Social Bayes: Using Bayesian Modeling to Study Autistic Trait-Related Differences in Social Cognition

Heterogeneity in strategy use during arbitration between experiential and observational learning

To navigate our complex social world, it is crucial to deploy multiple learning strategies, such as learning from directly experiencing action outcomes or from observing other people's behavior. Despite the prevalence of experiential and observational learning in humans and other social animals, it remains unclear how people favor one strategy over the other depending on the environment, and how individuals vary in their strategy use. Here, we describe an arbitration mechanism in which the prediction errors associated with each learning strategy influence their weight over behavior. We designed an online behavioral task to test our computational model, and found that while a substantial proportion of participants relied on the proposed arbitration mechanism, there was some meaningful heterogeneity in how people solved this task. Four other groups were identified: those who used a fixed mixture between the two strategies, those who relied on a single strategy and non-learners with irrelevant strategies. Furthermore, groups were found to differ on key behavioral signatures, and on transdiagnostic symptom dimensions, in particular autism traits and anxiety. Together, these results demonstrate how large heterogeneous datasets and computational methods can be leveraged to better characterize individual differences.

Is she still angry? Intact learning but no updating of facial expressions priors in autism

Autistic people exhibit atypical use of prior information when processing simple perceptual stimuli; yet, it remains unclear whether and how these difficulties in using priors extend to complex social stimuli. Here, we compared autistic people without accompanying intellectual disability and nonautistic people in their ability to acquire an "emotional prior" of a facial expression and update this prior to a different facial expression of the same identity. Participants performed a two-interval same/different discrimination task between two facial expressions. To study the acquisition of the prior, we examined how discrimination was modified by the contraction of the perceived facial expressions toward the average of presented stimuli (i.e., regression to the mean). At first, facial expressions surrounded one average emotional prior (mostly sad or angry), and then the average switched (to mostly angry or sad, accordingly). Autistic people exhibited challenges in facial discrimination, and yet acquired the first prior, demonstrating typical regression-to-the-mean effects. However, unlike nonautistic people, autistic people did not update their perception to the second prior, suggesting they are less flexible in updating an acquired prior of emotional expressions. Our findings shed light on the perception of emotional expressions, one of the most pressing challenges in autism.

Attachment and borderline personality disorder as the dance unfolds: A quantitative analysis of a novel paradigm

Current research on personality disorders strives to identify key behavioural and cognitive facets of patient functioning, to unravel the underlying root causes and maintenance mechanisms. This process often involves the application of social paradigms - however, these often only include momentary affective depictions rather than unfolding interactions. This constitutes a limitation in our capacity to probe core symptoms, and leaves potential findings uncovered which could help those who are in close relationships with affected individuals. Here, we deployed a novel task in which subjects interact with four unknown virtual partners in a turn-taking paradigm akin to a dance, and report on their experience with each. The virtual partners embody four combinations of low/high expressivity of positive/negative mood. Higher scores on our symptomatic measures of attachment anxiety, avoidance, and borderline personality disorder (BPD) were all linked to a general negative appraisal of all the interpersonal experiences. Moreover, the negative appraisal of the partner who displayed a high negative/low positive mood was tied with attachment anxiety and BPD symptoms. The extent to which subjects felt responsible for causing partners' distress was most strongly linked to attachment anxiety. Finally, we provide a fully-fledged exploration of move-by-move action latencies and click distances from partners. This analysis underscored slower movement initiation from anxiously attached individuals throughout all virtual interactions. In summary, we describe a novel paradigm for second-person neuroscience, which allowed both the replication of established results and the capture of new behavioural signatures associated with attachment anxiety, and discuss its limitations.

Improved emotion differentiation under reduced acoustic variability of speech in autism

BACKGROUND

Socio-emotional impairments are among the diagnostic criteria for autism spectrum disorder (ASD), but the actual knowledge has substantiated both altered and intact emotional prosodies recognition. Here, a Bayesian framework of perception is considered suggesting that the oversampling of sensory evidence would impair perception within highly variable environments. However, reliable hierarchical structures for spectral and temporal cues would foster emotion discrimination by autistics.

METHODS

Event-related spectral perturbations (ERSP) extracted from electroencephalographic (EEG) data indexed the perception of anger, disgust, fear, happiness, neutral, and sadness prosodies while listening to speech uttered by (a) human or (b) synthesized voices characterized by reduced volatility and variability of acoustic environments. The assessment of mechanisms for perception was extended to the visual domain by analyzing the behavioral accuracy within a non-social task in which dynamics of precision weighting between bottom-up evidence and top-down inferences were emphasized. Eighty children (mean 9.7 years old; standard deviation 1.8) volunteered including 40 autistics. The symptomatology was assessed at the time of the study via the Autism Diagnostic Observation Schedule, Second Edition, and parents' responses on the Autism Spectrum Rating Scales. A mixed within-between analysis of variance was conducted to assess the effects of group (autism versus typical development), voice, emotions, and interaction between factors. A Bayesian analysis was implemented to quantify the evidence in favor of the null hypothesis in case of non-significance. Post hoc comparisons were corrected for multiple testing.

