# Early Signatures of Brain Injury in the Preterm Neonatal EEG
## 2 Materials and Methods
### Micro-Scale Sharp-Wave EEG Waveforms--An HI Biomarker  
We have previously shown that micro-scale sharp-wave EEG patterns with amplitudes between 20-80 uV and a duration between 70 and 250 ms (frequency range: 4 to 14.3 Hz, in the \(\theta\) (4-8 Hz), \(\alpha\) (8-12 Hz), and lower-beta \(\beta\) band (i.e., 12-14.3 Hz)) were superimposed on a suppressed EEG background, within the latent phase of fetal sheep data (103 \(\pm\) 1 days, human brain maturation equivalent \(\sim\)28-30 weeks) which are a reliable marker for hypoxic-ischemic encephalopathy (HIE) (see Figure 1c,d) [6, 15]. We have shown that EEG sharp-waves can help to predict the latent phase of injury after an HI insult, where a larger number of sharp-waves within the first 30 min post-HI is associated with greater subcortical neuronal survival in the caudate nucleus (r = 0.80). Conversely, greater numbers of sharp-wave activity between 2-4 h after HI are associated with more damage and a reduced neuronal survival in the same subcortical region (r = \(-\)0.83) [6]. This experimental observation highlights the significance of these micro-scale EEG waveforms in a suppressed background as early indicators of HIE, emphasizing the necessity to explore their presence in bedside monitoring, at birth.  
This study investigated the potential \"translatability\" of micro-scale sharp wave EEG patterns within the critical early postnatal period, with a specific focus on documenting their presence within clinical recordings derived from profoundly premature neonates. To achieve this, we examined the comparability of EEG power signal behaviour as well as these sharp-wave EEG patterns within neonatal clinical recordings, compared to our animal data.  
Here, in a preliminary analysis of a subset (n = 7) of an observational cohort study of EEG recordings in 33 extremely preterm infants born at \(\leq\)28 weeks estimated gestation, we investigated whether the micro-scale EEG waveforms previously reported in our fetal sheep models were also present within the first 6 h after birth. The micro-scale sharp waves were initially detected using our deep learning-based sharp wave identifiers from animal experiments [15, 16]. Sharp-waves were automatically identified throughout the entire duration of EEG recordings, starting from the initiation of neonatal recording and continuing 6 h post-birth. Similarly, sharp-waves were automatically identified throughout the entire duration of EEG post-hypoperfusion phase (30 min after the HI event), extending for 6 h post-HI, in the preterm fetal sheep data.  
A total of 5191 sharp waves were extracted from the clinical EEG set, while 6086 sharp waves were extracted from the experimental EEG set in the fetal sheep data. Sharp wave patterns from each baby and fetal sheep were centralized at their peaks. The sharp waves per subject were then averaged, and correlations were calculated between the average pattern of all subjects within the neonatal and fetal sheep groups. The matrix of correlation coefficients between the average of sharp patterns in all subjects was calculated using Matlab's 'corrcoef' function.  
Here we used Pearson's correlation coefficient (r, between \(-\)1 to +1) to report the correlation coefficient (i.e., the strength in the 'degree of similarity'--morphological characteristics) between the average of micro-scale sharp-waves seen in our fetal sheep models post-HI, and the'similar' patterns observed in the early hours (<6 h) of birth.  
Thus, the current paper focuses on the'signal observation' aspects of the work and does not investigate the potential correlations between the quantifications and timing of these EEG patterns with neonatal outcomes.