Supporting data for "Examining Emotion-related Perceptual Decision Making in Internalising Psychopathology"

We first established a novel paradigm which allowed the examination of both, bottom-up stimulus features and top-down attention-guided components (Study 1, Chapter 2, <i>N</i> = 168). The dataset for Chapter 2 contains behavioural data and computational modeling data (HDDM = hierarchical drift diffusion model). Behavioural data is included for one main experiment and two control experiments. Script folders (run in MATLAB and python) for analysis purposes are included. HDDM data contains traces for three models.Next, we applied the introduced and tested paradigm among a clinical (internalising psychopathology = IP) and healthy control (HC) sample (Study 2, Chapter 3, <i>N</i> = 137). The dataset for Chapter 3 contains behavioural data and computational modelling data (HDDM). Behavioural data is included for one main experiment and script folders (run in MATLAB and python) for analysis purposes. For HDDM analysis, traces for the winning model established in Chapter 2 are included.Study 3 addressed a different type of emotion-related perceptual decision making. We investigated potential differences among IP and HC under exposure to myriad pieces of emotional evidence (Study 3, Chapter 4, <i>N</i> = 122). Here, we employed a multi-element paradigm under exposure to face crowds. The dataset for Chapter 4 includes behavioural data and computational modelling data (EMHMM = Eye movement analysis with hidden Markov models). Behavioural data is included for one main experiment and script folders contain MATLAB and python codes for analysis purposes.Psychopathology data includes anonymised scoresheets of the Structured Clinical Interview for DSM-5, Research Version (SCID-5-RV) as well as questionnaire outputs with demographic information and dimensionally assessed symptom severities.