Developmental and evolutionary constraints on olfactory circuit selection.
Developmental and evolutionary constraints on olfactory circuit selection.
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DOI：
10.1073/pnas.2100600119
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发表时间：
2022-03-15
影响因子：
11.1
通讯作者：
Latham PE
中科院分区：
文献类型：
--
作者：
Hiratani N;Latham PE
在这项工作中，我们探讨了生物神经网络通过进化优化其结构以进行学习的假设。我们研究了哺乳动物和昆虫的早期嗅觉回路，它们具有相对相似的结构，但在大小上存在巨大的差异。我们近似这些电路作为三层网络和估计，分析，最佳隐藏层的大小与输入层的大小的缩放。我们发现，寿命和基因组中的信息都限制了隐藏层的大小，因此异速生长缩放范围是可能的。然而，在哺乳动物和昆虫中实验观察到的异速生长比例与生物学上合理的值一致。这种分析应该为更深入地理解生物和人工网络铺平道路。在不同的物种中，神经回路表现出显著的规律性，这表明它们的结构是由潜在的最优性原则驱动的。在这里，我们问我们是否可以通过优化神经结构来预测不同物种的神经回路，以使学习尽可能有效。我们专注于嗅觉系统，主要是因为它有一个相对简单的进化保守的结构，因为它的输入和中间层的大小表现出紧密的异速生长缩放。在哺乳动物中，梨状皮质第2层的神经元数量与肾小球（输入单位）数量的3/2次方成比例;在无脊椎动物中，我们发现蘑菇体凯尼恩细胞的数量与肾小球数量的7/2次方成比例。为了理解这些比例律，我们将嗅觉系统建模为三层非线性神经网络，并分析优化中间层的大小，以便从有限的样本中进行有效的学习。我们发现，如所观察到的，幂律缩放，与指数强烈依赖于样本的数量，从而对寿命。在哺乳动物中观察到的3/2比例与观察到的寿命一致，但在无脊椎动物中观察到的7/2比例则不一致。然而，当嗅觉回路的一部分是遗传指定的，而不是学习，缩放变得陡峭的物种与少数肾小球和恢复无脊椎动物缩放的一致性。这项研究提供了分析洞察的原则，异速生长缩放跨物种和人工网络的最佳架构。
In this work, we explore the hypothesis that biological neural networks optimize their architecture, through evolution, for learning. We study early olfactory circuits of mammals and insects, which have relatively similar structure but a huge diversity in size. We approximate these circuits as three-layer networks and estimate, analytically, the scaling of the optimal hidden-layer size with input-layer size. We find that both longevity and information in the genome constrain the hidden-layer size, so a range of allometric scalings is possible. However, the experimentally observed allometric scalings in mammals and insects are consistent with biologically plausible values. This analysis should pave the way for a deeper understanding of both biological and artificial networks. Across species, neural circuits show remarkable regularity, suggesting that their structure has been driven by underlying optimality principles. Here we ask whether we can predict the neural circuitry of diverse species by optimizing the neural architecture to make learning as efficient as possible. We focus on the olfactory system, primarily because it has a relatively simple evolutionarily conserved structure and because its input- and intermediate-layer sizes exhibit a tight allometric scaling. In mammals, it has been shown that the number of neurons in layer 2 of piriform cortex scales as the number of glomeruli (the input units) to the 3/2 power; in invertebrates, we show that the number of mushroom body Kenyon cells scales as the number of glomeruli to the 7/2 power. To understand these scaling laws, we model the olfactory system as a three-layer nonlinear neural network and analytically optimize the intermediate-layer size for efficient learning from limited samples. We find, as observed, a power-law scaling, with the exponent depending strongly on the number of samples and thus on longevity. The 3/2 scaling seen in mammals is consistent with observed longevity, but the 7/2 scaling in invertebrates is not. However, when a fraction of the olfactory circuit is genetically specified, not learned, scaling becomes steeper for species with a small number of glomeruli and recovers consistency with the invertebrate scaling. This study provides analytic insight into the principles underlying both allometric scaling across species and optimal architectures in artificial networks.
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影响因子：
7.7
作者：
Aso Y;Hattori D;Yu Y;Johnston RM;Iyer NA;Ngo TT;Dionne H;Abbott LF;Axel R;Tanimoto H;Rubin GM
通讯作者：
Rubin GM
DOI：
10.1523/jneurosci.2753-12.2013
发表时间：
2013-02-27
期刊：
The Journal of neuroscience : the official journal of the Society for Neuroscience
影响因子：
--
作者：
Barak O;Rigotti M;Fusi S
通讯作者：
Fusi S
影响因子：
2.9
作者：
AMARI, S;MURATA, N
通讯作者：
MURATA, N
影响因子：
8.6
作者：
BARKAI, N;SEUNG, HS;SOMPOLINSKY, H
通讯作者：
SOMPOLINSKY, H
影响因子：
7.5
作者：
BARRON, AR
通讯作者：
BARRON, AR