Hippocampus

Cajal-Retzius neurons (CRs) are a transient cell type that populates the postnatal hippocampus. To test how the persistence of CRs shapes the maturation of hippocampal function, we used a CRs-specific transgenic mouse line combined with targeted viral delivery to selectively ablate CRs in the postnatal hippocampus. Single cell sequencing revealed that gene networks in superficial CA1 pyramidal cells were more strongly perturbed compared to deep CA1 pyramidal cells. To test if these two subpopulations were also distinctly affected in their function, we performed in vivo recordings from spatially modulated cells in CA1. Our analysis showed an impaired spatial representation specifically in superficial CA1 pyramidal cells. Additionally, we observed an increased CA3 to CA1 excitatory drive, as indicated by increased gamma oscillations, and alterations of intrinsic firing properties in superficial CA1 pyramidal neurons confirmed by in vitro electrophysiological recordings. Together, these results indicate a crucial role for CRs in the maturation of hippocampal subcircuits.

BackgroundFlexibility and robustness of neuronal function are closely linked to degeneracy, the ability of distinct structural or parametric configurations to produce similar functional outcomes. At the cellular level, this often manifests as ion-channel degeneracy, in which multiple combinations of intrinsic conductances yield comparable electrophysiological phenotypes. MethodologyWe used a population-based, data-driven modelling framework to generate large ensembles of biophysically detailed CA1 pyramidal neuron models constrained by somatic electrophysiological features extracted from patch-clamp recordings in acute slices from early-birth rats. 10 reconstructed morphologies were incorporated, and model populations were analyzed using parameter correlation analysis, principal component analysis, and generalization tests to assess robustness, degeneracy, and morphology dependence of intrinsic properties. ConclusionsAcross the model population, similar somatic firing behaviours emerged from widely different combinations of intrinsic parameters, demonstrating robust two-level ion channel degeneracy both within and across morphologies. Each morphology occupied a distinct region of parameter space, indicating morphology-specific compensatory effects, while weak pairwise parameter correlations suggested distributed compensation rather than tight parameter dependencies. Even with a fixed morphology, multiple parameter subspaces supported comparable electrophysiological phenotypes. Generalization across morphologies was structure-dependent and non-reciprocal, with successful parameter similarity occurring preferentially between structurally similar neurons. Interestingly, to accurately simulate spike-frequency adaptation, it was important to retain some kinetic properties of the ion channel models as free parameters during optimization. Together, these findings show that dendrite morphology shapes the valid parameter space, and similar electrophysiology of CA1 pyramidal neurons arises from the interplay between structural variability and ion-channel diversity. This work highlights the importance of population-based modelling for capturing biological variability and provides insights into how neuronal robustness might be maintained despite substantial heterogeneity, and offers a scalable pipeline for generating biophysically realistic CA1 neuron populations for use in network simulations. Author summaryNeurons must reliably process information even though their internal components, such as ion channels and cellular shape, can vary widely from cell to cell. How stable behaviour emerges from such variability is a fundamental question in neuroscience. In this study, we explored this problem using detailed computer models of early-birth rat hippocampal CA1 pyramidal neurons, a cell type that plays a central role in learning and memory. Instead of building a single "average" neuron model, we created large populations of models that all reproduced key experimental recordings but differed in their internal parameters. We found that neurons with different shapes and different combinations of ion channels could nevertheless generate similar electrical activity. This phenomenon, known as ion channel degeneracy, allows neurons to remain functional despite biological variability or perturbations. Our results show that neuronal shape strongly influences which parameter combinations are viable, but that multiple solutions exist even for the same morphology. The population of models we provide offers a resource for future studies of early-birth CA1 pyramidal cell function and dysfunction.

