Background
I'm the lab head, and also director of the Centre for Theoretical
Neuroscience (of which the CNRG is a part). I'm
jointly appointed in Philosophy and Systems Design Engineering, and cross-
appointed to Computer Science. I have supervised students in each of these
departments as well as Biology and Psychology. I did my undergrad in
Engineering (Waterloo), and my PhD in Philosophy at Washington University in
St. Louis. My first book with Charlie Anderson is called 'Neural Engineering'
(MIT Press, 2003). My second called 'How to build a brain' (Oxford University
Press) will be out in 2013.
Research Interests
I'm interested in everything that is currently being worked on in the lab,
including perception, motor control, learning, and cognition in the brain. I'm
particularly interested in how all of the various aspects of the brain work in
concert to generate sophisticated, adaptive behaviour. To this end, I work on
developing mathematical and conceptual tools that allow us to rigorously test
hypotheses about the principles of neural computation and biological
cognition. I think such hypotheses need to be highly constrained by all of the
various sources of information we have about brain function (e.g.
electrophysiology, neuroanatomy, molecular biology, fMRI, behaviour, etc.). I
also think the best way to test such hypotheses is through detailed
simulation.
Please see my main personal page for
more information.
Publications
Theses
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Chris Eliasmith
(2000)
How neurons mean: A neurocomputational theory of representational content.
Master's thesis, Washington University, St. Louis, MO.
Abstract
PDF
Books and Book Chapters
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Aaron R. Voelker,
Chris Eliasmith
(2021)
Programming Neuromorphics Using the Neural Engineering Framework.
Nitish V. Thakor, editor. Programming Neuromorphics Using the Neural Engineering Framework, pages 1–43. Springer Singapore, Singapore.
Abstract
PDF
DOI
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Chris Eliasmith
(2015)
On the Eve of Artificial Minds.
In Thomas Metzinger and Jennifer Windt, editors, Open MIND. Frankfurt am Main: MIND Group.
Abstract
PDF
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Chris Eliasmith
(2015)
Building a behaving brain.
In Gary Marcus and Jeremy Freeman, editors, The Future of the Brain: Essays by the World's Leading Neuroscientists. Princeton University Press.
Abstract
PDF
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Chris Eliasmith
(2013)
How to build a brain: A neural architecture for biological cognition.
Oxford University Press, New York, NY.
Abstract
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Terrence C. Stewart,
Chris Eliasmith
(2012)
Compositionality and biologically plausible models.
In Wolfram Hinzen, Markus Werning, and Edouard Machery, editors, Oxford Handbook of Compositionality. Oxford University Press.
Abstract
PDF
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Maya Carrillo,
Esau Villatoro-Tello,
Aurelio Lopez-Lopez,
Chris Eliasmith,
Manuel Montes-y-Gomez,
Luis Villasenor-Pineda
(2009)
Representing Context Information for Document Retrieval.
In Troels Andreasen, Ronald R. Yager, Henrik Bulskov, Henning Christiansen, and Henrik Legind Larsen, editors, Flexible Query Answering Systems, FQAS 2009, pages 239-250. Springer.
Abstract
PDF
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Chris Eliasmith
(2009)
Neurocomputational models: Theory and applications.
In John Bickle, editor, Oxford Handbook of Philosophy of Neuroscience. Oxford University Press.
Abstract
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Chris Eliasmith
(2009)
Dynamics, control, and cognition.
In Philip Robbins and Murat Aydede, editors, Cambridge Handbook of Situated Cognition. Cambridge University Press.
Abstract
PDF
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Chris Eliasmith
(2007)
Computational neuroscience.
In Paul Thagard, editor, Philosophy of Psychology and Cognitive Science. Elsevier.
Abstract
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Chris Eliasmith
(2006)
Neurosemantics and categories.
In Claire Lefebvre and Henri Cohen, editors, Handbook of Categorization in Cognitive Science. Elsevier.
Abstract
PDF
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Chris Eliasmith,
William Bechtel
(2003)
Symbolic versus subsymbolic computation and representation.
In Lynn Nadel, editor, Encyclopedia of Cognitive Science. MacMillian.
Abstract
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Chris Eliasmith,
Charles H. Anderson
(2003)
Neural engineering: Computation, representation, and dynamics in neurobiological systems.
MIT Press, Cambridge, MA.
Abstract
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Andy Clark,
Chris Eliasmith
(2002)
Philosophical issues in brain theory and connectionism.
In Michael A. Arbib, editor, Handbook of Brain Theory and Neural Networks. MIT Press, Cambridge, MA, 2nd edition.
Abstract
External link
Journal Articles
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Peter Duggins,
Chris Eliasmith
(2024)
A spiking neural model of decision making and the speed–accuracy trade-off.
Psychological Review.
Abstract
PDF
DOI
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Chris Eliasmith
(2024)
Artificial Cognition.
The GESDA 2024 Science Breakthrough Radar.
Abstract
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Peter Duggins,
Chris Eliasmith
(2024)
A scalable spiking amygdala model that explains fear conditioning, extinction, renewal and generalization.
European Journal of Neuroscience.
Abstract
PDF
DOI
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Joost de Jong,
Aaron R. Voelker,
Terrence C. Stewart,
Elkan G. Akyürek,
Hedderik van Rijn,
Chris Eliasmith
(2024)
A Unified Neurocomputational Model of Prospective and Retrospective Timing.
Psychological Review.
Abstract
PDF
DOI
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Nicole Sandra-Yaffa Dumont,
Andreas Stöckel,
P. Michael Furlong,
Madeleine Bartlett,
Chris Eliasmith,
Terrence C. Stewart
(2023)
Biologically-Based Computation: How Neural Details and Dynamics Are Suited for Implementing a Variety of Algorithms.
Brain Sciences, 13(2):245.
Abstract
PDF
DOI
External link
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Travis DeWolf,
Kinjal Patel,
Pawel Jaworski,
Roxana Leontie,
Joseph Hays,
Chris Eliasmith
(2023)
Neuromorphic control of a simulated 7-DOF arm using Loihi.
Neuromorphic Computing and Engineering.
Abstract
External link
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P Michael Furlong,
Chris Eliasmith
(2023)
A new paradigm for probabilistic neuromorphic programming.
IEEE Brain e-Newsletter.
Abstract
PDF
External link
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Nicole Sandra-Yaffa Dumont,
P. Michael Furlong,
Jeff Orchard,
Chris Eliasmith
(2023)
Exploiting semantic information in a spiking neural SLAM system.
Frontiers in Neuroscience.
Abstract
PDF
DOI
External link
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Andreas Stöckel,
Chris Eliasmith
(2022)
Computational properties of multi-compartment LIF neurons with passive dendrites.
