Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling
<italic>Goal:</italic> Modeling neurovascular coupling is very important to understand brain functions, yet challenging due to the complexity of the involved phenomena. An alternative approach was recently proposed where the framework of fractional-order modeling is employed to character...
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2022-01-01
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| author | Zehor Belkhatir Fahd Alhazmi Mohamed A. Bahloul Taous-Meriem Laleg-Kirati |
| author_facet | Zehor Belkhatir Fahd Alhazmi Mohamed A. Bahloul Taous-Meriem Laleg-Kirati |
| author_sort | Zehor Belkhatir |
| collection | DOAJ |
| description | <italic>Goal:</italic> Modeling neurovascular coupling is very important to understand brain functions, yet challenging due to the complexity of the involved phenomena. An alternative approach was recently proposed where the framework of fractional-order modeling is employed to characterize the complex phenomena underlying the neurovascular. Due to its nonlocal property, a fractional derivative is suitable for modeling delayed and power-law phenomena. <italic>Methods:</italic> In this study, we analyze and validate a fractional-order model, which characterizes 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. <italic>Results:</italic> 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 hemody-namic response, e.g., post-stimulus undershoot. This investigation authenticates the ability and adaptability of the fractional-order framework to characterize a wider range of well-shaped cerebral blood flow responses while preserving low model complexity through a series of unconstrained and constrained optimizations. <italic>Conclusions:</italic> The analysis of the proposed fractional-order model demonstrates that the proposed framework yields a powerful tool for a flexible characterization of the neurovascular coupling mechanism. |
| format | Article |
| id | doaj-art-0f4e8ce4692449819cebd49deba4458c |
| institution | Kabale University |
| issn | 2644-1276 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Engineering in Medicine and Biology |
| spelling | doaj-art-0f4e8ce4692449819cebd49deba4458c2025-08-20T03:30:52ZengIEEEIEEE Open Journal of Engineering in Medicine and Biology2644-12762022-01-013697710.1109/OJEMB.2022.31672819756937Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular CouplingZehor Belkhatir0https://orcid.org/0000-0001-7277-3895Fahd Alhazmi1Mohamed A. Bahloul2https://orcid.org/0000-0002-4510-8029Taous-Meriem Laleg-Kirati3https://orcid.org/0000-0001-5944-0121School of Engineering and Sustainable Development, De Montfort University, Leicester, U.K.Graduate Center and Brooklyn College, City University of New York, New York, NY, USAComputer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi ArabiaComputer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia<italic>Goal:</italic> Modeling neurovascular coupling is very important to understand brain functions, yet challenging due to the complexity of the involved phenomena. An alternative approach was recently proposed where the framework of fractional-order modeling is employed to characterize the complex phenomena underlying the neurovascular. Due to its nonlocal property, a fractional derivative is suitable for modeling delayed and power-law phenomena. <italic>Methods:</italic> In this study, we analyze and validate a fractional-order model, which characterizes 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. <italic>Results:</italic> 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 hemody-namic response, e.g., post-stimulus undershoot. This investigation authenticates the ability and adaptability of the fractional-order framework to characterize a wider range of well-shaped cerebral blood flow responses while preserving low model complexity through a series of unconstrained and constrained optimizations. <italic>Conclusions:</italic> The analysis of the proposed fractional-order model demonstrates that the proposed framework yields a powerful tool for a flexible characterization of the neurovascular coupling mechanism.https://ieeexplore.ieee.org/document/9756937/Neurovascular couplingCerebral blood flowNeural activityFractional-order calculusfractional differentiation ordersSensitivity analysis |
| spellingShingle | Zehor Belkhatir Fahd Alhazmi Mohamed A. Bahloul Taous-Meriem Laleg-Kirati Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling IEEE Open Journal of Engineering in Medicine and Biology Neurovascular coupling Cerebral blood flow Neural activity Fractional-order calculus fractional differentiation orders Sensitivity analysis |
| title | Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling |
| title_full | Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling |
| title_fullStr | Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling |
| title_full_unstemmed | Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling |
| title_short | Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling |
| title_sort | parameter sensitivity and experimental validation for fractional order dynamical modeling of neurovascular coupling |
| topic | Neurovascular coupling Cerebral blood flow Neural activity Fractional-order calculus fractional differentiation orders Sensitivity analysis |
| url | https://ieeexplore.ieee.org/document/9756937/ |
| work_keys_str_mv | AT zehorbelkhatir parametersensitivityandexperimentalvalidationforfractionalorderdynamicalmodelingofneurovascularcoupling AT fahdalhazmi parametersensitivityandexperimentalvalidationforfractionalorderdynamicalmodelingofneurovascularcoupling AT mohamedabahloul parametersensitivityandexperimentalvalidationforfractionalorderdynamicalmodelingofneurovascularcoupling AT taousmeriemlalegkirati parametersensitivityandexperimentalvalidationforfractionalorderdynamicalmodelingofneurovascularcoupling |