Pain and Reorganization after Amputation: Is Interoceptive Prediction a Key?

Abstract

There is an ongoing discussion on the relevance of brain reorganization following amputation for phantom limb pain. Recent attempts to provide explanations for seemingly controversial findings-specifically, maladaptive plasticity versus persistent functional representation as a complementary process-acknowledged that reorganization in the primary somatosensory cortex is not sufficient to explain phantom limb pain satisfactorily. Here we provide theoretical considerations that might help integrate the data reviewed and suppose a possible additional driver of the development of phantom limb pain-namely, an error in interoceptive predictions to somatosensory sensations and movements of the missing limb. Finally, we derive empirically testable consequences based on our considerations to guide future research.

Keywords: cortical reorganization; interoception; phantom limb pain; prediction error; predictive coding.

Figure 1.

Theoretical models for understanding phantom limb pain. Right: In healthy subjects, the stimulation of the lip results in activation of its representation in the primary somatosensory cortex (S1), while motor programming or motor imagery of the hand leads to activation of sensorimotor representations of the hand. Left: Amputation leads to somatotopic reorganization in the respective contralateral S1 area such that peripheral stimulation of areas in close proximity accesses the S1 area of the amputated limb. Stimulation of the lip hence leads to neural signaling not only within the lip area but also in the area of the amputated hand. (A) The model of maladaptive plasticity indicates that neural activation in the hand area also involves nociceptive neurons and hence directly leads to pain. (B) The model of persistent pain representation suggests that activation of motor programs in the primary motor cortex leads to activation of somatosensory neurons in the respective area. Hence, the imagination of movement of the amputated hand is followed by activation of the reorganized S1 hand area. (C) In the view of predictive coding, we assume that activation of the reorganized S1 hand representation either to peripheral stimulation of neighbor representations that received access or by motor programming leads to a prediction error, as this activation does not match other sensory input or expected sensory consequences for motor control. The prediction error may directly lead to the percept of pain and additionally to attempts for error reduction. Those attempts include 1) the increase of salience processing, which might enhance pain perception, and 2) peripheral and central disinhibition, allowing increased information flow as an attempt to 3) adjust prediction errors.

Figure 2.

Visualization of the neurologic signature of physical pain identified in a series of four studies by Wager using machine learning analysis for an objective prediction of pain intensity (Wager and others 2013). Red areas show positive predictive values: CER = cerebellum; dACC = dorsal anterior cingulate cortex; HY = hypothalamus; INS = insula; PAG = periaqueductal gray matter; S2 = secondary somatosensory cortex; SMA = supplementary motor area; SMG = supramarginal gyrus; THAL = thalamus. Regions showing negative predictive values were not included in the figure (for these regions, see Wager and others 2013). As the pain signature shares the nodes of the anterior cingulate gyrus and both insulae with the salience network (Ham and others 2013), it enables the initiation of fast and salient processing of pain stimuli.

Figure 3.

Incidence of physical sensations triggered incongruent visual and motoric information as reported by McCabe and others (2005). The study investigated whether conflicting motor and sensory information processing can lead to pain in healthy volunteers. For this, 41 healthy adults were seated in front of a metal frame with a mirror on the one side and a whiteboard on the other side. They placed one limb on each side of the frame such that one arm and leg were hidden from view. Participants then moved their limbs congruently (e.g., both arms up and down at the same time) or incongruently (e.g., one arm up and the other arm down) while looking at the mirror (visual feedback) or the whiteboard (control). After the movement, subjects described all feelings and changes in either limb: 66% of participants reported symptoms at least in one condition, with most reports in the incongruent mirror condition. Of these participants, most reported symptoms of peculiarity, the perception of the loss of a limb, or having an extra limb and painful sensations. Noteworthy, the participants reported such sensations more often in the incongruent condition than in the congruent condition, which is of high importance with respect to phantom limb pain.

Figure 4.

Referred sensations in a patient with amputation of the left forearm and chronic phantom limb pain (PLP) with experience of telescoping. Standardized body sites were touched in the face and the upper trunk with a brush or von Frey hairs with 16 or 512 mN. Each dot represents one stimulation location, each triangle an evoked cramping after stimulation. Although most locations did not constantly evoke PLP (blue), some points never elicited PLP (black), while the stimulation left to the nose (contralateral to the amputation) always evoked cramping in the phantom hand (red). Adapted from Dietrich, Nehrdich, Zimmer, and others (2018).