Description
Explicit coding and categoriesA code, such as the neural code, is a mapping of items to codewords. The
neural codewords, i.e. the neural activity patterns have interesting
properties, such as the density/sparseness, and the breadth of tuning of
the individual neurons. These 'internal' properties have important
implications themselves, such as the storage capacity of an associative
network receiving such input. However, the 'semantic' aspects of the
code, which refer to the connection between codewords and the things in
the world to which they refer, are at least as important. Such semantic
aspects include the explicitness of the code (i.e. whether neurons
divide the world into meaningful subsets), selectivity, invariance, and
categorisation. An important goal of sensory processing is to form
meaningful categories, and such categories should be related to the
semantic properties the neural code itself. I will discuss a simple
hypothesis about the way in which this could be achieved by overlaps of
the codewords alone, mapping an arbitrarty semantic net into a code and
vice versa.
| Period | 9 Dec 2011 |
|---|---|
| Event title | Bayesian Inference: From Spikes to Behaviour, Bernstein Center for Computational Neuroscience Tübingen |
| Event type | Conference |
| Location | University of Tuebingen, GermanyShow on map |