Spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity.

Understanding the functional connectivity between brain regions and its emergent dynamics is a central challenge. Here we present a theory-experiment hybrid approach involving iteration between a minimal computational model and in vivo electrophysiological measurements. Our model not only predicted spontaneous persistent activity (SPA) during Up-Down-State oscillations, but also inactivity (SPI), which has never been reported. These were confirmed in vivo in the membrane potential of neurons, especially from layer 3 of the medial and lateral entorhinal cortices. The data was then used to constrain two free parameters, yielding a unique, experimentally determined model for each neuron. Analytic and computational analysis of the model generated a dozen quantitative predictions about network dynamics, which were all confirmed in vivo to high accuracy. Our technique predicted functional connectivity; e. g. the recurrent excitation is stronger in the medial than lateral entorhinal cortex. This too was confirmed with connectomics data. This technique uncovers how differential cortico-entorhinal dialogue generates SPA and SPI, which could form an energetically efficient working-memory substrate and influence the consolidation of memories during sleep. More broadly, our procedure can reveal the functional connectivity of large networks and a theory of their emergent dynamics.

Altered grid-like coding in early blind people.

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

Neuronal population representation of human emotional memory.

Understanding how emotional processing modulates learning and memory is crucial for the treatment of neuropsychiatric disorders characterized by emotional memory dysfunction. We investigate how human medial temporal lobe (MTL) neurons support emotional memory by recording spiking activity from the hippocampus, amygdala, and entorhinal cortex during encoding and recognition sessions of an emotional memory task in patients with pharmaco-resistant epilepsy. Our findings reveal distinct representations for both remembered compared to forgotten and emotional compared to neutral scenes in single units and MTL population spiking activity. Additionally, we demonstrate that a distributed network of human MTL neurons exhibiting mixed selectivity on a single-unit level collectively processes emotion and memory as a network, with a small percentage of neurons responding conjointly to emotion and memory. Analyzing spiking activity enables a detailed understanding of the neurophysiological mechanisms underlying emotional memory and could provide insights into how emotion alters memory during healthy and maladaptive learning.

Evidence for grid-cell-like activity in the time domain.

The relation between the processing of space and time in the brain has been an enduring cross-disciplinary question. Grid cells have been recognized as a hallmark of the mammalian navigation system, with recent studies attesting to their involvement in the organization of conceptual knowledge in humans. To determine whether grid-cell-like representations support temporal processing, we asked subjects to mentally simulate changes in age and time-of-day, each constituting "trajectory" in an age-day space, while undergoing fMRI. We found that grid-cell-like representations supported trajecting across this age-day space. Furthermore, brain regions concurrently coding past-to-future orientation positively modulated the magnitude of grid-cell-like representation in the left entorhinal cortex. Finally, our findings suggest that temporal processing may be supported by spatially modulated systems, and that innate regularities of abstract domains may interface and alter grid-cell-like representations, similarly to spatial geometry.

Low frequency stimulation for seizure suppression: Identification of optimal targets in the entorhinal-hippocampal circuit.

BACKGROUND: Mesial temporal lobe epilepsy (MTLE) with hippocampal sclerosis (HS) is a common form of drug-resistant focal epilepsy in adults. Treatment for pharmacoresistant patients remains a challenge, with deep brain stimulation (DBS) showing promise for alleviating intractable seizures. This study explores the efficacy of low frequency stimulation (LFS) on specific neuronal targets within the entorhinal-hippocampal circuit in a mouse model of MTLE. OBJECTIVE: Our previous research demonstrated that LFS of the medial perforant path (MPP) fibers in the sclerotic hippocampus reduced seizures in epileptic mice. Here, we aimed to identify the critical neuronal population responsible for this antiepileptic effect by optogenetically stimulating presynaptic and postsynaptic compartments of the MPP-dentate granule cell (DGC) synapse at 1 Hz. We hypothesize that specific targets for LFS can differentially influence seizure activity depending on the cellular identity and location within or outside the seizure focus. METHODS: We utilized the intrahippocampal kainate (ihKA) mouse model of MTLE and targeted specific neural populations using optogenetic stimulation. We recorded intracranial neuronal activity from freely moving chronically epileptic mice with and without optogenetic LFS up to 3 h. RESULTS: We found that LFS of MPP fibers in the sclerotic hippocampus effectively suppressed epileptiform activity while stimulating principal cells in the MEC had no impact. Targeting DGCs in the sclerotic septal or non-sclerotic temporal hippocampus with LFS did not reduce seizure numbers but shortened the epileptiform bursts. CONCLUSION: Presynaptic stimulation of the MPP-DGC synapse within the sclerotic hippocampus is critical for seizure suppression via LFS.

