Impairments in face discrimination and emotion recognition are related to aging and cognitive dysfunctions in Parkinson's disease with dementia

Neuronal response of the primate striatum tail to face of socially familiar persons

Recent studies have suggested that the basal ganglia, the center of stimulus-reward associative learning, are involved in social behavior. However, the role of the basal ganglia in social information processing remains unclear. Here, we demonstrate that the striatum tail (STRt) in macaque monkeys, which is sensitive to visual objects with long-term reward history (i.e., stable object value), is also sensitive to socially familiar persons. Many STRt neurons responded to face images of persons, especially those who took daily care of the subject monkeys. These face-responsive neurons also encoded stable object value. The strength of the neuronal modulation of social familiarity and stable object value biases were positively correlated. These results suggest that both social familiarity and stable object value information are mediated by a common neuronal mechanism. Thus, the representation of social information is linked to reward information in the STRt, not in the dedicated social information circuit.

Neurocognitive Impairment and Social Cognition in Parkinson's Disease Patients

In addition to motor symptoms, neurocognitive impairment (NCI) affects patients with prodromal Parkinson's disease (PD). NCI in PD ranges from subjective cognitive complaints to dementia. The purpose of this review is to present the available evidence of NCI in PD and highlight the heterogeneity of NCI phenotypes as well as the range of factors that contribute to NCI onset and progression. A review of publications related to NCI in PD up to March 2023 was performed using PubMed/Medline. There is an interconnection between the neurocognitive and motor symptoms of the disease, suggesting a common underlying pathophysiology as well as an interconnection between NCI and non-motor symptoms, such as mood disorders, which may contribute to confounding NCI. Motor and non-motor symptom evaluation could be used prognostically for NCI onset and progression in combination with imaging, laboratory, and genetic data. Additionally, the implications of NCI on the social cognition of afflicted patients warrant its prompt management. The etiology of NCI onset and its progression in PD is multifactorial and its effects are equally grave as the motor effects. This review highlights the importance of the prompt identification of subjective cognitive complaints in PD patients and NCI management.

Facial expressions and identities recognition in Parkinson disease

Parkinson's Disease (PD) is associated with motor and non-motor symptoms. Among the latter are deficits in matching, identification, and recognition of emotional facial expressions. On one hand, this deficit has been attributed to a dysfunction in emotion processing. Another explanation (which does not exclude the former) links this deficit with reduced facial expressiveness in these patients, which prevents them from properly understanding or embodying emotions. To disentangle the specific contribution of emotion comprehension and that of facial expression processing in PD's observed deficit with emotions we performed two experiments on non-emotional facial expressions. In Experiment 1, a group of PD patients and a group of Healthy Controls (HC) underwent a task of non-emotional expression recognition in faces of different identity and a task of identity recognition in faces with different expression. No differences were observed between the two groups in accuracies. In Experiment 2, PD patients and Healthy Controls underwent a task where they had to recognize the identity of faces encoded through a non-emotional facial expression, through a rigid head movement, or as neutral. Again, no group differences were observed. In none of the two experiments hypomimia scores had a specific effect on expression processing. We conclude that in PD patients the observed impairment with emotional expressions is likely due to a specific deficit for emotions to a greater extent than for facial expressivity processing.

Differentiating Use of Facial Expression between Individuals with and without Traumatic Brain Injury Using Affectiva Software: A Pilot Study

This study investigated the feasibility of using an automated facial coding engine, Affectiva (integrated in iMotions, version 8.2), for evaluating facial expression after traumatic brain injury (TBI). An observational cross-sectional study was conducted based on facial expression data from videos of participants with TBI and control participants. The aims were to compare TBI and control groups, and identify confounding factors affecting the data analysis. Video samples of two narrative tasks (personal event and story retell) from ten participants with severe TBI and ten control participants without TBI were analyzed using Affectiva. Automated data on participants' engagement, smile and brow furrow were compared statistically between and within groups. Qualitative notes for each sample were also recorded. Affectiva detected a higher percentage of time of engagement for TBI participants than for control participants on both tasks. There was also a higher percentage of time of smiling for TBI participants in one task. Within groups, there were no significant differences between the two narrative tasks. Affectiva provides standardized data about facial expression and may be sensitive to detecting change in the use of facial expression after TBI. This study also identified factors to avoid during videorecording to ensure high quality samples for future research.

