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  • Ala-Kurikka, Tommi; Pospelov, Alexey; Summanen, Milla; Alafuzoff, Aleksander; Kurki, Samu; Voipio, Juha; Kaila, Kai (2021)
    Objective Birth asphyxia (BA) is often associated with seizures that may exacerbate the ensuing hypoxic-ischemic encephalopathy. In rodent models of BA, exposure to hypoxia is used to evoke seizures, that commence already during the insult. This is in stark contrast to clinical BA, in which seizures are typically seen upon recovery. Here, we introduce a term-equivalent rat model of BA, in which seizures are triggered after exposure to asphyxia. Methods Postnatal day 11-12 male rat pups were exposed to steady asphyxia (15 min; air containing 5% O-2 + 20% CO2) or to intermittent asphyxia (30 min; three 5 + 5-min cycles of 9% and 5% O-2 at 20% CO2). Cortical activity and electrographic seizures were recorded in freely behaving animals. Simultaneous electrode measurements of intracortical pH, Po-2, and local field potentials (LFPs) were made under urethane anesthesia. Results Both protocols decreased blood pH to Significance The rate of brain pH recovery has a strong influence on post-asphyxia seizure propensity. The recurring hypoxic episodes during intermittent asphyxia promote neuronal excitability, which leads to seizures only after the suppressing effect of the hypercapnic acidosis is relieved. The present rodent model of BA is to our best knowledge the first one in which, consistent with clinical BA, behavioral and electrographic seizures are triggered after and not during the BA-mimicking insult.
  • O'Toole, John M.; Boylan, Geraldine B.; Lloyd, Rhodri O.; Goulding, Robert M.; Vanhatalo, Sampsa; Stevenson, Nathan J. (2017)
    Aim: To develop a method that segments preterm EEG into bursts and inter-bursts by extracting and combining multiple EEG features. Methods: Two EEG experts annotated bursts in individual EEG channels for 36 preterm infants with gestational age <30 weeks. The feature set included spectral, amplitude, and frequency-weighted energy features. Using a consensus annotation, feature selection removed redundant features and a support vector machine combined features. Area under the receiver operator characteristic (AUC) and Cohen's kappa (K) evaluated performance within a cross-validation procedure. Results: The proposed channel-independent method improves AUC by 4-5% over existing methods (p <0.001, n = 36), with median (95% confidence interval) AUC of 0.989 (0.973-0.997) and sensitivity -specificity of 95.8-94.4%. Agreement rates between the detector and experts' annotations, K = 0.72 (0.36-0.83) and K = 0.65 (0.32-0.81), are comparable to inter-rater agreement, K = 0.60 (0.21-0.74). Conclusions: Automating the visual identification of bursts in preterm EEG is achievable with a high level of accuracy. Multiple features, combined using a data-driven approach, improves on existing single-feature methods. (C) 2017 The Authors. Published by Elsevier Ltd on behalf of IPEM.
  • Stevenson, N. J.; Oberdorfer, L.; Koolen, N.; O'Toole, J. M.; Werther, T.; Klebermass-Schrehof, K.; Vanhatalo, S. (2017)
    Minimally invasive, automated cot-side tools for monitoring early neurological development can be used to guide individual treatment and benchmark novel interventional studies. We develop an automated estimate of the EEG maturational age (EMA) for application to serial recordings in preterm infants. The EMA estimate was based on a combination of 23 computational features estimated from both the full EEG recording and a period of low EEG activity (46 features in total). The combination function (support vector regression) was trained using 101 serial EEG recordings from 39 preterm infants with a gestational age less than 28 weeks and normal neurodevelopmental outcome at 12 months of age. EEG recordings were performed from 24 to 38 weeks post-menstrual age (PMA). The correlation between the EMA and the clinically determined PMA at the time of EEG recording was 0.936 (95% CI: 0.932-0.976; n = 39). All infants had an increase in EMA between the first and last EEG recording and 57/62 (92%) of repeated measures within an infant had an increasing EMA with PMA of EEG recording. The EMA is a surrogate measure of age that can accurately determine brain maturation in preterm infants.
  • Bajo, R.; Pusil, S.; Lopez, M. E.; Canuet, L.; Pereda, E.; Osipova, D.; Maestu, F.; Pekkonen, E. (2015)
    Scopolamine administration may be considered as a psychopharmacological model of Alzheimer's disease (AD). Here, we studied a group of healthy elderly under scopolamine to test whether it elicits similar changes in brain connectivity as those observed in AD, thereby verifying a possible model of AD impairment. We did it by testing healthy elderly subjects in two experimental conditions: glycopyrrolate (placebo) and scopolamine administration. We then analyzed magnetoencephalographic (MEG) data corresponding to both conditions in resting-state with eyes closed. This analysis was performed in source space by combining a nonlinear frequency band-specific measure of functional connectivity (phase locking value, PLV) with network analysis methods. Under scopolamine, functional connectivity between several brain areas was significantly reduced as compared to placebo, in most frequency bands analyzed. Besides, regarding the two complex network indices studied (clustering and shortest path length), clustering significantly decreased in the alpha band while shortest path length significantly increased also in alpha band both after scopolamine administration. Overall our findings indicate that both PLV and graph analysis are suitable tools to measure brain connectivity changes induced by scopolamine, which causes alterations in brain connectivity apparently similar to those reported in AD.