Volume 16 Supplement 1
Self-organization of complex cortex-like wiring in a spiking neural network model
© Miner and Triesch 2015
Published: 4 December 2015
Understanding the structure and dynamics of cortical connectivity is vital to understanding cortical function. Experimental data strongly suggest that local recurrent connectivity in the cortex is significantly non-random, exhibiting above-chance bidirectionality, an overrepresentation of certain triangular motifs, and a heavy-tailed distribution of synaptic efficacies . Additional evidence suggests a significant distance dependency to connectivity over a local scale of a few hundred microns , and particular patterns of synaptic turnover dynamics . It is currently not understood how many of these non-random features arise. Gaining understanding, then, of the processes that lead to these complexities would provide valuable insights into the development and computational functionality of the cortex. While previous work has attempted to model some of the individual features of local cortical wiring, there is no model that comprehensively begins to account for all of them.
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