RESULTS

Autistic children presented impaired emotion differentiation while listening to speech uttered by human voices, which was improved when the acoustic volatility and variability of voices were reduced. Divergent neural patterns were observed from neurotypicals to autistics, emphasizing different mechanisms for perception. Accordingly, behavioral measurements on the visual task were consistent with the over-precision ascribed to the environmental variability (sensory processing) that weakened performance. Unlike autistic children, neurotypicals could differentiate emotions induced by all voices.

CONCLUSIONS

This study outlines behavioral and neurophysiological mechanisms that underpin responses to sensory variability. Neurobiological insights into the processing of emotional prosodies emphasized the potential of acoustically modified emotional prosodies to improve emotion differentiation by autistics.

TRIAL REGISTRATION

BioMed Central ISRCTN Registry, ISRCTN18117434. Registered on September 20, 2020.

The effect of autistic traits on prosocial behavior: The chain mediating role of received social support and perceived social support

ABSTRACT

There is growing evidence that the defining characteristics of autism spectrum disorder are distributed across the general population; therefore, understanding the correlates of prosocial behavior in individuals with high levels of autistic traits could shed light on autism spectrum disorder and prosocial behavior. In this study, the mechanism underlying the influence of individuals’ autistic traits on their prosocial behavior was explored by conducting a questionnaire survey of 414 Chinese college students. The results showed that autistic traits can influence individuals’ prosocial behavior not only through the separate effects of received social support and perceived social support but also through the chain mediating effects of received social support and perceived social support; however, the direct effect of autistic traits on individuals’ prosocial behavior is not significant. This study is conducive to understanding the internal mechanism underlying the relationship between autistic traits and prosocial behavior. Future work is required to further investigate the clinical autism spectrum disorder samples and cross-cultural applicability of the model found in this study.

Altered Perception of Environmental Volatility During Social Learning in Emerging Psychosis

Paranoid delusions or unfounded beliefs that others intend to deliberately cause harm are a frequent and burdensome symptom in early psychosis, but their emergence and consolidation still remains opaque. Recent theories suggest that overly precise prediction errors lead to an unstable model of the world providing a breeding ground for delusions. Here, we employ a Bayesian approach to test for such an unstable model of the world and investigate the computational mechanisms underlying emerging paranoia. We modelled behaviour of 18 first-episode psychosis patients (FEP), 19 individuals at clinical high risk for psychosis (CHR-P), and 19 healthy controls (HC) during an advice-taking task designed to probe learning about others' changing intentions. We formulated competing hypotheses comparing the standard Hierarchical Gaussian Filter (HGF), a Bayesian belief updating scheme, with a mean-reverting HGF to model an altered perception of volatility. There was a significant group-by-volatility interaction on advice-taking suggesting that CHR-P and FEP displayed reduced adaptability to environmental volatility. Model comparison favored the standard HGF in HC, but the mean-reverting HGF in CHR-P and FEP in line with perceiving increased volatility, although model attributions in CHR-P were heterogeneous. We observed correlations between perceiving increased volatility and positive symptoms generally as well as with frequency of paranoid delusions specifically. Our results suggest that FEP are characterised by a different computational mechanism - perceiving the environment as increasingly volatile - in line with Bayesian accounts of psychosis. This approach may prove useful to investigate heterogeneity in CHR-P and identify vulnerability for transition to psychosis.

Bayesian Decision-Making Under Uncertainty in Borderline Personality Disorder

Bayesian decision theory suggests that optimal decision-making should use and weigh prior beliefs with current information, according to their relative uncertainties. However, some characteristics of borderline personality disorder (BPD) patients, such as fast, drastic changes in the overall perception of themselves and others, suggest they may be underrelying on priors. Here, we investigated if BPD patients have a general deficit in relying on or combining prior with current information. We analyzed this by having BPD patients (n = 23) and healthy controls (n = 18) perform a coin-catching sensorimotor task with varying levels of prior and current information uncertainty. Our results indicate that BPD patients learned and used prior information and combined it with current information in a qualitatively Bayesian-like way. Our results show that, at least in a lower-level, nonsocial sensorimotor task, BPD patients can appropriately use both prior and current information, illustrating that potential deficits using priors may not be widespread or domain-general.

