Compensatory variability in network parameters enhances memory performance in the Drosophila mushroom body.
Compensatory variability in network parameters enhances memory performance in the Drosophila mushroom body.
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DOI：
10.1073/pnas.2102158118
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发表时间：
2021-12-07
影响因子：
11.1
通讯作者：
Lin AC
中科院分区：
文献类型：
--
作者：
Abdelrahman NY;Vasilaki E;Lin AC
神经元之间的变异性如何影响神经回路功能？尽管神经元具有不同的潜在功能，但它的行为可能相似吗？我们在被称为凯尼恩细胞的神经元中解决了这些问题，凯尼恩细胞存储果蝇的嗅觉记忆。凯尼恩细胞在影响它们活动程度的关键特征上有所不同，在果蝇记忆电路的一个模型中，增加了这种神经元间的可变性，使该模型在学习多种气味的值方面表现得更差。然而，如果可变的潜在特征之间的补偿允许Kenyon细胞平均同样活跃，并且我们在真实的Kenyon细胞的解剖中发现了假设的补偿性可变性，那么记忆性能就得到了拯救。这项工作揭示了神经网络中补偿可变性的存在和计算效益。神经电路使用自平衡补偿来实现一致的行为，尽管潜在的内在参数和网络参数存在差异。然而，目前尚不清楚补偿如何调节个体内同一类型神经元群体的可变性，以及这种补偿可能带来什么计算上的好处。我们在果蝇的嗅觉记忆中心--蘑菇体中解决了这些问题。在一个计算模型中，我们表明在稀疏编码条件下，当蘑菇体的主要神经元--Kenyon细胞(KCs)在控制其兴奋性的关键参数上发生实际变化时，记忆性能会下降。然而，如果参数相互补偿以平衡KC平均活动，则在保持现实可变性的同时，存储性能被拯救。这种补偿既可以通过依赖活动的机制实现，也可以通过非活动机制实现。最后，我们表明，我们的模型的补偿机制预测的相关性出现在果蝇的半脑连接体中。这些发现揭示了蘑菇体中的代偿性可变性，并描述了它对联想记忆的计算好处。
How does variability between neurons affect neural circuit function? How might neurons behave similarly despite having different underlying features? We addressed these questions in neurons called Kenyon cells, which store olfactory memories in flies. Kenyon cells differ among themselves in key features that affect how active they are, and in a model of the fly’s memory circuit, adding this interneuronal variability made the model fly worse at learning the values of multiple odors. However, memory performance was rescued if compensation between the variable underlying features allowed Kenyon cells to be equally active on average, and we found the hypothesized compensatory variability in real Kenyon cells’ anatomy. This work reveals the existence and computational benefits of compensatory variability in neural networks. Neural circuits use homeostatic compensation to achieve consistent behavior despite variability in underlying intrinsic and network parameters. However, it remains unclear how compensation regulates variability across a population of the same type of neurons within an individual and what computational benefits might result from such compensation. We address these questions in the Drosophila mushroom body, the fly’s olfactory memory center. In a computational model, we show that under sparse coding conditions, memory performance is degraded when the mushroom body’s principal neurons, Kenyon cells (KCs), vary realistically in key parameters governing their excitability. However, memory performance is rescued while maintaining realistic variability if parameters compensate for each other to equalize KC average activity. Such compensation can be achieved through both activity-dependent and activity-independent mechanisms. Finally, we show that correlations predicted by our model’s compensatory mechanisms appear in the Drosophila hemibrain connectome. These findings reveal compensatory variability in the mushroom body and describe its computational benefits for associative memory.
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影响因子：
7.7
作者：
Li F;Lindsey JW;Marin EC;Otto N;Dreher M;Dempsey G;Stark I;Bates AS;Pleijzier MW;Schlegel P;Nern A;Takemura SY;Eckstein N;Yang T;Francis A;Braun A;Parekh R;Costa M;Scheffer LK;Aso Y;Jefferis GS;Abbott LF;Litwin-Kumar A;Waddell S;Rubin GM
通讯作者：
Rubin GM
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
4.6
作者：
Houston CM;Diamanti E;Diamantaki M;Kutsarova E;Cook A;Sultan F;Brickley SG
通讯作者：
Brickley SG
影响因子：
7.7
作者：
Amin H;Apostolopoulou AA;Suárez-Grimalt R;Vrontou E;Lin AC
通讯作者：
Lin AC
影响因子：
16.2
作者：
Inada, Kengo;Tsuchimoto, Yoshiko;Kazama, Hokto
通讯作者：
Kazama, Hokto