Temporal–spectral signaling of sensory information and expectations in the cerebral processing of pain

Pain perception as hierarchical Bayesian inference: A test case for the theory of constructed emotion

An intriguing perspective about human emotion, the theory of constructed emotion considers emotions as generative models according to the Bayesian brain hypothesis. This theory brings fresh insight to existing findings, but its complexity renders it challenging to test experimentally. We argue that laboratory studies of pain could support the theory because although some may not consider pain to be a genuine emotion, the theory must at minimum be able to explain pain perception and its dysfunction in pathology. We review emerging evidence that bear on this question. We cover behavioral and neural laboratory findings, computational models, placebo hyperalgesia, and chronic pain. We conclude that there is substantial evidence for a predictive processing account of painful experience, paving the way for a better understanding of neuronal and computational mechanisms of other emotions.

Pain reflects the informational value of nociceptive inputs

ABSTRACT

Pain perception and its modulation are fundamental to human learning and adaptive behavior. This study investigated the hypothesis that pain perception is tied to pain's learning function. Thirty-one participants performed a threat conditioning task where certain cues were associated with a possibility of receiving a painful electric shock. The cues that signaled potential pain or safety were regularly changed, requiring participants to continually establish new associations. Using computational models, we quantified participants' pain expectations and prediction errors throughout the task and assessed their relationship with pain perception and electrophysiological responses. Our findings suggest that subjective pain perception increases with prediction error, that is, when pain was unexpected. Prediction errors were also related to physiological nociceptive responses, including the amplitude of nociceptive flexion reflex and electroencephalography markers of cortical nociceptive processing (N1-P2-evoked potential and gamma-band power). In addition, higher pain expectations were related to increased late event-related potential responses and alpha/beta decreases in amplitude during cue presentation. These results further strengthen the idea of a crucial link between pain and learning and suggest that understanding the influence of learning mechanisms in pain modulation could help us understand when and why pain perception is modulated in health and disease.

Test-retest reliability of Bayesian estimations of the effects of stimulation, prior information and individual traits on pain perception

BACKGROUND

There is inter-individual variability in the influence of different components (e.g. nociception and expectations) on pain perception. Identifying the individual effect of these components could serve for patient stratification, but only if these influences are stable in time.

METHODS

In this study, 30 healthy participants underwent a cognitive pain paradigm in which they rated pain after viewing a probabilistic cue informing of forthcoming pain intensity and then receiving electrical stimulation. The trial information was then used in a Bayesian probability model to compute the relative weight each participant put on stimulation, cue, cue uncertainty and trait-like bias. The same procedure was repeated 2 weeks later. Relative and absolute test-retest reliability of all measures was assessed.

RESULTS

Intraclass correlation results showed good reliability for the effect of the stimulation (0.83), the effect of the cue (0.75) and the trait-like bias (0.75 and 0.75), and a moderate reliability for the effect of the cue uncertainty (0.55). Absolute reliability measures also supported the temporal stability of the results and indicated that a change in parameters corresponding to a difference in pain ratings ranging between 0.47 and 1.45 (depending on the parameters) would be needed to consider differences in outcomes significant. The comparison of these measures with the closest clinical data we possess supports the reliability of our results.

CONCLUSIONS

These findings support the hypothesis that inter-individual differences in the weight placed on different pain factors are stable in time and could therefore be a possible target for patient stratification.

SIGNIFICANCE

Our results demonstrate the temporal stability of the weight healthy individuals place on the different factors leading to the pain response. These findings give validity to the idea of using Bayesian estimations of the influence of different factors on pain as a way to stratify patients for treatment personalization.

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 temporal effect of uncertain context on the perceptual processing of painful and non-painful stimulation

