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LTD windows of the STDP learning rule and synaptic connections having a large transmission delay enable robust sequence learning amid background noise

机译:STDP学习规则的LTD窗口和具有较大传输延迟的突触连接可在背景噪声中实现强大的序列学习

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摘要

Spike-timing-dependent synaptic plasticity (STDP) is a simple and effective learning rule for sequence learning. However, synapses being subject to STDP rules are readily influenced in noisy circumstances because synaptic conductances are modified by pre- and postsynaptic spikes elicited within a few tens of milliseconds, regardless of whether those spikes convey information or not. Noisy firing existing everywhere in the brain may induce irrelevant enhancement of synaptic connections through STDP rules and would result in uncertain memory encoding and obscure memory patterns. We will here show that the LTD windows of the STDP rules enable robust sequence learning amid background noise in cooperation with a large signal transmission delay between neurons and a theta rhythm, using a network model of the entorhinal cortex layer II with entorhinal-hippocampal loop connections. The important element of the present model for robust sequence learning amid background noise is the symmetric STDP rule having LTD windows on both sides of the LTP window, in addition to the loop connections having a large signal transmission delay and the theta rhythm pacing activities of stellate cells. Above all, the LTD window in the range of positive spike-timing is important to prevent influences of noise with the progress of sequence learning.
机译:尖峰时序依赖的突触可塑性(STDP)是序列学习的一种简单有效的学习规则。但是,在嘈杂的环境中,受STDP规则约束的突触很容易受到影响,因为突触电导会在几十毫秒内引起的突触前和突触后突波改变,无论这些突波是否传达信息。大脑各处无处不在的嘈杂射击可能会通过STDP规则引起突触连接的不适当增强,并会导致不确定的记忆编码和模糊的记忆模式。我们将在此处显示STDP规则的LTD窗口,结合使用内嗅皮层II和内海马-海马环连接的网络模型,结合神经元和theta节律之间的大信号传输延迟,在背景噪声中实现强大的序列学习。用于在背景噪声中进行鲁棒序列学习的本模型的重要元素是对称STDP规则,在LTP窗口的两侧均具有LTD窗口,此外环路连接具有较大的信号传输延迟和星状体的theta节奏起搏活动细胞。最重要的是,正尖峰定时范围内的LTD窗口对于防止噪声随着序列学习的进展而产生的影响很重要。

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