I am currently a PhD student at the CNRG after completing my MMath (also at the CNRG) in 2011.

My primary research interest is in learning and memory. In my masters degree, I explored how to do supervised, unsupervised, and reinforcement learning in networks of biologically plausible spiking neurons. In my PhD, I am applying this knowledge to the domain of audition to explore how sounds coming into the ear become complex linguistic structures in the brain.

Publications

Theses

• Trevor Bekolay (2016) Biologically inspired methods in speech recognition and synthesis: closing the loop. PhD thesis, University of Waterloo.  Abstract  PDF  External link
• Trevor Bekolay (2011) Learning in large-scale spiking neural networks. Master's thesis, University of Waterloo, Waterloo, ON.  Abstract  PDF  External link

Journal Articles

• Valentin Senft, Terrence C Stewart, Trevor Bekolay, Chris Eliasmith, Bernd J Kröger (2018) Inhibiting Basal Ganglia Regions Reduces Syllable Sequencing Errors in Parkinson’s Disease: A Computer Simulation Study. Frontiers in computational neuroscience, 12:41.  Abstract  External link
• Bernd J. Kroger, Eric Crawford, Trevor Bekolay, Chris Eliasmith (2016) Modeling interactions between speech production and perception: speech error detection at semantic and phonological levels and the inner speech loop. Frontiers in Computational Neuroscience, 10:51.  Abstract  DOI  External link
• Valentin Senft, Terry Stewart, Trevor Bekolay, Chris Eliasmith, Bernd J. Kröger (2015) Reduction of dopamine in basal ganglia and its effects on syllable sequencing in speech: A computer simulation study. Basal Ganglia, pages -.  Abstract  PDF  DOI  External link
• Trevor Bekolay, James Bergstra, Eric Hunsberger, Travis DeWolf, Terrence C Stewart, Daniel Rasmussen, Xuan Choo, Aaron R. Voelker, Chris Eliasmith (2014) Nengo: A Python tool for building large-scale functional brain models. Frontiers in Neuroinformatics.  Abstract  PDF  DOI  External link
• Trevor Bekolay, Mark Laubach, Chris Eliasmith (2014) A spiking neural integrator model of the adaptive control of action by the medial prefrontal cortex. The Journal of Neuroscience, 34(5):1892–1902.  Abstract  PDF  External link
• Terrence C. Stewart, Trevor Bekolay, Chris Eliasmith (2012) Learning to select actions with spiking neurons in the basal ganglia. Frontiers in Decision Neuroscience.  Abstract  PDF  DOI
• Chris Eliasmith, Terrence C. Stewart, Xuan Choo, Trevor Bekolay, Travis DeWolf, Yichuan Tang, Daniel Rasmussen (2012) A large-scale model of the functioning brain. Science, 338:1202-1205.  Abstract  PDF  Poster  DOI  External link
• Terrence C. Stewart, Trevor Bekolay, Chris Eliasmith (2011) Neural Representations of Compositional Structures: Representing and Manipulating Vector Spaces with Spiking Neurons. Connection Science, 22:145-153.  Abstract  PDF  DOI

Conference and Workshop Papers

• Catharina Marie Stille, Trevor Bekolay, Bernd J. Kröger (2017) Neural modeling of developmental lexical disorders. In Bernstein Conference 2017. Council of Ontario Universities.  Abstract  DOI
• Bernd J. Kroger, Trevor Bekolay, Peter Blouw (2016) Modeling motor planning in speech production using the Neural Engineering Framework. In Electronic Speech Signal Processing (ESSV), 15–22.  Abstract  PDF
• Trevor Bekolay, Terrence C. Stewart, Xuan Choo, Travis DeWolf, Yichuan Tang, Daniel Rasmussen, Jan Gosmann, Chris Eliasmith (2015) Spaun: A biologically realistic large-scale functional brain model. In Ontario and Canada Research Chairs Symposium. Council of Ontario Universities.  Abstract  PDF
• Bernd J. Kroger, Trevor Bekolay, Chris Eliasmith (2014) Modeling speech production using the Neural Engineering Framework. In 2014 5th IEEE Conference on Cognitive Infocommunications, 203–208.  Abstract  PDF  DOI  External link
• Trevor Bekolay, Carter Kolbeck, Chris Eliasmith (2013) Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks. In 35th Annual Conference of the Cognitive Science Society, 169–174. Cognitive Science Society.  Abstract  PDF
• Carter Kolbeck, Trevor Bekolay, Chris Eliasmith (2013) A Biologically Plausible Spiking Neuron Model of Fear Conditioning. In ICCM, 53–58. ICCM.  Abstract  PDF
• Trevor Bekolay, Terrence C. Stewart, Xuan Choo, Travis DeWolf, Yichuan Tang, Daniel Rasmussen, Chris Eliasmith (2013) Spaun: A Large-Scale Model of the Functioning Brain. In Cheriton Symposium. David R. Cheriton School of Computer Science.  Abstract  PDF
• Trevor Bekolay, Benjamine Liu, Chris Eliasmith, Mark Laubach (2012) A spiking neural model of strategy shifting in a simple reaction time task. In Society for Neuroscience 2012.  Abstract  PDF  Poster
• Trevor Bekolay, Chris Eliasmith (2011) A general error-modulated STDP learning rule applied to reinforcement learning in the basal ganglia. In Cognitive and Systems Neuroscience.  Abstract  PDF  Poster

Technical Reports and Preprints

• Trevor Bekolay (2010) Automating the Nengo build process. Technical Report, Centre for Theoretical Neuroscience, Waterloo, ON.  Abstract  PDF
• Trevor Bekolay (2010) A general error-based spike-timing dependent learning rule for the Neural Engineering Framework. Technical Report, Centre for Theoretical Neuroscience, Waterloo, ON.  Abstract  PDF
• Trevor Bekolay (2010) Using and extending plasticity rules in Nengo. Technical Report, Centre for Theoretical Neuroscience, Waterloo, ON.  Abstract  PDF
• Trevor Bekolay (2010) Learning nonlinear functions on vectors: examples and predictions. Technical Report, Centre for Theoretical Neuroscience, Waterloo, ON.  Abstract  PDF

Blog Posts

• Chris Eliasmith at TPL Cutting Edge
• Chris Eliasmith on Research2Reality
• How to Build a Brain: Now Softer and Cheaper
• Synthesizing Symbolicism and Connectionism
• Nengo 2.0 released
• Member of the College of the Royal Society
• Nengo character recognition demo
• Chris at What Matters Now
• Chris Eliasmith at WICI
• CNRG in Berlin for Cognitive Science 2013