Heterosynaptic plasticity of the visuo-auditory projection requires cholecystokinin released from entorhinal cortex afferents.

The entorhinal cortex is involved in establishing enduring visuo-auditory associative memory in the neocortex. Here we explored the mechanisms underlying this synaptic plasticity related to projections from the visual and entorhinal cortices to the auditory cortex in mice using optogenetics of dual pathways. High-frequency laser stimulation (HFS laser) of the visuo-auditory projection did not induce long-term potentiation. However, after pairing with sound stimulus, the visuo-auditory inputs were potentiated following either infusion of cholecystokinin (CCK) or HFS laser of the entorhino-auditory CCK-expressing projection. Combining retrograde tracing and RNAscope in situ hybridization, we show that Cck expression is higher in entorhinal cortex neurons projecting to the auditory cortex than in those originating from the visual cortex. In the presence of CCK, potentiation in the neocortex occurred when the presynaptic input arrived 200 ms before postsynaptic firing, even after just five trials of pairing. Behaviorally, inactivation of the CCK+ projection from the entorhinal cortex to the auditory cortex blocked the formation of visuo-auditory associative memory. Our results indicate that neocortical visuo-auditory association is formed through heterosynaptic plasticity, which depends on release of CCK in the neocortex mostly from entorhinal afferents.

Monosynaptic Rabies Tracing Reveals Sex- and Age-Dependent Dorsal Subiculum Connectivity Alterations in an Alzheimer's Disease Mouse Model.

The subiculum (SUB), a hippocampal formation structure, is among the earliest brain regions impacted in Alzheimer's disease (AD). Toward a better understanding of AD circuit-based mechanisms, we mapped synaptic circuit inputs to dorsal SUB using monosynaptic rabies tracing in the 5xFAD mouse model by quantitatively comparing the circuit connectivity of SUB excitatory neurons in age-matched controls and 5xFAD mice at different ages for both sexes. Input-mapped brain regions include the hippocampal subregions (CA1, CA2, CA3), medial septum and diagonal band, retrosplenial cortex, SUB, postsubiculum (postSUB), visual cortex, auditory cortex, somatosensory cortex, entorhinal cortex, thalamus, perirhinal cortex (Prh), ectorhinal cortex, and temporal association cortex. We find sex- and age-dependent changes in connectivity strengths and patterns of SUB presynaptic inputs from hippocampal subregions and other brain regions in 5xFAD mice compared with control mice. Significant sex differences for SUB inputs are found in 5xFAD mice for CA1, CA2, CA3, postSUB, Prh, lateral entorhinal cortex, and medial entorhinal cortex: all of these areas are critical for learning and memory. Notably, we find significant changes at different ages for visual cortical inputs to SUB. While the visual function is not ordinarily considered defective in AD, these specific connectivity changes reflect that altered visual circuitry contributes to learning and memory deficits. Our work provides new insights into SUB-directed neural circuit mechanisms during AD progression and supports the idea that neural circuit disruptions are a prominent feature of AD.

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

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

Spontaneous Dynamics of Hippocampal Place Fields in a Model of Combinatorial Competition among Stable Inputs.

We present computer simulations illustrating how the plastic integration of spatially stable inputs could contribute to the dynamic character of hippocampal spatial representations. In novel environments of slightly larger size than typical apparatus, the emergence of well-defined place fields in real place cells seems to rely on inputs from normally functioning grid cells. Theoretically, the grid-to-place transformation is possible if a place cell is able to respond selectively to a combination of suitably aligned grids. We previously identified the functional characteristics that allow a synaptic plasticity rule to accomplish this selection by synaptic competition during rat foraging behavior. Here, we show that the synaptic competition can outlast the formation of place fields, contributing to their spatial reorganization over time, when the model is run in larger environments and the topographical/modular organization of grid inputs is taken into account. Co-simulated cells that differ only by their randomly assigned grid inputs display different degrees and kinds of spatial reorganization-ranging from place-field remapping to more subtle in-field changes or lapses in firing. The model predicts a greater number of place fields and propensity for remapping in place cells recorded from more septal regions of the hippocampus and/or in larger environments, motivating future experimental standardization across studies and animal models. In sum, spontaneous remapping could arise from rapid synaptic learning involving inputs that are functionally homogeneous, spatially stable, and minimally stochastic.

