Conjunctive representation of position, direction, and velocity in entorhinal cortex

Interactions between neural representations of the social and spatial environment

Even in our highly interconnected modern world, geographic factors play an important role in human social connections. Similarly, social relationships influence how and where we travel, and how we think about our spatial world. Here, we review the growing body of neuroscience research that is revealing multiple interactions between social and spatial processes in both humans and non-human animals. We review research on the cognitive and neural representation of spatial and social information, and highlight recent findings suggesting that underlying mechanisms might be common to both. We discuss how spatial factors can influence social behaviour, and how social concepts modify representations of space. In so doing, this review elucidates not only how neural representations of social and spatial information interact but also similarities in how the brain represents and operates on analogous information about its social and spatial surroundings.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

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.

Intrinsic Bipolar Head-Direction Cells in the Medial Entorhinal Cortex

Head-direction (HD) cells are a fundamental component in the hippocampal-entorhinal circuit for spatial navigation and help maintain an internal sense of direction to anchor the orientation in space. A classical HD cell robustly increases its firing rate when the head is oriented toward a specific direction, with each cell tuned to only one direction. Although unidirectional HD cells are reported broadly across multiple brain regions, computation modelling has predicted the existence of multiple equilibrium states of HD network, which has yet to be proven. In this study, a novel HD variant of bipolar HD cells in the medial entorhinal cortex (MEC) are identified that exhibit stable double-peaked directional tuning properties. The bipolar patterns remain stable in the darkness and across environments of distinct geometric shapes. Moreover, bipolar HD cells co-rotate coherently with unipolar HD cells to anchor the external visual cue. The discovery reveals a new spatial cell type of bipolar HD cells, whose unique activity patterns may comprise a potential building block for a sophisticated local neural circuit configuration for the internal representation of direction. These findings may contribute to the understanding of how the brain processes spatial information by shedding light on the role of bipolar HD cells in this process.

Non-spatial hippocampal behavioral timescale synaptic plasticity during working memory is gated by entorhinal inputs

Behavioral timescale synaptic plasticity (BTSP) is a form of synaptic potentiation where the occurrence of a single large plateau potential in CA1 hippocampal neurons leads to the formation of reliable place fields during spatial learning tasks. We asked whether BTSP could also be a plasticity mechanism for generation of non-spatial responses in the hippocampus and what roles the medial and lateral entorhinal cortex (MEC and LEC) play in driving non-spatial BTSP. By performing simultaneous calcium imaging of dorsal CA1 neurons and chemogenetic inhibition of LEC or MEC while mice performed an olfactory working memory task, we discovered BTSP-like events which formed stable odor-specific fields. Critically, the success rate of calcium events generating a significant odor-field increased with event amplitude, and large events exhibited asymmetrical formation with the newly formed odor-fields preceding the timepoint of their induction event. We found that MEC and LEC play distinct roles in modulating BTSP: MEC inhibition reduced the frequency of large calcium events, while LEC inhibition reduced the success rate of odor-field generation. Using two-photon calcium imaging of LEC and MEC temporammonic axons projecting to CA1, we found that LEC projections to CA1 were strongly odor selective even early in task learning, while MEC projection odor-selectivity increased with task learning but remained weaker than LEC. Finally, we found that LEC and MEC inhibition both slowed representational drift of odor representations in CA1 across 48 hours. Altogether, odor-specific information from LEC and strong odor-timed activity from MEC are crucial for driving BTSP in CA1, which is a synaptic plasticity mechanism for generation of both spatial and non-spatial responses in the hippocampus that may play a role in explaining representational drift and one-shot learning of non-spatial information.

Optogenetic silencing of medial septal GABAergic neurons disrupts grid cell spatial and temporal coding in the medial entorhinal cortex

The hippocampus and medial entorhinal cortex (MEC) form a cognitive map that facilitates spatial navigation. As part of this map, MEC grid cells fire in a repeating hexagonal pattern across an environment. This grid pattern relies on inputs from the medial septum (MS). The MS, and specifically GABAergic neurons, are essential for theta rhythm oscillations in the entorhinal-hippocampal network; however, the role of this population in grid cell function is unclear. To investigate this, we use optogenetics to inhibit MS-GABAergic neurons and observe that MS-GABAergic inhibition disrupts grid cell spatial periodicity. Grid cell spatial periodicity is disrupted during both optogenetic inhibition periods and short inter-stimulus intervals. In contrast, longer inter-stimulus intervals allow for the recovery of grid cell spatial firing. In addition, grid cell phase precession is also disrupted. These findings highlight the critical role of MS-GABAergic neurons in maintaining grid cell spatial and temporal coding in the MEC.

Predictive grid coding in the medial entorhinal cortex

The entorhinal cortex represents allocentric spatial geometry and egocentric speed and heading information required for spatial navigation. However, it remains unclear whether it contributes to the prediction of an animal's future location. We discovered grid cells in the medial entorhinal cortex (MEC) that have grid fields representing future locations during goal-directed behavior. These predictive grid cells represented prospective spatial information by shifting their grid fields against the direction of travel. Predictive grid cells discharged at the trough phases of the hippocampal CA1 theta oscillation and, together with other types of grid cells, organized sequences of the trajectory from the current to future positions across each theta cycle. Our results suggest that the MEC provides a predictive map that supports forward planning in spatial navigation.

