Edgar Bermudez


Postdoctoral Fellow at the CCBN
e-mail: edgar.bermudez@uleth.ca
Phone: (403) 394-3973

Research Interests

I am interested in the study of mechanisms and processes by which neurons interact and form functional groups. To do this, I analyze electrophysiological recordings of multiple neurons and optical imaging of neuronal activity. Currently, I am working on a project to study memory formation and consolidation by understanding the computational role of the hippocampus in reactivation of patterns of cortical activity.

Biography

Edgar obtained his PhD in Computer Science and Artificial Intelligence at University of Sussex UK under the supervision of Andy Philippides and Anil Seth. He did a Master in Research in Computer Science and Artificial Intelligence under the supervision of Prof. Hilary Buxton at University of Sussex. Before that, Edgar completed a BSc in Computer Science at National Autonomous University of Mexico (UNAM).

Recent Publications

  1. Bermudez Contreras, E., Clark, B.J., Wilber, A. The Neuroscience of Spatial Navigation and the Relationship to Artificial Intelligence. Frontiers in Computational Neuroscience, 2020
  2. J. Karimi Abadchi, M. Nazari-Ahangarkolaee, S. Gattas, E. Bermudez-Contreras, B.L. McNaughton, M. H. Mohajerani. Spatiotemporal patterns of neocortical activity around hippocampal sharp-wave ripples. eLife, 2020.
  3. Ryait H, Bermudez-Contreras E, Harvey M, Faraji J, Mirza Agha B, Gomez-Palacio Schjetnan A, Gruber A, Doan J, Mohajerani M, Metz G.A.S, Whishaw IQ, Luczak A. Data-driven analyses of motor impairments in animal models and neurological disorders. PLoS Biology, 2019.
  4. Singh, S., Bermudez-Contreras, E., Nazari, M., Sutherland,R.J., Mohajerani, M.H. Low-Cost Solution for Rodent Home-Cage Behaviour Monitoring. PLoS ONE. August, 2019
  5. Bermudez-Contreras E, Chekhov S, Tarnowsky J, Sun J, McNaughton BL., Mohajerani MH. A High Performance, Inexpensive Setup for Simultaneous Multi-site Recording of Electrophysiological Signals and Wide-Field Imaging in the Mouse Cortex. Neurophotonics, 5(2), 2018.
  6. Chalmers, E., Bermudez Contreras, E., Robertson, B., Luczak, A. Gruber, A. Learning to Predict Consequences as a Method of Knowledge Transfer. IEEE Transactions on Neural Networks and Learning Systems, May, 2017
  7. Chalmers, E., Bermudez-Contreras, E., Robertson, B., Luczak, A., Gruber, A. “Context-switching and adaptation: Brain-inspired mechanisms for handling environmental changes,” 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, 2016, pp. 3522-3529.
  8. Bermudez Contreras, E.J., Schjetnan, A.G.P., Muhammad, A., Bartho, P., McNaughton, B.L., Kolb, B., Gruber, A.J., and Luczak, A. (2013). Formation and Reverberation of Sequential Neural Activity Patterns Evoked by Sensory Stimulation Are Enhanced during Cortical Desynchronization. Neuron 79, 555–566.
  9. Bermudez, E., Buxton, H. and Spier E. Attention can improve a simple model for visual object recognition. Image Vision Comput., 26(6):776.787, 2008.
  10. Bermudez-Contreras, E. Philippides, A. and Seth, A.K. Movement Strategies for Learning in Visual Recognition. In S. Bullock, J. Noble, R. A. Watson, and M. A. Bedau(Eds.) Proceedings of the 11th International Conference on Artificial Life, Alife XI 2008, Winchester, UK, MIT Press, Cambridge, MA.
  11. Bermudez-Contreras, E. and Seth, A.K. Simulations of simulations in evolutionary robotics. In Almeida e Costa, F. et al. Proc. 9th European Conference on Artificial Life (ECAL2007), pp.796-806.
  12. Bermudez, E. A Biologically Inspired Solution for an Evolved Simulated Agent. Proc. Genetic and Evolutionary Computation Conference (GECCO 2007). London, England. July, 2007.
  13. Bermudez, E. An Account for a Biologically-Inspired Machine Vision system. Presented at Students Paper Meeting of the BMVA. London, UK. March 2007. * Paper selected for publication in the Annals of the British Machine Vision Association.