Organization of pRF size along the AP axis of the hippocampus and adjacent medial temporal cortex is related to specialization for scenes versus faces.

The hippocampus is largely recognized for its integral contributions to memory processing. By contrast, its role in perceptual processing remains less clear. Hippocampal properties vary along the anterior-posterior (AP) axis. Based on past research suggesting a gradient in the scale of features processed along the AP extent of the hippocampus, the representations have been proposed to vary as a function of granularity along this axis. One way to quantify such granularity is with population receptive field (pRF) size measured during visual processing, which has so far received little attention. In this study, we compare the pRF sizes within the hippocampus to its activation for images of scenes versus faces. We also measure these functional properties in surrounding medial temporal lobe (MTL) structures. Consistent with past research, we find pRFs to be larger in the anterior than in the posterior hippocampus. Critically, our analysis of surrounding MTL regions, the perirhinal cortex, entorhinal cortex, and parahippocampal cortex shows a similar correlation between scene sensitivity and larger pRF size. These findings provide conclusive evidence for a tight relationship between the pRF size and the sensitivity to image content in the hippocampus and adjacent medial temporal cortex.

Older adults can use memory for distinctive objects, but not distinctive scenes, to rescue associative memory deficits.

Associative memory deficits in aging are frequently characterized by false recognition of novel stimulus associations, particularly when stimuli are similar. Introducing distinctive stimuli, therefore, can help guide item differentiation in memory and can further our understanding of how age-related brain changes impact behavior. How older adults use different types of distinctive information to distinguish overlapping events in memory and to avoid false associative recognition is still unknown. To test this, we manipulated the distinctiveness of items from two stimulus categories, scenes and objects, across three conditions: (1) distinct scenes paired with similar objects, (2) similar scenes paired with distinct objects, and (3) similar scenes paired with similar objects. Young and older adults studied scene-object pairs and then made both remember/know judgments toward single items as well as associative memory judgments to old and novel scene-object pairs ("Were these paired together?"). Older adults showed intact single item recognition of scenes and objects, regardless of whether those objects and scenes were similar or distinct. In contrast, relative to younger adults, older adults showed elevated false recognition for scene-object pairs, even when the scenes were distinct. These age-related associative memory deficits, however, disappeared if the pair contained an object that was visually distinct. In line with neural evidence that hippocampal functioning and scene processing decline with age, these results suggest that older adults can rely on memory for distinct objects, but not for distinct scenes, to distinguish between memories with overlapping features.

Exploration patterns shape cognitive map learning.

Spontaneous, volitional spatial exploration is crucial for building up a cognitive map of the environment. However, decades of research have primarily measured the fidelity of cognitive maps after discrete, controlled learning episodes. We know little about how cognitive maps are formed during naturalistic free exploration. Here, we investigated whether exploration trajectories predicted cognitive map accuracy, and how these patterns were shaped by environmental structure. In two experiments, participants freely explored a previously unfamiliar virtual environment. We related their exploration trajectories to a measure of how long they spent in areas with high global environmental connectivity (integration, as assessed by space syntax). In both experiments, we found that participants who spent more time on paths that offered opportunities for integration formed more accurate cognitive maps. Interestingly, we found no support for our pre-registered hypothesis that self-reported trait differences in navigation ability would mediate this relationship. Our findings suggest that exploration patterns predict cognitive map accuracy, even for people who self-report low ability, and highlight the importance of considering both environmental structure and individual variability in formal theory- and model-building.

Single voxel autocorrelation uncovers gradients of temporal dynamics in the hippocampus and entorhinal cortex during rest and navigation.

During navigation, information at multiple scales needs to be integrated. Single-unit recordings in rodents suggest that gradients of temporal dynamics in the hippocampus and entorhinal cortex support this integration. In humans, gradients of representation are observed, such that granularity of information represented increases along the long axis of the hippocampus. The neural underpinnings of this gradient in humans, however, are still unknown. Current research is limited by coarse fMRI analysis techniques that obscure the activity of individual voxels, preventing investigation of how moment-to-moment changes in brain signal are organized and how they are related to behavior. Here, we measured the signal stability of single voxels over time to uncover previously unappreciated gradients of temporal dynamics in the hippocampus and entorhinal cortex. Using our novel, single voxel autocorrelation technique, we show a medial-lateral hippocampal gradient, as well as a continuous autocorrelation gradient along the anterolateral-posteromedial entorhinal extent. Importantly, we show that autocorrelation in the anterior-medial hippocampus was modulated by navigational difficulty, providing the first evidence that changes in signal stability in single voxels are relevant for behavior. This work opens the door for future research on how temporal gradients within these structures support the integration of information for goal-directed behavior.

