# Complex excitability and “flipping" of granule cells: An experimental and computational study

## TL;DR

This study explores how artificial ion channels affect the firing patterns of granule cells in the Dentate Gyrus and identifies a new behavior called 'flipping' that allows cells to overcome depolarization block.

## Contribution

The study introduces a novel 'flipping' behavior in granule cells and links it to the number of states in the sodium channel model.

## Key findings

- Mimicked Na/KM channels significantly affect firing rates of low-frequency granule cells.
- 44% of cells exhibited 'flipping' behavior, overcoming depolarization block at higher current steps.
- A computational model links 'flipping' to the number of states in the sodium channel.

## Abstract

In response to prolonged depolarizing current steps, different classes of neurons display specific firing characteristics (i.e., excitability class), such as a regular train of action potentials with more or less adaptation, delayed responses, or bursting. In general, one or more specific ionic transmembrane currents underlie the different firing patterns. Here, we sought to investigate the influence of artificial sodium-like (Na channels) and slow potassium-like (KM channels) voltage-gated channels conductances on firing patterns and transition to depolarization block (DB) in Dentate Gyrus granule cells with dynamic clamp - a computer-controlled real-time closed-loop electrophysiological technique, which allows to couple mathematical models simulated in a computer with biological cells. Our findings indicate that the mimicked extra Na/KM channels significantly affect the firing rate of low-frequency cells, but not that of high-frequency cells. Moreover, we have observed that 44 percent of recorded cells exhibited what we have called a “flipping” behavior. This means that these cells were able to overcome the DB and generate trains of action potentials at higher current injection steps. We have developed a mathematical model of “flipping" cells to explain this phenomenon. Based on our computational model, we conclude that the appearance of “flipping" is linked to the number of states for the sodium channel of the model.