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

Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18-64
SponsorNew York University

About this trial

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.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

N/A

Disqualifiers

History of neurological or psychiatric illness

Vulnerable populations

Trial design

Design model

Single group

Treatments tested in this trial

  • 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.

Treatment groups

50 Participants
are divided into 1 treatment group
Group A: MEG cohortExperimental treatment 1 intervention

Trial outcomes

Primary outcomes

1

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.

Time frame
1 hour
2

MEG activity

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

Time frame
1 hour

Secondary outcomes

Other outcomes

Sponsors and contacts

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New York University

Lead sponsor

National Institute of Mental Health (NIMH)

Collaborator