Application of a "staggered walk" algorithm for generating large-scale morphological neuronal networks

Authors:
Jack Zito;Heraldo Memelli;Kyle G. Horn;Irene C. Solomon;Larry D. Wittie
Affiliations:
Department of Computer Science, Stony Brook University, Stony Brook, NY;Department of Computer Science and Department of Physiology and Biophysics, Stony Brook University, Stony Brook, NY;Department of Physiology and Biophysics and Program in Neuroscience, Stony Brook University, Stony Brook, NY;Department of Physiology and Biophysics, Stony Brook University, Stony Brook, NY;Department of Computer Science, Stony Brook University, Stony Brook, NY
Venue:
Computational Intelligence and Neuroscience
Year:
2012

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Abstract

Large-scale models of neuronal structures are needed to explore emergent properties of mammalian brains. Because these models have trillions of synapses, a major problem in their creation is synapse placement. Here we present a novel method for exploiting consistent fiber orientation in a neural tissue to perform a highly efficient modified plane-sweep algorithm, which identifies all regions of 3D overlaps between dendritic and axonal projection fields. The first step in placing synapses in physiological models is neurite-overlap detection, at large scales a computationally intensive task. We have developed an efficient "Staggered Walk" algorithm that can find all 3D overlaps of neurites where trillions of synapses connect billions of neurons.