[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100615517":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":20,"centralContacts":20,"locations":21,"responsibleParty":43,"collaborators":45,"id":49,"slug":50,"hasResults":51,"nctId":52,"briefTitle":53,"officialTitle":53,"acronym":20,"eligibilityCriteria":54,"healthyVolunteers":55,"sex":56,"minAge":57,"maxAge":58,"enrollmentInfo":59,"targetDuration":20,"studyType":62,"phases":63,"briefSummary":65,"conditions":66,"keywords":72,"overallStatus":23,"whyStopped":20,"lastUpdateSubmitDate":79,"lastUpdatePostDateStruct":80,"startDateStruct":83,"completionDateStruct":85,"leadSponsor":87,"locationsCount":88},{"fullName":5,"class":6},"New York University","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"MEG cohort","EXPERIMENTAL","Single-group study in healthy adults. Participants complete a behavioral training session and then an in-person session performing the Four-in-a-Row planning task during MEG (with an additional MEG localizer task, as applicable).",[13],"Behavioral: Four-in-a-Row Task",[15],{"type":16,"name":17,"description":18,"armGroupLabels":19,"otherNames":20},"BEHAVIORAL","Four-in-a-Row Task","Deterministic, adversarial 'Four-in-a-Row' decision-making task that requires thinking multiple steps ahead. Participants complete a training\u002Fgameplay session and a laboratory session in which they choose moves from mid-game positions while behavioral responses (and eye movements, if applicable) are recorded. After the neuroimaging session, participants may play a full match outside the scanner for an additional monetary reward.",[9],null,[22],{"facility":5,"status":23,"city":24,"state":24,"zip":25,"country":26,"countryCode":27,"cosmosGeoPoint":28,"geoPoint":33,"contacts":34},"RECRUITING","New York","10012","United States","US",{"type":29,"coordinates":30},"Point",[31,32],-74.00597,40.71427,{"lat":32,"lon":31},[35,40],{"name":36,"role":37,"phone":38,"phoneExt":20,"email":39},"Facility contact, Ph.D.","CONTACT","929-399-9886‬","mattar.lab.nyu@gmail.com",{"name":41,"role":42,"phone":20,"phoneExt":20,"email":20},"Marcelo G Mattar, PhD","PRINCIPAL_INVESTIGATOR",{"type":44,"investigatorFullName":20,"investigatorTitle":20,"investigatorAffiliation":20,"oldNameTitle":20,"oldOrganization":20},"SPONSOR",[46],{"name":47,"class":48},"National Institute of Mental Health (NIMH)","NIH","100615517","identifying-the-neural-correlates-of-mental-simulation-in-multi-step-planning-100615517",false,"NCT07293637","Identifying the Neural Correlates of Mental Simulation in Multi-Step Planning","Inclusion Criteria:\n\n* N\u002FA\n\nExclusion Criteria:\n\n* History of neurological or psychiatric illness\n* Vulnerable populations",true,"ALL","18 Years","64 Years",{"count":60,"type":61},50,"ESTIMATED","INTERVENTIONAL",[64],"NA","Planning is the ability to think ahead by considering possible future actions and their consequences. This research study aims to understand how the brain supports multi-step planning by testing whether people simulate promising future move sequences while deciding what to do next. Healthy adult volunteers will learn and play a strategy game called \"Four-in-a-Row\" (similar to Connect Four). Participants will complete two sessions on successive days: an online behavioral training\u002Fplaying session and an in-person brain-recording session at New York University. During the brain-recording session, participants will view mid-game board positions and choose the best move while the study team records brain activity (using magnetoencephalography \\[MEG\\] or functional MRI \\[fMRI\\]) and eye movements. Data from the game and eye tracking will also be used to fit computational models of planning that help interpret the neural measurements.",[67,68,69,70,71],"Decision Making","Cognition","Mental Simulation","Problem Solving","Planning",[73,71,74,75,76,77,78],"Four-in-a-Row","Tree search","Computational modeling","Eye tracking","MEG","fMRI","2026-01-07",{"date":81,"type":82},"2026-01-08","ACTUAL",{"date":84,"type":82},"2025-07-10",{"date":86,"type":61},"2026-12",{"name":5,"class":6},1]