Speed cells in the medial entorhinal cortex

Motor and vestibular signals in the visual cortex permit the separation of self versus externally generated visual motion

Knowing whether we are moving or something in the world is moving around us is possibly the most critical sensory discrimination we need to perform. How the brain and, in particular, the visual system solves this motion-source separation problem is not known. Here, we find that motor, vestibular, and visual motion signals are used by the mouse primary visual cortex (VISp) to differentially represent the same visual flow information according to whether the head is stationary or experiencing passive versus active translation. During locomotion, we find that running suppresses running-congruent translation input and that translation signals dominate VISp activity when running and translation speed become incongruent. This cross-modal interaction between the motor and vestibular systems was found throughout the cortex, indicating that running and translation signals provide a brain-wide egocentric reference frame for computing the internally generated and actual speed of self when moving through and sensing the external world.

Hand position fields of neurons in the premotor cortex of macaques during natural reaching

While hippocampus represents spatial information through place cells for body navigation, whether motor areas employ a similar framework to guide hand reaching remains unknown. Here, we investigate tuning properties in dorsal premotor cortex (PMd) during naturalistic reach-and-grasp tasks in four monkeys. We find that 22% (132/601) of PMd neurons increase firing rates when the monkey's hand occupies specific positions in space, forming the position fields. These cells represent the hand position highly efficiently, achieving ~80% accuracy for decoding hand trajectories with only 50 most dedicated position tuned cells ( ~ 10% of all recorded neurons). The hand position is co-represented with hand moving direction, speed, and reward location in the same population of PMd neurons, forming a mixed-selective framework to integrate positional and kinematic information. Our findings suggest field-like positional coding may be a mechanism shared across brain regions for spatial representation in goal-directed movements, including body navigation and forelimb reaching.

Hippocampus shapes entorhinal cortical output through a direct feedback circuit

Our brains integrate sensory, cognitive and internal state information with memories to extract behavioral relevance. Cortico-hippocampal interactions likely mediate this interplay, but underlying circuit mechanisms remain elusive. Unlike the entorhinal cortex-to-hippocampus pathway, we know little about the organization and function of the hippocampus-to-cortex feedback circuit. Here we report in mice, two functionally distinct parallel hippocampus-to-entorhinal cortex feedback pathways: the canonical disynaptic route via layer 5 and a novel monosynaptic input to layer 2/3. Circuit mapping reveals that hippocampal input predominantly drives excitation in layer 5 but feed-forward inhibition in layer 2/3. Upon repetitive pairing with cortical layer 1 inputs, hippocampal inputs undergo homosynaptic potentiation in layer 5, but induce heterosynaptic plasticity and spike output in layer 2/3. Behaviorally, hippocampal inputs to layer 5 and layer 2/3 support object memory encoding versus recall, respectively. Two-photon imaging during navigation reveals hippocampal suppression reduces spatially tuned cortical axonal activity. We present a model, where hippocampal feedback could iteratively shape ongoing cortical processing.

Impairment of theta oscillations in the hippocampal CA1 region may mediate age-dependent movement alternations in the 5xFAD mouse model of Alzheimer's disease

Clinical evidences indicate that multifaceted gait abnormalities may manifest in Alzheimer's disease (AD) patients, which are associated with cognitive decline. Although the correlation between hippocampal theta power and locomotion has been known for a long time, the mechanisms by how hippocampal impairment participates in the altered gait seen in AD is not fully understood. To explore the manifestations of gait disorders in AD, we characterized gait performance in 3-, 6-, and 9-month-old male 5xFAD and control mice in the semi-automated, highly sensitive, Catwalk XT system. The 5xFAD mice displayed a decrease in kinetic parameters (average speed and cadence), and spatial parameters (paw area), while the temporal parameters (stance and swing time) were significantly increased. The parameters of interlimb coordination also displayed deficits. The majority of impairment variables related to the slow speed in 5xFAD mice at 9-month-old. We further explored the theta oscillations in the brain by in vivo tetrode recording of the hippocampal CA1. The results showed that the theta oscillations reduced in the hippocampal CA1 of 5xFAD mice, which related to the gait impairments. In conclusion, gait impairments started at 6 months of age, manifested at 9 months of age in 5xFAD mice. A reduction in theta oscillation power of the hippocampal CA1 may be responsible for the gait impairments.

