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Frontiers in Neuroinformatics
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Self-referential forces are suffcient to explain different dendritic morphologies

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Abstract

Dendritic morphology constrains brain activity, as it determines first which neuronal circuits are possible and second which dendritic computations can be performed over a neuron's inputs. It is known that a range of chemical cues can infiuence the final shape of dendrites during development. Here, we investigate the extent to which self-referential infiuences, cues generated by the neuron itself, might infiuence morphology. To this end, we developed a phenomenological model and algorithm to generate virtual morphologies, which are then compared to experimentally reconstructed morphologies. In the model, branching probability follows a Galton-Watson process, while the geometry is determined by homotypic forces exerting infiuence on the direction of random growth in a constrained space. We model three such homotypic forces, namely an inertial force based on membrane stiffness, a soma-oriented tropism, and a force of self avoidance, as directional biases in the growth algorithm. With computer simulations we explored how each bias shapes neuronal morphologies. We show that based on these principles, we can generate realistic morphologies of several distinct neuronal types. We discuss the extent to which homotypic forces might infiuence real dendritic morphologies, and speculate about the infiuence of other environmental cues on neuronal shape and circuitry. © 2013 Memelli, Torben-Nielsen and Kozloski.

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Frontiers in Neuroinformatics

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