Recall Performance Improvement in a Bio-Inspired Model of the Mammalian Hippocampus

<p>Mammalian hippocampus is involved in short-term formation of declarative memories. We employed abio-inspired neural model of hippocampal CA1 region consisting of a zoo of excitatory and inhibitorycells. Cells’ firing was timed to a theta oscillation paced by two distinct neuronal populations exhibitinghighly regular bursting activity, one tightly coupled to the trough and the other to the peak of theta. Tosystematically evaluate the model’s recall performance against number of stored patterns, overlaps and‘active cells per pattern’, its cells were driven by a non-specific excitatory input to their dendrites. Thisexcitatory input to model excitatory cells provided context and timing information for retrieval ofpreviously stored memory patterns. Inhibition to excitatory cells’ dendrites acted as a non-specific globalthreshold machine that removed spurious activity during recall. Out of the three models tested, ‘model 1’recall quality was excellent across all conditions. ‘Model 2’ recall was the worst. The number of ‘activecells per pattern’ had a massive effect on network recall quality regardless of how many patterns werestored in it. As ‘active cells per pattern’ decreased, network’s memory capacity increased, interferenceeffects between stored patterns decreased, and recall quality improved. Key finding was that increasedfiring rate of an inhibitory cell inhibiting a network of excitatory cells has a better success at removingspurious activity at the network level and improving recall quality than increasing the synaptic strength ofthe same inhibitory cell inhibiting the same network of excitatory cells, while keeping its firing rate fixed.</p>