| A neurally controlled computer game avatar with humanlike behavior D Gamez, Z Fountas, AK Fidjeland IEEE Transactions on Computational Intelligence and AI in Games 5 (1), 1-14, 2012 | 32 | 2012 |
| Activity in perceptual classification networks as a basis for human subjective time perception W Roseboom, Z Fountas, K Nikiforou, D Bhowmik, M Shanahan, AK Seth Nature communications 10 (1), 1-9, 2019 | 21 | 2019 |
| A neuronal global workspace for human-like control of a computer game character Z Fountas, D Gamez, AK Fidjeland 2011 IEEE Conference on Computational Intelligence and Games (CIG'11), 350-357, 2011 | 17 | 2011 |
| The role of cortical oscillations in a spiking neural network model of the basal ganglia Z Fountas, M Shanahan Plos one 12 (12), e0189109, 2017 | 12 | 2017 |
| Spiking neural networks for human-like avatar control in a simulated environment Z Fountas Computing Science of Imperial College London, 2011 | 10* | 2011 |
| GPU-based fast parameter optimization for phenomenological spiking neural models Z Fountas, M Shanahan 2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015 | 9 | 2015 |
| Time without clocks: Human time perception based on perceptual classification W Roseboom, Z Fountas, K Nikiforou, D Bhowmik, M Shanahan, AK Seth BioRxiv, 172387, 2018 | 6 | 2018 |
| Phase offset between slow oscillatory cortical inputs influences competition in a model of the basal ganglia Z Fountas, M Shanahan 2014 International Joint Conference on Neural Networks (IJCNN), 2407-2414, 2014 | 6 | 2014 |
| Perceptual content, not physiological signals, determines perceived duration when viewing dynamic, natural scenes M Suárez-Pinilla, K Nikiforou, Z Fountas, AK Seth, W Roseboom, ... Collabra: Psychology 5 (1), 2019 | 5 | 2019 |
| A cognitive neural architecture as a robot controller Z Fountas, M Shanahan Conference on Biomimetic and Biohybrid Systems, 371-373, 2013 | 4 | 2013 |
| Deep active inference agents using Monte-Carlo methods Z Fountas, N Sajid, PAM Mediano, K Friston arXiv preprint arXiv:2006.04176, 2020 | 3 | 2020 |
| Building proactive voice assistants: When and how (not) to interact O Miksik, I Munasinghe, J Asensio-Cubero, SR Bethi, ST Huang, S Zylfo, ... arXiv preprint arXiv:2005.01322, 2020 | 3 | 2020 |
| A predictive processing model of episodic memory and time perception Z Fountas, A Sylaidi, K Nikiforou, AK Seth, M Shanahan, W Roseboom bioRxiv, 2020 | 2 | 2020 |
| Multimodal Data Fusion based on the Global Workspace Theory C Bao, Z Fountas, T Olugbade, N Bianchi-Berthouze Proceedings of the 2020 International Conference on Multimodal Interaction …, 2020 | 1 | 2020 |
| Accumulation of Salient Perceptual Events Predicts Subjective Time MT Sherman, Z Fountas, AK Seth, W Roseboom bioRxiv, 2020 | 1 | 2020 |
| Accumulation of salient events in sensory cortex activity predicts subjective time MT Sherman, Z Fountas, AK Seth, W Roseboom bioRxiv, 2020 | 1 | 2020 |
| Assessing selectivity in the basal ganglia: The “gearbox” hypothesis Z Fountas, M Shanahan bioRxiv, 197129, 2017 | 1 | 2017 |
| Action selection in the rhythmic brain: The role of the basal ganglia and tremor. Z Fountas Imperial College London, 2016 | 1 | 2016 |
| Episodic Memory for Learning Subjective-Timescale Models A Zakharov, M Crosby, Z Fountas arXiv preprint arXiv:2010.01430, 2020 | | 2020 |
| Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning J Yamada, J Shawe-Taylor, Z Fountas 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | | 2020 |
Murray ShanahanImperial College London / DeepMindVerified email at imperial.ac.uk
