Preconfigured architecture of the developing mouse brain

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 to have 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 and the olfactory bulb of mice aged 4–60 postnatal days. We show that firing rates and spike train interactions have a largely stable distribution shape throughout the first 60 postnatal days and that the prefrontal cortex displays a functional small-world architecture. Moreover, early brain activity exhibits an oligarchical organization, where high-firing neurons have hub-like properties. In a neural network model, we show that analogously right-skewed and heavy-tailed synaptic parameters are instrumental to consistently 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. [Display omitted] •Single-unit parameters have a right-skewed and heavy-tailed distribution across development•Synaptic parameters with this type of distribution are needed to stably model the data•In early development, neurons display an oligarchical organization that decreases with age•Inhibitory synaptic plasticity recapitulates the decrease in the oligarchical organization Chini et al. show that the distribution shape of single-unit-related parameters is largely stable across the early development of cortical circuits. Using computational modeling, they predict that synaptic parameters have similar dynamics. Thus, they conclude that this aspect of cortical organization is preconfigured and experience independent.