Direct Medial Entorhinal Cortex Input to Hippocampal CA1 Is Crucial for Extended Quiet Awake Replay

Brain State-Dependent Neocortico-Hippocampal Network Dynamics Are Modulated by Postnatal Stimuli

Neurons in the cerebral cortex and hippocampus discharge synchronously in a brain state-dependent manner to transfer information. Published studies have highlighted the temporal coordination of neuronal activities between the hippocampus and a neocortical area; however, how the spatial extent of neocortical activity relates to hippocampal activity remains partially unknown. We imaged mesoscopic neocortical activity while recording hippocampal local field potentials in anesthetized and unanesthetized GCaMP-expressing transgenic mice. We found that neocortical activity elevates around hippocampal sharp wave ripples (SWRs). SWR-associated neocortical activities occurred predominantly in vision-related regions including the visual, retrosplenial, and frontal cortex. While pre-SWR neocortical activities were frequently observed in awake and natural sleeping states, post-SWR neocortical activity decreased significantly in the latter. Urethane-anesthetized mice also exhibited SWR-correlated calcium elevation, but in longer timescale than observed in natural sleeping mice. During hippocampal theta oscillation states, phase-locked oscillations of calcium activity were observed throughout the entire neocortical areas. In addition, possible environmental effects on neocortico-hippocampal dynamics were assessed in this study by comparing mice reared in ISO (isolated condition) and ENR (enriched environment). In both SWR and theta oscillations, mice reared in ISO exhibited clearer brain state-dependent dynamics than those reared in ENR. Our data demonstrate that the neocortex and hippocampus exhibit heterogeneous activity patterns that characterize brain states, and postnatal experience plays a significant role in modulating these patterns.

Dynamics of hippocampal reactivation for temporal association memory in mice

Reactivation refers to the re-emergence of activity in neuronal ensembles that were active during information encoding. Hippocampal CA1 neuronal ensembles generate firing activities that encode the temporal association among time-separated events. However, whether and how temporal association memory-related CA1 neuronal ensembles reactivate during sleep and their role in temporal association memory consolidation remain unclear. We utilized multiple unit recordings to monitor CA1 neuronal activity in mice learning a trace eyeblink conditioning (tEBC) task, in which presentation of the conditioned stimulus (CS, a light flash) was paired with presentation of the unconditioned stimulus (US, corneal puff) by a time-separated interval. We found that the CS-US paired training mice exhibited few conditioned eyeblink responses (CRs) at the initial-learning stage (ILS) and an asymptotic level of CRs at the well-learning stage (WLS). More than one third of CA1 pyramidal cells (PYR) in the CS-US paired training mice manifested a CS-evoked firing activity that was sustained from the CS to time-separated interval. The CS-evoked PYR firing activity was required for the tEBC acquisition and was greater when the CRs occurred. Intriguingly, the CS-evoked firing PYR ensembles reactivated, which coincided with increased hippocampal ripples during post-training sleep. The reactivation of CS-evoked firing PYR ensembles diminished across learning stages, with greater strength in the ILS. Disrupting the ripple-associated PYR activity impaired both the reactivation of CS-evoked firing PYR ensembles and tEBC consolidation. Our findings highlight the features of hippocampal CA1 neuronal ensemble reactivation during sleep, which support the consolidation of temporal association memory.

Hippocampal place cell sequences are impaired in a rat model of Fragile X Syndrome

Fragile X Syndrome (FXS) is a neurodevelopmental disorder that can cause impairments in spatial cognition and memory. The hippocampus is thought to support spatial cognition through the activity of place cells, neurons with spatial receptive fields. Coordinated firing of place cell populations is organized by different oscillatory patterns in the hippocampus during specific behavioral states. Theta rhythms organize place cell populations during awake exploration. Sharp wave-ripples organize place cell population reactivation during waking rest. Here, we examined the coordination of CA1 place cell populations during active behavior and subsequent rest in a rat model of FXS (Fmr1 knockout rats). While the organization of individual place cells by the theta rhythm was normal, the coordinated activation of sequences of place cells during individual theta cycles was impaired in Fmr1 knockout rats. Further, the subsequent replay of place cell sequences was impaired during waking rest following active exploration. Together, these results expand our understanding of how genetic modifications that model those observed in FXS affect hippocampal physiology and suggest a potential mechanism underlying impaired spatial cognition in FXS.

