Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment. - Elisa Capecci; Nikola K. Kasabov; Grace Y. Wang (Neural Networks, 2015)

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications. - Nikola K. Kasabov; Nathan Matthew Scott; Enmei Tu; Stefan Marks; Neelava Sengupta; Elisa Capecci; Muhaini Othman; Maryam Gholami Doborjeh; Norhanifah Murli; Reggio N. Hartono; Josafath Israel Espinosa Ramos; Lei Zhou 003; et al. (Neural Networks, 2016)

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects. - Maryam Gholami Doborjeh; Grace Y. Wang; Nikola K. Kasabov; Robert Kydd; Bruce Russell (IEEE Trans. Biomed. Eng., 2016)

Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression. - Dhvani Shah; Grace Y. Wang; Maryam Doborjeh; Zohreh Gholami Doborjeh; Nikola K. Kasabov (ICONIP (3), 2019)

Brain Signal Classification Based on Deep CNN. - Terry Gao; Grace Ying Wang (Int. J. Secur. Priv. Pervasive Comput., 2020)

Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture. - Zohreh Gholami Doborjeh; Maryam Doborjeh; Mark Crook-Rumsey; Tamasin Taylor; Grace Y. Wang; David Moreau; Christian U. Krägeloh; Wendy Wrapson; Richard J. Siegert; Nikola K. Kasabov; Grant Searchfield; Alexander Sumich (Sensors, 2020)

Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling. - Mahima Milinda Alwis Weerasinghe; Josafath Israel Espinosa Ramos; Grace Y. Wang; Dave Parry (IEEE Access, 2021)

Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network. - Maryam Doborjeh; Zohreh Gholami Doborjeh; Nikola K. Kasabov; Molood Barati; Grace Y. Wang (Sensors, 2021)

Ensemble plasticity and network adaptability in SNNs. - Mahima Milinda Alwis Weerasinghe; David Parry 001; Grace Y. Wang; Jacqueline Whalley (CoRR, 2022)

Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning. - Maryam Doborjeh; Xiaoxu Liu; Zohreh Gholami Doborjeh; Yuanyuan Shen; Grant Searchfield; Philip J. Sanders; Grace Y. Wang; Alexander Sumich; Wei Qi Yan 001 (Sensors, 2023)

Sentiment Analysis for Detection of Depressive Users on Social Networks. - Christopher Wigell; Xiaohui Tao 001; Lin Li 001; Grace Y. Wang; Ji Zhang 001; Yuan Sun (BESC, 2024)