What Is Social about Autism? The Role of Allostasis-Driven Learning

The association between early regulatory problems and adult peer relationship quality is mediated by the brain's allostatic-interoceptive system

BACKGROUND

Early regulatory problems (RPs), i.e., problems with crying, sleeping, and/or feeding during the first years, increase the risk for avoidant personality traits in adulthood, associated with social withdrawal and anxiety. Even more, RPs are linked with functional alterations in the adult default mode and salience networks, comprising the brain's allostatic-interoceptive system (AIS) and playing a role in social interactions. We investigated whether RPs assessed in infancy are associated with difficulties in adult peer relationships mediated by functional alterations of the AIS.

METHODS

As part of a large case-controlled prospective study, 42 adults with previous RPs and 70 matched controls (mean age = 28.48, SD = 2.65, 51% male) underwent fMRI during rest. The analysis focused on the intrinsic functional connectivity (iFC) of key nodes of the AIS. Peer relationship quality was assessed via a semi-structured Life Course Interview and the YASR scale. In these same individuals, RPs were assessed at ages 5, 20 and 56 months.

RESULTS

RPs in infancy were associated with lower-quality peer relationships and enhanced functional connectivity of the AIS nodes in adulthood, with a stronger effect for multiple and persistent RPs compared with transient-multiple or single-persistent RPs. Importantly, iFC changes of the dorsal mid insula, a primary interoceptive cortex with frontal and temporal regions, mediated the relationship between early RPs and adult peer relationship quality.

CONCLUSIONS

Results indicate long-lasting social and neural changes associated with early RPs. Our findings further implicate the AIS in both interoceptive and social processes, while indicating the need for early screening of early RPs.

Understanding early maladaptive schemas in autistic and ADHD individuals: exploring the impact, changing the narrative, and schema therapy considerations

Autistic/ADHD individuals are increasingly recognised as a valid minority group, with consistent research demonstrating a higher prevalence of co-occurring mental health conditions such as PTSD, anxiety, depression, substance use, and eating disorders among other mental health challenges. Due to this, there is increasing focus on the adaptations required for Autistic and ADHD individuals of current therapeutic approaches such as Schema Therapy. Particular emphasis when creating these adaptations needs to include looking at the developmental experiences, social influences, and continued adversity faced by Autistic and ADHD individuals across the lifespan, and how the narrative around Autism and ADHD within psychotherapy in general needs to change. This paper critically examines the role of attachment, unmet needs, and adverse childhood experiences in Autistic and ADHD individuals and the subsequent impact on schema development and maintenance and mental health. This will include an overview of the current literature in this area, reconsideration of understandings of Autism and ADHD, particular therapeutic considerations and adjustments and importantly discussion around the wider societal changes that need to occur to prevent schema development and reinforcement across the lifespan.

Predictive coding for the actions and emotions of others and its deficits in autism spectrum disorders

Traditionally, the neural basis of social perception has been studied by showing participants brief examples of the actions or emotions of others presented in randomized order to prevent participants from anticipating what others do and feel. This approach is optimal to isolate the importance of information flow from lower to higher cortical areas. The degree to which feedback connections and Bayesian hierarchical predictive coding contribute to how mammals process more complex social stimuli has been less explored, and will be the focus of this review. We illustrate paradigms that start to capture how participants predict the actions and emotions of others under more ecological conditions, and discuss the brain activity measurement methods suitable to reveal the importance of feedback connections in these predictions. Together, these efforts draw a richer picture of social cognition in which predictive coding and feedback connections play significant roles. We further discuss how the notion of predicting coding is influencing how we think of autism spectrum disorder.

Diagnosis of Autism in Children Based on their Gait Pattern and Movement Signs Using the Kinect Sensor

Background

Autism spectrum disorders are a type of developmental disorder that primarily disrupt social interactions and communications. Autism has no treatment, but early diagnosis of it is crucial to reduce these effects. The incidence of autism is represented in repetitive patterns of children's motion. When walking, these children tighten their muscles and cannot control and maintain their body position. Autism is not only a mental health disorder but also a movement disorder.

Method

This study aims to identify autistic children based on data recorded from their gait patterns using a Kinect sensor. The database used in this study comprises walking information, such as joint positions and angles between joints, of 50 autistic and 50 healthy children. Two groups of features were extracted from the Kinect data in this study. The first one was statistical features of joints' position and angles between joints. The second group was the features based on medical knowledge about autistic children's behaviors. Then, extracted features were evaluated through statistical tests, and optimal features were selected. Finally, these selected features were classified by naïve Bayes, support vector machine, k-nearest neighbors, and ensemble classifier.

