Fractional dynamical model for neurovascular coupling

Handle URI:
http://hdl.handle.net/10754/564965
Title:
Fractional dynamical model for neurovascular coupling
Authors:
Belkhatir, Zehor; Laleg-Kirati, Taous-Meriem ( 0000-0001-5944-0121 )
Abstract:
The neurovascular coupling is a key mechanism linking the neural activity to the hemodynamic behavior. Modeling of this coupling is very important to understand the brain function but it is at the same time very complex due to the complexity of the involved phenomena. Many studies have reported a time delay between the neural activity and the cerebral blood flow, which has been described by adding a delay parameter in some of the existing models. An alternative approach is proposed in this paper, where a fractional system is used to model the neurovascular coupling. Thanks to its nonlocal property, a fractional derivative is suitable for modeling the phenomena with delay. The proposed model is coupled with the first version of the well-known balloon model, which relates the cerebral blood flow to the Blood Oxygen Level Dependent (BOLD) signal measured using functional Magnetic Resonance Imaging (fMRI). Through some numerical simulations, the properties of the fractional model are explained and some preliminary comparisons to a real BOLD data set are provided. © 2014 IEEE.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Applied Mathematics and Computational Science Program
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Conference/Event name:
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Issue Date:
Aug-2014
DOI:
10.1109/EMBC.2014.6944726
Type:
Conference Paper
ISBN:
9781424479290
Appears in Collections:
Conference Papers; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorBelkhatir, Zehoren
dc.contributor.authorLaleg-Kirati, Taous-Meriemen
dc.date.accessioned2015-08-04T07:26:28Zen
dc.date.available2015-08-04T07:26:28Zen
dc.date.issued2014-08en
dc.identifier.isbn9781424479290en
dc.identifier.doi10.1109/EMBC.2014.6944726en
dc.identifier.urihttp://hdl.handle.net/10754/564965en
dc.description.abstractThe neurovascular coupling is a key mechanism linking the neural activity to the hemodynamic behavior. Modeling of this coupling is very important to understand the brain function but it is at the same time very complex due to the complexity of the involved phenomena. Many studies have reported a time delay between the neural activity and the cerebral blood flow, which has been described by adding a delay parameter in some of the existing models. An alternative approach is proposed in this paper, where a fractional system is used to model the neurovascular coupling. Thanks to its nonlocal property, a fractional derivative is suitable for modeling the phenomena with delay. The proposed model is coupled with the first version of the well-known balloon model, which relates the cerebral blood flow to the Blood Oxygen Level Dependent (BOLD) signal measured using functional Magnetic Resonance Imaging (fMRI). Through some numerical simulations, the properties of the fractional model are explained and some preliminary comparisons to a real BOLD data set are provided. © 2014 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleFractional dynamical model for neurovascular couplingen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentApplied Mathematics and Computational Science Programen
dc.identifier.journal2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Societyen
dc.conference.date26 August 2014 through 30 August 2014en
dc.conference.name2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014en
kaust.authorLaleg-Kirati, Taous-Meriemen
kaust.authorBelkhatir, Zehoren
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