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Mahmoudzadeh, M.

Publications and source records attributed to Mahmoudzadeh, M..

2 recordsLinked to original sources

Detection of regularities in auditory sequences before and at term-age in human neonates

During the last trimester of gestation, fetuses and preterm neonates begin to respond to sensory stimulation and to discover the structure of their environment. Yet, neuronal migration is still ongoing. This late migration notably concerns the supra-granular layers neurons, which are believed to play a critical role in encoding predictions and detecting regularities. In order to gain a deeper understanding of how the brain processes and perceives regularities during this stage of development, we conducted a study in which we recorded event-related potentials (ERP) in 31-wGA preterm and full-term neonates exposed to alternating auditory sequences (e.g. "ba ga ba ga ba"), when the regularity of these sequences was violated by a repetition (e.g., "ba ga ba ga ga"). We compared the ERPs in this case to those obtained when violating a simple repetition pattern ("ga ga ga ga ga" vs "ga ga ga ga ba"). Our results indicated that both preterm and full-term neonates were able to detect violations of regularity in both types of sequences, indicating that as early as 31 weeks gestational age, human neonates are sensitive to the conditional statistics between successive auditory elements. Full-term neonates showed an early and similar mismatch response (MMR) in the repetition and alternating sequences. In contrast, 31-wGA neonates exhibited a two-component MMR. The first component which was only observed for simple sequences with repetition, corresponded to sensory adaptation. It was followed much later by a deviance-detection component that was observed for both alternation and repetition sequences. This pattern confirms that MMRs detected at the scalp may correspond to a dual cortical process and shows that deviance detection computed by higher-level regions accelerates dramatically with brain maturation during the last weeks of gestation to become indistinguishable from bottom-up sensory adaptation at term. HighlightsO_LIStarting at 31 wGA, neonates are sensitive to conditional statistics between successive events. C_LIO_LIThe MisMatch Response detected at the scalp may correspond to a dual cortical process C_LIO_LIThe prediction error signal accelerates during the third trimester of gestation C_LIO_LIIt overlaps with the phenomenon of sensory adaptation at term age C_LI

neuroscience↗

Multiscale entropy analysis of combined EEG-fNIRS measurement in preterm neonates

In nature, biological systems such as the human brain are characterized by complex and non-linear dynamics. One way of quantifying signal complexity is Multiscale Entropy (MSE), which is suitable for structures with long-range correlation at different time scales. In developmental neuroscience, MSE can be taken as an index of brain maturation, and can differentiate between healthy and pathological development. In our current work, we explored the developmental trends of MSE on the basis of 30 simultaneous EEG - fNIRS recordings in premature infants between 27 and 34 weeks of gestational age (wGA). To explore potential factors impacting MSE, we determined the relation between MSE and the EEG Power Spectrum Density (PSD) and Spontaneous Activity Transients (SATs). As a result, via wGA, the MSE calculated on the EEG increases, thus reflecting the maturational processes in the brain networks, whereas in the fNIRS, MSE decreases, which might indicate a maturation of the brain blood supply. Moreover, we propose that the EEG power in the beta band (13-30 Hz) might be the main contributor to MSE in the EEG. Finally, we highlight the importance of SATs in determining MSE as calculated from the fNIRS recordings. HighlightsBiological systems show complex and non-linear dynamics. With Multiscale Entropy (MSE) we studied simultaneous EEG-fNIRS in premature infants. MSE in the EEG increases over gestational age, MSE in the fNIRS decreases. EEG power spectrum density and spontaneous activity transients contribute to MSE.

neuroscience↗