Predictive Representations in Hippocampal and Prefrontal Hierarchies.

As we navigate the world, we use learned representations of relational structures to explore and to reach goals. Studies of how relational knowledge enables inference and planning are typically conducted in controlled small-scale settings. It remains unclear, however, how people use stored knowledge in continuously unfolding navigation (e.g., walking long distances in a city). We hypothesized that multiscale predictive representations guide naturalistic navigation in humans, and these scales are organized along posterior-anterior prefrontal and hippocampal hierarchies. We conducted model-based representational similarity analyses of neuroimaging data collected while male and female participants navigated realistically long paths in virtual reality. We tested the pattern similarity of each point, along each path, to a weighted sum of its successor points within predictive horizons of different scales. We found that anterior PFC showed the largest predictive horizons, posterior hippocampus the smallest, with the anterior hippocampus and orbitofrontal regions in between. Our findings offer novel insights into how cognitive maps support hierarchical planning at multiple scales.SIGNIFICANCE STATEMENT Whenever we navigate the world, we represent our journey at multiple horizons: from our immediate surroundings to our distal goal. How are such cognitive maps at different horizons simultaneously represented in the brain? Here, we applied a reinforcement learning-based analysis to neuroimaging data acquired while participants virtually navigated their hometown. We investigated neural patterns in the hippocampus and PFC, key cognitive map regions. We uncovered predictive representations with multiscale horizons in prefrontal and hippocampal gradients, with the longest predictive horizons in anterior PFC and the shortest in posterior hippocampus. These findings provide empirical support for the computational hypothesis that multiscale neural representations guide goal-directed navigation. This advances our understanding of hierarchical planning in everyday navigation of realistic distances.

Prediction errors disrupt hippocampal representations and update episodic memories.

The brain supports adaptive behavior by generating predictions, learning from errors, and updating memories to incorporate new information. Prediction error, or surprise, triggers learning when reality contradicts expectations. Prior studies have shown that the hippocampus signals prediction errors, but the hypothesized link to memory updating has not been demonstrated. In a human functional MRI study, we elicited mnemonic prediction errors by interrupting familiar narrative videos immediately before the expected endings. We found that prediction errors reversed the relationship between univariate hippocampal activation and memory: greater hippocampal activation predicted memory preservation after expected endings, but memory updating after surprising endings. In contrast to previous studies, we show that univariate activation was insufficient for understanding hippocampal prediction error signals. We explain this surprising finding by tracking both the evolution of hippocampal activation patterns and the connectivity between the hippocampus and neuromodulatory regions. We found that hippocampal activation patterns stabilized as each narrative episode unfolded, suggesting sustained episodic representations. Prediction errors disrupted these sustained representations and the degree of disruption predicted memory updating. The relationship between hippocampal activation and subsequent memory depended on concurrent basal forebrain activation, supporting the idea that cholinergic modulation regulates attention and memory. We conclude that prediction errors create conditions that favor memory updating, prompting the hippocampus to abandon ongoing predictions and make memories malleable.

Structuring Knowledge with Cognitive Maps and Cognitive Graphs.

Humans and animals use mental representations of the spatial structure of the world to navigate. The classical view is that these representations take the form of Euclidean cognitive maps, but alternative theories suggest that they are cognitive graphs consisting of locations connected by paths. We review evidence suggesting that both map-like and graph-like representations exist in the mind/brain that rely on partially overlapping neural systems. Maps and graphs can operate simultaneously or separately, and they may be applied to both spatial and nonspatial knowledge. By providing structural frameworks for complex information, cognitive maps and cognitive graphs may provide fundamental organizing schemata that allow us to navigate in physical, social, and conceptual spaces.

Integration and differentiation of hippocampal memory traces.

