Pezzulo, Giovanni, Francesco Donnarumma, Domenico Maisto, and Ivilin Stoianov. “Planning at decision time and in the background during spatial navigation.” Current Opinion in Behavioral Sciences 29 (2019): 69-76.

Highlights
• Planning is the model-based approach to solving control problems.

• We review recent studies of planning during spatial navigation in rodents and humans.

• We distinguish two complementary planning modes: ‘at decision time’ and ‘in the background’.

• We discuss the putative neuronal signatures of the two planning modes in the rodent brain.

• We make parallels between empirical evidence and planning models in artificial intelligence.

Planning is the model-based approach to solving control problems. The hallmark of planning is the endogenous generation of dynamical representations of future states, like goal locations, or state sequences, like trajectories to the goal location, using an internal model of the task. We review recent evidence of model-based planning processes and the representation of future goal states in the brain of rodents and humans engaged in spatial navigation tasks. We highlight two distinct but complementary usages of planning as identified in artificial intelligence: ‘at decision time’, to support goal-directed choices and sequential memory encoding, and ‘in the background’, to learn behavioral policies and to optimize internal models. We discuss how two kinds of internally generated sequences in the hippocampus– theta and SWR sequences – might participate in the neuronal implementation of these two planning modes, thus supporting a flexible model-based system for adaptive cognition and action.

For further info, please read the paper Pezzulo et al. 2019

Pezzulo, Giovanni, Francesco Donnarumma, Domenico Maisto, and Ivilin Stoianov. “Planning at decision time and in the background during spatial navigation.” Current Opinion in Behavioral Sciences 29 (2019): 69-76.