Hippocampus

We recently reported that rats performed better at a task distance of 2 m than at 0 m in a T-maze delayed alternation paradigm using a movable home cage in the longer-delay condition (Takita & Ichitani, 2026). We simultaneously recorded local field potentials from the bilateral prefrontal cortex, intermediate hippocampus, and ventral hippocampus. Across task epochs, coherence and two cross-frequency measures (phase-locking value and modulation index [MI]) revealed differences between correct and error trials in prefrontal interactions with hippocampal subregions. Among these measures, only MI was affected by task distance during the pre-task delay epoch. MI was highest in 2-m error trials and lowest in correct trials. In 0-m error trials, MI transiently increased during arm entry to levels comparable to those in 2-m error trials before declining toward the levels observed in correct trials during the later post-task delay. These MI dynamics appeared to be consistent with distance-dependent differences in behavioral performance. In addition, normalized Correct-Error Indices calculated for each electrophysiological measure revealed differential contributions of prefrontal coupling with the intermediate and ventral hippocampus across task distances. These findings suggest the existence of distinct near and far working memory states underlying distance-dependent behavioral differences, with distinct yet complementary contributions of the intermediate and ventral hippocampus to prefrontal interactions.

Spatial navigation requires animals to integrate current environmental information with previously acquired spatial memories. The locus coeruleus provides neuromodulatory input to the hippocampus, but whether this pathway facilitates spatial learning in general or preferentially supports the updating of established representations remains unclear. Here, we selectively activated LC projections to the dorsal hippocampus while mice performed object-location recognition and an appetitive radial-maze task involving initial spatial learning followed by reversal. LC-hippocampal activation enhanced object-location memory and improved reversal learning, reducing total and working-memory errors, but did not affect initial spatial reference acquisition or retention. To characterize navigation beyond classical performance measures, we developed a graph-based analysis comparing each observed trajectory with paths generated from random, regular, small-world and heuristic goal-directed network models. Radial-maze trajectories contained a structured mixture of goal-directed-like and regular or serial-like patterns that evolved across learning. In addition, agreement with the goal-directed model was associated with fewer errors and greater proximity to the rewarded arm. Together, these findings indicate that LC inputs to the hippocampus preferentially facilitate spatial memory updating rather than uniformly enhancing spatial learning, and introduce a complementary framework for quantifying the organization of radial-maze trajectories.

The GABAA positive allosteric modulator diazepam is taken systemically by millions of people daily. GABAA signaling is essential for hippocampal circuit function, but the effects of systemic diazepam on hippocampal information processing during behavior has not been studied. To answer this question, large neural ensembles were recorded from rats running a linear track under systemic diazepam administration. A cross-correlation of spiking activity revealed significantly increased inhibition from interneurons, aligned with the timescale of GABAA, suggesting a direct effect on local circuits. Local field potentials (LFP) showed an increase in theta and lo-gamma (30-50 Hz) power but a decrease in hi-gamma (80-120 Hz) power. We also found decreased amplitude and rate of sharp wave ripple (SWR) events and a reduction of firing rate and proportion of cells recruited to the SWRs. An autocorrelation of single-cell spike trains revealed a decrease and shift from shorter to longer timescales, aligning differently with theta frequencies. Phase coupling measurements showed decreased cellular coupling to theta and increased coupling to lo-gamma and hi-gamma. Finally, entropy of decoding along the track was increased, suggesting less precise spatial representations under diazepam. These changes suggest mechanisms that would likely disrupt hippocampal memory storage and consolidation processes under systemic diazepam.

