UC Irvine

We developed a cooperative model of the cortical column incorporating an idealized subunit, the trion (which represents a localized group of neurons), and a discrete time step for firing. We found that networks composed of a small number of trions (with symmetric interactions) supported up to thousands of quasi-stable, periodic firing patterns (MPs) which could be selected out with only small changes in interaction strengths using a Hebb-type algorithm. Here we report a study of the associative recall properties showing striking features: By considering all possible initial firing patterns (for a given set of network connections), we find 1) It takes on the average only 2-5 time steps to recall an MP. 2) Many of the MPs can be individually accessed by thousands of different initial patterns. The variety of examples presented illustrate the rich, general nature of the model.