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

, , , , and . Sensors, 21 (14): 4900 (2021)

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Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data., , and . Evol. Syst., 9 (3): 195-211 (2018)EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes., , and . IJCNN, page 1-7. IEEE, (2018)Spatiotemporal EEG Dynamics of Prospective Memory in Ageing and Mild Cognitive Impairment., , , , , , and . Cogn. Comput., 15 (4): 1273-1299 (2023)Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning., , , , , , , , and . Sensors, 23 (2): 902 (January 2023)Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia., , , , , , , , , and 6 other author(s). Neural Networks, (2021)Personalised modelling with spiking neural networks integrating temporal and static information., , , , , and . Neural Networks, (2019)Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network., , , , and . Sensors, 21 (14): 4900 (2021)Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression., , , , and . ICONIP (3), volume 11955 of Lecture Notes in Computer Science, page 195-206. Springer, (2019)Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks., , and . IEEE Trans. Neural Networks Learn. Syst., 28 (4): 887-899 (2017)Efficient Recognition of Attentional Bias Using EEG Data and the NeuCube Evolving Spatio-Temporal Data Machine., , and . ICONIP (4), volume 9950 of Lecture Notes in Computer Science, page 645-653. (2016)