Does Parkinson's disease lead to alterations in the facial expression of pain?

Effects of facial biofeedback on hypomimia, emotion recognition, and affect in Parkinson's disease

OBJECTIVES

Facial expressions are a core component of emotions and nonverbal social communication. Therefore, hypomimia as secondary symptom of Parkinson's disease (PD) has adverse effects like social impairment, stigmatization, under-diagnosis and under-treatment of depression, and a generally lower quality of life. Beside unspecific dopaminergic treatment, specific treatment options for hypomimia in PD are rarely investigated. This quasi-randomized controlled trial evaluated the short-term effects of facial electromyogram (EMG) based biofeedback to enhance facial expression and emotion recognition as nonverbal social communication skills in PD patients. Furthermore effects on affect are examined.

METHOD

A sample of 34 in-patients with PD were allocated either to facial EMG-biofeedback as experimental group or non-facial exercises as control group. Facial expression during posing of emotions (measured via EMG), facial emotion recognition, and positive and negative affect were assessed before and after treatment. Stronger improvements were expected in the EMG-biofeedback in comparison to the control group.

RESULTS

The facial EMG-biofeedback group showed significantly greater improvements in overall facial expression, and especially for happiness and disgust. Also, overall facial emotion recognition abilities improved significantly stronger in the experimental group. Positive affect was significantly increased in both groups with no significant differences between them, while negative affect did not change within both groups.

CONCLUSIONS

The study provides promising evidence for facial EMG-biofeedback as a tool to improve facial expression and emotion recognition in PD. Embodiment theories are discussed as working mechanism.

The Story behind the Mask: A Narrative Review on Hypomimia in Parkinson's Disease

Facial movements are crucial for social and emotional interaction and well-being. Reduced facial expressions (i.e., hypomimia) is a common feature in patients with Parkinson's disease (PD) and previous studies linked this manifestation to both motor symptoms of the disease and altered emotion recognition and processing. Nevertheless, research on facial motor impairment in PD has been rather scarce and only a limited number of clinical evaluation tools are available, often suffering from poor validation processes and high inter- and intra-rater variability. In recent years, the availability of technology-enhanced quantification methods of facial movements, such as automated video analysis and machine learning application, led to increasing interest in studying hypomimia in PD. In this narrative review, we summarize the current knowledge on pathophysiological hypotheses at the basis of hypomimia in PD, with particular focus on the association between reduced facial expressions and emotional processing and analyze the current evaluation tools and management strategies for this symptom, as well as future research perspectives.

Vicarious facilitation of facial responses to pain

INTRODUCTION

Observing facial expressions of pain has been shown to lead to increased subjective, neural and autonomic pain responses. Surprisingly, these vicarious facilitation effects on its corresponding response channel, namely facial responses to pain have mostly been neglected. We aim to examine whether the prior exposure to facial expressions of pain leads to a facilitation of facial responses to experimental pain; and whether this facilitation is linked to the valence (pain vs. neutral expression) or also linked to specific motor-features of the facial pain expressions (different facial muscle movements).

METHOD

Subjective (intensity and unpleasantness ratings) and facial responses (Facial Action Coding System) of 64 participants (34 female) to painful and non-painful heat stimuli were assessed. Before each heat stimulus, video clips of computer-generated facial expressions (three different pain expressions and a neutral expression) were presented.

RESULTS

The prior exposure to facial expressions of pain led to increased subjective and facial responses to pain. Further, vicarious pain facilitation of facial responses was significantly correlated with facilitation of unpleasantness ratings. We also found evidence that this vicarious facilitation of facial responses was not only linked to the presentation of pain versus neutral expressions but also to specific motor-features of the pain cue (increase in congruent facial muscle movements).

DISCUSSION

Vicarious pain facilitation was found for subjective and facial responses to pain. The results are discussed with reference to the motivational priming hypothesis as well as with reference to motor priming.

SIGNIFICANCE

Our study uncovers evidence that facial pain responses are not only influenced by motivational priming (similar to other types of pain responses), but also by motor-priming. These findings shed light on the complexity - ranging from social, affective and motor mechanisms - underling vicarious facilitation of pain.

Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives

Although proper pain evaluation is mandatory for establishing the appropriate therapy, self-reported pain level assessment has several limitations. Data-driven artificial intelligence (AI) methods can be employed for research on automatic pain assessment (APA). The goal is the development of objective, standardized, and generalizable instruments useful for pain assessment in different clinical contexts. The purpose of this article is to discuss the state of the art of research and perspectives on APA applications in both research and clinical scenarios. Principles of AI functioning will be addressed. For narrative purposes, AI-based methods are grouped into behavioral-based approaches and neurophysiology-based pain detection methods. Since pain is generally accompanied by spontaneous facial behaviors, several approaches for APA are based on image classification and feature extraction. Language features through natural language strategies, body postures, and respiratory-derived elements are other investigated behavioral-based approaches. Neurophysiology-based pain detection is obtained through electroencephalography, electromyography, electrodermal activity, and other biosignals. Recent approaches involve multimode strategies by combining behaviors with neurophysiological findings. Concerning methods, early studies were conducted by machine learning algorithms such as support vector machine, decision tree, and random forest classifiers. More recently, artificial neural networks such as convolutional and recurrent neural network algorithms are implemented, even in combination. Collaboration programs involving clinicians and computer scientists must be aimed at structuring and processing robust datasets that can be used in various settings, from acute to different chronic pain conditions. Finally, it is crucial to apply the concepts of explainability and ethics when examining AI applications for pain research and management.

Using AI to Detect Pain through Facial Expressions: A Review

Pain assessment is a complex task largely dependent on the patient's self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI in clinical settings are still largely unknown to many medical professionals. In this literature review, we present a conceptual understanding of the application of AI to detect pain through facial expressions. We provide an overview of the current state of the art as well as the technical foundations of AI/ML techniques used in pain detection. We highlight the ethical challenges and the limitations associated with the use of AI in pain detection, such as the scarcity of databases, confounding factors, and medical conditions that affect the shape and mobility of the face. The review also highlights the potential impact of AI on pain assessment in clinical practice and lays the groundwork for further study in this area.

A Pilot Trial of Dopamine Replacement for Dynamic Facial Expressions in Parkinson's Disease

Background

Current conflict exists regarding the potential beneficial effects of dopamine medications on facial expressivity in Parkinson's disease. Via digital video analysis software, we previously found reduced facial movement (entropy) and slower time to reach peak entropy in individuals with Parkinson's disease compared to controls.

Objectives

We aimed to determine whether levodopa medications improved parameters of dynamic facial expressions (amplitude, speed).

Methods

A total of 34 individuals with idiopathic Parkinson's disease were videotaped making voluntary facial expressions (happy, fear, anger, disgust) when "on" and "off" levodopa. Participants were 52 to 80 years old, early to mid-stage disease, non-demented, and included more men (65%). Expressions were digitized and analyzed using software that extracted three variables: two indices of movement change (total entropy, percent entropy change) and time to reach peak expression.

Results

Indices of facial movement (total entropy, peak entropy) and timing were significantly improved when patients were "on" vs "off" medication (all F's ≥ 3.00, P < 0.05). For total movement and time to reach peak entropy, levodopa-related improvements were emotion nonspecific. Levodopa-related improvement for peak entropy was driven primarily by happy expressions. There was no relationship between quantitative indices and clinical measures of mood (depression, anxiety) and motor disease severity.

Conclusion

The effects of levodopa on Parkinson's disease voluntary facial movement and on timing were robust and consistent with those of levodopa on other intentional movements in Parkinson's disease. This improvement possibly occurred because of levodopa enhanced activation of face representation areas in fronto-cortical regions or because of less movement-based suppression.

External validation of binary machine learning models for pain intensity perception classification from EEG in healthy individuals

Discrimination of pain intensity using machine learning (ML) and electroencephalography (EEG) has significant potential for clinical applications, especially in scenarios where self-report is unsuitable. However, existing research is limited due to a lack of external validation (assessing performance using novel data). We aimed for the first external validation study for pain intensity classification with EEG. Pneumatic pressure stimuli were delivered to the fingernail bed at high and low pain intensities during two independent EEG experiments with healthy participants. Study one (n = 25) was utilised for training and cross-validation. Study two (n = 15) was used for external validation one (identical stimulation parameters to study one) and external validation two (new stimulation parameters). Time-frequency features of peri-stimulus EEG were computed on a single-trial basis for all electrodes. ML training and analysis were performed on a subset of features, identified through feature selection, which were distributed across scalp electrodes and included frontal, central, and parietal regions. Results demonstrated that ML models outperformed chance. The Random Forest (RF) achieved the greatest accuracies of 73.18, 68.32 and 60.42% for cross-validation, external validation one and two, respectively. Importantly, this research is the first to externally validate ML and EEG for the classification of intensity during experimental pain, demonstrating promising performance which generalises to novel samples and paradigms. These findings offer the most rigorous estimates of ML's clinical potential for pain classification.