Self-supervised learning of scale-invariant neural representations of space and time

Hippocampal representations of space and time seem to share a common coding scheme characterized by neurons with bell-shaped tuning curves called place and time cells. The properties of the tuning curves are consistent with Weber's law, such that, in the absence of visual inputs, width scales with the peak time for time cells and with distance for place cells. Building on earlier computational work, we examined how neurons with such properties can emerge through self-supervised learning. We found that a network based on autoencoders can, given a particular inputs and connectivity constraints, produce scale-invariant time cells. When the animal's velocity modulates the decay rate of the leaky integrators, the same network gives rise to scale-invariant place cells. Importantly, this is not the case when velocity is fed as a direct input to the leaky integrators, implying that weight modulation by velocity might be critical for developing scale-invariant spatial receptive fields. Finally, we demonstrated that after training, scale-invariant place cells emerge in environments larger than those used during training. Taken together, these findings bring us closer to understanding the emergence of neurons with bell-shaped tuning curves in the hippocampus and highlight the critical role of velocity modulation in the formation of scale-invariant place 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 the 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 the MEC and between HPC and 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.

How does the response of egocentric boundary cells depend upon the coordinate system of environmental features?

Neurons in the retrosplenial (RSC) (Alexander et al., 2020a; LaChance and Hasselmo, 2024) and postrhinal cortex (POR) respond to environmental boundaries and configurations in egocentric coordinates relative to an animals current position. Neurons in these structures and adjacent structures also respond to spatial dimensions of self- motion such as running velocity (Carstensen et al., 2021; Robinson et al., 2024). Data and modeling suggest that these responses could be essential for guiding behaviors such as barrier avoidance and goal finding (Erdem and Hasselmo, 2012; 2014). However, these findings still leave the unanswered question: What are the features and what are the coordinate systems of these features that drive these egocentric neural responses? Here we present models of the potential circuit mechanisms generating egocentric responses in RSC. These can be generated based on coding of internal representations of barriers in head-centered coordinates of distance and angle that are transformed based on current running velocity for trajectory planning and obstacle avoidance. This hypothesis is compared with an alternate potentially complementary hypothesis that neurons in the same regions might respond to retinotopic position of features at the top, bottom or edges of walls as a precursor to head-centered coordinates. Alternate hypotheses include the forward scanning of trajectories (ray tracing) to test for collision with barriers, or the comparison of optic flow on different sides of the animal. These hypotheses generate complementary modeling predictions about how changes in environmental parameters could alter the neural responses of egocentric boundary cells that are presented here.

Allocentric and egocentric spatial representations coexist in rodent medial entorhinal cortex

Successful navigation relies on reciprocal transformations between spatial representations in world-centered (allocentric) and self-centered (egocentric) frames of reference. The neural basis of allocentric spatial representations has been extensively investigated with grid, border, and head-direction cells in the medial entorhinal cortex (MEC) forming key components of a 'cognitive map'. Recently, egocentric spatial representations have also been identified in several brain regions, but evidence for the coexistence of neurons encoding spatial variables in each reference frame within MEC is so far lacking. Here, we report that allocentric and egocentric spatial representations are both present in rodent MEC, with neurons in deeper layers representing the egocentric bearing and distance towards the geometric center and / or boundaries of an environment. These results demonstrate a unity of spatial coding that can guide efficient navigation and suggest that MEC may be one locus of interactions between egocentric and allocentric spatial representations in the mammalian brain.

Hippocampal Discoveries: Spatial View Cells, Connectivity, and Computations for Memory and Navigation, in Primates Including Humans

Two key series of discoveries about the hippocampus are described. One is the discovery of hippocampal spatial view cells in primates. This discovery opens the way to a much better understanding of human episodic memory, for episodic memory prototypically involves a memory of where people or objects or rewards have been seen in locations "out there" which could never be implemented by the place cells that encode the location of a rat or mouse. Further, spatial view cells are valuable for navigation using vision and viewed landmarks, and provide for much richer, vision-based, navigation than the place to place self-motion update performed by rats and mice who live in dark underground tunnels. Spatial view cells thus offer a revolution in our understanding of the functions of the hippocampus in memory and navigation in humans and other primates with well-developed foveate vision. The second discovery describes a computational theory of the hippocampal-neocortical memory system that includes the only quantitative theory of how information is recalled from the hippocampus to the neocortex. It is shown how foundations for this research were the discovery of reward neurons for food reward, and non-reward, in the primate orbitofrontal cortex, and representations of value including of monetary value in the human orbitofrontal cortex; and the discovery of face identity and face expression cells in the primate inferior temporal visual cortex and how they represent transform-invariant information. This research illustrates how in order to understand a brain computation, a whole series of integrated interdisciplinary discoveries is needed to build a theory of the operation of each neural system.

