Abstract Early adversity can change educational, cognitive, and mental health outcomes. However, the neural processes through which early adversity exerts these effects remain largely unknown. We used generative network modelling of the mouse connectome to test whether unpredictable postnatal stress shifts the constraints that govern the formation of the structural connectome. A model that trades off the wiring cost of long-distance connections with topological homophily (i.e. links between regions with shared neighbours) generated simulations that replicate the organisation of the rodent connectome. The imposition of early life adversity significantly shifted the best-performing parameter combinations toward zero, heightening the stochastic nature of the generative process. Put simply, unpredictable postnatal stress changes the economic constraints that shape network formation, introducing greater randomness into the structural development of the brain. While this change may constrain the development of cognitive abilities, it could also reflect an adaptive mechanism. In other words, neural development could harness heightened stochasticity to make networks more robust to perturbation, thereby facilitating effective responses to future threats and challenges. Significance statement Children who experience adversity early in life – such as chronic poverty or abuse – show numerous neural differences that are linked to poorer cognition and mental health later in life. To effectively mitigate the burden of adversity, it is critical to identify how these differences arise. In this paper, we use computational modelling to test whether growing up in an impoverished and unpredictable environment changes the development of structural connections in the mouse brain. We found that early adversity appears to introduce more stochasticity in the formation of neural architecture. Our findings point to a potential mechanism for how early adversity could change the course of child development.

Early adversity changes the economic conditions of structural brain network organisation