Gaze-Triggered Communicative Intention Compresses Perceived Temporal Duration

Eye gaze communicates a person's attentional state and intentions toward objects. Here we demonstrate that this important social signal has the potential to distort time perception of gazed-at objects (N = 70 adults). By using a novel gaze-associated learning paradigm combined with the time-discrimination task, we showed that objects previously associated with others' eye gaze were perceived as significantly shorter in duration than the nonassociated counterparts. The time-compression effect cannot be attributed to general attention allocation because it disappeared when objects were associated with nonsocial attention cues (i.e., arrows). Critically, this effect correlated with observers' autistic traits and vanished when the gazing agent's line of sight was blocked by barriers, reflecting the key role of intention processing triggered by gaze in modulating time perception. Our findings support the existence of a special mechanism tuned to social cues, which can shape our perception of the outer world in time domains.

Impaired social concept processing in persons with autistic-like traits

Situated models suggest that social concepts are grounded in interpersonal experience. However, few studies have tested this notion experimentally, and none has targeted individuals with reduced social interaction. Here, we assessed comprehension of text-level social and non-social concepts in persons with and without autistic-like traits. Participants read a social and a non-social text and answered questionnaires targeting social and non-social concepts, respectively. We compared behavioral outcomes, gauged their contribution to subject-level classification, and examined their association with validated measures of autism. Persons with autistic-like traits showed selective deficits in grasping text-level social concepts, even adjusting for intelligence, memory, and vocabulary. Also, social concept comprehension was the only variable that significantly classified between groups. Finally, social concept outcomes correlated negatively with measures of autism, including social interaction. Our results suggest that reduced interpersonal experience selectively compromises text-level social concept processing, offering empirical constraints for situated models of social semantics.

Gyrus rectus asymmetry predicts trait alexithymia, cognitive empathy, and social function in neurotypical adults

Reduced empathy and elevated alexithymia are observed in autism spectrum disorder (ASD), which has been linked to altered asymmetry in brain morphology. Here, we investigated whether trait autism, empathy, and alexithymia in the general population is associated with brain morphological asymmetry. We determined left-right asymmetry indexes for cortical thickness and cortical surface area (CSA) and applied these features to a support-vector regression model that predicted trait autism, empathy, and alexithymia. Results showed that less leftward asymmetry of CSA in the gyrus rectus (a subregion of the orbitofrontal cortex) predicted more difficulties in social functioning, as well as reduced cognitive empathy and elevated trait alexithymia. Meta-analytic decoding of the left gyrus rectus annotated functional items related to social cognition. Furthermore, the link between gyrus rectus asymmetry and social difficulties was accounted by trait alexithymia and cognitive empathy. These results suggest that gyrus rectus asymmetry could be a shared neural correlate among trait alexithymia, cognitive empathy, and social functioning in neurotypical adults. Left-right asymmetry of gyrus rectus influenced social functioning by affecting the cognitive processes of emotions in the self and others. Interventions that increase leftward asymmetry of the gyrus rectus might improve social functioning for individuals with ASD.

10 years of Bayesian theories of autism: A comprehensive review

Ten years ago, Pellicano and Burr published one of the most influential articles in the study of autism spectrum disorders, linking them to aberrant Bayesian inference processes in the brain. In particular, they proposed that autistic individuals are less influenced by their brains' prior beliefs about the environment. In this systematic review, we investigate if this theory is supported by the experimental evidence. To that end, we collect all studies which included comparisons across diagnostic groups or autistic traits and categorise them based on the investigated priors. Our results are highly mixed, with a slight majority of studies finding no difference in the integration of Bayesian priors. We find that priors developed during the experiments exhibited reduced influences more frequently than priors acquired previously, with various studies providing evidence for learning differences between participant groups. Finally, we focus on the methodological and computational aspects of the included studies, showing low statistical power and often inconsistent approaches. Based on our findings, we propose guidelines for future research.

The (un)learning of social functions and its significance for mental health

Social interactions are dynamic, context-dependent, and reciprocal events that influence prospective strategies and require constant practice and adaptation. This complexity of social interactions creates several research challenges. We propose a new framework encouraging future research to investigate not only individual differences in capacities relevant for social functioning and their underlying mechanisms, but also the flexibility to adapt or update one's social abilities. We suggest three key capacities relevant for social functioning: (1) social perception, (2) sharing emotions or empathizing, and (3) mentalizing. We elaborate on how adaptations in these capacities may be investigated on behavioral and neural levels. Research on these flexible adaptations of one's social behavior is needed to specify how humans actually "learn to be social". Learning to adapt implies plasticity of the relevant brain networks involved in the underlying social processes, indicating that social abilities are malleable for different contexts. To quantify such measures, researchers need to find ways to investigate learning through dynamic changes in adaptable social paradigms and examine several factors influencing social functioning within the three aformentioned social key capacities. This framework furthers insight concerning individual differences, provides a holistic approach to social functioning, and may improve interventions for ameliorating social abilities in patients.

