A Computational Framework for Understanding the Impact of Prior Experiences on Pain Perception and Neuropathic Pain
Fig 8
Schematic figure of the Kalman filter model, depicting the evolution of states across iterations and the relationship between model variables and parameters.
The related variance/noise/covariance to each parameter is indicated next to the arrows. “Top-down” predictions, , are formed by the control input, u, and the internal model,
, where
,. The prediction is combined with “bottom-up” sensory input, z, to form the final estimate,
, which, in our model, reflects the perceived level of pain.