Grid-cell representations in mental simulation

Resting-State Network Plasticity Following Category Learning Depends on Sensory Modality

Learning new categories is fundamental to cognition, occurring in daily life through various sensory modalities. However, it is not well known how acquiring new categories can modulate the brain networks. Resting-state functional connectivity is an effective method for detecting short-term brain alterations induced by various modality-based learning experiences. Using fMRI, our study investigated the intricate link between novel category learning and brain network reorganization. Eighty-four adults participated in an object categorization experiment utilizing visual (n = 41, with 20 females and a mean age of 23.91 ± 3.11 years) or tactile (n = 43, with 21 females and a mean age of 24.57 ± 2.58 years) modalities. Resting-state networks (RSNs) were identified using independent component analysis across the group of participants, and their correlation with individual differences in object category learning across modalities was examined using dual regression. Our results reveal an increased functional connectivity of the frontoparietal network with the left superior frontal gyrus in visual category learning task and with the right superior occipital gyrus and the left middle temporal gyrus after tactile category learning. Moreover, the somatomotor network demonstrated an increased functional connectivity with the left parahippocampus exclusively after tactile category learning. These findings illuminate the neural mechanisms of novel category learning, emphasizing distinct brain networks' roles in diverse modalities. The dynamic nature of RSNs emphasizes the ongoing adaptability of the brain, which is essential for efficient novel object category learning. This research provides valuable insights into the dynamic interplay between sensory learning, brain plasticity, and network reorganization, advancing our understanding of cognitive processes across different modalities.

Improved Navigation Performance Through Memory Triggering Maps: A Neurocartographic Approach

When using navigation devices the "cognitive map" created in the user's mind is much more fragmented, incomplete and inaccurate, compared to the mental model of space created when reading a conventional printed map. As users become more dependent on digital devices that reduce orientation skills, there is an urgent need to develop more efficient navigation systems that promote orientation skills. This paper proposes to consider brain processes for creating more efficient maps that use a network of optimally located cardinal lines and landmarks organized to support and stabilize the neurocognitive structures in the brain that promote spatial orientation. This new approach combines neurocognitive insights with classical research on the efficiency of cartographic visualizations. Recent neuroscientific findings show that spatially tuned neurons could be linked to navigation processes. In particular, the activity of grid cells, which appear to be used to process metric information about space, can be influenced by environmental stimuli such as walls or boundaries. Grid cell activity could be used to create a new framework for map-based interfaces that primarily considers the brain structures associated with the encoding and retrieval of spatial information. The new framework proposed in this paper suggests to arrange map symbols in a specific way that the map design helps to stabilize grid cell firing in the brain and by this improve spatial orientation and navigational performance. Spatially oriented cells are active in humans not only when moving in space, but also when imagining moving through an area-such as when reading a map. It seems likely that the activity of grid cells can be stabilized simply by map symbols that are perceived when reading a map.

Quantitative modeling of the emergence of macroscopic grid-like representations

When subjects navigate through spatial environments, grid cells exhibit firing fields that are arranged in a triangular grid pattern. Direct recordings of grid cells from the human brain are rare. Hence, functional magnetic resonance imaging (fMRI) studies proposed an indirect measure of entorhinal grid-cell activity, quantified as hexadirectional modulation of fMRI activity as a function of the subject's movement direction. However, it remains unclear how the activity of a population of grid cells may exhibit hexadirectional modulation. Here, we use numerical simulations and analytical calculations to suggest that this hexadirectional modulation is best explained by head-direction tuning aligned to the grid axes, whereas it is not clearly supported by a bias of grid cells toward a particular phase offset. Firing-rate adaptation can result in hexadirectional modulation, but the available cellular data is insufficient to clearly support or refute this option. The magnitude of hexadirectional modulation furthermore depends considerably on the subject's navigation pattern, indicating that future fMRI studies could be designed to test which hypothesis most likely accounts for the fMRI measure of grid cells. Our findings also underline the importance of quantifying the properties of human grid cells to further elucidate how hexadirectional modulations of fMRI activity may emerge.

Spatial memory and learning: investigating the role of dynamic visual acuity

Introduction

The vestibular system's contribution to spatial learning and memory abilities may be clarified using the virtual Morris Water Maze Task (vMWMT). This is important because of the connections between the vestibular system and the hippocampus area. However, there is ongoing debate over the role of the vestibular system in developing spatial abilities. This study aimed to evaluate the relationship between Dynamic Visual Acuity (DVA) across three planes and spatial abilities.

Methods

This cross-sectional study was conducted with 50 healthy adults aged 18 to 55 with normal stress levels and mental health and no neurological, audiological, or vestibular complaints. The Trail-Making Test (TMT) Forms A and B for the assessment of executive functions, the DVA test battery for the evaluation of visual motor functions, and the Virtual Morris Water Maze Test (vMWMT) for the assessment of spatial learning and spatial memory were performed. All participants also underwent the Benton Face Recognition Test (BFRT) and Digit Symbol Substitution Tests (DSST) to assess their relation with spatial memory.

Results

DVA values in horizontal (H-DVA), vertical (V-DVA), and sagittal (S-DVA) planes ranged from (-0.26) to 0.36 logMAR, (-0.20) to 0.36 logMAR, and (-0.28) to 0.33 logMAR, respectively. The latency of three planes of DVA was affected by vMWMT (Horizontal, Vertical, and Sagittal; Estimate: 22.733, 18.787, 13.341, respectively p < 0.001). Moreover, a moderately significant correlation was also found, with a value of 0.571 between the Virtual MWM test and BFRT and a value of 0.539 between the DSST (p < 0.001).

Conclusion

Spatial abilities in healthy adults were significantly influenced by dynamic visual functions across horizontal, vertical, and sagittal planes. These findings are expected to trigger essential discussions about the mechanisms that connect the vestibular-visual system to the hippocampus. The original vMWMT protocol is likely to serve as a model for future studies utilizing this technology.

