Attractor Dynamics In Realistic Hippocampal Networks

INTRODUCTION Autoassociative attractor neural networks 1,2 provide a powerful paradigm for the storage and recall of memories, however, their biological plausibility has always remained in question. Given the complexity and variability of biological networks, it seems likely that a "biological" attractor network must be regulated by some control structure. We describe a functional architecture for implementing the Hopfield attractor paradigm in a model of the CA3 region of the hippocampus. In this model the control structure is provided by the intrinsic and extrinsic rhythms (gamma and theta) of the hippocampus and neuromodulatory input. Cellular-level simulations are shown that serve as a "proof-of-concept." The function of the model is demonstrated in the left-hand panel of Figure 1. Shown are hypothetical spike traces of CA3 pyramidal cells with idealized gamma and theta population rhythms shown for reference. The state of the network is defined by the sp