Biology subjects

Zandvoort, C. S.

Publications and source records attributed to Zandvoort, C. S..

3 recordsLinked to original sources

bioRxiv2024

Apnoea suppresses brain activity in infants

Apnoea - the cessation of breathing - is commonly observed in premature infants. These events can reduce cerebral oxygenation and are associated with poorer neurodevelopmental outcomes. However, relatively little is known about how apnoea and shorter pauses in breathing impact brain function in infants, which will provide greater mechanistic understanding of how apnoea affects brain development. We analysed simultaneous recordings of respiration, electroencephalography (EEG), heart rate, and peripheral oxygen saturation in 124 recordings from 118 infants (post-menstrual age: 38.6 {+/-} 2.7 weeks [mean {+/-} standard deviation]) during apnoeas (pauses in breathing greater than 15 seconds) and shorter pauses in breathing between 5 and 15 seconds. EEG amplitude significantly decreased during both apnoeas and shorter pauses in breathing compared with normal breathing periods. Change in EEG amplitude was significantly associated with change in heart rate during apnoea and breathing pauses and, during apnoeas only, with oxygen saturation change. No associations were found between EEG amplitude and pause duration or post-menstrual age. The decrease in EEG amplitude may be a result of the changing metabolism and/or homeostasis following changes in oxygen and carbon dioxide concentrations, which alters the release of neurotransmitters. As apnoeas often occur in premature infants, frequent disruption to brain activity may impact neural development and result in long-term neurodevelopmental consequences.

neuroscience↗

bioRxiv2023

Sensory event-related potential morphology predicts age in premature infants

Preterm 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 infants 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 infants response to sensory stimuli in their environment and may be predictive of later life abnormal neurodevelopmental outcome.

neuroscience↗

bioRxiv2020

Understanding phase-amplitude coupling from bispectral analysis

Two measures of cross-frequency coupling (CFC) are Phase-Amplitude Coupling (PAC) and bicoherence. The estimation of PAC with meaningful bandwidth for the high frequency amplitude is crucial in order to avoid misinterpretations. While recommendations on the bandwidth of PACs amplitude component exist, there is no consensus yet. Here, we show that the earlier recommendations on filter settings lead to estimates which are smeared in the frequency domain, which makes it difficult to distinguish higher harmonics from other types of CFC. We also show that smearing can be avoided with a different choice of filter settings by theoretically relating PAC to bicoherence. To illustrate this, PAC estimates of simulations and empirical data are compared to bispectral analyses. We used simulations replicated from an earlier study and empirical data from human electro-encephalography and rat local field potentials. PACs amplitude component was estimated using a bandwidth with a ratio of (1) 2:1, (2) 1:1, or (3) 0.5:1 relative to the frequency of the phase component. For both simulated and empirical data, PAC was smeared over a broad frequency range and not present when the estimates comprised a 2:1- and 0.5:1-ratio, respectively. In contrast, the 1:1-ratio accurately avoids smearing and results in clear signals of CFC. Bicoherence estimates, which do not smear across frequencies by construction, were found to be essentially identical to PAC calculated with the recommended frequency setting.

neuroscience↗