Comparison of computational models of familiarity discrimination in the perirhinal cortex
Comparison of computational models of familiarity discrimination in the perirhinal cortex
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DOI：
10.1002/hipo.10093
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发表时间：
2003-01-01
期刊：
影响因子：
3.5
通讯作者：
Brown, MW
中科院分区：
文献类型：
--
作者：
Bogacz, R;Brown, MW
本研究比较了已发表的嗅周皮层熟悉性辨别的计算模型的效率和可行性。大量证据表明，嗅周皮层既涉及识别记忆的熟悉性辨别方面，也涉及与完整刺激的表征有关的感知功能（即，对象标识）。已发表的关于嗅周皮层如何进行熟悉性辨别的模型可以分为两组。第一组假设一部分嗅周神经元形成专门用于熟悉性辨别的网络（这些模型可能基于赫布或反赫布突触可塑性）。与此相反，第二组假设，熟悉的歧视和学习表示完整的刺激内进行一个单一的组合网络。这项研究确定，当向熟悉性辨别网络提供输入的神经元的反应是相关的（如实验数据所示）时，基于反赫布学习的专门网络可以识别先前发生的更多刺激（即，比基于Hebbian学习的专门网络的容量大数千倍。目前公布的组合模型不学习最佳的刺激表示（它们不完全提取统计独立的特征），因此它们的能力甚至低于基于Hebbian学习的专门模型。因此，迄今为止公布的组合模型比基于反赫布学习的专门模型效率低得多。本研究还比较了模型的一致性与实验观察有关什么是已知的突触可塑性在嗅周皮层和其神经元的反应。许多理论上重要的参数仍未确定，并建议实验提供关键的信息，用于细化和区分各种模型。然而，上述理论论点和目前公布的数据支持存在一个专门用于熟悉歧视的单独网络。
This study compares the efficiency and plausibility of published computational models of familiarity discrimination in the perirhinal cortex. Substantial evidence indicates that the perirhinal cortex is involved in both the familiarity discrimination aspect of recognition memory and in perceptual functions involved with representations of complete stimuli (i.e., object identification). Published models of how the perirhinal cortex may perform familiarity discrimination can be divided into two groups. The first group assumes that a proportion of perirhinal neurons form a network specialised just for familiarity discrimination (these models may be based on Hebbian or anti-Hebbian synaptic plasticity). In contrast, the second group assumes that both familiarity discrimination and learning representations of complete stimuli are performed within a single combined network. This study establishes that when the responses of neurons that provide input to the familiarity discrimination network are correlated (as indicated by experimental data), specialised networks based on anti-Hebbian learning may recognise the previous occurrence of many more stimuli (i.e., have a capacity up to thousands of times larger) than specialised networks based on Hebbian learning. The currently published combined models do not learn an optimal stimulus representation (they do not fully extract statistically independent features), and hence their capacities are even lower than those of the specialised models based on Hebbian learning. Hence, the combined models published thus far are critically less efficient than the specialised models based on anti-Hebbian learning. This study also compares the consistency of the models with experimental observations concerning what is known of synaptic plasticity in the perirhinal cortex and the responses of its neurons. Many theoretically important parameters remain undetermined, and experiments are suggested to provide information critical for refining and distinguishing between the various models. However, the above theoretical arguments and currently published data favour the existence of a separate network specialised for familiarity discrimination.