The ability of patients with Parkinson's disease to recognize masked faces during the COVID-19 pandemic

Patients with Parkinson's disease (PwP) have face recognition difficulties.

Objective

This study aimed to evaluate the difficulties of PwP in recognizing masked faces during the COVID-19 pandemic.

Methods

A total of 64 PwP, 58 age-matched older healthy controls (OHCs), and 61 younger healthy controls (YHCs) were included in the study. The Benton Face Recognition Test - short form (BFRT-sf) and the 13-item questionnaire on face recognition difficulties due to masks during the pandemic developed by the authors were applied to all three study groups.

Results

Both the PwP and OHC groups scored worse in BFRT-sf when compared with the YHC group (p<0.001 and p<0.001, respectively). The number of those who had difficulty in recognizing people seen every day and the number of those who asked people to remove their masks because they did not recognize them were higher in the PWP group (p=0.026 and p=0.002, respectively). The number of individuals who looked at the posture and gait of people when they did not recognize their masked faces and those who stated that this difficulty affected their daily lives were higher in the OHC group (p=0.002 and p=0.009, respectively). The number of participants whose difficulty in recognizing masked faces decreased over time was higher in the YHC group (p=0.003).

Conclusions

The PwP group demonstrated similar performance to their peers but differed from the YHC group in recognizing masked faces. Knowing difficulties experienced by elderly people in recognizing people who are masked can increase awareness on this issue and enhance their social interaction in pandemic conditions through measures to be taken.

Utilizing computer vision for facial behavior analysis in schizophrenia studies: A systematic review

Background

Schizophrenia is a severe psychiatric disorder that causes significant social and functional impairment. Currently, the diagnosis of schizophrenia is based on information gleaned from the patient’s self-report, what the clinician observes directly, and what the clinician gathers from collateral informants, but these elements are prone to subjectivity. Utilizing computer vision to measure facial expressions is a promising approach to adding more objectivity in the evaluation and diagnosis of schizophrenia.

Method

We conducted a systematic review using PubMed and Google Scholar. Relevant publications published before (including) December 2021 were identified and evaluated for inclusion. The objective was to conduct a systematic review of computer vision for facial behavior analysis in schizophrenia studies, the clinical findings, and the corresponding data processing and machine learning methods.

Results

Seventeen studies published between 2007 to 2021 were included, with an increasing trend in the number of publications over time. Only 14 articles used interviews to collect data, of which different combinations of passive to evoked, unstructured to structured interviews were used. Various types of hardware were adopted and different types of visual data were collected. Commercial, open-access, and in-house developed models were used to recognize facial behaviors, where frame-level and subject-level features were extracted. Statistical tests and evaluation metrics varied across studies. The number of subjects ranged from 2-120, with an average of 38. Overall, facial behaviors appear to have a role in estimating diagnosis of schizophrenia and psychotic symptoms. When studies were evaluated with a quality assessment checklist, most had a low reporting quality.

Conclusion

Despite the rapid development of computer vision techniques, there are relatively few studies that have applied this technology to schizophrenia research. There was considerable variation in the clinical paradigm and analytic techniques used. Further research is needed to identify and develop standardized practices, which will help to promote further advances in the field.