Modulating hierarchical learning by high-definition transcranial alternating current stimulation at theta frequency

Considerable evidence highlights the dorsolateral prefrontal cortex (DLPFC) as a key region for hierarchical (i.e. multilevel) learning. In a previous electroencephalography (EEG) study, we found that the low-level prediction errors were encoded by frontal theta oscillations (4-7 Hz), centered on right DLPFC (rDLPFC). However, the causal relationship between frontal theta oscillations and hierarchical learning remains poorly understood. To investigate this question, in the current study, participants received theta (6 Hz) and sham high-definition transcranial alternating current stimulation (HD-tACS) over the rDLPFC while performing the probabilistic reversal learning task. Behaviorally, theta tACS induced a significant reduction in accuracy for the stable environment, but not for the volatile environment, relative to the sham condition. Computationally, we implemented a combination of a hierarchical Bayesian learning and a decision model. Theta tACS induced a significant increase in low-level (i.e. probability-level) learning rate and uncertainty of low-level estimation relative to sham condition. Instead, the temperature parameter of the decision model, which represents (inverse) decision noise, was not significantly altered due to theta stimulation. These results indicate that theta frequency may modulate the (low-level) learning rate. Furthermore, environmental features (e.g. its stability) may determine whether learning is optimized as a result.

Pupil dilation predicts modulation of direct gaze on action value calculations

Perceiving direct gaze facilitates social cognition and behaviour. We hypothesized that direct gaze modulates decision-making, particularly calculations of action values. To test our hypothesis, we used the reinforcement learning paradigm in situations with or without direct gaze. Forty adults were recruited and participated in pupil size measurements and a two-armed bandit task. The task was conducted with 70% and 30% reward probabilities for each option. During the task, a female showing the Direct Gaze (DG) or Closed Eyes (CE) condition was presented from the start of each trial. The results showed that behavioural bias to choices with 70% reward probability increased more in the DG condition than in the CE condition and the expected reward value. This bias to choices with 70% reward in the DG condition was predicted by pupil dilation to DG. These results suggest that participants over-evaluated the expected reward value in the DG condition, and this DG effect may be related to subjective expectations of rewarding events indexed by pupil dilations. It is considered that perceiving direct gaze is a driver of reward expectations that modulate action value calculations and then cognitive processing and behaviours are facilitated.

Atypical processing pattern of gaze cues in dynamic situations in autism spectrum disorders

Psychological studies have generally shown that individuals with Autism Spectrum Disorder (ASD) have particularity in the processing of social information by using static or abstract images. Yet, a recent study showed that there was no difference in their use of social or non-social cues in dynamic interactive situations. To establish the cause of the inconsistent results, we added gaze cues in different directions to the chase detection paradigm to explore whether they would affect the performance of participants with ASD. Meanwhile, eye-tracking methodology was used to investigate whether the processing patterns of gaze cues were different between individuals with ASD and TD. In this study, unlike typical controls, participants with ASD showed no detection advantage when the direction of gaze was consistent with the direction of movement (oriented condition). The results suggested that individuals with ASD may utilize an atypical processing pattern, which makes it difficult for them to use social information contained in oriented gaze cues in dynamic interactive situations.

Unity Assumption in Audiovisual Emotion Perception

We experience various sensory stimuli every day. How does this integration occur? What are the inherent mechanisms in this integration? The “unity assumption” proposes a perceiver’s belief of unity in individual unisensory information to modulate the degree of multisensory integration. However, this has yet to be verified or quantified in the context of semantic emotion integration. In the present study, we investigate the ability of subjects to judge the intensities and degrees of similarity in faces and voices of two emotions (angry and happy). We found more similar stimulus intensities to be associated with stronger likelihoods of the face and voice being integrated. More interestingly, multisensory integration in emotion perception was observed to follow a Gaussian distribution as a function of the emotion intensity difference between the face and voice—the optimal cut-off at about 2.50 points difference on a 7-point Likert scale. This provides a quantitative estimation of the multisensory integration function in audio-visual semantic emotion perception with regards to stimulus intensity. Moreover, to investigate the variation of multisensory integration across the population, we examined the effects of personality and autistic traits of participants. Here, we found no correlation of autistic traits with unisensory processing in a nonclinical population. Our findings shed light on the current understanding of multisensory integration mechanisms.

