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Beyond $\ell_1$ sparse coding in V1
Compared to other methods, soft thresholding achieves this level of sparsity at the expense of much degraded reconstruction performance, that more likely than not is not acceptable in biological vision.
Adaptive rewiring of random neural networks generates convergent-divergent units
Convergent-divergent units operate within and between sensory, motor, and cognitive brain regions as their connective core, mediating context-sensitivity to local network units.
Functional and spatial rewiring jointly generate convergent-divergent units in self-organizing networks
The prominence of minimizing wiring distance in the dynamic evolution of the network determines the extent to which the core is encapsulated from the rest of the network, i. e., the context-sensitivity of its computations.
