Name
Title | ||
|---|---|---|
A Topology Inference Method of Cortical Neuron Networks Based on Network Tomography and the Internet of Bio-Nano Things |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LNET.2019.2943692 | IEEE Networking Letters |
Keywords | DocType | Volume |
Neurons,Topology,Tomography,Network topology,Delays,Biological system modeling,Weight measurement | Journal | 1 |
Issue | Citations | PageRank |
4 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael Taynnan Barros | 1 | 13 | 6.47 |
| Harun Siljak | 2 | 0 | 0.68 |
| Alaa Ekky | 3 | 0 | 0.34 |
| Nicola Marchetti | 4 | 192 | 33.90 |