Extreme distributions in the preconfigured developing brain

Abstract

In the adult brain, structural and functional parameters, such as synaptic sizes and neuronal firing rates, follow right-skewed and heavy-tailed distributions. While this organization is thought of having significant implications, its development is still largely unknown. Here, we address this knowledge gap by investigating a large-scale dataset recorded from the prefrontal cortex (PFC) and the olfactory bulb of mice aged 4-60 postnatal days. We show that firing rates and pairwise correlations have a largely stable distribution shape over age, and that neural activity displays a small-world architecture. Moreover, early brain activity displays an oligarchical organization, i.e., neurons with high firing rates are likely to have hub-like properties. Leveraging neural network modeling, we show that analogously extremely distributed synaptic parameters are necessary to recapitulate the experimental data. Thus, functional and structural parameters in the developing brain are already extremely distributed, suggesting that this organization is preconfigured and not experience-dependent.