Episodic memory depends on neural representations encoded in the hippocampus. Experimental and computational evidence suggests that the hippocampus encodes pattern-separated representations that support later recall of episodic event elements. While extant data in humans predominantly focus on assaying the relationship between the similarity of spatial neural patterns at encoding and later memory performance, similarity of neural patterns in the temporal domain may also reveal encoding computations predictive of future memory. To examine how the similarity among temporal patterns of hippocampal activity during encoding relates to later episodic retrieval (associative cued recall and recognition memory), hippocampal activity was recorded from human participants (n=7) with implanted intracranial electrodes while they encoded arbitrary (A-B) paired-associates. Subsequent memory analyses first revealed that hippocampal high-frequency broadband power (HFB; 70-180Hz) was linked to a graded increase in memory strength; HFB power was greater during the encoding of pairs later correctly recalled relative to events later recognized and was lowest for events later forgotten. Second, and critically, subsequent memory analyses further revealed that more distinctive temporal patterns in the hippocampus during encoding -- indexed by the similarity of the HFB timeseries elicited by a given event to that elicited by other events -- were associated with superior subsequent memory performance. Finally, exploratory analyses revealed stimulus category effects on hippocampal HFB power during encoding and retrieval cuing. These results indicate that the temporal distinctiveness of hippocampal traces during encoding is important for subsequent retrieval of episodic event elements, consistent with theories that posit that pattern separation facilitates future remembering.

The hippocampal CA1 subregion supports learning, memory formation, and spatial navigation. Although its three-layered architecture has been described in ex-vivo investigations, the in-vivo microstructural profile of CA1 and its relation to individual variations in memory performance remain poorly characterized. In this study, we used ultra-high field structural MRI at 7 Tesla to investigate the depth-dependent myelination patterns (measured by quantitative T1) of CA1 in younger adults, their relation to the local arterial architecture, and their association with individual differences in cognitive functions, specifically memory performance. Results show that left and right CA1 present depth-dependent patterns of myelination, with the outer and inner compartments showing higher myelination than the middle compartment. No significant relationship between layer-specific myelination of CA1 and distance to the nearest artery was observed. Right CA1 was found to be more myelinated than left CA1. Pairwise correlations and regression models showed that higher left CA1 myelination is linked to higher accuracy in object localization. Together, our data demonstrates the feasibility of describing the three layered myelin architecture of CA1 in vivo, and provides information on how alterations in the architecture of CA1 may relate to alterations in cognitive performance in younger adults.

Current evidence suggests that older adults perform worse at tasks involving spatial memory and navigation, yet the underlying reasons remain unclear. Here, we tested the hypothesis that age-related declines in spatial memory stem from difficulties in recognizing spatial environments from rotated perspectives. Young and older adults underwent fMRI as they encoded virtual scenes which were later viewed either from the same or rotated perspective. Older adults were worse at identifying changes in these scenes, although the age effect was equally robust across perspective conditions. Neural specificity of scene representations was examined with the phenomenon of fMRI repetition adaptation. We predicted that young adults would show significant fMRI adaptation to the same but not rotated perspective, indicative of intact viewpoint specificity, while older adults show would adaptation effects to both. While analyses of raw fMRI BOLD produced results consistent with these predictions, follow-up analyses revealed a general attenuation of activity in older adults across both perspective conditions. Additionally, although older adults showed both lower fMRI BOLD and worse spatial memory, lower trial-wise BOLD was associated with better performance independent of age. This suggests that the variance associated with fMRI adaptation is reflective of two independent sources of variance: age and cognition. Our results suggest that age differences in spatial memory may manifest due to cognitive and neural factors that are shared across same and rotated perspectives, and thus they cannot be explained by a selective deficit in allocentric (viewpoint-independent) processing. Significance StatementIncreasing age is often associated with reduced spatial memory and navigation. Prior research suggests that age differences in spatial memory could be exacerbated by changes in perspective, possibly due to increased difficulties in the ability to construct allocentric (viewpoint-independent) representations from previously encoded egocentric perspectives. Here, we demonstrate that older adults are equally disadvantaged when recognizing layouts across same and rotated perspectives. FMRI analyses indicate that older age is associated with reduced fMRI BOLD in higher-level visual cortex across both perspective conditions, as opposed to altered specificity of perspective coding. Consequently, the present study challenges the notion that aging is associated with a selective decline in allocentric spatial memory and instead supports a more general age-related difficulty with scene processing.

