Social Cognition Research Articles

Understanding Voice Shopping Value Co-Creation: A Sem-Fsqca Method

ABSTRACT Despite a large number of retailers have embraced the voice shopping channels, the factors that determine consumers' voice shopping value co-creation intentions are still unclear. This study explores the impacts of two social cognition dimensions (competence and warmth) on voice shopping value co-creation intention from the perspectives of confidence in consumers themselves and in AI. Based on the social exchange theory and stimulus—organism—response, a research model was developed and empirically examined by data collected from 363 students at a university in China. The results of structural equation modeling (SEM) analysis indicate that perceived competence and perceived warmth positively affect confidence in consumers themselves and in AI and consequently determine voice shopping value co-creation intention. In addition, the impacts of confidence in consumers themselves and in AI on voice shopping value co-creation intention varies. The results of the fuzzy set qualitative comparative analysis (fsQCA) method further validate these findings.

Longitudinal inference of multiscale markers in psychosis: from hippocampal centrality to functional outcome.

Multiscale neuroscience conceptualizes mental illness as arising from aberrant interactions across and within multiple biopsychosocial scales. We leverage this framework to propose a multiscale disease progression model of psychosis, in which hippocampal-cortical dysconnectivity precedes impairments in episodic memory and social cognition, which lead to more severe negative symptoms and lower functional outcome. As psychosis represents a heterogeneous collection of biological and behavioral alterations that evolve over time, we further predict this disease progression for a subtype of the patient sample, with other patients showing normal-range performance on all variables. We sampled data from two cross-sectional datasets of first- and multi-episode psychosis, resulting in a sample of 163 patients and 119 non-clinical controls. To address our proposed disease progression model and evaluate potential heterogeneity, we applied a machine-learning algorithm, SuStaIn, to the patient data. SuStaIn uniquely integrates clustering and disease progression modeling and identified three patient subtypes. Subtype 0 showed normal-range performance on all variables. In comparison, Subtype 1 showed lower episodic memory, social cognition, functional outcome, and higher negative symptoms, while Subtype 2 showed lower hippocampal-cortical connectivity and episodic memory. Subtype 1 deteriorated from episodic memory to social cognition, negative symptoms, functional outcome to bilateral hippocampal-cortical dysconnectivity, while Subtype 2 deteriorated from bilateral hippocampal-cortical dysconnectivity to episodic memory and social cognition, functional outcome to negative symptoms. This first application of SuStaIn in a multiscale psychiatric model provides distinct disease trajectories of hippocampal-cortical connectivity, which might underlie the heterogeneous behavioral manifestations of psychosis.

Социально-психологические предикторы воспринимаемого возраста как прогностического маркера старения и риска смерти

<p style="text-align: justify;"><strong>Objective. </strong>The study of socio-psychological predictors of the perceived age of adults aged 35 to 75 years.<br><strong>Background. </strong>The relevance of the work is determined by the interdisciplinary status of the phenomenon of perceived age (the phenomenon of social cognition and the result of the influence of numerous factors associated with predicting the risk of death) in modern science and the need to determine the influence of socio-psychological factors on the perceived age of a person at the stage of "maturity" and "old age". <br><strong>Study design. </strong>Photographs of perceptual objects previously tested using a block of techniques were shown to perceptual subjects ("evaluators") to assess their age, the arithmetic mean of the estimates corresponded to the perceived age of the study participants. Next, a list of possible predictors was compiled, to which multiple regression analysis (step-by-step method) was applied. <br><strong>Participants. </strong>523 people (207 men and 316 women) aged 35 to 75 years took part in the study as objects of perception; 140 people acted as subjects of perception ("evaluators") in various rounds of presenting photographs to assess the age of objects of perception. The sample was divided into subgroups of "mature" (age 35-59 years, 368 people, 142 men and 226 women, M = 49 years) and "elderly" (age 60-75 years, 155 people, 65 men and 90 women, M = 65 years). <br><strong>Measurements. </strong>The procedure of "Photovideopresentation of appearance" by T.A. Vorontsova; the questionnaire "Self-assessment of age" by T.A. Vorontsova; a set of techniques developed by V.A. Labunskaya for the diagnosis of attitude to one's appearance. <br><strong>Results. </strong>The paper identifies socio-psychological predictors of a person's perceived age at the age stages of "maturity" and "old age": subjective age, the importance of appearance, integral assessment of appearance, assessment of appearance by the mother, the need to look younger than their years, economic status. Regression models were compiled separately on male/female subsamples, as well as adults aged 35-59 and 60-75 years. It was found that the regression model built on the data of elderly study participants (from 60 to 75 years old), which included a combination of predictors "significance of appearance", "satisfaction with appearance" and "planned life expectancy", has the greatest predictive value. It is also shown that the behavioral component of the attitude to one's appearance (the severity of appearance-perfectionism) does not affect the indicator of the difference between chronological and perceived age ("saved years").<br><strong>Conclusions. </strong>The combination of socio-psychological predictors of perceived age varies depending on gender and age stage of life. Universal and gender-specific predictors of perceived age have been identified. The universal predictor, regardless of gender and age stage of life, is the importance of appearance.</p>

