Neocortical Self-Structuration as a Basis for Learning

Neocortical connectivity displays striking regularities that self-organize via epigenetic interactions with activity. We construe this self-structuration as a process of spatiotemporal pattern formation in a simple neural network model. Starting from random connections, ordered “synfire-chain” structures and wave-like correlations emerge simultaneously and reinforce each other through cooperation, while the global stability of the network is maintained by competition. Out of broad diffuse contacts and low stochastic firing, select synapses are strengthened and spike correlations increase. We suggest that the concurrent growth of multiple chains defines a mesoscopic scale of neural organization, and view the ontogenetic development of the nervous system as a “self-made tapestry” of synfire patterns, which could provide the basis for compositionality and learning. Index Terms – Synfire Chains, Self-Organization, Hebbian Learning, Spatiotemporal Patterns, Correlations, Compositionality.