Distance and grid-like codes support the navigation of abstract social space in the human brain

People form impressions about others during daily social encounters and infer personality traits from others' behaviors. Such trait inference is thought to rely on two universal dimensions: competence and warmth. These two dimensions can be used to construct a 'social cognitive map' organizing massive information obtained from social encounters efficiently. Originating from spatial cognition, the neural codes supporting the representation and navigation of spatial cognitive maps have been widely studied. Recent studies suggest similar neural mechanism subserves the map-like architecture in social cognition as well. Here we investigated how spatial codes operate beyond the physical environment and support the representation and navigation of social cognitive map. We designed a social value space defined by two dimensions of competence and warmth. Behaviorally, participants were able to navigate to a learned location from random starting locations in this abstract social space. At the neural level, we identified the representation of distance in the precuneus, fusiform gyrus, and middle occipital gyrus. We also found partial evidence of grid-like representation patterns in the medial prefrontal cortex and entorhinal cortex. Moreover, the intensity of grid-like response scaled with the performance of navigating in social space and social avoidance trait scores. Our findings suggest a neurocognitive mechanism by which social information can be organized into a structured representation, namely cognitive map and its relevance to social well-being.

Mental navigation in the primate entorhinal cortex

A cognitive map is a suitably structured representation that enables novel computations using previous experience; for example, planning a new route in a familiar space1. Work in mammals has found direct evidence for such representations in the presence of exogenous sensory inputs in both spatial2,3 and non-spatial domains4-10. Here we tested a foundational postulate of the original cognitive map theory1,11: that cognitive maps support endogenous computations without external input. We recorded from the entorhinal cortex of monkeys in a mental navigation task that required the monkeys to use a joystick to produce one-dimensional vectors between pairs of visual landmarks without seeing the intermediate landmarks. The ability of the monkeys to perform the task and generalize to new pairs indicated that they relied on a structured representation of the landmarks. Task-modulated neurons exhibited periodicity and ramping that matched the temporal structure of the landmarks and showed signatures of continuous attractor networks12,13. A continuous attractor network model of path integration14 augmented with a Hebbian-like learning mechanism provided an explanation of how the system could endogenously recall landmarks. The model also made an unexpected prediction that endogenous landmarks transiently slow path integration, reset the dynamics and thereby reduce variability. This prediction was borne out in a reanalysis of firing rate variability and behaviour. Our findings link the structured patterns of activity in the entorhinal cortex to the endogenous recruitment of a cognitive map during mental navigation.

Forming cognitive maps for abstract spaces: the roles of the human hippocampus and orbitofrontal cortex

How does the human brain construct cognitive maps for decision-making and inference? Here, we conduct an fMRI study on a navigation task in multidimensional abstract spaces. Using a deep neural network model, we assess learning levels and categorized paths into exploration and exploitation stages. Univariate analyses show higher activation in the bilateral hippocampus and lateral prefrontal cortex during exploration, positively associated with learning level and response accuracy. Conversely, the bilateral orbitofrontal cortex (OFC) and retrosplenial cortex show higher activation during exploitation, negatively associated with learning level and response accuracy. Representational similarity analysis show that the hippocampus, entorhinal cortex, and OFC more accurately represent destinations in exploitation than exploration stages. These findings highlight the collaboration between the medial temporal lobe and prefrontal cortex in learning abstract space structures. The hippocampus may be involved in spatial memory formation and representation, while the OFC integrates sensory information for decision-making in multidimensional abstract spaces.

Altered grid-like coding in early blind people

Cognitive maps in the hippocampal-entorhinal system are central for the representation of both spatial and non-spatial relationships. Although this system, especially in humans, heavily relies on vision, the role of visual experience in shaping the development of cognitive maps remains largely unknown. Here, we test sighted and early blind individuals in both imagined navigation in fMRI and real-world navigation. During imagined navigation, the Human Navigation Network, constituted by frontal, medial temporal, and parietal cortices, is reliably activated in both groups, showing resilience to visual deprivation. However, neural geometry analyses highlight crucial differences between groups. A 60° rotational symmetry, characteristic of a hexagonal grid-like coding, emerges in the entorhinal cortex of sighted but not blind people, who instead show a 90° (4-fold) symmetry, indicative of a square grid. Moreover, higher parietal cortex activity during navigation in blind people correlates with the magnitude of 4-fold symmetry. In sum, early blindness can alter the geometry of entorhinal cognitive maps, possibly as a consequence of higher reliance on parietal egocentric coding during navigation.

Changes in spatial self-consciousness elicit grid cell-like representation in the entorhinal cortex

Grid cells in the entorhinal cortex (EC) encode an individual's location in space, integrating both environmental and multisensory bodily cues. Notably, body-derived signals are also primary signals for the sense of self. While studies have demonstrated that continuous application of visuo-tactile bodily stimuli can induce perceptual shifts in self-location, it remains unexplored whether these illusory changes suffice to trigger grid cell-like representation (GCLR) within the EC, and how this compares to GCLR during conventional virtual navigation. To address this, we systematically induced illusory drifts in self-location toward controlled directions using visuo-tactile bodily stimulation, while maintaining the subjects' visual viewpoint fixed (absent conventional virtual navigation). Subsequently, we evaluated the corresponding GCLR in the EC through functional MRI analysis. Our results reveal that illusory changes in perceived self-location (independent of changes in environmental navigation cues) can indeed evoke entorhinal GCLR, correlating in strength with the magnitude of perceived self-location, and characterized by similar grid orientation as during conventional virtual navigation in the same virtual room. These data demonstrate that the same grid-like representation is recruited when navigating based on environmental, mainly visual cues, or when experiencing illusory forward drifts in self-location, driven by perceptual multisensory bodily cues.

Self-esteem mediates the relationship between the parahippocampal gyrus and decisional procrastination at resting state

When faced with a conflict or dilemma, we tend to postpone or even avoid making a decision. This phenomenon is known as decisional procrastination. Here, we investigated the neural correlates of this phenomenon, in particular the parahippocampal gyrus (PHG) that has previously been identified in procrastination studies. In this study, we applied an individual difference approach to evaluate participants' spontaneous neural activity in the PHG and their decisional procrastination levels, assessed outside the fMRI scanner. We discovered that the fractional amplitude of low-frequency fluctuations (fALFF) in the caudal PHG (cPHG) could predict participants' level of decisional procrastination, as measured by the avoidant decision-making style. Importantly, participants' self-esteem mediated the relationship between the cPHG and decisional procrastination, suggesting that individuals with higher levels of spontaneous activity in the cPHG are likely to have higher levels of self-esteem and thus be more likely to make decisions on time. In short, our study broadens the PHG's known role in procrastination by demonstrating its link with decisional procrastination and the mediating influence of self-esteem, underscoring the need for further exploration of this mediation mechanism.