The expression of empathy in human's closest relatives, bonobos and chimpanzees: current and future directions.

Empathy is a complex, multi-dimensional capacity that facilitates the sharing and understanding of others' emotions. As our closest living relatives, bonobos (Pan paniscus) and chimpanzees (P. troglodytes) provide an opportunity to explore the origins of hominin social cognition, including empathy. Despite certain assumptions that bonobos and chimpanzees may differ empathically, these species appear to overlap considerably in certain socio-emotional responses related to empathy. However, few studies have systematically tested for species variation in Pan empathic or socio-emotional tendencies. To address this, we synthesise the growing literature on Pan empathy to inform our understanding of the selection pressures that may underlie the evolution of hominin empathy, and its expression in our last common ancestor. As bonobos and chimpanzees show overlaps in their expression of complex socio-emotional phenomena such as empathy, we propose that group comparisons may be as or more meaningful than species comparisons when it comes to understanding the evolutionary pressures for such behaviour. Furthermore, key differences, such as how humans and Pan communicate, appear to distinguish how we experience empathy compared to our closest living relatives.

Disentangling the Relationship Between Social Cognition, Executive Functions, and Behaviour Changes in Amyotrophic Lateral Sclerosis (S18.009)

Disentangling the Relationship Between Social Cognition, Executive Functions, and Behaviour Changes in Amyotrophic Lateral Sclerosis (S18.009)

Psychology-Guided Environment Aware Network for Discovering Social Interaction Groups from Videos

Social interaction is a common phenomenon in human societies. Different from discovering groups based on the similarity of individuals’ actions, social interaction focuses more on the mutual influence between people. Although people can easily judge whether or not there are social interactions in a real-world scene, it is difficult for an intelligent system to discover social interactions. Initiating and concluding social interactions are greatly influenced by an individual’s social cognition and the surrounding environment, which are closely related to psychology. Thus, converting the psychological factors that impact social interactions into quantifiable visual representations and creating a model for interaction relationships poses a significant challenge. To this end, we propose a Psychology-Guided Environment Aware Network (PEAN) that models social interaction among people in videos using supervised learning. Specifically, we divide the surrounding environment into scene-aware visual-based and human-aware visual-based descriptions. For the scene-aware visual clue, we utilize 3D features as global visual representations. For the human-aware visual clue, we consider instance-based location and behaviour-related visual representations to map human-centered interaction elements in social psychology: distance, openness and orientation. In addition, we design an environment aware mechanism to integrate features from visual clues, with a Transformer to explore the relation between individuals and construct pairwise interaction strength features. The interaction intensity matrix reflecting the mutual nature of the interaction is obtained by processing the interaction strength features with the interaction discovery module. An interaction constrained loss function composed of interaction critical loss function and smooth F β loss function is proposed to optimize the whole framework to improve the distinction of the interaction matrix and alleviate class imbalance caused by pairwise interaction sparsity. Given the diversity of real-world interactions, we collect a new dataset named Social Basketball Activity Dataset (Soical-BAD), covering complex social interactions. Our method achieves the best performance among social-CAD, social-BAD, and their combined dataset named Video Social Interaction Dataset (VSID).

