year: 2022/05
paper: https://claude.ai/api/eff8b703-adc5-4a01-b018-eb469e1e3bbc/files/ad23ed6c-e2b2-42a9-a713-750de66d35d3/document_pdf/2022.05.30.494086v1.full.pdf
website:
code:
connections: heavy-tailed, self-organization, neuronal connectivity, clustering, neuronal networks
In networks of neurons, the connections are heavy–tailed, with a small number of neurons
connected much more strongly than the vast majority of pairs.1–6 Yet it remains unclear
whether, and how, such heavy–tailed connectivity emerges from simple underlying mech-
anisms. Here we propose a minimal model of synaptic self–organization: connections are
pruned at random, and the synaptic strength rearranges under a mixture of Hebbian and
random dynamics. Under these generic rules, networks evolve to produce scale–free distri-
butions of connectivity strength..