What does it take to evolve behaviorally complex organisms?
What does it take to evolve behaviorally complex organisms?
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DOI：
10.1016/s0303-2647(02)00140-5
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发表时间：
2003-05-01
期刊：
影响因子：
1.6
通讯作者：
Parisi, D
中科院分区：
文献类型：
--
作者：
Calabretta, R;Di Ferdinando, A;Parisi, D
哪些基因型特征可以解释必须完成许多不同任务的生物体的进化性？行为复杂的生物体的基因型可能更有可能编码模块化神经架构，因为专用于不同任务的神经模块避免了神经干扰，即在学习过程中改变连接权重值的冲突消息的到来。然而，如果各个模块的连接权重是遗传性的，就会引发遗传连锁问题：有利的突变可能落在编码一个神经模块的基因型的一部分上，而不利的突变可能落在编码另一模块的另一部分上。我们证明这可以阻止基因型达到适应性最佳值。这种效应不同于文献中描述的其他连锁效应，我们认为它代表了一类新的遗传约束。通过模拟，我们表明有性生殖可以通过重组单独的模块来缓解遗传连锁问题，所有这些模块都包含有利或不利的突变。我们推测这种效应可能有助于高等生物中有性生殖的分类学流行。除了性重组之外，行为复杂的生物体的遗传连锁问题可以通过将寻找适当的模块化架构的任务委托给进化以及为这些架构寻找适当的连接权重的学习任务来缓解。 (C) 2002 Elsevier Science Ireland Ltd. 保留所有权利。
What genotypic features explain the evolvability of organisms that have to accomplish many different tasks? The genotype of behaviorally complex organisms may be more likely to encode modular neural architectures because neural modules dedicated to distinct tasks avoid neural interference, i.e. the arrival of conflicting messages for changing the value of connection weights during learning. However, if the connection weights for the various modules are genetically inherited, this raises the problem of genetic linkage: favorable mutations may fall on one portion of the genotype encoding one neural module and unfavorable mutations on another portion encoding another module. We show that this can prevent the genotype from reaching an adaptive optimum. This effect is different from other linkage effects described in the literature and we argue that it represents a new class of genetic constraints. Using simulations we show that sexual reproduction can alleviate the problem of genetic linkage by recombining separate modules all of which incorporate either favorable or unfavorable mutations. We speculate that this effect may contribute to the taxonomic prevalence of sexual reproduction among higher organisms. In addition to sexual recombination, the problem of genetic linkage for behaviorally complex organisms may be mitigated by entrusting evolution with the task of finding appropriate modular architectures and learning with the task of finding the appropriate connection weights for these architectures. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.