The hippocampus is characterized by a stereotypical macroscopic structure, where the nuclei are densely and heterogeneously packed among different subregions of the hippocampus. Despite the fact that tissue-specific cellular organization has been implicated in neural function, it has been technically challenging to quantitatively analyze mesoscopic cellular organization in the hippocampus due to its high cellular density. To overcome this technical hurdle, we developed Computational Biophysical Histomorphometry Software (CBHS), an automated image-analysis pipeline, aimed at quantifying nuclear shape and the order of the cellular ensemble in high-density areas. When applied to the subfields of hippocampus, we found that denser regions, most notably the dentate gyrus, were the most positionally, but least orientationally ordered. Nuclear shape exhibited a dependence on the local environment in a packing-dependent manner. This association was cell-type specific, with neurons, but not astrocytes displaying nuclear shape that varied with neighbour proximity, although astrocytes demonstrated greater intrinsic shape variance. The results reveal the presence of reproducible mesoscale cell packing order in hippocampal tissue, and are consistent with a nucleus-driven mechanical coupling between neighbouring cells. The present study provides a quantitative framework with which to understand mesoscopic tissue organization, thus enabling the formulation of testable hypotheses for future investigation.

Working memory has been considered a delay-dependent retention system, but variability in delay duration across species and tasks suggests that task-intrinsic factors may also contribute. Here, we investigated the effects of delay duration (75 s vs. 150 s) and task distance (0 m vs. 2 m) on working memory using a T-maze delayed alternation task with a movable home-cage apparatus in rats. At the 150-s delay, accuracy was 9% lower at 0 m than at 2 m (75% vs. 84%), with a similar numerical tendency observed at the 75-s delay (4% lower). A two-way repeated measures ANOVA revealed significant main effects of both task distance and delay duration, with no significant interaction (p = 0.217). Post hoc pairwise comparisons indicated that accuracy in the 0-m condition was significantly lower at 150 s than at 75 s (adjusted p = 0.038). At the 150-s delay, accuracy was also significantly lower in the 0-m condition than in the 2-m condition (adjusted p = 0.019). These results suggest that working memory retention is influenced not only by temporal constraints but also by task-intrinsic factors such as task distance, with the observed effects appearing independent and consistent with a two-factor framework.

Automated segmentation has made hippocampal subfield volumes a routine measurement, and studies now report which subfield relates to an outcome rather than whether the hippocampus does. Those reports do not agree with one another, and the standard explanation is insufficient statistical power. We argue that a second limit operates independently of sample size. Using 638 participants from a population-derived adult lifespan cohort, we first show that no individual subfield contributes to a general cognitive factor beyond a single global size component: no coefficient interval excludes zero, the local block carries half a percent of outcome variance, and no model improves out-of-sample prediction over the global factor alone. Because an observed null cannot distinguish an absent effect from an effect the design cannot locate, we then planted effects of known location and size in the measured design and in a whitened copy of it that preserves sample size, dimensionality and effect size while removing only the correlation between subfields. The arms were paired down to the noise vector. Collinearity did not place recovery out of reach; it multiplied the required sample size by a factor of roughly two to three, and the penalty widened as cohorts grew. At the effect sizes this literature reports, neither design reached an adequate recovery rate at any sample size, and coarsening the parcellation rescued neither. The choice of estimator moved recovery further than collinearity did. We provide a calibration surface on which a planned design can be located before data collection.

Animals must often navigate environments where feedback about progress toward a goal is sparse or delayed, requiring internal representations of space and memory of prior experience. The hippocampal-entorhinal system is believed to support this capability through distributed spatial representations that guide goal-directed behavior. However, many computational models of these circuits focus primarily on reproducing neural dynamics rather than demonstrating how such representations support learning on navigation tasks. We present a biologically inspired spiking neuronal network (SNN) model that combines grid-cell-derived spatial representations, {Delta}Q-modulated Hebbian plasticity, and context-dependent modulation to support navigation under sparse reward conditions. Grid Cell populations generate distributed spatial codes that are transformed by an Association Cell population into more spatially selective internal representations. Learning is driven by changes in Q-values ({Delta}Q) computed from a goal-conditioned Q-table, allowing local synaptic plasticity to incorporate information about long-term navigation outcomes. For environments containing multiple navigation objectives, a Context Cell population provides task-dependent modulation that enables a shared network architecture to support distinct navigation policies. Across two complementary maze environments, the model demonstrates three core capabilities: generation of distinct spatial representations, learning of efficient navigation policies under sparse and delayed reward, and support for multiple navigation objectives within a shared environment. The results further show that contextual modulation introduces subtle task-dependent variations into a largely shared population representation, allowing identical spatial locations to support different navigation behaviors. These findings demonstrate that biologically inspired spatial representations, value-guided plasticity, and contextual modulation can jointly support flexible navigation in spiking neuronal networks, providing a bridge between mechanistic neural circuit models and functional reinforcement learning.

