Lab

Social Neuroscience Lab

Featured projects (1)

Project
The main goal of the project is to investigate differences between individuals with autism spectrum disorders and typically developing individuals in neural and behavioural mechanisms linked to basic and complex social cognition.

Featured research (10)

While considerable emphasis has been put on investigating the mechanisms that drive reduced social connection in patients with schizophrenia (SCZ), recent studies have increasingly focused on the issue of loneliness in SCZ. Both social cognitive bias and self-reported empathy predict loneliness in non-clinical populations, the current study, therefore, aims to examine the relationship between loneliness, reduced social connection and social cognitive biases, and self-reported empathy in SCZ. Ninety-three adult SCZ and sixty-six matched healthy individuals completed a battery of questionnaires measuring loneliness and social connection (Revised-UCLA Loneliness scale, Lubben Social Network Scale, Social Disconnectedness Scale), cognitive biases (Ambiguous Intentions Hostility Questionnaire (AIHQ); Davos Assessment of Cognitive Biases Scale (DACOBS), Cognitive Biases Questionnaire for psychosis, CBQp) and self-reported empathy (Interpersonal Reactivity Index, IRI). Significant predictors of loneliness in SCZ were entered into two latent variables (“Social Threat Bias”, “Social Connection”), and structural equation modeling was used to explore the direct and indirect relationships between Social Threat Bias and loneliness in SCZ. Patients reported higher levels of loneliness, cognitive biases, and personal distress compared to controls. Furthermore, SCZ reported less social connection and perspective-taking compared to controls. AIHQ Blame Score, CBQp Threatening Events, DACOBS, and IRI Personal Distress were significantly associated with loneliness in SCZ. SEM modeling revealed that Social Threat Bias was linked to increased loneliness in SCZ both directly and indirectly via a decreased social connection. The results of the current study suggest that social threat bias should be considered while planning the interventions aimed to reduce loneliness in schizophrenia.
Background Loneliness is a concern for patients with schizophrenia (SCZ). However, the correlates of loneliness in SCZ are unclear; thus, the aim of the study is to investigate neuro- and social cognitive (SC) mechanisms associated with loneliness in SCZ. Methods Data for the study were pooled from two cross-national samples (Poland/USA) and included 147 SCZ and 103 healthy controls (HC) overall. Data from clinical, neurocognitive, and SC assessments were examined as potential predictors of loneliness in HC and SCZ samples pooled across two sites. Furthermore, Latent Class Analysis (LCA) was used to cluster patients based on SC capacity. Next, the relationship between SC and loneliness was explored in each cluster of SCZ. Results SCZ reported higher levels of loneliness than HC. Loneliness was linked to increased negative and affective symptoms in patients. A negative association between loneliness and mentalizing and emotion recognition abilities was found in the patients with social-cognitive impairments, but not in those who performed at normative levels. Conclusions We have elucidated a novel mechanism which may explain previous inconsistent findings regarding the correlates of loneliness in SCZ. As decreased SC capacity may be linked with loneliness only in patients with observable SC impairments, SC heterogeneity in SCZ needs to be recognized while planning psychosocial interventions targeting loneliness in this group.
Ta książka jest próbą dyskusji na temat wybranych aspektów problematyki zdrowia psychicznego w kontekście obserwowanych zmian zachodzących we współczesnym świecie. Autorzy wskazali, w jaki sposób takie procesy jak rozluźnienie więzi społecznych, wzrost poczucia osamotnienia, stopniowe zwiększanie się wpływu technologii na nasze codzienne funkcjonowanie, przyczyniają się do zmian w rozumieniu wybranych zaburzeń psychicznych oraz w jaki sposób mogą one zwiększać prawdopodobieństwo rozwoju niektórych z nich. W poszczególnych rozdziałach zostały omówione zagadnienia, mogące być dobrym tłem do szerszej dyskusji związków zmian zachodzących w świecie z zaburzeniami psychicznymi.
Computational linguistics has enabled the introduction of objective tools that measure some of the symptoms of schizophrenia, including the coherence of speech associated with formal thought disorder (FTD). Our goal was to investigate whether neural network based utterance embeddings are more accurate in detecting FTD than models based on individual indicators. The present research used a comprehensive Embeddings from Language Models (ELMo) approach to represent interviews with patients suffering from schizophrenia (N=35) and with healthy people (N=35). We compared its results to the approach described by Bedi et al. (2015), referred to here as the coherence model. Evaluations were also performed by a clinician using the Scale for the Assessment of Thought, Language and Communication (TLC). Using all six TLC questions the ELMo obtained an accuracy of 80% in distinguishing patients from healthy people. Previously used coherence models were less accurate at 70%. The classifying clinician was accurate 74% of the time. Our analysis shows that both ELMo and TLC are sensitive to the symptoms of disorganization in patients. In this study methods using text representations from language models were more accurate than those based solely on the assessment of FTD, and can be used as measures of disordered language that complement human clinical ratings.
Introduction Both objective social isolation (OSI) and subjective feelings of loneliness (perceived social isolation; PSI) are linked to cognitive problems in the general community. However, examination of the relationship between social cognitive capacity and social functioning in adults has mostly been limited to clinical samples. Thus, the aim of the current study is to examine the pathways linking social cognitive capacity, OSI and PSI in young and middle-aged adults. Methods Two-hundred fifty-two healthy individuals aged 18–50 completed a battery of social cognitive tasks, as well as self-report questionnaires measuring OSI and PSI. Results Worse lower-level processing of social cues predicted higher level of OSI, but not PSI. More pronounced hostile attribution bias predicted higher levels of both OSI and PSI. Conclusion Results of the current study suggest that objective social cognitive capacity may predict objective but not perceived levels of social functioning. At the same time, social cognitive biases may affect both objective and perceived social isolation in healthy individuals.

Lab head

Łukasz Okruszek
Department
  • Institute of Psychology
About Łukasz Okruszek
  • Łukasz Okruszek currently works at the Institute of Psychology , Polish Academy of Sciences.

Members (7)

Aleksandra Piejka
  • Polish Academy of Sciences
Anna Schudy
  • University of Warsaw
Marcelina Wiśniewska
  • Polish Academy of Sciences
Marta Chrustowicz
  • Institude of Psychology Polish Academy of Sciences
Karolina Żurek
  • Polish Academy of Sciences
Małgorzata Krawczyk
  • Polish Academy of Sciences
Monika Malon
  • Polish Academy of Sciences