Memory without feedback in a neural network.
Memory without feedback in a neural network.
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DOI:
10.1016/j.neuron.2008.12.012
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发表时间:
2009-02-26
期刊:
影响因子:
16.2
通讯作者:
Goldman, Mark S.
中科院分区:
文献类型:
--
作者:
Goldman, Mark S.
Memory storage on short time scales is thought to be maintained by neuronal activity that persists after the remembered stimulus is removed. Although previous work suggested that positive feedback is necessary to maintain persistent activity, here it is demonstrated how neuronal responses can instead be maintained by a purely feedforward mechanism in which activity is passed sequentially through a chain of network states. This feedforward form of memory storage is shown to occur both in architecturally feedforward networks and in recurrent networks that nevertheless function in a feedforward manner. The networks can be tuned to be perfect integrators of their inputs, or to reproduce the time-varying firing patterns observed during some working memory tasks but not easily reproduced by feedback-based attractor models. This work illustrates a new mechanism for maintaining short-term memory in which both feedforward and feedback processes interact to govern network behavior.
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