While cognitive and behavioral manifestations of obsessive-compulsive disorder (OCD) are well known, the neuronal dynamics underlying these symptoms remain poorly understood. Theoretical work suggests that changes in the attractor dynamics of neuronal networks towards increased stability and decreased flexibility might cause behavioral and cognitive symptoms of OCD. We used chronic treatment with the D2 and D3 dopamine receptor agonist quinpirole as a rat model of the disease. In this model, we examined changes in behavioral dynamics and, in a parallel experiment, changes in organization of neuronal activity in the hippocampus and anterior cingulate cortex (ACC). At the behavioral level, we observed increased locomotion and repetitive stereotypical trajectories in quinpirole-treated rats, with frequency of repetitions increasing over the course of the session. At the level of neuronal activity, a gradual increase in the firing rate of ACC neurons within a session paralleled the dynamics of behavioral stereotypy after quinpirole treatment. In quinpirole-treated rats, we observed increased stability in the temporal organization of hippocampal neuronal firing, but no increase in the stability of the spatial organization of discharge. The increased stability of hippocampal firing was observed at both the level of single neurons and coordinated activity of neuronal pairs, and was connected to modulation of activity by theta rhythm. Studying neuronal activity changes underlying behavioral and cognitive manifestations of brain disorders is crucial for understanding and treating brain pathologies. HIGHLIGHTSO_LIDynamics of behavior and neuronal activity was characterized in rats after chronic quinpirole treatment, which is considered a model of obsessive-compulsive disorder. C_LIO_LIThe quinpirole treatment led to repetitive stereotypical trajectories, with increasing frequency of repetitions over the course of a session. C_LIO_LIThe quinpirole treatment was associated with more stable theta modulation of single-cell hippocampal firing within experimental sessions. C_LIO_LIQuinpirole increased stability in cell-pair correlations of hippocampal units within and between sessions. C_LIO_LIQuinpirole led to more stable coordination of local field potential activity between the hippocampus and anterior cingulate cortex at theta frequencies. C_LI

