Sensory event-related potential morphology predicts age in premature infants

Author:

Zandvoort Coen S.ORCID,van der Vaart MarianneORCID,Robinson Shellie,Usman Fatima,Schmidt Mellado GabrielaORCID,Evans Fry RiaORCID,Worley AlanORCID,Adams Eleri,Slater RebeccahORCID,Baxter LukeORCID,de Vos MaartenORCID,Hartley CarolineORCID

Abstract

AbstractPreterm infants undergo substantial neurosensory development in the first weeks after birth. Infants born prematurely are more likely to have long-term adverse neurological outcomes and early detection of abnormal brain development is essential for timely interventions. We investigated whether sensory-evoked cortical potentials could be used to accurately estimate the age of an infant. Such a model could be used to identify infants who deviate from normal neurodevelopment by comparing the brain age to the infant’s postmenstrual age (PMA). Infants aged between 28- and 40-weeks PMA from a training and test sample (consisting of 101 and 65 recording sessions in 82 and 14 infants, respectively) received trains of approximately 10 visual and 10 tactile stimuli (interstimulus interval approximately 10 seconds). PMA could be predicted accurately from the magnitude of the evoked responses (training set mean absolute error (MAE and 95% confidence intervals): 1.41 [1.14; 1.74] weeks,p= 0.0001; test set MAE: 1.55 [1.21; 1.95] weeks,p= 0.0002. Moreover, we show with two examples that brain age, and the deviations between brain age and PMA, may be biologically and clinically meaningful. By firstly demonstrating that brain age is correlated with a measure known to relate to maturity of the nervous system (based on animal and human literature, the magnitude of reflex withdrawal is used) and secondly by linking brain age to long-term neurological outcomes, we show that brain age deviations are related to biologically meaningful individual differences in the rate of functional nervous system maturation rather than noise generated by the model. In summary, we demonstrate that sensory-evoked potentials are predictive of age in premature infants. It takes less than 5 minutes to collect the stimulus electroencephalographic data required for our model, hence, increasing its potential utility in the busy neonatal care unit. This model could be used to detect abnormal development of infant’s response to sensory stimuli in their environment and may be predictive of later life abnormal neurodevelopmental outcome.

Publisher

Cold Spring Harbor Laboratory

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