The subiculum (SUB) is the main output structure of the hippocampus, influencing diverse behaviors through its widespread cortical and subcortical connections. Our previous work creating the mouse Hippocampus Gene Expression Atlas (HGEA) identified four genetically distinct cellular layers across five columnar domains in the SUB, with gene expression boundaries corresponding to distinct connectivity patterns and brain-wide networks involved in spatial navigation, social behavior, and neuroendocrine regulation (Bienkowski et al., 2018). Using the Digital Brain Mouse Projectome Atlas (MPA) tool, we conducted virtual tract-tracing to assess whether connectivity patterns of single-neuron 3D reconstructions aligned with HGEA-defined SUB cell types (Qiu et al., 2024). We classified 689 SUB projection neurons into 12 HGEA cell-type groups based on their laminar and columnar distributions, whose spatial organization recapitulated HGEA-defined 3D boundaries. Using this population sample, we performed a SUB cell-type census, characterized neuronal heterogeneity and projection prevalence, identified common and rare connectivity motifs and axonal collateralization patterns, and defined distinct projection themes for each SUB cell type. Together, this analysis integrates single-neuron and population-level data to advance understanding of SUB cell type organization and its contributions to brain-wide networks regulating diverse behaviors.

Development of the brain networks is highly vulnerable to stressful events. Early life stress (ELS) has been linked to multifaceted cognitive and emotional deficits in adulthood. Despite a growing body of evidence showing ELS-induced structural and functional changes in the prefrontal cortex (PFC) and basolateral amygdala (BLA), a circuit crucial for emotional processing, our knowledge of the resulting changes in the network dynamics is incomplete. Here, we investigate how maternal separation (MS) affects prefrontal-amygdala network in terms of neuronal avalanches, spatiotemporal clusters of activity, using simultaneous multielectrode recordings in the medial PFC (mPFC) and the BLA of urethane-anaesthetized juvenile (postnatal day (p) 14 - p15) and young adult (p50 - p 60) rats. Firstly, we show that MS leads to an intensified spread of activity within both regions as reflected in the higher mean branching ratios of the avalanches. Next, we demonstrate that most of the avalanches occur locally in one region, however, a small percentage of avalanches has clusters of activity in both regions simultaneously. We show that in MS animals prefrontal clusters followed by activity in the amygdala tend to be larger compared to controls and each event in the mPFC is followed by smaller number of events in the BLA, pointing towards impaired spread of activity from the mPFC to the BLA. Interestingly, avalanche spread from the BLA to the mPFC remains unaffected by MS. Abovementioned effects manifest only in adulthood and, intriguingly, only in males highlighting prolonged developmental and sex-dependent nature of ELS outcome. Significance statementBrain criticality implies that the brain self-organizers towards critical state, characterized by sustained activity propagation reflected in the unitary branching ratios of neuronal avalanches. Here we show how adverse events during early periods of network maturation, namely ELS, can disrupt developmental trajectories of the critical dynamics in the mPFC-BLA circuit in a sex-specific manner. This study broadens our understanding of the critical dynamics emergence in the prefrontal-limbic network and highlights ELS as a potential criticality control parameter.