The dentate gyrus (DG) decorrelates entorhinal inputs (pattern separation); area CA3 completes partial cues via recurrent autoassociation. The density of CA3 recurrent connectivity is contested, with estimates from [~]0.9% (Guzman et al., 2016) to [~]9-11% (Sammons et al., 2024). We ask how completion depends on recurrent connectivity (CRC) and whether the answer is intrinsic to CA3 dynamics or inherited from the DG front-end. Using a trisynaptic model that crosses two DG implementations (a point-LIF network with Santhakumar et al., 2005 topology; an abstract fixed-in-degree spiking network validated size-invariant to N = 107) with two CA3 autoassociators (binary k-WTA; spiking excitatory/inhibitory attractor) via burst-gated mossy-fiber detonators, we find: (i) completion in the binary CA3 improves monotonically with CRC and is robust across DG implementation; (ii) the spiking CA3 exhibits a runaway transition whose boundary is set by the product (active fraction x CRC), is not rescued by stronger feedback inhibition (8x), is insensitive to input overlap, and is size-invariant (N = 104-105); (iii) the two CA3 types have opposite failure modes (binary under-completes at low CRC; spiking runs away at high active-fraction x CRC) and a capacity/stability trade-off. Adult neurogenesis flips sign by the same logic: excitability-only young cells densify the code and collapse the spiking attractor, but if they recruit feedback inhibition they instead sparsen it and preserve recall. Consistent with classical sparse-coding attractor theory (Tsodyks and Feigelman, 1988), we propose that the contested CA3 connectivity is better read as an implementation-mode trade-off, and that the empirically sparse activity of CA3 (a {approx} 0.02-0.05) is the condition that lets a highly recurrent network perform stable autoassociation. Significance StatementHow densely CA3 pyramidal neurons interconnect is contested, with functional and anatomical estimates differing roughly tenfold. In a dentate-gyrus[->]CA3 model run across two DG and two CA3 implementations, we show this need not be a contradiction: whether higher recurrent connectivity helps or harms pattern completion depends on the CA3 computational mode and, above all, on how sparse CA3 activity is. A spiking attractor collapses once the product of active fraction and recurrent in-degree exceeds an approximately size-invariant threshold, whereas a hard-sparsity network is immune. Whether neurogenesis helps or harms depends on whether young neurons recruit inhibition: without it they destabilise an E/I CA3; with it they protect it. Sparse coding is thus the control variable for stable memory.

Hilar mossy cells in the dentate gyrus project widely throughout the hippocampus, broadly contributing to circuit function. Their loss in disease is associated with local functional and structural rearrangements, including retrograde granule cell axon sprouting, aberrant neurogenesis, and disinhibition. To examine how mossy cell loss contributes to these circuit rearrangements, we ablated or silenced hilar mossy cells using viral approaches in transgenic (Crlr-Cre) mice. Both mossy cell ablation and silencing dramatically altered dentate gyrus structure and function, as assessed using immunohistochemical, viral labeling, electrophysiology, and anatomical methods. Both manipulations accelerated the maturation of adult-born neurons, but did not alter neuroblast proliferation or cause granule cell axon sprouting. However, mossy cell ablation, but not silencing, caused collapse of the inner molecular layer accompanied by proximal translocation of middle molecular layer inputs. In both cases, granule cell activity measured by cFos labeling and seizure susceptibility were unchanged after mossy cell loss, indicating functional compensation for the altered network organization. Our results highlight how mossy cells influence dentate gyrus organization and adult neurogenesis but also demonstrate the resilience of the hippocampal circuit to structural or functional perturbations.

Sleep supports episodic memory consolidation, yet it remains unclear how naturalistic post-encoding sleep quality relates to the neural reinstatement of episodic representations across adulthood. The present study examined whether sleep discontinuity during the retention interval predicted delayed context memory and encoding-retrieval similarity (ERS) of EEG in younger and older adults. Participants completed an object-scene context memory task with immediate and delayed retrieval, while EEG was recorded during encoding and retrieval. Actigraphy was used to measure sleep across the post-encoding retention period, and principal component analysis identified sleep discontinuity and sleep time components. Behavioral results showed that greater post-encoding sleep discontinuity, but not sleep time, was associated with poorer delayed memory accuracy for mismatching object-context pairs across age. ERS analyses further showed that greater sleep discontinuity was associated with reduced ERS for correctly rejected mismatching pairs across frontal and posterior spatiotemporal clusters. Age moderated sleep-ERS associations: greater sleep discontinuity was generally related to lower ERS in younger adults, whereas some spatiotemporal clusters showed positive associations in older adults, potentially reflecting compensatory or effortful retrieval-related processing in poorer sleepers. Together, these findings suggest that sleep continuity during the post-encoding retention interval is important for preserving high-fidelity episodic representations needed for later context discrimination. More broadly, the results demonstrate that naturalistic sleep fragmentation is linked to both behavioral memory outcomes and neural reinstatement across adults.

