在储层计算框架内对秀丽隐杆线虫连接组进行基准测试

中文摘要 AI 辅助

本工作的目的是通过储层计算框架的计算视角来检查秀丽隐杆线虫的连接组。连接组是生物神经网络的映射；秀丽隐杆线虫是第一个已发布覆盖整个神经系统的物理连接组的生物。本文中使用的秀丽隐杆线虫连接组是在该生物的不同年龄阶段获得的，并基于三种不同的细胞间连接测量方式。经过最少的预处理，它们被实现为回声状态网络形式的储层，回声状态网络是一种递归神经网络。在储层计算中，储层本身不被训练，而是将储层的输出传递给一个相对较小的读出模块，训练在该模块中进行。训练和测试在不同的神经启发任务中进行，目的是将这些任务用作连接组的基准。这个过程在不同的储层配置下重复进行，并使用同等规模但随机化的零模型进行比较。结果表明，生物布线以及储层输入和输出节点的生物信息配置并不一定带来更好的性能。相反，随机化的零模型在所选的基准上通常优于原始连接组。同时，很明显，结果在很大程度上取决于储层的配置以及连接组从生物体中获取的方式。来自不同年龄的连接组可能产生不同的结果，但没有出现明显的趋势。

英文摘要

The aim of this work is to examine the connectomes of Caenorhabditis elegans through a computational lens using the reservoir computing framework. Connectomes are mappings of biological neural networks; C. elegans is the first organism for which physical connectomes covering the whole nervous system have been published. The connectomes of C. elegans used in this paper have been derived at different ages of the organism and are based on three different ways of measuring inter-cellular connections. They have, with minimal preprocessing, been implemented as reservoirs in the form of echo state networks, which are recurrent neural networks. In reservoir computing, the reservoir itself is not trained, rather the output of the reservoir is passed to a comparatively small read-out module in which training takes place. Training and testing is conducted in different neuro-inspired tasks, with the aim of using these tasks as a benchmark for the connectomes. This process has been repeated with different configurations of the reservoir and equally sized but randomized null models have been used for comparison. The results show that the biological wiring and a bio-informed configuration of input and output nodes of the reservoirs do not necessarily lead to better performance. Contrarily, the randomized null models are often outperforming the original connectomes on the chosen benchmarks. At the same time it becomes clear that the results depend a lot on the configuration of the reservoir and the way the connectome has been derived from the organism. Connectomes from different ages may produce varying outcome, without a clear trend becoming visible.

发表机构

• Østfold University College（东福尔德大学学院）
• Norwegian University of Life Sciences（挪威生命科学大学）
• University of Oslo（奥斯陆大学）

机构由 AI 辅助整理，请以论文原文为准。