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• W4387492852 abstract "Neural phenotypes are the result of probabilistic developmental processes. This means that stochasticity is an intrinsic aspect of the brain as it self-organizes over a protracted period. In other words, while both genomic and environmental factors shape the developing nervous system, another significant-though often neglected-contributor is the randomness introduced by probability distributions. Using generative modeling of brain networks, we provide a framework for probing the contribution of stochasticity to neurodevelopmental diversity. To mimic the prenatal scaffold of brain structure set by activity-independent mechanisms, we start our simulations from the medio-posterior neonatal rich club (Developing Human Connectome Project, n = 630). From this initial starting point, models implementing Hebbian-like wiring processes generate variable yet consistently plausible brain network topologies. By analyzing repeated runs of the generative process (>107 simulations), we identify critical determinants and effects of stochasticity. Namely, we find that stochastic variation has a greater impact on brain organization when networks develop under weaker constraints. This heightened stochasticity makes brain networks more robust to random and targeted attacks, but more often results in non-normative phenotypic outcomes. To test our framework empirically, we evaluated whether stochasticity varies according to the experience of early-life deprivation using a cohort of neurodiverse children (Centre for Attention, Learning and Memory; n = 357). We show that low-socioeconomic status predicts more stochastic brain wiring. We conclude that stochasticity may be an unappreciated contributor to relevant developmental outcomes and make specific predictions for future research." @default.
• W4387492852 created "2023-10-11" @default.
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• W4387492852 date "2023-10-10" @default.
• W4387492852 modified "2023-10-12" @default.
• W4387492852 title "The adaptive stochasticity hypothesis: Modeling equifinality, multifinality, and adaptation to adversity" @default.
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• W4387492852 doi "https://doi.org/10.1073/pnas.2307508120" @default.
• W4387492852 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37816058" @default.
• W4387492852 hasPublicationYear "2023" @default.
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