Neuromorphic Computing and Engineering.
Abstract
DOI
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Peter Duggins,
Chris Eliasmith
(2022)
Constructing functional models from biophysically-detailed neurons.
PLoS computational biology, 18(9):e1010461.
Abstract
PDF
External link
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Yexin Yan,
Terrence Stewart,
Xuan Choo,
Bernhard Vogginger,
Johannes Partzsch,
Sebastian Hoeppner,
Florian Kelber,
Chris Eliasmith,
Steve Furber,
Christian Mayr
(2021)
Comparing Loihi with a SpiNNaker 2 Prototype on Low-Latency Keyword Spotting and Adaptive Robotic Control.
Neuromorphic Computing and Engineering.
Abstract
DOI
External link
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Aaron R. Voelker,
Peter Blouw,
Xuan Choo,
Nicole Sandra-Yaffa Dumont,
Terrence C. Stewart,
Chris Eliasmith
(2021)
Simulating and Predicting Dynamical Systems With Spatial Semantic Pointers.
Neural Computation, 33(8):2033-2067.
Abstract
PDF
DOI
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Andreas Stöckel,
Terrence C. Stewart,
Chris Eliasmith
(2021)
Connecting Biological Detail with Neural Computation: Application to the Cerebellar Granule-Golgi Microcircuit.
Topics in Cognitive Science, 13(3):515-533.
Abstract
PDF
DOI
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Andreas Stöckel,
Chris Eliasmith
(2021)
Passive Nonlinear Dendritic Interactions as a Computational Resource in Spiking Neural Networks.
Neural Computation, 33(1):96-128. PMID: 33080158.
Abstract
DOI
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Jan Gosmann,
Chris Eliasmith
(2021)
CUE: A unified spiking neuron model of short-term and long-term memory.
Psychological Review, 128(1):104-124.
Abstract
PDF
DOI
External link
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P. Michael Furlong,
Terrrence C. Stewart,
Chris Eliasmith
(2021)
Fractional Binding in Vector Symbolic Representations for Efficient Mutual Information Exploration.
ICRA Workshop: Towards Curious Robots: Modern Approaches for Intrinsically-Motivated Intelligent Behavior.
Abstract
PDF
External link
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Chris Eliasmith,
Terrence C. Stewart
(2020)
Scaling, Low Power Needed for a Neuromorphic Future.
eeTimes.
Abstract
External link
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Travis DeWolf,
Pawel Jaworski,
Chris Eliasmith
(2020)
Nengo and Low-Power AI Hardware for Robust Embedded Neurorobotics.
Frontiers in Neurorobotics.
Abstract
External link
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Jan Gosmann,
Chris Eliasmith
(2019)
Vector-Derived Transformation Binding: An Improved Binding Operation for Deep Symbol-Like Processing in Neural Networks.
Neural Computation, 31(5):849-869.
Abstract
PDF
DOI
External link
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Alexander Neckar,
Sam Fok,
Ben V. Benjamin,
Terrence C. Stewart,
Nick N. Oza,
Aaron R. Voelker,
Chris Eliasmith,
Rajit Manohar,
Kwabena Boahen
(2019)
Braindrop: A Mixed-Signal Neuromorphic Architecture With a Dynamical Systems-Based Programming Model.
Proceedings of the IEEE, 107:144–164.
Abstract
PDF
DOI
External link
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Aaron R. Voelker,
Chris Eliasmith
(2018)
Improving Spiking Dynamical Networks: Accurate Delays, Higher-Order Synapses, and Time Cells.
Neural Computation, 30(3):569-609.
Abstract
PDF
DOI
External link
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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
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Peter Blouw,
Chris Eliasmith
(2018)
Using neural networks to generate inferential roles for natural language.
Frontiers in Psychology, pages 1-14.
Abstract
PDF
DOI
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Ivana Kajić,
Jan Gosmann,
Terrence C. Stewart,
Thomas Wennekers,
Chris Eliasmith
(2017)
A Spiking Neuron Model of Word Associations for the Remote Associates Test.
Frontiers in Psychology, 8:99.
Abstract
DOI
External link
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Travis DeWolf,
Chris Eliasmith
(2017)
Trajectory generation using a spiking neuron implementation of dynamic movement primitives.
27th Annual Meeting for the Society for the Neural Control of Movement.
Abstract
External link
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Jan Gosmann,
Chris Eliasmith
(2017)
Automatic Optimization of the Computation Graph in the Nengo Neural Network Simulator.
Frontiers in Neuroinformatics, 11:33.
Abstract
DOI
External link
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Daniel Rasmussen,
Aaron R. Voelker,
Chris Eliasmith
(2017)
A neural model of hierarchical reinforcement learning.
PLoS ONE, 12(7):1–39.
Abstract
PDF
DOI
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Peter Duggins,
Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2017)
Effects of Guanfacine and Phenylephrine on a Spiking Neuron Model of Working Memory.
Topics in Cognitive Science.
Abstract
PDF
DOI
External link
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Peter Blouw,
Eugene Solodkin,
Paul Thagard,
Chris Eliasmith
(2016)
Concepts as semantic pointers: A framework and computational model.
Cognitive Science, 40(5):1128–1162.
Abstract
PDF
DOI
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Ken Elmar Friedl,
Aaron R. Voelker,
Angelika Peer,
Chris Eliasmith
(2016)
Human-Inspired Neurorobotic System for Classifying Surface Textures by Touch.
Robotics and Automation Letters, 1(1):516-523.
Abstract
PDF
DOI
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Sean Aubin,
Aaron R. Voelker,
Chris Eliasmith
(2016)
Improving With Practice: A Neural Model of Mathematical Development.
Topics in Cognitive Science.
Abstract
PDF
DOI
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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
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Jan Gosmann,
Chris Eliasmith
(2016)
Optimizing Semantic Pointer Representations for Symbol-Like Processing in Spiking Neural Networks.
PLoS ONE, 11(2):1-18.
Abstract
DOI
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Sugandha Sharma,
Sean Aubin,
Chris Eliasmith
(2016)
Large-scale cognitive model design using the Nengo neural simulator.
Biologically Inspired Cognitive Architectures, 17:86–100.
Abstract
PDF
DOI
External link
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Brent Komer,
Chris Eliasmith
(2016)
A unified theoretical approach for biological cognition and learning.
Current Opinion in Behavioral Sciences.
Abstract
PDF
External link
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Travis DeWolf,
Terrence C Stewart,
Jean-Jacques Slotine,
Chris Eliasmith
(2016)
A spiking neural model of adaptive arm control.
Proceedings of the Royal Society B.
Abstract
DOI
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Bryan Tripp,
Chris Eliasmith
(2016)
Function approximation in inhibitory networks.
