The facial feedback hypothesis states that feedback from cutaneous and muscular afferents affects our emotion. Based on the facial feedback hypothesis, the purpose of this study was to determine whether enhancing negative emotion by activating a facial muscle (corrugator supercilii) increases the intensity of cognitive and emotional components of empathic pain. We also assessed whether the muscle contraction changed the pupil size, which would indicate a higher level of arousal. Forty-eight individuals completed 40 muscular contraction and relaxation trials while looking at images of five male and five female patients with neutral and painful facial expressions, respectively. Participants were asked to rate (1) how much pain the patient was in, and (2) how unpleasant their own feelings were. We also examined their facial muscle activities and changes in pupil size. No significant differences in pain or unpleasantness ratings were detected for the neutral face between the two conditions; however, the pain and unpleasantness ratings for the painful face were considerably higher in the contraction than relaxation condition. The pupils were considerably larger in the contraction than relaxation condition for both the painful and neutral faces. Our findings indicate that, by strengthening the corrugator supercilii, facial feedback can affect both the cognitive evaluative and affective sharing aspects of empathic pain.

Memory retrieval is accompanied by a reactivation of cortical and subcortical areas that have been active during encoding. This neural reinstatement is stronger during retrieval of pain-associated material compared with other unpleasant events. In this functional magnetic resonance imaging study, we investigated the differences in neural reinstatement during recognition of visual stimuli that had been paired with face or hand pain during memory encoding. Body site-specific neural reinstatement was tested in 23 healthy young volunteers who performed a visual categorization and a surprise recognition task. Our data shows increased neural reinstatement in task-specific and encoding-related areas, such as the parahippocampus (left: x = -26, y = -30, z = -18, t = 4.11; right: x = 26, y = -38, z = -6, t = 4.36), precuneus (x = 2, y = -56, z = 2, t = 3.77), fusiform gyrus (left: x = -24, y = -26, z = -20, t = 5.41; right: x = 18, y = -58, z = -14, t = 4.52), and amygdala (x = -34, y = -4, z = -20, t = 4.49) for pictures that were previously presented with face compared with hand pain. These results correlated with the individual's recognition confidence, although recognition rates did not differ between the conditions. Functional connectivity was increased between the amygdala and parahippocampus (x = 34, y = -10, z = -28, t = 5.13) for pictures that had previously been paired with face compared with hand pain. Our results were positively correlated with pain-related fear, represented by neural activation in the thalamus (x = -14, y = -35, z = 4, t = 3.54). The reported results can be interpreted as compensatory resource activation and support the notion of a stronger affective component of face compared with hand pain, potentially in line with its greater biological relevance. PERSPECTIVE: This study demonstrates neural reinstatement of face pain-related information, which might be related to the increased biological and affective component of face pain compared with pain on the extremities. Our results might contribute to the understanding of the development and prevalence of head and face pain conditions.

Previous research has revealed that the face is a finely tuned medium for pain communication. Studies assessing the decoding of facial expressions of pain have revealed an interesting discrepancy, namely that, despite eyes narrowing being the most frequent facial expression accompanying pain, individuals mostly rely on brow lowering and nose wrinkling/upper lip raising to evaluate pain. The present study verifies if this discrepancy may reflect an interaction between the features coding pain expressions and the features used by observers and stored in their mental representations. Experiment 1 shows that more weight is allocated to the brow lowering and nose wrinkling/upper lip raising, supporting the idea that these features are allocated more importance when mental representations of pain expressions are stored in memory. These 2 features have been associated with negative valence and with the affective dimension of pain, whereas the eyes narrowing feature has been associated more closely with the sensory dimension of pain. However, experiment 2 shows that these 2 features remain more salient than eyes narrowing, even when attention is specifically directed toward the sensory dimension of pain. Together, these results suggest that the features most saliently coded in the mental representation of facial expressions of pain may reflect a bias toward allocating more weight to the affective information encoded in the face. PERSPECTIVE: This work reveals the relative importance of 3 facial features representing the core of pain expressions during pain decoding. The results show that 2 features are over-represented; this finding may potentially be linked with the estimation biases occurring when clinicians and lay persons evaluate pain based on facial appearance.

