the `sleeping brain'. This innovative description of the sleep EEG recordings will be evaluated in various contexts, from the early maturation of the brain during childhood to clinical applications in epilepsy and other neuro-degenerative diseases.