Neural Networks, 77:95-106.
Abstract
PDF
DOI
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James Bergstra,
Brent Komer,
Chris Eliasmith,
Dan Yamins,
David D Cox
(2015)
Hyperopt: a Python library for model selection and hyperparameter optimization.
Computational Science & Discovery, 8(1):014008.
Abstract
External link
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Terrence C Stewart,
Travis DeWolf,
Ashley Kleinhans,
Chris Eliasmith
(2015)
Closed-Loop Neuromorphic Benchmarks.
Frontiers in neuroscience.
Abstract
PDF
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Chris Eliasmith,
Carter Kolbeck
(2015)
Marr's Attacks: On Reductionism and Vagueness.
Topics in Cognitive Science, pages 1-13.
Abstract
PDF
DOI
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Eric Crawford,
Matthew Gingerich,
Chris Eliasmith
(2015)
Biologically Plausible, Human-Scale Knowledge Representation.
Cognitive Science.
Abstract
PDF
DOI
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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
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Terrence C. Stewart,
Chris Eliasmith
(2014)
Large-Scale Synthesis of Functional Spiking Neural Circuits.
Proceedings of the IEEE, 102(5):881–898.
Abstract
PDF
DOI
External link
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Steven Leigh,
James Danckert,
Chris Eliasmith
(2014)
Modelling the differential effects of prisms on perception and action in neglect..
Experimental Brain Research.
Abstract
DOI
External link
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Daniel Rasmussen,
Chris Eliasmith
(2014)
A spiking neural model applied to the study of human performance and cognitive decline on Raven's Advanced Progressive Matrices.
Intelligence, 42:53–82.
Abstract
DOI
External link
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Eric Hunsberger,
Matthew Scott,
Chris Eliasmith
(2014)
The Competing Benefits of Noise and Heterogeneity in Neural Coding.
Neural Computation.
Abstract
PDF
DOI
External link
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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
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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
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Bruce Bobier,
Terrence C Stewart,
Chris Eliasmith
(2014)
A unifying mechanistic model of selective attention in spiking neurons..
PLoS computational biology, 10(6):e1003577.
Abstract
DOI
External link
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Eric Hunsberger,
Matthew Scott,
Chris Eliasmith
(2013)
Heterogeneity Increases Information Transmission in Neuronal Populations.
Cognitive and Systems Neuroscience.
Abstract
PDF
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Terrence C Stewart,
Chris Eliasmith
(2013)
Realistic neurons can compute the operations needed by quantum probability theory and other vector symbolic architectures.
Behavioral and Brain Sciences.
Abstract
DOI
External link
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Chris Eliasmith,
Oliver Trujillo
(2013)
The use and abuse of large-scale brain models.
Current Opinion in Neurobiology, 25:1–6.
Abstract
PDF
DOI
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Daniel Rasmussen,
Chris Eliasmith
(2013)
God, the devil, and details: Fleshing out the predictive processing framework (commentary on Clark).
Behavioral and Brain Sciences, 36:223-224.
Abstract
External link
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Daniel Rasmussen,
Chris Eliasmith
(2013)
Modeling brain function: Current developments and future prospects.
JAMA Neurology, 70(10):1325–1329.
Abstract
DOI
External link
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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
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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
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Terrence C. Stewart,
Yichuan Tang,
Chris Eliasmith
(2011)
A Biologically Realistic Cleanup Memory: Autoassociation in Spiking Neurons.
Cognitive Systems Research, 12:84-92.
Abstract
PDF
DOI
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Daniel Rasmussen,
Chris Eliasmith
(2011)
A neural model of rule generation in inductive reasoning.
Topics in Cognitive Science, 3:140-153.
Abstract
PDF
External link
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Chris Eliasmith,
James Martens
(2011)
Normalization for probabilistic inference with neurons.
Biological Cybernetics, 104:251-262.
Abstract
PDF
External link
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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
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David MacNeil,
Chris Eliasmith
(2011)
Fine-tuning and the stability of recurrent neural networks.
PLoS ONE.
Abstract
PDF
External link
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Travis DeWolf,
Chris Eliasmith
(2011)
The neural optimal control hierarchy for motor control.
The Journal of Neural Engineering, 8:21.
Abstract
PDF
External link
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Bryan Tripp,
Chris Eliasmith
(2010)
Population models of temporal differentiation.
Neural Computation, 22:621-659.
Abstract
PDF
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Chris Eliasmith
(2010)
How we ought to describe computation in the brain.
Studies in History and Philosophy of Science, 41:313-320.
Abstract
PDF
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Terrence C. Stewart,
Bryan Tripp,
Chris Eliasmith
(2009)
Python scripting in the Nengo simulator.
Frontiers in Neuroinformatics.
Abstract
PDF
DOI
External link
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Abninder Litt,
Chris Eliasmith,
Paul Thagard
(2008)
Neural affective decision theory: Choices, brains, and emotions.
Cognitive Systems Research, 9:252-273.
Abstract
PDF
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Christopher Parisien,
Charles H. Anderson,
Chris Eliasmith
(2008)
Solving the problem of negative synaptic weights in cortical models.
Neural Computation, 20:1473-1494.
Abstract
PDF
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Chris Eliasmith
(2007)
How to build a brain: From function to implementation.
Synthese, 153:373-388.
Abstract
PDF
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Chris Eliasmith
(2007)
Attractor network.
Scholarpedia, 2:1380.
Abstract
External link
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Bryan Tripp,
Chris Eliasmith
(2007)
Neural populations can induce reliable postsynaptic currents without observable spike rate changes or precise spike timing.
Cerebral Cortex, 17:1830-1840. [code](/files/cc07.zip) [ModelDB](http://senselab.med.yale.edu/modeldb/ShowModel.asp?model=136380).
Abstract
PDF
External link
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Ray Singh,
Chris Eliasmith
(2006)
Higher-dimensional neurons explain the tuning and dynamics of working memory cells.
Journal of Neuroscience, 26:3667-3678.
Abstract
PDF
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Abninder Litt,
Chris Eliasmith,
Frederick W. Kroon,
Steven Weinstein,
Paul Thagard
(2006)
Is the brain a quantum computer?.
Cognitive Science, 30:593-603.
Abstract
PDF
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Chris Eliasmith
(2005)
A unified approach to building and controlling spiking attractor networks.
Neural computation, 7(6):1276-1314.
Abstract
PDF
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P. Dwight Kuo,
Chris Eliasmith
(2005)
Integrating behavioral and neural data in a model of zebrafish network interaction.
Biological Cybernetics, 93(3):178-187.
Abstract
PDF
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John Conklin,
Chris Eliasmith
(2005)
A controlled attractor network model of path integration in the rat.
