Automated Reconstruction of Neural Tissue and the Role of Large-Scale Simulation

Keywords DIADEM.High-throughput.Neuralreconstruction.Neural tissue.Simulation.Compartmentalmodeling.Hodgkin Huxley model.Structural modeling.Developmental modeling.Neuron growth.Parallelcomputing.Data decomposition.Neural Tissue Simulator.Blue GeneThe brain implements a myriad of global brain functions tosupport adaptive behaviors. Despite their seeming innumer-ability, these emerge from combinations of lower levelfunctions implemented by a relatively small set of braintissues. Evidence from brain imaging studies shows thatspatiotemporal patterns of activations across different braintissues correlate with brain function (and hence with anorganism’s behavior). To support a diversity of globalfunctions, gross connections between brain tissues, whilestructurally static, must undergo modulation. The strengthof this modulation can define functional boundaries andinterfaces between brain tissues: wherever functionalrelationships between brain regions are highly modulated,tissue boundaries occur.Tissue-level functions, while also diverse, are morestereotyped than global brain functions. Similar to spatio-temporal modulation and recombination of tissue activa-tion, variation and recombination of familiar structuralelements of the brain (neurons and their connections,synapses) generate tissue-level functions. Unlike otherorgans’ gross morphological specializations of singletissues (e.g., muscle, bone) brain specialization yieldsdistinct tissues derived from stationary statistical combina-tions of a variety of neuron and synapse types in space,which we define as microcircuitry. Measurable, consistentpatterning of microcircuitry across a tissue and in differentorganisms (i.e., stereotypy) further defines a tissue’sboundaries: wherever patterning changes abruptly, onetissue ends and another begins.Shepherd defined microcircuits abstractly and indepen-dent of neural tissues, based on simple computations theymight implement.

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