Tentacle Microelectrode Arrays Uncover Soft Boundary Neurons in Hippocampal CA1

Hippocampal CA1 neurons show intense firing at specific spatial locations, modulated by isolated landmarks. However, the impact of real-world scene transitions on neuronal activity remains unclear. Moreover, long-term neural recording during movement challenges device stability. Conventional rigid-based electrodes cause inflammatory responses, restricting recording durations. Inspired by the jellyfish tentacles, the multi-conductive layer ultra-flexible microelectrode arrays (MEAs) are developed. The tentacle MEAs ensure stable recordings during movement, thereby enabling the discovery of soft boundary neurons. The soft boundary neurons demonstrate high-frequency firing that aligns with the boundaries of scene transitions. Furthermore, the localization ability of soft boundary neurons improves with more scene transition boundaries, and their activity decreases when these boundaries are removed. The innovation of ultra-flexible, high-biocompatible tentacle MEAs improves the understanding of neural encoding in spatial cognition. They offer the potential for long-term in vivo recording of neural information, facilitating breakthroughs in the understanding and application of brain spatial navigation mehanisms.

Grid Cells in Cognition: Mechanisms and Function

The activity patterns of grid cells form distinctively regular triangular lattices over the explored spatial environment and are largely invariant to visual stimuli, animal movement, and environment geometry. These neurons present numerous fascinating challenges to the curious (neuro)scientist: What are the circuit mechanisms responsible for creating spatially periodic activity patterns from the monotonic input-output responses of single neurons? How and why does the brain encode a local, nonperiodic variable-the allocentric position of the animal-with a periodic, nonlocal code? And, are grid cells truly specialized for spatial computations? Otherwise, what is their role in general cognition more broadly? We review efforts in uncovering the mechanisms and functional properties of grid cells, highlighting recent progress in the experimental validation of mechanistic grid cell models, and discuss the coding properties and functional advantages of the grid code as suggested by continuous attractor network models of grid cells.

Retrosplenial inputs drive visual representations in the medial entorhinal cortex

The importance of visual cues for navigation and goal-directed behavior is well established, although the neural mechanisms supporting sensory representations in navigational circuits are largely unknown. Navigation is fundamentally dependent on the medial entorhinal cortex (MEC), which receives direct projections from neocortical visual areas, including the retrosplenial cortex (RSC). Here, we perform high-density recordings of MEC neurons in awake, head-fixed mice presented with simple visual stimuli and assess the dynamics of sensory-evoked activity. We find that a large fraction of neurons exhibit robust responses to visual input. Visually responsive cells are located primarily in layer 3 of the dorsal MEC and can be separated into subgroups based on functional and molecular properties. Furthermore, optogenetic suppression of RSC afferents within the MEC strongly reduces visual responses. Overall, our results demonstrate that the MEC can encode simple visual cues in the environment that may contribute to neural representations of location necessary for accurate navigation.

Transformation of spatial representations along hippocampal circuits

The hippocampus is thought to provide the brain with a cognitive map of the external world by processing various types of spatial information. To understand how essential spatial variables such as direction, position, and distance are transformed along its circuits to construct this global map, we perform single-photon widefield microendoscope calcium imaging in the dentate gyrus and CA3 of mice freely navigating along a narrow corridor. We find that spatial activity maps in the dentate gyrus, but not in CA3, are correlated after aligning them to the running directions, suggesting that they represent the distance traveled along the track in egocentric coordinates. Together with population activity decoding, our data suggest that while spatial representations in the dentate gyrus and CA3 are anchored in both egocentric and allocentric coordinates, egocentric distance coding is more prevalent in the dentate gyrus than in CA3, providing insights into the assembly of the cognitive map.

Projection neurons from medial entorhinal cortex to basolateral amygdala are critical for the retrieval of morphine withdrawal memory

The medial entorhinal cortex (MEC) is crucial for contextual memory, yet its role in context-induced retrieval of morphine withdrawal memory remains unclear. This study investigated the role of the MEC and its projection neurons from MEC layer 5 to the basolateral amygdala (BLA) (MEC-BLA neurons) in context-induced retrieval of morphine withdrawal memory. Results show that context activates the MEC in morphine withdrawal mice, and the inactivation of the MEC inhibits context-induced retrieval of morphine withdrawal memory. At neural circuits, context activates MEC-BLA neurons in morphine withdrawal mice, and the inactivation of MEC-BLA neurons inhibits context-induced retrieval of morphine withdrawal memory. But MEC-BLA neurons are not activated by conditioning of context and morphine withdrawal, and the inhibition of MEC-BLA neurons do not influence the coupling of context and morphine withdrawal memory. These results suggest that MEC-BLA neurons are critical for the retrieval, but not for the formation, of morphine withdrawal memory.

Application of scaling to mouse spontaneous movement: Path curvature varies with speed and linear distance features isochrony

To conserve sequential behavior in relation to the topographic challenges of space, it is proposed that humans and nonhuman animals can organize behavior using different scaling principles. To deal with increases in linear distance, isochrony suggest that there is a corresponding increase in speed, whereas to deal with changes in curvature, speed is adjusted according to a power function. The present study investigates whether these principles provide a framework for describing the organization of mouse behavior in a variety of standard experimental tasks. The structure of movement was examined in ambulation during open field exploration; manipulation in a string-pulling task, in which a string is advanced hand over hand to retrieve food; and rung-walking, in which the limbs successively step from rung to rung on a horizontal ladder. Both principles were found to be conserved in the organization of mouse behavior across scales of movement. These principles provide novel measures of the temporal and geometric features of movement in the mouse and insights into how the temporal and geometric features of movement are conserved within different species.

Reelin differentially shapes dendrite morphology of medial entorhinal cortical ocean and island cells

The function of medial entorhinal cortex layer II (MECII) excitatory neurons has been recently explored. MECII dysfunction underlies deficits in spatial navigation and working memory. MECII neurons comprise two major excitatory neuronal populations, pyramidal island and stellate ocean cells, in addition to the inhibitory interneurons. Ocean cells express reelin and surround clusters of island cells that lack reelin expression. The influence of reelin expression by ocean cells and interneurons on their own morphological differentiation and that of MECII island cells has remained unknown. To address this, we used a conditional reelin knockout (RelncKO) mouse to induce reelin deficiency postnatally in vitro and in vivo. Reelin deficiency caused dendritic hypertrophy of ocean cells, interneurons and only proximal dendritic compartments of island cells. Ca2+ recording showed that both cell types exhibited an elevation of calcium frequencies in RelncKO, indicating that the hypertrophic effect is related to excessive Ca2+ signalling. Moreover, pharmacological receptor blockade in RelncKO mouse revealed malfunctioning of GABAB, NMDA and AMPA receptors. Collectively, this study emphasizes the significance of reelin in neuronal growth, and its absence results in dendrite hypertrophy of MECII neurons.

