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Synaptic computation

机译:突触计算

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Neurons are often considered to be the computational engines of the brain, with synapses acting solely as conveyers of information. But the diverse types of synaptic plasticity and the range of timescales over which they operate suggest that synapses have a more active role in information processing. Long-term changes in the transmission properties of synapses provide a physiological substrate for learning and memory, whereas short-term changes support a variety of computations. By expressing several forms of synaptic plasticity, a single neuron can convey an array of different signals to the neural circuit in which it operates.
机译:神经元通常被认为是大脑的计算引擎,而突触仅充当信息的传递者。但是,突触可塑性的不同类型及其作用的时标范围表明,突触在信息处理中具有更积极的作用。突触传递特性的长期变化为学习和记忆提供了生理基础,而短期变化则支持多种计算。通过表达几种形式的突触可塑性,单个神经元可以将一系列不同的信号传递到其运行的神经回路。

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