The time course and organization of hippocampal replay

The mechanisms by which the brain replays neural activity sequences remain unknown. Recording from large ensembles of hippocampal place cells in freely behaving rats, we observed that replay content is strictly organized over multiple timescales and governed by self-avoidance. After movement cessation, replays avoided the animal's previous path for 3 seconds. Chains of replays avoided self-repetition over a shorter timescale. We used a continuous attractor model of neural activity to demonstrate that neuronal fatigue both generates replay sequences and produces self-avoidance over the observed timescales. In addition, replay of past experience became predominant later into the stopping period, in a manner requiring cortical input. These results indicate a mechanism for replay generation that unexpectedly constrains which sequences can be produced across time.

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

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

Sleep microstructure organizes memory replay

Recently acquired memories are reactivated in the hippocampus during sleep, an initial step for their consolidation1-3. This process is concomitant with the hippocampal reactivation of previous memories4-6, posing the problem of how to prevent interference between older and recent, initially labile, memory traces. Theoretical work has suggested that consolidating multiple memories while minimizing interference can be achieved by randomly interleaving their reactivation7-10. An alternative is that a temporal microstructure of sleep can promote the reactivation of different types of memories during specific substates. Here, to test these two hypotheses, we developed a method to simultaneously record large hippocampal ensembles and monitor sleep dynamics through pupillometry in naturally sleeping mice. Oscillatory pupil fluctuations revealed a previously unknown microstructure of non-REM sleep-associated memory processes. We found that memory replay of recent experiences dominated in sharp-wave ripples during contracted pupil substates of non-REM sleep, whereas replay of previous memories preferentially occurred during dilated pupil substates. Selective closed-loop disruption of sharp-wave ripples during contracted pupil non-REM sleep impaired the recall of recent memories, whereas the same manipulation during dilated pupil substates had no behavioural effect. Stronger extrinsic excitatory inputs characterized the contracted pupil substate, whereas higher recruitment of local inhibition was prominent during dilated pupil substates. Thus, the microstructure of non-REM sleep organizes memory replay, with previous versus new memories being temporally segregated in different substates and supported by local and input-driven mechanisms, respectively. Our results suggest that the brain can multiplex distinct cognitive processes during sleep to facilitate continuous learning without interference.

Coordinated Interactions between the Hippocampus and Retrosplenial Cortex in Spatial Memory

While a hippocampal-cortical dialogue is generally thought to mediate memory consolidation, which is crucial for engram function, how it works remains largely unknown. Here, we examined the interplay of neural signals from the retrosplenial cortex (RSC), a neocortical region, and from the hippocampus in memory consolidation by simultaneously recording sharp-wave ripples (SWRs) of dorsal hippocampal CA1 and neural signals of RSC in free-moving mice during the delayed spatial alternation task (DSAT) and subsequent sleep. Hippocampal-RSC coordination during SWRs was identified in nonrapid eye movement (NREM) sleep, reflecting neural reactivation of decision-making in the task, as shown by a peak reactivation strength within SWRs. Using modified generalized linear models (GLMs), we traced information flow through the RSC-CA1-RSC circuit around SWRs during sleep following DSAT. Our findings show that after spatial training, RSC excitatory neurons typically increase CA1 activity prior to hippocampal SWRs, potentially initiating hippocampal memory replay, while inhibitory neurons are activated by hippocampal outputs in post-SWRs. We further identified certain excitatory neurons in the RSC that encoded spatial information related to the DSAT. These neurons, classified as splitters and location-related cells, showed varied responses to hippocampal SWRs. Overall, our study highlights the complex dynamics between the RSC and hippocampal CA1 region during SWRs in NREM sleep, underscoring their critical interplay in spatial memory consolidation.

Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments

During both sleep and awake immobility, hippocampal place cells reactivate time-compressed versions of sequences representing recently experienced trajectories in a phenomenon known as replay. Intriguingly, spontaneous sequences can also correspond to forthcoming trajectories in novel environments experienced later, in a phenomenon known as preplay. Here, we present a model showing that sequences of spikes correlated with the place fields underlying spatial trajectories in both previously experienced and future novel environments can arise spontaneously in neural circuits with random, clustered connectivity rather than pre-configured spatial maps. Moreover, the realistic place fields themselves arise in the circuit from minimal, landmark-based inputs. We find that preplay quality depends on the network's balance of cluster isolation and overlap, with optimal preplay occurring in small-world regimes of high clustering yet short path lengths. We validate the results of our model by applying the same place field and preplay analyses to previously published rat hippocampal place cell data. Our results show that clustered recurrent connectivity can generate spontaneous preplay and immediate replay of novel environments. These findings support a framework whereby novel sensory experiences become associated with preexisting "pluripotent" internal neural activity patterns.