Dysconnectivity of the Nucleus Accumbens and Amygdala in Youths with Thought Problems: A Dimensional Approach.

Background: Youths with thought problems (TP) are at risk to develop psychosis and obsessive-compulsive disorder (OCD). Yet, the pathophysiological mechanisms underpinning TP are still unclear. Functional magnetic resonance imaging (fMRI) studies have shown that striatal and limbic alterations are associated with psychosis-like and obsessive-like symptoms in individuals at clinical risk for psychosis, schizophrenia, and OCD. More specifically, nucleus accumbens (NAcc) and amygdala are mainly involved in these associations. The current study aims to investigate the neural correlates of TP in youth populations using a dimensional approach and explore potential cognitive functions and neurotransmitters associated with it. Methods: Seed-to-voxels functional connectivity analyses using NAcc and amygdala as regions-of-interest were conducted with resting-state fMRI data obtained from 1360 young individuals, and potential confounders related to TP such as anxiety and cognitive functions were included as covariates in multiple regression analyses. Replicability was tested in using an adult cohort. In addition, functional decoding and neurochemical correlation analyses were performed to identify the associated cognitive functions and neurotransmitters. Results: The altered functional connectivities between the right NAcc and posterior parahippocampal gyrus, between the right amygdala and lateral prefrontal cortex, and between the left amygdala and the secondary visual area were the best predictors of TP in multiple regression model. These functional connections are mainly involved in social cognition and reward processing. Conclusions: The results show that alterations in the functional connectivity of the NAcc and the amygdala in neural pathways involved in social cognition and reward processing are associated with severity of TP in youths.

Dorso-medial prefrontal cortex responses to social smiles predict sociability in early human development

Abstract Dorso-medial prefrontal cortex (dmPFC) plays a vital role in social cognition and behavior among humans. Enhanced responses in dmPFC when viewing social scenes predict increased levels of sociability in adults. The current longitudinal study examined the association between dmPFC response and sociability in early development. Brain responses were measured in response to social smiles and frowns using functional near-infrared spectroscopy (fNIRS) at 11 months. Individual differences in sociability were measured using the Early Childhood Behavior Questionnaire (ECBQ) at 18 months. Our longitudinal results show that greater engagement of the dmPFC when processing social smiles, but not frowns, at 11 months predicts higher levels of sociability at 18 months. This demonstrates that early variability in dmPFC response during positive social interactions is linked to individual differences in overtly displayed social behavior. This supports the view that dmPFC plays an important role in social cognition and behavior from early in human ontogeny.

Prebiotic diet normalizes aberrant immune and behavioral phenotypes in a mouse model of autism spectrum disorder.

Autism spectrum disorder (ASD) is a cluster of neurodevelopmental disorders characterized by deficits in communication and behavior. Increasing evidence suggests that the microbiota-gut-brain axis and the likely related immune imbalance may play a role in the development of this disorder. Gastrointestinal deficits and gut microbiota dysfunction have been linked to the development or severity of autistic behavior. Therefore, treatments that focus on specific diets may improve gastrointestinal function and aberrant behavior in individuals with ASD. In this study, we investigated whether a diet containing specific prebiotic fibers, namely, 3% galacto-oligosaccharide/fructo-oligosaccharide (GOS/FOS; 9:1), can mitigate the adverse effects of in utero exposure to valproic acid (VPA) in mice. Pregnant BALB/cByJ dams were injected with VPA (600 mg/kg, sc.) or phosphate-buffered saline (PBS) on gestational day 11 (G11). Male offspring were divided into four groups: (1) in utero PBS-exposed with a control diet, (2) in utero PBS-exposed with GOS/FOS diet, (3) in utero VPA-exposed with a control diet, and (4) in utero VPA-exposed with GOS/FOS diet. Dietary intervention started from birth and continued throughout the duration of the experiment. We showed that the prebiotic diet normalized VPA-induced alterations in male offspring, including restoration of key microbial taxa, intestinal permeability, peripheral immune homeostasis, reduction of neuroinflammation in the cerebellum, and impairments in social behavior and cognition in mice. Overall, our research provides valuable insights into the gut-brain axis involvement in ASD development. In addition, dietary interventions might correct the disbalance in gut microbiota and immune responses and, ultimately, might improve detrimental behavioral outcomes in ASD.

