Biased pain reports through vicarious information: A computational approach to investigate the role of uncertainty

Topographic mapping of the sensorimotor qualities of empathic reactivity: A psychophysiological study in people with spinal cord injuries

The experience of empathy for pain is underpinned by sensorimotor and affective dimensions which, although interconnected, are at least in part behaviorally and neurally distinct. Spinal cord injuries (SCI) induce a massive, below-lesion level, sensorimotor body-brain disconnection. This condition may make it possible to test whether sensorimotor deprivation alters specific dimensions of empathic reactivity to observed pain. To explore this issue, we asked SCI people with paraplegia and healthy controls to observe videos of painful or neutral stimuli administered to a hand (intact) or a foot (deafferented). The stimuli were displayed by means of a virtual reality set-up and seen from a first person (1PP) or third person (3PP) visual perspective. A number of measures were recorded ranging from explicit behaviors like explicit verbal reports on the videos, to implicit measures of muscular activity (like EMG from the corrugator and zygomatic muscles that may represent a proxy of sensorimotor empathy) and of autonomic reactivity (like the electrodermal response and Respiratory Sinus Arrhythmia that may represent a general proxy of affective empathy). While no across group differences in explicit verbal reports about the pain stimuli were found, SCI people exhibited reduced facial muscle reactivity to the stimuli applied to the foot (but not the hand) seen from the 1PP. Tellingly, the corrugator activity correlated with SCI participants' neuropathic pain. There were no across group differences in autonomic reactivity suggesting that SCI lesions may affect sensorimotor dimensions connected to empathy for pain.

Expectations underlie the effects of unpredictable pain: a behavioral and electroencephalogram study

ABSTRACT

Previous studies on the potential effects of unpredictability on pain perception and its neural correlates yielded divergent results. This study examined whether this may be explained by differences in acquired expectations. We presented 41 healthy volunteers with laser heat stimuli of different intensities. The stimuli were preceded either by predictable low, medium, or high cues or by unpredictable low-medium, medium-high, or low-high cues. We recorded self-reports of pain intensity and unpleasantness and laser-evoked potentials (LEPs). Furthermore, we investigated whether dynamic expectations that evolved throughout the experiment based on past trials were better predictors of pain ratings than fixed (nonevolving) expectations. Our results replicate previous findings that unpredictable pain is higher than predictable pain for low-intensity stimuli but lower for high-intensity stimuli. Moreover, we observed higher ratings for the medium-high unpredictable condition than the medium-low unpredictable condition, in line with an effect of expectation. We found significant interactions (N1, N2) for the LEP components between intensity and unpredictability. However, the few significant differences in LEP peak amplitudes between cue conditions did not survive correction for multiple testing. In line with predictive coding perspectives, pain ratings were best predicted by dynamic expectations. Surprisingly, expectations of reduced precision (increased variance) were associated with lower pain ratings. Our findings provide strong evidence that (dynamic) expectations contribute to the opposing effects of unpredictability on pain perception; therefore, we highlight the importance of controlling for them in pain unpredictability manipulations. We also suggest to conceptualize pain expectations more often as dynamic constructs incorporating previous experiences.

The effect of unpredictability on the perception of pain: a systematic review and meta-analysis

ABSTRACT

Despite being widely assumed, the worsening impact of unpredictability on pain perception remains unclear because of conflicting empirical evidence, and a lack of systematic integration of past research findings. To fill this gap, we conducted a systematic review and meta-analysis focusing on the effect of unpredictability on pain perception. We also conducted meta-regression analyses to examine the moderating effect of several moderators associated with pain and unpredictability: stimulus duration, calibrated stimulus pain intensity, pain intensity expectation, controllability, anticipation delay, state and trait negative affectivity, sex/gender and age of the participants, type of unpredictability (intensity, onset, duration, location), and method of pain induction (thermal, electrical, mechanical pressure, mechanical distention). We included 73 experimental studies with adult volunteers manipulating the (un)predictability of painful stimuli and measuring perceived pain intensity and pain unpleasantness in predictable and unpredictable contexts. Because there are insufficient studies with patients, we focused on healthy volunteers. Our results did not reveal any effect of unpredictability on pain perception. However, several significant moderators were found, ie, targeted stimulus pain intensity, expected pain intensity, and state negative affectivity. Trait negative affectivity and uncontrollability showed no significant effect, presumably because of the low number of included studies. Thus, further investigation is necessary to clearly determine their role in unpredictable pain perception.