Anatomically and biophysically detailed models of neurons have been widely used to study information processing in these cells. Most studies focused on understanding specific phenomena, while more general models that aim to capture various cellular processes simultaneously remain rare even though such models are required to predict neuronal behavior under more complex, natural conditions. In this study, we aimed to develop a detailed, data-driven, general-purpose biophysical model of hippocampal CA1 pyramidal neurons. We leveraged extensive morphological, biophysical and physiological data available for this cell type, and established a systematic workflow for model construction and validation that relies on our recently developed software tools. The model is based on a high-quality morphological reconstruction and includes a diverse curated set of ion channel models. After incorporating the available constraints on the distribution of ion channels, the remaining free parameters were optimized using the Neuroptimus tool to fit a variety of electrophysiological features extracted from somatic whole-cell recordings. Validation using HippoUnit confirmed the models ability to replicate key electrophysiological features, including somatic voltage responses to current input, the attenuation of synaptic potentials and backpropagating action potentials, and nonlinear synaptic integration in oblique dendrites. Our model also included active dendritic spines, modeled either explicitly or by merging their biophysical mechanisms into those of the parent dendrite. We found that many aspects of neuronal behavior were unaffected by the level of detail in modeling spines, but modeling nonlinear synaptic integration accurately required the explicit modeling of spines. Our data-driven model of CA1 pyramidal cells matching diverse experimental constraints is a general tool for the investigation of the activity and plasticity of these cells and can also be a reliable component of detailed models of the hippocampal network. Our systematic approach to building and validating general-purpose models should apply to other cell types as well. Author SummaryThe brain processes information through the activity of billions of individual neurons. To understand how these cells work, scientists build detailed computer models that reproduce their electrical behavior. These models make it possible to explore situations that are difficult or impossible to test experimentally. However, many existing neuron models were designed to explain only a few specific phenomena, which limits their usefulness in more complex settings. In this study, we developed a comprehensive computer model of a hippocampal CA1 pyramidal neuron, a cell type that plays a central role in learning and memory. We built the model using extensive experimental data and applied automated methods to ensure that it reproduces a broad range of observed neuronal behaviors. We also examined how small structures called dendritic spines--tiny protrusions where most synaptic communication occurs--affect how neurons combine incoming signals. We found that even simplified models without individual spines can capture many aspects of neuronal activity, but understanding more complex forms of signal integration requires modeling spines explicitly. Our work also supports the development of more realistic simulations of brain circuits.

An increasing number of epidemiological and experimental studies have demonstrated a bidirectional relationship between mood disorders and the circadian system, with disrupted circadian rhythms contributing to depressive states, and their restoration playing a key role in antidepressants effects. In this context, we sought to examine whether key molecular targets of antidepressants exhibit diurnal regulatory patterns. Naive adult male and female C57BL/6 mice were euthanized at 3-hour intervals beginning at Zeitgeber Time 0 (ZT0), and hippocampal (HC) and medial prefrontal cortex (mPFC) tissues were collected for RT-qPCR and western blot analyses. We observed statistically significant diurnal rhythmicity in all analyzed transcripts (cFos, Arc, Nr4a1, Dusp1, Dusp5, and Dusp6) in both HC and mPFC samples, with peak expression occurring during the dark (active) phase (ZT15-18). Phosphorylation levels of TrkBY816 (tropomyosin-related kinase) and GSK3{beta}S9 (glycogen synthase kinase 3{beta}) also showed periodic rhythmicity, peaking during the light (inactive) phase. Levels of p-ERK2T185/Y187 (extracellular-signal regulated kinase) did not display rhythmicity, but peaked during the light phase in the HC, especially in males. Collectively, these findings demonstrate that antidepressant targets are subject to diurnal regulation, highlighting the importance of integrating circadian biology and time-of-day as relevant variables in the development of translationally relevant antidepressant research. HighlightsO_LIKey molecular targets of antidepressants exhibit diurnal regulation in adult mice C_LIO_LIDiurnal patterns were conserved across targets, sexes, and brain regions (HC&PFC) C_LIO_LIcFos, Arc, Nr4a1, Dusp1,5,6 mRNAs display peak expression during the dark phase C_LIO_LITrkBY816 and GSK3{beta}S9 phosphorylation peak during the light (inactive) phase C_LIO_LIAntidepressant mechanisms may be linked with circadian and sleep-wake dynamics C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=102 SRC="FIGDIR/small/716906v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1e65e60org.highwire.dtl.DTLVardef@13e302corg.highwire.dtl.DTLVardef@1ccc25forg.highwire.dtl.DTLVardef@1ed10d3_HPS_FORMAT_FIGEXP M_FIG C_FIG