Autistic Traits and Empathy for Others' Pain Among the General Population: Test of the Mediating Effects of First-Hand Pain Sensitivity

Autism spectrum disorders (ASD) are characterized by reduced pain empathy-a process that is grounded in first-hand pain perception. Because autistic traits are continuously distributed in the general population, we hypothesized that first-hand pain sensitivity would mediate the link between autistic traits and pain empathy. After controlling for alexithymia, higher autistic traits were associated with lower cognitive and emotional empathy in response to others' pain, as well as lower sensitivity to cold and heat pain (higher cold pain tolerance and lower laser heat pain-intensity ratings). Importantly, pain sensitivity fully mediated the link between autistic traits and pain empathy. These findings highlight the role of atypical first-hand pain sensitivity in the lack of pain empathy observed in people with high autistic traits or ASD.

Empathy for pain in individuals with autistic traits during observation of static and dynamic stimuli

Previous studies have reported that individuals with autistic traits, like those with Autism Spectrum Disorder (ASD), may have impaired empathic responses when observing static stimuli of others' pain. However, it remains unclear whether individuals with autistic traits exhibit impaired empathy for pain in response to dynamic stimuli. The present study addressed this question by recruiting 529 individuals whose autistic traits were assessed using the autism-spectrum quotient (AQ) questionnaire. Thirty participants who scored within the top 10% and bottom 10% on the AQ were selected into High-AQ and Low-AQ groups, respectively. This study employed painful whole-body action pictures and videos as static and dynamic stimuli. Both groups were instructed to judge whether the models in the stimuli were experiencing pain, and their reaction times, accuracy and event-related potential (ERP) data were recorded. Results showed that the P2 amplitudes were larger in the High-AQ group than in the Low-AQ group when viewing painful static stimuli, while no difference between the two groups was found when viewing painful dynamic stimuli. These results suggest that autistic traits influenced the emotional processing of others' pain in response to static stimuli.

Neural network modeling of altered facial expression recognition in autism spectrum disorders based on predictive processing framework

The mechanism underlying the emergence of emotional categories from visual facial expression information during the developmental process is largely unknown. Therefore, this study proposes a system-level explanation for understanding the facial emotion recognition process and its alteration in autism spectrum disorder (ASD) from the perspective of predictive processing theory. Predictive processing for facial emotion recognition was implemented as a hierarchical recurrent neural network (RNN). The RNNs were trained to predict the dynamic changes of facial expression movies for six basic emotions without explicit emotion labels as a developmental learning process, and were evaluated by the performance of recognizing unseen facial expressions for the test phase. In addition, the causal relationship between the network characteristics assumed in ASD and ASD-like cognition was investigated. After the developmental learning process, emotional clusters emerged in the natural course of self-organization in higher-level neurons, even though emotional labels were not explicitly instructed. In addition, the network successfully recognized unseen test facial sequences by adjusting higher-level activity through the process of minimizing precision-weighted prediction error. In contrast, the network simulating altered intrinsic neural excitability demonstrated reduced generalization capability and impaired emotional clustering in higher-level neurons. Consistent with previous findings from human behavioral studies, an excessive precision estimation of noisy details underlies this ASD-like cognition. These results support the idea that impaired facial emotion recognition in ASD can be explained by altered predictive processing, and provide possible insight for investigating the neurophysiological basis of affective contact.

The Association among Autistic Traits, Interactional Synchrony and Typical Pattern of Motor Planning and Execution in Neurotypical Individuals

Autism spectrum disorder (ASD) is characterized by deficits in interactional synchrony and motor performance, but little is known about the association between them. The current study investigated the association among aberrant interactional synchrony (as measured by interactors’ symmetry in the form of the hand at each time-point along movement’s execution), motor functioning and the level of Autistic traits. In this study, autistic traits were evaluated by the Autistic Spectrum Quotient (AQ). Two tasks were used: (1) an interactional synchrony task where participants and the research assistant were instructed to move their hands together; and (2) a motor planning task which allows for continuous monitoring of natural hand movements. Pearson correlation analysis indicated a significant association between lower communication skills (i.e., higher AQ communication scores) and lower intentional synchrony rates. In addition, lower communication skills were found associated with typical patterns of motor planning and execution characterized by shorter time to start the movement and higher value of max speed. Mediator analyses supported the notion that aberrant intentional synchrony in individuals with low communication skills is partially mediated through typical patterns of motor planning and execution. These results suggest typical patterns of motor functions may account for intentional synchrony difficulties.