Effects of high-intensity interval training and moderate-intensity continuous training on neural dynamics and firing in the CA1-MEC region of mice

The aim of this study is to investigate the differential impacts of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on neural circuit dynamics and neuronal firing in the hippocampal CA1 subregion (CA1) region and medial entorhinal cortex (MEC) of mice. Forty-two male ICR mice were randomized into control, HIIT, and MICT groups. Electrophysiological recordings were performed pre- and postintervention to assess neural circuit dynamics and neuronal firing patterns in the CA1-MEC pathway. Both exercise protocols increased local field potential (LFP) coherence, with MICT showing a more pronounced effect on δ and γ coherences (P < 0.05). Both modalities reduced δ power spectral density (PSD) (HIIT, P < 0.05; MICT, P < 0.01) and elevated θ, β, and γ PSDs. Neuronal firing frequency improved in both CA1 and MEC following HIIT and MICT (P < 0.05). HIIT enhanced firing regularity in CA1 (P < 0.05), whereas MICT improved regularity in both regions (P < 0.05). Both protocols reduced firing latency (HIIT, P < 0.05; MICT, P < 0.01) and enhanced burst firing ratio, interburst interval (IBI), burst duration (BD), and LFP phase locking (P < 0.05 or P < 0.01). Notably, MICT significantly improved spatial working memory and novel recognition abilities, as evidenced by increased novel arm time, entries, and preference index (P < 0.01). This study reveals that both HIIT and MICT positively impact neural processing and information integration in the CA1-MEC network of mice. Notably, MICT exhibits a more pronounced impact on neural functional connectivity and cognitive function compared with HIIT. These findings, coupled with the similarities in hippocampal electrophysiological characteristics between rodents and humans, suggest potential exercise-mediated neural plasticity and cognitive benefits in humans.NEW & NOTEWORTHY This study is the first to investigate HIIT and MICT's effects on neural activity in the mouse CA1-MEC circuit, demonstrating that exercise modulates processing, enhances integration, and boosts cognitive performance. Due to similar hippocampal electrophysiology in rodents and humans during movement and navigation, our findings suggest implications for human brain neural changes, advancing the understanding of neurophysiological mechanisms underlying exercise-cognition interactions and informing exercise recommendations for cognitive health.

Unweaving the Cognitive Map: A Personal History

I have been incredibly fortunate to have worked in the field of hippocampal spatial coding during three of its most exciting decades, the 1990s, 2000s, and 2010s. During this time I had a ringside view of some of the foundational discoveries that were made which have transformed our understanding of the hippocampal system and its role in cognition (especially spatial cognition) and memory. These discoveries inspired me in my own lab over the years to pursue three broad lines of enquiry-3D spatial encoding, context and the sense of direction-which are outlined here. If some of my personal recollections are a little inaccurate (such is the nature of episodic memory!) I apologize in advance.

Vector coding and place coding in hippocampus share a common directional signal

Vector coding is a major mechanism by which neural systems represent an animal's location in both global and local, item-based reference frames. Landmark vector cells (LVCs) in the hippocampus complement classic place cells by encoding vector relationships between the organism and specific landmarks. How these place- and vector-coding properties interact is not known. We recorded place cells and LVCs using calcium imaging of the CA1 region of freely moving rats during cue-card rotation studies. Place fields rotated around the center of the platform to follow the cue rotation, whereas the fields of simultaneously recorded LVCs rotated by the same amount around the nearby landmarks. Some neurons demonstrated conjunctive coding of both classic place field properties and LVC properties. These results demonstrate that CA1 neurons employ a common directional input, presumably provided by the head direction cell system, to encode animals' locations in both world-centered and landmark-centered reference frames.

