Modeling of grid cell activity demonstrates in vivo entorhinal 'look-ahead' properties

Simultaneous representation of multiple time horizons by entorhinal grid cells and CA1 place cells

Grid cells and place cells represent the spatiotemporal continuum of an animal's past, present, and future locations. However, their spatiotemporal relationship is unclear. Here, we co-record grid and place cells in freely foraging rats. We show that average time shifts in grid cells tend to be prospective and are proportional to their spatial scale, providing a nearly instantaneous readout of a spectrum of progressively increasing time horizons ranging hundreds of milliseconds. Average time shifts of place cells are generally larger compared to grid cells and also increase with place field sizes. Moreover, time horizons display nonlinear modulation by the animal's trajectories in relation to the local boundaries and locomotion cues. Finally, long and short time horizons occur at different parts of the theta cycle, which may facilitate their readout. Together, these findings suggest that population activity of grid and place cells may represent local trajectories essential for goal-directed navigation and planning.

Neuronal Computation Underlying Inferential Reasoning in Humans and Mice

Every day we make decisions critical for adaptation and survival. We repeat actions with known consequences. But we also draw on loosely related events to infer and imagine the outcome of entirely novel choices. These inferential decisions are thought to engage a number of brain regions; however, the underlying neuronal computation remains unknown. Here, we use a multi-day cross-species approach in humans and mice to report the functional anatomy and neuronal computation underlying inferential decisions. We show that during successful inference, the mammalian brain uses a hippocampal prospective code to forecast temporally structured learned associations. Moreover, during resting behavior, coactivation of hippocampal cells in sharp-wave/ripples represent inferred relationships that include reward, thereby "joining-the-dots" between events that have not been observed together but lead to profitable outcomes. Computing mnemonic links in this manner may provide an important mechanism to build a cognitive map that stretches beyond direct experience, thus supporting flexible behavior.

Computational cognitive models of spatial memory in navigation space: a review

Spatial memory refers to the part of the memory system that encodes, stores, recognizes and recalls spatial information about the environment and the agent's orientation within it. Such information is required to be able to navigate to goal locations, and is vitally important for any embodied agent, or model thereof, for reaching goals in a spatially extended environment. In this paper, a number of computationally implemented cognitive models of spatial memory are reviewed and compared. Three categories of models are considered: symbolic models, neural network models, and models that are part of a systems-level cognitive architecture. Representative models from each category are described and compared in a number of dimensions along which simulation models can differ (level of modeling, types of representation, structural accuracy, generality and abstraction, environment complexity), including their possible mapping to the underlying neural substrate. Neural mappings are rarely explicated in the context of behaviorally validated models, but they could be useful to cognitive modeling research by providing a new approach for investigating a model's plausibility. Finally, suggested experimental neuroscience methods are described for verifying the biological plausibility of computational cognitive models of spatial memory, and open questions for the field of spatial memory modeling are outlined.

Hippocampal theta sequences reflect current goals

Hippocampal information processing is discretized by oscillations, and the ensemble activity of place cells is organized into temporal sequences bounded by theta cycles. Theta sequences represent time-compressed trajectories through space. Their forward-directed nature makes them an intuitive candidate mechanism for planning future trajectories, but their connection to goal-directed behavior remains unclear. As rats performed a value-guided decision-making task, the extent to which theta sequences projected ahead of the animal's current location varied on a moment-by-moment basis depending on the rat's goals. Look-ahead extended farther on journeys to distant goals than on journeys to more proximal goals and was predictive of the animal's destination. On arrival at goals, however, look-ahead was similar regardless of where the animal began its journey from. Together, these results provide evidence that hippocampal theta sequences contain information related to goals or intentions, pointing toward a potential spatial basis for planning.

A high-resolution study of hippocampal and medial temporal lobe correlates of spatial context and prospective overlapping route memory

When navigating our world we often first plan or retrieve an ideal route to our goal, avoiding alternative paths that lead to other destinations. The medial temporal lobe (MTL) has been implicated in processing contextual information, sequence memory, and uniquely retrieving routes that overlap or "cross paths." However, the identity of subregions of the hippocampus and neighboring cortex that support these functions in humans remains unclear. The present study used high-resolution functional magnetic resonance imaging (hr-fMRI) in humans to test whether the CA3/DG hippocampal subfield and parahippocampal cortex are important for processing spatial context and route retrieval, and whether the CA1 subfield facilitates prospective planning of mazes that must be distinguished from alternative overlapping routes. During hr-fMRI scanning, participants navigated virtual mazes that were well-learned from prior training while also learning new mazes. Some routes learned during scanning shared hallways with those learned during pre-scan training, requiring participants to select between alternative paths. Critically, each maze began with a distinct spatial contextual Cue period. Our analysis targeted activity from the Cue period, during which participants identified the current navigational episode, facilitating retrieval of upcoming route components and distinguishing mazes that overlap. Results demonstrated that multiple MTL regions were predominantly active for the contextual Cue period of the task, with specific regions of CA3/DG, parahippocampal cortex, and perirhinal cortex being consistently recruited across trials for Cue periods of both novel and familiar mazes. During early trials of the task, both CA3/DG and CA1 were more active for overlapping than non-overlapping Cue periods. Trial-by-trial Cue period responses in CA1 tracked subsequent overlapping maze performance across runs. Together, our findings provide novel insight into the contributions of MTL subfields to processing spatial context and route retrieval, and support a prominent role for CA1 in distinguishing overlapping episodes during navigational "look-ahead" periods.