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Content available remote An Improved Boolean Circuit for Maximum Matching in a Convex Bipartite Graph
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EN
The Boolean circuit is a simple and realistic model for parallel computation. Chung and Lee considered the problem of finding a maximum matching in a convex bipartite graph, which has two sets of vertices, A and B, such that for any vertex v of A, the neighbors of v in B are contiguous. They gave a Boolean circuit for the problem in O(log2 n +lognźloglognźlogb) depth and O(bn3) size, where n is the number of vertices in set A of the convex bipartite graph and b is the number of bits representing a vertex. Using Boolean circuits of prefix computation, odd-even merge, and some other parallel techniques, we present an improved Boolean circuit for the same problem in O(log2nź(logb+loglogn)) depth and O(bn2logn) size.
EN
Fluorescence-based synapse detection enables dense, high-throughput and multichannel analysis of synapse properties and connections in brain tissue. Using fluorogen activating proteins (FAPs) or YFP coupled to a neuroligin tether, we have developed genetically-encoded reagents for fluorescence-labeling of post-synaptic sites. Sparse viral expression of YFP-post or FAP-post in mouse somatosensory (barrel) cortex enables compartment-specific quantitation of synapses across the surface of an individual neuron, as well as cell-type specific presynaptic input assignment. High-resolution, 3D confocal stacks were used for semi-automated, high-throughput assignment of YFP-post and FAP-post synaptic puncta across specific neuron cell-types. Using transgenic mice where specific subtypes of presynaptic inhibitory neurons were fluorescently-labeled with YFP, far red-fluorescence of FAP-post synaptic puncta and dTomato-filled postsynaptic pyramidal cells could be aligned to specific presynaptic partners using tricolor colocalization. Fluorescent post-synaptic puncta properties were evaluated to generate metrics reflecting synapse location, size, shape, and fluorescence intensity that could be used to differentiate synapses from different inhibitory sources. We used these quantitative metrics to evaluate changes in inhibitory inputs after sensory association training for pyramidal neurons in barrel cortex. Genetically-encoded fluorescence-based synaptic labeling reagents provide a powerful approach to enable high-throughput and automated analysis of synapse organization in brain tissue across development, learning, and disease states.
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