At least three basic architectural schemes are present in mammalian brains. The simplest, typified by the cerebellum, uses strictly local wiring in which a few neuronal types form individual “modules” that may be repeated as necessary. Because interaction between modules is restricted to neighbors, it is massively parallel in nature. A different type of network uses random connections. The third architectural scheme, exemplified by the neocortex, combines local modularity with more random, long-range connectivity. In cortical networks, a dynamic balance between excitation and inhibition gives rise to an array of network oscillations. This self-organized, or “spontaneous,” activity gives rise to the appearance of “noise” in an electroencephalogram, which reflects a metastable state. Because local computation can be sensed by large parts of the cortex through long-range connections, and is also modified by this background “noise,” the term “local-global computation” best captures the nature of cortical operations.
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