Simulation of morphologically realistic neural structures

What is it about?

The present work is related to the synthesis and modeling of morphologically realistic neurons and, from these neurons, is generated neural structures.

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Why is it important?

We show that the extension of the dendritic arborization in the neural structures generated is a determinant factor on the convergence rate and selectivity in the models, and that gradients in the extension of the synaptic arborizations are essentials for the adequate codification of orientations in centric models containing distributed random somata.