Effects of perineuronal nets on neural firing properties

Abstract The perineuronal nets (PNNs) are sugar coated protein structures that encapsulate certain neurons in the brain, such as parvalbumin positive (PV) inhibitory neurons. As PNNs are theorized to act as a barrier to ion transport, they may effectively increase the membrane charge-separation distance, thereby affecting the membrane capacitance. Tewari et al. (2018) found that degradation of PNNs induced a 25\%-50\% increase in capacitance and a reduction in the firing rates of PV-cells. In the current work, we attempted to reproduce the experiments by Tewari et al. using a selection of computational neuron models, ranging in complexity from a single compartment Hodgkin-Huxley model to morphologically detailed PV-neuron models. In none of these models, the experimentally reported change in capacitance was sufficient to explain the experimentally reported reduction in firing rate. We therefore hypothesized that PNN degradation in the experiments affected cellular reversal potentials and ion channel conductances in addition to the capacitance. In simulations, we explored how various model parameters affected the firing rate of the model neurons, and identified main candidates for explaining the experiments.