Older adults show disproportionate impairments in associative memory relative to memory for individual items. Unitization, the process by which discrete elements are encoded as a single integrated representation, has been proposed to mitigate this deficit by reducing reliance on hippocampal binding and shifting processing toward perirhinal cortex-mediated item-based encoding. However, most prior work has not included a single item baseline, leaving unclear whether unitized associations are truly processed like items. Here, we investigated whether spatial proximity supports associative memory in older adults and how this benefit is reflected in medial temporal lobe (MTL) encoding activity. Participants encoded unrelated object pairs presented either proximally (spatially integrated) or distally (spatially separated), alongside a single item condition. Behaviorally, older adults showed better memory for proximal than distal pairs, though performance remained below that of single items. Neurally, MTL activity scaled with associative demand, with hippocampal activity increasing and perirhinal activity decreasing as demand increased. Results further revealed an anterior-posterior MTL dissociation, with proximal pairs sharing neural properties with both single items and distal pairs without uniquely recruiting either. Furthermore, hippocampal patterns reliably distinguished item from associative encoding, and the parahippocampal cortex discriminated all three conditions, indicating that the item-associative structure of the MTL was preserved in aging. Together, these findings suggest that proximal pairs occupy an intermediate position between item and associative representations within an intact MTL architecture, and that spatial proximity benefits associative memory in older adults by partially, but not fully, shifting associative demands toward item-based processing. HighlightsO_LISpatial proximity improved associative memory in older adults. C_LIO_LIHippocampal and PRC activity scaled with associative binding demands. C_LIO_LISpatially unitized associations fell between single items and distal associations in MTL encoding activity. C_LIO_LIMTL item-association functional structure was preserved in older adults. C_LI

Pattern completion refers to the reinstatement of a stored memory representation from partial or degraded cues. In this sense, it enables a form of cue-based generalization: the same memory representation can be retrieved across different, incomplete versions of the original input. Sleep supports hippocampus-dependent memory consolidation and may facilitate such flexible retrieval, but it remains unclear whether post-encoding sleep improves visual pattern completion from degraded cues. Previous sleep studies have mainly examined mnemonic discrimination or relational memory, leaving open whether sleep directly enhances the recovery of learned visual scenes from sparse perceptual information. We tested this question using the Memory Image Completion (MIC) task in a polysomnographic within-subject sleep-wake design. Twenty-eight healthy young adults (14 female; mean age 23.4 {+/-} 3.1 years) encoded scene-label associations and were tested immediately and after either a 90-min daytime nap or a matched wake interval. During retrieval, learned and new scenes were presented at five levels of visual completeness. A separate pre-encoding baseline nap assessed individual sleep physiology without prior learning. Sleep did not generally improve performance across all retrieval conditions. Instead, it selectively enhanced consolidation of learned scenes when visual cues were maximally degraded (p = .001) indicating increased pattern completion. No corresponding sleep effect was found for new scenes (all p > .31), suggesting that the benefit was specific to the recovery of previously encoded scene representations. Slow-wave amplitude during the post-encoding nap predicted consolidation of learned scenes under the most degraded condition (p = .011; FDR-corrected p = .042), whereas baseline slow-wave amplitude did not (p > .11). These findings suggest that post-encoding sleep facilitates cue-based recovery of learned visual representations from strongly degraded input, and that this benefit is linked to slow-wave amplitude during post-encoding sleep. Together, these results link sleep-dependent consolidation to visual pattern-completion-like retrieval and extend previous work on sleep-related memory transformation from verbal and relational paradigms to the recovery of learned scene representations from degraded cues.

Single-cell or single-nucleus RNA sequencing are common methods to investigate gene expression. However, to clarify the genes in specific types of cells in a small circuit there are limitations to current approaches. Here we present modifications to standard protocols to overcome the limitations and do so in a manner that will be accessible to novices. Then the modified methods are applied to a question about a small area of the brain, the dentate gyrus (DG) of the mouse, where information about cell types was of interest. The question arose from data acquired in a mouse model of Alzheimers disease where early hyperactivity of the principal cells, granule cells (GCs), was identified that was difficult to explain by existing data. Therefore, we investigated altered gene expression in GCs, and other DG cell types that influence GCs, to identify putative mechanisms. Validations of the modified methods are addressed, comparisons are made to other methods, and comparisons of mouse and human data are presented.

