Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network

Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network

The paper proposes a new method for deep learning and knowledge discovery in a brain-inspired Spiking Neural Networks (SNN) architecture that enhances the model’s explainability while learning from streaming spatiotemporal brain data (STBD) in an incremental and on-line mode of operation. This led t...

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Bibliographic Details
Main Authors: Maryam Doborjeh, Zohreh Doborjeh, Nikola Kasabov, Molood Barati, Grace Y. Wang
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Sensors
Subjects:
interpretable
explainable
dynamic clustering
feature selection
spiking neural networks
spatiotemporal data
Online Access:https://www.mdpi.com/1424-8220/21/14/4900

Internet

https://www.mdpi.com/1424-8220/21/14/4900

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