Uncovering 2-D toroidal representations in grid cell ensemble activity during 1-D behavior

Minimal experiments, such as head-fixed wheel-running and sleep, offer experimental advantages but restrict the amount of observable behavior, making it difficult to classify functional cell types. Arguably, the grid cell, and its striking periodicity, would not have been discovered without the perspective provided by free behavior in an open environment. Here, we show that by shifting the focus from single neurons to populations, we change the minimal experimental complexity required. We identify grid cell modules and show that the activity covers a similar, stable toroidal state space during wheel running as in open field foraging. Trajectories on grid cell tori correspond to single trial runs in virtual reality and path integration in the dark, and the alignment of the representation rapidly shifts with changes in experimental conditions. Thus, we provide a methodology to discover and study complex internal representations in even the simplest of experiments.

Odors in space

As an evolutionarily ancient sense, olfaction is key to learning where to find food, shelter, mates, and important landmarks in an animal's environment. Brain circuitry linking odor and navigation appears to be a well conserved multi-region system among mammals; the anterior olfactory nucleus, piriform cortex, entorhinal cortex, and hippocampus each represent different aspects of olfactory and spatial information. We review recent advances in our understanding of the neural circuits underlying odor-place associations, highlighting key choices of behavioral task design and neural circuit manipulations for investigating learning and memory.

Border cells without theta rhythmicity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is a key brain structure for higher cognitive functions such as decision-making and goal-directed behavior, many of which require awareness of spatial variables including one's current position within the surrounding environment. Although previous studies have reported spatially tuned activities in mPFC during memory-related trajectory, the spatial tuning of mPFC network during freely foraging behavior remains elusive. Here, we reveal geometric border or border-proximal representations from the neural activity of mPFC ensembles during naturally exploring behavior, with both allocentric and egocentric boundary responses. Unlike most of classical border cells in the medial entorhinal cortex (MEC) discharging along a single wall, a large majority of border cells in mPFC fire particularly along four walls. mPFC border cells generate new firing fields to external insert, and remain stable under darkness, across distinct shapes, and in novel environments. In contrast to hippocampal theta entrainment during spatial working memory tasks, mPFC border cells rarely exhibited theta rhythmicity during spontaneous locomotion behavior. These findings reveal spatially modulated activity in mPFC, supporting local computation for cognitive functions involving spatial context and contributing to a broad spatial tuning property of cortical circuits.

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.

Robust variability of grid cell properties within individual grid modules enhances encoding of local space

Although grid cells are one of the most well studied functional classes of neurons in the mammalian brain, the assumption that there is a single grid orientation and spacing per grid module has not been carefully tested. We investigate and analyze a recent large-scale recording of medial entorhinal cortex to characterize the presence and degree of heterogeneity of grid properties within individual modules. We find evidence for small, but robust, variability and hypothesize that this property of the grid code could enhance the ability of encoding local spatial information. Performing analysis on synthetic populations of grid cells, where we have complete control over the amount heterogeneity in grid properties, we demonstrate that variability, of a similar magnitude to the analyzed data, leads to significantly decreased decoding error, even when restricted to activity from a single module. Our results highlight how the heterogeneity of the neural response properties may benefit coding and opens new directions for theoretical and experimental analysis of grid cells.

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.

Cognitive maps and the magnetic sense in vertebrates

Navigation requires a network of neurons processing inputs from internally generated cues and external landmarks. Most studies on the neuronal basis of navigation in vertebrates have focused on rats and mice and the canonical senses vision, hearing, olfaction, and somatosensation. Some animals have evolved the ability to sense the Earth's magnetic field and use it for orientation. It can be expected that in these animals magnetic cues are integrated with other sensory cues in the cognitive map. We provide an overview of the behavioral evidence and brain regions involved in magnetic sensing in support of this idea, hoping that this will guide future experiments.

A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal is to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software (version 1.0) is released as open source to enable broad community reuse and encourage novel applications.

A non-canonical visual cortical-entorhinal pathway contributes to spatial navigation

Visual information is important for accurate spatial coding and memory-guided navigation. As a crucial area for spatial cognition, the medial entorhinal cortex (MEC) harbors diverse spatially tuned cells and functions as the major gateway relaying sensory inputs to the hippocampus containing place cells. However, how visual information enters the MEC has not been fully understood. Here, we identify a pathway originating in the secondary visual cortex (V2) and directly targeting MEC layer 5a (L5a). L5a neurons served as a network hub for visual processing in the MEC by routing visual inputs from multiple V2 areas to other local neurons and hippocampal CA1. Interrupting this pathway severely impaired visual stimulus-evoked neural activity in the MEC and performance of mice in navigation tasks. These observations reveal a visual cortical-entorhinal pathway highlighting the role of MEC L5a in sensory information transmission, a function typically attributed to MEC superficial layers before.

Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus

The role of the hippocampus in spatial navigation has been primarily studied in nocturnal mammals, such as rats, that lack many adaptations for daylight vision. Here we demonstrate that during 3D navigation, the common marmoset, a new world primate adapted to daylight, predominantly uses rapid head-gaze shifts for visual exploration while remaining stationary. During active locomotion marmosets stabilize the head, in contrast to rats that use low-velocity head movements to scan the environment as they locomote. Pyramidal neurons in the marmoset hippocampus CA3/CA1 regions predominantly show mixed selectivity for 3D spatial view, head direction, and place. Exclusive place selectivity is scarce. Inhibitory interneurons are predominantly mixed selective for angular head velocity and translation speed. Finally, we found theta phase resetting of local field potential oscillations triggered by head-gaze shifts. Our findings indicate that marmosets adapted to their daylight ecological niche by modifying exploration/navigation strategies and their corresponding hippocampal specializations.

A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal was to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software is released as open source to enable broad community reuse and encourage novel applications.

Spatial Coding Dysfunction and Network Instability in the Aging Medial Entorhinal Cortex

Across species, spatial memory declines with age, possibly reflecting altered hippocampal and medial entorhinal cortex (MEC) function. However, the integrity of cellular and network-level spatial coding in aged MEC is unknown. Here, we leveraged in vivo electrophysiology to assess MEC function in young, middle-aged, and aged mice navigating virtual environments. In aged grid cells, we observed impaired stabilization of context-specific spatial firing, correlated with spatial memory deficits. Additionally, aged grid networks shifted firing patterns often but with poor alignment to context changes. Aged spatial firing was also unstable in an unchanging environment. In these same mice, we identified 458 genes differentially expressed with age in MEC, 61 of which had expression correlated with spatial firing stability. These genes were enriched among interneurons and related to synaptic transmission. Together, these findings identify coordinated transcriptomic, cellular, and network changes in MEC implicated in impaired spatial memory in aging.

Beyond hippocampus: Thalamic and prefrontal contributions to an evolving memory

The hippocampus has long been at the center of memory research, and rightfully so. However, with emerging technological capabilities, we can increasingly appreciate memory as a more dynamic and brain-wide process. In this perspective, our goal is to begin developing models to understand the gradual evolution, reorganization, and stabilization of memories across the brain after their initial formation in the hippocampus. By synthesizing studies across the rodent and human literature, we suggest that as memory representations initially form in hippocampus, parallel traces emerge in frontal cortex that cue memory recall, and as they mature, with sustained support initially from limbic then diencephalic then cortical circuits, they become progressively independent of hippocampus and dependent on a mature cortical representation. A key feature of this model is that, as time progresses, memory representations are passed on to distinct circuits with progressively longer time constants, providing the opportunity to filter, forget, update, or reorganize memories in the process of committing to long-term storage.

Differentiated somatic gene expression is triggered in the dorsal hippocampus and the anterior retrosplenial cortex by hippocampal synaptic plasticity prompted by spatial content learning

Hippocampal afferent inputs, terminating on proximal and distal subfields of the cornus ammonis (CA), enable the functional discrimination of 'what' (item identity) and 'where' (spatial location) elements of a spatial representation. This kind of information is supported by structures such as the retrosplenial cortex (RSC). Spatial content learning promotes the expression of hippocampal synaptic plasticity, particularly long-term depression (LTD). In the CA1 region, this is specifically facilitated by the learning of item-place features of a spatial environment. Gene-tagging, by means of time-locked fluorescence in situ hybridization (FISH) to detect nuclear expression of immediate early genes, can reveal neuronal populations that engage in experience-dependent information encoding. In the current study, using FISH, we examined if learning-facilitated LTD results in subfield-specific information encoding in the hippocampus and RSC. Rats engaged in novel exploration of small items during stimulation of Schaffer collateral-CA1 synapses. This resulted in LTD (> 24 h). FISH, to detect nuclear expression of Homer1a, revealed that the distal-CA1 and proximal-CA3 subcompartments were particularly activated by this event. By contrast, all elements of the proximodistal cornus ammonis-axis showed equal nuclear Homer1a expression following LTD induction solely by means of afferent stimulation. The RSC exhibited stronger nuclear Homer1a expression in response to learning-facilitated LTD, and to novel item-place experience, compared to LTD induced by sole afferent stimulation in CA1. These results show that both the cornus ammonis and RSC engage in differentiated information encoding of item-place learning that is salient enough, in its own right, to drive the expression of hippocampal LTD. These results also reveal a novel role of the RSC in item-place learning.

Comparison of head direction cell firing characteristics across thalamo-parahippocampal circuitry

Head direction (HD) cells, which fire persistently when an animal's head is pointed in a particular direction, are widely thought to underlie an animal's sense of spatial orientation and have been identified in several limbic brain regions. Robust HD cell firing is observed throughout the thalamo-parahippocampal system, although recent studies report that parahippocampal HD cells exhibit distinct firing properties, including conjunctive aspects with other spatial parameters, which suggest they play a specialized role in spatial processing. Few studies, however, have quantified these apparent differences. Here, we performed a comparative assessment of HD cell firing characteristics across the anterior dorsal thalamus (ADN), postsubiculum (PoS), parasubiculum (PaS), medial entorhinal (MEC), and postrhinal (POR) cortices. We report that HD cells with a high degree of directional specificity were observed in all five brain regions, but ADN HD cells display greater sharpness and stability in their preferred directions, and greater anticipation of future headings compared to parahippocampal regions. Additional analysis indicated that POR HD cells were more coarsely modulated by other spatial parameters compared to PoS, PaS, and MEC. Finally, our analyses indicated that the sharpness of HD tuning decreased as a function of laminar position and conjunctive coding within the PoS, PaS, and MEC, with cells in the superficial layers along with conjunctive firing properties showing less robust directional tuning. The results are discussed in relation to theories of functional organization of HD cell tuning in thalamo-parahippocampal circuitry.

Task-anchored grid cell firing is selectively associated with successful path integration-dependent behaviour

Grid firing fields have been proposed as a neural substrate for spatial localisation in general or for path integration in particular. To distinguish these possibilities, we investigate firing of grid and non-grid cells in the mouse medial entorhinal cortex during a location memory task. We find that grid firing can either be anchored to the task environment, or can encode distance travelled independently of the task reference frame. Anchoring varied between and within sessions, while spatial firing of non-grid cells was either coherent with the grid population, or was stably anchored to the task environment. We took advantage of the variability in task-anchoring to evaluate whether and when encoding of location by grid cells might contribute to behaviour. We find that when reward location is indicated by a visual cue, performance is similar regardless of whether grid cells are task-anchored or not, arguing against a role for grid representations when location cues are available. By contrast, in the absence of the visual cue, performance was enhanced when grid cells were anchored to the task environment. Our results suggest that anchoring of grid cells to task reference frames selectively enhances performance when path integration is required.