Journal of Computational Neuroscience, 18:183-203.
Abstract
PDF
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Chris Eliasmith
(2005)
A new perspective on representational problems.
Journal of Cognitive Science, 6:97-123.
Abstract
PDF
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P. Dwight Kuo,
Chris Eliasmith
(2004)
Understanding interactions between networks controlling distinct behaviors: Escape and swimming in larval zebrafish.
Neurocomputing, 58-60:541-547.
Abstract
PDF
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Chris Eliasmith
(2003)
Moving beyond metaphors: Understanding the mind for what it is.
Journal of Philosophy, 100:493-520. Reprinted in Brooks and Akins (eds). Cognition and the Brain. 2005. Cambridge University Press. p.131-159.
Abstract
PDF
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Chris Eliasmith,
Michael B. Westover,
Charles H. Anderson
(2002)
A general framework for neurobiological modeling: An application to the vestibular system.
Neurocomputing, 46:1071-1076.
Abstract
PDF
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Chris Eliasmith
(2002)
Discreteness and relevance: A reply to Roman Poznanski.
Minds and Machines, 12:437-443.
Abstract
PDF
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M. B. Westover,
Chris Eliasmith,
Charles H. Anderson
(2002)
Linearly decodable functions from neural population codes.
Neurocomputing, 45:691-696.
Abstract
PDF
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Chris Eliasmith
(2002)
The myth of the Turing machine: the failings of functionalism and related theses.
Journal of Experimental and Theoretical Artificial Intelligence, 14:1-8.
Abstract
PDF
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Chris Eliasmith,
Paul Thagard
(2001)
Integrating structure and meaning: a distributed model of analogical mapping.
Cognitive Science, 25:245-286.
Abstract
External link
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Chris Eliasmith,
Charles H. Anderson
(2001)
Beyond bumps: Spiking networks that store sets of functions.
Neurocomputing, 38:581-586.
Abstract
PDF
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Chris Eliasmith
(2001)
Attractive and in-discrete: A critique of two putative virtues of the dynamicist theory of mind.
Minds and Machines, 11:417-426.
Abstract
PDF
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Chris Eliasmith
(2000)
Is the brain analog or digital? The solution and its consequences for cognitive science.
Cognitive Science Quarterly, 1:147-170.
Abstract
PDF
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Chris Eliasmith,
Charles H. Anderson
(2000)
Rethinking central pattern generators: a general approach.
Neurocomputing, 32:735-740.
Abstract
PDF
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Chris Eliasmith,
Charles H. Anderson
(1999)
Developing and applying a toolkit from a general neurocomputational framework.
Neurocomputing, 26:1013-1018.
Abstract
PDF
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Chris Eliasmith
(1997)
Computation and dynamical models of mind.
Minds and Machines, 7:531-541.
Abstract
PDF
Conference and Workshop Papers
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P Michael Furlong,
Katherine Simone,
Nicole Dumont,
Madeline Bartlett,
Terrence C. Stewart,
Jeff Orchard,
Chris Eliasmith
(2024)
Biologically-plausible Markov Chain Monte Carlo Sampling from Vector Symbolic Algebra-encoded Distributions.
In ICANN.
Abstract
PDF
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Ryan Laube,
Chris Eliasmith
(2024)
QAVSA: Question Answering using Vector Symbolic Algebras.
In ACL 2024 9th Workshop on Representation Learning for NLP.
Abstract
External link
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P Michael Furlong,
Chris Eliasmith
(2023)
Bridging Cognitive Architectures and Generative Models with Vector Symbolic Algebras.
In Proceedings of the 2023 AAAI Fall Symposium.
Abstract
PDF
External link
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Madeline Bartlett,
Katherine Simone,
Nicole Dumont,
P Michael Furlong,
Chris Eliasmith,
Jeff Orchard,
Terrence C. Stewart
(2023)
Improving Reinforcement Learning with Biologically Motivated Continuous State Representations.
In Proceedings of the International Conference on Cognitive Modeling.
Abstract
PDF
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Nicole Sandra-Yaffa Dumont,
Jeff Orchard,
Chris Eliasmith
(2022)
A model of path integration that connects neural and symbolic representation.
In Proceedings of the Annual Meeting of the Cognitive Science Society, volume 44. Toronto, ON. Cognitive Science Society.
Abstract
PDF
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Narsimha Chilkuri,
Chris Eliasmith
(2022)
Debugging using Orthogonal Gradient Descent.
In Updatable Machine Learning, ICML. arXiv.
Abstract
PDF
arXiv
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Brent Komer,
Pawel Jaworski,
Steven Harbour,
Chris Eliasmith,
Travis DeWolf
(2022)
BatSLAM: Neuromorphic Spatial Reasoning in 3D Environments.
In 41st Digital Avionics Systems Conference. Portsmouth, VA, USA. DASC.
Abstract
PDF
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P. Michael Furlong,
Chris Eliasmith
(2022)
Fractional Binding in Vector Symbolic Architectures as Quasi-Probability Statements.
In 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society.
Abstract
PDF
External link
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Chris Eliasmith,
P. Michael Furlong
(2022)
Continuous then discrete: A recommendation for building robotic brains.
In Aleksandra Faust, David Hsu, and Gerhard Neumann, editors, Proceedings of the 5th Conference on Robot Learning, volume 164 of Proceedings of Machine Learning Research, 1758–1763. PMLR.
Abstract
PDF
External link
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Peter Duggins,
Terrence C Stewart,
Chris Eliasmith
(2022)
Reinforcement Learning, Social Value Orientation, and Decision Making: Computational Models and Empirical Validation.
In Proceedings of the Annual Meeting of the Cognitive Science Society, volume 44.
Abstract
PDF
External link
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Narsimha Reddy Chilkuri,
Chris Eliasmith
(2021)
Parallelizing Legendre Memory Unit Training.
In Marina Meila and Tong Zhang, editors, Proceedings of the 38th International Conference on Machine Learning, volume 139 of Proceedings of Machine Learning Research, 1898–1907. PMLR.
Abstract
PDF
External link
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Peter Blouw,
Gurshaant Malik,
Benjamin Morcos,
Aaron Voelker,
Chris Eliasmith
(2021)
Hardware Aware Training for Efficient Keyword Spotting on General Purpose and Specialized Hardware.
In TinyML Research Symposium.
Abstract
arXiv
-
Joost de Jong,
Aaron Voelker,
Terry Stewart,
Chris Eliasmith,
Heddrick van Rijn
(2021)
A neurocomputational model of prospective and retrospective timing.
In International Conference on Cognitive Modeling. Toronto, ON. Society for Mathematical Psychology.