Propagation of sharp wave-ripple activity in the mouse hippocampal CA3 subfield in vitro

Sharp wave-ripple complexes (SPW-Rs) are spontaneous oscillatory events that characterize hippocampal activity during resting periods and slow-wave sleep. SPW-Rs are related to memory consolidation - the process during which newly acquired memories are transformed into long-lasting memory traces. To test the involvement of SPW-Rs in this process, it is crucial to understand how SPW-Rs originate and propagate throughout the hippocampus. SPW-Rs can originate in CA3, and they typically spread from CA3 to CA1, but little is known about their formation within CA3. To investigate the generation and propagation of SPW-Rs in CA3, we recorded from mouse hippocampal slices using multi-electrode arrays and patch-clamp electrodes. We characterized extracellular and intracellular correlates of SPW-Rs and quantified their propagation along the pyramidal cell layer of CA3. We found that a hippocampal slice can be described by a speed and a direction of propagation of SPW-Rs. The preferred propagation direction was from CA3c (the subfield closer to the dentate gyrus) toward CA3a (the subfield at the boundary to CA2). In patch-clamp recordings from CA3 pyramidal neurons, propagation was estimated separately for excitatory and inhibitory currents associated with SPW-Rs. We found that propagation speed and direction of excitatory and inhibitory currents were correlated. The magnitude of the speed of propagation of SPW-Rs within CA3 was consistent with the speed of propagation of action potentials in axons of CA3 principal cells. KEY POINTS: Hippocampal sharp waves are considered important for memory consolidation; therefore, it is of interest to understand the mechanisms of their generation and propagation. Here, we used two different approaches to study the propagation of sharp waves in mouse CA3 in vitro: multi-electrode arrays and multiple single-cell recordings. We find a preferred direction of propagation of sharp waves from CA3c toward CA3a - both in the local field potential and in sharp wave-associated excitatory and inhibitory synaptic activity. The speed of sharp wave propagation is consistent with the speed of action potential propagation along the axons of CA3 pyramidal neurons. These new insights into the dynamics of sharp waves in the CA3 network will inform future experiments and theoretical models of sharp-wave generation mechanisms.

Haploinsufficiency of intraflagellar transport protein 172 causes autism-like behavioral phenotypes in mice through BDNF

INTRODUCTION

Primary cilia are hair-like solitary organelles growing on most mammalian cells that play fundamental roles in embryonic patterning and organogenesis. Defective cilia often cause a suite of inherited diseases called ciliopathies with multifaceted manifestations. Intraflagellar transport (IFT), a bidirectional protein trafficking along the cilium, actively facilitates the formation and absorption of primary cilia. IFT172 is the largest component of the IFT-B complex, and its roles in Bardet-Biedl Syndrome (BBS) have been appreciated with unclear mechanisms.

OBJECTIVES

We performed a battery of behavioral tests with Ift172 haploinsufficiency (Ift172+/-) and WT littermates. We use RNA sequencing to identify the genes and signaling pathways that are differentially expressed and enriched in the hippocampus of Ift172+/- mice. Using AAV-mediated sparse labeling, electron microscopic examination, patch clamp and local field potential recording, western blot, luciferase reporter assay, chromatin immunoprecipitation, and neuropharmacological approach, we investigated the underlying mechanisms for the aberrant phenotypes presented by Ift172+/- mice.

RESULTS

Ift172+/- mice displayed excessive self-grooming, elevated anxiety, and impaired cognition. RNA sequencing revealed enrichment of differentially expressed genes in pathways relevant to axonogenesis and synaptic plasticity, which were further confirmed by less spine density and synaptic number. Ift172+/- mice demonstrated fewer parvalbumin-expressing neurons, decreased inhibitory synaptic transmission, augmented theta oscillation, and sharp-wave ripples in the CA1 region. Moreover, Ift172 haploinsufficiency caused less BDNF production and less activated BDNF-TrkB signaling pathway through transcription factor Gli3. Application of 7,8-Dihydroxyflavone, a potent small molecular TrkB agonist, fully restored BDNF-TrkB signaling activity and abnormal behavioral phenotypes presented by Ift172+/- mice. With luciferase and chip assays, we provided further evidence that Gli3 may physically interact with BDNF promoter I and regulate BDNF expression.

