Attractor Networks Nets Mozer 2008 pdf
<p>Feb 24, 2009 7:20 PM
 
Artificial neural networks (ANNs), sometimes referred to as connectionist networks, are computational
models based loosely on the neural architecture of the brain. Over the past twenty years, ANNs have
proven to be a fruitful framework for modeling many aspects of cognition, including perception, attention,
learning and memory, language, and executive control. A particular type of ANN, called an <b>attractor net-
work, is central to computational theories of consciousness,</b> because attractor networks can be analyzed in
terms of properties—such as <b>temporal stability, and strength, quality, and discreteness of representation—
that have been ascribed to conscious states. Some theories have gone so far as to posit that attractor nets are
the computational substrate from which conscious states arise</b>.
 
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