Cognition, Decision Making, Mental Simulation, Planning, Problem Solving
Conditions
Keywords
Four-in-a-Row, Planning, Tree search, Computational modeling, Eye tracking, MEG, fMRI
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.
Detailed description
This is a human neuroimaging study consisting of two related experiments designed to characterize the neural correlates of mental simulation during multi-step planning in the Four-in-a-Row game. Planning is modeled as a feature-based heuristic evaluation combined with look-ahead (tree search) that evaluates candidate actions by simulating future states and outcomes. Participants complete two sessions on successive days. Session 1 is a \ 60-minute online behavioral session in which participants learn the rules of Four-in-a-Row (including a comprehension/quiz check) and play multiple games against computer opponents spanning difficulty levels. Behavioral data from Session 1 are used to fit a computational model of planning for each participant. Session 2 is an in-person neuroimaging session with simultaneous eye tracking. In the MEG experiment, participants complete a feature localizer followed by a primary planning task in which they evaluate mid-game board positions with a fixed decision window (e.g., 15 seconds) to encourage planning. B2 In the fMRI experiment, participants complete a planning task while BOLD activity and eye movements are recorded, using a trial structure designed to dissociate model-derived quantities such as myopic value and tree-search value. The main analyses will test where (fMRI) and when (MEG) the brain represents simulated future states, their values, and the evolving decision process, guided by participant-specific computational-model predictions.
Interventions
BEHAVIORALFour-in-a-Row Task
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.
Sponsors
National Institute of Mental Health (NIMH)
New York University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
BASIC_SCIENCE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 64 Years
Healthy volunteers
Yes
Inclusion criteria
* N/A
Exclusion criteria
* History of neurological or psychiatric illness * Vulnerable populations
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Percent of moves correctly predicted by the behavioral model | 1 hour | 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. |
| MEG activity | 1 hour | Task-evoked MEG activity during different stages of the task, specifically deliberation about upcoming decisions. |
Countries
United States
Outcome results
None listed