Flexible selection of working memory representations to reduce cognitive cost

Abstract

Across psychology 1-4, economics 5,6, machine learning 7, and neuroscience 8,9, it is well established that choosing a good internal representation can make complex problems easier to solve. Thus, intelligent behavior depends not only on what is stored in working memory, but on the format in which it is stored. Selecting a lower-load format can substantially reduce the mental effort required for a task, since working-memory load is a major contributor to cognitive cost 10-12. Whether non-human animals make such representational choices, and how these choices are implemented in neural circuits, has remained unclear. Here we show that rats flexibly adjust the format of working memory to reduce cognitive cost. In an egocentric task that encourages an action-based code, rats maintained the relevant information as a stable motor plan supported by frontal cortex. When the same behavioral problem was reformulated in allocentric coordinates, the action-based code became costly, and rats instead stored a sensory trace in auditory cortex. A cost-sensitive model explains which internal format should be used under each task variant and predicted that simplifying the allocentric task would reduce the advantage of a sensory code and drive reinstatement of frontal motor planning; this prediction was confirmed, as rats rapidly returned to a motorplan representation and the frontal cortex again became necessary for performance. These results demonstrate that flexible representational selection is not unique to humans 13 but is present in rodents and reflected in circuit-level reallocation of working memory. This establishes a neural basis for classic theories linking problem representation to computational efficiency and provides a path toward a circuit-level understanding of how the brain selects internal formats to reduce cognitive cost.