Synthetic Brain Cells and Graph Theory

Yes Semantic Web fans, even the generation of the branching patterns in synthetic brain cells may be based on graph theory. The recent paper “One Rule to Grow Them All: A General Theory of Neuronal Branching and Its Practical Application” published August 5, 2010 in PLoS Computational Biology describes one team’s approach to generating realistically branched brain cell (neuron) structures.

Note: This paper includes research that uses data from the online data repository

Their formalism is inspired by the laws of conservation of cytoplasm and conduction time set out by Ramón y Cajal. How complete is this formalism in determining the shape of a neuron’s branching structures? Does computation also play a role in determining the shape? The authors keep these two questions in mind while exploring their algorithm’s general applicability.

To test their algorithm’s general applicability, the authors synthesize dendritic trees of the starburst amacrine cell of the mammalian retina, hippocampal dentate gyrus granule cells, rat somatosensory cortex layer 2/3, 4 and 5 pyramidal cells, Purkinje cells from the cerebellum, and CA3 pyramidal cells in the hippocampus. They found that these synthetic dendritic trees were indistinguishable from their real counterparts.