A Topology Inference Method of Cortical Neuron Networks Based on Network Tomography and the Internet of Bio-Nano Things

Michael Taynnan Barros; Harun Siljak; Alaa Ekky; Nicola Marchetti

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A Topology Inference Method of Cortical Neuron Networks Based on Network Tomography and the Internet of Bio-Nano Things

机译：基于网络断层扫描和生物纳米互联网的皮质神经元网络拓扑推理方法

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摘要

This letter presents a topology inference technique for neuronal networks of the cortex of the human brain based on network tomography theory. We envision that this technique will be used for high-resolution and high-precision brain tissue tomography and imaging using principles of the Internet of Bio-Nano Things. Our network tomography solution relies on the classification of processed data of spike delay and synaptic weight functions of neuronal network activity. For a 6-layer cortical neural network, we achieved 99.27% of accuracy using the Decision Tree machine learning technique for individual neurons, 2-leaf and 4-leaf star topologies of neuronal networks.

机译：基于网络断层扫描理论，这封信给了人脑皮质的神经元网络拓扑推理技术。我们设想这种技术将用于高分辨率和高精度脑组织断层扫描和使用生物纳米互联网原理的成像。我们的网络断层扫描解决方案依赖于神经元网络活动的尖峰延迟和突触重量函数的处理数据的分类。对于6层皮质神经网络，我们使用神经网络的单个神经元，2叶和4-叶星形拓扑的决策树机学习技术实现了99.27％的准确性。

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《IEEE Networking Letters》 |2019年第4期|142-145|共4页
作者
Michael Taynnan Barros; Harun Siljak; Alaa Ekky; Nicola Marchetti;
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作者单位

TSSG Waterford Institute of Technology Waterford Ireland;

Department of Electronic and Electrical Engineering Trinity College Dublin Dublin Ireland;

Department of Electronic and Electrical Engineering Trinity College Dublin Dublin Ireland;

Department of Electronic and Electrical Engineering Trinity College Dublin Dublin Ireland;

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正文语种 eng
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关键词
Neurons; Topology; Tomography; Network topology; Delays; Biological system modeling; Weight measurement;

机译：神经元;拓扑;断层扫描;网络拓扑;延迟;生物系统建模;重量测量;

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1. Evaluating network inference methods in terms of their ability to preserve the topology and complexity of genetic networks [J] . Kiani Narsis A., Zenil Hector, Olczak Jakub, Seminars in cell and developmental biology . 2016,第Null期

机译：根据网络推理方法保持遗传网络的拓扑结构和复杂性的能力进行评估
2. Impact of network topology on inference of synaptic connectivity from multi-neuronal spike data simulated by a large-scale cortical network model [J] . Ryota Kobayashi, Katsunori Kitano Journal of Computational Neuroscience . 2013,第1期

机译：网络拓扑对大规模皮层网络模型模拟的多神经突峰数据推断突触连通性的影响
3. Topology Inference With Network Tomography Based on t-Test [J] . Zhang R., Li Y., Li X. IEEE communications letters . 2014,第6期

机译：基于t检验的网络层析成像拓扑推断
4. Race networks: a theory of competitive recognition networks based on the rate of reactivation of neurons in cortical columns [C] . Templeman, J.N. . 1988

机译：种族网络：基于皮层神经元重新激活速率的竞争性识别网络理论
5. Statistical Methods for Topology Inference, Denoising, and Bootstrapping in Networks [D] . Kang, Xinyu. 2018

机译：网络中拓扑推断，降噪和自举的统计方法
6. Inference of Genetic Networks From Time-Series and Static Gene Expression Data: Combining a Random-Forest-Based Inference Method With Feature Selection Methods [O] . Shuhei Kimura, Ryo Fukutomi, Masato Tokuhisa, 2020

机译：从时间序列和静态基因表达数据引起遗传网络：组合具有特征选择方法的随机林类推断方法
7. Evaluating network inference methods in terms of their ability to preserve the topology and complexity of genetic networks [O] . Narsis A. Kiani, Hector Zenil, Jakub Olczak, 2016

机译：评估网络推论方法，以维护遗传网络的拓扑和复杂性的能力

A Topology Inference Method of Cortical Neuron Networks Based on Network Tomography and the Internet of Bio-Nano Things

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