Rapid Correspondence Finding in Networks of Cortical Columns

We describe a neural network able to rapidly establish correspondence between neural fields. The network is based on a cortical columnar model described earlier. It realizes dynamic links with the help of specialized columns that evaluate similarities between the activity distributions of local feature cell populations, are subject to a topology constraint, and gate the transfer of feature information between the neural fields. Correspondence finding requires little time (estimated to 10-40ms in physiological terms) and is robust to noise in feature signals.