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A Computational Framework for Understanding the Impact of Prior Experiences on Pain Perception and Neuropathic Pain

Fig 6

Results from hierarchical Kalman filter simulations of how the value of the internal model parameters are determined by previous painful experiences and may contribute to neuropathic pain following a nerve injury.

In the left panels, A = 0.99, yielding persistent pain (solid red line in lower plots) following noxious stimuli (indicated by stars). This value of A results in (solid blue line in the upper plot), and a high risk of spontaneous neuropathic pain following a nerve injury (corresponding to a change in the value of R, indicated by the vertical dashed line). In the middle panels A = 0.9, resulting in quickly transient pain, a lower value of and a lower risk of spontaneous neuropathic pain. In the right panels A = 0.9 again, but in this simulation, there are no noxious stimuli. These circumstances result in and a higher risk of spontaneous neuropathic pain than in the example in the middle. The shaded areas indicate the interquartile ranges.

doi: https://doi.org/10.1371/journal.pcbi.1012097.g006