Distinct Functional Classes of CA1 Hippocampal Interneurons Are Modulated by Cerebellar Stimulation in a Coordinated Manner

There is mounting evidence that the cerebellum impacts hippocampal functioning, but the impact of the cerebellum on hippocampal interneurons remains obscure. Using miniscopes in freely behaving male and female mice, we found optogenetic stimulation of Purkinje cells alters the calcium activity of a large percentage of CA1 interneurons. This includes both increases and decreases in activity. Remarkably, this bidirectional impact occurs in a coordinated fashion, in line with interneurons' functional properties. Specifically, CA1 interneurons activated by cerebellar stimulation are commonly locomotion-active, while those inhibited by cerebellar stimulation are commonly rest-active interneurons. We additionally found that subsets of CA1 interneurons show altered activity during object investigations. Importantly, these interneurons also show coordinated modulation by cerebellar stimulation: CA1 interneurons that are activated by cerebellar stimulation are more likely to be activated, rather than inhibited, during object investigations, while interneurons that show decreased activity during cerebellar stimulation show the opposite profile. We examined two different stimulation locations (IV/V vermis or simplex) and two different stimulation approaches (7 Hz or a single 1 s light pulse)-in all cases, the cerebellum induces similar coordinated CA1 interneuron changes congruent with an explorative state. Overall, our data show that CA1 interneurons are impacted by cerebellar manipulation in a bidirectional and coordinated fashion and are therefore likely to play an important role in cerebello-hippocampal communication.

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.

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 mechanisms by which LEC integrates spatial and temporal information remain elusive. Here, we recorded LEC neurons while male rats performed one-dimensional tasks. Many LEC cells displayed spatial firing fields and demonstrated selectivity for traveling directions. Furthermore, some LEC neurons changed the firing rates of their spatial rate maps during a session (rate remapping). Importantly, this temporal modulation was consistent across sessions, even when the spatial environment was altered. Notably, the strength of temporal modulation was greater in LEC compared to other brain regions, such as the medial entorhinal cortex, CA1, and CA3. Thus, we demonstrate spatial rate mapping in LEC neurons, which may serve as a coding mechanism for temporal context, and allow for flexible multiplexing of spatial and temporal information.

Impaired spatial coding and neuronal hyperactivity in the medial entorhinal cortex of aged App NL-G-F mice

The progressive accumulation of amyloid beta (Aβ) pathology in the brain has been associated with aberrant neuronal network activity and poor cognitive performance in preclinical mouse models of Alzheimer's disease (AD). Presently, our understanding of the mechanisms driving pathology-associated neuronal dysfunction and impaired information processing in the brain remains incomplete. Here, we assessed the impact of advanced Aβ pathology on spatial information processing in the medial entorhinal cortex (MEC) of 18-month App NL-G-F/NL- G-F knock-in (APP KI) mice as they explored contextually novel and familiar open field arenas in a two-day, four-session recording paradigm. We tracked single unit firing activity across all sessions and found that spatial information scores were decreased in MEC neurons from APP KI mice versus those in age-matched C57BL/6J controls. MEC single unit spatial representations were also impacted in APP KI mice. Border cell firing preferences were unstable across sessions and spatial periodicity in putative grid cells was disrupted. In contrast, MEC border cells and grid cells in Control mice were intact and stable across sessions. We then quantified the stability of MEC spatial maps across sessions by utilizing a metric based on the Earth Mover's Distance (EMD). We found evidence for increased instability in spatially-tuned APP KI MEC neurons versus Controls when mice were re-exposed to familiar environments and exposed to a novel environment. Additionally, spatial decoding analysis of MEC single units revealed deficits in position and speed coding in APP KI mice in all session comparisons. Finally, MEC single unit analysis revealed a mild hyperactive phenotype in APP KI mice that appeared to be driven by narrow-spiking units (putative interneurons). These findings tie Aβ-associated dysregulation in neuronal firing to disruptions in spatial information processing that may underlie certain cognitive deficits associated with AD.

Idiothetic representations are modulated by availability of sensory inputs and task demands in the hippocampal-septal circuit

The hippocampus is a higher-order brain structure responsible for encoding new episodic memories and predicting future outcomes. In the absence of external stimuli, neurons in the hippocampus track elapsed time, distance traveled, and other idiothetic variables. To this day, the exact determinants of idiothetic representations during free navigation remain unclear. Here, we developed unsupervised approaches to extract population and single-cell properties of more than 30,000 CA1 pyramidal neurons in freely moving mice. We find that spatiotemporal representations are composed of a mixture of idiothetic and allocentric information, the balance of which is dictated by task demand and environmental conditions. Additionally, a subset of CA1 pyramidal neurons encodes the spatiotemporal distance to rewards. Finally, distance and time information is integrated postsynaptically in the lateral septum, indicating that these high-level representations are effectively integrated in downstream neurons.