Tauopathy is characterized by progressive synaptic failure and neuroinflammation, yet the laminar-specific nature of these disruptions remains poorly understood. We investigated hippocampal functional integrity and glial reactivity in 8-10-month-old PS19 (P301S) mice. Electrophysiological recordings in the CA1 stratum radiatum revealed an unexpected increase in basal synaptic transmission despite profound deficits in both maintenance and early induction of the LTP phase. Conversely, the dentate gyrus exhibited reduced basal transmission and impaired LTP maintenance, alongside significant paired-pulse plasticity changes not observed in CA1. Furthermore, we demonstrate that transregional metaplasticity, as driven by prior activity in the stratum oriens (SO) in a way that inhibits subsequent LTP in wild-type mice, is occluded in PS19 mice. These data suggest that the tauopathic hippocampus exists in a "metaplastic" state, which inhibits future LTP. Immunofluorescence studies revealed that while astrogliosis and microglial activation were pan-hippocampal, specific neuroinflammatory markers exhibited striking laminar specificity. Mean fluorescence intensity for the neuroinflammatory astrocyte marker C3 was significantly upregulated only in the SO, and the lysosomal marker CD68 showed heightened occupancy specifically in the SO and stratum lacunosum-moleculare. Our findings indicate that tau pathology does not affect the hippocampus uniformly. Instead, it induces region-specific shifts in synaptic efficacy and a breakdown of metaplastic control that coincides with anatomically localized neuroinflammatory signaling.

Accurate alignment of hippocampal anatomy across individuals remains challenging due to complex and highly variable folding patterns that are not well captured by conventional volumetric approaches. HippUnfold introduced a surface-based representation of the hippocampus, but key components--including coordinate estimation and inter-subject correspondence--were defined in the volumetric domain, making them susceptible to topological errors and interpolation artifacts. Here, we introduce a surface-intrinsic formulation of hippocampal unfolding in which geometry, intrinsic coordinates, and correspondence are defined directly on subject-specific surface manifolds. Intrinsic anterior-posterior and proximal-distal coordinates are computed by solving Laplace equations on the surface, and correspondence is established through surface-based resampling in unfolded space, replacing inverse volumetric warping. Relative to the original HippUnfold approach, this formulation improves test-retest consistency, subject identifiability, and mesh quality, while better preserving subject-specific gyral and sulcal morphology. Surface representations show reduced distortion between folded and unfolded spaces and eliminate misplaced or outlier vertices associated with volumetric warping. These improvements translate to enhanced sensitivity in a clinical application, improving lateralization of temporal lobe epilepsy. These results demonstrate that a surface-intrinsic formulation provides a principled and robust foundation for hippocampal unfolding, enabling topology-preserving alignment and more accurate characterization of inter-individual variability in health and disease.