Prevailing theories of hippocampal function argue that memories are rapidly encoded by non-overlapping memory traces. Concurrently, the hippocampus has been argued to integrate across related experiences, enabling generalization. The cognitive neuroscience of memory has been transformed by the recent proliferation of studies using pattern similarity analyses to investigate the neural substrates of memory in humans, marking an exciting and significant advance in our understanding of population-level neural representations. We provide an overview of hippocampal pattern similarity studies published to date. By considering the effects of stimulus type, time-scale, and hippocampal subregions, we account for both increases and decreases in representational similarity. We argue that hippocampal representations for related memories are not fixed. Instead, the evoked representations are flexibly modulated, depending on whether the current goal is to extract generalities or to reinstate specific experiences. In the first comprehensive review of hippocampal pattern similarity analyses, we provide insight into the mechanisms of memory representation and implications for the interpretation of pattern similarity more generally.

Turns during navigation act as boundaries that enhance spatial memory and expand time estimation.

Ongoing experience unfolds over time. To segment continuous experience into component events, humans rely on physical and conceptual boundaries. Here we explored the subjective representation of turns along travelled routes as boundaries. Across two experiments, turns selectively enhanced participants' subjective recollection of locations immediately preceding them, compared to their recollection of locations in the middle of a route straightaway or immediately following turns. In Experiment 2, we also observed a subjective expansion of the time spent at pre-turn, relative to post-turn, locations. These results highlight the influence of turns on memory for travelled routes and provide further evidence for a link between subjective episodic re-experiencing and temporal memory. Taken together, this evidence suggests that turns during navigation act much as boundaries do for events, enhancing memory and processing of pre-boundary locations.

Cognitive mapping style relates to posterior-anterior hippocampal volume ratio.

As London taxi drivers acquire "the knowledge" and develop a detailed cognitive map of London, their posterior hippocampi (pHPC) gradually increase in volume, reflecting an increasing pHPC/aHPC volume ratio. In the mnemonic domain, greater pHPC/aHPC volume ratios in young adults have been found to relate to better recollection ability, indicating that the balance between pHPC and aHPC volumes might be reflective of cross-domain individual differences. Here, we examined participants' self-reported use of cognitive map-based navigational strategies in relation to their pHPC/aHPC hippocampal volume ratio. We find that greater reported cognitive map use was related to significantly greater posterior, relative to anterior, hippocampal volume in two separate samples of young adults. Further, greater reported cognitive map usage correlated with better performance on a self-initiated navigation task. Together, these data help to advance our understanding of differences between aHPC and pHPC and the greater role of pHPC in spatial mapping.

Multiple Scales of Representation along the Hippocampal Anteroposterior Axis in Humans.

The ability to represent the world accurately relies on simultaneous coarse and fine-grained neural information coding, capturing both gist and detail of an experience. The longitudinal axis of the hippocampus may provide a gradient of representational granularity in spatial and episodic memory in rodents and humans [1-8]. Rodent place cells in the ventral hippocampus exhibit significantly larger place fields and greater autocorrelation than those in the dorsal hippocampus [1, 9-11], which may underlie a coarser and slower changing representation of space [10, 12]. Recent evidence suggests that properties of cellular dynamics in rodents can be captured with fMRI in humans during spatial navigation [13] and conceptual learning [14]. Similarly, mechanisms supporting granularity along the long axis may also be extrapolated to the scale of fMRI signal. Here, we provide the first evidence for separable scales of representation along the human hippocampal anteroposterior axis during navigation and rest by showing (1) greater similarity among voxel time courses and (2) higher temporal autocorrelation in anterior hippocampus (aHPC), relative to posterior hippocampus (pHPC), the human homologs of ventral and dorsal rodent hippocampus. aHPC voxels exhibited more similar activity at each time point and slower signal change over time than voxels in pHPC, consistent with place field organization in rodents. Importantly, similarity between voxels was related to navigational strategy and episodic memory. These findings provide evidence that the human hippocampus supports an anterior-to-posterior gradient of coarse-to-fine spatiotemporal representations, suggesting the existence of a cross-species mechanism, whereby lower neural similarity supports more complex coding of experience.

Boundaries Shape Cognitive Representations of Spaces and Events.

