An analytical approach to neuronal connectivity |
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Authors: | L da F?Costa Email author" target="_blank">M S?BarbosaEmail author |
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Institution: | (1) Cybernetic Vision Research Group, GII-IFSC, Universidade de São Paulo, Caixa Postal 369, São Carlos, SP, 13560-970, Brasil |
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Abstract: | This paper describes how to analytically characterize the
connectivity of neuromorphic networks taking into account the
morphology of their elements. By assuming that all neurons have the
same shape and are regularly distributed along a two-dimensional
orthogonal lattice with parameter , we obtain the exact
number of connections and cycles of any length by applying
convolutions and the respective spectral density derived from the
adjacency matrix. It is shown that neuronal shape plays an
important role in defining the spatial distribution of synapses in
neuronal networks. In addition, we observe that neuromorphic
networks typically present an interesting property where the pattern
of connections is progressively shifted along the spatial domain for
increasing connection lengths. This arises from the fact that the
axon reference point usually does not coincide with the cell center
of mass of neurons. Morphological measurements for characterization
of the spatial distribution of connections, including the adjacency
matrix spectral density and the lacunarity of the connections, are
suggested and illustrated. We also show that Hopfield networks with
connectivity defined by different neuronal morphologies, which are
quantified by the analytical approach proposed herein, lead to
distinct performances for associative recall, as measured by the
overlap index. The potential of our approach is illustrated for
digital images of real neuronal cells. |
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Keywords: | |
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