Dendritic spines are the principal postsynaptic sites of excitatory transmission. For over a century, their shape has been sorted into discrete categories such as filopodia, thin, long thin, stubby, mushroom, and branched, largely by Golgi-Cox impregnation and, more recently, confocal microscopy. However, both approaches share a fundamental limitation. The histological sectioning and single-viewpoint imaging that these methods rely on cannot control the orientation of a spine relative to the observer. Because a spine is a three-dimensional object, the projection seen depends on how its parent dendrite lies within the section. Here, using the publicly available H01 petavoxel reconstruction of human temporal cortex imaged by serial-section electron microscopy (EM), we show that spine-shape classification depends strongly on viewing angle. A total of 445 spines on layer 4 basal dendrites of five pyramidal neurons were classified from an initial viewpoint (Angle 1), then reclassified after rotation in Neuroglancer (Angle 2). Only 20.9% kept their category, so chance-corrected agreement was negligible (Cohens kappa = 0.027). These observations provide direct evidence that the rigid Golgi-Cox and confocal taxonomies conflate true spine morphology with the arbitrary angle of view. Our results, therefore, support recasting spine shape as a three-dimensional continuum, measurable in petavoxel reconstructions such as H01 through free rotation in Neuroglancer. Significance statementThe classification of dendritic spines into discrete shape classes underpins a vast literature on synaptic plasticity, development, and disease. Yet it rests on two-dimensional images whose viewing angle is not controlled. By rotating the same human spines in a nanoscale EM reconstruction, this study shows that four out of five spines change category with viewpoint alone. The finding exposes a systematic bias in Golgi-Cox and confocal classifications. It argues that spine morphology should be treated as a measurable three-dimensional continuum rather than a set of fixed labels.

RationaleAdaptive behavior requires revising memories when outcomes deviate from expectations. The orbitofrontal cortex (OFC) is implicated in representing outcome expectancies, but its role in memory-updating, beyond value-based learning, remains unclear. ObjectivesWe tested whether the ventrolateral OFC (VLO) contributes to hippocampal-dependent memory-updating in the Objects in Updated Locations (OUL) task, where novelty-driven exploration provides a behavioral readout consistent with successful updating of spatial information MethodsUsing inhibitory DREADDs, in male and female (Swiss Webster and C57BL/6) mice, we suppressed VLO activity during the Updating session, when new object-location information was introduced. ResultsControl mice preferentially explored the updated object-location configuration during Updating and discriminated between updated and novel object-location configurations at Test, whereas VLO-inhibited mice did not. VLO inhibition when no updating demand was present did not alter exploration of novel object-location configurations or memory for the original spatial configuration at Test. ConclusionsThese results indicate that VLO activity is selectively required when novelty must be interpreted relative to prior experience, implicating this region in evaluating change rather than detecting it. To assess hippocampal ensemble dynamics, we tagged neuronal ensembles, in the dorsal dentate gyrus (dDG) recruited during Updating, followed by quantification of overlap between Updating-tagged cells and ensembles reactivated at Test. We found that VLO inhibition reduced reactivation of Updating-tagged dDG ensembles, paralleling the behavioral impairments observed in the OUL task. These findings support a role for the VLO in hippocampal-dependent memory-updating and extend OFC models beyond reward contexts to include predictive updating of spatial memory representations. Significance StatementUsing a spatial paradigm that distinguishes detection of changed information from incorporation of that information into an updated hippocampal representation, we found that ventrolateral orbitofrontal cortex (VLO) activity is required for memory-updating when new information is present. We found behavioral deficits accompanied by impairments in hippocampal ensemble representations, indicating VLO activity is necessary for memory-updating at the hippocampal engram level. Through this mechanism, the OFC supports the flexible updating of expected outcomes when environmental conditions shift, allowing for the re-evaluation of previously learned associations. These findings extend models of orbitofrontal cortex function beyond reward-guided behavior and identify a cortical contribution to predictive spatial memory processes. Disruption of this computation may contribute to the cognitive rigidity observed in neuropsychiatric disorders.

