2016/05/01 by Jan Balaguer, Hugo J. Spiers, Demis Hassabis +1 · 1 voice · 2 citations
Computer Science · #Bayesian Modeling and Causal Inference #Cognitive Computing and Networks #Cognitive Science and Mapping
paper · pdf · doi:10.1016/j.neuron.2016.03.037
openalex publication_date 2016/05/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Planning allows actions to be structured in pursuit of a future goal. However, in natural environments, planning over multiple possible future states incurs prohibitive computational costs. To represent plans efficiently, states can be clustered hierarchically into "contexts". For example, representing a journey through a subway network as a succession of individual states (stations) is more costly than encoding a sequence of contexts (lines) and context switches (line changes). Here, using functional brain imaging, we asked humans to perform a planning task in a virtual subway network. Behavioral analyses revealed that humans executed a hierarchically organized plan. Brain activity in the dorsomedial prefrontal cortex and premotor cortex scaled with the cost of hierarchical plan representation and unique neural signals in these regions signaled contexts and context switches. These results suggest that humans represent hierarchical plans using a network of caudal prefrontal structures. VIDEO ABSTRACT.