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Speaker:

Dr. Eliasmith

Content:

This course will focus on applying recent methods in computational
neuroscience to constructing cognitive models.  Methods to successfully
address the following four main challenges will be presented: 1)
large-scale neurally realistic modeling; 2) implementing
high-dimensional nonlinear and dynamic computation in spiking neural
networks; 3) constructing symbolic (i.e., language-like)
representations in spiking neurons; and 4) manipulating and processing
such representations to perform cognitive tasks in an extensible
architecture.

• Slides 1
• Slides 2
• Slides 3
• Slides 4

Disciplines:

The topics that will be discussed include some basic neuroanatomy and
neurophysiology, theoretical neuroscience, computer science

References:

Relevant background can be found in this bibliography:
http://compneuro.uwaterloo.ca/cnrglab/?q=biblio

• Eliasmith, C., Anderson, C.H. (2003).  Neural engineering: Computation, representation, and dynamics in neurobiological systems.   Cambridge, MA: MIT Press.
• Eliasmith, C. (2005).  A unified approach to building and controlling spiking attractor networks.  Neural computation. 7, 1276--1314.)
• Stewart, T., Eliasmith, C. (2009).  Compositionality and biologically plausible models.  In W. Hinzen, E. Machery, and M. Werning (Ed.), Oxford Handbook of Compositionality.
• Stewart, T.C., Tripp, B., Eliasmith, C. (2009).  Python scripting in the Nengo simulator.  Frontiers in Neuroinformatics. 3(7),
• Stewart, T.C., Choo, X., Eliasmith, C. (2010).  Symbolic Reasoning in Spiking Neurons: A Model of the Cortex/Basal Ganglia/Thalamus Loop. 32nd Annual Meeting of the Cognitive Science Society.

CV:

Dr. Eliasmith holds a Canada Research Chair in Theoretical Neuroscience
at the University of Waterloo.  He is also director of the Centre for
Theoretical Neuroscience.  He has co-authored the book Neural
Engineering with MIT Press and is currently working on a new book
entitled 'How to Build a Brain: A neural architecture for
biological cognition' to come out in 2011 with Oxford University Press.