We propose that hierarchical development along the S–A axis in humans is driven by a cascade of critical periods that culminate in association cortices during adolescence.
We also highlight advances in in vivo neuroimaging and computational approaches that can provide insights into the development of critical period mechanisms along the S–A axis in humans.

Despite the importance of the environment in shaping individual differences in cognitive neurodevelopment, it has been challenging to quantify the many interconnected features of a child's environment ('exposome'). Here, we leverage a large-scale dataset to investigate to demonstrate that the exposome is associated with individual differences in functional brain network organization and cognition. We find that models trained on a single variable capturing a child′s exposome can more accurately and parsimoniously predict future cognitive performance than models trained on a wealth of personalized neuroimaging data. This highlights the importance of childhood environments in shaping neurocognitive development.

Network neuroscience is principally concerned with studying the connectome, the complete description of whole brain connectivity. This connectome is often encoded as a graph of nodes interconnected by edges that can be defined across multiple scales, species, and data modalities. In any case, these descriptions of brain connectivity give rise to complex topology, and understanding how this topology shapes and constrains the brain’s rich repertoire of dynamics is a central goal of network neuroscience. NCT provides a simple yet powerful approach to studying these dynamics that yields insights into how they emerge from this topology.