Almost Faces? ;-) Emoticons and Emojis as Cultural Artifacts for Social Cognition Online

AbstractEmoticons and facial emojis are ubiquitous in contemporary digital communication, where it has been proposed that they make up for the lack of social information from real faces. In this paper, I construe them as cultural artifacts that exploit the neurocognitive mechanisms for face perception. Building on a step-by-step comparison of psychological evidence on the perception of faces vis-à-vis the perception of emoticons/emojis, I assess to what extent they do effectively vicariate real faces with respect to the following four domains: (1) the expression of emotions, (2) the cultural norms for expressing emotions, (3) conveying non-affective social information, and (4) attention prioritization.

“Do You Know Where the Dragons Are?” - Introducing a Novel Enactive Framework to Map the Wide Unknown of Social Spaces With Neurodivergent Young People

Experiences of being are fundamentally different for neurodivergent young people. Differences in brain connectivity and function conferred by neurodivergence give rise to differences in construal processes underlying intersubjective engagement and shared meaning. Normative therapeutic and educational interventions refer to ‘social communication disorders’, ‘cognitive inflexibility’ and ‘social anxiety’. Peers call them ‘weird’. Parents struggle with guilt, exasperation and despair. The world demands social conformity. “Toby” (11yrs) requested a map and sword to slay the fearsome dragons lurking in the unknown spaces between himself and others- between here and there; intention and action; words and meaning; friend and foe. This paper describes a contextualizing model in a novel systematized approach to meeting the social engagement challenges of neurodivergent young people, devised in collaboration with those young people as Experts by Experience. The approach was formulated on the principle that social competence in neurodivergence should be shaped around self- discovery of authentic modes of being and relating, rather than imposed normative criteria. The 12 Social Spaces model integrates theoretical and clinical principles of Personal Construct Psychology, Enactivism, play theory, neurocognition and social competence, to provide a contextualizing framework of twelve interactional spaces to scaffold social cognition during evolving play between neurodivergent young people.

Liver kinase B-1 modulates the activity of dopamine neurons in the ventral tegmental area and regulates social memory formation

Social memory is the ability to discriminate between familiar and unknown conspecifics. It is an important component of social cognition and is therefore essential for the establishment of social relationships. Although the neural circuit mechanisms underlying social memory encoding have been well investigated, little focus has been placed on the regulatory mechanisms of social memory processing. The dopaminergic system, originating from the midbrain ventral tegmental area (VTA), is a key modulator of cognitive function. This study aimed to illustrate its role in modulating social memory and explore the possible molecular mechanisms. Here, we show that the activation of VTA dopamine (DA) neurons is required for the formation, but not the retrieval, of social memory. Inhibition of VTA DA neurons before social interaction, but not 24 h after social interaction, significantly impaired social discrimination the following day. In addition, we showed that the activation of VTA DA neurons was regulated by the serine/threonine protein kinase liver kinase B1 (Lkb1). Deletion of Lkb1 in VTA DA neurons reduced the frequency of burst firing of dopaminergic neurons. Furthermore, Lkb1 plays an important role in regulating social behaviors. Both genetic and virus-mediated deletions of Lkb1 in the VTA of adult mice impaired social memory and subsequently attenuated social familiarization. Altogether, our results provide direct evidence linking social memory formation to the activation of VTA DA neurons in mice and illustrate the crucial role of Lkb1 in regulating VTA DA neuron function.

The Correction Strategy of Artificial Intelligence Embedding into the Negative Social Mentality of the Marginal Group of College Students in the New Era