The hippocampal CA3 subfield is central to associative learning and memory consolidation. The principal cells of the CA3, pyramidal neurons, execute these functions by generating hypersynchronous bursts that feed forward to the CA1. Extensive recurrent collateral connections within the CA3 neuron population are crucial for the generation of this burst activity. Double C2 domain-containing protein (Doc2) and synaptotagmin 7 (Syt7) are high-affinity calcium sensors implicated in asynchronous synaptic vesicle (SV) release and in the exocytosis of dense-core vesicles (DCVs). Additionally, Doc2 is a sensor for miniature neurotransmission, whereas Syt7 is involved in synaptic facilitation and SV replenishment. Both Doc2 and Syt7 are expressed in the hippocampus, but their potential roles in spontaneous excitatory network activity remain unanswered. Using whole-cell recordings in disinhibited acute hippocampal slices obtained from juvenile Doc2- and Syt7- knockout (KO) mice (P15-21), we report increased CA3 burst generation without changes in spontaneous excitatory postsynaptic current (sEPSC) frequency or amplitude. Moreover, the intrinsic properties of CA3 pyramidal neurons, such as the resting membrane potential, firing rate and input resistance, are unchanged. We propose that this novel burst phenotype in Doc2- and Syt7- KO mice is unrelated to changes in SV release but might be mediated by changes in neuropeptide release from DCVs. Regardless of the underlying mechanisms, this work reveals that both proteins act to regulate network activity. The hippocampal CA3 subfield is central to associative learning and memory consolidation. The principal cells of the CA3, pyramidal neurons, execute these functions by generating hypersynchronous bursts that feed forward to the CA1. Extensive recurrent collateral connections within the CA3 neuron population are crucial for the generation of this burst activity. Double C2 domain-containing protein (Doc2) and synaptotagmin 7 (Syt7) are high-affinity calcium sensors implicated in asynchronous synaptic vesicle (SV) release and in the exocytosis of dense-core vesicles (DCVs). Additionally, Doc2 is a sensor for miniature neurotransmission, whereas Syt7 is involved in synaptic facilitation and SV replenishment. Both Doc2 and Syt7 are expressed in the hippocampus, but their potential roles in spontaneous excitatory network activity remain unanswered. Using whole-cell recordings in disinhibited acute hippocampal slices obtained from juvenile Doc2- and Syt7- knockout (KO) mice (P15-21), we report increased CA3 burst generation without changes in spontaneous excitatory postsynaptic current (sEPSC) frequency or amplitude. Moreover, the intrinsic properties of CA3 pyramidal neurons, such as the resting membrane potential, firing rate and input resistance, are unchanged. We propose that this novel burst phenotype in Doc2- and Syt7- KO mice is unrelated to changes in SV release but might be mediated by changes in neuropeptide release from DCVs. Regardless of the underlying mechanisms, this work reveals that both proteins act to regulate network activity.

Sleep is thought to promote memory consolidation through the offline reactivation and reorganization of newly acquired information. However, most studies assess memory shortly after sleep, leaving unresolved whether an initial post-learning sleep episode produces enduring modifications that influence how memories respond to later reactivation. Importantly, the absence of behavioral differences after prolonged retention intervals does not necessarily imply that sleep failed to modify the original memory. Instead, sleep-dependent changes may persist in latent forms that are not readily captured by conventional memory assessments. Here, we investigated whether post-learning sleep produces lasting changes in declarative memories that influence their subsequent response to reactivation. In Study 1, participants learned a declarative memory task and were assigned to either a short nap, a wake condition, or an exploratory long-nap condition that included both NREM and REM sleep. Memory was assessed one week later. Despite substantial forgetting across the retention interval, no significant differences in memory performance were observed between groups. In Study 2, participants learned the same task and subsequently underwent either a short nap or wakefulness. Memory was reactivated six days after learning using an incomplete reminder previously shown to induce memory updating in human declarative memory, and memory was tested one day later. Under these conditions, participants who slept after learning showed better memory performance than wake controls. Moreover, sleep physiological measures predicted the magnitude of the post-reactivation memory benefit. These findings suggest that post-learning sleep induces enduring modifications in declarative memories that are not readily detectable through delayed memory testing alone. Instead, these sleep-dependent changes become evident when memories are challenged through subsequent reactivation. Our results indicate that sleep-dependent consolidation influences the future expression of memory, shaping how memories respond to later reactivation experiences and providing new insight into the relationship between consolidation and reconsolidation.