Oral Health Disorders in Parkinson's Disease: More than Meets the Eye

Despite clinical evidence of poor oral health and hygiene in Parkinson’s disease (PD) patients, the mouth is often overlooked by both patients and the medical community, who generally focus on motor or psychiatric disorders considered more burdensome. Yet, oral health is in a two-way relationship with overall health—a weakened status triggering a decline in the quality of life. Here, we aim at giving a comprehensive overview of oral health disorders in PD, while identifying their etiologies and consequences. The physical (abnormal posture, muscle tone, tremor, and dyskinesia), behavioral (cognitive and neuropsychiatric disorders), and iatrogenic patterns associated with PD have an overall detrimental effect on patients’ oral health, putting them at risk for other disorders (infections, aspiration, pain, malnutrition), reducing their quality of life and increasing their isolation (anxiety, depression, communication issues). Interdisciplinary cooperation for prevention, management and follow-up strategies need to be implemented at an early stage to maintain and improve patients’ overall comfort and condition. Recommendations for practice, including (non-)pharmacological management strategies are discussed, with an emphasis on the neurologists’ role. Of interest, the oral cavity may become a valuable tool for diagnosis and prognosis in the near future (biomarkers). This overlooked but critical issue requires further attention and interdisciplinary research.

Pain processing in older adults with dementia-related cognitive impairment is associated with frontal neurodegeneration

Experimental pain research has shown that pain processing seems to be heightened in dementia. It is unclear which neuropathological changes underlie these alterations. This study examined whether differences in pressure pain sensitivity and endogenous pain inhibition (conditioned pain modulation (CPM)) between individuals with a dementia-related cognitive impairment (N=23) and healthy controls (N=35) are linked to dementia-related neurodegeneration. Pain was assessed via self-report ratings and by analyzing the facial expression of pain using the Facial Action Coding System. We found that cognitively impaired individuals show decreased CPM inhibition as assessed by facial responses compared to healthy controls, which was mediated by decreased gray matter volume in the medial orbitofrontal and anterior cingulate cortex in the patient group. This study confirms previous findings of intensified pain processing in dementia when pain is assessed using non-verbal responses. Our findings suggest that a loss of pain inhibitory functioning caused by structural changes in prefrontal areas might be one of the underlying mechanisms responsible for amplified pain responses in individuals with a dementia-related cognitive impairment.

Towards optimising experimental quantification of persistent pain in Parkinson's disease using psychophysical testing

People with Parkinson's disease (PD) may live for multiple decades after diagnosis. Ensuring that effective healthcare provision is received across the range of symptoms experienced is vital to the individual's wellbeing and quality of life. As well as the hallmark motor symptoms, PD patients may also suffer from non-motor symptoms including persistent pain. This type of pain (lasting more than 3 months) is inconsistently described and poorly understood, resulting in limited treatment options. Evidence-based pain remedies are coming to the fore but therapeutic strategies that offer an improved analgesic profile remain an unmet clinical need. Since the ability to establish a link between the neurodegenerative changes that underlie PD and those that underlie maladaptive pain processing leading to persistent pain could illuminate mechanisms or risk factors of disease initiation, progression and maintenance, we evaluated the latest research literature seeking to identify causal factors underlying persistent pain in PD through experimental quantification. The majority of previous studies aimed to identify neurobiological alterations that could provide a biomarker for pain/pain phenotype, in PD cohorts. However heterogeneity of patient cohorts, result outcomes and methodology between human psychophysics studies overwhelmingly leads to inconclusive and equivocal evidence. Here we discuss refinement of pain-PD paradigms in order that future studies may enhance confidence in the validity of observed effect sizes while also aiding comparability through standardisation. Encouragingly, as the field moves towards cross-study comparison of data in order to more reliably reveal mechanisms underlying dysfunctional pain processing, the potential for better-targeted treatment and management is high.

The effect of optimism on the facial expression of pain: Implications for pain communication

BACKGROUND

There is a broad range of evidence on optimism dampening the pain experience, as assessed by subjective self-report. Facial expression of pain conveys supplementary information about the pain experience, is an integral part of pain communication and assists psychosocial pain coping. Nevertheless, the effect of induced optimism on facial activity during pain has to our knowledge not been examined.

METHODS

In our experiment, 40 healthy participants underwent two blocks of thermal stimulation containing phasic non-painful and painful stimuli. Between the two blocks, the Best Possible Self imagery and writing task was performed to induce situational optimism, while a control group wrote about their typical day. Facial activity and self-report ratings of intensity and unpleasantness were recorded. Facial activity was analysed using the Facial Action Coding System.

RESULTS

The optimism manipulation was successful in increasing state optimism. It did not affect self-report ratings, but resulted in a stronger facial expression of pain, caused especially by increases in Action Units 4 (furrowed brows) and 6_7 (narrowed eyes).

CONCLUSIONS

All Action Units, which were affected by the optimism induction, are known to be prevalent during pain stimulation. The increase in facial expression might reflect reduced inhibition of pain communication in temporarily optimistic participants. Optimism might lead to expecting positive and helpful reactions from others and, by that, to great readiness to elicit these reactions by non-verbal social behaviour.