Recognition of pain in patients who are incapable of expressing themselves allows for several possibilities of improved diagnosis and treatment. Despite the advancements that have already been made in this field, research is still lacking with respect to the detection of pain in live videos, especially under unfavourable conditions. To address this gap in existing research, the current study proposed a hybrid model that allowed for efficient pain recognition. The hybrid, which consisted of a combination of the Constrained Local Model (CLM), Active Appearance Model (AAM), and Patch-Based Model, was applied in conjunction with image algebra. This contributed to a system that enabled the successful detection of pain from a live stream, even with poor lighting and a low-resolution recording device. The final process and output allowed for memory for storage that was reduced up to 40%-55% and an improved processing time of 20%-25%. The experimental system met with success and was able to detect pain for the 22 analysed videos with an accuracy of 55.75%-100.00%. To increase the fidelity of the proposed technique, the hybrid model was tested on UNBC-McMaster Shoulder Pain Database as well.

Facial expressions of pain are able to elicit empathy and adaptive behavioral responses in the observer. An influential theory posits that empathy relies on an affective mirror mechanism, according to which emotion recognition relies upon the internal simulation of motor and interoceptive states triggered by emotional stimuli. We tested this hypothesis comparing representations of self or others' expressions of pain in nineteen young healthy female volunteers by means of functional magnetic resonance imaging (fMRI). We hypothesized that one's own facial expressions are more likely to elicit the internal simulation of emotions, being more strictly related to self. Video-clips of the facial expressions of each volunteer receiving either painful or non-painful mechanical stimulations to their right hand dorsum were recorded and used as stimuli in a 2 × 2 (Self/Other; Pain/No-Pain) within-subject design. During each trial, a 2 s video clip was presented, displaying either the subject's own neutral or painful facial expressions (Self No-Pain, SNP; Self Pain, SP), or the expressions of other unfamiliar volunteers (Others' No-Pain, ONP; Others' Pain, OP), displaying a comparable emotional intensity. Participants were asked to indicate whether each video displayed a pain expression. fMRI signals were higher while viewing Pain than No-Pain stimuli in a large bilateral array of cortical areas including middle and superior temporal, supramarginal, superior mesial and inferior frontal (IFG) gyri, anterior insula (AI), anterior cingulate (ACC), and anterior mid-cingulate (aMCC) cortex, as well as right fusiform gyrus. Bilateral activations were also detected in thalamus and basal ganglia. The Self vs. Other contrast showed signal changes in ACC and aMCC, IFG, AI, and parietal cortex. A significant interaction between Self and Pain [(SP vs. SNP) >(OP vs. ONP)] was found in a pre-defined region of aMCC known to be also active during noxious stimulation. These findings demonstrate that the observation of one's own and others' facial expressions share a largely common neural network, but self-related stimuli induce generally higher activations. In line with our hypothesis, selectively greater activity for self pain-related stimuli was found in aMCC, a medial-wall region critical for pain perception and recognition.

Facial pain may be divided into several distinct categories, each requiring a specific treatment approach. In some cases, however, such categorization is difficult and treatment is ineffective. We reviewed our extensive clinical experience and designed an algorithmic approach to the treatment of medically intractable facial pain that can be treated through surgical intervention.

Facial mimicry has been suggested to be a behavioral index for emotional empathy. The present study is the first to investigate the link between facial muscle activity and empathy for pain by facial electromyographic (EMG) recording while observers watched videos depicting real-life painful events. Three types of visual stimulus were used: an intact painful scene and arm-only (needle injection) and face only (painful expression) scenes. Enhanced EMG activity of the corrugator supercilii (CS) and zygomaticus major (ZM) muscles was found when observers viewed others in pain, supporting a unique pain expression that is distinct from the expression of basic emotions. In the intact video stimulus condition, CS activity was correlated positively with the empathic concern score and ZM activity, suggesting facial mimicry mediated empathy for pain. Cluster analysis of facial EMG responses revealed markedly different patterns among stimulus types, including response category, ratio, and temporal dynamics, indicating greater ecological validity of the intact scene in eliciting pain empathy as compared with partial scenes. This study is the first to quantitatively describe pain empathy in terms of facial EMG data. It may provide important evidence for facial mimicry as a behavioral indicator of pain empathy.

