# Computational modeling of Adelta-fiber-mediated nociceptive detection of electrocutaneous stimulation

## TL;DR

This paper presents a computational model to study how electrocutaneous stimulation is detected through Adelta fibers in the nociceptive pathway.

## Contribution

A neurophysiologically plausible model is developed to characterize peripheral and central mechanisms of nociception.

## Key findings

- Both models show similar psychophysical functions but differ in computational efficiency.
- Model-based effects on detection thresholds align with human subject data.
- Temporal stimulus parameters significantly influence detection thresholds.

## Abstract

Sensitization is an example of malfunctioning of the nociceptive pathway in either the peripheral or central nervous system. Using quantitative sensory testing, one can only infer sensitization, but not determine the defective subsystem. The states of the subsystems may be characterized using computational modeling together with experimental data. Here, we develop a neurophysiologically plausible model replicating experimental observations from a psychophysical human subject study. We study the effects of single temporal stimulus parameters on detection thresholds corresponding to a 0.5 detection probability. To model peripheral activation and central processing, we adapt a stochastic drift-diffusion model and a probabilistic hazard model to our experimental setting without reaction times. We retain six lumped parameters in both models characterizing peripheral and central mechanisms. Both models have similar psychophysical functions, but the hazard model is computationally more efficient. The model-based effects of temporal stimulus parameters on detection thresholds are consistent with those from human subject data.