Abstract
External link
-
Nicole Sandra-Yaffa Dumont,
Chris Eliasmith
(2020)
Accurate representation for spatial cognition using grid cells.
In 42nd Annual Meeting of the Cognitive Science Society, 2367–2373. Toronto, ON. Cognitive Science Society.
Abstract
PDF
-
Peter Blouw,
Chris Eliasmith
(2020)
Event-Driven Signal Processing with Neuromorphic Computing Systems.
In 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Abstract
External link
-
Peter Duggins,
Dominik Krzeminski,
Chris Eliasmith,
Simon Wichary
(2020)
A spiking neuron model of inferential decision making: Urgency, uncertainty, and the speed-accuracy tradeoff.
In 42nd Annual Meeting of the Cognitive Science Society, 1891–1897. Toronto, ON. Cognitive Science Society.
Abstract
PDF
-
Andreas Stöckel,
Terrence C. Stewart,
Chris Eliasmith
(2020)
A Biologically Plausible Spiking Neural Model of Eyeblink Conditioning in the Cerebellum.
In 42nd Annual Meeting of the Cognitive Science Society, 1614–1620. Toronto, ON. Cognitive Science Society.
Abstract
PDF
Poster
-
Brent Komer,
Chris Eliasmith
(2020)
Efficient navigation using a scalable, biologically inspired spatial representation.
In 42nd Annual Meeting of the Cognitive Science Society. Toronto, ON. Cognitive Science Society.
Abstract
PDF
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Hugo Chateau-Laurent,
Chris Eliasmith,
Serge Thill
(2020)
Flexibly chaining mental operations with spiking neurons.
In 2nd International Workshop on Concepts in Action: Representation, Learning, and Application.
Abstract
PDF
External link
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Andreas Stöckel,
Terrence C. Stewart,
Chris Eliasmith
(2020)
Connecting Biological Detail with Neural Computation: Application to the Cerebellar Granule-Golgi Microcircuit.
In 18th Annual Meeting of the International Conference on Cognitive Modelling, 277–282. Toronto, ON. Society for Mathematical Psychology.
Abstract
PDF
-
Peter Duggins,
Chris Eliasmith
(2019)
A spiking neuron model of pharmacologically-biased fear conditioning in the amygdala.
In SfN Abstracts. Chicago USA.
Abstract
PDF
Poster
External link
-
Joost de Jong,
Aaron R. Voelker,
Hedderik van Rijn,
Terrence C. Stewart,
Chris Eliasmith
(2019)
Flexible Timing with Delay Networks – The Scalar Property and Neural Scaling.
In 17th Annual Meeting of the International Conference on Cognitive Modelling (ICCM).
Abstract
PDF
External link
-
Natarajan Vaidyanathan,
Chris Eliasmith
(2019)
Spiking neuron model of motor control with adaptation to visuomotor rotation.
In 49th Annual Meeting of the Society of Neuroscience. Chicago, IL. Society of Neuroscience.
Abstract
PDF
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Joost de Jong,
Aaron R. Voelker,
Hedderik van Rijn,
Terrence C. Stewart,
Chris Eliasmith
(2019)
A Neurocomputational Account of Ecologically Plausible, Flexible Timing with Legendre Memory.
In 2nd Annual Conference of the Timing Research Forum. Querétaro, México.
Abstract
Poster
External link
-
Florian Mirus,
Terrence C. Stewart,
Chris Eliasmith,
Jorg Conradt
(2019)
A Mixture-of-Experts Model for Vehicle Prediction Using an Online Learning Approach.
In International Conference on Artificial Neural Networks, 456–471. ICANN.
Abstract
External link
-
Andreas Stöckel,
Terrence C. Stewart,
Chris Eliasmith
(2019)
A Geometric Interpretation of Feedback Alignment.
In 41nd Annual Meeting of the Cognitive Science Society, 3366. Montreal, QC. Cognitive Science Society. Abstract.
Abstract
PDF
Poster
-
Aaron R. Voelker,
Ivana Kajić,
Chris Eliasmith
(2019)
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural Networks.
In Advances in Neural Information Processing Systems, 15544–15553.
Abstract
PDF
Poster
External link
-
Brent Komer,
Terrence C. Stewart,
Aaron R. Voelker,
Chris Eliasmith
(2019)
A neural representation of continuous space using fractional binding.
In 41st Annual Meeting of the Cognitive Science Society. Montreal, QC. Cognitive Science Society.
Abstract
PDF
-
Thomas Lu,
Aaron R. Voelker,
Brent Komer,
Chris Eliasmith
(2019)
Representing spatial relations with fractional binding.
In 41st Annual Meeting of the Cognitive Science Society. Montreal, QC. Cognitive Science Society.
Abstract
PDF
-
Sverrir Thorgeirsson,
Terrence C. Stewart,
Chris Eliasmith
(2018)
Analysis of Learning Action Selection Parameters in a Neural Cognitive Model.
In International Conference on Cognitive Modelling.
Abstract
PDF
-
Benjamin Morcos,
Terrence C Stewart,
Chris Eliasmith,
Nachiket Kapre
(2018)
Implementing NEF Neural Networks on Embedded FPGAs.
In International Conference on Field-Programmable Technology (FPT), 25-32. IEEE.
Abstract
PDF
DOI
-
Andreas Stöckel,
Aaron R. Voelker,
Chris Eliasmith
(2018)
Nonlinear synaptic interaction as a computational resource in the Neural Engineering Framework.
In Cosyne Abstracts. Denver USA.
Abstract
PDF
Poster
External link
-
Terrence C. Stewart,
Sverrir Thorgeirsson,
Chris Eliasmith
(2018)
Supervised Learning of Action Selection in Cognitive Spiking Neuron Models.
In 40th Annual Conference of the Cognitive Science Society, 1086–1091. Cognitive Science Society.
Abstract
PDF
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Sverrir Thorgeirsson,
Brent Komer,
Chris Eliasmith
(2018)
Incorporating an adaptive learning rate in a neural model of action selection.
In Cognitive Computational Neuroscience. Philadelphia, USA.
Abstract
PDF
Poster
External link
-
Mariah Martin Shein,
Terrence C. Stewart,
Chris Eliasmith
(2017)
Parameter exploration of a neural model of state transition probabilities in model-based reinforcement learning.
In Proceedings of the 15th International Conference on Cognitive Modelling.
Abstract
PDF
-
Terry Stewart,
Chris Eliasmith
(2017)
Continuous and Parallel: Challenges for a Standard Model of the Mind.
In Common Model of Cognition Bulletin, 466-469. AAAI.
Abstract
PDF
-
Jan Gosmann,
Aaron R. Voelker,
Chris Eliasmith
(2017)
A Spiking Independent Accumulator Model for Winner-Take-All Computation.