Protocol to study microcircuits in the medial entorhinal cortex in mice using multiple patch-clamp recordings and morphological reconstruction.

Multiple patch-clamp recordings and morphological reconstruction are powerful approaches for neuronal microcircuitry dissection and cell type classification but are challenging due to the sophisticated expertise needed. Here, we present a protocol for applying these techniques to neurons in the medial entorhinal cortex (MEC) of mice. We detail steps to prepare brain slices containing MEC and perform simultaneous multiple whole-cell recordings, followed by procedures of histological staining and neuronal reconstruction. We then describe how we analyze morphological and electrophysiological features. For complete details on the use and execution of this protocol, please refer to Shi et al.1.

[Spatial navigation method based on the entorhinal-hippocampal-prefrontal information transmission circuit of rat's brain].

Physiological studies have revealed that rats perform spatial localization relying on grid cells and place cells in the entorhinal-hippocampal CA3 structure. The dynamic connection between the entorhinal-hippocampal structure and the prefrontal cortex is crucial for navigation. Based on these findings, this paper proposes a spatial navigation method based on the entorhinal-hippocampal-prefrontal information transmission circuit of the rat's brain, with the aim of endowing the mobile robot with strong spatial navigation capability. Using the hippocampal CA3-prefrontal spatial navigation model as a foundation, this paper constructed a dynamic self-organizing model with the hippocampal CA1 place cells as the basic unit to optimize the navigation path. The path information was then fed back to the impulse neural network via hippocampal CA3 place cells and prefrontal cortex action neurons, improving the convergence speed of the model and helping to establish long-term memory of navigation habits. To verify the validity of the method, two-dimensional simulation experiments and three-dimensional simulation robot experiments were designed in this paper. The experimental results showed that the method presented in this paper not only surpassed other algorithms in terms of navigation efficiency and convergence speed, but also exhibited good adaptability to dynamic navigation tasks. Furthermore, our method can be effectively applied to mobile robots.

Gamma oscillatory complexity conveys behavioral information in hippocampal networks.

The hippocampus and entorhinal cortex exhibit rich oscillatory patterns critical for cognitive functions. In the hippocampal region CA1, specific gamma-frequency oscillations, timed at different phases of the ongoing theta rhythm, are hypothesized to facilitate the integration of information from varied sources and contribute to distinct cognitive processes. Here, we show that gamma elements -a multidimensional characterization of transient gamma oscillatory episodes- occur at any frequency or phase relative to the ongoing theta rhythm across all CA1 layers in male mice. Despite their low power and stochastic-like nature, individual gamma elements still carry behavior-related information and computational modeling suggests that they reflect neuronal firing. Our findings challenge the idea of rigid gamma sub-bands, showing that behavior shapes ensembles of irregular gamma elements that evolve with learning and depend on hippocampal layers. Widespread gamma diversity, beyond randomness, may thus reflect complexity, likely functional but invisible to classic average-based analyses.

Outer layer of Vb neurons in medial entorhinal cortex project to hippocampal dentate gyrus in mice.

Entorhinal cortical (EC)-hippocampal (HPC) circuits are crucial for learning and memory. Although it was traditionally believed that superficial layers (II/III) of the EC mainly project to the HPC and deep layers (V/VI) receive input from the HPC, recent studies have highlighted the significant projections from layers Va and VI of the EC into the HPC. However, it still remains unknown whether Vb neurons in the EC provide projections to the hippocampus. In this study, using a molecular marker for Vb and retrograde tracers, we identified that the outer layer of Vb neurons in the medial EC (MEC) directly project to both dorsal and ventral hippocampal dentate gyrus (DG), with a significant preference for the ventral DG. In contrast to the distribution of DG-projecting Vb cells, anterior thalamus-projecting Vb cells are distributed through the outer to the inner layer of Vb. Furthermore, dual tracer injections revealed that DG-projecting Vb cells and anterior thalamus-projecting Vb cells are distinct populations. These results suggest that the roles of MEC Vb neurons are not merely limited to the formation of EC-HPC loop circuits, but rather contribute to multiple neural processes for learning and memory.