Advantages of Persistent Cohomology in Estimating Animal Location From Grid Cell Population Activity

Many cognitive functions are represented as cell assemblies. In the case of spatial navigation, the population activity of place cells in the hippocampus and grid cells in the entorhinal cortex represents self-location in the environment. The brain cannot directly observe self-location information in the environment. Instead, it relies on sensory information and memory to estimate self-location. Therefore, estimating low-dimensional dynamics, such as the movement trajectory of an animal exploring its environment, from only the high-dimensional neural activity is important in deciphering the information represented in the brain. Most previous studies have estimated the low-dimensional dynamics (i.e., latent variables) behind neural activity by unsupervised learning with Bayesian population decoding using artificial neural networks or gaussian processes. Recently, persistent cohomology has been used to estimate latent variables from the phase information (i.e., circular coordinates) of manifolds created by neural activity. However, the advantages of persistent cohomology over Bayesian population decoding are not well understood. We compared persistent cohomology and Bayesian population decoding in estimating the animal location from simulated and actual grid cell population activity. We found that persistent cohomology can estimate the animal location with fewer neurons than Bayesian population decoding and robustly estimate the animal location from actual noisy data.

Grid-like entorhinal representation of an abstract value space during prospective decision making

How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming a trajectory through an abstract two-dimensional value space. During this task, the entorhinal cortex exhibited a grid-like representation with an orientation aligned to the axis through the value space most informative for choices. A network of brain regions, including ventromedial prefrontal cortex, tracked the prospective value difference between options. These findings suggest that the entorhinal grid system supports the prediction of future values by representing a cognitive map, which might be used to generate lower-dimensional value signals to guide prospective decision making.

Grid codes underlie multiple cognitive maps in the human brain

Grid cells fire at multiple positions that organize the vertices of equilateral triangles tiling a 2D space and are well studied in rodents. The last decade witnessed rapid progress in two other research lines on grid codes-empirical studies on distributed human grid-like representations in physical and multiple non-physical spaces, and cognitive computational models addressing the function of grid cells based on principles of efficient and predictive coding. Here, we review the progress in these fields and integrate these lines into a systematic organization. We also discuss the coordinate mechanisms of grid codes in the human entorhinal cortex and medial prefrontal cortex and their role in neurological and psychiatric diseases.

Mental search of concepts is supported by egocentric vector representations and restructured grid maps

The human hippocampal-entorhinal system is known to represent both spatial locations and abstract concepts in memory in the form of allocentric cognitive maps. Using fMRI, we show that the human parietal cortex evokes complementary egocentric representations in conceptual spaces during goal-directed mental search, akin to those observable during physical navigation to determine where a goal is located relative to oneself (e.g., to our left or to our right). Concurrently, the strength of the grid-like signal, a neural signature of allocentric cognitive maps in entorhinal, prefrontal, and parietal cortices, is modulated as a function of goal proximity in conceptual space. These brain mechanisms might support flexible and parallel readout of where target conceptual information is stored in memory, capitalizing on complementary reference frames.

Physical Body Orientation Impacts Virtual Navigation Experience and Performance

Most human navigation studies in MRI rely on virtual navigation. However, the necessary supine position in MRI makes it fundamentally different from daily ecological navigation. Nonetheless, until now, no study has assessed whether differences in physical body orientation (BO) affect participants' experienced BO during virtual navigation. Here, combining an immersive virtual reality navigation task with subjective BO measures and implicit behavioral measures, we demonstrate that physical BO (either standing or supine) modulates experienced BO. Also, we show that standing upright BO is preferred during spatial navigation: participants were more likely to experience a standing BO and were better at spatial navigation when standing upright. Importantly, we report that showing a supine virtual agent reduces the conflict between the preferred BO and physical supine BO. Our study provides critical, but missing, information regarding experienced BO during virtual navigation, which should be considered cautiously when designing navigation studies, especially in MRI.

Recruitment of grid-like responses in human entorhinal and piriform cortices by odor landmark-based navigation

Olfactory navigation is universal across the animal kingdom. Humans, however, have rarely been considered in this context. Here, we combined olfactometry techniques, virtual reality (VR) software, and neuroimaging methods to investigate whether humans can navigate an olfactory landscape by learning the spatial relationships among discrete odor cues and integrating this knowledge into a spatial map. Our data show that over time, participants improved their performance on the odor navigation task by taking more direct paths toward targets and completing more trials within a given time period. This suggests that humans can successfully navigate a complex odorous environment, reinforcing the notion of human olfactory navigation. fMRI data collected during the olfactory navigation task revealed the emergence of grid-like responses in entorhinal and piriform cortices that were attuned to the same grid orientation. This result implies the existence of a specialized olfactory grid network tasked with guiding spatial navigation based on odor landmarks.

Effects of Acute Stress on Rigid Learning, Flexible Learning, and Value-Based Decision-Making in Spatial Navigation

The current study investigated how stress affects value-based decision-making during spatial navigation and different types of learning underlying decisions. Eighty-two adult participants (42 females) first learned to find object locations in a virtual environment from a fixed starting location (rigid learning) and then to find the same objects from unpredictable starting locations (flexible learning). Participants then decided whether to reach goal objects from the fixed or unpredictable starting location. We found that stress impairs rigid learning in females, and it does not impair, and even improves, flexible learning when performance with rigid learning is controlled for. Critically, examining how earlier learning influences subsequent decision-making using computational models, we found that stress reduces memory integration, making participants more likely to focus on recent memory and less likely to integrate information from other sources. Collectively, our results show how stress impacts different memory systems and the communication between memory and decision-making.

Concepts as plug & play devices

Research on concepts has focused on categorization. Categorization starts with a stimulus. Equally important are episodes that start with a thought. We engage in thinking to draw out new consequences from stored information, or to work out how to act. Each of the concepts out of which thought is constructed provides access to a large body of stored information. Access is not always just a matter of retrieving a stored belief (semantic memory). Often it depends on running a simulation. Simulation allows conceptual thought to draw on information in special-purpose systems, information stored in special-purpose computational dispositions and special-purpose representational structures. While the utility of simulation, prospection or imagination is widely appreciated, the role of concepts in the process is not well understood. This paper turns to cognitive and computational neuroscience for a model of how simulations enable thinkers to reach novel conclusions. Carried over to conceptual thought, the model suggests that concepts are 'plug & play' devices. The distinctive power of thought-driven simulation derives from the ability of concepts to plug into two kinds of structure at once: the combinatorial structure of a thought at one end and special-purpose structural representations at the other. This article is part of the theme issue 'Concepts in interaction: social engagement and inner experiences'.

Entorhinal grid-like codes and time-locked network dynamics track others navigating through space

Navigating through crowded, dynamically changing environments requires the ability to keep track of other individuals. Grid cells in the entorhinal cortex are a central component of self-related navigation but whether they also track others' movement is unclear. Here, we propose that entorhinal grid-like codes make an essential contribution to socio-spatial navigation. Sixty human participants underwent functional magnetic resonance imaging (fMRI) while observing and re-tracing different paths of a demonstrator that navigated a virtual reality environment. Results revealed that grid-like codes in the entorhinal cortex tracked the other individual navigating through space. The activity of grid-like codes was time-locked to increases in co-activation and entorhinal-cortical connectivity that included the striatum, the hippocampus, parahippocampal and right posterior parietal cortices. Surprisingly, the grid-related effects during observation were stronger the worse participants performed when subsequently re-tracing the demonstrator's paths. Our findings suggests that network dynamics time-locked to entorhinal grid-cell-related activity might serve to distribute information about the location of others throughout the brain.

Spatial memory deficits in Alzheimer's disease and their connection to cognitive maps' formation by place cells and grid cells

Whenever we navigate through different contexts, we build a cognitive map: an internal representation of the territory. Spatial navigation is a complex skill that involves multiple types of information processing and integration. Place cells and grid cells, collectively with other hippocampal and medial entorhinal cortex neurons (MEC), form a neural network whose activity is critical for the representation of self-position and orientation along with spatial memory retrieval. Furthermore, this activity generates new representations adapting to changes in the environment. Though there is a normal decline in spatial memory related to aging, this is dramatically increased in pathological conditions such as Alzheimer's disease (AD). AD is a multi-factorial neurodegenerative disorder affecting mainly the hippocampus-entorhinal cortex (HP-EC) circuit. Consequently, the initial stages of the disease have disorientation and wandering behavior as two of its hallmarks. Recent electrophysiological studies have linked spatial memory deficits to difficulties in spatial information encoding. Here we will discuss map impairment and remapping disruption in the HP-EC network, as a possible circuit mechanism involved in the spatial memory and navigation deficits observed in AD, pointing out the benefits of virtual reality as a tool for early diagnosis and rehabilitation.

A unified theory for the computational and mechanistic origins of grid cells

The discovery of entorhinal grid cells has generated considerable interest in how and why hexagonal firing fields might emerge in a generic manner from neural circuits, and what their computational significance might be. Here, we forge a link between the problem of path integration and the existence of hexagonal grids, by demonstrating that such grids arise in neural networks trained to path integrate under simple biologically plausible constraints. Moreover, we develop a unifying theory for why hexagonal grids are ubiquitous in path-integrator circuits. Such trained networks also yield powerful mechanistic hypotheses, exhibiting realistic levels of biological variability not captured by hand-designed models. We furthermore develop methods to analyze the connectome and activity maps of our networks to elucidate fundamental mechanisms underlying path integration. These methods provide a road map to go from connectomic and physiological measurements to conceptual understanding in a manner that could generalize to other settings.

Integrated world modeling theory expanded: Implications for the future of consciousness

Integrated world modeling theory (IWMT) is a synthetic theory of consciousness that uses the free energy principle and active inference (FEP-AI) framework to combine insights from integrated information theory (IIT) and global neuronal workspace theory (GNWT). Here, I first review philosophical principles and neural systems contributing to IWMT's integrative perspective. I then go on to describe predictive processing models of brains and their connections to machine learning architectures, with particular emphasis on autoencoders (perceptual and active inference), turbo-codes (establishment of shared latent spaces for multi-modal integration and inferential synergy), and graph neural networks (spatial and somatic modeling and control). Future directions for IIT and GNWT are considered by exploring ways in which modules and workspaces may be evaluated as both complexes of integrated information and arenas for iterated Bayesian model selection. Based on these considerations, I suggest novel ways in which integrated information might be estimated using concepts from probabilistic graphical models, flow networks, and game theory. Mechanistic and computational principles are also considered with respect to the ongoing debate between IIT and GNWT regarding the physical substrates of different kinds of conscious and unconscious phenomena. I further explore how these ideas might relate to the "Bayesian blur problem," or how it is that a seemingly discrete experience can be generated from probabilistic modeling, with some consideration of analogies from quantum mechanics as potentially revealing different varieties of inferential dynamics. I go on to describe potential means of addressing critiques of causal structure theories based on network unfolding, and the seeming absurdity of conscious expander graphs (without cybernetic symbol grounding). Finally, I discuss future directions for work centered on attentional selection and the evolutionary origins of consciousness as facilitated "unlimited associative learning." While not quite solving the Hard problem, this article expands on IWMT as a unifying model of consciousness and the potential future evolution of minds.

Human Variation in Error-Based and Reinforcement Motor Learning Is Associated With Entorhinal Volume

Error-based and reward-based processes are critical for motor learning and are thought to be mediated via distinct neural pathways. However, recent behavioral work in humans suggests that both learning processes can be bolstered by the use of cognitive strategies, which may mediate individual differences in motor learning ability. It has been speculated that medial temporal lobe regions, which have been shown to support motor sequence learning, also support the use of cognitive strategies in error-based and reinforcement motor learning. However, direct evidence in support of this idea remains sparse. Here we first show that better overall learning during error-based visuomotor adaptation is associated with better overall learning during the reward-based shaping of reaching movements. Given the cognitive contribution to learning in both of these tasks, these results support the notion that strategic processes, associated with better performance, drive intersubject variation in both error-based and reinforcement motor learning. Furthermore, we show that entorhinal cortex volume is larger in better learning individuals-characterized across both motor learning tasks-compared with their poorer learning counterparts. These results suggest that individual differences in learning performance during error and reinforcement learning are related to neuroanatomical differences in entorhinal cortex.

Are Grid-Like Representations a Component of All Perception and Cognition?

Grid cells or grid-like responses have been reported in the rodent, bat and human brains during various spatial and non-spatial tasks. However, the functions of grid-like representations beyond the classical hippocampal formation remain elusive. Based on accumulating evidence from recent rodent recordings and human fMRI data, we make speculative accounts regarding the mechanisms and functional significance of the sensory cortical grid cells and further make theory-driven predictions. We argue and reason the rationale why grid responses may be universal in the brain for a wide range of perceptual and cognitive tasks that involve locomotion and mental navigation. Computational modeling may provide an alternative and complementary means to investigate the grid code or grid-like map. We hope that the new discussion will lead to experimentally testable hypotheses and drive future experimental data collection.

Sense of self impacts spatial navigation and hexadirectional coding in human entorhinal cortex

Grid cells in entorhinal cortex (EC) encode an individual's location in space and rely on environmental cues and self-motion cues derived from the individual's body. Body-derived signals are also primary signals for the sense of self and based on integrated sensorimotor signals (proprioceptive, tactile, visual, motor) that have been shown to enhance self-centered processing. However, it is currently unknown whether such sensorimotor signals that modulate self-centered processing impact grid cells and spatial navigation. Integrating the online manipulation of bodily signals, to modulate self-centered processing, with a spatial navigation task and an fMRI measure to detect grid cell-like representation (GCLR) in humans, we report improved performance in spatial navigation and decreased GCLR in EC. This decrease in entorhinal GCLR was associated with an increase in retrosplenial cortex activity, which was correlated with participants' navigation performance. These data link self-centered processes during spatial navigation to entorhinal and retrosplenial activity and highlight the role of different bodily factors at play when navigating in VR.

A Brave New World: Virtual Reality and Augmented Reality in Systems Biology

How we interact with computer graphics has not changed significantly from viewing 2D text and images on a flatscreen since their invention. Yet, recent advances in computing technology, internetworked devices and gaming are driving the design and development of new ideas in other modes of human-computer interfaces (HCIs). Virtual Reality (VR) technology uses computers and HCIs to create the feeling of immersion in a three-dimensional (3D) environment that contains interactive objects with a sense of spatial presence, where objects have a spatial location relative to, and independent of the users. While this virtual environment does not necessarily match the real world, by creating the illusion of reality, it helps users leverage the full range of human sensory capabilities. Similarly, Augmented Reality (AR), superimposes virtual images to the real world. Because humans learn the physical world through a gradual sensory familiarization, these immersive visualizations enable gaining familiarity with biological systems not realizable in the physical world (e.g., allosteric regulatory networks within a protein or biomolecular pathways inside a cell). As VR/AR interfaces are anticipated to be explosive in consumer markets, systems biologists will be more immersed into their world. Here we introduce a brief history of VR/AR, their current roles in systems biology, and advantages and disadvantages in augmenting user abilities. We next argue that in systems biology, VR/AR technologies will be most useful in visually exploring and communicating data; performing virtual experiments; and education/teaching. Finally, we discuss our perspective on future directions for VR/AR in systems biology.

Spatial goal coding in the hippocampal formation

The mammalian hippocampal formation contains several distinct populations of neurons involved in representing self-position and orientation. These neurons, which include place, grid, head direction, and boundary-vector cells, are thought to collectively instantiate cognitive maps supporting flexible navigation. However, to flexibly navigate, it is necessary to also maintain internal representations of goal locations, such that goal-directed routes can be planned and executed. Although it has remained unclear how the mammalian brain represents goal locations, multiple neural candidates have recently been uncovered during different phases of navigation. For example, during planning, sequential activation of spatial cells may enable simulation of future routes toward the goal. During travel, modulation of spatial cells by the prospective route, or by distance and direction to the goal, may allow maintenance of route and goal-location information, supporting navigation on an ongoing basis. As the goal is approached, an increased activation of spatial cells may enable the goal location to become distinctly represented within cognitive maps, aiding goal localization. Lastly, after arrival at the goal, sequential activation of spatial cells may represent the just-taken route, enabling route learning and evaluation. Here, we review and synthesize these and other evidence for goal coding in mammalian brains, relate the experimental findings to predictions from computational models, and discuss outstanding questions and future challenges.

Spatialization of Time in the Entorhinal-Hippocampal System

The functional role of the entorhinal-hippocampal system has been a long withstanding mystery. One key theory that has become most popular is that the entorhinal-hippocampal system represents space to facilitate navigation in one's surroundings. In this Perspective article, I introduce a novel idea that undermines the inherent uniqueness of spatial information in favor of time driving entorhinal-hippocampal activity. Specifically, by spatializing events that occur in succession (i.e., across time), the entorhinal-hippocampal system is critical for all types of cognitive representations. I back up this argument with empirical evidence that hints at a role for the entorhinal-hippocampal system in non-spatial representation, and computational models of the logarithmic compression of time in the brain.

Structural connectivity-based segmentation of the human entorhinal cortex

The medial (MEC) and lateral entorhinal cortex (LEC), widely studied in rodents, are well defined and characterized. In humans, however, the exact locations of their homologues remain uncertain. Previous functional magnetic resonance imaging (fMRI) studies have subdivided the human EC into posteromedial (pmEC) and anterolateral (alEC) parts, but uncertainty remains about the choice of imaging modality and seed regions, in particular in light of a substantial revision of the classical model of EC connectivity based on novel insights from rodent anatomy. Here, we used structural, not functional imaging, namely diffusion tensor imaging (DTI) and probabilistic tractography to segment the human EC based on differential connectivity to other brain regions known to project selectively to MEC or LEC. We defined MEC as more strongly connected with presubiculum and retrosplenial cortex (RSC), and LEC as more strongly connected with distal CA1 and proximal subiculum (dCA1pSub) and lateral orbitofrontal cortex (OFC). Although our DTI segmentation had a larger medial-lateral component than in the previous fMRI studies, our results show that the human MEC and LEC homologues have a border oriented both towards the posterior-anterior and medial-lateral axes, supporting the differentiation between pmEC and alEC.

The neural representation of absolute direction during mental navigation in conceptual spaces

When humans mentally “navigate” bidimensional uniform conceptual spaces, they recruit the same grid-like and distance codes typically evoked when exploring the physical environment. Here, using fMRI, we show evidence that conceptual navigation also elicits another kind of spatial code: that of absolute direction. This code is mostly localized in the medial parietal cortex, where its strength predicts participants’ comparative semantic judgments. It may provide a complementary mechanism for conceptual navigation outside the hippocampal formation.

Viganò et al. use fMRI in healthy human participants to show that conceptual navigation elicits a spatial code for absolute direction in the medial parietal cortex. Their findings are suggestive of a complementary mechanism for conceptual navigation outside the hippocampal formation.

Hippocampal contributions to social and cognitive deficits in autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by hallmark impairments in social functioning. Nevertheless, nonsocial cognition, including hippocampus-dependent spatial reasoning and episodic memory, is also commonly impaired in ASD. ASD symptoms typically emerge between 12 and 24 months of age, a time window associated with critical developmental events in the hippocampus. Despite this temporal overlap and evidence of hippocampal structural abnormalities in ASD individuals, relatively few human studies have focused on hippocampal function in ASD. Herein, we review the existing evidence for the involvement of the hippocampus in ASD and highlight the hippocampus as a promising area of interest for future research in ASD.

Using your nose to find your way: Ethological comparisons between human and non-human species

Olfaction is arguably the least valued among our sensory systems, and its significance for human behavior is often neglected. Spatial navigation represents no exception to the rule: humans are often characterized as purely visual navigators, a view that undermines the contribution of olfactory cues. Accordingly, research investigating whether and how humans use olfaction to navigate space is rare. In comparison, research on olfactory navigation in non-human species is abundant, and identifies behavioral strategies along with neural mechanisms characterizing the use of olfactory cues during spatial tasks. Using an ethological approach, our review draws from studies on olfactory navigation across species to describe the adaptation of strategies under the influence of selective pressure. Mammals interact with spatial environments by abstracting multisensory information into cognitive maps. We thus argue that olfactory cues, alongside inputs from other sensory modalities, play a crucial role in spatial navigation for mammalian species, including humans; that is, odors constitute one of the many building blocks in the formation of cognitive maps.

How do we generalize?

Humans and animals are able to generalize or transfer information from previous experience so that they can behave appropriately in novel situations. What mechanisms-computations, representations, and neural systems-give rise to this remarkable ability? The members of this Generative Adversarial Collaboration (GAC) come from a range of academic backgrounds but are all interested in uncovering the mechanisms of generalization. We started out this GAC with the aim of arbitrating between two alternative conceptual accounts: (1) generalization stems from integration of multiple experiences into summary representations that reflect generalized knowledge, and (2) generalization is computed on-the-fly using separately stored individual memories. Across the course of this collaboration, we found that-despite using different terminology and techniques, and although some of our specific papers may provide evidence one way or the other-we in fact largely agree that both of these broad accounts (as well as several others) are likely valid. We believe that future research and theoretical synthesis across multiple lines of research is necessary to help determine the degree to which different candidate generalization mechanisms may operate simultaneously, operate on different scales, or be employed under distinct conditions. Here, as the first step, we introduce some of these candidate mechanisms and we discuss the issues currently hindering better synthesis of generalization research. Finally, we introduce some of our own research questions that have arisen over the course of this GAC, that we believe would benefit from future collaborative efforts.

Human brain dynamics in active spatial navigation

Spatial navigation is a complex cognitive process based on multiple senses that are integrated and processed by a wide network of brain areas. Previous studies have revealed the retrosplenial complex (RSC) to be modulated in a task-related manner during navigation. However, these studies restricted participants' movement to stationary setups, which might have impacted heading computations due to the absence of vestibular and proprioceptive inputs. Here, we present evidence of human RSC theta oscillation (4-8 Hz) in an active spatial navigation task where participants actively ambulated from one location to several other points while the position of a landmark and the starting location were updated. The results revealed theta power in the RSC to be pronounced during heading changes but not during translational movements, indicating that physical rotations induce human RSC theta activity. This finding provides a potential evidence of head-direction computation in RSC in healthy humans during active spatial navigation.

Remapping and realignment in the human hippocampal formation predict context-dependent spatial behavior

To guide spatial behavior, the brain must retrieve memories that are appropriately associated with different navigational contexts. Contextual memory might be mediated by cell ensembles in the hippocampal formation that alter their responses to changes in context, processes known as remapping and realignment in the hippocampus and entorhinal cortex, respectively. However, whether remapping and realignment guide context-dependent spatial behavior is unclear. To address this issue, human participants learned object-location associations within two distinct virtual reality environments and subsequently had their memory tested during functional MRI (fMRI) scanning. Entorhinal grid-like representations showed realignment between the two contexts, and coincident changes in fMRI activity patterns consistent with remapping were observed in the hippocampus. Critically, in a third ambiguous context, trial-by-trial remapping and realignment in the hippocampal-entorhinal network predicted context-dependent behavior. These results reveal the hippocampal-entorhinal mechanisms mediating human contextual memory and suggest that the hippocampal formation plays a key role in spatial behavior under uncertainty.

Spatial Integration in Normal Face Processing and Its Breakdown in Congenital Prosopagnosia

Congenital prosopagnosia (CP), a life-long impairment in face processing that occurs in the absence of any apparent brain damage, provides a unique model in which to explore the psychological and neural bases of normal face processing. The goal of this review is to offer a theoretical and conceptual framework that may account for the underlying cognitive and neural deficits in CP. This framework may also provide a novel perspective in which to reconcile some conflicting results that permits the expansion of the research in this field in new directions. The crux of this framework lies in linking the known behavioral and neural underpinnings of face processing and their impairments in CP to a model incorporating grid cell-like activity in the entorhinal cortex. Moreover, it stresses the involvement of active, spatial scanning of the environment with eye movements and implicates their critical role in face encoding and recognition. To begin with, we describe the main behavioral and neural characteristics of CP, and then lay down the building blocks of our proposed model, referring to the existing literature supporting this new framework. We then propose testable predictions and conclude with open questions for future research stemming from this model. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

What are grid-like responses doing in the orbitofrontal cortex?

In 2005, the Moser group identified a new type of cell in the entorhinal cortex (ERC): the grid cell (Hafting, Nature, 436, 2005, pp. 801-806). A landmark series of studies from these investigators showed that grid cells support spatial navigation by encoding position, direction as well as distance information, and they subsequently found grid cells in pre- and para-subiculum areas adjacent to the ERC (Boccara, Nature Neuroscience, 13, 2010, pp. 987-994). Fast forward to 2010, when some clever investigators developed fMRI analysis methods to document grid-like responses in the human ERC (Doeller, Nature, 463, 2010, pp. 657-661). What was not at all expected was the co-identification of grid-like fMRI responses outside of the ERC, in particular, the orbitofrontal cortex (OFC) and the ventromedial prefrontal cortex (vmPFC). Here we provide a compact overview of the burgeoning literature on grid cells in both rodent and human species, while considering the intriguing question: what are grid-like responses doing in the OFC and vmPFC? (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Grid-like and distance codes for representing word meaning in the human brain

Relational information about items in memory is thought to be represented in our brain thanks to an internal comprehensive model, also referred to as a "cognitive map". In the human neuroimaging literature, two signatures of bi-dimensional cognitive maps have been reported: the grid-like code and the distance-dependent code. While these kinds of representation were previously observed during spatial navigation and, more recently, during processing of perceptual stimuli, it is still an open question whether they also underlie the representation of the most basic items of language: words. Here we taught human participants the meaning of novel words as arbitrary labels for a set of audiovisual objects varying orthogonally in size and sound. The novel words were therefore conceivable as points in a navigable 2D map of meaning. While subjects performed a word comparison task, we recorded their brain activity using functional magnetic resonance imaging (fMRI). By applying a combination of representational similarity and fMRI-adaptation analyses, we found evidence of (i) a grid-like code, in the right postero-medial entorhinal cortex, representing the relative angular positions of words in the word space, and (ii) a distance-dependent code, in medial prefrontal, orbitofrontal, and mid-cingulate cortices, representing the Euclidean distance between words. Additionally, we found evidence that the brain also separately represents the single dimensions of word meaning: their implied size, encoded in visual areas, and their implied sound, in Heschl's gyrus/Insula. These results support the idea that the meaning of words, when they are organized along two dimensions, is represented in the human brain across multiple maps of different dimensionality. SIGNIFICANT STATEMENT: How do we represent the meaning of words and perform comparative judgements on them in our brain? According to influential theories, concepts are conceivable as points of an internal map (where distance represents similarity) that, as the physical space, can be mentally navigated. Here we use fMRI to show that when humans compare newly learnt words, they recruit a grid-like and a distance code, the same types of neural codes that, in mammals, represent relations between locations in the environment and support physical navigation between them.

Allocentric representation in the human amygdala and ventral visual stream

The hippocampus and the entorhinal cortex are considered the main brain structures for allocentric representation of the external environment. Here, we show that the amygdala and the ventral visual stream are involved in allocentric representation. Thirty-one young men explored 35 virtual environments during high-resolution functional magnetic resonance imaging (fMRI) of the medial temporal lobe (MTL) and were subsequently tested on recall of the allocentric pattern of the objects in each environment-in other words, the positions of the objects relative to each other and to the outer perimeter. We find increasingly unique brain activation patterns associated with increasing allocentric accuracy in distinct neural populations in the perirhinal cortex, parahippocampal cortex, fusiform cortex, amygdala, hippocampus, and entorhinal cortex. In contrast to the traditional view of a hierarchical MTL network with the hippocampus at the top, we demonstrate, using recently developed graph analyses, a hierarchical allocentric MTL network without a main connector hub.

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.

The broadband power shifts in entorhinal EEG are related to the firing of grid cells

The relationship between the firing of the grid cell and mesoscopic neural oscillations is one of the key issues to understand the neural mechanism of grid cells. Previous studies have focused more on the correspondence between neuronal firing and phases of oscillations, such as phase precession. There are also some conclusions about the relationship between the activity of grid cells and the intensity of neural oscillations, such as the disappearance of grid pattern caused by the blocking of theta rhythm, but the correlation between the firing rates of grid cells and the narrowband power of neural oscillations or the broadband LFP power is still scarce. Through analyzing the records of spike times of grid cells and local entorhinal EEG obtained by Hafting et al., in the spatial navigation experiment, we find that grid cells are, to a large proportion, a kind of broadband-shift neurons, and the positive correlation between grid cell activity and power of low theta and gamma bands was observed. These results have well verified, promoted, and connected many scattered research conclusions, such as the broadband shift phenomenon of hippocampal neurons, the influence of low theta activity on the firing pattern of grid cells, and the positive correlation between single-cell activity and gamma-band activity. This work is of great significance for the study of the neural mechanism of grid cells at the micro and mesoscopic levels, and may also inspire the use of indicators such as broadband power as markers for grid cell activity.

Tracking the Emergence of Location-based Spatial Representations in Human Scene-Selective Cortex

Scene-selective regions of the human brain form allocentric representations of locations in our environment. These representations are independent of heading direction and allow us to know where we are regardless of our direction of travel. However, we know little about how these location-based representations are formed. Using fMRI representational similarity analysis and linear mixed models, we tracked the emergence of location-based representations in scene-selective brain regions. We estimated patterns of activity for two distinct scenes, taken before and after participants learnt they were from the same location. During a learning phase, we presented participants with two types of panoramic videos: (1) an overlap video condition displaying two distinct scenes (0° and 180°) from the same location and (2) a no-overlap video displaying two distinct scenes from different locations (which served as a control condition). In the parahippocampal cortex (PHC) and retrosplenial cortex (RSC), representations of scenes from the same location became more similar to each other only after they had been shown in the overlap condition, suggesting the emergence of viewpoint-independent location-based representations. Whereas these representations emerged in the PHC regardless of task performance, RSC representations only emerged for locations where participants could behaviorally identify the two scenes as belonging to the same location. The results suggest that we can track the emergence of location-based representations in the PHC and RSC in a single fMRI experiment. Further, they support computational models that propose the RSC plays a key role in transforming viewpoint-independent representations into behaviorally relevant representations of specific viewpoints.