Uncertainty has been demonstrated to influence the perception of noxious stimuli, but little is known about the effects of prolonged uncertain contexts on the perception of painful and non-painful stimuli. To address this knowledge gap, the present study utilized a cue-based NPU-threat task, where uncertain and certain trials were separated into distinct blocks. The objective was to investigate the impact of uncertain contexts on the temporal dynamics of electroencephalogram (EEG) activity during the processing of painful and non-painful stimuli. The results revealed that the influence of uncertain contexts on neural responses extends beyond painful trials and is also evident in non-painful trials. In uncertain contexts, it has been observed that painful stimuli elicit larger P2 amplitudes and late beta band (13-30 Hz) event-related desynchronization (ERD) around 500-700 ms. However, in certain contexts, painful stimuli evoke stronger late gamma band (50-70 Hz) event-related synchronization (ERS) around 600-700 ms. For non-painful trials, in uncertain contexts, significantly higher amplitudes of the late positive potential (LPP) component and delta-theta band (2-7 Hz) ERS were observed compared to certain non-painful stimuli. These findings demonstrate that uncertain contexts exert a significant impact on the processing of both painful and non-painful stimuli, and this influence is mediated by distinct neural mechanisms.

The role of ongoing oscillation in pain perception: Absence of modulation by a concomitant arithmetic task

Sustained nociceptive stimuli have been shown to modulate the amplitude of ongoing neural oscillations in the theta, alpha and beta frequency bands at the frequency of stimulation, suggesting a relationship between these ongoing oscillations and pain perception. Yet, whether these ongoing oscillations are actually related to the pain experience remains unclear. If it were the case, then cognitive processes that are known to affect pain intensity should also affect these ongoing oscillations. To this end, we used electroencephalography (EEG) to investigate whether distraction - an attentional state known to affect pain perception - also modulates the amplitude of these neural oscillations. More specifically, we hypothesized that performing an unrelated arithmetic task during sustained nociceptive stimulation would lead to a decrease in the modulations of ongoing oscillations exerted by the stimulation. To assess the selectivity of this modulation for nociception, we compared the modulations of ongoing oscillations exerted by sustained periodic thermonociceptive and non-nociceptive vibrotactile stimulation (.2 Hz, 75 sec), while participants were either asked to solve an unrelated arithmetic task (distraction task) or received no specific instruction (baseline). The intensity of perception was significantly reduced by the arithmetic task in both the thermonociceptive and the vibrotactile modality, and the sustained periodic stimulation elicited a periodic response at the frequency of stimulation in both modalities. However, the distraction task did not show a differential effect for the two stimulation modalities in any of the frequency bands. The fact that, unlike pain perception, these oscillations did not appear to be affected by the task suggests that they are dissociable from pain perception. Whether a different task (leading to a stronger degree of distraction) could lead to different results is unclear.

Local brain oscillations and interregional connectivity differentially serve sensory and expectation effects on pain

Pain emerges from the integration of sensory information about threats and contextual information such as an individual's expectations. However, how sensory and contextual effects on pain are served by the brain is not fully understood so far. To address this question, we applied brief painful stimuli to 40 healthy human participants and independently varied stimulus intensity and expectations. Concurrently, we recorded electroencephalography. We assessed local oscillatory brain activity and interregional functional connectivity in a network of six brain regions playing key roles in the processing of pain. We found that sensory information predominantly influenced local brain oscillations. In contrast, expectations exclusively influenced interregional connectivity. Specifically, expectations altered connectivity at alpha (8 to 12 hertz) frequencies from prefrontal to somatosensory cortex. Moreover, discrepancies between sensory information and expectations, i.e., prediction errors, influenced connectivity at gamma (60 to 100 hertz) frequencies. These findings reveal how fundamentally different brain mechanisms serve sensory and contextual effects on pain.

A parahippocampal-sensory Bayesian vicious circle generates pain or tinnitus: a source-localized EEG study

Pain and tinnitus share common pathophysiological mechanisms, clinical features, and treatment approaches. A source-localized resting-state EEG study was conducted in 150 participants: 50 healthy controls, 50 pain, and 50 tinnitus patients. Resting-state activity as well as functional and effective connectivity was computed in source space. Pain and tinnitus were characterized by increased theta activity in the pregenual anterior cingulate cortex, extending to the lateral prefrontal cortex and medial anterior temporal lobe. Gamma-band activity was increased in both auditory and somatosensory cortex, irrespective of the pathology, and extended to the dorsal anterior cingulate cortex and parahippocampus. Functional and effective connectivity were largely similar in pain and tinnitus, except for a parahippocampal-sensory loop that distinguished pain from tinnitus. In tinnitus, the effective connectivity between parahippocampus and auditory cortex is bidirectional, whereas the effective connectivity between parahippocampus and somatosensory cortex is unidirectional. In pain, the parahippocampal-somatosensory cortex is bidirectional, but parahippocampal auditory cortex unidirectional. These modality-specific loops exhibited theta-gamma nesting. Applying a Bayesian brain model of brain functioning, these findings suggest that the phenomenological difference between auditory and somatosensory phantom percepts result from a vicious circle of belief updating in the context of missing sensory information. This finding may further our understanding of multisensory integration and speaks to a universal treatment for pain and tinnitus-by selectively disrupting parahippocampal-somatosensory and parahippocampal-auditory theta-gamma activity and connectivity.

