Parameter Sensitivity and Experimental Validation for Fractional-Order Dynamical Modeling of Neurovascular Coupling

Zehor Belkhatir, Fahd Alhazmi, Mohamed Bahloul, Taous-Meriem Laleg-Kirati

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Goal: 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. Due to its nonlocal property, a fractional derivative is suitable for modeling delayed and power-law phenomena. Methods: 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. 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. 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. Conclusions: 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.
Original languageEnglish (US)
Pages (from-to)1-1
Number of pages1
JournalIEEE Open Journal of Engineering in Medicine and Biology
StatePublished - Apr 13 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-04-29
Acknowledgements: The 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.


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