Nonlinear Transfer Entropy to Assess the Neurovascular Coupling in Premature Neonates

• Published in: Advances in experimental medicine and biology Vol. 1232; pp. 11 - 17
• Main Authors: Hendrikx, Dries, Thewissen, Liesbeth, Smits, Anne, Naulaers, Gunnar, Allegaert, Karel, Van Huffel, Sabine, Caicedo, Alexander
• Format: Book Chapter Journal Article
• Language: English
• Published: Cham Springer International Publishing 2020
• Series: Advances in Experimental Medicine and Biology
• Subjects: Adult; Brain - physiopathology; Brain Diseases - diagnosis; Brain Diseases - physiopathology; EEG; Electroencephalography; Entropy; Humans; Infant, Newborn; Neurometabolic Coupling (NMC); Neurovascular Coupling - physiology; NIRS; Premature Neonates; Spectroscopy, Near-Infrared; Transfer Entropy (TE); NIRS; Transfer Entropy (TE); Neurometabolic Coupling (NMC); EEG; Premature Neonates
• ISBN: 3030344592; 9783030344597
• ISSN: 0065-2598; 2214-8019
• DOI: 10.1007/978-3-030-34461-0_2

In the adult brain, it is well known that increases in local neural activity trigger changes in regional blood flow and, thus, changes in cerebral energy metabolism. This regulation mechanism is called neurovascular coupling (NVC). It is not yet clear to what extent this mechanism is present in the premature brain. In this study, we explore the use of transfer entropy (TE) in order to compute the nonlinear coupling between changes in brain function, assessed by means of EEG, and changes in brain oxygenation, assessed by means of near-infrared spectroscopy (NIRS). In a previous study, we measured the coupling between both variables using a linear model to compute TE. The results indicated that changes in brain oxygenation were likely to precede changes in EEG activity. However, using a nonlinear and nonparametric approach to compute TE, the results indicate an opposite directionality of this coupling. The source of the different results provided by the linear and nonlinear TE is unclear and needs further research. In this study, we present the results from a cohort of 21 premature neonates. Results indicate that TE values computed using the nonlinear approach are able to discriminate between neonates with brain abnormalities and healthy neonates, indicating a less functional NVC in neonates with brain abnormalities.