Dynamics of memory representations in networks with novelty-facilitated synaptic plasticity
Dynamics of memory representations in networks with novelty-facilitated synaptic plasticity
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DOI：
10.1016/j.neuron.2006.08.016
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发表时间：
2006-10-19
期刊：
影响因子：
16.2
通讯作者：
Tsodyks, Misha
中科院分区：
文献类型：
--
作者：
Blumenfeld, Barak;Preminger, Son;Tsodyks, Misha
在区分其他刺激的同时将一些刺激联系起来的能力是生物记忆的一个基本特征。理论模型将记忆识别为神经网络活动的吸引子，学习基于Hebb样突触修饰。我们的分析表明，当网络输入相关时，这种机制会导致过度关联，甚至会导致多个记忆“合并”为一个。为了抵消这种趋势，我们引入了一种学习机制，涉及新奇促进的修改，强调突触的变化成比例的网络输入和存储的记忆之间的差异。这种机制引入了突触修饰对先前获得的记忆的依赖性，从而实现了从绝对辨别到完全合并的广泛的记忆关联。该模型预测，记忆表征应该是敏感的学习顺序，与最近的心理物理学研究的人脸识别和海马位置细胞的电生理实验。建议的机制是兼容的，最近的生物模型新奇促进学习海马电路。
The ability to associate some stimuli while differentiating between others is an essential characteristic of biological memory. Theoretical models identify memories as attractors of neural network activity, with learning based on Hebb-like synaptic modifications. Our analysis shows that when network inputs are correlated, this mechanism results in overassociations, even up to several memories "merging" into one. To counteract this tendency, we introduce a learning mechanism that involves novelty-facilitated modifications, accentuating synaptic changes proportionally to the difference between network input and stored memories. This mechanism introduces a dependency of synaptic modifications on previously acquired memories, enabling a wide spectrum of memory associations, ranging from absolute discrimination to complete merging. The model predicts that memory representations should be sensitive to learning order, consistent with recent psychophysical studies of face recognition and electrophysiological experiments on hippocampal place cells. The proposed mechanism is compatible with a recent biological model of novelty-facilitated learning in hippocampal circuitry.