SIGNIFICANCE

This study is the first to indicate that state optimism increases the facial expression of pain as a social signal for help and empathy without concomitant changes in the subjective pain experience.

Pain Processing in Older Adults and Its Association with Prefrontal Characteristics

Aging is known to affect nociceptive processing, e.g., the ability to inhibit pain. This study aims to investigate whether pain responses in older individuals are associated with prefrontal characteristics, namely (i) executive functioning performance and (ii) structural brain variations in the prefrontal cortex. Heat and pressure stimuli were applied to assess pressure pain sensitivity and endogenous pain inhibition in 46 healthy older individuals. Executive functioning performance was assessed in three domains (i.e., cognitive inhibition, shifting, and updating) and structural brain variations were assessed in both gray and white matter. Overall pain responses were significantly associated with the executive functioning domains cognitive inhibition and shifting. However, no specific type of pain response showed an especially strong association. Endogenous pain inhibition specifically showed a significant association with gray matter volume in the prefrontal cortex and with variations in white matter structure of tracts connecting the prefrontal cortex with the periaqueductal gray. Hierarchical regression analyses showed that these variations in the prefrontal cortex can explain variance in pain inhibition beyond what can be explained by executive functioning. This might indicate that known deficits in pain inhibition in older individuals are associated with structural variations in prefrontal areas.

Dementia and Parkinson's Disease: Similar and Divergent Challenges in Providing Palliative Care

Dementia and Parkinson's disease are incurable neurological conditions. Patients often experience specific, complex, and varying needs along their disease trajectory. Current management typically employs a multidisciplinary team approach. Recognition is growing that this team approach should also address palliative care issues to optimize quality of life for patient and family caregivers, but it remains unclear how palliative care is best delivered. To inspire future service development and research, we compare the trajectories and conceptualization of palliative care between dementia and Parkinson's disease. Both Parkinson's disease and dementia are characterized by a protracted course, with progressive but fairly insidious development of disability. However, patients with Parkinson's disease may experience relatively stable periods initially but with time, a wide range of debilitating symptoms develops, many of which do not respond well to treatment. Eventually, dementia develops in most Parkinson patients, while motor disability develops in many dementia patients. In both diseases, symptoms such as pain, apathy, sleeping problems, falls, and a high caregiver burden are prevalent. Advance care planning has benefits in terms of being prepared before the disease progresses into a stage with communication problems or severe cognitive impairment. However, for both conditions, the protracted disease trajectories complicate conceptualization of palliative care through different stages of the disease, with pertinent questions such as when to offer what interventions pro-actively. Given the similarities and differences, we should develop palliative approaches that are partially generic and partially disease-specific. These should be integrated seamlessly with disease-specific care. Substantial research is already being performed on dementia palliative care. This may also inform the further development of palliative care for Parkinson's disease, including an evaluation of palliative interventions and services.

Problems of video-based pain detection in patients with dementia: a road map to an interdisciplinary solution

BACKGROUND

Given the unreliable self-report in patients with dementia, pain assessment should also rely on the observation of pain behaviors, such as facial expressions. Ideal observers should be well trained and should observe the patient continuously in order to pick up any pain-indicative behavior; which are requisitions beyond realistic possibilities of pain care. Therefore, the need for video-based pain detection systems has been repeatedly voiced. Such systems would allow for constant monitoring of pain behaviors and thereby allow for a timely adjustment of pain management in these fragile patients, who are often undertreated for pain.

METHODS

In this road map paper we describe an interdisciplinary approach to develop such a video-based pain detection system. The development starts with the selection of appropriate video material of people in pain as well as the development of technical methods to capture their faces. Furthermore, single facial motions are automatically extracted according to an international coding system. Computer algorithms are trained to detect the combination and timing of those motions, which are pain-indicative.

RESULTS/CONCLUSION

We hope to encourage colleagues to join forces and to inform end-users about an imminent solution of a pressing pain-care problem. For the near future, implementation of such systems can be foreseen to monitor immobile patients in intensive and postoperative care situations.

The use of facial expressions for pain assessment purposes in dementia: a narrative review

Facial expressions convey reliable nonverbal signals about pain and thus are very useful for assessing pain in patients with limited communicative ability, such as patients with dementia. In this review, we present an overview of the available pain observation tools and how they make use of facial expressions. Utility and reliability of facial expressions to measure pain in dementia are discussed, together with the effect of dementia severity on these facial expressions. Next, we present how behavioral alterations may overlap with facial expressions of pain, and may even influence the extent to which pain is facially expressed. The main focus is on disinhibition, apathy and emotional changes. Finally, an overview of theoretical considerations and practical implications is presented for assessing pain using facial expressions in clinical settings.