In Proceedings of the 39th Annual Conference of the Cognitive Science Society. London, UK. Cognitive Science Society.
Abstract
PDF
Poster
External link
-
Sugandha Sharma,
Aaron R. Voelker,
Chris Eliasmith
(2017)
A Spiking Neural Bayesian Model of Life Span Inference.
In Proceedings of the 39th Annual Conference of the Cognitive Science Society. London, UK. Cognitive Science Society.
Abstract
PDF
External link
-
Peter Blouw,
Chris Eliasmith
(2017)
Inferential Role Semantics for Natural Language.
In Thora Tenbrink, Glenn Gunzelmann, Andrew Howes and Eddy Davelaar, editors, Proceedings of the 39th Annual Conference of the Cognitive Science Society, 142–147. Philadelphia, Pennsylvania. Cognitive Science Society.
Abstract
PDF
External link
-
Eric Hunsberger,
Chris Eliasmith
(2017)
Deep learning in spiking LIF neurons.
In Cosyne Abstracts. Salt Lake City USA.
Abstract
Poster
External link
-
Aaron R. Voelker,
Ben V. Benjamin,
Terrence C. Stewart,
Kwabena Boahen,
Chris Eliasmith
(2017)
Extending the Neural Engineering Framework for Nonideal Silicon Synapses.
In IEEE International Symposium on Circuits and Systems (ISCAS). Baltimore, MD. IEEE.
Abstract
PDF
Poster
External link
-
Taylor S Clawson,
Terrence C Stewart,
Chris Eliasmith,
Silvia Ferrari
(2017)
An adaptive spiking neural controller for flapping insect-scale robots.
In IEEE Symposium Series on Computational Intelligence (SSCI), 1–7. IEEE.
Abstract
External link
-
Ivana Kajić,
Jan Gosmann,
Brent Komer,
Ryan W. Orr,
Terrence C. Stewart,
Chris Eliasmith
(2017)
A Biologically Constrained Model of Semantic Memory Search.
In Proceedings of the 39th Annual Conference of the Cognitive Science Society. London, UK. Cognitive Science Society.
Abstract
PDF
External link
-
Ivana Kajić,
Jan Gosmann,
Terrence C. Stewart,
Thomas Wennekers,
Chris Eliasmith
(2016)
Towards a Cognitively Realistic Representation of Word Associations.
In 38th Annual Meeting of the Cognitive Science Society, 2183–2188. Austin, TX. Cognitive Science Society.
Abstract
PDF
-
Murphy Berzish,
Chris Eliasmith,
Bryan Tripp
(2016)
Real-Time FPGA Simulation of Surrogate Models of Large Spiking Networks.
In ICANN, 1.
Abstract
PDF
-
Sugandha Sharma,
Brent J. Komer,
Terrence C. Stewart,
Chris Eliasmith
(2016)
A Neural Model of Context Dependent Decision Making in the Prefrontal Cortex.
In 38th Annual Meeting of the Cognitive Science Society, 1122–1127. Austin, TX. Cognitive Science Society.
Abstract
PDF
-
Sean Aubin,
Aaron R. Voelker,
Chris Eliasmith
(2016)
Improving with Practice: A Neural Model of Mathematical Development.
In Anna Papafragou Dan Grodner, Dan Mirman and John Trueswell, editors, Proceedings of the 38th Annual Conference of the Cognitive Science Society, 2012–2026. Philadelphia, Pennsylvania. Cognitive Science Society.
Abstract
PDF
External link
-
Peter Blouw,
Chris Eliasmith,
Brian Tripp
(2016)
A scaleable spiking neural model of action planning.
In Anna Papafragou Dan Grodner, Dan Mirman and John Trueswell, editors, Proceedings of the 38th Annual Conference of the Cognitive Science Society, 1583–1588. Philadelphia, Pennsylvania. Cognitive Science Society.
Abstract
PDF
External link
-
James Knight,
Aaron R. Voelker,
Andrew Mundy,
Chris Eliasmith,
Steve Furber
(2016)
Efficient SpiNNaker simulation of a heteroassociative memory using the Neural Engineering Framework.
In The 2016 International Joint Conference on Neural Networks (IJCNN). Vancouver, British Columbia. IEEE.
Abstract
External link
-
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
-
Peter Blouw,
Chris Eliasmith
(2015)
Constraint-based parsing with distributed representations.
In 37th Annual Conference of the Cognitive Science Society, 238–243.
Abstract
PDF
-
Aaron R. Voelker,
Chris Eliasmith
(2015)
Computing with temporal representations using recurrently connected populations of spiking neurons.
In Connecting Network Architecture and Network Computation. Banff International Research Station for Mathematical Innovation and Discovery.
Abstract
DOI
-
Terrence C. Stewart,
Peter Blouw,
Chris Eliasmith
(2015)
Explorations in Distributed Recurrent Biological Parsing.
In International Conference on Cognitive Modelling.
Abstract
PDF
-
Jan Gosmann,
Chris Eliasmith
(2015)
A Spiking Neural Model of the n-Back Task.
In 37th Annual Meeting of the Cognitive Science Society, 812–817.
Abstract
PDF
-
Federico Corradi,
Chris Eliasmith,
Giacomo Indiveri
(2014)
Mapping Arbitrary Mathematical Functions and Dynamical Systems to Neuromorphic VLSI Circuits for Spike-Based Neural Computation.
In IEEE International Symposium on Circuits and Systems (ISCAS). Melbourne.
Abstract
PDF
-
Brent Komer,
James Bergstra,
Chris Eliasmith
(2014)
Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn.
In ICML 2014 AutoML Workshop, 8.
Abstract
PDF
Poster
External link
-
James Bergstra,
Brent Komer,
Chris Eliasmith,
David Warde-Farley
(2014)
Preliminary Evaluation of Hyperopt Algorithms on HPOLib.
In ICML 2014 AutoML Workshop, 7.
Abstract
PDF
Poster
External link
-
Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2014)
Sentence processing in spiking neurons: A biologically plausible left-corner parser.
In 36th Annual Conference of the Cognitive Science Society, 1533–1538. Cognitive Science Society.
Abstract
PDF
-
Francesco Galluppi,
Christian Denk,
Matthias Meiner,
Terrence C Stewart,
Luis Plana,
Chris Eliasmith,
Steve Furber,
Jorg Conradt
(2014)
Event-based neural computing on an autonomous mobile platform.
In Proceedings of IEEE International Conference on Robotics and Automation (ICRA). Hong Kong.
Abstract
PDF
-
Oliver Trujillo,
Chris Eliasmith
(2014)
A spiking-neuron model of memory encoding and replay in hippocampus.