Keeping in time with social and non-social stimuli: Synchronisation with auditory, visual, and audio-visual cues

Everyday social interactions require us to closely monitor, predict, and synchronise our movements with those of an interacting partner. Experimental studies of social synchrony typically examine the social-cognitive outcomes associated with synchrony, such as affiliation. On the other hand, research on the sensorimotor aspects of synchronisation generally uses non-social stimuli (e.g. a moving dot). To date, the differences in sensorimotor aspects of synchronisation to social compared to non-social stimuli remain largely unknown. The present study aims to address this gap using a verbal response paradigm where participants were asked to synchronise a 'ba' response in time with social and non-social stimuli, which were presented auditorily, visually, or audio-visually combined. For social stimuli a video/audio recording of an actor performing the same verbal 'ba' response was presented, whereas for non-social stimuli a moving dot, an auditory metronome or both combined were presented. The impact of autistic traits on participants' synchronisation performance was examined using the Autism Spectrum Quotient (AQ). Our results revealed more accurate synchronisation for social compared to non-social stimuli, suggesting that greater familiarity with and motivation in attending to social stimuli may enhance our ability to better predict and synchronise with them. Individuals with fewer autistic traits demonstrated greater social learning, as indexed through an improvement in synchronisation performance to social vs non-social stimuli across the experiment.

Human aging alters social inference about others' changing intentions

Decoding others' intentions accurately in order to adapt one's own behavior is pivotal throughout life. In this study, we asked how younger and older adults deal with uncertainty in dynamic social environments. We used an advice-taking paradigm together with Bayesian modeling to characterize effects of aging on learning about others' time-varying intentions. We observed age differences when comparing learning on two levels of social uncertainty: the fidelity of the adviser and the volatility of intentions. Older adults expected the adviser to change his/her intentions more frequently (i.e., a higher volatility of the adviser). They also showed higher confidence (i.e., precision) in their volatility beliefs and were less willing to change their beliefs about volatility over the course of the experiment. This led them to update their predictions about the fidelity of the adviser more quickly. Potentially indicative of stereotype effects, we observed that older advisers were perceived as more volatile, but also more faithful than younger advisers. This offers new insights into adult age differences in response to social uncertainty.

Interpersonal Motor Interactions Shape Multisensory Representations of the Peripersonal Space

This perspective review focuses on the proposal that predictive multisensory integration occurring in one's peripersonal space (PPS) supports individuals' ability to efficiently interact with others, and that integrating sensorimotor signals from the interacting partners leads to the emergence of a shared representation of the PPS. To support this proposal, we first introduce the features of body and PPS representations that are relevant for interpersonal motor interactions. Then, we highlight the role of action planning and execution on the dynamic expansion of the PPS. We continue by presenting evidence of PPS modulations after tool use and review studies suggesting that PPS expansions may be accounted for by Bayesian sensory filtering through predictive coding. In the central section, we describe how this conceptual framework can be used to explain the mechanisms through which the PPS may be modulated by the actions of our interaction partner, in order to facilitate interpersonal coordination. Last, we discuss how this proposal may support recent evidence concerning PPS rigidity in Autism Spectrum Disorder (ASD) and its possible relationship with ASD individuals' difficulties during interpersonal coordination. Future studies will need to clarify the mechanisms and neural underpinning of these dynamic, interpersonal modulations of the PPS.

Performance in a gaze-cueing task is associated with autistic traits

Individuals with autism spectrum disorder (ASD) show impairments in processing social cues such as facial expressions and gaze direction. Several researchers have proposed that autistic traits form a continuum that may be distributed within the general, typically developed, population. Accordingly, several studies have indicated that typically developed individuals with high levels of self-reported autistic traits have autistic-like performance in a variety of paradigms. Here, we designed a gaze-cueing task to examine whether gaze-triggered orienting is related to the extent of typically developed (TD) individuals' autistic traits (determined by their AQ test scores) and whether it is modulated by previous eye contact and different facial expressions. At each trial, TD subjects observed faces with or without eye contact. This facial stimulus then gazed toward the left or right side. Finally, a target appeared on the left or right side of the display and reaction time (RT) to the target was measured. RTs were modulated by congruency between gazing directions and target locations, and by prior eye contact in the congruent trials. In addition, individuals with higher AQ scores were slower at detecting the target when the cue was a happy face. Furthermore, faster RTs in congruent trials were associated with one specific autistic trait (attention switching deficits). Together, these results indicate that autistic traits may influence performance in a gaze cueing task.