Efficient navigation from one place to another is facilitated by the ability to use spatial boundaries to segment routes into their component parts. Similarly, memory for individual episodes relies on the ability to use shifts in spatiotemporal contexts to segment the ongoing stream of experience. The segmentation of experiences in spatial and episodic domains may therefore share neural underpinnings, manifesting in similar behavioral phenomena and cognitive biases. Here, we review evidence for such shared mechanisms, focusing on the key role of boundaries in spatial and episodic memory. We propose that a fundamental event boundary detection mechanism enables navigation in both the spatial and episodic domains, and serves to form cohesive representations that can be used to predict and guide future behavior.

Contracted time and expanded space: The impact of circumnavigation on judgements of space and time.

The ability to estimate distance and time to spatial goals is fundamental for survival. In cases where a region of space must be navigated around to reach a location (circumnavigation), the distance along the path is greater than the straight-line Euclidean distance. To explore how such circumnavigation impacts on estimates of distance and time, we tested participants on their ability to estimate travel time and Euclidean distance to learned destinations in a virtual town. Estimates for approximately linear routes were compared with estimates for routes requiring circumnavigation. For all routes, travel times were significantly underestimated, and Euclidean distances overestimated. For routes requiring circumnavigation, travel time was further underestimated and the Euclidean distance further overestimated. Thus, circumnavigation appears to enhance existing biases in representations of travel time and distance.

Recollection-dependent memory for event duration in large-scale spatial navigation.

Time and space represent two key aspects of episodic memories, forming the spatiotemporal context of events in a sequence. Little is known, however, about how temporal information, such as the duration and the order of particular events, are encoded into memory, and if it matters whether the memory representation is based on recollection or familiarity. To investigate this issue, we used a real world virtual reality navigation paradigm where periods of navigation were interspersed with pauses of different durations. Crucially, participants were able to reliably distinguish the durations of events that were subjectively "reexperienced" (i.e., recollected), but not of those that were familiar. This effect was not found in temporal order (ordinal) judgments. We also show that the active experience of the passage of time (holding down a key while waiting) moderately enhanced duration memory accuracy. Memory for event duration, therefore, appears to rely on the hippocampally supported ability to recollect or reexperience an event enabling the reinstatement of both its duration and its spatial context, to distinguish it from other events in a sequence. In contrast, ordinal memory appears to rely on familiarity and recollection to a similar extent.

Chronologically organized structure in autobiographical memory search.

Each of us has a rich set of autobiographical memories that provides us with a coherent story of our lives. These memories are known to be highly structured both thematically and temporally. However, it is not known how we naturally tend to explore the mental timeline of our memories. Here we developed a novel cued retrieval paradigm in order to investigate the temporal element of memory search. We found that, when asked to search for memories in the days immediately surrounding a salient cued event, participants displayed a marked set of temporal biases in their search patterns. Specifically, participants first tended to jump back in time and retrieve memories from the day prior to the cued event. Following this they then transitioned forward in time, and retrieved memories from the day after the cued event. This pattern of results replicated in a second experiment with a much larger group of participants, and a different method of cueing the memories. We argue that this set of temporal biases is consistent with memory search conforming to a temporally ordered narrative structure.

Transcranial electrical brain stimulation modulates neuronal tuning curves in perception of numerosity and duration.

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation method with many putative applications and reported to effectively modulate behaviour. However, its effects have yet to be considered at a computational level. To address this we modelled the tuning curves underlying the behavioural effects of stimulation in a perceptual task. Participants judged which of the two serially presented images contained more items (numerosity judgement task) or was presented longer (duration judgement task). During presentation of the second image their posterior parietal cortices (PPCs) were stimulated bilaterally with opposite polarities for 1.6s. We also examined the impact of three stimulation conditions on behaviour: anodal right-PPC and cathodal left-PPC (rA-lC), reverse order (lA-rC) and no-stimulation condition. Behavioural results showed that participants were more accurate in numerosity and duration judgement tasks when they were stimulated with lA-rC and rA-lC stimulation conditions respectively. Simultaneously, a decrease in performance on numerosity and duration judgement tasks was observed when the stimulation condition favoured the other task. Thus, our results revealed a double-dissociation of laterality and task. Importantly, we were able to model the effects of stimulation on behaviour. Our computational modelling showed that participants' superior performance was attributable to a narrower tuning curve--smaller standard deviation of detection noise. We believe that this approach may prove useful in understanding the impact of brain stimulation on other cognitive domains.