OxTalks will soon move to the new Halo platform and will become 'Oxford Events.' There will be a need for an OxTalks freeze. This was previously planned for Friday 14th November – a new date will be shared as soon as it is available (full details will be available on the Staff Gateway).
In the meantime, the OxTalks site will remain active and events will continue to be published.
If staff have any questions about the Oxford Events launch, please contact halo@digital.ox.ac.uk
Human thought is inherently symbolic. For example, working memory can manipulate information according to rules that apply to any kind of content. How can populations of neurons achieve this? We model prefrontal cortex as holding flexible codes, that rapidly change the way they map onto the world.
Three examples of symbolic tasks include 1) binding features into objects in working memory, 2) pairing arbitrary stimuli with responses to perform zero-shot instructed actions, or 3) filling the grammatical roles in a sentence with arbitrary contents. These tasks can be solved with flexible codes. To encode novel information, we employ transient strengthening of synapses. This can form new stable states (attractors), or generate symbolic grammars to represent sentences. This new kind of neural network can turn a static idea into a sequence of words and back, using transient synaptic facilitation to hold grammatical relationships between words.
I will demonstrate some tiny neural networks that apply this flexible coding to working memory, task rules, and language. But are they a good model of the prefrontal cortex? I will show some cases in which the model agrees or disagrees with empirical data.
