Identifying the neural correlates of mental simulation in multi-step planning - PROJECT SUMMARY/ABSTRACT Planning, the ability to mentally simulate possible futures toward a goal, is essential for everyday decision-making. Indeed, many psychiatric and neurological disorders are associated with dysfunctions in planning, including obsessive-compulsive disorder and autism spectrum disorder. However, the neural mechanisms underlying complex planning remain poorly understood, partly due to the disconnect between the oversimplified tasks used in most neuroscience studies and the rich, strategic planning required in real life. This project addresses this challenge by studying the neural basis of planning in Four-in-a-Row, a game that captures the essence of complex planning while being amenable to detailed computational modeling. We posit that the brain plans by simulating promising sequences of future actions and evaluating their outcomes using a feature-based heuristic – a process we formalize in a computational model. To track this process in the brain, we will combine fMRI and MEG neuroimaging techniques and eye-tracking measurements, leveraging the computational model to guide the analyses of these data. Aim 1 will employ fMRI to identify brain regions representing the value of potential moves and the features involved in their evaluation. This spatial mapping will reveal where value and decision signals are computed in the brain during planning. Aim 2 will leverage the high temporal resolution of MEG to track the dynamic unfolding of mental simulation, allowing us to pinpoint when specific value computations and representations of possible future scenarios occur. Aim 3 expands our investigation by applying deep neural network models to extensive gameplay data, intending to uncover distinct, individualized planning strategies and improve our characterization of the neural mechanisms of complex planning. Overall, we will obtain a unified picture of planning, linking behavior, spatial neural correlates, and the temporal dynamics of this complex cognitive process. This research will be the first to provide direct neural evidence of mental simulation during planning, promising fundamental insights into a core aspect of human cognition. Our interdisciplinary team, with expertise in computational modeling, neuroimaging, and machine learning, is uniquely equipped to carry out this innovative research program. Although immediate translational applications are not the focus, our findings could eventually enhance the behavioral and neural characterization of planning deficits in various mental health disorders, potentially informing the design of more targeted interventions.