Influence of STDP rule choice and network connectivity on polychronous groups and cell ensembles in spiking neural networks

Spike-timing dependent plasticity plays an important role in how biological neural networks modify themselves with experience. However, the relationship between STDP and memory is not fully understood. Previously, an important advancement in understanding the relationship between spike-timing dependent plasticity (STDP) and memory was made through cortical simulations. The proposed memory items, polychronous groups (PGs), combined the network anatomy with precise spike-timing relationships between the connected cells of the network. However, there are some challenges with this previous work. It is unclear how different STDP rules would impact the PG results and if the PG results are complementary with purely spike-pattern defined memory items called cell ensembles (CEs). Lastly, it is unclear how these results are affected by changes in network connectivity. We address these challenges by comparing the PGs and CEs detected in spiking neural network simulations of cortical and hippocampal CA1 networks with two different STDP rule implementations. We show that the PG and CE results differ greatly for the two different STDP rules and for the cortical and CA1 networks. Our results show an important disconnect between anatomically defined and spike-pattern defined memories in spiking neural network simulations illustrating that care must be taken when drawing conclusions on the relationship between STDP and memory in simulation studies.