Interpersonal similarity of autistic traits predicts friendship quality

Autistic traits are known to be associated with social interaction difficulties. Yet, somewhat paradoxically, relevant research has been typically restricted to studying individuals. In line with the 'dialectical misattunement hypothesis' and clinical insights of intact social interactions among autistic individuals, we hypothesized that friendship quality varies as a function of interpersonal similarity and more concretely the difference value of autistic traits in a dyad, above and beyond autistic traits per se. Therefore, in this study, we used self-report questionnaires to investigate these measures in a sample of 67 neurotypical dyads across a broad range of autistic traits. Our results demonstrate that the more similar two persons are in autistic traits, the higher is the perceived quality of their friendship, irrespective of friendship duration, age, sex and, importantly, the (average of) autistic traits in a given dyad. More specifically, higher interpersonal similarity of autistic traits was associated with higher measures of closeness, acceptance and help. These results, therefore, lend support to the idea of an interactive turn in the study of social abilities across the autism spectrum and pave the way for future studies on the multiscale dynamics of social interactions.

Schema therapy versus cognitive behavioral therapy versus individual supportive therapy for depression in an inpatient and day clinic setting: study protocol of the OPTIMA-RCT

BACKGROUND

Major depressive disorder represents (MDD) a major cause of disability and disease burden. Beside antidepressant medication, psychotherapy is a key approach of treatment. Schema therapy has been shown to be effective in the treatment of psychiatric disorders, especially personality disorders, in a variety of settings and patient groups. Nevertheless, there is no evidence on its effectiveness for MDD in an inpatient nor day clinic setting and little is known about the factors that drive treatment response in such a target group.

METHODS

In the current protocol, we outline OPTIMA (OPtimized Treatment Identification at the MAx Planck Institute): a single-center randomized controlled trial of schema therapy as a treatment approach for MDD in an inpatient and day clinic setting. Over the course of 7 weeks, we compare schema therapy with cognitive behavioral therapy and individual supportive therapy, conducted in individual and group sessions and with no restrictions regarding concurrent antidepressant medication, thus approximating real-life treatment conditions. N = 300 depressed patients are included. All study therapists undergo a specific training and supervision and therapy adherence is assessed. Primary outcome is depressive symptom severity as self-assessment (Beck Depression Inventory-II) and secondary outcomes are clinical ratings of MDD (Montgomery-Asberg Depression Rating Scale), recovery rates after 7 weeks according to the Munich-Composite International Diagnostic Interview, general psychopathology (Brief Symptom Inventory), global functioning (World Health Organization Disability Assessment Schedule), and clinical parameters such as dropout rates. Further parameters on a behavioral, cognitive, psychophysiological, and biological level are measured before, during and after treatment and in 2 follow-up assessments after 6 and 24 months after end of treatment.

DISCUSSION

To our knowledge, the OPTIMA-Trial is the first to investigate the effectiveness of schema therapy as a treatment approach of MDD, to investigate mechanisms of change, and explore predictors of treatment response in an inpatient and day clinic setting by using such a wide range of parameters. Insights from OPTIMA will allow more integrative approaches of psychotherapy of MDD. Especially, the identification of intervention-specific markers of treatment response can improve evidence-based clinical decision for individualizing treatment.

TRIAL REGISTRATION

Identifier on clinicaltrials.gov : NCT03287362 ; September, 12, 2017.

Aberrant computational mechanisms of social learning and decision-making in schizophrenia and borderline personality disorder

Psychiatric disorders are ubiquitously characterized by debilitating social impairments. These difficulties are thought to emerge from aberrant social inference. In order to elucidate the underlying computational mechanisms, patients diagnosed with major depressive disorder (N = 29), schizophrenia (N = 31), and borderline personality disorder (N = 31) as well as healthy controls (N = 34) performed a probabilistic reward learning task in which participants could learn from social and non-social information. Patients with schizophrenia and borderline personality disorder performed more poorly on the task than healthy controls and patients with major depressive disorder. Broken down by domain, borderline personality disorder patients performed better in the social compared to the non-social domain. In contrast, controls and major depressive disorder patients showed the opposite pattern and schizophrenia patients showed no difference between domains. In effect, borderline personality disorder patients gave up a possible overall performance advantage by concentrating their learning in the social at the expense of the non-social domain. We used computational modeling to assess learning and decision-making parameters estimated for each participant from their behavior. This enabled additional insights into the underlying learning and decision-making mechanisms. Patients with borderline personality disorder showed slower learning from social and non-social information and an exaggerated sensitivity to changes in environmental volatility, both in the non-social and the social domain, but more so in the latter. Regarding decision-making the modeling revealed that compared to controls and major depression patients, patients with borderline personality disorder and schizophrenia showed a stronger reliance on social relative to non-social information when making choices. Depressed patients did not differ significantly from controls in this respect. Overall, our results are consistent with the notion of a general interpersonal hypersensitivity in borderline personality disorder and schizophrenia based on a shared computational mechanism characterized by an over-reliance on beliefs about others in making decisions and by an exaggerated need to make sense of others during learning specifically in borderline personality disorder.