Histamine-tuned subicular circuit mediates alert-driven accelerated locomotion in mice

The locomotive action involves diverse coordination, necessitating the integration of multiple motor neural circuits. However, the precise circuitry mechanism governing emotion-driven accelerated locomotion remains predominantly elusive. Here we dissect projections from the tuberomammillary nucleus (TMN) to subiculum (SUB) which promote alert-driven accelerated locomotion. We find that TMN histaminergic neurons respond to high-speed locomotion in both natural and alert acceleration. The TMN-SUB circuit is sufficient but not essential for amplifying accelerated locomotion from low to high-speed movement in basal condition, but it is both sufficient and necessary in alert condition for modulating accelerated locomotion during high-speed escape behavior. TMN histaminergic neuron activates SUB glutamatergic "fast locomotor cell" that projects to retrosplenial granular cortex (RSG) mainly through histamine H2 receptor (H2R). This study reveals the critical role of the histamine-tuned SUB circuit in alert-driven accelerated locomotion in mice, providing a theoretical foundation for comprehending neural circuit mechanisms of instinctive behaviors under alert.

Mapping spatial memory in teleosts: a new Frontier in neural logging techniques

Recent advancements in microelectromechanical system technology have significantly enhanced our ability to monitor neuronal activity in free-swimming fish without disrupting their natural movement, thereby greatly improving the capabilities of neural logging using "neurologger" technology. In this review, we compiled the findings from studies applying neurologgers to teleost fish, emphasizing the discovery of various spatial-cognition cells in regions of the telencephalon analogous to the mammalian hippocampus that are deeply involved in spatial navigation. We detailed how different fish species, such as goldfish and salmonids, correlate their neural activity with environmental boundaries, head direction, speed, and other navigational cues for spatial memory and navigation strategies. We critically analyzed the similarities and differences in these mechanisms to provide insights into the evolutionary aspects of spatial cognition. We also identified gaps in current methodologies and suggest directions for future research, emphasizing the need for further exploration of spatial encoding in aquatic environments. The insights gained herein suggest the existence of a complex and evolutionarily conserved substrate for navigation and memory in vertebrates, highlighting the potential of neurologgers to expand our understanding of spatial cognition.

Integration and competition between space and time in the hippocampus

Episodic memory is organized in both spatial and temporal contexts. The hippocampus is crucial for episodic memory and has been demonstrated to encode spatial and temporal information. However, how the representations of space and time interact in the hippocampal memory system is still unclear. Here, we recorded the activity of hippocampal CA1 neurons in mice in a variety of one-dimensional navigation tasks while systematically varying the speed of the animals. For all tasks, we found neurons simultaneously represented space and elapsed time. There was a negative correlation between the preferred space and lap duration, e.g., the preferred spatial position shifted more toward the origin when the lap duration became longer. A similar relationship between the preferred time and traveled distance was also observed. The results strongly suggest a competitive and integrated representation of space-time by single hippocampal neurons, which may provide the neural basis for spatiotemporal contexts.

Neural circuits for goal-directed navigation across species

Across species, navigation is crucial for finding both resources and shelter. In vertebrates, the hippocampus supports memory-guided goal-directed navigation, whereas in arthropods the central complex supports similar functions. A growing literature is revealing similarities and differences in the organization and function of these brain regions. We review current knowledge about how each structure supports goal-directed navigation by building internal representations of the position or orientation of an animal in space, and of the location or direction of potential goals. We describe input pathways to each structure - medial and lateral entorhinal cortex in vertebrates, and columnar and tangential neurons in insects - that primarily encode spatial and non-spatial information, respectively. Finally, we highlight similarities and differences in spatial encoding across clades and suggest experimental approaches to compare coding principles and behavioral capabilities across species. Such a comparative approach can provide new insights into the neural basis of spatial navigation and neural computation.