Artificial intelligence is a rapidly developing technology that is gradually changing the pace of modern people's lives and ways of working. As AI enters the field of higher education, it is generating increasingly significant functions and effects. Artificial intelligence is having a certain impact on the growth of college students, and as a marginalized group of college students in the new era, it also presents unique social attitudes and patterns. Strengthening the correction of negative social attitudes towards marginalized groups of college students is of great practical significance for promoting social progress and development. This article takes the marginalized group of college students in a certain university in China as the research basis and concludes that: 1.there are significant differences in the scores of social emotions among marginalized groups of college students of different genders; 2.There are significant differences in the scores of social needs, social cognition, and social emotions among marginalized groups of college students from different disciplines; 3.There are significant differences in the scores of social needs, social cognition, social emotions, social values, and social behavioral tendencies among marginalized groups of college students of different grades. Research has found that artificial intelligence can have a positive impact on academic achievement, career planning, social responsibility, and creativity of marginalized groups of college students. It is suggested that universities should take artificial intelligence as their starting point and think from four dimensions: family factors, school factors, social factors, and personal factors, striving to guide marginalized groups of college students to establish a healthy and positive social mentality

How language affects social cognition and emotional competence in typical and atypical development: A systematic review.

The ability to understand the mental state of others (social cognition), as well as language, is crucial for children to have good social adaptation. Social cognition (SC) has been shown to be a hierarchical model of three factors (Cognitive, intermediate and affective SC) interrelated with linguistic processes. Children on the autism spectrum and children with developmental language disorder (DLD) or social communication disorder (SCD) manifest language and SC difficulties, albeit in different ways. This systematic review aims to find how language and SC interact with each other and identify linguistic and socio-affective profiles in the target population. About 1593 articles were systematically reviewed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guide in November 2022, obtaining, through inclusion/exclusion criteria, a total of 38 articles for qualitative assessment. The majority of them were on autism (26) or DLD (14) and to a lesser extent SCD (3). Although SC is related to all components of language, SC is strongly related to narrative and morphosyntax and partially related to lexicon. Pragmatics shows a complex relation with SC due to greater sensitivity to other factors such as age or task, and prosody appears to be more related to emotional processes. Besides, autistic, SCD and DLD children showed differences in their language and socio-affective performance. Mainstream DLD children have lower performance in general language, where autistic and SCD children have more linguistic variation and are lower in pragmatic and SC tasks, SCD children being more associated with language production difficulties and autistic children with both receptive and productive language. Each language component has a different interaction with SC. Likewise, different linguistic profiles are partially found for each disorder. These results are important for future lines of research focusing on specific components of interaction and socio-emotional processes, as well as for clinical and educational treatment. What is already known on the subject The hierarchical model of Schurz etal. (2021), divide social cognition into three brain constructs: cognitive social cognition (CSC), affective social cognition (ASC) and intermediate social cognition (ISC). They observe a large relationship between language and ISC, a fact that has been corroborated with some other studies. Studies have also found lower linguistic and socio-affective abilities in children with autism and language and communication disorders compared with children with neurotypical development, and large behavioural and neurocognitive overlaps between these disorders (Durrleman etal., 2019; Löytömäki etal., 2019). What this paper adds to existing knowledge This is the first review that relates all linguistic components (narrative, lexicon, morphosyntax, pragmatic and prosody) with the three constructs of social cognition (Cognitive, intermediate and affective). Moreover, it is the first review that studies the socio-linguistic factors comparing autism, developmental language disorder and social communication disorder with each other and with neurotypical development in children aged from 4 to 9 years. What are the potential or actual clinical implications of this work? Understanding how language and social cognition interact with each other in autism spectrum disorder, developmental language disorder and social communication disorder allows us to trace socio-linguistic profiles for each of the studied disorders, understand better children with these difficulties, and, with this, find specific potential intervention points to improve and prevent these difficulties.

High Frequency of Cognitive and Behavioral Impairment in Amyotrophic Lateral Sclerosis Patients with SOD1 Pathogenic Variants.