Observing pain in others facilitates self-pain in the observer. Vicarious pain facilitation mechanisms are poorly understood. We scanned 21 subjects while they observed pain, fear and neutral dynamic facial expressions. In 33% of the trials, a noxious electrical stimulus was delivered. The nociceptive flexion reflex (NFR) and pain ratings were recorded. Both pain and fear expressions increased self-pain ratings (fear > pain) and the NFR amplitude. Enhanced response to self-pain following pain and fear observation involves brain regions including the insula (INS) (pain > fear in anterior part), amygdala, mid-cingulate cortex (MCC), paracentral lobule, precuneus, supplementary motor area and pre-central gyrus. These results are consistent with the motivational priming account where vicarious pain facilitation involves a global enhancement of pain-related responses by negatively valenced stimuli. However, a psychophysiological interaction analysis centered on the left INS revealed increased functional connectivity with the aMCC in response to the painful stimulus following pain observation compared to fear. The opposite connectivity pattern (fear > pain) was observed in the fusiform gyrus, cerebellum (I-IV), lingual gyrus and thalamus, suggesting that pain and fear expressions influence pain-evoked brain responses differentially. Distinctive connectivity patterns demonstrate a stronger effect of pain observation in the cingulo-insular network, which may reflect partly overlapping networks underlying the representation of pain in self and others.

Pain and anxiety are common symptoms in head and neck cancer patients. The anticonvulsant pregabalin has therapeutic indication for the treatment of pain and anxiety, and may represent a useful drug for both conditions. Thus, the aim of this study was to investigate the relationship between pain and anxiety in rats with facial carcinoma, as the influence of pregabalin treatment in both aspects. Facial carcinoma was induced by subcutaneous inoculation of Walker-256 tumor cells in the vibrissa pad of Wistar rats. On day 6 after inoculation spontaneous facial grooming and conditioned place preference were assessed as non-evoked pain measurements and facial mechanical hyperalgesia were assessed 3 and 6 days after tumor cells inoculation. Moreover, anxiety-like behavior was evaluated on the elevated plus maze and light-dark transition tests at the same time points. The effect of pregabalin treatment (30 mg/kg, p.o.) was evaluated in all tests. Our results demonstrated that pregabalin treatment reduced the spontaneous facial grooming and induced conditioned place preference 6 days post tumor inoculation. Tumor-bearing rats developed mechanical hyperalgesia starting 3 days post tumor induction, which was also significant on day 6, but the anxiety-like behavior was detected only in tumor-bearing rats that developed mechanical hyperalgesia and only six days after tumor cells inoculation. Both, the mechanical hyperalgesia and the anxiety-like behavior related to the tumor were significantly reduced by pregabalin treatment on day 6. Pregabalin treatment resulted in antinociceptive and anxiolytic-like effects on facial tumor-bearing rats and may represent a promising therapeutic option for cancer patients.

Advances in neuroimaging have permitted the non-invasive examination of the human brain in pain. However, a persisting challenge is in the objective differentiation of neuropathic facial pain subtypes, as diagnosis is based on patients' symptom descriptions. We use artificial intelligence (AI) models with neuroimaging data to distinguish subtypes of neuropathic facial pain and differentiate them from healthy controls. We conducted a retrospective analysis of diffusion tensor and T1-weighted imaging data using random forest and logistic regression AI models on 371 adults with trigeminal pain (265 classical trigeminal neuralgia (CTN), 106 trigeminal neuropathic pain (TNP)) and 108 healthy controls (HC). These models distinguished CTN from HC with up to 95% accuracy, and TNP from HC with up to 91% accuracy. Both classifiers identified gray and white matter-based predictive metrics (gray matter thickness, surface area, and volume; white matter diffusivity metrics) that significantly differed across groups. Classification of TNP and CTN did not show significant accuracy (51%) but highlighted two structures that differed between pain groups-the insula and orbitofrontal cortex. Our work demonstrates that AI models with brain imaging data alone can differentiate neuropathic facial pain subtypes from healthy data and identify regional structural indicates of pain.