In BMC Neuroscience, 166. Organization for Computational Neurosciences.
Abstract
PDF
Poster
-
Daniel Rasmussen,
Chris Eliasmith
(2014)
A neural model of hierarchical reinforcement learning.
In Paul Bello, Marcello Guarini, Marjorie McShane, and Brian Scassellati, editors, Proceedings of the 36th Annual Conference of the Cognitive Science Society, 1252–1257. Austin. Cognitive Science Society.
Abstract
PDF
External link
-
Chris Eliasmith,
Eric Hunsberger
(2014)
Deep spiking networks and their use in large-scale brain models.
In Workshop on Deep Learning and the Brain. Cognitive Science Society.
Abstract
-
Aaron R. Voelker,
Eric Crawford,
Chris Eliasmith
(2014)
Learning large-scale heteroassociative memories in spiking neurons.
In Steffen Kopecki Oscar H. Ibarra, Lila Kari, editor, Unconventional Computation and Natural Computation. London, Ontario. Springer International Publishing.
Abstract
PDF
Poster
-
Brent Komer,
James Bergstra,
Chris Eliasmith
(2014)
Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn.
In Proceedings of the 13th Python in Science Conference, 33-39.
Abstract
PDF
Poster
External link
-
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
-
Daniel Rasmussen,
Chris Eliasmith
(2013)
A neural reinforcement learning model for tasks with unknown time delays.
In 35th Annual Conference of the Cognitive Science Society, 3257–3262.
Abstract
PDF
Poster
-
Peter Blouw,
Chris Eliasmith
(2013)
A Neurally Plausible Encoding of Word Order Information into a Semantic Vector Space.
In 35th Annual Conference of the Cognitive Science Society, 1905–1910.
Abstract
PDF
Poster
-
Aziz Hurzook,
Oliver Trujillo,
Chris Eliasmith
(2013)
Visual motion processing and perceptual decision making.
In 35th Annual Conference of the Cognitive Science Society, 2590–2595. Cognitive Science Society.
Abstract
PDF
Poster
-
Terrence C. Stewart,
Chris Eliasmith
(2013)
Parsing Sequentially Presented Commands in a Large-Scale Biologically Realistic Brain Model.
In 35th Annual Conference of the Cognitive Science Society, 3460–3467. Cognitive Science Society.
Abstract
PDF
Poster
-
Eric Hunsberger,
Peter Blouw,
James Bergstra,
Chris Eliasmith
(2013)
A Neural Model of Human Image Categorization.
In 35th Annual Conference of the Cognitive Science Society, 633–638. Cognitive Science Society.
Abstract
PDF
-
Travis DeWolf,
Chris Eliasmith
(2013)
A neural model of the development of expertise.
In Robert L. West & Terrence C. Stewart, editor, The 12th International Conference on Cognitive Modelling, 119-124. Ottawa, Ontario. Carleton University.
Abstract
PDF
Poster
-
Xuan Choo,
Chris Eliasmith
(2013)
General Instruction Following in a Large-Scale Biologically Plausible Brain Model.
In 35th Annual Conference of the Cognitive Science Society, 322–327. Cognitive Science Society.
Abstract
PDF
-
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
-
Eric Crawford,
Matthew Gingerich,
Chris Eliasmith
(2013)
Biologically Plausible, Human-scale Knowledge Representation.
In 35th Annual Conference of the Cognitive Science Society, 412–417.
Abstract
PDF
-
Sergio Davies,
Terrence C. Stewart,
Chris Eliasmith,
Steve Furber
(2013)
Spike-based learning of transfer functions with the SpiNNaker neuromimetic simulator.
In International Joint Conference on Neural Networks.
Abstract
PDF
-
Chris Eliasmith,
Terrence C. Stewart
(2012)
Nengo and the Neural Engineering Framework: From Spikes to Cognition.
In Cognitive Science Society, 22-23.
Abstract
PDF
-
Swadesh Choudhary,
Steven Sloan,
Sam Fok,
Alexander Neckar,
Eric Trautmann,
Peiran Gao,
Terrence C. Stewart,
Chris Eliasmith,
Kwabena Boahen
(2012)
Silicon Neurons that Compute.
In International Conference on Artificial Neural Networks, volume 7552, 121-28.
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
-
Francesco Galluppi,
Sergio Davies,
Terrence C. Stewart,
Chris Eliasmith,
Steve Furber
(2012)
Real Time On-Chip Implementation of Dynamical Systems with Spiking Neurons.
In IJCNN.
Abstract
PDF
-
Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2012)
Spaun: A Perception-Cognition-Action Model Using Spiking Neurons.
In Cognitive Science Society, 1018-1023.
Abstract
PDF
-
Terrence C. Stewart,
Chris Eliasmith
(2011)
Neural Cognitive Modelling: A Biologically Constrained Spiking Neuron Model of the Tower of Hanoi Task.
In Cognitive Science Society. Austin, TX.
Abstract
PDF
-
Julie Dethier,
Paul Nuyujukian,
Chris Eliasmith,
Terrence C. Stewart,
Shauki A. Elassaad,
Krishna Shenoy,
Kwabena Boahen
(2011)
A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm.
In Neural Information Processing Systems (NIPS) 24.
Abstract
PDF
External link
-
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
-
Bruce Bobier,
Terrence C. Stewart,
Chris Eliasmith
(2011)
The attentional routing circuit: receptive field modulation through nonlinear dendritic interactions.
In Cognitive and Systems Neuroscience. Salt Lake City, UT.
Abstract
PDF
-
Travis DeWolf,
Chris Eliasmith
(2011)
A spiking neuron model of movement and pre-movement activity in M1.
In Cognitive and Systems Neuroscience. Salt Lake City, UT.
Abstract
-
Bruce Bobier,
Terrence C. Stewart,
Chris Eliasmith
(2010)
Dynamic Routing Model for Visuospatial Attention.
In Cognitive and Systems Neuroscience. Poster from COSYNE 2010.
Abstract
PDF
-
Maya Carrillo,
Esau Villatoro-Tello,
Aurelio Lopez-Lopez,
Chris Eliasmith,
Luis Villasenor-Pineda,
Manuel Montes-y-Gomez
(2010)
Concept Based Representations for Ranking in Geographic Information Retrieval.
In IceTAL 2010. Reykjavik, Iceland.
Abstract
PDF
-
Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2010)
Symbolic Reasoning in Spiking Neurons: A Model of the Cortex/Basal Ganglia/Thalamus Loop.
In Stellan Ohlsson and Richard Catrambone, editors, 32nd Annual Meeting of the Cognitive Science Society, 1100–1105. Portland, Oregon. Cognitive Science Society.
