Investigating the relationship between Psychopathy, Fear Conditioning, and Facial Affect Recognition

<p>Psychopathic offenders are often considered to be untreatable, especially dangerous, and at very high risk of reoffending. Psychopathy has generated considerable research interest. Despite this interest, our understanding of psychopathy is relatively poor, with ongoing debate regarding how best to define psychopathy, and a lack of clarity regarding how psychopathy develops. Etiological theories of psychopathy posit deficits in recognising and responding to others’ emotions, and an attenuated experience of fear as crucial mechanisms in the development of psychopathy. The aims of this thesis are to investigate the pattern of psychopathic traits present within an inmate sample, and to investigate the relationship between these psychopathic traits and performance on two tasks related to etiological theories of psychopathy: facial affect recognition and fear conditioning. Part One of this thesis addresses the first aim, investigating the presentation of psychopathy in the current sample. The relationship between psychopathic traits in the present sample was largely consistent with previous research. A Principal Components Analysis identified two factors of psychopathic traits: a Bold/ Fearlessness factor which measures an absence of fear and anxiety and the presence of self-assurance, and a Mean/ Disinhibited factor which measures the presence of externalising and disinhibited behaviour, alongside aggression and the use of other people for one’s own gain. These findings are discussed in relation to common conceptualisations and operationalisations of psychopathy. Part Two of this thesis uses the measurement of psychopathy from Part One to investigate performance on a facial affect recognition task and a fear conditioning task. The Violence Inhibition Mechanism theory suggests that psychopaths should show impairments on facial affect recognition tasks, particularly in the recognition of fearful and sad facial expressions. However, in the current research psychopathy was unrelated to affect recognition, across all emotional expressions. When criminal offenders were compared to a student sample, the offenders showed poorer affect recognition than the students. These results suggest that there may be an effect of antisociality on affect recognition, but no effect of psychopathy. Low fear theories of psychopathy suggest that psychopaths should be impaired at learning conditioned fear associations. However, the present study found no evidence of psychopathy-related deficits in fear conditioning. Rather, higher psychopathy was related to better fear conditioning, with higher scores on the Mean/ Disinhibited factor predicting better discrimination between the conditioned and neutral stimuli. Taken together, these findings suggest that psychopathy was not related to deficits in either affect recognition or fear conditioning. These findings are inconsistent with etiological theories of psychopathy, and question common assumptions about the deficits which characterise psychopathy.</p>

Investigating the relationship between Psychopathy, Fear Conditioning, and Facial Affect Recognition

<p>Psychopathic offenders are often considered to be untreatable, especially dangerous, and at very high risk of reoffending. Psychopathy has generated considerable research interest. Despite this interest, our understanding of psychopathy is relatively poor, with ongoing debate regarding how best to define psychopathy, and a lack of clarity regarding how psychopathy develops. Etiological theories of psychopathy posit deficits in recognising and responding to others’ emotions, and an attenuated experience of fear as crucial mechanisms in the development of psychopathy. The aims of this thesis are to investigate the pattern of psychopathic traits present within an inmate sample, and to investigate the relationship between these psychopathic traits and performance on two tasks related to etiological theories of psychopathy: facial affect recognition and fear conditioning. Part One of this thesis addresses the first aim, investigating the presentation of psychopathy in the current sample. The relationship between psychopathic traits in the present sample was largely consistent with previous research. A Principal Components Analysis identified two factors of psychopathic traits: a Bold/ Fearlessness factor which measures an absence of fear and anxiety and the presence of self-assurance, and a Mean/ Disinhibited factor which measures the presence of externalising and disinhibited behaviour, alongside aggression and the use of other people for one’s own gain. These findings are discussed in relation to common conceptualisations and operationalisations of psychopathy. Part Two of this thesis uses the measurement of psychopathy from Part One to investigate performance on a facial affect recognition task and a fear conditioning task. The Violence Inhibition Mechanism theory suggests that psychopaths should show impairments on facial affect recognition tasks, particularly in the recognition of fearful and sad facial expressions. However, in the current research psychopathy was unrelated to affect recognition, across all emotional expressions. When criminal offenders were compared to a student sample, the offenders showed poorer affect recognition than the students. These results suggest that there may be an effect of antisociality on affect recognition, but no effect of psychopathy. Low fear theories of psychopathy suggest that psychopaths should be impaired at learning conditioned fear associations. However, the present study found no evidence of psychopathy-related deficits in fear conditioning. Rather, higher psychopathy was related to better fear conditioning, with higher scores on the Mean/ Disinhibited factor predicting better discrimination between the conditioned and neutral stimuli. Taken together, these findings suggest that psychopathy was not related to deficits in either affect recognition or fear conditioning. These findings are inconsistent with etiological theories of psychopathy, and question common assumptions about the deficits which characterise psychopathy.</p>

