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在虚拟视觉辨别任务中重现决策网络。

Reproducing a decision-making network in a virtual visual discrimination task.

作者信息

Trapani Alessandra, Sheiban Francesco Jamal, Bertone Elisa, Chiosso Serena, Colombo Luca, D'Andrea Matteo, De Santis Francesco, Fati Francesca, Fossati Veronica, Gonzalez Victor, Pedrocchi Alessandra

机构信息

NearLab, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.

出版信息

Front Integr Neurosci. 2022 Aug 10;16:930326. doi: 10.3389/fnint.2022.930326. eCollection 2022.

Abstract

We reproduced a decision-making network model using the neural simulator software neural simulation tool (NEST), and we embedded the spiking neural network in a virtual robotic agent performing a simulated behavioral task. The present work builds upon the concept of replicability in neuroscience, preserving most of the computational properties in the initial model although employing a different software tool. The proposed implementation successfully obtains equivalent results from the original study, reproducing the salient features of the neural processes underlying a binary decision. Furthermore, the resulting network is able to control a robot performing an visual discrimination task, the implementation of which is openly available on the EBRAINS infrastructure through the neuro robotics platform (NRP).

摘要

我们使用神经模拟器软件神经模拟工具(NEST)重现了一个决策网络模型,并将脉冲神经网络嵌入到一个执行模拟行为任务的虚拟机器人代理中。本研究基于神经科学中的可复制性概念,尽管使用了不同的软件工具,但保留了初始模型中的大部分计算属性。所提出的实现成功地从原始研究中获得了等效结果,重现了二元决策背后神经过程的显著特征。此外,由此产生的网络能够控制一个执行视觉辨别任务的机器人,其实现可通过神经机器人平台(NRP)在EBRAINS基础设施上公开获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e6a/9399926/57ebd84416b5/fnint-16-930326-g0001.jpg

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