10 papers analyzed
These studies suggest that brain development is studied and modeled using graph-theoretical modeling, connectionist models, longitudinal neuroimaging, brain organoids, developmental neuroscience integration, deep collaborative learning, mathematical models, and the NDDL approach.
Studying and modeling brain development is crucial for understanding the emergence of cognitive functions and the origins of developmental disorders. Various methodologies, including neuroimaging, computational modeling, and in vitro techniques, have been employed to explore the structural and functional changes in the brain from prenatal stages through early childhood.
Graph-Theoretical Network Modeling:
Connectionist and Computational Models:
Individual Differences in Brain Development:
Brain Organoids:
Neuroimaging Techniques:
Deep Collaborative Learning (DCL):
Mathematical and Statistical Models:
Discriminative Dictionary Learning:
The study and modeling of brain development employ a diverse array of methodologies, from graph-theoretical and connectionist models to advanced neuroimaging and brain organoids. These approaches collectively enhance our understanding of the structural and functional evolution of the brain, the heterogeneity in developmental patterns, and the potential for predicting cognitive and mental health outcomes. As technologies and models advance, they offer deeper insights into the intricate processes underlying brain development and open new avenues for early interventions and therapeutic strategies.
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