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dc.contributor.authorBelkhatir, Zehor
dc.contributor.authorAlhazmi, Fahd
dc.contributor.authorBahloul, Mohamed
dc.contributor.authorLaleg-Kirati, Taous-Meriem
dc.date.accessioned2021-10-26T13:24:43Z
dc.date.available2021-10-26T13:24:43Z
dc.date.issued2021-10-20
dc.identifier.citationBelkhatir, Z., Alhazmi, F., Bahloul, M., & Laleg-Kirati, T.-M. (2021). Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling. doi:10.1101/2021.10.20.465072
dc.identifier.doi10.1101/2021.10.20.465072
dc.identifier.urihttp://hdl.handle.net/10754/672969
dc.description.abstractGoal: Neurovascular coupling is a fundamental mechanism linking neural activity to cerebral blood flow (CBF) response. Modeling this coupling is very important to understand brain functions, yet challenging due to the complexity of the involved phenomena. One key feature that different studies have reported is the time delay that is inherently present between the neural activity and cerebral blood flow, which has been described by adding a delay parameter in standard models. An alternative approach was recently proposed where the framework of fractional-order modeling is employed to characterize the complex phenomena underlying the neurovascular. Thanks to its nonlocal property, a fractional derivative is suitable for modeling delayed and power-law phenomena. Methods: In this study, we analyzed and validated an effective fractional-order for the effective modeling and characterization of the neurovascular coupling mechanism. To show the added value of the fractional order parameters of the proposed model, we perform a parameter sensitivity analysis of the fractional model compared to its integer counterpart. Moreover, the model was validated using neural activity-CBF data related to both event and block design experiments that were acquired using electrophysiology and laser Doppler flowmetry recordings, respectively. Results: The validation results show the aptitude and flexibility of the fractional-order paradigm in fitting a more comprehensive range of well-shaped CBF response behaviors while maintaining a low model complexity. Comparison with the standard integer-order models shows the added value of the fractional-order parameters in capturing various key determinants of the cerebral hemodynamic response, e.g., post-stimulus undershoot. Conclusions: This investigation authenticates the ability and adaptability of the fractional-order framework to characterize a wider range of wellshaped cerebral blood flow responses while preserving low model complexity through a series of unconstrained and constrained optimizations.
dc.description.sponsorshipThe authors would like to thank Prof. Ying Zheng from the University of Sheffield, UK, who provided them with the real data that helped in conducting the work of Section II.
dc.publisherCold Spring Harbor Laboratory
dc.relation.urlhttp://biorxiv.org/lookup/doi/10.1101/2021.10.20.465072
dc.rightsArchived with thanks to Cold Spring Harbor Laboratory
dc.titleParameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling
dc.typePreprint
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.contributor.departmentElectrical and Computer Engineering
dc.contributor.departmentElectrical and Computer Engineering Program
dc.contributor.departmentEstimation, Modeling and ANalysis Group
dc.eprint.versionPre-print
dc.contributor.institutionSchool of Engineering and Sustainable Development, De Montfort University, United Kingdom.
dc.contributor.institutionThe Graduate Center and Brooklyn College, City University of New York (CUNY), New York, United States.
dc.contributor.institutionNational Institute for Research in Digital Science and Technology, France.
kaust.personBahloul, Mohamed
kaust.personLaleg-Kirati, Taous-Meriem
refterms.dateFOA2021-10-26T13:28:37Z


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