دورية أكاديمية
Predictive modeling of optimism bias using gray matter cortical thickness.
| العنوان: | Predictive modeling of optimism bias using gray matter cortical thickness. |
|---|---|
| المؤلفون: | Kotikalapudi, Raviteja, Moser, Dominik A, Dricu, Mihai, Spisak, Tamas, Aue, Tatjana |
| المصدر: | Kotikalapudi, Raviteja; Moser, Dominik A; Dricu, Mihai; Spisak, Tamas; Aue, Tatjana (2023). Predictive modeling of optimism bias using gray matter cortical thickness. Scientific reports, 13(1), p. 302. Springer Nature 10.1038/s41598-022-26550-y |
| بيانات النشر: | Springer Nature |
| سنة النشر: | 2023 |
| المجموعة: | BORIS (Bern Open Repository and Information System, University of Bern) |
| مصطلحات موضوعية: | 150 Psychology, 300 Social sciences, sociology & anthropology |
| الوصف: | People have been shown to be optimistically biased when their future outcome expectancies are assessed. In fact, we display optimism bias (OB) toward our own success when compared to a rival individual's (personal OB [POB]). Similarly, success expectancies for social groups we like reliably exceed those we mention for a rival group (social OB [SOB]). Recent findings suggest the existence of neural underpinnings for OB. Mostly using structural/functional MRI, these findings rely on voxel-based mass-univariate analyses. While these results remain associative in nature, an open question abides whether MRI information can accurately predict OB. In this study, we hence used predictive modelling to forecast the two OBs. The biases were quantified using a validated soccer paradigm, where personal (self versus rival) and social (in-group versus out-group) forms of OB were extracted at the participant level. Later, using gray matter cortical thickness, we predicted POB and SOB via machine-learning. Our model explained 17% variance (R2 = 0.17) in individual variability for POB (but not SOB). Key predictors involved the rostral-caudal anterior cingulate cortex, pars orbitalis and entorhinal cortex-areas that have been associated with OB before. We need such predictive models on a larger scale, to help us better understand positive psychology and individual well-being. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| العلاقة: | https://boris.unibe.ch/177036Test/ |
| الإتاحة: | https://doi.org/10.1038/s41598-022-26550-yTest https://boris.unibe.ch/177036/1/s41598-022-26550-y.pdfTest https://boris.unibe.ch/177036Test/ |
| حقوق: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.6F80E3 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |