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Journal of Computational Neuroscience|February 17, 2005
A controlled attractor network model of path integration in the ratJohn Conklin, Chris EliasmithStudies in History and Philosophy of Science|April 7, 2011
How we ought to describe computation in the brainChris EliasmithTopics in Cognitive Science|January 19, 2012
The complex systems approach: rhetoric or revolutionChris EliasmithNeural Computation|May 20, 2005
A unified approach to building and controlling spiking attractor networksChris EliasmithNeural Computation|October 20, 2020
Passive Nonlinear Dendritic Interactions as a Computational Resource in Spiking Neural NetworksAndreas Stöckel, Chris EliasmithPlos One|February 23, 2016
Optimizing Semantic Pointer Representations for Symbol-Like Processing in Spiking Neural NetworksJan Gosmann, Chris EliasmithBiological Cybernetics|May 17, 2011
Normalization for probabilistic inference with neuronsChris Eliasmith, James MartensCerebral Cortex (New York, N.Y. : 1991)|October 18, 2006
Neural populations can induce reliable postsynaptic currents without observable spike rate changes or precise spike timingBryan Tripp, Chris EliasmithThe Behavioral and Brain Sciences|May 14, 2013
God, the devil, and the details: Fleshing out the predictive processing frameworkDaniel Rasmussen, Chris EliasmithCurrent Opinion in Neurobiology|April 9, 2014
The use and abuse of large-scale brain modelsChris Eliasmith, Oliver TrujilloPageof 13