One-shot entorhinal maps enable flexible navigation in novel environments

Animals must navigate changing environments to find food, shelter or mates. In mammals, grid cells in the medial entorhinal cortex construct a neural spatial map of the external environment1-5. However, how grid cell firing patterns rapidly adapt to novel or changing environmental features on a timescale relevant to behaviour remains unknown. Here, by recording over 15,000 grid cells in mice navigating virtual environments, we tracked the real-time state of the grid cell network. This allowed us to observe and predict how altering environmental features influenced grid cell firing patterns on a nearly instantaneous timescale. We found evidence that visual landmarks provide inputs to fixed points in the grid cell network. This resulted in stable grid cell firing patterns in novel and altered environments after a single exposure. Fixed visual landmark inputs also influenced the grid cell network such that altering landmarks induced distortions in grid cell firing patterns. Such distortions could be predicted by a computational model with a fixed landmark to grid cell network architecture. Finally, a medial entorhinal cortex-dependent task revealed that although grid cell firing patterns are distorted by landmark changes, behaviour can adapt via a downstream region implementing behavioural timescale synaptic plasticity6. Overall, our findings reveal how the navigational system of the brain constructs spatial maps that balance rapidity and accuracy. Fixed connections between landmarks and grid cells enable the brain to quickly generate stable spatial maps, essential for navigation in novel or changing environments. Conversely, plasticity in regions downstream from grid cells allows the spatial maps of the brain to more accurately mirror the external spatial environment. More generally, these findings raise the possibility of a broader neural principle: by allocating fixed and plastic connectivity across different networks, the brain can solve problems requiring both rapidity and representational accuracy.

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'.

Distinct cortical spatial representations learned along disparate visual pathways

Recent experimental studies have discovered diverse spatial properties, such as head direction tuning and egocentric tuning, of neurons in the postrhinal cortex (POR) and revealed how the POR spatial representation is distinct from the retrosplenial cortex (RSC). However, how these spatial properties of POR neurons emerge is unknown, and the cause of distinct cortical spatial representations is also unclear. Here, we build a learning model of POR based on the pathway from the superior colliculus (SC) that has been shown to have motion processing within the visual input. Our designed SC-POR model demonstrates that diverse spatial properties of POR neurons can emerge from a learning process based on visual input that incorporates motion processing. Moreover, combining SC-POR model with our previously proposed V1-RSC model, we show that distinct cortical spatial representations in POR and RSC can be learnt along disparate visual pathways (originating in SC and V1), suggesting that the varying features encoded in different visual pathways contribute to the distinct spatial properties in downstream cortical areas.

Predictive Representations: Building Blocks of Intelligence

Adaptive behavior often requires predicting future events. The theory of reinforcement learning prescribes what kinds of predictive representations are useful and how to compute them. This review integrates these theoretical ideas with work on cognition and neuroscience. We pay special attention to the successor representation and its generalizations, which have been widely applied as both engineering tools and models of brain function. This convergence suggests that particular kinds of predictive representations may function as versatile building blocks of intelligence.

Conjunctive processing of spatial border and locomotion in retrosplenial cortex during spatial navigation

Spatial information and dynamic locomotor behaviours are equally important for achieving locomotor goals during spatial navigation. However, it remains unclear how spatial and locomotor information is integrated during the processing of self-initiated spatial navigation. Anatomically, the retrosplenial cortex (RSC) has reciprocal connections with brain regions related to spatial processing, including the hippocampus and para-hippocampus, and also receives inputs from the secondary motor cortex. In addition, RSC is functionally associated with allocentric and egocentric spatial targets and head-turning. So, RSC may be a critical region for integrating spatial and locomotor information. In this study, we first examined the role of RSC in spatial navigation using the Morris water maze and found that mice with inactivated RSC took a longer time and distance to reach their destination. Then, by imaging neuronal activity in freely behaving mice within two open fields of different sizes, we identified a large proportion of border cells, head-turning cells and locomotor speed cells in the superficial layer of RSC. Interestingly, some RSC neurons exhibited conjunctive coding for both spatial and locomotor signals. Furthermore, these conjunctive neurons showed higher prediction accuracy compared with simple spatial or locomotor neurons in special navigator scenes using the border, turning and positive-speed conjunctive cells. Our study reveals that the RSC is an important conjunctive brain region that processes spatial and locomotor information during spatial navigation. KEY POINTS: Retrosplenial cortex (RSC) is indispensable during spatial navigation, which was displayed by the longer time and distance of mice to reach their destination after the inactivation of RSC in a water maze. The superficial layer of RSC has a larger population of spatial-related border cells, and locomotion-related head orientation and speed cells; however, it has few place cells in two-dimensional spatial arenas. Some RSC neurons exhibited conjunctive coding for both spatial and locomotor signals, and the conjunctive neurons showed higher prediction accuracy compared with simple spatial or locomotor neurons in special navigation scenes. Our study reveals that the RSC is an important conjunctive brain region that processes both spatial and locomotor information during spatial navigation.