Pain: A Precision Signal for Reinforcement Learning and Control

Since noxious stimulation usually leads to the perception of pain, pain has traditionally been considered sensory nociception. But its variability and sensitivity to a broad array of cognitive and motivational factors have meant it is commonly viewed as inherently imprecise and intangibly subjective. However, the core function of pain is motivational-to direct both short- and long-term behavior away from harm. Here, we illustrate that a reinforcement learning model of pain offers a mechanistic understanding of how the brain supports this, illustrating the underlying computational architecture of the pain system. Importantly, it explains why pain is tuned by multiple factors and necessarily supported by a distributed network of brain regions, recasting pain as a precise and objectifiable control signal.

The Influence of Pain-Related Expectations on Intensity Perception of Nonpainful Somatosensory Stimuli

OBJECTIVE

The extent to which pain-related expectations, known to affect pain perception, also affect perception of nonpainful sensations remains unclear, as well as the potential role of unpredictability in this context.

METHODS

In a proprioceptive fear conditioning paradigm, various arm extension movements were associated with predictable and unpredictable electrocutaneous pain or its absence. During a subsequent test phase, nonpainful electrocutaneous stimuli with a high or low intensity were presented during movement execution. We used hierarchical drift diffusion modeling to examine the influence of expecting pain on the perceptual decision-making process underlying intensity perception of nonpainful sensations. In the first experiment (n = 36), the pain stimulus was never presented during the test phase after conditioning. In the second experiment (n = 39), partial reinforcement was adopted to prevent extinction of pain expectations.

RESULTS

In both experiments, movements that were associated with (un)predictable pain led to higher pain expectancy, self-reported fear, unpleasantness, and arousal as compared with movements that were never paired with pain (effect sizes η2 ranging from 0.119 to 0.557; all p values < .05). Only in the second experiment-when the threat of pain remained present-we found that the expectation of pain affected decision making. Compared with the no pain condition, an a priori decision-making bias toward the high-intensity decision threshold was found with the strongest bias during unpredictable pain (effect sizes η2 ranging from 0.469 to 0.504; all p-values < .001).

CONCLUSIONS

Thus, the expectation of pain affects inferential processes not only for subsequent painful but also for nonpainful bodily stimuli, with unpredictability moderating these effects, and only when the threat of pain remains present due to partial reinforcement.

Others' Pain Appraisals Modulate the Anticipation and Experience of Subsequent Pain

The present study investigated how pain appraisals from other individuals modulated self-pain anticipation and perception. Appraisals of pain intensity from 10 other individuals were presented before the participants received identical electrical pain stimulation themselves. In reality, the presented other's pain appraisals, with either low or high in mean and variance, were generated by the experimenter, and were randomly paired with the subsequent electrical stimulation at either low or high intensity. Specifically, the mean and variance of others' pain appraisals were manipulated to induce participants' expectation and certainty to the upcoming pain. Subjective ratings of pain intensity and electroencephalographic (EEG) responses to the electrical stimulation, as well as anticipatory EEG activities measured prior to the onset of electrical stimulation, were compared. Results showed that the mean and variance of others' pain appraisal modulated the subjective pain ratings and the affective-motivational P2 responses elicited by the electrical stimulation, as well as anticipatory sensorimotor α-oscillation measured before the onset of pain stimulation. When the mean of others' pain appraisal was low, higher variance suppressed the sensorimotor α-oscillations and enhanced subsequent pain perception. In contrast, when the mean was high, the higher variance enhanced sensorimotor α-oscillations and suppressed subsequent pain perception. These results demonstrated that others' pain appraisals can modulate both of the anticipation and perception of first-hand pain. It also suggested that the top-down modulation of others' pain appraisals on pain perception could be partially driven by the different brain states during the anticipation stage, as captured by the prestimulus sensorimotor α-oscillations.