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coincidence detection in neurobiology
Coincidence detection in the context of neurobiology is a process by which a neuron or a neural circuit can encode information by detecting the occurrence of temporally close but spatially distributed input signals. Coincidence detectors influence neuronal information processing by reducing temporal jitter, reducing spontaneous activity, and forming associations between separate neural events. This concept has led to a greater understanding of neural processes and the formation of computational maps in the brain.
==Principles of coincidence detection==
Coincidence detection relies on separate inputs converging on a common target. Consider a basic neural circuit with two input neurons, A and B, that have excitatory synaptic terminals converging on a single output neuron, C (Fig. 1). If each input neuron's EPSP is subthreshold for an action potential at C, then C will not fire unless the two inputs from A and B are temporally close together. Synchronous arrival of these two inputs may push the membrane potential of a target neuron over the threshold required to create an action potential. If the two inputs arrive too far apart, the depolarization of the first input may have time to drop significantly, preventing the membrane potential of the target neuron from reaching the action potential threshold. This example incorporates the principles of spatial and temporal summation. Furthermore, coincidence detection can reduce the jitter formed by spontaneous activity. While random sub-threshold stimulations by neuronal cells may not often fire coincidentally, coincident synaptic inputs derived from a unitary external stimulus will ensure that a target neuron fires as a result of the stimulus.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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