Interventions for social cognitive deficits

Interventions for social cognitive deficits establishes the large impact these deficits exert on psychosocial functioning in major depressive disorder. The chapter reviews a variety of impairments of social cognition and how these may influence psychosocial functioning in the key domains of social performance, emotional/empathic performance, general cognitive functioning, and quality of life. It introduces multiple treatment modalities including antidepressant medication, psychotherapeutic approaches, and procedural interventions with potential treatment efficacy on facial affect recognition, interpretation of affective pictures, theory of mind performance, and prosody. It reviews evidence indicating that many current therapies are shown to have a normalizing effect on the accuracy of interpretation and the reduction of underlying negative interpretative bias. It concludes from evaluating the literature that certain antidepressants seem to correct facial affect recognition deficits, and several psychotherapeutic approaches appear well-suited for addressing impaired theory of mind or mood-congruent interpretive biases.

How Interpersonal Distance Between Avatar and Human Influences Facial Affect Recognition in Immersive Virtual Reality

Purpose: The purpose of this study was to determine the optimal interpersonal distance (IPD) between humans and affective avatars in facial affect recognition in immersive virtual reality (IVR). The ideal IPD is the one in which the humans show the highest number of hits and the shortest reaction times in recognizing the emotions displayed by avatars. The results should help design future therapies to remedy facial affect recognition deficits.Methods: A group of 39 healthy volunteers participated in an experiment in which participants were shown 65 dynamic faces in IVR and had to identify six basic emotions plus neutral expression presented by the avatars. We decided to limit the experiment to five different distances: D1 (35 cm), D2 (55 cm), D3 (75 cm), D4 (95 cm), and D5 (115 cm), all belonging to the intimate and personal interpersonal spaces. Of the total of 65 faces, 13 faces were presented for each of the included distances. The views were shown at different angles: 50% in frontal view, 25% from the right profile, and 25% from the left profile. The order of appearance of the faces presented to each participant was randomized.Results: The overall success rate in facial emotion identification was 90.33%, being D3 the IPD with the best overall emotional recognition hits, although statistically significant differences could not be found between the IPDs. Consistent with results obtained in previous studies, identification rates for negative emotions were higher with increasing IPD, whereas the recognition task improved for positive emotions when IPD was closer. In addition, the study revealed irregular behavior in the facial detection of the emotion surprise.Conclusions: IVR allows us to reliably assess facial emotion recognition using dynamic avatars as all the IPDs tested showed to be effective. However, no statistically significant differences in facial emotion recognition were found among the different IPDs.