Abstract
PDF
-
Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2010)
Dynamic Behaviour of a Spiking Model of Action Selection in the Basal Ganglia.
In 10th International Conference on Cognitive Modeling.
Abstract
PDF
-
Yichuan Tang,
Chris Eliasmith
(2010)
Deep networks for robust visual recognition.
In International Conference on Machine Learning.
Abstract
PDF
-
Travis DeWolf,
Chris Eliasmith
(2010)
NOCH: A framework for biologically plausible models of neural motor control.
In 20th Annual Neural Control of Movement Conference. Naples, FL.
Abstract
-
Xuan Choo,
Chris Eliasmith
(2010)
A Spiking Neuron Model of Serial-Order Recall.
In Richard Cattrambone and Stellan Ohlsson, editors, 32nd Annual Conference of the Cognitive Science Society. Portland, OR. Cognitive Science Society.
Abstract
PDF
-
Daniel Rasmussen,
Chris Eliasmith
(2010)
A neural model of rule generation in inductive reasoning.
In Richard Cattrambone and Stellan Ohlsson, editors, 32nd Annual Conference of the Cognitive Science Society. Portland, OR. Cognitive Science Society.
Abstract
PDF
-
Terrence C. Stewart,
Chris Eliasmith
(2009)
Spiking neurons and central executive control: The origin of the 50-millisecond cognitive cycle.
In 9th International Conference on Cognitive Modelling.
Abstract
PDF
-
Maya Carrillo,
Chris Eliasmith,
Aurelio Lopez-Lopez
(2009)
Combining Text Vector Representations for Information Retrieval.
In Proceedings of the 12th International Conference on Text, Speech and Dialogue.
Abstract
PDF
-
Lloyd Elliott,
Chris Eliasmith
(2009)
MCMC with spiking neurons.
In NIPS Workshop on Bayesian Inference in the Brain.
Abstract
PDF
-
Maya Carrillo,
Esau Villatoro-Tello,
Aurelio Lopez-Lopez,
Chris Eliasmith,
Manuel Montes-y-Gomez,
Luis Villasenor-Pineda
(2009)
Concept representations in Geographic Information Retrieval as Re-ranking Strategies.
In 18th ACM Conference on Information and Knowledge Management.
Abstract
-
Terrence C. Stewart,
Yichuan Tang,
Chris Eliasmith
(2009)
A biologically realistic cleanup memory: Autoassociation in spiking neurons.
In 9th International Conference on Cognitive Modelling.
Abstract
PDF
-
Jonathan M. Fishbein,
Chris Eliasmith
(2008)
Integrating structure and meaning: A new method for encoding structure for text classification.
In Advances in Information Retrieval, 514-521. Springer.
Abstract
PDF
DOI
-
Terrence C. Stewart,
Chris Eliasmith
(2008)
Building production systems with realistic spiking neurons.
In Cognitive Science Conference. Washington, DC.
Abstract
PDF
-
Jonathan M. Fishbein,
Chris Eliasmith
(2008)
Methods for augmenting semantic models with structural information for text classification.
In Advances in Information Retrieval, 575-579. Springer.
Abstract
PDF
DOI
-
Chris Eliasmith
(2005)
Cognition with neurons: A large-scale, biologically realistic model of the Wason task.
In 27th Annual Meeting of the Cognitive Science Society.
Abstract
PDF
-
Ray Singh,
Chris Eliasmith
(2004)
A dynamic model of working memory in the PFC during a somatosensory discrimination task.
In Computational and Systems Neuroscience. Cold Spring Harbour, NY.
Abstract
-
Chris Eliasmith
(2004)
Learning context sensitive logical inference in a neurobiological simulation.
In AAAI Fall Symposium: Compositional Connectionism in Cognitive Science, 17-20. AAAI Press.
Abstract
PDF
-
Chris Eliasmith,
John Conklin,
Ray Singh
(2004)
A neurobiological simulation of deductive reasoning.
In Computational and Systems Neuroscience. Cold Spring Harbour, NY.
Abstract
Technical Reports and Preprints
-
P. Michael Furlong,
Andreas Stöckel,
Terrence C. Stewart,
Chris Eliasmith
(2022)
Learned Legendre Predictor: Learning with Compressed Representations for Efficient Online Multistep Prediction.
Technical Report, Centre for Theoretical Neuroscience.
Abstract
PDF
External link
-
Narsimha Chilkuri,
Eric Hunsberger,
Aaron Voelker,
Gurshaant Malik,
Chris Eliasmith
(2021)
Language Modeling using LMUs: 10x Better Data Efficiency or Improved Scaling Compared to Transformers.
arXiv preprint.
Abstract
PDF
arXiv
-
Aaron R. Voelker,
Daniel Rasmussen,
Chris Eliasmith
(2020)
A Spike in Performance: Training Hybrid-Spiking Neural Networks with Quantized Activation Functions.
arxiv.
Abstract
PDF
DOI
-
Ivana Kajić,
Chris Eliasmith
(2018)
Evaluating the psychological plausibility of word2vec and GloVe distributional semantic models.
Technical Report, Centre for Theoretical Neuroscience, Waterloo, ON.
Abstract
PDF
DOI
External link
-
Peter Blouw,
Xuan Choo,
Eric Hunsberger,
Chris Eliasmith
(2018)
Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware.
arXiv preprint arXiv:1812.01739.
Abstract
PDF
arXiv
-
Aaron R. Voelker,
Chris Eliasmith
(2017)
Methods for applying the Neural Engineering Framework to neuromorphic hardware.
arXiv preprint arXiv:1708.08133.
Abstract
PDF
arXiv
-
Aaron R. Voelker,
Chris Eliasmith
(2017)
Analysis of oscillatory weight changes from online learning with filtered spiking feedback.
Technical Report, Centre for Theoretical Neuroscience, Waterloo, ON.
Abstract
DOI
External link
-
Andreas Stöckel,
Aaron R. Voelker,
Chris Eliasmith
(2017)
Point Neurons with Conductance-Based Synapses in the Neural Engineering Framework.
arXiv preprint arXiv:1710.07659.
Abstract
PDF
arXiv
-
Eric Hunsberger,
Chris Eliasmith
(2016)
Training Spiking Deep Networks for Neuromorphic Hardware.
arXiv:1611.05141.
Abstract
DOI
arXiv
-
Chris Eliasmith,
Jan Gosmann,
Xuan-Feng Choo
(2016)
BioSpaun: A large-scale behaving brain model with complex neurons.
ArXiv.
Abstract
PDF
-
Eric Hunsberger,
Chris Eliasmith
(2015)
Spiking Deep Networks with LIF Neurons.
arXiv:1510.08829.
Abstract
arXiv
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