- Poster presentation
- Open Access
Electrocutaneous stimulus setting for identification of the ascending nociceptive pathway
© Yang et al; licensee BioMed Central Ltd. 2013
- Published: 8 July 2013
- Stimulus Setting
- Artificial Dataset
- Multiple Combination
- Nociceptive Pathway
- Nociceptive System
We model this pathway as a cascaded two leaky integrate-and-fire models followed by a nonlinear binary detector at the supraspinal level (Figure 1B). A white noise source presents at the output of neuronal activity. The model has five unknown parameters: two time constants (τ1, τ2 [msec]), two compound gain-threshold parameters (α1, α2) and standard deviation of the neuronal noise (σε). The multiple combinations of stimulus settings depend on two variables IPIt and PWt [msec] (Table 1). Using each setting to generate an artificial dataset, we estimate the parameters by maximizing the likelihood function of these parameters and the stimulus-response dataset. Varying IPIt and PWt, we look for an optimal setting of the stimulus.
For each setting, we present estimation errors in a cumulative distribution with particular values of the parameters, θ= (τ1 = 0.2, τ2 = 20, α1 = 0.1, α2 = 0.04, σε = 0.005). The chance with an estimation error below 17% is a half when IPIt is 10 and PWt is 0.2. Furthermore, we show the median of the estimation error in a 2D plot with varying IPIt and PWt.
To identify the ascending nociceptive pathway, we have proposed an estimation approach using stimulus-response measurements. Optimal temporal settings of stimulus are found for a reliable estimation within the region of IPIt 10-25 [msec] and PWt 0.15-0.4 [msec].
This research is supported by the Dutch Technology Foundation STW, which is part of the Netherlands Organisation for Scientific Research (NWO) and partly funded by the Ministry of Economic Affairs, Agriculture and Innovation.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.