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Learning Context Sensitive Logical Inference in a Neurobiolobical Simulation Chris Eliasmith
 

Summary: Learning Context Sensitive Logical Inference in a Neurobiolobical Simulation
Chris Eliasmith
Dept. of Philosophy and Dept. of Systems Design Engineering
University of Waterloo, Waterloo, Ontario
Introduction and model description
There remains a large difference between the kinds of mod-
els typical of cognitive neuroscience versus those typical of
systems neuroscience: the former tend to be `high-level',
where components of the model are very large portions of
cortex and the relevant behaviors are cognitive, whereas the
latter tend to be `low-level', where each component is a
single cell and the relevant phenomena are sub-personal.
This is true despite the fact that researchers in these areas
share a similar interest in brain-based explanations of be-
havioral phenomena. In this paper I apply the neural engi-
neering framework (NEF) described in Eliasmith & Ander-
son (2003) to describe a model that is both `high-level' and
`low-level'. I do this by constructing a biologically detailed
model of a traditionally cognitive phenonema logical in-
ference.

  

Source: Anderson, Charles H. - Departments of Anatomy and Neurobiology & Physics, Washington University in St. Louis

 

Collections: Computer Technologies and Information Sciences; Biology and Medicine