The cognitive mechanisms of complex planning

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PROJECT SUMMARY/ABSTRACT The goal of this project is to lay the groundwork for understanding the neural basis of complex planning. Planning, defined as sequential decision-making that involves mental simulation of potential futures, is crucial for the organization of our behavior in everyday life — from navigation to playing sports or writing a long text. Real-world planning is often “complex”, in the sense that there is a explosively large number of possible futures and the decision-maker has to think multiple steps ahead. By contrast, studies of human planning typically use simple tasks, in which the number of possible states is low and thinking ahead is barely necessary. To serve as a suitable behavioral paradigm to study complex planning, a task should meet multiple criteria: it should require thinking ahead, it should be novel to subjects, it should have simple rules, and it should allow for computational modeling in order to disentangle component processes. We previously developed a behavioral paradigm that satisfies these requirements, as well as a computational process model of choices in this task based on a heuristic value function and partial tree search. This model can be used to estimate depth of planning (EDOP). The goals of the present proposal are two-fold: to prepare the model for use in future neural studies by establishing the construct validity of EDOP (Aim 1), and to go beyond choice data to probe the dynamics of complex planning using eye movements made while a choice is being prepared (Aim 2). Although this work does not have direct clinical relevance, it could in the future serve to improve the behavioral and neural characterization of deficits in planning, as well as the effectiveness of interventions. Planning is disrupted in many neurological and psychiatric disorders. For example, performance on planning tasks is impaired in individuals with Obsessive Compulsive Disorder, Autism Spectrum Disorder, and prefrontal lesions.