Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity

TLDR

The authors introduce a two‑dimensional integrate‑and‑fire model that combines an exponential spike mechanism with an adaptation equation. A systematic method estimates its parameters using current‑clamp pulses and ramps and applies the model to a detailed conductance‑based regular spiking neuron. The model accurately predicts 96 % of spike timings within ±2 ms, performs best in high‑conductance states, and reproduces several in‑vitro electrophysiological classes.

Abstract

We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiological protocols (current-clamp injection of pulses and ramps) and apply it to a detailed conductance-based model of a regular spiking neuron. Our simple model predicts correctly the timing of 96% of the spikes (+/-2 ms) of the detailed model in response to injection of noisy synaptic conductances. The model is especially reliable in high-conductance states, typical of cortical activity in vivo, in which intrinsic conductances were found to have a reduced role in shaping spike trains. These results are promising because this simple model has enough expressive power to reproduce qualitatively several electrophysiological classes described in vitro.