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Epihova, G.

Publications and source records attributed to Epihova, G..

2 recordsLinked to original sources

Molecular mechanisms driving divergent development of the human frontal and visual cortex during prenatal development

Key principles of structural brain organization are established very early in fetal development. The frontal cortex is an important hub for integration and control of information, and its integrity and connectivity within the wider neural system are linked to individual differences across multiple cognitive domains and neurodevelopmental conditions. Here we leveraged fetal brain transcriptomics to investigate molecular mechanisms during prenatal development that drive early differences between the two regions at the opposite poles of the physical and representational gradient of the brain - the frontal and visual cortex. We show that the frontal cortex exhibits significantly higher cumulative gene expression for pathways involved in the continued growth and maintenance of larger neurons. These pathways include the gene ontology terms of neuron development and neuronal cell body as well as glucose metabolism important in trophically supporting larger cell sizes. Whole pathways for axonal growth (axonal growth cone, microtubules, filopodia, lamellipodia) and single genes involved in circuit connectivity exhibited increased expression in the frontal cortex. In contrast, in line with the established earlier completion of neurogenesis and lower number of neurons in the anterior cortex, expression of genes involved in DNA replication was significantly lower relative to the visual cortex. We further demonstrate differential cellular composition with higher expression of marker genes for inhibitory neurons in the prenatal frontal cortex. Together, these results suggest that the cellular architecture and composition facilitates earlier connectivity in the frontal cortex which may determine its role as an integrative hub in the global brain organization.

neuroscience↗

Dynamic transient brain states in preschoolers mirror parental report of behavior and emotion regulation

The temporal dynamics of resting-state networks (RSNs) may represent an intrinsic functional repertoire supporting cognitive control performance across the lifespan (Kupis et al., 2021). However, little is known about brain dynamics during the preschool period, which is a sensitive time window for cognitive control development. The fast timescale of synchronization and switching characterizing cortical network functional organization gives rise to quasi-stable patterns (i.e., brain states) that recur over time. These can be inferred at the whole-brain level using Hidden Markov Models (HMMs), an unsupervised machine learning technique that allows the identification of rapid oscillatory patterns at the macro-scale of cortical networks (Vidaurre et al., 2018). The present study used a HMM technique to investigate dynamic neural reconfigurations and their associations with behavioral (i.e., parental questionnaires) and cognitive (i.e., neuropsychological tests) measures in typically developing preschoolers (4-6 years old). We used high density EEG to better capture the fast reconfiguration patterns of the HMM-derived metrics (i.e., switching rates, entropy rates, transition probabilities and fractional occupancies). Our results revealed that the HMM-derived metrics were reliable indices of individual neural variability and differed between boys and girls. However, only brain state transition patterns toward prefrontal and default-mode brain states, predicted differences on parental-report questionnaire scores. Overall, these findings support the importance of resting-state brain dynamics as functional scaffolds for behavior and cognition. Brain state transitions may be crucial markers of individual differences in cognitive control development in preschoolers. KeypointsO_LIHMM-derived metrics are reliable hallmarks of individual neural variability and show gender-related differences. C_LIO_LIBrain state transition patterns toward prefrontal and default-mode brain states predict differences on parental-report questionnaires scores. C_LIO_LIBrain state transitions may be crucial markers of individual differences in cognitive control development in preschoolers. C_LI

neuroscience↗