A large-scale model of the functioning brain C Eliasmith, TC Stewart, X Choo, T Bekolay, T DeWolf, C Tang, ... Science 338 (6111), 1202-1205, 2012 | 1045 | 2012 |
Nengo: a Python tool for building large-scale functional brain models T Bekolay, J Bergstra, E Hunsberger, T DeWolf, TC Stewart, ... Frontiers in neuroinformatics 7, 48, 2014 | 561 | 2014 |
Learning to select actions with spiking neurons in the basal ganglia TC Stewart, T Bekolay, C Eliasmith Frontiers in Neuroscience 6, 2012 | 117 | 2012 |
Neural representations of compositional structures: Representing and manipulating vector spaces with spiking neurons TC Stewart, T Bekolay, C Eliasmith Connection Science 23 (2), 145-153, 2011 | 78 | 2011 |
Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks T Bekolay, C Kolbeck, C Eliasmith 35th Annual Conference of the Cognitive Science Society, 169-174, 2013 | 62 | 2013 |
A spiking neural integrator model of the adaptive control of action by the medial prefrontal cortex T Bekolay, M Laubach, C Eliasmith The Journal of Neuroscience 34 (5), 1892-1902, 2014 | 45 | 2014 |
Methods and systems for artificial cognition CD Eliasmith, TC Stewart, F Choo, TW Bekolay, T Crncich-dewolf, Y Tang, ... US Patent 20,140,156,577, 2014 | 37* | 2014 |
Reduction of dopamine in basal ganglia and its effects on syllable sequencing in speech: a computer simulation study V Senft, TC Stewart, T Bekolay, C Eliasmith, BJ Kröger Basal Ganglia 6 (1), 7-17, 2016 | 29 | 2016 |
Modeling interactions between speech production and perception: speech error detection at semantic and phonological levels and the inner speech loop BJ Kröger, E Crawford, T Bekolay, C Eliasmith Frontiers in Computational Neuroscience 10, 51, 2016 | 25 | 2016 |
Learning in large-scale spiking neural networks T Bekolay University of Waterloo, 2011 | 18 | 2011 |
Modeling the mental lexicon as part of long-term and working memory and simulating lexical access in a naming task including semantic and phonological cues CM Stille, T Bekolay, P Blouw, BJ Kröger Frontiers in Psychology 11, 1594, 2020 | 17 | 2020 |
Modeling speech production using the Neural Engineering Framework BJ Kröger, T Bekolay, C Eliasmith 2014 5th IEEE Conference on Cognitive Infocommunications (CogInfoCom), 203-208, 2014 | 17 | 2014 |
Hierarchical sequencing and feedforward and feedback control mechanisms in speech production: a preliminary approach for modeling normal and disordered speech BJ Kröger, CM Stille, P Blouw, T Bekolay, TC Stewart Frontiers in Computational Neuroscience 14, 573554, 2020 | 11 | 2020 |
Neural modeling of speech processing and speech learning BJ Kröger, T Bekolay Springer International Publishing, 2019 | 11 | 2019 |
Inhibiting basal ganglia regions reduces syllable sequencing errors in Parkinson's disease: a computer simulation study V Senft, TC Stewart, T Bekolay, C Eliasmith, BJ Kröger Frontiers in computational neuroscience 12, 41, 2018 | 10 | 2018 |
Biologically inspired methods in speech recognition and synthesis: closing the loop T Bekolay University of Waterloo, 2016 | 10 | 2016 |
Modeling motor planning in speech production using the Neural Engineering Framework BJ Kröger, T Bekolay, P Blouw Electronic Speech Signal Processing (ESSV), 2016 | 10 | 2016 |
A general error-modulated STDP learning rule applied to reinforcement learning in the basal ganglia T Bekolay, C Eliasmith | 9 | 2011 |
On the emergence of phonological knowledge and on motor planning and motor programming in a developmental model of speech production BJ Kröger, T Bekolay, M Cao Frontiers in Human Neuroscience 16, 844529, 2022 | 8 | 2022 |
Learning nonlinear functions on vectors: examples and predictions T Bekolay CTN Technical Report, 2010 | 6 | 2010 |