Gauging the capacity for concurrent motor planning in human fMRI with information constraints in bounded rational decision-making models

While traditional theories of sensorimotor processing have often assumed a serial decision-making pipeline, more recent approaches have suggested that multiple actions may be planned concurrently and vie for execution. As most of the evidence for the latter comes from monkeys, here we study concurrent prospective motor planning in humans by recording functional magnetic resonance imaging (fMRI) during a sequence planning task with multiple potential targets. We find that fMRI activity in premotor and parietal brain areas modulates both with the sequence complexity and the number of targets. We test the hypothesis that fMRI activity is best explained by concurrent planning as opposed to the incomplete determination of a single action plan. We devise a bounded rationality model with information constraints that optimally assigns information resources for planning and memory for this task and determine predicted information profiles according to the two hypotheses. When regressing fMRI activity using this model, we find that the concurrent planning strategy provides a significantly better explanation of the fMRI modulation profile. Moreover, we find that concurrent planning is limited for most subjects, as expressed by the best fitting information capacities. We conclude that bounded rational decision-making models allow relating both behavior and neural representations to utilitarian task descriptions based on bounded optimal information-processing assumptions.

Session-based concurrency, declaratively

Session-based concurrency is a type-based approach to the analysis of message-passing programs. These programs may be specified in an operational or declarative style: the former defines how interactions are properly structured; the latter defines governing conditions for correct interactions. In this paper, we study rigorous relationships between operational and declarative models of session-based concurrency. We develop a correct encoding of session $$\pi $$ π -calculus processes into the linear concurrent constraint calculus ($$\texttt {lcc}$$ lcc ), a declarative model of concurrency based on partial information (constraints). We exploit session types to ensure that our encoding satisfies precise correctness properties and that it offers a sound basis on which operational and declarative requirements can be jointly specified and reasoned about. We demonstrate the applicability of our results by using our encoding in the specification of realistic communication patterns with time and contextual information.