Entangled brains and the experience of pains

The International Association for the Study of Pain (IASP) revised its definition of pain to "an unpleasant sensory and emotional experience." Three recent recommendations for understanding pain if there are no clear brain correlates include eliminativism, multiple realizability, and affordance-based approaches. I adumbrate a different path forward. Underlying each of the proposed approaches and the new IASP definition is the suspicion that there are no specific correlates for pain. I suggest that this basic assumption is misguided. As we learn more about brain function, it is becoming clear that many areas process many different types of information at the same time. In this study, I analogize how animal brains navigate in three-dimensional space with how the brain creates pain. Underlying both cases is a large-scale combinatorial system that feeds back on itself through a diversity of convergent and divergent bi-directional connections. Brains are not like combustion engines, with energy driving outputs via the structure of the machine, but are instead more like whirlpools, which are essentially dynamic patterns in some substrates. We should understand pain experiences as context-dependent, spatiotemporal trajectories that reflect heterogeneous, multiplex, and dynamically adaptive brain cells.

Distinct changes to hippocampal and medial entorhinal circuits emerge across the progression of cognitive deficits in epilepsy

Temporal lobe epilepsy (TLE) causes pervasive and progressive memory impairments, yet the specific circuit changes that drive these deficits remain unclear. To investigate how hippocampal-entorhinal dysfunction contributes to progressive memory deficits in epilepsy, we performed simultaneous in vivo electrophysiology in hippocampus (HPC) and medial entorhinal cortex (MEC) of control and epileptic mice 3 or 8 weeks after pilocarpine-induced status epilepticus (Pilo-SE). We found that HPC synchronization deficits (including reduced theta power, coherence, and altered interneuron spike timing) emerged within 3 weeks of Pilo-SE, aligning with early-onset, relatively subtle memory deficits. In contrast, abnormal synchronization within MEC and between HPC-MEC emerged later, by 8 weeks after Pilo-SE, when spatial memory impairment was more severe. Furthermore, a distinct subpopulation of MEC layer 3 excitatory neurons (active at theta troughs) was specifically impaired in epileptic mice. Together, these findings suggest that hippocampal-entorhinal circuit dysfunction accumulates and shifts as cognitive impairment progresses in TLE.

Unsupervised classification of brain-wide axons reveals the presubiculum neuronal projection blueprint

We present a quantitative strategy to identify all projection neuron types from a given region with statistically different patterns of anatomical targeting. We first validate the technique with mouse primary motor cortex layer 6 data, yielding two clusters consistent with cortico-thalamic and intra-telencephalic neurons. We next analyze the presubiculum, a less-explored region, identifying five classes of projecting neurons with unique patterns of divergence, convergence, and specificity. We report several findings: individual classes target multiple subregions along defined functions; all hypothalamic regions are exclusively targeted by the same class also invading midbrain and agranular retrosplenial cortex; Cornu Ammonis receives input from a single class of presubicular axons also projecting to granular retrosplenial cortex; path distances from the presubiculum to the same targets differ significantly between classes, as do the path distances to distinct targets within most classes; the identified classes have highly non-uniform abundances; and presubicular somata are topographically segregated among classes. This study thus demonstrates that statistically distinct projections shed light on the functional organization of their circuit.

Spatial periodicity in grid cell firing is explained by a neural sequence code of 2-D trajectories

Spatial periodicity in grid cell firing has been interpreted as a neural metric for space providing animals with a coordinate system in navigating physical and mental spaces. However, the specific computational problem being solved by grid cells has remained elusive. Here, we provide mathematical proof that spatial periodicity in grid cell firing is the only possible solution to a neural sequence code of 2-D trajectories and that the hexagonal firing pattern of grid cells is the most parsimonious solution to such a sequence code. We thereby provide a teleological cause for the existence of grid cells and reveal the underlying nature of the global geometric organization in grid maps as a direct consequence of a simple local sequence code. A sequence code by grid cells provides intuitive explanations for many previously puzzling experimental observations and may transform our thinking about grid cells.

Parahippocampal neurons encode task-relevant information for goal-directed navigation

A behavioral strategy crucial to survival is directed navigation to a goal, such as a food or home location. One potential neural substrate for supporting goal-directed navigation is the parahippocampus, which contains neurons that represent an animal's position, orientation, and movement through the world, and that change their firing activity to encode behaviorally relevant variables such as reward. However, little prior work on the parahippocampus has considered how neurons encode variables during goal-directed navigation in environments that dynamically change. Here, we recorded single units from rat parahippocampal cortex while subjects performed a goal-directed task. The maze dynamically changed goal-locations via a visual cue on a trial-to-trial basis, requiring subjects to use cue-location associations to receive reward. We observed a mismatch-like signal, with elevated neural activity on incorrect trials, leading to rate-remapping. The strength of this remapping correlated with task performance. Recordings during open-field foraging allowed us to functionally define navigational coding for a subset of the neurons recorded in the maze. This approach revealed that head-direction coding units remapped more than other functional-defined units. Taken together, this work thus raises the possibility that during goal-directed navigation, parahippocampal neurons encode error information reflective of an animal's behavioral performance.

