Tuesday, July 22, 2014

A simple oscillatory short-term memory

Type: 
Peer-reviewed Article
Research Area: 
Cognitive Neuroscience

Oscillatory neural network models have been an increasing focus of study over the last several years. These models consist of recurrent neural networks whose dynamics are characterized by persistent learned/designed rhythmic activity. Here we consider simple oscillatory memories for short-term retention of items occurring as temporal sequences. By incorporating decay as well as interference, we find that it is easy to match behavioral data from human subjects recalling temporal sequences under different situations by adjusting a single parameter in the model. These results suggest that simple oscillatory memories capture at least some key properties of human short-term memory, and might be used effectively in future biologically-inspired cognitive architectures.

Publication: 
Association for the Advancement of Artificial Intelligence
Year: 
2009
Notes: 
Upcoming
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