Application of a "staggered walk" algorithm for generating large-scale morphological neuronal networks.
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.
Department of Computer Science, Stony Brook University, Stony Brook, NY 11794-4400, USA.
Jack
J
Zito
Heraldo
H
Memelli
Kyle G
KG
Horn
Irene C
IC
Solomon
Larry D
LD
Wittie
D000465:Algorithms; D001369:Axons / Q000502:physiology; D009415:Nerve Net / Q000502:physiology*; D016501:Neurites / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D013569:Synapses / Q000502:physiology; D013647:Task Performance and Analysis