Hippocampome.org 2.0 is a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits

Hippocampome.org is a mature open-access knowledge base of the rodent hippocampal formation focusing on neuron types and their properties. Previously, Hippocampome.org v1.0 established a foundational classification system identifying 122 hippocampal neuron types based on their axonal and dendritic morphologies, main neurotransmitter, membrane biophysics, and molecular expression (Wheeler et al., 2015). Releases v1.1 through v1.12 furthered the aggregation of literature-mined data, including among others neuron counts, spiking patterns, synaptic physiology, in vivo firing phases, and connection probabilities. Those additional properties increased the online information content of this public resource over 100-fold, enabling numerous independent discoveries by the scientific community. Hippocampome.org v2.0, introduced here, besides incorporating over 50 new neuron types, now recenters its focus on extending the functionality to build real-scale, biologically detailed, data-driven computational simulations. In all cases, the freely downloadable model parameters are directly linked to the specific peer-reviewed empirical evidence from which they were derived. Possible research applications include quantitative, multiscale analyses of circuit connectivity and spiking neural network simulations of activity dynamics. These advances can help generate precise, experimentally testable hypotheses and shed light on the neural mechanisms underlying associative memory and spatial navigation.

RatInABox, a toolkit for modelling locomotion and neuronal activity in continuous environments

Generating synthetic locomotory and neural data is a useful yet cumbersome step commonly required to study theoretical models of the brain's role in spatial navigation. This process can be time consuming and, without a common framework, makes it difficult to reproduce or compare studies which each generate test data in different ways. In response, we present RatInABox, an open-source Python toolkit designed to model realistic rodent locomotion and generate synthetic neural data from spatially modulated cell types. This software provides users with (i) the ability to construct one- or two-dimensional environments with configurable barriers and visual cues, (ii) a physically realistic random motion model fitted to experimental data, (iii) rapid online calculation of neural data for many of the known self-location or velocity selective cell types in the hippocampal formation (including place cells, grid cells, boundary vector cells, head direction cells) and (iv) a framework for constructing custom cell types, multi-layer network models and data- or policy-controlled motion trajectories. The motion and neural models are spatially and temporally continuous as well as topographically sensitive to boundary conditions and walls. We demonstrate that out-of-the-box parameter settings replicate many aspects of rodent foraging behaviour such as velocity statistics and the tendency of rodents to over-explore walls. Numerous tutorial scripts are provided, including examples where RatInABox is used for decoding position from neural data or to solve a navigational reinforcement learning task. We hope this tool will significantly streamline computational research into the brain's role in navigation.

Grid cells: the missing link in understanding Parkinson's disease?

The mechanisms underlying Parkinson's disease (PD) are complex and not fully understood, and the box-and-arrow model among other current models present significant challenges. This paper explores the potential role of the allocentric brain and especially its grid cells in several PD motor symptoms, including bradykinesia, kinesia paradoxa, freezing of gait, the bottleneck phenomenon, and their dependency on cueing. It is argued that central hubs, like the locus coeruleus and the pedunculopontine nucleus, often narrowly interpreted in the context of PD, play an equally important role in governing the allocentric brain as the basal ganglia. Consequently, the motor and secondary motor (e.g., spatially related) symptoms of PD linked with dopamine depletion may be more closely tied to erroneous computation by grid cells than to the basal ganglia alone. Because grid cells and their associated central hubs introduce both spatial and temporal information to the brain influencing velocity perception they may cause bradykinesia or hyperkinesia as well. In summary, PD motor symptoms may primarily be an allocentric disturbance resulting from virtual faulty computation by grid cells revealed by dopamine depletion in PD.

Distinct manifold encoding of navigational information in the subiculum and hippocampus

The subiculum (SUB) plays a crucial role in spatial navigation and encodes navigational information differently from the hippocampal CA1 area. However, the representation of subicular population activity remains unknown. Here, we investigated the neuronal population activity recorded extracellularly from the CA1 and SUB of rats performing T-maze and open-field tasks. The trajectory of population activity in both areas was confined to low-dimensional neural manifolds homoeomorphic to external space. The manifolds conveyed position, speed, and future path information with higher decoding accuracy in the SUB than in the CA1. The manifolds exhibited common geometry across rats and regions for the CA1 and SUB and between tasks in the SUB. During post-task ripples in slow-wave sleep, population activity represented reward locations/events more frequently in the SUB than in CA1. Thus, the CA1 and SUB encode information distinctly into the neural manifolds that underlie navigational information processing during wakefulness and sleep.

Object-place-context learning impairment correlates with spatial learning impairment in aged Long-Evans rats

The hippocampal formation is vulnerable to the process of normal aging. In humans, the extent of this age-related deterioration varies among individuals. Long-Evans rats replicate these individual differences as they age, and therefore they serve as a valuable model system to study aging in the absence of neurodegenerative diseases. In the Morris water maze, aged memory-unimpaired (AU) rats navigate to remembered goal locations as effectively as young rats and demonstrate minimal alterations in physiological markers of synaptic plasticity, whereas aged memory-impaired (AI) rats show impairments in both spatial navigation skills and cellular and molecular markers of plasticity. The present study investigates whether another cognitive domain is affected similarly to navigation in aged Long-Evans rats. We tested the ability of young, AU, and AI animals to recognize novel object-place-context (OPC) configurations and found that performance on the novel OPC recognition paradigm was significantly correlated with performance on the Morris water maze. In the first OPC test, young and AU rats, but not AI rats, successfully recognized and preferentially explored objects in novel OPC configurations. In a second test with new OPC configurations, all age groups showed similar OPC associative recognition memory. The results demonstrated similarities in the behavioral expression of associative, episodic-like memory between young and AU rats and revealed age-related, individual differences in functional decline in both navigation and episodic-like memory abilities.