Hippocampal cells integrate past memory and present perception for the future

The ability to use stored information in a highly flexible manner is a defining feature of the declarative memory system. However, the neuronal mechanisms underlying this flexibility are poorly understood. To address this question, we recorded single-unit activity from the hippocampus of 2 nonhuman primates performing a newly devised task requiring the monkeys to retrieve long-term item-location association memory and then use it flexibly in different circumstances. We found that hippocampal neurons signaled both mnemonic information representing the retrieved location and perceptual information representing the external circumstance. The 2 signals were combined at a single-neuron level to construct goal-directed information by 3 sequentially occurring neuronal operations (e.g., convergence, transference, and targeting) in the hippocampus. Thus, flexible use of knowledge may be supported by the hippocampal constructive process linking memory and perception, which may fit the mnemonic information into the current situation to present manageable information for a subsequent action.

This study reveals that three neuronal operations in the macaque hippocampus combine retrieved memory and incoming perceptual information to construct goal-directed information; this constructive memory process may equip us to use past knowledge flexibly according to the current situation.

Current Promises and Limitations of Combined Virtual Reality and Functional Magnetic Resonance Imaging Research in Humans: A Commentary on Huffman and Ekstrom (2019)

Real-world navigation requires movement of the body through space, producing a continuous stream of visual and self-motion signals, including proprioceptive, vestibular, and motor efference cues. These multimodal cues are integrated to form a spatial cognitive map, an abstract, amodal representation of the environment. How the brain combines these disparate inputs and the relative importance of these inputs to cognitive map formation and recall are key unresolved questions in cognitive neuroscience. Recent advances in virtual reality technology allow participants to experience body-based cues when virtually navigating, and thus it is now possible to consider these issues in new detail. Here, we discuss a recent publication that addresses some of these issues (D. J. Huffman and A. D. Ekstrom. A modality-independent network underlies the retrieval of large-scale spatial environments in the human brain. Neuron, 104, 611-622, 2019). In doing so, we also review recent progress in the study of human spatial cognition and raise several questions that might be addressed in future studies.

Neuronal vector coding in spatial cognition

Several types of neurons involved in spatial navigation and memory encode the distance and direction (that is, the vector) between an agent and items in its environment. Such vectorial information provides a powerful basis for spatial cognition by representing the geometric relationships between the self and the external world. Here, we review the explicit encoding of vectorial information by neurons in and around the hippocampal formation, far from the sensory periphery. The parahippocampal, retrosplenial and parietal cortices, as well as the hippocampal formation and striatum, provide a plethora of examples of vector coding at the single neuron level. We provide a functional taxonomy of cells with vectorial receptive fields as reported in experiments and proposed in theoretical work. The responses of these neurons may provide the fundamental neural basis for the (bottom-up) representation of environmental layout and (top-down) memory-guided generation of visuospatial imagery and navigational planning.

Unmasking selective path integration deficits in Alzheimer's disease risk carriers

Alzheimer's disease (AD) manifests with progressive memory loss and spatial disorientation. Neuropathological studies suggest early AD pathology in the entorhinal cortex (EC) of young adults at genetic risk for AD (APOE ε4-carriers). Because the EC harbors grid cells, a likely neural substrate of path integration (PI), we examined PI performance in APOE ε4-carriers during a virtual navigation task. We report a selective impairment in APOE ε4-carriers specifically when recruitment of compensatory navigational strategies via supportive spatial cues was disabled. A separate fMRI study revealed that PI performance was associated with the strength of entorhinal grid-like representations when no compensatory strategies were available, suggesting grid cell dysfunction as a mechanistic explanation for PI deficits in APOE ε4-carriers. Furthermore, posterior cingulate/retrosplenial cortex was involved in the recruitment of compensatory navigational strategies via supportive spatial cues. Our results provide evidence for selective PI deficits in AD risk carriers, decades before potential disease onset.

Behavior-dependent directional tuning in the human visual-navigation network

The brain derives cognitive maps from sensory experience that guide memory formation and behavior. Despite extensive efforts, it still remains unclear how the underlying population activity unfolds during spatial navigation and how it relates to memory performance. To examine these processes, we combined 7T-fMRI with a kernel-based encoding model of virtual navigation to map world-centered directional tuning across the human cortex. First, we present an in-depth analysis of directional tuning in visual, retrosplenial, parahippocampal and medial temporal cortices. Second, we show that tuning strength, width and topology of this directional code during memory-guided navigation depend on successful encoding of the environment. Finally, we show that participants' locomotory state influences this tuning in sensory and mnemonic regions such as the hippocampus. We demonstrate a direct link between neural population tuning and human cognition, where high-level memory processing interacts with network-wide visuospatial coding in the service of behavior.

Knowledge Across Reference Frames: Cognitive Maps and Image Spaces

In human and non-human animals, conceptual knowledge is partially organized according to low-dimensional geometries that rely on brain structures and computations involved in spatial representations. Recently, two separate lines of research have investigated cognitive maps, that are associated with the hippocampal formation and are similar to world-centered representations of the environment, and image spaces, that are associated with the parietal cortex and are similar to self-centered spatial relationships. We review evidence supporting cognitive maps and image spaces, and we propose a hippocampal-parietal network that can account for the organization and retrieval of knowledge across multiple reference frames. We also suggest that cognitive maps and image spaces may be two manifestations of a more general propensity of the mind to create low-dimensional internal models.

Sequence Memory in the Hippocampal-Entorhinal Region

Episodic memories are constructed from sequences of events. When recalling such a memory, we not only recall individual events, but we also retrieve information about how the sequence of events unfolded. Here, we focus on the role of the hippocampal-entorhinal region in processing and remembering sequences of events, which are thought to be stored in relational networks. We summarize evidence that temporal relations are a central organizational principle for memories in the hippocampus. Importantly, we incorporate novel insights from recent studies about the role of the adjacent entorhinal cortex in sequence memory. In rodents, the lateral entorhinal subregion carries temporal information during ongoing behavior. The human homologue is recruited during memory recall where its representations reflect the temporal relationships between events encountered in a sequence. We further introduce the idea that the hippocampal-entorhinal region might enable temporal scaling of sequence representations. Flexible changes of sequence progression speed could underlie the traversal of episodic memories and mental simulations at different paces. In conclusion, we describe how the entorhinal cortex and hippocampus contribute to remembering event sequences-a core component of episodic memory.