Evolution leads to a diversity of motion-detection neuronal circuits

被引:0
作者
Tehrani-Saleh, Ali [1 ,2 ]
LaBar, Thomas [2 ,3 ,4 ]
Adami, Christoph [2 ,3 ,4 ,5 ]
机构
[1] Michigan State Univ, Dept Comp Sci & Engn, E Lansing, MI 48824 USA
[2] Michigan State Univ, BEACON Ctr Study Evolut Act, E Lansing, MI 48824 USA
[3] Michigan State Univ, Dept Microbiol & Mol Genet, E Lansing, MI 48824 USA
[4] Michigan State Univ, Program Ecol Evolutionary Biol & Behav, E Lansing, MI 48824 USA
[5] Michigan State Univ, Dept Phys & Astron, E Lansing, MI 48824 USA
来源
2018 CONFERENCE ON ARTIFICIAL LIFE (ALIFE 2018) | 2018年
基金
美国国家科学基金会;
关键词
ORGANIZATION; MAINTENANCE; NETWORKS; NUMBER;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A central goal of evolutionary biology is to explain the origins and distribution of diversity across life. Beyond species or genetic diversity, we also observe diversity in the circuits (genetic or otherwise) underlying complex functional traits. However, while the theory behind the origins and maintenance of genetic and species diversity has been studied for decades, theory concerning the origin of diverse functional circuits is still in its infancy. It is not known how many different circuit structures can implement any given function, which evolutionary factors lead to different circuits, and whether the evolution of a particular circuit was due to adaptive or non-adaptive processes. Here, we use digital experimental evolution to study the diversity of neural circuits that encode motion detection in digital (artificial) brains. We find that evolution leads to an enormous diversity of potential neural architectures encoding motion detection circuits, even for circuits encoding the exact same function. Evolved circuits vary in both redundancy and complexity (as previously found in genetic circuits) suggesting that similar evolutionary principles underlie circuit formation using any substrate. We also show that a simple (designed) motion detection circuit that is optimally-adapted gains in complexity when evolved further, and that selection for mutational robustness led this gain in complexity.
引用
收藏
页码:625 / 632
页数:8
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