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

Fig 3

Results from Kalman filter simulations of neuropathic pain.

Damage to the sensory nervous system may result in increased uncertainty of sensory input relating to the level of tissue damage. Depending on the level of uncertainty (value of R, dash-dotted purple line in upper plots) and the value of the internal model parameter (solid blue lines in upper plots), these changes could result in spontaneous neuropathic pain (solid red lines in lower plot, the shaded area indicates the interquartile range).The initial overshoot for in the two rightmost plots, where R = 80² and R = 800², is caused by the initial variance of the estimate P, being low. When P≪R, the posterior estimate is dominated by the prior, which here predicts increasing pain since . Due to the uncertainty in the sensory input, the value of P rapidly increases, until an equilibrium is reached, in which the posterior still is strongly influenced by the prior, but also has some influence from the noisy sensory input.

doi: https://doi.org/10.1371/journal.pcbi.1012097.g003