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

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

Waveform-based classification of dentate spikes.

Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer's disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing.

Environment geometry alters subiculum boundary vector cell receptive fields in adulthood and early development.

Boundaries to movement form a specific class of landmark information used for navigation: Boundary Vector Cells (BVCs) are neurons which encode an animal's location as a vector displacement from boundaries. Here we characterise the prevalence and spatial tuning of subiculum BVCs in adult and developing male rats, and investigate the relationship between BVC spatial firing and boundary geometry. BVC directional tunings align with environment walls in squares, but are uniformly distributed in circles, demonstrating that environmental geometry alters BVC receptive fields. Inserted barriers uncover both excitatory and inhibitory components to BVC receptive fields, demonstrating that inhibitory inputs contribute to BVC field formation. During post-natal development, subiculum BVCs mature slowly, contrasting with the earlier maturation of boundary-responsive cells in upstream Entorhinal Cortex. However, Subiculum and Entorhinal BVC receptive fields are altered by boundary geometry as early as tested, suggesting this is an inherent feature of the hippocampal representation of space.

Lateral entorhinal cortex subpopulations represent experiential epochs surrounding reward.

During goal-directed navigation, 'what' information, describing the experiences occurring in periods surrounding a reward, can be combined with spatial 'where' information to guide behavior and form episodic memories. This integrative process likely occurs in the hippocampus, which receives spatial information from the medial entorhinal cortex; however, the source of the 'what' information is largely unknown. Here, we show that mouse lateral entorhinal cortex (LEC) represents key experiential epochs during reward-based navigation tasks. We discover separate populations of neurons that signal goal approach and goal departure and a third population signaling reward consumption. When reward location is moved, these populations immediately shift their respective representations of each experiential epoch relative to reward, while optogenetic inhibition of LEC disrupts learning the new reward location. Therefore, the LEC contains a stable code of experiential epochs surrounding and including reward consumption, providing reward-centric information to contextualize the spatial information carried by the medial entorhinal cortex.

Grid codes underlie multiple cognitive maps in the human brain.

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

Variations of the grid and place cells in the entorhinal cortex and dentate gyrus of 6 individuals aged 56 to 87 years.

INTRODUCTION: The relationship between the entorhinal cortex (EC) and the hippocampus has been studied by different authors, who have highlighted the importance of grid cells, place cells, and the trisynaptic circuit in the processes that they regulate: the persistence of spatial, explicit, and recent memory and their possible impairment with ageing. OBJECTIVE: We aimed to determine whether older age causes changes in the size and number of grid cells contained in layer III of the EC and in the granular layer of the dentate gyrus (DG) of the hippocampus. METHODS: We conducted post-mortem studies of the brains of 6 individuals aged 56-87 years. The brain sections containing the DG and the adjacent EC were stained according to the Klüver-Barrera method, then the ImageJ software was used to measure the individual neuronal area, the total neuronal area, and the number of neurons contained in rectangular areas in layer III of the EC and layer II of the DG. Statistical analysis was subsequently performed. RESULTS: We observed an age-related reduction in the cell population of the external pyramidal layer of the EC, and in the number of neurons in the granular layer of the DG. CONCLUSION: Our results indicate that ageing causes a decrease in the size and density of grid cells of the EC and place cells of the DG.

The grid-cell normative model: Unifying 'principles'.

A normative model for the emergence of entorhinal grid cells in the brain's navigational system has been proposed (Sorscher et al., 2023. Neuron 111, 121-137). Using computational modeling of place-to-grid cell interactions, the authors characterized the fundamental nature of grid cells through information processing. However, the normative model does not consider certain discoveries that complement or contradict the conditions for such emergence. By briefly reviewing current evidence, we draw some implications on the interplay between place cell replay sequences and intrinsic grid cell oscillations related to the hippocampal-entorhinal navigation system that can extend the normative model.