Automated analysis of facial emotions in subjects with cognitive impairment

Differences in expressing facial emotions are broadly observed in people with cognitive impairment. However, these differences have been difficult to objectively quantify and systematically evaluate among people with cognitive impairment across disease etiologies and severity. Therefore, a computer vision-based deep learning model for facial emotion recognition trained on 400.000 faces was utilized to analyze facial emotions expressed during a passive viewing memory test. In addition, this study was conducted on a large number of individuals (n = 493), including healthy controls and individuals with cognitive impairment due to diverse underlying etiologies and across different disease stages. Diagnoses included subjective cognitive impairment, Mild Cognitive Impairment (MCI) due to AD, MCI due to other etiologies, dementia due to Alzheimer's diseases (AD), and dementia due to other etiologies (e.g., Vascular Dementia, Frontotemporal Dementia, Lewy Body Dementia, etc.). The Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance across all participants. A participant with a score of less than or equal to 24 was considered cognitively impaired (CI). Compared to cognitively unimpaired (CU) participants, CI participants expressed significantly less positive emotions, more negative emotions, and higher facial expressiveness during the test. In addition, classification analysis revealed that facial emotions expressed during the test allowed effective differentiation of CI from CU participants, largely independent of sex, race, age, education level, mood, and eye movements (derived from an eye-tracking-based digital biomarker for cognitive impairment). No screening methods reliably differentiated the underlying etiology of the cognitive impairment. The findings provide quantitative and comprehensive evidence that the expression of facial emotions is significantly different in people with cognitive impairment, and suggests this may be a useful tool for passive screening of cognitive impairment.

Cholinergic Receptor Modulation as a Target for Preventing Dementia in Parkinson's Disease

Parkinson’s disease (PD) is a neurodegenerative condition characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) in the midbrain resulting in progressive impairment in cognitive and motor abilities. The physiological and molecular mechanisms triggering dopaminergic neuronal loss are not entirely defined. PD occurrence is associated with various genetic and environmental factors causing inflammation and mitochondrial dysfunction in the brain, leading to oxidative stress, proteinopathy, and reduced viability of dopaminergic neurons. Oxidative stress affects the conformation and function of ions, proteins, and lipids, provoking mitochondrial DNA (mtDNA) mutation and dysfunction. The disruption of protein homeostasis induces the aggregation of alpha-synuclein (α-SYN) and parkin and a deficit in proteasome degradation. Also, oxidative stress affects dopamine release by activating ATP-sensitive potassium channels. The cholinergic system is essential in modulating the striatal cells regulating cognitive and motor functions. Several muscarinic acetylcholine receptors (mAChR) and nicotinic acetylcholine receptors (nAChRs) are expressed in the striatum. The nAChRs signaling reduces neuroinflammation and facilitates neuronal survival, neurotransmitter release, and synaptic plasticity. Since there is a deficit in the nAChRs in PD, inhibiting nAChRs loss in the striatum may help prevent dopaminergic neurons loss in the striatum and its pathological consequences. The nAChRs can also stimulate other brain cells supporting cognitive and motor functions. This review discusses the cholinergic system as a therapeutic target of cotinine to prevent cognitive symptoms and transition to dementia in PD.

Detection of hypomimia in patients with Parkinson's disease via smile videos

Background

Parkinson’s disease (PD) is a neurodegenerative disease characterized by the impairment of facial expression, known as hypomimia. Hypomimia has serious impacts on patients’ ability to communicate, and it is difficult to detect at early stages of the disease. Furthermore, due to bradykinesia or other reasons, it is inconvenient for PD patients to visit the hospital. Therefore, it is appealing to develop an auxiliary diagnostic method that remotely detects hypomimia.

Methods

We proposed an automatic detection system for Parkinson’s hypomimia based on facial expressions (DSPH-FE). DSPH-FE provides a convenient remote service for those who potentially suffer from hypomimia and only requires patients to input their facial videos. Specifically, patients can detect hypomimia through two aspects: geometric features and texture features. Geometric features focus on visually representing structures of facial muscles. Facial expression factors (FEFs) are used as the first metric to quantify the current activation state of the facial muscles. Facial expression change factors (FECFs) are subsequently used as the second metric to calculate the moving trajectories of the activation states in the videos. Geometric features primarily concentrate on spatial information, with little involvement of temporal information. Thus, the extended histogram of oriented gradients (HOG) algorithm is introduced. This algorithm can extract texture features within multiple continuous frames and incorporate the temporal information into the features. Finally, these features are applied to four machine learning algorithms to model the relationship between these features and hypomimia.