Results

The highest classification accuracy for medical knowledge-based features was 87% with 86% sensitivity and 88% specificity using an ensemble classifier; for statistical features, 84% of accuracy was obtained with 86% sensitivity and 82% specificity using naïve Bayes.

Conclusion

The dimension of the resulted feature vector based on autistic children's medical knowledge was 16, with an accuracy of 87%, showing the superiority of these features compared to 42 statistical features.

Social and nonsocial synchrony are interrelated and romantically attractive

The mechanisms of romantic bonding in humans are largely unknown. Recent research suggests that physiological synchrony between partners is associated with bonding. This study combines an experimental approach with a naturalistic dating setup to test whether the individual differences in social and nonsocial synchrony are interdependent, and linked to romantic attractiveness. In a preregistered online experiment with 144 participants, we discover that inducing physiological synchrony between an actor and an actress determines their attractiveness ratings by participants, indicating that synchrony can increase perceived attraction. In a lab-based naturalistic speed-dating experiment, we quantify in 48 participants the individual tendency for social physiological synchrony, nonsocial sensorimotor synchrony, and romantic attractiveness. We discover that the individual propensity to synchronize in social and nonsocial tasks is correlated. Some individuals synchronize better regardless of partners or tasks, and such Super Synchronizers are rated as more attractive. Altogether, this demonstrates that humans prefer romantic partners who can synchronize.

The Human Affectome

Over the last decades, theoretical perspectives in the interdisciplinary field of the affective sciences have proliferated rather than converged due to differing assumptions about what human affective phenomena are and how they work. These metaphysical and mechanistic assumptions, shaped by academic context and values, have dictated affective constructs and operationalizations. However, an assumption about the purpose of affective phenomena can guide us to a common set of metaphysical and mechanistic assumptions. In this capstone paper, we home in on a nested teleological principle for human affective phenomena in order to synthesize metaphysical and mechanistic assumptions. Under this framework, human affective phenomena can collectively be considered algorithms that either adjust based on the human comfort zone (affective concerns) or monitor those adaptive processes (affective features). This teleologically-grounded framework offers a principled agenda and launchpad for both organizing existing perspectives and generating new ones. Ultimately, we hope the Human Affectome brings us a step closer to not only an integrated understanding of human affective phenomena, but an integrated field for affective research.

Disgust Processing and Potential Relationships with Behaviors in Autism

PURPOSE OF REVIEW

While there are reports of differences in emotion processing in autism, it is less understood whether the emotion of disgust, in particular, plays a significant role in these effects. Here, we review literature on potential disgust processing differences in autism and its possible associations with autistic traits.

RECENT FINDINGS

In autism, there is evidence for differences in physical disgust processing, pica behaviors, attention away from other's disgust facial expressions, and differences in neural activity related to disgust processing. In typically developing individuals, disgust processing is related to moral processing, but modulated by individual differences in interoception and alexithymia. Autistic individuals may experience atypical disgust, which may lead to difficulty avoiding contaminants and affect socio-emotional processing. In autism, such outcomes may lead to increased occurrences of illness, contribute to gastrointestinal issues, diminish vicarious learning of disgust expression and behaviors, and potentially contribute to differences in processes related to moral reasoning, though further research is needed.

The impact of sociality and affective valence on brain activation: A meta-analysis

Thirty years of neuroimaging reveal the set of brain regions consistently associated with pleasant and unpleasant affect in humans-or the neural reference space for valence. Yet some of humans' most potent affective states occur in the context of other humans. Prior work has yet to differentiate how the neural reference space for valence varies as a product of the sociality of affective stimuli. To address this question, we meta-analyzed across 614 social and non-social affective neuroimaging contrasts, summarizing the brain regions that are consistently activated for social and non-social affective information. We demonstrate that across the literature, social and non-social affective stimuli yield overlapping activations within regions associated with visceromotor control, including the amygdala, hypothalamus, anterior cingulate cortex and insula. However, we find that social processing differs from non-social affective processing in that it involves additional cortical activations in the medial prefrontal and posterior cingulum that have been associated with mentalizing and prediction. A Bayesian classifier was able to differentiate unpleasant from pleasant affect, but not social from non-social affective states. Moreover, it was not able to classify unpleasantness from pleasantness at the highest levels of sociality. These findings suggest that highly social scenarios may be equally salient to humans, regardless of their valence.

Cognitive and Behavioral Patterns across Psychiatric Conditions

Psychiatric conditions represent a highly heterogeneous group of disorders associated with chronic distress and a sharp decline in quality of life [...].