Social distance modulates the influence of social observation on pro-environmental behavior: An event-related potential (ERP) study

Pro-environmental behavior benefits the environment but is individually costly. Therefore, understanding the neural processes of pro-environmental behavior can advance our knowledge of its implicit cost-benefit calculations and mechanisms. Previous studies have focused separately on the effects of social distance and social observation on explicit pro-environmental behavior responses, yet the underlying neurophysiological mechanism remains unknown. Using the event-related potentials (ERPs), we investigated the neural responses to the effects of social distance and social observation on pro-environmental behavior. Participants were instructed to decide between self-interest and pro-environmental choices towards different social distance targets (family members, acquaintances, or strangers) under observable and non-observable conditions. The behavioral results demonstrated that the rate of pro-environmental choices towards acquaintances and strangers was higher under the observable condition than under the non-observable condition. Nonetheless, the rate of pro-environmental choices was higher-unaffected by social observation-towards family members than towards acquaintances and strangers. The ERP results showed that the P2 and P3 amplitudes were smaller under the observable than under the non-observable condition when the potential bearers of environmental decisions were acquaintances and strangers. However, this difference did not emerge when the potential bearers of environmental decisions were family members. The ERP findings of smaller P2 and P3 amplitudes suggest that social observation may reduce the deliberate calculation of personal costs, thereby promoting individuals' pro-environmental behaviors towards acquaintances and strangers.

Agency affects pain inference through prior shift as opposed to likelihood precision modulation in a Bayesian pain model

Agency and expectations play a crucial role in pain perception and treatment. In the Bayesian pain model, somatosensation (likelihood) and expectations (prior) are weighted by their precision and integrated to form a pain percept (posterior). Combining pain treatment with stimulus-related expectations allows the mechanistic assessment of whether agency enters this model as a shift of the prior or a relaxation of the likelihood precision. In two experiments, heat pain was sham treated either externally or by the subject, while a predictive cue was utilized to create high or low treatment expectations. Both experiments revealed additive effects and greater pain relief under self-treatment and high treatment expectations. Formal model comparisons favored a prior shift rather than a modulation of likelihood precision. Electroencephalography revealed a theta-to-alpha effect, temporally associated with expectations, which was correlated with trial-by-trial pain ratings, further supporting a prior shift through which agency exerts its influence in the Bayesian pain model.

Confidence of probabilistic predictions modulates the cortical response to pain

Pain typically evolves over time, and the brain needs to learn this temporal evolution to predict how pain is likely to change in the future and orient behavior. This process is termed temporal statistical learning (TSL). Recently, it has been shown that TSL for pain sequences can be achieved using optimal Bayesian inference, which is encoded in somatosensory processing regions. Here, we investigate whether the confidence of these probabilistic predictions modulates the EEG response to noxious stimuli, using a TSL task. Confidence measures the uncertainty about the probabilistic prediction, irrespective of its actual outcome. Bayesian models dictate that the confidence about probabilistic predictions should be integrated with incoming inputs and weight learning, such that it modulates the early components of the EEG responses to noxious stimuli, and this should be captured by a negative correlation: when confidence is higher, the early neural responses are smaller as the brain relies more on expectations/predictions and less on sensory inputs (and vice versa). We show that participants were able to predict the sequence transition probabilities using Bayesian inference, with some forgetting. Then, we find that the confidence of these probabilistic predictions was negatively associated with the amplitude of the N2 and P2 components of the vertex potential: the more confident were participants about their predictions, the smaller the vertex potential. These results confirm key predictions of a Bayesian learning model and clarify the functional significance of the early EEG responses to nociceptive stimuli, as being implicated in confidence-weighted statistical learning.