CONCLUSIONS

Our data suggest that Ift172 per se drives neurotrophic effects and, when defective, could cause neurodevelopmental disorders reminiscent of autism-like disorders.

Sleep maintains excitatory synapse diversity in the cortex and hippocampus

Insufficient sleep is a global problem with serious consequences for cognition and mental health.1 Synapses play a central role in many aspects of cognition, including the crucial function of memory consolidation during sleep.2 Interference with the normal expression or function of synapse proteins is a cause of cognitive, mood, and other behavioral problems in over 130 brain disorders.3 Sleep deprivation (SD) has also been reported to alter synapse protein composition and synapse number, although with conflicting results.4,5,6,7 In our study, we conducted synaptome mapping of excitatory synapses in 125 regions of the mouse brain and found that sleep deprivation selectively reduces synapse diversity in the cortex and in the CA1 region of the hippocampus. Sleep deprivation targeted specific types and subtypes of excitatory synapses while maintaining total synapse density (synapse number/area). Synapse subtypes with longer protein lifetimes exhibited resilience to sleep deprivation, similar to observations in aging and genetic perturbations. Moreover, the altered synaptome architecture affected the responses to neural oscillations, suggesting that sleep plays a vital role in preserving cognitive function by maintaining the brain's synaptome architecture.

Interplay of hippocampal long-term potentiation and long-term depression in enabling memory representations

Hippocampal long-term potentiation (LTP) and long-term depression (LTD) are Hebbian forms of synaptic plasticity that are widely believed to comprise the physiological correlates of associative learning. They comprise a persistent, input-specific increase or decrease, respectively, in synaptic efficacy that, in rodents, can be followed for days and weeks in vivo. Persistent (>24 h) LTP and LTD exhibit distinct frequency-dependencies and molecular profiles in the hippocampal subfields. Moreover, causal and genetic studies in behaving rodents indicate that both LTP and LTD fulfil specific and complementary roles in the acquisition and retention of spatial memory. LTP is likely to be responsible for the generation of a record of spatial experience, which may serve as an associative schema that can be re-used to expedite or facilitate subsequent learning. In contrast, LTD may enable modification and dynamic updating of this representation, such that detailed spatial content information is included and the schema is rendered unique and distinguishable from other similar representations. Together, LTP and LTD engage in a dynamic interplay that supports the generation of complex associative memories that are resistant to generalization. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Mechanisms of Neuronal Reactivation in Memory Consolidation: A Perspective from Pathological Conditions

Memory consolidation refers to a process by which labile newly formed memory traces are progressively strengthened into long term memories and become more resistant to interference. Recent work has revealed that spontaneous hippocampal activity during rest, commonly referred to as "offline" activity, plays a critical role in the process of memory consolidation. Hippocampal reactivation occurs during sharp-wave ripples (SWRs), which are events associated with highly synchronous neural firing in the hippocampus and modulation of neural activity in distributed brain regions. Memory consolidation occurs primarily through a coordinated communication between hippocampus and neocortex. Cortical slow oscillations drive the repeated reactivation of hippocampal memory representations together with SWRs and thalamo-cortical spindles, inducing long-lasting cellular and network modifications responsible for memory stabilization.In this review, we aim to comprehensively cover the field of "reactivation and memory consolidation" research by detailing the physiological mechanisms of neuronal reactivation and firing patterns during SWRs and providing a discussion of more recent key findings. Several mechanistic explanations of neuropsychiatric diseases propose that impaired neural replay may underlie some of the symptoms of the disorders. Abnormalities in neuronal reactivation are a common phenomenon and cause pathological impairment in several diseases, such as Alzheimer's disease (AD), epilepsy and schizophrenia. However, the specific pathological changes and mechanisms of reactivation in each disease are different. Recent work has also enlightened some of the underlying pathological mechanisms of neuronal reactivation in these diseases. In this review, we further describe how SWRs, ripples and slow oscillations are affected in Alzheimer's disease, epilepsy, and schizophrenia. We then compare the differences of neuronal reactivation and discuss how different reactivation abnormalities cause pathological changes in these diseases. Aberrant neural reactivation provides insights into disease pathogenesis and may even serve as biomarkers for early disease progression and treatment response.