Results

The DSPH-FE detection system achieved the best performance when concatenating geometric features and texture features, resulting in a F1 score of 0.9997. The best F1 scores achieved with geometric features and texture features were 0.8286 and 0.9446, respectively. This indicated that both geometric features and texture features have an ability to predict hypomimia, and demonstrated that temporal information can boost the model performance. Thus, DSPH-FE is an effective supportive tool in the medical management of PD patients.

Conclusions

Comprehensive experiments demonstrated that proposed features fit well with real-world videos and are beneficial in the clinical diagnosis of hypomimia. In particular, hypomimia had a greater impact on eyes and mouths when patients are smiling.

Multimodal mechanisms of human socially reinforced learning across neurodegenerative diseases

Social feedback can selectively enhance learning in diverse domains. Relevant neurocognitive mechanisms have been studied mainly in healthy persons, yielding correlational findings. Neurodegenerative lesion models, coupled with multimodal brain measures, can complement standard approaches by revealing direct multidimensional correlates of the phenomenon.

To this end, we assessed socially reinforced and non-socially reinforced learning in 40 healthy participants as well as persons with behavioural variant frontotemporal dementia (n = 21), Parkinson’s disease (n = 31) and Alzheimer’s disease (n = 20). These conditions are typified by predominant deficits in social cognition, feedback-based learning and associative learning, respectively, although all three domains may be partly compromised in the other conditions. We combined a validated behavioural task with ongoing EEG signatures of implicit learning (medial frontal negativity) and offline MRI measures (voxel-based morphometry).

In healthy participants, learning was facilitated by social feedback relative to non-social feedback. In comparison with controls, this effect was specifically impaired in behavioural variant frontotemporal dementia and Parkinson’s disease, while unspecific learning deficits (across social and non-social conditions) were observed in Alzheimer’s disease. EEG results showed increased medial frontal negativity in healthy controls during social feedback and learning. Such a modulation was selectively disrupted in behavioural variant frontotemporal dementia. Neuroanatomical results revealed extended temporo-parietal and fronto-limbic correlates of socially reinforced learning, with specific temporo-parietal associations in behavioural variant frontotemporal dementia and predominantly fronto-limbic regions in Alzheimer’s disease. In contrast, non-socially reinforced learning was consistently linked to medial temporal/hippocampal regions. No associations with cortical volume were found in Parkinson’s disease. Results are consistent with core social deficits in behavioural variant frontotemporal dementia, subtle disruptions in ongoing feedback-mechanisms and social processes in Parkinson’s disease and generalized learning alterations in Alzheimer’s disease. This multimodal approach highlights the impact of different neurodegenerative profiles on learning and social feedback.

Our findings inform a promising theoretical and clinical agenda in the fields of social learning, socially reinforced learning and neurodegeneration.

Autonomic factors do not underlie the elevated self-disgust levels in Parkinson's disease

INTRODUCTION

Parkinson's disease (PD) is manifested along with non-motor symptoms such as impairments in basic emotion regulation, recognition and expression. Yet, self-conscious emotion (SCEs) such as self-disgust, guilt and shame are under-investigated. Our previous research indicated that Parkinson patients have elevated levels of self-reported and induced self-disgust. However, the cause of that elevation-whether lower level biophysiological factors, or higher level cognitive factors, is unknown.

