Identifying the Neural Correlates of Mental Simulation in Multi-Step Planning

NCT07293637 | Recruiting

• 2 other identifiers: 24-13311R01MH134979-01A1
• Study Type: interventional
• Target: 50
• Locations: 1 country
• Sites: 1

Brief Summary

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/playing 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.

Conditions

Cognition; Mental Simulation; Problem Solving; Planning; Decision Making

Keywords

Four-in-a-Row; Planning; Tree search; Computational modeling; Eye tracking; MEG; fMRI

Outcome Measures

Primary Outcomes (2)

• Percent of moves correctly predicted by the behavioral model

  Participant choices in the Four-in-a-Row task are used to fit a computational behavioral model. After fitting, the model predicts an action for each state; we quantify the percent of participant moves matched by the model's predicted move.

  1 hour

• MEG activity

  Task-evoked MEG activity during different stages of the task, specifically deliberation about upcoming decisions.

  1 hour

Study Arms (1)

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).

Behavioral: Four-in-a-Row Task

Interventions

Four-in-a-Row Task BEHAVIORAL

Deterministic, adversarial 'Four-in-a-Row' decision-making task that requires thinking multiple steps ahead. Participants complete a training/gameplay 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.

MEG cohort

Eligibility Criteria

• Age: 18 Years - 64 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• N/A

You may not qualify if:

• History of neurological or psychiatric illness
• Vulnerable populations

Sponsors & Collaborators

• New York University: lead
• National Institute of Mental Health (NIMH): collaborator

Study Sites (1)

New York University

New York, New York, 10012, United States

RECRUITING

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: BASIC SCIENCE
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 17, 2025
• First Posted: December 19, 2025
• Study Start: July 10, 2025
• Primary Completion: March 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: January 8, 2026

Record last verified: 2025-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, ICF, ANALYTIC CODE
• Time Frame: IPD and supporting information will be made available starting 12 months after the NIH award begins, with updates deposited every 6 months thereafter, and will remain available indefinitely.
• Access Criteria: De-identified IPD will be available through the NIMH Data Archive (NDA) and via OSF/OpenNeuro for relevant datasets, with analytic code shared via GitHub. We will not impose any investigator-specific limitations on access, distribution, or reuse beyond standard repository requirements (e.g., account registration and agreement to repository terms). All shared data will be de-identified.

Locations

US (1)