Paranoia and Bias in Social Belief Updating in Clinical High Risk for Psychosis
Paranoia and Bias in Social Belief Updating in Clinical High Risk for Psychosis
批准号:
10750091
负责人:
Trevor Ford Williams
金额:
$6.87万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-08-01 至 2025-07-31
关键词:
AccountingAffectAttenuatedAutomobile DrivingBayesian ModelingBehavioralBeliefBiological AssayBrainClinicalComputer ModelsControl GroupsCuesDataData AnalysesDelusionsDevelopmentDiseaseDisease ProgressionEarly identificationEducational workshopEnvironmentFeedbackFoodFundingFutureHypersensitivityImpairmentIndividualInterventionInterviewerJudgmentKnowledgeLearningLinear ModelsLinkLiteratureLongitudinal StudiesMeasuresModelingNational Institute of Mental HealthOccupationalOutcomeParanoiaParticipantPathologic ProcessesPerformancePersonsPopulationPositioning AttributePredictive ValueProbabilityProbability LearningProcessPsychological reinforcementPsychopathologyPsychosesPsychotic DisordersPunishmentResearchReversal LearningRewardsRiskRoleSamplingSchizophreniaSensorySocial ChangeSocial EnvironmentSocial FunctioningSocial ProcessesSocial ReinforcementSpecificitySymptomsTestingTimeTrainingUncertaintyUniversitiesUpdateVariantVolatilizationWorkcareerclinical high risk for psychosisclinical predictorscommon symptomdisabling symptomexperiencefunctional outcomesinformation processingmeetingspreventive interventionprogramspsychosis riskpsychotic symptomsskillssocialsocial biassocial cognitionsocial learningsocial relationshipsstemsymposiumtheories
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英文摘要
Project Summary
Individuals at clinical high risk for psychosis (CHR) experience attenuated positive symptoms (e.g.,
delusions) and may later develop psychosis spectrum disorders (e.g., schizophrenia).1 Paranoia is a common
and impairing psychotic symptom, also present in CHR individuals.2–5 Emerging mechanistic research using
reinforcement learning task paradigms suggest that individuals with paranoia hold rigid prior beliefs about their
environments being highly unpredictable and others being untrustworthy, which is in turn linked to reduced
learning from actual environmental feedback that may challenge these beliefs.6–8 While these explanations
hold promise for explaining a complicated phenomenon, they have not been tested in CHR individuals and a
number of questions remain. For instance, there is debate within the literature as to whether general vs. social
learning processes are most relevant to paranoia; however, existing tasks poorly examine this issue.9,10
Furthermore, previous research has focused mainly on one reinforcement learning paradigm (e.g., learning
volatile probabilities) and paradigms measuring other learning processes relevant to delusions (e.g.,
inappropriate learning about blocked cues) may also be related to paranoia.11 Finally, the connection between
reinforcement learning processes and symptom progression and functional outcomes (e.g., worsening) has not
been examined. The proposed study will examine these gaps in the literature using samples of CHR
individuals (N = 50), clinical controls (N = 50), and healthy controls (N = 50), with half being followed for one
year. Using this data, the study aims to develop and validate two distinct socially-salient reinforcement learning
tasks (Aim 1), compare these two distinct learning paradigms in terms of relevance to paranoia (Aim 2),
examine the value of these two social learning tasks for predicting symptom progression (e.g., worsening
paranoia) and social functioning decline, above and beyond non-social versions of these tasks (Aim 3). These
aims and this project will make use of a larger, ongoing NIMH-funded project,12 which will provide data on 50
CHR individuals, as well as 50 clinical controls and 50 healthy controls. Training Plan: to complete this project
and build an independent research career the applicant will (a) pursue in-depth knowledge of psychosis risk,
development, delusion formation, social cognition, and learning theory, (b) learn to develop and validate
dynamic behavioral tasks, and (c) develop longitudinal data analysis skills. This training will be accomplished
through regular meetings with a team of expert scholars, coursework, workshops, and attending conferences.
Training Environment: The training will take place at Northwestern University, which offers an excellent and
collaborative training environment, which includes both the sponsor and the project’s data analysis consultant.
The environment, alongside the proposed study and training plan, will position the applicant to launch a unique
program of research and advance our understanding of social processes in psychopathology.
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