Facial Affect Recognition by Patients with Schizophrenia Using Human Avatars

People with schizophrenia have difficulty recognizing the emotions in the facial expressions of others, which affects their social interaction and functioning in the community. Static stimuli such as photographs have been used traditionally to examine deficiencies in the recognition of emotions in patients with schizophrenia, which has been criticized by some authors for lacking the dynamism that real facial stimuli have. With the aim of overcoming these drawbacks, in recent years, the creation and validation of virtual humans has been developed. This work presents the results of a study that evaluated facial recognition of emotions through a new set of dynamic virtual humans previously designed by the research team, in patients diagnosed of schizophrenia. The study included 56 stable patients, compared with 56 healthy controls. Our results showed that patients with schizophrenia present a deficit in facial affect recognition, compared to healthy controls (average hit rate 71.6% for patients vs 90.0% for controls). Facial expressions with greater dynamism (compared to less dynamic ones), as well as those presented from frontal view (compared to profile view) were better recognized in both groups. Regarding clinical and sociodemographic variables, the number of hospitalizations throughout life did not correlate with recognition rates. There was also no correlation between functioning or quality of life and recognition. A trend showed a reduction in the emotional recognition rate as a result of increases in Positive and Negative Syndrome Scale (PANSS), being statistically significant for negative PANSS. Patients presented a learning effect during the progression of the task, slightly greater in comparison to the control group. This finding is relevant when designing training interventions for people with schizophrenia. Maintaining the attention of patients and getting them to improve in the proposed tasks is a challenge for today’s psychiatry.

Validation of dynamic virtual faces for facial affect recognition

The ability to recognise facial emotions is essential for successful social interaction. The most common stimuli used when evaluating this ability are photographs. Although these stimuli have proved to be valid, they do not offer the level of realism that virtual humans have achieved. The objective of the present paper is the validation of a new set of dynamic virtual faces (DVFs) that mimic the six basic emotions plus the neutral expression. The faces are prepared to be observed with low and high dynamism, and from front and side views. For this purpose, 204 healthy participants, stratified by gender, age and education level, were recruited for assessing their facial affect recognition with the set of DVFs. The accuracy in responses was compared with the already validated Penn Emotion Recognition Test (ER-40). The results showed that DVFs were as valid as standardised natural faces for accurately recreating human-like facial expressions. The overall accuracy in the identification of emotions was higher for the DVFs (88.25%) than for the ER-40 faces (82.60%). The percentage of hits of each DVF emotion was high, especially for neutral expression and happiness emotion. No statistically significant differences were discovered regarding gender. Nor were significant differences found between younger adults and adults over 60 years. Moreover, there is an increase of hits for avatar faces showing a greater dynamism, as well as front views of the DVFs compared to their profile presentations. DVFs are as valid as standardised natural faces for accurately recreating human-like facial expressions of emotions.

QOL-15. NEURAL NETWORK INTEGRITY FOR FACIAL AFFECT RECOGNITION IN SURVIVORS OF MEDULLOBLASTOMA

BACKGROUND Medulloblastoma survivors are at risk for social deficits, yet underlying mechanisms are poorly understood. METHODS Facial affect recognition was assessed in 50 medulloblastoma survivors treated with craniospinal radiation (median[range] 21.4[12.5–30.9] years old, 11.0[5.7–22.6] years since diagnosis) and 56 non-cancer age-, sex-, and race-matched controls. Brain activation and connectivity in core regions/nodes of the face perception network (fusiform gyri, occipital gyri, superior temporal sulcus) were examined using structural and functional neuroimaging. Structural networks were constructed from diffusion tensor imaging (DTI) data and individual node strength and efficiency were assessed. Functional MRI (fMRI) was conducted using a 1-back facial affect recognition task with assessment of regional differences in task-related cerebral blood flow (BOLD). Standardized neurocognitive testing was completed with 24 hours of brain imaging. RESULTS Medulloblastoma survivors performed worse on a behavioral measure of facial affect recognition (P=0.003) compared to matched controls. During the facial affect recognition task, controls demonstrated greater BOLD activation of the left and right fusiform gyri and the left and right middle occipital gyri compared to survivors (P’s&lt;0.05, corrected for multiple comparisons). DTI indicated weaker core node strength in survivors in the right lateral occipital gyri (P=0.02) and efficiency was lower in the left (P=0.01) and right (P=0.03) occipital gyri compared to controls. CONCLUSIONS Medulloblastoma survivors have deficits in facial affect recognition and reduced activation and efficiency in brain regions comprising the face perception network compared to matched controls. Interventions targeting this specific skill and neural network may improve social functioning in survivors.