People suffering from psychiatric disorders frequently experience difficulties in social interaction, such as an impaired ability to use social signals to build representations of others and use these to guide behavior. Compuational models of learning and decision-making enable the characterization of individual patterns in learning and decision-making mechanisms that may be disorder-specific or disorder-general. We employed this approach to investigate the behavior of healthy participants and patients diagnosed with depression, schizophrenia, and borderline personality disorder while they performed a probabilistic reward learning task which included a social component. Patients with schizophrenia and borderline personality disorder performed more poorly on the task than controls and depressed patients. In addition, patients with borderline personality disorder concentrated their learning efforts more on the social compared to the non-social information. Computational modeling additionally revealed that borderline personality disorder patients showed a reduced flexibility in the weighting of newly obtained social and non-social information when learning about their predictive value. Instead, we found exaggerated learning of the volatility of social and non-social information. Additionally, we found a pattern shared between patients with borderline personality disorder and schizophrenia who both showed an over-reliance on predictions about social information during decision-making. Our modeling therefore provides a computational account of the exaggerated need to make sense of and rely on one’s interpretation of others’ behavior, which is prominent in both disorders.

Integration of social cues and individual experiences during instrumental avoidance learning

Learning to avoid harmful consequences can be a costly trial-and-error process. In such situations, social information can be leveraged to improve individual learning outcomes. Here, we investigated how participants used their own experiences and others' social cues to avoid harm. Participants made repeated choices between harmful and safe options, each with different probabilities of generating shocks, while also seeing the image of a social partner. Some partners made predictive gaze cues towards the harmful choice option while others cued an option at random, and did so using neutral or fearful facial expressions. We tested how learned social information about partner reliability transferred across contexts by letting participants encounter the same partner in multiple trial blocks while facing novel choice options. Participants' decisions were best explained by a reinforcement learning model that independently learned the probabilities of options being safe and of partners being reliable and combined these combined these estimates to generate choices. Advice from partners making a fearful facial expression influenced participants' decisions more than advice from partners with neutral expressions. Our results showed that participants made better decisions when facing predictive partners and that they cached and transferred partner reliability estimates into new blocks. Using simulations we show that participants' transfer of social information into novel contexts is better adapted to variable social environments where social partners may change their cuing strategy or become untrustworthy. Finally, we found no relation between autism questionnaire scores and performance in our task, but do find autism trait related differences in learning rate parameters.

The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes

BACKGROUND

A major research finding in the field of Biological Psychiatry is that symptom-based categories of mental disorders map poorly onto dysfunctions in brain circuits or neurobiological pathways. Many of the identified (neuro) biological dysfunctions are "transdiagnostic", meaning that they do not reflect diagnostic boundaries but are shared by different ICD/DSM diagnoses. The compromised biological validity of the current classification system for mental disorders impedes rather than supports the development of treatments that not only target symptoms but also the underlying pathophysiological mechanisms. The Biological Classification of Mental Disorders (BeCOME) study aims to identify biology-based classes of mental disorders that improve the translation of novel biomedical findings into tailored clinical applications.

METHODS

BeCOME intends to include at least 1000 individuals with a broad spectrum of affective, anxiety and stress-related mental disorders as well as 500 individuals unaffected by mental disorders. After a screening visit, all participants undergo in-depth phenotyping procedures and omics assessments on two consecutive days. Several validated paradigms (e.g., fear conditioning, reward anticipation, imaging stress test, social reward learning task) are applied to stimulate a response in a basic system of human functioning (e.g., acute threat response, reward processing, stress response or social reward learning) that plays a key role in the development of affective, anxiety and stress-related mental disorders. The response to this stimulation is then read out across multiple levels. Assessments comprise genetic, molecular, cellular, physiological, neuroimaging, neurocognitive, psychophysiological and psychometric measurements. The multilevel information collected in BeCOME will be used to identify data-driven biologically-informed categories of mental disorders using cluster analytical techniques.

DISCUSSION

The novelty of BeCOME lies in the dynamic in-depth phenotyping and omics characterization of individuals with mental disorders from the depression and anxiety spectrum of varying severity. We believe that such biology-based subclasses of mental disorders will serve as better treatment targets than purely symptom-based disease entities, and help in tailoring the right treatment to the individual patient suffering from a mental disorder. BeCOME has the potential to contribute to a novel taxonomy of mental disorders that integrates the underlying pathomechanisms into diagnoses.

TRIAL REGISTRATION

Retrospectively registered on June 12, 2019 on ClinicalTrials.gov (TRN: NCT03984084).