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两个同源“扇出-扇入”学习记忆网络中突触可塑性的替代部位。

Alternative sites of synaptic plasticity in two homologous "fan-out fan-in" learning and memory networks.

机构信息

Department of Neurobiology, Life Sciences Institute and the Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem 91904, Israel.

出版信息

Curr Biol. 2011 Nov 8;21(21):1773-82. doi: 10.1016/j.cub.2011.09.011. Epub 2011 Oct 20.

Abstract

BACKGROUND

To what extent are the properties of neuronal networks constrained by computational considerations? Comparative analysis of the vertical lobe (VL) system, a brain structure involved in learning and memory, in two phylogenetically close cephalopod mollusks, Octopus vulgaris and the cuttlefish Sepia officinalis, provides a surprising answer to this question.

RESULTS

We show that in both the octopus and the cuttlefish the VL is characterized by the same simple fan-out fan-in connectivity architecture, composed of the same three neuron types. Yet, the sites of short- and long-term synaptic plasticity and neuromodulation are different. In the octopus, synaptic plasticity occurs at the fan-out glutamatergic synaptic layer, whereas in the cuttlefish plasticity is found at the fan-in cholinergic synaptic layer.

CONCLUSIONS

Does this dramatic difference in physiology imply a difference in function? Not necessarily. We show that the physiological properties of the VL neurons, particularly the linear input-output relations of the intermediate layer neurons, allow the two different networks to perform the same computation. The convergence of different networks to the same computational capacity indicates that it is the computation, not the specific properties of the network, that is self-organized or selected for by evolutionary pressure.

摘要

背景

神经网络的性质在多大程度上受到计算考虑的限制?对参与学习和记忆的脑结构——垂直叶(VL)系统,在两种亲缘关系密切的头足类软体动物——普通章鱼和乌贼中的比较分析,对这个问题给出了一个惊人的答案。

结果

我们表明,在章鱼和乌贼中,VL 都具有相同的简单扇出-扇入连接架构,由相同的三种神经元类型组成。然而,短期和长期突触可塑性和神经调制的位置不同。在章鱼中,突触可塑性发生在扇出谷氨酸能突触层,而在乌贼中,可塑性发生在扇入胆碱能突触层。

结论

这种生理学上的显著差异是否意味着功能上的差异?不一定。我们表明,VL 神经元的生理特性,特别是中间层神经元的线性输入-输出关系,允许这两个不同的网络执行相同的计算。不同网络收敛到相同的计算能力表明,是计算而不是网络的特定性质,是由进化压力自我组织或选择的。

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