While the cognitive-behavioral characteristics of amyotrophic lateral sclerosis (ALS) patients carrying C9orf72 pathological repeat expansion have been extensively studied, our understanding of those carrying SOD1 variants is mostly based on case reports. The aim of this paper is to extensively explore the cognitive-behavioral characteristics of a cohort of ALS patients carrying pathogenetic variants of SOD1 gene, comparing them to patients without pathogenetic variants of 46 ALS-related genes (wild-type [WT]-ALS) and healthy controls. All ALS patients seen at the Turin ALS expert center in the 2009-2021 period who underwent both cognitive/behavioral and extensive genetic testing were eligible to be included in the study. Only patients with SOD1 pathogenetic variants (n = 28) (SOD1-ALS) and WT-ALS (n = 829) were enrolled in the study. A series of 129 controls was also included. Among the 28 SOD1-ALS patients, 16 (57.1%) had normal cognitive function, 5 (17.9%) isolated cognitive impairment (ALSci) (17.9%), 6 (21.4%) isolated behavioral impairment (ALSbi), 1 (3.6%) cognitive and behavioral impairment (ALScbi), and no one ALS-FTD. SOD1-ALS performed worse than controls in all explored domains, in particular Social Cognition and Language domains. SOD1-ALS patients had similar scores in all tests compared to WT-ALS, except the Story-based Empathy Task (SET), where they performed worse. Cognitive-behavioral impairment is much more common in SOD1 patients than previously assumed. SOD1-ALS are characterized by a more frequent impairment of Social Cognition and, less markedly, of Language domains. These findings have relevant implication both in the clinical and in the research setting, also considering recently approved treatment for SOD1-ALS. ANN NEUROL 2024.

A Practical Guide to EEG Hyperscanning in Joint Action Research: From Motivation to Implementation.

Developments in cognitive neuroscience have led to the emergence of hyperscanning, the simultaneous measurement of brain activity from multiple people. Hyperscanning is useful for investigating social cognition, including joint action, because of its ability to capture neural processes that occur within and between people as they coordinate actions toward a shared goal. Here, we provide a practical guide for researchers considering using hyperscanning to study joint action and seeking to avoid frequently raised concerns from hyperscanning skeptics. We focus specifically on EEG hyperscanning, which is widely available and optimally suited for capturing fine-grained temporal dynamics of action coordination. Our guidelines cover questions that are likely to arise when planning a hyperscanning project, ranging from whether hyperscanning is appropriate for answering one's research questions to considerations for study design, dependent variable selection, data analysis, and visualization. By following clear guidelines that facilitate careful consideration of the theoretical implications of research design choices and other methodological decisions, joint action researchers can mitigate interpretability issues and maximize the benefits of hyperscanning paradigms.

Subregional thalamic functional connectivity abnormalities and cognitive impairments in first-episode schizophrenia

BackgroundPrevious studies have documented thalamic functional connectivity (FC) abnormalities in schizophrenia, typically examining the thalamus as a whole. The specific link between subregional thalamic FC and cognitive deficits in first-episode schizophrenia (FES) remains unexplored. MethodsUsing data from resting-state functional magnetic resonance imaging, we compared whole-brain FC with thalamic subregions between patients and HCs, and analyzed FC changes in drug-naïve patients separately. We then examined correlations between FC abnormalities with both cognitive impairment and clinical symptoms. ResultsA total of 33 FES patients (20 drug-naïve) and 32 age- and sex-matched healthy controls (HCs) were included. Compared to HCs, FES patients exhibited increased FC between specific thalamic subregions and cortical regions, particularly bilateral middle temporal lobe and cuneus gyrus, left medial superior frontal gyrus, and right inferior/superior occipital gyrus. Decreased FC was observed between certain thalamic subregions and the left inferior frontal triangle. These findings were largely consistent in drug-naïve patients. Notably, deficits in social cognition and visual learning in FES patients correlated with increased FC between certain thalamic subregions and cortical regions involving the right superior occipital gyrus and cuneus gyrus. The severity of negative symptoms was associated with increased FC between a thalamic subregion and the left middle temporal gyrus. ConclusionOur findings suggest FC abnormalities between thalamic subregions and cortical areas in FES patients. Increased FC correlated with cognitive deficits and negative symptoms, highlighting the importance of thalamo-cortical connectivity in the pathophysiology of schizophrenia.

