The quantity of information flowing across neural networks undergoes a dramatic increase across development. The spatial structure of these flows is locked-in during early development, after which there is a substantial temporal correlation in the information flows across recording days.
The brains of many organisms are capable of complicated distributed computation underpinned by a highly advanced information processing capacity. Although substantial progress has been made towards characterising the information flow component of this capacity in mature brains, there is a distinct lack of work characterising its emergence during neural development. This lack of progress has been largely driven by the lack of effective estimators of information processing operations for the spiking data available for developing neural networks. Here, we leverage recent advances in this estimation task in order to quantify the changes in information flow during development. We find that the quantity of information flowing across these networks undergoes a dramatic increase across development. Moreover, the spatial structure of these flows is locked-in during early development, after which there is a substantial temporal correlation in the information flows across recording days. We analyse the flow of information during the crucial periods of population bursts. We find that, during these bursts, nodes undertake specialised computational roles as either transmitters, mediators or receivers of information, with these roles tending to align with their spike ordering - either early, mid or late in the bursts. That the nodes identified as information flow mediators tend to spike mid burst aligns with conjecture that nodes spiking in this position play an important role as brokers of neuronal communication. Finally, it was found that the specialised computational roles occupied by nodes during bursts tend to be locked in early.