Functional significance of long-term potentiation for sequence learning and prediction
Functional significance of long-term potentiation for sequence learning and prediction
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DOI：
10.1093/cercor/6.3.406
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发表时间：
1996-05-01
期刊：
影响因子：
3.7
通讯作者：
Blum, KI
中科院分区：
文献类型：
--
作者：
Abbott, LF;Blum, KI
群体编码，其中具有广泛和重叠的放电率调谐曲线的神经元共同编码关于刺激的信息，是感觉系统的共同特征。我们使用解码方法和NMDA介导的LTP诱导的测量特性来研究这种编码阵列的神经元之间突触的长时程增强的影响。我们发现，由于NMDA介导的LTP诱导的时间不对称性，最初代表感觉输入的当前值的神经元阵列中的放电模式在训练后将提供对该输入的基于经验的预测，我们计算这种预测如何产生并取决于训练经验。我们还展示了如何编码的预测可以用来生成学习的运动序列，如肢体的运动。这涉及到一种由运动反应驱动的新型记忆回忆，以便它以适合正在执行的任务的速度自动生成新信息。
Population coding, where neurons with broad and overlapping firing rate tuning curves collectively encode information about a stimulus, is a common feature of sensory systems, We use decoding methods and measured properties of NMDA-mediated LTP induction to study the impact of long-term potentiation of synapses between the neurons of such a coding array. We find that, due to a temporal asymmetry in the induction of NMDA-mediated LTP, firing patterns in a neuronal array that initially represent the current value of a sensory input will, after training, provide an experienced-based prediction of that input instead, We compute how this prediction arises from and depends on the training experience. We also show how the encoded prediction can be used to generate learned motor sequences, such as the movement of a limb. This involves a novel form of memory recall that is driven by the motor response so that it automatically generates new information at a rate appropriate for the task being performed.