Hippocampus最新文献

The subiculum is highly interconnected with the hippocampus, sub-regions of the thalamus, and the entorhinal and retrosplenial cortices. Together, these regions form a distributed network that plays critical roles in spatial cognition and learning and memory. Despite recent discoveries detailing subiculum's circuitry and neural dynamics, a unique role for subiculum in this system has yet to be determined. Traditionally, the subiculum has been considered the "fourth leg" and output region of the trisynaptic pathway. However, recent evidence highlights the subiculum as a site of integration, receiving and redistributing outputs from the hippocampus, anterior thalamus, retrosplenial cortex, and entorhinal cortex. We review how these afferents may explain the diverse forms of spatial and directional tuning observed in the subiculum, including location coding, boundary-related signals, axis of travel, and head orientation. We also discuss more recently identified "non-canonical" connections that suggest additional roles for the subiculum in refining hippocampal processing. Together, these findings call for a reconceptualization of the subiculum's role in spatial cognition, memory, and integration across thalamic, cortical, and hippocampal networks.

In the classical view of hippocampal function, the subiculum is assigned the role of the output layer. In spatial paradigms, some subiculum neurons manifest as so-called boundary vector cells (BVCs), firing in response to boundaries at specific allocentric directions and distances. More recently, it has been shown that some subiculum BVCs can be classified as vector trace cells (VTCs), which exhibit traces of activity after a boundary/object has been removed. Here, we propose a model of processing within subiculum that accounts for VTCs, taking into account proximodistal differences in subiculum (pSub vs. dSub) and CA1. dSub neurons receive feedforward input, either in the form of perceptual information (from BVCs in pSub) or mnemonic information (from place cells in CA1). Mismatch between these two inputs updates associative memory encoded in the synapses between CA1 and dSub. With a range of learning rates, the model captures the majority of experimental findings, including the distribution of VTCs along the proximodistal axis, the percentage of VTCs across different cue types, and the hours-long persistence of the vector trace. Incorporating experimentally reported effects of inserted objects/rewards on place cells (place field shift), we also explain why VTCs have longer tuning distances after cue removal. This adds predictive character to subiculum traces and suggests the online use of mnemonic content during navigation. Our model suggests that mismatch detection for updating spatial memory content provides a mechanistic explanation for findings in the CA1-subiculum pathway. This work constitutes the first dedicated circuit-level model of computation within the subiculum, consistent with known effects in CA1, and provides a potential framework to extend the canonical model of hippocampal function with a subiculum component.

Grid cells in medial entorhinal cortex (MEC) support spatial navigation by responding to multiple variables, including position, speed, and head direction. While tuning curves for each of these variables have been examined individually at the level of single cells, less is known about the conjunctive coding of grid cells for these properties. To investigate this, we analyzed neural recordings of freely foraging rats and constructed four-dimensional (4D) tuning curves across 2D position and 2D velocity. In order to combat the sparse sampling of such a large behavioral space, we applied Gaussian Process (GP) methods to estimate firing rates at un-sampled points. Comparing GP model-derived tuning curves to those predicted by a fully separable model revealed that some cells exhibited significant non-separability of position and velocity tuning, and suggested a data coverage threshold necessary to observe this non-separability. In summary, our use of GPs allowed us to distinguish interactions in position-velocity tuning across a 4D behavioral space that have not been apparent in 2D analyses.

Grid cells have been identified in the entorhinal cortex of rodents and humans, as well as other mammals. In rodents, these "distance computing" neurons exhibit altered firing fields in response to environmental manipulations, including changes to geometry or specific contextual cues (e.g., color). The current study investigated whether these neurophysiological observations in rodents could predict human behavior in a distance judgment task under various environmental manipulations. Participants (n = 51) completed 22 trials involving distance traversal, memorisation, and distance replication across five experimental conditions: control (no manipulation), contextual manipulation (novel environment), and geometric manipulations (local expansion and contraction; global expansion and contraction). Results demonstrated that environmental expansions led to significant overestimations in distance judgments, consistent with rodent grid cell data. Global geometric manipulations yielded significant overestimations compared to the control condition. For the local manipulations, judgments were least accurate when made in the vicinity of the local manipulation. These behavioral patterns are consistent with localized deformations in spatial representations, as would be predicted from rodent grid cell studies. As hypothesized, changes to the environmental context (the novel environment condition) also resulted in significant distance overestimations. In conclusion, environmental manipulations influenced the accuracy of human distance judgments in a manner paralleling the firing field changes observed in rodent grid cells under similar environmental alterations. These findings demonstrate behavioral parallels between human distance estimation and rodent grid cell responses to environmental manipulations, suggesting possible commonalities in spatial processing across species.

