Oscillatory model of the hippocampal memory

We describe a biologically inspired oscillatory neural network for memorizing temporal sequences of neural activity patterns. The neural network consists of interactive neural oscillators with all-to-all excitatory connections forced by a slow T-periodic signal. The dynamics of the network are viewed through a time window with duration T. The network memorizes binary patterns in terms of low and high activity of the corresponding oscillators. The learning rule is temporally asymmetric, and it takes into account the activity level of pre- and post-”synaptic” oscillators in two contiguous time windows. Recall by the network is fast: all memorized patterns of sequences are reproduced in the correct order during the same time window, but with a short time delay. The applicability of these results to studies of the hippocampus is discussed