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In computer science, binary space partitioning (BSP) is a method for space partitioning which recursively subdivides a Euclidean space into two convex sets by using hyperplanes as partitions. This process of subdividing gives rise to a representation of objects within the space in the form of a tree data structure known as a BSP tree .
The bulk synchronous parallel (BSP) abstract computer is a bridging model for designing parallel algorithms. It is similar to the parallel random access machine (PRAM) model, but unlike PRAM, BSP does not take communication and synchronization for granted. In fact, quantifying the requisite synchronization and communication is an important part ...
Computational neuroscience (also known as theoretical neuroscience or mathematical neuroscience) is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
Richard Caton discovered electrical activity in the cerebral hemispheres of rabbits and monkeys and presented his findings in 1875. [4] Adolf Beck published in 1890 his observations of spontaneous electrical activity of the brain of rabbits and dogs that included rhythmic oscillations altered by light, detected with electrodes directly placed on the surface of the brain. [5]
Brodmann area 43, the subcentral area, is a structurally distinct area of the cerebral cortex defined on the basis of cytoarchitecture. Along with Brodmann Area 1, 2, and 3, Brodmann area 43 is a subdivision of the postcentral region of the brain, [ 1 ] suggesting a somatosensory ('feeling of the body') function.
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Get ready for all of today's NYT 'Connections’ hints and answers for #587 on Saturday, January 18, 2025. Today's NYT Connections puzzle for Saturday, January 18, 2025 The New York Times
Advanced Simulation Library (ASL) is a free and open-source hardware-accelerated multiphysics simulation platform. It enables users to write customized numerical solvers in C++ and deploy them on a variety of massively parallel architectures , ranging from inexpensive FPGAs , DSPs and GPUs [ 1 ] up to heterogeneous clusters and supercomputers.