There remains a large difference between the kinds of models typical
of cognitive neuroscience versus those typical of systems
neuroscience: the former tend to be highlevel , 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
behavioral phenomena. In this paper I apply the neural engineering
framework (NEF) described in Eliasmith and Anderson (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 inference.