Washington University School of Medicine
In Study 3, all tasks and models from Aim 1 will be evaluated in a large community sample of online participants recruited through Prolific. Aim 3 will establish 1) requirements for testing computational algorithms in population-based samples, 2) whether task length is optimal, and 3) whether computational parameters help predict psychopathology (hallucinations and delusions in particular) in the general population, and how these predictors may be impacted by demographic variables, such as race, ethnicity, gender, age and other social determinants of health. Participant demographics will be matched to the U.S. Census 2023 American Community Survey (ACS) data release (updated as available). MPI MacDonald has successfully recruited large online samples for over a decade. Specifically, researchers will recruit two samples of n=2,000 to preregister hypotheses and then n=3,000 to independently confirm those hypotheses. Multiple methods will affirm the highest quality human self-report and behavioral data for online samples. Researchers use Prolific, which is known for high quality research participation, maintaining low levels of bots through strategies such as requiring a photo ID and a waiting period. Second, inclusion criteria will require an approval rating of 90-100% from previous researchers. Participants will complete three sessions, each limited to \~60 min to avoid burnout.
Researchers will recruit two samples of 2,000 to preregister hypotheses and then 3,000 to independently confirm those hypotheses. Multiple methods will affirm the highest quality human self-report and behavioral data for online samples. First, researchers will use Prolific, which is known for high quality research participation, maintaining low levels of bots through strategies such as requiring a photo ID and a waiting period. Participants will complete 3 sessions, each limited to \~60 min to avoid burnout. Researchers anticipate complete data from 74% of participants, based on data completi…
Inclusion Criteria: * Residents of the U.S. * between 18-59 years of age Exclusion Criteria: * Resides outside of U.S. * under 18 or over 59 years of age
Assesses updating of beliefs from new sensory inputs with prior knowledge via perceiving direction changes in random dot motion stimuli
Measures the degree to which overweighting of prior beliefs impacts processing of sensory inputs (detection of speech).
Measures the updating of priors about the location of a bag drop from a helicopter when the location changes (prediction errors).
Assesses prior belief updating when feedback about obtaining positive outcomes changes (prediction errors).
Examines the role of mismatches between learned priors and new information (prediction errors) in belief formation about event causes.
Assesses the degree to which people distinguish between their priors about others' motivations, such as selfishness and spite, and impersonal chance in one-shot trust game and dictator games.
Assesses degree to which people learn and update priors about trusting partners from dynamic social feedback (prediction error) in a social exchange game.