To evaluate the effects of mental nerve injury in the facial reactions elicited by mechanical stimulation of different intensities and detect and quantify spontaneous facial pain-like expressions during a period free of stimuli, as signs of evoked and spontaneous pain in a mouse model for neuropathic orofacial pain.

Equine orthopedic pain scales are targeted towards horses with moderate to severe orthopedic pain. Improved assessment of pain behavior and pain-related facial expressions at rest may refine orthopedic pain detection for mild lameness grades. Therefore, this study explored pain-related behaviors and facial expressions and sought to identify frequently occurring combinations. Orthopedic pain was induced by intra-articular LPS in eight horses, and objective movement asymmetry analyses were performed before and after induction together with pain assessments at rest. Three observers independently assessed horses in their box stalls, using four equine pain scales simultaneously. Increase in movement asymmetry after induction was used as a proxy for pain. Behaviors and facial expressions commonly co-occurred and were strongly associated with movement asymmetry. Posture-related scale items were the strongest predictors of movement asymmetry. Display of facial expressions at rest varied between horses but, when present, were strongly associated with movement asymmetry. Reliability of facial expression items was lower than reliability of behavioral items. These findings suggest that five body behaviors (posture, head position, location in the box stall, focus, and interactive behavior) should be included in a scale for live assessment of mild orthopedic pain. We also recommend inclusion of facial expressions in pain assessment.

Grimace scales quantify characteristic facial expressions associated with spontaneous pain in rodents and other mammals. However, these scales have not been widely adopted largely because of the time and effort required for highly trained humans to manually score the images. Convoluted neural networks were recently developed that distinguish individual humans and objects in images. Here, we trained one of these networks, the InceptionV3 convolutional neural net, with a large set of human-scored mouse images. Output consists of a binary pain/no-pain assessment and a confidence score. Our automated Mouse Grimace Scale integrates these two outputs and is highly accurate (94%) at assessing the presence of pain in mice across different experimental assays. In addition, we used a novel set of "pain" and "no pain" images to show that automated Mouse Grimace Scale scores are highly correlated with human scores (Pearson's r = 0.75). Moreover, the automated Mouse Grimace Scale classified a greater proportion of images as "pain" following laparotomy surgery when compared to animals receiving a sham surgery or a post-surgical analgesic. Together, these findings suggest that the automated Mouse Grimace Scale can eliminate the need for tedious human scoring of images and provide an objective and rapid way to quantify spontaneous pain and pain relief in mice.

According to the Scalar Expectancy Theory, humans are equipped with a biological internal clock, possibly modulated by attention and arousal. Both emotions and pain are arousing and can absorb attentional resources, thus causing distortions of temporal perception. The aims of the present single-event fMRI study were to investigate: a) whether observation of facial expressions of pain interferes with time production; and b) the neural network subserving this kind of temporal distortions. Thirty healthy volunteers took part in the study. Subjects were asked to perform a temporal production task and a concurrent gender discrimination task, while viewing faces of unknown people with either pain-related or neutral expressions. Behavioural data showed temporal underestimation (i.e., longer produced intervals) during implicit pain expression processing; this was accompanied by increased activity of right middle temporal gyrus, a region known to be active during the perception of emotional and painful faces. Psycho-Physiological Interaction analyses showed that: 1) the activity of middle temporal gyrus was positively related to that of areas previously reported to play a role in timing: left primary motor cortex, middle cingulate cortex, supplementary motor area, right anterior insula, inferior frontal gyrus, bilateral cerebellum and basal ganglia; 2) the functional connectivity of supplementary motor area with several frontal regions, anterior cingulate cortex and right angular gyrus was correlated to the produced interval during painful expression processing. Our data support the hypothesis that observing emotional expressions distorts subjective time perception through the interaction of the neural network subserving processing of facial expressions with the brain network involved in timing. Within this frame, middle temporal gyrus appears to be the key region of the interplay between the two neural systems.

