Sampsa Vanhatalo

The paper examines how cortical bursts influence phase synchrony development in preterm infants and links persistent phase-based connectivity to poorer neurocognitive outcomes.

This study identifies the emergence of a synergistic scaffold in the human brain around birth, influenced by environmental factors and linked to later neurocognitive development.

This study uses Bayesian reduced-rank regression to extract stable neural fingerprints from EEG data of children during nREM sleep, showing increased fingerprint stability with age.

This paper develops a functional brain age (FBA) measure from EEG data in children, showing high accuracy in tracking neurodevelopmental maturation.

This study examines how prematurity affects phase-phase cortical synchrony networks in infants, finding sleep-state and frequency-specific differences linked to clinical outcomes.

This paper develops a deep learning algorithm to detect and classify artefacts in neonatal EEG signals, achieving high accuracy in identifying artefact types and clean EEG periods.

This paper develops a method to track functional brain age in preterm infants using EEG, showing it correlates strongly with postmenstrual age and predicts neurodevelopmental outcomes.