Entorhinal cortex-hippocampal circuit connectivity in health and disease

The entorhinal cortex (EC) and hippocampal (HC) connectivity is the main source of episodic memory formation and consolidation. The entorhinal-hippocampal (EC-HC) connection is classified as canonically glutamatergic and, more recently, has been characterized as a non-canonical GABAergic connection. Recent evidence shows that both EC and HC receive inputs from dopaminergic, cholinergic, and noradrenergic projections that modulate the mnemonic processes linked to the encoding and consolidation of memories. In the present review, we address the latest findings on the EC-HC connectivity and the role of neuromodulations during the mnemonic mechanisms of encoding and consolidation of memories and highlight the value of the cross-species approach to unravel the underlying cellular mechanisms known. Furthermore, we discuss how EC-HC connectivity early neurodegeneration may contribute to the dysfunction of episodic memories observed in aging and Alzheimer's disease (AD). Finally, we described how exercise may be a fundamental tool to prevent or decrease neurodegeneration.

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.

A spatial transformation-based CAN model for information integration within grid cell modules

The hippocampal-entorhinal circuit is considered to play an important role in the spatial cognition of animals. However, the mechanism of the information flow within the circuit and its contribution to the function of the grid-cell module are still topics of discussion. Prevailing theories suggest that grid cells are primarily influenced by self-motion inputs from the Medial Entorhinal Cortex, with place cells serving a secondary role by contributing to the visual calibration of grid cells. However, recent evidence suggests that both self-motion inputs and visual cues may collaboratively contribute to the formation of grid-like patterns. In this paper, we introduce a novel Continuous Attractor Network model based on a spatial transformation mechanism. This mechanism enables the integration of self-motion inputs and visual cues within grid-cell modules, synergistically driving the formation of grid-like patterns. From the perspective of individual neurons within the network, our model successfully replicates grid firing patterns. From the view of neural population activity within the network, the network can form and drive the activated bump, which describes the characteristic feature of grid-cell modules, namely, path integration. Through further exploration and experimentation, our model can exhibit significant performance in path integration. This study provides a new insight into understanding the mechanism of how the self-motion and visual inputs contribute to the neural activity within grid-cell modules. Furthermore, it provides theoretical support for achieving accurate path integration, which holds substantial implications for various applications requiring spatial navigation and mapping.

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.

A theory of hippocampal function: New developments

We develop further here the only quantitative theory of the storage of information in the hippocampal episodic memory system and its recall back to the neocortex. The theory is upgraded to account for a revolution in understanding of spatial representations in the primate, including human, hippocampus, that go beyond the place where the individual is located, to the location being viewed in a scene. This is fundamental to much primate episodic memory and navigation: functions supported in humans by pathways that build 'where' spatial view representations by feature combinations in a ventromedial visual cortical stream, separate from those for 'what' object and face information to the inferior temporal visual cortex, and for reward information from the orbitofrontal cortex. Key new computational developments include the capacity of the CA3 attractor network for storing whole charts of space; how the correlations inherent in self-organizing continuous spatial representations impact the storage capacity; how the CA3 network can combine continuous spatial and discrete object and reward representations; the roles of the rewards that reach the hippocampus in the later consolidation into long-term memory in part via cholinergic pathways from the orbitofrontal cortex; and new ways of analysing neocortical information storage using Potts networks.

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.

Modeling the grid cell activity based on cognitive space transformation

The grid cells in the medial entorhinal cortex are widely recognized as a critical component of spatial cognition within the entorhinal-hippocampal neuronal circuits. To account for the hexagonal patterns, several computational models have been proposed. However, there is still considerable debate regarding the interaction between grid cells and place cells. In response, we have developed a novel grid-cell computational model based on cognitive space transformation, which established a theoretical framework of the interaction between place cells and grid cells for encoding and transforming positions between the local frame and global frame. Our model not only can generate the firing patterns of the grid cells but also reproduces the biological experiment results about the grid-cell global representation of connected environments and supports the conjecture about the underlying reason. Moreover, our model provides new insights into how grid cells and place cells integrate external and self-motion cues.