Multiplexing of temporal and spatial information in the lateral entorhinal cortex

Episodic memory involves the processing of spatial and temporal aspects of personal experiences. The lateral entorhinal cortex (LEC) plays an essential role in subserving memory. However, the specific mechanism by which LEC integrates spatial and temporal information remains elusive. Here, we recorded LEC neurons while rats performed foraging and shuttling behaviors on one-dimensional, linear or circular tracks. Unlike open-field foraging tasks, many LEC cells displayed spatial firing fields in these tasks and demonstrated selectivity for traveling directions. Furthermore, some LEC neurons displayed changes in the firing rates of their spatial rate maps during a session, a phenomenon referred to as rate remapping. Importantly, this temporal modulation was consistent across sessions, even when the spatial environment was altered. Notably, the strength of temporal modulation was found to be greater in LEC compared to other brain regions, such as the medial entorhinal cortex (MEC), CA1, and CA3. Thus, the spatial rate mapping observed in LEC neurons may serve as a coding mechanism for temporal context, allowing for flexible multiplexing of spatial and temporal information.

The journey within: mental navigation as a novel framework for understanding psychotherapeutic transformation

BACKGROUND

Despite the demonstrated efficacy of psychotherapy, the precise mechanisms that drive therapeutic transformations have posed a challenge and still remain unresolved. Here, we suggest a potential solution to this problem by introducing a framework based on the concept of mental navigation. It refers to our ability to navigate our cognitive space of thoughts, ideas, concepts, and memories, similar to how we navigate physical space. We start by analyzing the neural, cognitive, and experiential constituents intrinsic to mental navigation. Subsequently, we posit that the metaphoric spatial language we employ to articulate introspective experiences (e.g., "unexplored territory" or "going in circles") serves as a robust marker of mental navigation.

METHODS

Using large text corpora, we compared the utilization of spatial language between transcripts of psychotherapy sessions (≈ 12 M. words), casual everyday conversations (≈ 12 M. words), and fictional dialogues in movies (≈ 14 M. words). We also examined 110 psychotherapy transcripts qualitatively to discern patterns and dynamics associated with mental navigation.

RESULTS

We found a notable increase in the utilization of spatial metaphors during psychotherapy compared to casual everyday dialogues (U = 192.0, p = .001, d = 0.549) and fictional conversations (U = 211, p < .001, d = 0.792). In turn, analyzing the usage of non-spatial metaphors, we did not find significant differences between the three datasets (H = 0.682, p = 0.710). The qualitative analysis highlighted specific examples of mental navigation at play.

CONCLUSION

Mental navigation might underlie the psychotherapy process and serve as a robust framework for understanding the transformative changes it brings about.

Hippocampome.org v2.0: a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits

Hippocampome.org is a mature open-access knowledge base of the rodent hippocampal formation focusing on neuron types and their properties. Hippocampome.org v1.0 established a foundational classification system identifying 122 hippocampal neuron types based on their axonal and dendritic morphologies, main neurotransmitter, membrane biophysics, and molecular expression. Releases v1.1 through v1.12 furthered the aggregation of literature-mined data, including among others neuron counts, spiking patterns, synaptic physiology, in vivo firing phases, and connection probabilities. Those additional properties increased the online information content of this public resource over 100-fold, enabling numerous independent discoveries by the scientific community. Hippocampome.org v2.0, introduced here, besides incorporating over 50 new neuron types, now recenters its focus on extending the functionality to build real-scale, biologically detailed, data-driven computational simulations. In all cases, the freely downloadable model parameters are directly linked to the specific peer-reviewed empirical evidence from which they were derived. Possible research applications include quantitative, multiscale analyses of circuit connectivity and spiking neural network simulations of activity dynamics. These advances can help generate precise, experimentally testable hypotheses and shed light on the neural mechanisms underlying associative memory and spatial navigation.

Minute-scale oscillatory sequences in medial entorhinal cortex

The medial entorhinal cortex (MEC) hosts many of the brain's circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience1. Whereas location is known to be encoded by spatially tuned cell types in this brain region2,3, little is known about how the activity of entorhinal cells is tied together over time at behaviourally relevant time scales, in the second-to-minute regime. Here we show that MEC neuronal activity has the capacity to be organized into ultraslow oscillations, with periods ranging from tens of seconds to minutes. During these oscillations, the activity is further organized into periodic sequences. Oscillatory sequences manifested while mice ran at free pace on a rotating wheel in darkness, with no change in location or running direction and no scheduled rewards. The sequences involved nearly the entire cell population, and transcended epochs of immobility. Similar sequences were not observed in neighbouring parasubiculum or in visual cortex. Ultraslow oscillatory sequences in MEC may have the potential to couple neurons and circuits across extended time scales and serve as a template for new sequence formation during navigation and episodic memory formation.

Direct cortical inputs to hippocampal area CA1 transmit complementary signals for goal-directed navigation

The subregions of the entorhinal cortex (EC) are conventionally thought to compute dichotomous representations for spatial processing, with the medial EC (MEC) providing a global spatial map and the lateral EC (LEC) encoding specific sensory details of experience. Yet, little is known about the specific types of information EC transmits downstream to the hippocampus. Here, we exploit in vivo sub-cellular imaging to record from EC axons in CA1 while mice perform navigational tasks in virtual reality (VR). We uncover distinct yet overlapping representations of task, location, and context in both MEC and LEC axons. MEC transmitted highly location- and context-specific codes; LEC inputs were biased by ongoing navigational goals. However, during tasks with reliable reward locations, the animals' position could be accurately decoded from either subregion. Our results revise the prevailing dogma about EC information processing, revealing novel ways spatial and non-spatial information is routed and combined upstream of the hippocampus.

A realistic computational model for the formation of a Place Cell

Hippocampal Place Cells (PCs) are pyramidal neurons showing spatially localized firing when an animal gets into a specific area within an environment. Because of their obvious and clear relation with specific cognitive functions, Place Cells operations and modulations are intensely studied experimentally. However, although a lot of data have been gathered since their discovery, the cellular processes that interplay to turn a hippocampal pyramidal neuron into a Place Cell are still not completely understood. Here, we used a morphologically and biophysically detailed computational model of a CA1 pyramidal neuron to show how, and under which conditions, it can turn into a neuron coding for a specific cue location, through the self-organization of its synaptic inputs in response to external signals targeting different dendritic layers. Our results show that the model is consistent with experimental findings demonstrating PCs stability within the same spatial context over different trajectories, environment rotations, and place field remapping to adapt to changes in the environment. To date, this is the only biophysically and morphologically accurate cellular model of PCs formation, which can be directly used in physiologically accurate microcircuits and large-scale model networks to study cognitive functions and dysfunctions at cellular level.