Environmental enrichment enhances hippocampus-dependent learning and memory, yet the underlying circuit mechanisms remain largely unknown. Here we combined miniscope calcium imaging during spatial exploration with synaptic circuit analysis in hippocampal slices to determine how enrichment experience alters hippocampal network dynamics. Prolonged enrichment reduced average firing rates and immediate early gene expression in CA1 pyramidal cells, while increasing peak firing and spatial selectivity. Population activity was sparser and more diverse, resulting in a higher Gini index. Circuit analysis revealed enhanced excitatory drive onto both pyramidal cells and somatostatin (SOM) interneurons, together with a strengthened SOM-mediated feedback inhibition onto pyramidal cells. Suppressing SOM interneurons occluded the enrichment-induced augmentation of sparsity and Gini index and prevented improvements in hippocampus-dependent learning. These findings demonstrate that environmental enrichment dynamically enhances hippocampal sparse coding through potentiation of SOM-mediated feedback inhibition, linking experience-dependent inhibitory plasticity to enhanced memory performance.

Cognitive flexibility, switching behaviour responses to changing task demands, is classically attributed to the prefrontal cortex. Yet thalamocortical circuits involving the mediodorsal thalamus (MD) and thalamic nucleus reuniens (Re) are dysfunctional across a range of neurological conditions with cognitive flexibility deficits. Interventions involving thalamocortical interactions may offer therapeutic benefits. Here we examined the effects of MD or Re bilateral glutamatergic neurotoxic damage in rats on cognitive flexibility using the attentional set-shifting task. Rats must attend to a sensory dimension that reliably predicts reward (intradimensional shift, ID) followed by a shift in attention to a previously irrelevant sensory dimension when contingencies change (extradimensional shift, ED). We found MD rats required more trials to criterion in the ED, while Re rats showed significant impairments on the first of three ID subtasks (ID1) only. Both MD and Re rats required more trials to criterion to complete each subtask than Sham controls. Intraperitoneal noradrenaline (atipamezole 1mg/kg), given 30 minutes prior to the task reduced trials to criterion across all rats, improving cognitive flexibility even after thalamic damage. These findings demonstrate the influence MD and Re contribute to cognitive flexibility and support noradrenergic regulation of thalamocortical circuits as potential therapeutic targets for cognitive flexibility dysfunction.

Stressors are commonly used in rats to induce models of anxiety or depression. The effectiveness of these stressors is often evaluated using specific behavioural tests. In a previous meta-analysis of chronic variable stress (CVS) procedures, we predicted that longer and more intensive stress procedures would result in larger effect sizes in behavioural tests. However, we found that the duration or intensity of CVS procedures did not correlate strongly with the magnitude of the effect sizes reported in behaviouraltests. In that study, we were concerned that the large and unexplained diversity in CVS procedure design, both in terms of duration and the types of stressors used, made it challenging to detect the factors that were influencing effect size. In an effort to address this, we explore here the use of a much simpler stress procedure - chronic restraint stress (CRS) - to study the relationship between the duration of CRS procedures and the effect sizes obtained in subsequent behavioural tests. We searched PubMed for articles using CRS procedures with rats, systematically documented the total duration of restraint, and carried out a meta-analysis of the effect sizes obtained in four behavioural tests: the forced swim test (FST), the sucrose preference test (SPT), the elevated plus maze (EPM) and the open field test (OFT). We found that chronic restraint stress increased immobility in the FST, decreased sucrose preference in the SPT, decreased time spent in the open arms of the EPM but had no effect on time spent in the centre of the OFT. However, the effect sizes in all behavioural tests, except the SPT, were not moderated by the duration of the CRS procedure, indicating that longer CRS procedures are associated with larger effect sizes in the SPT but not in the FST or EPM.

Neuronal activity alters extracellular ion concentrations and electric potentials. Ephaptic effects refer to the feedback influence that these extracellular changes can have on neuronal activity. While electric ephaptic effects occur on a fast timescale due to extracellular potential perturbations, ionic ephaptic effects are driven by slower, accumulative changes in ion concentrations. Among the previous computational studies of ephaptic effects, the vast majority have focused exclusively on electric effects, while ionic ephaptic effects have largely been neglected. In this work, we present an electrodiffusive computational framework consisting of two-compartment neurons that interact via a shared extracellular space. By accounting for both electric potentials and ion-concentration dynamics in a self-consistent manner, our framework enables us to explore the relative roles of electric and ionic ephaptic effects. Through numerical experiments, we demonstrate that ionic and electric ephaptic interactions play very different roles. While ionic ephaptic interactions increase population firing rates, electric ephaptic interactions primarily drive subtle shifts in spike timing. Furthermore, we show that these spike shifts cause the phase difference (the distance in spike times between a small collection of neurons) to converge to a stable, unique phase difference, which we coin the ephaptic intrinsic phase preference. Author summaryNeurons predominantly communicate through synapses: specialized contact points where a brief electrical signal, known as a spike or action potential, in one neuron influences another. Neurons generate these spikes by exchanging ions with the surrounding extracellular space. This way, spiking neurons alter extracellular ion concentrations and electric potentials. Since neurons are sensitive to such changes in their environment, they can also influence one another indirectly through the shared extracellular medium. This form of non-synaptic interaction is known as ephaptic coupling. Most computational models of neuronal activity neglect ephaptic interactions, and those that include them typically consider only electric effects while ignoring ionic contributions. As a result, the relative roles of electric and ionic ephaptic effects remain poorly understood. Here, we introduce a computational framework that accounts for both mechanisms in a self-consistent way. Our results show a functional distinction: ionic ephaptic effects act slowly, regulating population firing rates, whereas electric ephaptic effects act on millisecond timescales and subtly shift spike timing. These shifts cause spike-time differences between neurons to converge to a stable value, a phenomenon we call ephaptic intrinsic phase preference.

The circadian clock controls a vast array of cellular and organismal functions, from the molecular scale to behavior. While each cell is regimented by a cell-autonomous clock, few studies in the brain have dissected the circuit and behavioral contributions of cell-specific clocks. Relatedly, astrocytes are now known to play key roles in regulating synaptic function, circuit activity and behavior, but whether these functions are guided by astrocyte-autonomous clocks is unknown. Here, we report that post-natal deletion of the critical circadian clock gene Bmal1 in astrocytes, which abrogates core clock function in a cell type specific manner, induced expression of genes related to extracellular matrix (ECM) production, maintenance, and remodeling. Circadian variations have been shown in a specific ECM structure, perineuronal nets (PNNs), which are implicated in synaptic function and plasticity. In astrocyte-specific Bmal1 knockouts, hippocampal PNN abundance was decreased, and the circadian rhythm of these structures was also abolished. In line with evidence implicating PNNs, and the ECM in general, in synaptic function and plasticity, we found that astrocyte-specific Bmal1 KO mice had increased synaptic strength but blunted long term potentiation (LTP), as well as impaired learning and memory performance in a novel object recognition task. Taken together, these findings suggest that the astrocyte circadian clock regulates circadian rhythms in perineuronal net abundance as well as synaptic plasticity and behavioral learning and memory.

Sleep deprivation (SD) disrupts memory processes, particularly those dependent on the hippocampus. Six hours of SD after training in a hippocampus-dependent task typically induces amnesia in mice and impairs performance upon memory testing later. However, we previously demonstrated that object-location memories (OLMs) encoded under SD conditions can be recovered several days later, suggesting that these memories were not lost but suboptimally stored. Given that engrams of a specific memory are distributed across multiple functionally connected brain regions, we hypothesized that SD-induced amnesia arises from disrupted network alterations extending beyond the hippocampus. Consistent with this, brain-wide cFos mapping revealed a widespread reduction in cFos in memory associated regions during recall in SD mice and connectivity analysis identified the hippocampus as a central hub in this network. Since cGMP signaling modulates memory processes, we next tested whether the cGMP-specific PDE5 inhibitor vardenafil could restore access to these latent memories. One day after training, vardenafil reversed SD-induced OLM impairment when administered 30 minutes before testing, but this effect was lost when testing occurred several days later. To achieve persistent access to OLMs formed under SD conditions, we combined vardenafil treatment with optogenetic engram stimulation. This combined approach successfully maintained OLM retrievability for several days post-manipulation. Crucially, successful retrieval in these mice was associated with a significant increase in engram cell reactivation within the dorsal dentate gyrus compared to mice that failed to recall. Collectively, these findings provide novel insight into the molecular and network mechanisms underlying SD-induced amnesia and offer a strong rationale for developing targeted PDE5-mediated therapies to reverse SD-related memory deficits. HighlightsO_LISD-induced amnesia is associated with reduced cFos expression within memory-associative circuitry C_LIO_LIThe phosphodiestarase-5-inhibitor vardenafil can be used to restore memory access C_LIO_LICombining optogenetics with vardenafil treatment sustains memory retrieval over several days C_LIO_LISuccessful retrieval reflects increased reactivation of engram cells in the dentate gyrus C_LI

Hippocampal place and time cells encode spatial and temporal aspects of experience. Both have the same neural substrate, but have been modeled as having different functions and mechanistic origins, place cells as continuous attractors, and time cells as leaky integrators. Here, we show that both types emerge from two dynamical regimes of a single recurrent network (RNN) modeling hippocampal CA3 as a predictive autoencoder. The network receives simulated, partially occluded "experience vectors" containing spatial patterns (location-specific activity sampled during environmental traversal) and/or temporal patterns (correlated activity pairs separated by "void" intervals), and is trained to reconstruct missing input. During spatial navigation, the network generates stable attractor-like place fields. But trained on temporally structured inputs, the network produces sequentially broad-ened fields, recapitulating time cells. By varying spatio-temporal input patterning, we observe hidden units transition smoothly between time cell-like and place cell-like representations. These results suggest a shared origin, but task-driven difference, between place and time cells.

Spatial navigation could theoretically serve as an early neurobehavioral marker of Alzheimers disease risk, yet technological limitations have hindered its widespread adoption. We leveraged breakthroughs in technology to create a custom smartphone application to compare real-world spatial memory with lab-based measures. Specifically, we compared performance across two established lab-based tasks, judgments of relative direction (JRD) and map drawing, and our novel app-based, in situ pointing task administered in a familiar large-scale, real-world environment. Young adults completed both laboratory and mobile navigation tasks, allowing within-subject comparisons across modalities. JRD performance strongly correlated with map drawing performance. In contrast, App-based pointing showed lower error and reduced inter-individual variability relative to JRD performance, but weak correlations with lab-based measures. We also developed a novel analytical technique in which we transformed the app-based pointing into a relational, JRD-like metric, and we observed strong correlations and correlated patterns of errors across all tasks. Thus, real-world, app-based pointing captures stable directional performance (e.g., as indexed by the lower errors and lower variability relative to the JRD Task) and, when expressed in a common framework, correlates with laboratory measures of spatial memory, thus suggesting that these tasks tap into partially overlapping cognitive representations. These results provide a pivotal advancement to our understanding of both shared and unique variance across spatial memory paradigms, and support the use and further development of mobile navigation tools as scalable complements to lab-based assessments for studying spatial cognition and its decline in preclinical and clinical stages of Alzheimers disease. HighlightsO_LISpatial memory is a core cognitive function and is impaired in Alzheimers disease C_LIO_LITesting memory in large-scale, real-world environments enhances ecological validity C_LIO_LIWe compared performance of our novel real-world measure with lab measures C_LIO_LIWe observed strong correlations between the lab-based measures C_LIO_LIWe observed shared and unique variance between lab- and real-world measures C_LI