Astrocytes from distinct hippocampal layers exhibit region-specific morphological traits, which may be influenced by their local microenvironment. During viral encephalitis, these cells undergo dynamic changes that can reflect layer-specific vulnerability. In this study, we characterized whether astrocytes from different CA3 hippocampal layers display distinct morphological responses to Piry virus-induced encephalitis. Adult female Swiss mice were intranasally inoculated with the Piry virus and sacrificed at 20- or 40-days post-infection (dpi). GFAP+ astrocytes from the Stratum lacunosum-moleculare (SLM) and Stratum oriens (SO) were three-dimensionally reconstructed. Morphometric data were evaluated using hierarchical clustering, linear discriminant analysis (LDA), and generalized linear models. Immunohistochemistry confirmed widespread viral neuroinvasion across olfactory and limbic regions. Hierarchical clustering identified 3–4 morphotypes per layer and time point with robust internal consistency, and LDA validated cluster assignments with high accuracy (> 91%). At 20 dpi, SLM astrocytes displayed significantly greater morphological complexity than SO astrocytes, whereas at 40 dpi responses were more heterogeneous, indicating temporal diversification of astrocytic reactivity. These findings provide an observational description of layer- and time-dependent astrocyte morphological plasticity during viral encephalitis. They underscore the value of morphometric and multivariate analyses for dissecting glial heterogeneity, while highlighting the need for future studies to determine the functional significance of these morphotypes.

This review offers a personal and historical perspective on spatial representations of the local environment in hippocampal regions CA1 and subiculum, as derived from extracellular electrophysiological recording of neurons in these regions in freely behaving rodents. I focus upon geometric responses and discrimination learning in CA1 place cells, and upon boundary vector cells, boundary-off cells, and vector trace cells in the subiculum. Vector trace cells are a type of boundary vector cell with an additional memory capability.

The subiculum is a main output structure of the hippocampus, transmitting information from the CA1 to the entorhinal cortex in a spatially structured manner. Prior studies revealed a high electrophysiological and molecular heterogeneity of subicular pyramidal neurons (PYNs) with evidence for further spatial subdivisions of the subiculum. In this study we focused on the cellular organization of the proximal to mid-distal part of the subiculum, designated as subregion 2 (Sub2) and performed a comprehensive electrophysiological and morphological characterization of PYNs by whole-cell patch-clamp recordings combined with intracellular labeling in acute rat hippocampal brain slices. Principal component analysis based on discharge pattern-related parameters and subsequent unsupervised, hierarchical clustering classified the PYNs into three subtypes: regular firing (RF), weak-bursting (WB), and strong-bursting (SB) neurons. Electrophysiological analysis revealed further differences between RF neurons and the two subtypes of bursting neurons in their active and passive properties. The three subtypes also showed differences in their morphometric features, including the apical and basal dendritic spread and branching pattern. Additionally, we identified a divergent morphological subset among RF neurons, bearing two apical dendrites. Mapping the three PYN subtypes onto the subiculum revealed specific spatial distributions along the superficial-deep and proximo-distal axes. Thus, this work maps the heterogeneity of subicular PYN onto differentially distributed subclasses in the Sub2 region with distinct physiological and morphological features. These findings together with prior observations of divergent anatomical projections from subicular subregions are pivotal for the understanding of how subicular morpho-electric neuron types relate to each other and contribute to processing and distribution of information to cortical regions from this hippocampal output region.

Object recognition memory (ORM) plays a key role in identifying familiar items and encoding episodic information. ORM consolidation depends on β-adrenergic receptor (βAR) signaling and is associated with increased BDNF expression in the dorsal hippocampus. Although hippocampal activation of cannabinoid type-1 receptors (CB1Rs) is known to impair ORM consolidation, the mechanisms underlying this effect remain unclear. In this study, we used the novel object recognition task to examine the interaction between CB1Rs and βARs during ORM consolidation in adult male Wistar rats. Intra-dorsal CA1 infusion of the CB1R agonist ACEA, the βAR antagonist propranolol, or the PKA inhibitor myristoylated PKI_14–22, administered 5-min post-training, impaired ORM consolidation. Notably, co-administration of the PKA activator 8Br-cAMP or the βAR agonist isoproterenol reversed ACEA-induced amnesia. In contrast, the CB1R inverse agonist AM251 failed to reverse propranolol-induced amnesia, which was instead rescued by recombinant BDNF infusion into the hippocampus 120-min post-training. These findings suggest that hippocampal CB1Rs regulate ORM consolidation by acting upstream of βARs via a signaling cascade involving PKA activation and BDNF expression.