Estimating neuronal firing density: A quantitative analysis of firing rate map algorithms

The analysis of neurons that exhibit receptive fields dependent on an organism's spatial location, such as grid, place or boundary cells typically begins by mapping their activity in space using firing rate maps. However, mapping approaches are varied and depend on multiple tuning parameters that are usually chosen qualitatively by the experimenter and thus vary significantly across studies. Small changes in parameters such as these can impact results significantly, yet, to date a quantitative investigation of firing rate maps has not been attempted. Using simulated datasets, we examined how tuning parameters, recording duration and firing field size affect the accuracy of spatial maps generated using the most widely used approaches. For each approach we found a clear subset of parameters which yielded low-error firing rate maps and isolated the parameters yielding 1) the least error possible and 2) the Pareto-optimal parameter set which balanced error, computation time, place field detection accuracy and the extrapolation of missing values. Smoothed bivariate histograms and averaged shifted histograms were consistently associated with the fastest computation times while still providing accurate maps. Adaptive smoothing and binning approaches were found to compensate for low positional sampling the most effectively. Kernel smoothed density estimation also compensated for low sampling well and resulted in accurate maps, but it was also among the slowest methods tested. Overall, the bivariate histogram, coupled with spatial smoothing, is likely the most desirable method in the majority of cases.

Variational log-Gaussian point-process methods for grid cells

We present practical solutions to applying Gaussian-process (GP) methods to calculate spatial statistics for grid cells in large environments. GPs are a data efficient approach to inferring neural tuning as a function of time, space, and other variables. We discuss how to design appropriate kernels for grid cells, and show that a variational Bayesian approach to log-Gaussian Poisson models can be calculated quickly. This class of models has closed-form expressions for the evidence lower-bound, and can be estimated rapidly for certain parameterizations of the posterior covariance. We provide an implementation that operates in a low-rank spatial frequency subspace for further acceleration, and demonstrate these methods on experimental data.

Minute-scale periodicity of neuronal firing in the human entorhinal cortex

Grid cells in the entorhinal cortex demonstrate spatially periodic firing, thought to provide a spatial map on behaviorally relevant length scales. Whether such periodicity exists for behaviorally relevant time scales in the human brain remains unclear. We investigate neuronal firing during a temporally continuous experience by presenting 14 neurosurgical patients with a video while recording neuronal activity from multiple brain regions. We report on neurons that modulate their activity in a periodic manner across different time scales-from seconds to many minutes, most prevalently in the entorhinal cortex. These neurons remap their dominant periodicity to shorter time scales during a subsequent recognition memory task. When the video is presented at two different speeds, a significant percentage of these temporally periodic cells (TPCs) maintain their time scales, suggesting a degree of invariance. The TPCs' temporal periodicity might complement the spatial periodicity of grid cells and together provide scalable spatiotemporal metrics for human experience.

Levodopa suppresses grid-like activity and impairs spatial learning in novel environments in healthy young adults

Accumulated evidence from animal studies suggests a role for the neuromodulator dopamine in memory processes, particularly under conditions of novelty or reward. Our understanding of how dopaminergic modulation impacts spatial representations and spatial memory in humans remains limited. Recent evidence suggests age-specific regulation effects of dopamine pharmacology on activity in the medial temporal lobe, a key region for spatial memory. To which degree this modulation affects spatially patterned medial temporal representations remains unclear. We reanalyzed recent data from a pharmacological dopamine challenge during functional brain imaging combined with a virtual object-location memory paradigm to assess the effect of Levodopa, a dopamine precursor, on grid-like activity in the entorhinal cortex. We found that Levodopa impaired grid cell-like representations in a sample of young adults (n = 55, age = 26-35 years) in a novel environment, accompanied by reduced spatial memory performance. We observed no such impairment when Levodopa was delivered to participants who had prior experience with the task. These results are consistent with a role of dopamine in modulating the encoding of novel spatial experiences. Our results suggest that dopamine signaling may play a larger role in shaping ongoing spatial representations than previously thought.

Entorhinal cortex glutamatergic and GABAergic projections bidirectionally control discrimination and generalization of hippocampal representations

Discrimination and generalization are crucial brain-wide functions for memory and object recognition that utilize pattern separation and completion computations. Circuit mechanisms supporting these operations remain enigmatic. We show lateral entorhinal cortex glutamatergic (LEC GLU ) and GABAergic (LEC GABA ) projections are essential for object recognition memory. Silencing LEC GLU during in vivo two-photon imaging increased the population of active CA3 pyramidal cells but decreased activity rates, suggesting a sparse coding function through local inhibition. Silencing LEC GLU also decreased place cell remapping between different environments validating this circuit drives pattern separation and context discrimination. Optogenetic circuit mapping confirmed that LEC GLU drives dominant feedforward inhibition to prevent CA3 somatic and dendritic spikes. However, conjunctively active LEC GABA suppresses this local inhibition to disinhibit CA3 pyramidal neuron soma and selectively boost integrative output of LEC and CA3 recurrent network. LEC GABA thus promotes pattern completion and context generalization. Indeed, without this disinhibitory input, CA3 place maps show decreased similarity between contexts. Our findings provide circuit mechanisms whereby long-range glutamatergic and GABAergic cortico-hippocampal inputs bidirectionally modulate pattern separation and completion, providing neuronal representations with a dynamic range for context discrimination and generalization.