It is critical to identify which factors induce specific brain states as these large-scale patterns of coordinated neural activity drive downstream processing and behavior. The retrieval state, a brain state engaged when attempting to retrieve the past, is thought to specifically support episodic memory, remembering experiences within a spatiotemporal context, as opposed to semantic memory, remembering general knowledge. However, we hypothesize that the retrieval state reflects internal attention engaged to access stored episodic and semantic information. To test these alternatives, we recorded scalp electroencephalography while participants made episodic, semantic, or perceptual judgments, and applied an independently validated mnemonic state classifier to measure retrieval state engagement. We found that retrieval state engagement was greater for both episodic and semantic judgments compared to perceptual judgments. These findings suggest that the retrieval state reflects a domain-general internal attention process that supports not just episodic memory, but internally directed cognition.

Meningeal lymphatic vessels (mLV) play essential roles in draining cerebrospinal fluid (CSF) into peripheral blood. The mLVs are hypothesized to be supportive structures to the glymphatic system, which is thought to remove metabolic byproducts from brain parenchyma and has been most directly studied in rodent models. Previous rodent studies have indicated a correlation between mLV function and cognitive performance, but this relationship in humans remains unexplored. Age-related declines in glymphatic system efficiency in humans and cognitive performance have been observed separately. This study investigates age- and sex-related differences in CSF production via choroid plexus volumes, mLV characteristics, and glymphatic system efficiency, overall elucidating the implication of cerebral lymphatic function on cognition. We recruited 26 healthy adults from Dallas-Fort Worth and acquired magnetic resonance images. mLVs along the sagittal sinus were visualized and segmented from T2-FLAIR images. The glymphatic system was evaluated by measuring diffusivity along the perivascular space. Choroid plexus volume and brain volume were estimated from T1-MPRAGE. Neuropsychological tests were conducted to assess cognitive function. Our findings indicate that glymphatic function diminishes with age, while mLV and choroid plexus volumes increase. Males displayed greater mLV volume than females, yet no sex differences were found in glymphatic function or choroid plexus volume. Notably, mLV volume increased as glymphatic function declined, independent of age. Moreover, a glymphatic-mLV latent variable significantly predicted processing speed, underscoring the influence of cerebral lymphatics on cognition. In conclusion, this study highlights a decline in glymphatic function with age, accompanied by increased mLV volumes and altered processing speed. These lymphatic system changes may underlie or contribute to the cognitive declines observed in healthy and pathological aging. Significance StatementThe glymphatic system and meningeal lymphatic vessels play crucial roles in removing brain cell waste. The relationship between these systems and their effect on human cognition, particularly processing speed, is unknown. We demonstrate that these systems change with advancing age. Variations in cerebral lymphatic function contribute to differences in processing speed independent of age, ultimately affecting higher-order cognitive function. The findings presented have implications for cognitive function in both healthy and diseased states.

Declining spatial navigation abilities are a critical hallmark of aging, where the loss of spatial abilities precedes global cognitive impairment. While navigational decline is traditionally attributed to deficits in higher-order cognitive functions, emerging cognitive-motor frameworks suggest that age-related sensorimotor alterations play a significant, yet previously overlooked, role. Here, we investigate the coupling between locomotor integrity and navigation by combining an immersive virtual-reality path-integration paradigm with systematic manipulations of landmark availability and reliability, while recording gait kinematics alongside neural dynamics using high-density mobile-EEG from 30 young and 32 older adults. We demonstrate that older adults accumulate angular homing error more rapidly than younger adults, a deficit linked to altered gait dynamics. These age-dependent differences are reflected in increased mid-frontal theta activity, highlighting a robust coupling between gait-related sensorimotor alterations and decline in navigation. Older adults also exhibited increased reliance on visual landmarks, and particularly those with degraded gait, yet this compensatory reweighting of navigational cues remained less efficient and less precise than in younger adults. These findings highlight sensorimotor gait alterations as a central determinant of age-related navigation deficits, challenging the traditional separation of motor and cognitive domains and identifying locomotor integrity as a critical target for preserving spatial navigation abilities.