Neurocognition and social cognition in youth and young adults at ultra-high-risk for psychosis and bipolar disorder

BackgroundSchizophrenia and bipolar disorder are associated with significant deficits in neurocognition and social cognition. Unlike the studies in chronic stages of these disorders, very limited information is available regarding neurocognitive and social-cognitive impairment before the onset of bipolar disorder. Our main aim was to investigate the differences in neurocognition and social cognition between individuals at ultra-high risk for psychosis (UHR-P) and bipolar disorder (UHR-BD). MethodsThis study included 152 help-seeking individuals identified as UHR-P (n = 78) and UHR-BD (n = 74), who were compared with a healthy control group (n = 43). A comprehensive neuropsychological battery was administered to all participants. ResultsUHR-P was associated with widespread deficits in all neurocognitive and social-cognitive domains. Effect sizes (Cohen's d) of these deficits ranged from −0.57 to −1.34. UHR-BD was associated with significant deficits in processing speed, executive functions, sustained attention and social cognition (d = −0.48 to-0.70, p < 0.05). UHR-P performed significantly worse than UHR-BD in social cognition, processing speed, verbal memory and executive function domains (d = −0.39 to-0.64, p < 0.05). Negative symptoms were associated with impaired social cognition in the UHR-P group and verbal memory deficits in the UHR-BD group. Cognitive impairment was associated with functional impairment in both groups. ConclusionsWhile UHR-P is associated with more widespread cognitive impairment, deficits in processing speed, executive functions, sustained attention and social cognition might be common features of both UHR groups. In early intervention services, cognition should be considered as a target for assessment and intervention not only for individuals at high risk for psychosis but also for bipolar disorder.

Early identification of autism spectrum disorder based on machine learning with eye-tracking data

BackgroundEarly identification of autism spectrum disorder (ASD) improves long-term outcomes, yet significant diagnostic delays persist. MethodsA retrospective cohort of 449 children (ASD: 246, typically developing [TD]: 203) was used for model development. Eye-movement data were collected from the participants watching videos that featured eye-tracking paradigms for assessing social and non-social cognition. Five machine learning algorithms, namely random forest, support vector machine, logistic regression, artificial neural network, and extreme gradient boosting, were trained to classify children with ASD and TD. The best-performing algorithm was selected to build the final model which was further evaluated in a prospective cohort of 80 children. The Shapley values interpreted important eye-tracking features. ResultsRandom forest outperformed other algorithms during model development and achieved an area under the curve of 0.849 (< 3 years: 0.832, ≥ 3 years: 0.868) on the external validation set. Of the ten most important eye-tracking features, three measured social cognition, and the rest were related to non-social cognition. A deterioration in model performance was observed using only the social or non-social cognition-related eye-tracking features. LimitationsThe sample size of this study, although larger than that of existing studies of ASD based on eye-tracking data, was still relatively small compared to the number of features. ConclusionsMachine learning models based on eye-tracking data have the potential to be cost- and time-efficient digital tools for the early identification of ASD. Eye-tracking phenotypes related to social and non-social cognition play an important role in distinguishing children with ASD from TD children.

Connectome-based prediction of decreased trust propensity in older adults with mild cognitive impairment: A resting-state functional magnetic resonance imaging study

Trust propensity (TP) relies more on social than economic rationality to transform the perceived probability of betrayal into positive reciprocity expectations in older adults with normal cognition. While deficits in social rationality have been observed in older adults with mild cognitive impairment (MCI), there is limited research on TP and its associated resting-state functional connectivity (RSFC) mechanisms in this population. To measure TP and related psychological functions (affect, motivation, executive cognition, and social cognition), MCI (n=42) and normal healthy control (NHC, n=115) groups completed a one-shot trust game and additional assessments of related psychological functions. RSFC associated with TP was analyzed using connectome-based predictive modeling (CPM) and lesion simulations. Our behavioral results showed that the MCI group trusted less (i.e., had lower TP) than the NHC group, with lower TP associated with higher sensitivity to the probability of betrayal in the MCI group. In the MCI group, only negative CPM models (RSFC negatively correlated with TP) significantly predicted TP, with a high salience network (SN) contribution. In contrast, in the NHC group, positive CPM models (RSFC positively correlated with TP) significantly predicted TP, with a high contribution from the default mode network (DMN). In addition, the total network strength of the NHC-specific positive network was lower in the MCI group than in the NHC group. Our findings demonstrated a decrease in TP in the MCI group compared to the NHC group, which is associated with deficits in social rationality (social cognition, associated with DMN) and increased sensitivity to betrayal (affect, associated with SN) in a trust dilemma. In conclusion, our study contributes to understanding MCI-related alterations in trust and their underlying neural mechanisms.