What can the hippocampal representation of environmental geometry tell us about Hebbian learning?
What can the hippocampal representation of environmental geometry tell us about Hebbian learning?
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DOI：
10.1007/s00422-002-0360-z
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发表时间：
2002-12-01
影响因子：
1.9
通讯作者：
O'Keefe, J
中科院分区：
文献类型：
--
作者：
Lever, C;Burgess, N;O'Keefe, J
海马体在空间表征中的重要性已经得到了充分的证实。这表明，啮齿动物海马网络应该为无监督Hebbian学习的研究提供一个最佳的基板。我们专注于海马位置细胞在形态学上不同的环境中的放电特性。一个硬连线的定量几何模型的个人的地方字段进行审查，并作为框架，了解突触可塑性的额外影响。采用Hebbian学习的智能模型也进行了审查。新的信息提出了关于在实验中使用障碍和不同形状的围墙环境的动态的地方字段可塑性在短期和长期的时间尺度。有人认为，在海马位置细胞表示的稳定性和可塑性的时间动力学方面都表示修改，并通知的性质，突触可塑性的位置细胞模型。我们的研究结果确定了一个潜在的神经基础的长期附带学习的环境，并提供了强有力的约束方式的赫布设想的细胞组装的无监督学习可能会发生在海马。
The importance of the hippocampus in spatial representation is well established. It is suggested that the rodent hippocampal network should provide an optimal substrate for the study of unsupervised Hebbian learning. We focus on the firing characteristics of hippocampal place cells in morphologically different environments. A hard-wired quantitative geometric model of individual place fields is reviewed and presented as the framework in which to understand the additional effects of synaptic plasticity. Existent models employing Hebbian learning are also reviewed. New information is presented regarding the dynamics of place field plasticity over short and long time scales in experiments using barriers and differently shaped walled environments. It is argued that aspects of the temporal dynamics of stability and plasticity in the hippocampal place cell representation both indicate modifications to, and inform the nature of, the synaptic plasticity in place cell models. Our results identify a potential neural basis for long-term incidental learning of environments and provide strong constraints for the way the unsupervised learning in cell assemblies envisaged by Hebb might occur within the hippocampus.