No abstract available

Pain is a private experience observable through various verbal and non-verbal behavioural manifestations. Despite the importance of understanding the cerebral mechanisms underlying those manifestations, there is currently limited knowledge on the neural correlates of facial expression of pain. Here, we applied a brain decoding approach to functional magnetic resonance imaging (fMRI) data to predict the facial expression of pain during noxious heat stimulation in healthy volunteers. Results revealed the inability of previously developed pain neurosignatures to predict the facial expression of pain. We thus propose a Facial Expression of Pain Signature (FEPS) conveying distinctive information about the brain response to nociceptive stimulations with minimal overlap with other pain-relevant brain signatures. The FEPS provides a better characterization of the distributed cerebral representations of non-verbal pain communication. This underscores the complexity of pain phenomenology by reinforcing the view that neurosignatures conceived as biomarkers must be interpreted in relation to the specific pain manifestation predicted.

The endogenous opioid system is strongly involved in the modulation of pain. However, the potential role of this system in perceiving painful facial expressions from others has not been sufficiently explored as of yet. To elucidate the contribution of the opioid system to the perception of painful facial expressions, we conducted a double-blind, within-subjects pharmacological functional magnetic resonance imaging (fMRI) study, in which 42 participants engaged in an emotion discrimination task (pain vs. disgust expressions) in two experimental sessions, receiving either the opioid receptor antagonist naltrexone or an inert substance (placebo). On the behavioral level, participants less frequently judged an expression as pain under naltrexone as compared to placebo. On the neural level, parametric modulation of activation in the (putative) right fusiform face area (FFA), which was correlated with increased pain intensity, was higher under naltrexone than placebo. Regression analyses revealed that brain activity in the right FFA significantly predicted behavioral performance in disambiguating pain from disgust, both under naltrexone and placebo. These findings suggest that reducing opioid system activity decreased participants' sensitivity for facial expressions of pain, and that this was linked to possibly compensatory engagement of processes related to visual perception, rather than to higher level affective processes, and pain regulation.

Facial chronic neuropathic pain (FCNP) is a disabling clinical entity, its incidence is increasing within the chronic pain population. There is indication for neuromodulation when conservative treatment fails. Motor cortex stimulation (MCS) has emerged as an alternative in the advanced management of these patients. The aim of this work is to review the worldwide literature on MCS for FCNP.

The aim of this study is to clarify the neural mechanisms underlying orofacial pain abnormalities after cervical spinal nerve injury. Nocifensive behavior, phosphorylated extracellular signal-regulated kinase (pERK) expression and astroglial cell activation in the trigeminal spinal subnucleus caudalis (Vc) and upper cervical spinal dorsal horn (C1-C2) neurons were analyzed in rats with upper cervical spinal nerve transection (CNX).

The aim of this study was to develop and evaluate a machine vision algorithm to assess the pain level in horses, using an automatic computational classifier based on the Horse Grimace Scale (HGS) and trained by machine learning method. The use of the Horse Grimace Scale is dependent on a human observer, who most of the time does not have availability to evaluate the animal for long periods and must also be well trained in order to apply the evaluation system correctly. In addition, even with adequate training, the presence of an unknown person near an animal in pain can result in behavioral changes, making the evaluation more complex. As a possible solution, the automatic video-imaging system will be able to monitor pain responses in horses more accurately and in real-time, and thus allow an earlier diagnosis and more efficient treatment for the affected animals. This study is based on assessment of facial expressions of 7 horses that underwent castration, collected through a video system positioned on the top of the feeder station, capturing images at 4 distinct timepoints daily for two days before and four days after surgical castration. A labeling process was applied to build a pain facial image database and machine learning methods were used to train the computational pain classifier. The machine vision algorithm was developed through the training of a Convolutional Neural Network (CNN) that resulted in an overall accuracy of 75.8% while classifying pain on three levels: not present, moderately present, and obviously present. While classifying between two categories (pain not present and pain present) the overall accuracy reached 88.3%. Although there are some improvements to be made in order to use the system in a daily routine, the model appears promising and capable of measuring pain on images of horses automatically through facial expressions, collected from video images.