METHODS

To explore the former, we analysed Skin Conductance Response (SCR, measuring sympathetic activity) amplitude and high frequency Heart Rate Variability (HRV, measuring parasympathetic activity) across two emotion induction paradigms, one involving narrations of personal experiences of self-disgust, shame and guilt, and one targeting self-disgust selectively via images of the self. Both paradigms had a neutral condition.

RESULTS

Photo paradigm elicited significant changes in physiological responses in patients relative to controls-higher percentages of HRV in the high frequency range but lower SCR amplitudes, with patients to present lower responses compared to controls. In the narration paradigm, only guilt condition elicited significant SCR differences between groups.

CONCLUSIONS

Consequently, lower level biophysiological factors are unlikely to cause elevated self-disgust levels in Parkinson's disease, which by implication suggests that higher level cognitive factors may be responsible.

Immunology and microbiology: how do they affect social cognition and emotion recognition?

Social interactions profoundly influence animals' life. The quality of social interactions and many everyday life decisions are determined by a proper perception, processing and reaction to others' emotions. Notably, alterations in these social processes characterize a number of neurodevelopmental disorders, including autism spectrum disorders and schizophrenia. Increasing evidences support an implication of immune system vulnerability and inflammatory processes in disparate behavioral functions and the aforementioned neurodevelopmental disorders. In this review, we show a possible unifying view on how immune responses, within and outside the brain, and the communication between the immune system and brain responses might influence emotion recognition and related social responses. In particular, we highlight the importance of combining genetics, immunology and microbiology factors in understanding social behaviors. We underline the importance of better disentangling the whole machinery between brain-immune system interactions to better address the complexity of social processes.

Approach to Cognitive Impairment in Parkinson's Disease

Cognitive dysfunction is common in Parkinson's disease (PD) and predicts poor clinical outcomes. It is associated primarily with pathologic involvement of basal forebrain cholinergic and prefrontal dopaminergic systems. Impairments in executive functions, attention, and visuospatial abilities are its hallmark features with eventual involvement of memory and other domains. Subtle symptoms in the premotor and early phases of PD progress to mild cognitive impairment (MCI) which may be present at the time of diagnosis. Eventually, a large majority of PD patients develop dementia with advancing age and longer disease duration, which is usually accompanied by immobility, hallucinations/psychosis, and dysautonomia. Dopaminergic medications and deep brain stimulation help motor dysfunction, but may have potential cognitive side effects. Central acetylcholinesterase inhibitors, and possibly memantine, provide modest and temporary symptomatic relief for dementia, although there is no evidence-based treatment for MCI. There is no proven disease-modifying treatment for cognitive impairment in PD. The symptomatic and disease-modifying role of physical exercise, cognitive training, and neuromodulation on cognitive impairment in PD is under investigation. Multidisciplinary approaches to cognitive impairment with effective treatment of comorbidities, proper rehabilitation, and maintenance of good support systems in addition to pharmaceutical treatment may improve the quality of life of the patients and caregivers.

Multicentric evidence of emotional impairments in hypertensive heart disease

The mechanisms underlying emotional alterations constitute a key research target in neuroscience. Emerging evidence indicates that these disruptions can be related to abnormal interoception (i.e., the sensing of visceral feelings), as observed in patients with cardiodynamic deficits. To directly assess these links, we performed the first multicenter study on emotion recognition and interoception in patients with hypertensive heart disease (HHD). Participants from two countries completed a facial emotion recognition test, and a subsample additionally underwent an interoception protocol based on a validated heartbeat detection task. HHD patients from both countries presented deficits in the recognition of overall and negative emotions. Moreover, interoceptive performance was impaired in the HHD group. In addition, a significant association between interoceptive performance and emotion recognition was observed in the control group, but this relation was abolished in the HHD group. All results survived after covariance with cognitive status measures, suggesting they were not biased by general cognitive deficits in the patients. Taken together, these findings suggest that emotional recognition alterations could represent a sui generis deficit in HHD, and that it may be partially explained by the disruption of mechanisms subserving the integration of neuro-visceral signals.