Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network

Balaguer, Jan; Spiers, Hugo J.; Hassabis, Demis; Summerfield, Christopher

doi:10.1016/j.neuron.2016.03.037

Cited by 158 publications

(178 citation statements)

References 45 publications

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“…While the hippocampus appears to represent information about changes in topological properties, the lateral prefrontal activity reflected the demands of searching the network of possible future paths when re-planning was required at Detours. This is consistent with prefrontal regions playing a role in spatial planning during navigation103839. However, it has not been clear which regions of PFC are central to this function.…”

Section: Discussionsupporting

confidence: 60%

“…It is possible that prolonged exposure to the environment would drive an increase in global processing of network topology in the hippocampus, or a switch to topological processing in cortical regions. In light of recent discoveries of the brain regions that support navigation of subway networks38, it is possible that learning to exploit the hierarchical structure leads to the transfer of planning from a BFS in lateral PFC to a more efficient hierarchically organized plan mediated by dorsomedial PFC and premotor cortex.…”

Section: Discussionmentioning

confidence: 99%

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Hippocampal and prefrontal processing of network topology to simulate the future

et al. 2017

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Topological networks lie at the heart of our cities and social milieu. However, it remains unclear how and when the brain processes topological structures to guide future behaviour during everyday life. Using fMRI in humans and a simulation of London (UK), here we show that, specifically when new streets are entered during navigation of the city, right posterior hippocampal activity indexes the change in the number of local topological connections available for future travel and right anterior hippocampal activity reflects global properties of the street entered. When forced detours require re-planning of the route to the goal, bilateral inferior lateral prefrontal activity scales with the planning demands of a breadth-first search of future paths. These results help shape models of how hippocampal and prefrontal regions support navigation, planning and future simulation.

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Section: Discussionsupporting

confidence: 60%

Section: Discussionmentioning

confidence: 99%

Hippocampal and prefrontal processing of network topology to simulate the future

et al. 2017

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“…For example, theta sequences emerge under the variational scheme of active inference if one considers that at each (theta) cycle successive elements of the policy state space are inferred, and the inference proceeds more rapidly for locations that the animal is approaching, which in turn produces a “phase precession” within this inferential scheme. These and other formal schemes may be used to test empirical predictions on how rodents solve challenging navigation tasks or even how humans solve abstract tasks . Compared with other computational proposals that also discuss hippocampal function in relation to generative models, we have stressed the idea that hippocampal coding and processing may be organized around sequences.…”

Section: Discussionmentioning

confidence: 99%

Internally generated hippocampal sequences as a vantage point to probe future‐oriented cognition

Pezzulo

Kemere

Meer

2017

Annals of the New York Academy of Sciences

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Information processing in the rodent hippocampus is fundamentally shaped by internally generated sequences (IGSs), expressed during two different network states: theta sequences, which repeat and reset at the ∼8 Hz theta rhythm associated with active behavior, and punctate sharp wave-ripple (SWR) sequences associated with wakeful rest or slow-wave sleep. A potpourri of diverse functional roles has been proposed for these IGSs, resulting in a fragmented conceptual landscape. Here, we advance a unitary view of IGSs, proposing that they reflect an inferential process that samples a policy from the animal's generative model, supported by hippocampus-specific priors. The same inference affords different cognitive functions when the animal is in distinct dynamical modes, associated with specific functional networks. Theta sequences arise when inference is coupled to the animal's action-perception cycle, supporting online spatial decisions, predictive processing, and episode encoding. SWR sequences arise when the animal is decoupled from the action-perception cycle and may support offline cognitive processing, such as memory consolidation, the prospective simulation of spatial trajectories, and imagination. We discuss the empirical bases of this proposal in relation to rodent studies and highlight how the proposed computational principles can shed light on the mechanisms of future-oriented cognition in humans.

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“…One disadvantage of our task is the inability to probe the time scale of plan formation and implementation in novel environments, particularly when choice accuracy and RT are influenced differently by path length differences. Most planning studies test after extensive training and are biased towards action-by-action evaluation without the need to maintain prior choices [3–4,48–50]. With extensively trained choices, the neural computations leading to increased decision implementation/RT are well studied [51–52].…”

Section: Discussionmentioning

confidence: 99%

The Neural Representation of Prospective Choice during Spatial Planning and Decisions

et al. 2017

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We are remarkably adept at inferring the consequences of our actions, yet the neuronal mechanisms that allow us to plan a sequence of novel choices remain unclear. We used functional magnetic resonance imaging (fMRI) to investigate how the human brain plans the shortest path to a goal in novel mazes with one (shallow maze) or two (deep maze) choice points. We observed two distinct anterior prefrontal responses to demanding choices at the second choice point: one in rostrodorsal medial prefrontal cortex (rd-mPFC)/superior frontal gyrus (SFG) that was also sensitive to (deactivated by) demanding initial choices and another in lateral frontopolar cortex (lFPC), which was only engaged by demanding choices at the second choice point. Furthermore, we identified hippocampal responses during planning that correlated with subsequent choice accuracy and response time, particularly in mazes affording sequential choices. Psychophysiological interaction (PPI) analyses showed that coupling between the hippocampus and rd-mPFC increases during sequential (deep versus shallow) planning and is higher before correct versus incorrect choices. In short, using a naturalistic spatial planning paradigm, we reveal how the human brain represents sequential choices during planning without extensive training. Our data highlight a network centred on the cortical midline and hippocampus that allows us to make prospective choices while maintaining initial choices during planning in novel environments.

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Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network

Cited by 158 publications

References 45 publications

Hippocampal and prefrontal processing of network topology to simulate the future

Hippocampal and prefrontal processing of network topology to simulate the future

Internally generated hippocampal sequences as a vantage point to probe future‐oriented cognition

The Neural Representation of Prospective Choice during Spatial Planning and Decisions

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