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.

A hippocampus-accumbens code guides goal-directed appetitive behavior

The dorsal hippocampus (dHPC) is a key brain region for the expression of spatial memories, such as navigating towards a learned reward location. The nucleus accumbens (NAc) is a prominent projection target of dHPC and implicated in value-based action selection. Yet, the contents of the dHPC→NAc information stream and their acute role in behavior remain largely unknown. Here, we found that optogenetic stimulation of the dHPC→NAc pathway while mice navigated towards a learned reward location was both necessary and sufficient for spatial memory-related appetitive behaviors. To understand the task-relevant coding properties of individual NAc-projecting hippocampal neurons (dHPC→NAc), we used in vivo dual-color two-photon imaging. In contrast to other dHPC neurons, the dHPC→NAc subpopulation contained more place cells, with enriched spatial tuning properties. This subpopulation also showed enhanced coding of non-spatial task-relevant behaviors such as deceleration and appetitive licking. A generalized linear model revealed enhanced conjunctive coding in dHPC→NAc neurons which improved the identification of the reward zone. We propose that dHPC routes specific reward-related spatial and behavioral state information to guide NAc action selection.

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.

Neural and behavioural state switching during hippocampal dentate spikes

Distinct brain and behavioural states are associated with organized neural population dynamics that are thought to serve specific cognitive functions1-3. Memory replay events, for example, occur during synchronous population events called sharp-wave ripples in the hippocampus while mice are in an 'offline' behavioural state, enabling cognitive mechanisms such as memory consolidation and planning4-11. But how does the brain re-engage with the external world during this behavioural state and permit access to current sensory information or promote new memory formation? Here we found that the hippocampal dentate spike, an understudied population event that frequently occurs between sharp-wave ripples12, may underlie such a mechanism. We show that dentate spikes are associated with distinctly elevated brain-wide firing rates, primarily observed in higher order networks, and couple to brief periods of arousal. Hippocampal place coding during dentate spikes aligns to the mouse's current spatial location, unlike the memory replay accompanying sharp-wave ripples. Furthermore, inhibiting neural activity during dentate spikes disrupts associative memory formation. Thus, dentate spikes represent a distinct brain state and support memory during non-locomotor behaviour, extending the repertoire of cognitive processes beyond the classical offline functions.

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.

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.

Fantastic beasts and how to study them: rethinking experimental animal behavior

Humans have been trying to understand animal behavior at least since recorded history. Recent rapid development of new technologies has allowed us to make significant progress in understanding the physiological and molecular mechanisms underlying behavior, a key goal of neuroethology. However, there is a tradeoff when studying animal behavior and its underlying biological mechanisms: common behavior protocols in the laboratory are designed to be replicable and controlled, but they often fail to encompass the variability and breadth of natural behavior. This Commentary proposes a framework of 10 key questions that aim to guide researchers in incorporating a rich natural context into their experimental design or in choosing a new animal study system. The 10 questions cover overarching experimental considerations that can provide a template for interspecies comparisons, enable us to develop studies in new model organisms and unlock new experiments in our quest to understand behavior.

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.

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.

Localized APP expression results in progressive network dysfunction by disorganizing spike timing

Progressive cognitive decline in Alzheimer's disease could either be caused by a spreading molecular pathology or by an initially focal pathology that causes aberrant neuronal activity in a larger network. To distinguish between these possibilities, we generated a mouse model with expression of mutant human amyloid precursor protein (APP) in only hippocampal CA3 cells. We found that performance in a hippocampus-dependent memory task was impaired in young adult and aged mutant mice. In both age groups, we then recorded from the CA1 region, which receives inputs from APP-expressing CA3 cells. We observed that theta oscillation frequency in CA1 was reduced along with disrupted relative timing of principal cells. Highly localized pathology limited to the presynaptic CA3 cells is thus sufficient to cause aberrant firing patterns in postsynaptic neuronal networks, which indicates that disease progression is not only from spreading pathology but also mediated by progressively advancing physiological dysfunction.