Self-avoidance dominates the selection of hippocampal replay

Spontaneous neural activity sequences are generated by the brain in the absence of external input 1-12 , yet how they are produced remains unknown. During immobility, hippocampal replay sequences depict spatial paths related to the animal's past experience or predicted future 13 . By recording from large ensembles of hippocampal place cells 14 in combination with optogenetic manipulation of cortical input in freely behaving rats, we show here that the selection of hippocampal replay is governed by a novel self-avoidance principle. Following movement cessation, replay of the animal's past path is strongly avoided, while replay of the future path predominates. Moreover, when the past and future paths overlap, early replays avoid both and depict entirely different trajectories. Further, replays avoid self-repetition, on a shorter timescale compared to the avoidance of previous behavioral trajectories. Eventually, several seconds into the stopping period, replay of the past trajectory dominates. This temporal organization contrasts with established and recent predictions 9,10,15,16 but is well-recapitulated by a symmetry-breaking attractor model of sequence generation in which individual neurons adapt their firing rates over time 26-35 . However, while the model is sufficient to produce avoidance of recently traversed or reactivated paths, it requires an additional excitatory input into recently activated cells to produce the later window of past-dominance. We performed optogenetic perturbations to demonstrate that this input is provided by medial entorhinal cortex, revealing its role in maintaining a memory of past experience that biases hippocampal replay. Together, these data provide specific evidence for how hippocampal replays are generated.

Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps

We propose a normative model for spatial representation in the hippocampal formation that combines optimality principles, such as maximizing coding range and spatial information per neuron, with an algebraic framework for computing in distributed representation. Spatial position is encoded in a residue number system, with individual residues represented by high-dimensional, complex-valued vectors. These are composed into a single vector representing position by a similarity-preserving, conjunctive vector-binding operation. Self-consistency between the representations of the overall position and of the individual residues is enforced by a modular attractor network whose modules correspond to the grid cell modules in entorhinal cortex. The vector binding operation can also associate different contexts to spatial representations, yielding a model for entorhinal cortex and hippocampus. We show that the model achieves normative desiderata including superlinear scaling of patterns with dimension, robust error correction, and hexagonal, carry-free encoding of spatial position. These properties in turn enable robust path integration and association with sensory inputs. More generally, the model formalizes how compositional computations could occur in the hippocampal formation and leads to testable experimental predictions.

Rescuing impaired hippocampal-cortical interactions and spatial reorientation learning and memory during sleep in a mouse model of Alzheimer's disease using hippocampal 40 Hz stimulation

In preclinical Alzheimer's disease (AD), spatial learning and memory is impaired. We reported similar impairments in 3xTg-AD mice on a virtual maze (VM) spatial-reorientation-task that requires using landmarks to navigate. Hippocampal (HPC)-cortical dysfunction during sleep (important for memory consolidation) is a potential mechanism for memory impairments in AD. We previously found deficits in HPC-cortical coordination during sleep coinciding with VM impairments the next day. Some forms of 40 Hz stimulation seem to clear AD pathology in mice, and improve functional connectivity in AD patients. Thus, we implanted a recording array targeting parietal cortex (PC) and HPC to assess HPC-PC coordination, and an optical fiber targeting HPC for 40 Hz or sham optogenetic stimulation in 3xTg/PV cre mice. We assessed PC delta waves (DW) and HPC sharp wave ripples (SWRs). In sham mice, SWR-DW cross-correlations were reduced, similar to 3xTg-AD mice. In 40 Hz mice, this phase-locking was rescued, as was performance on the VM. However, rescued HPC-PC coupling no longer predicted performance as in NonTg animals. Instead, DWs and SWRs independently predicted performance in 40 Hz mice. Thus, 40 Hz stimulation of HPC rescued functional interactions in the HPC-PC network, and rescued impairments in spatial navigation, but did not rescue the correlation between HPC-PC coordination during sleep and learning and memory. Together this pattern of results could inform AD treatment timing by suggesting that despite applying 40 Hz stimulation before significant tau and amyloid aggregation, pathophysiological processes led to brain changes that were not fully reversed even though cognition was recovered.

Significance Statement

One of the earliest symptoms of Alzheimer's disease (AD) is getting lost in space or experiencing deficits in spatial navigation, which involve navigation computations as well as learning and memory. We investigated cross brain region interactions supporting memory formation as a potential causative factor of impaired spatial learning and memory in AD. To assess this relationship between AD pathophysiology, brain changes, and behavioral alterations, we used a targeted approach for clearing amyloid beta and tau to rescue functional interactions in the brain. This research strongly connects brain activity patterns during sleep to tau and amyloid accumulation, and will aid in understanding the mechanisms underlying cognitive dysfunction in AD. Furthermore, the results offer insight for improving early identification and treatment strategies.

Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments

During both sleep and awake immobility, hippocampal place cells reactivate time-compressed versions of sequences representing recently experienced trajectories in a phenomenon known as replay. Intriguingly, spontaneous sequences can also correspond to forthcoming trajectories in novel environments experienced later, in a phenomenon known as preplay. Here, we present a model showing that sequences of spikes correlated with the place fields underlying spatial trajectories in both previously experienced and future novel environments can arise spontaneously in neural circuits with random, clustered connectivity rather than pre-configured spatial maps. Moreover, the realistic place fields themselves arise in the circuit from minimal, landmark-based inputs. We find that preplay quality depends on the network's balance of cluster isolation and overlap, with optimal preplay occurring in small-world regimes of high clustering yet short path lengths. We validate the results of our model by applying the same place field and preplay analyses to previously published rat hippocampal place cell data. Our results show that clustered recurrent connectivity can generate spontaneous preplay and immediate replay of novel environments. These findings support a framework whereby novel sensory experiences become associated with preexisting "pluripotent" internal neural activity patterns.

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.

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 generative neural microdynamics of cognitive processing

The entorhinal cortex and hippocampus form a recurrent network that informs many cognitive processes, including memory, planning, navigation, and imagination. Neural recordings from these regions reveal spatially organized population codes corresponding to external environments and abstract spaces. Aligning the former cognitive functionalities with the latter neural phenomena is a central challenge in understanding the entorhinal-hippocampal circuit (EHC). Disparate experiments demonstrate a surprising level of complexity and apparent disorder in the intricate spatiotemporal dynamics of sequential non-local hippocampal reactivations, which occur particularly, though not exclusively, during immobile pauses and rest. We review these phenomena with a particular focus on their apparent lack of physical simulative realism. These observations are then integrated within a theoretical framework and proposed neural circuit mechanisms that normatively characterize this neural complexity by conceiving different regimes of hippocampal microdynamics as neuromarkers of diverse cognitive computations.

CA3 Circuit Model Compressing Sequential Information in Theta Oscillation and Replay

The hippocampus plays a critical role in the compression and retrieval of sequential information. During wakefulness, it achieves this through theta phase precession and theta sequences. Subsequently, during periods of sleep or rest, the compressed information reactivates through sharp-wave ripple events, manifesting as memory replay. However, how these sequential neuronal activities are generated and how they store information about the external environment remain unknown. We developed a hippocampal cornu ammonis 3 (CA3) computational model based on anatomical and electrophysiological evidence from the biological CA3 circuit to address these questions. The model comprises theta rhythm inhibition, place input, and CA3-CA3 plastic recurrent connection. The model can compress the sequence of the external inputs, reproduce theta phase precession and replay, learn additional sequences, and reorganize previously learned sequences. A gradual increase in synaptic inputs, controlled by interactions between theta-paced inhibition and place inputs, explained the mechanism of sequence acquisition. This model highlights the crucial role of plasticity in the CA3 recurrent connection and theta oscillational dynamics and hypothesizes how the CA3 circuit acquires, compresses, and replays sequential information.

The hippocampus contributes to retroactive stimulus associations during trace fear conditioning

Binding events that occur at different times are essential for memory formation. In trace fear conditioning, animals associate a tone and footshock despite no temporal overlap. The hippocampus is thought to mediate this learning by maintaining a memory of the tone until shock occurrence, however, evidence for sustained hippocampal tone representations is lacking. Here, we demonstrate a retrospective role for the hippocampus in trace fear conditioning. Bulk calcium imaging revealed sustained increases in CA1 activity after footshock that were not observed after tone termination. Optogenetic silencing of CA1 immediately after footshock impaired subsequent memory. Additionally, footshock increased the number of sharp-wave ripples compared to baseline during conditioning. Therefore, post-shock hippocampal activity likely supports learning by reactivating and linking latent tone and shock representations. These findings highlight an underappreciated function of post-trial hippocampal activity in enabling retroactive temporal associations during new learning, as opposed to persistent maintenance of stimulus representations.

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.

Short-Term Preexposure to Novel Enriched Environment Augments Hippocampal Ripples in Urethane-Anesthetized Mice

Learning and memory are affected by novel enriched environment, a condition where animals play and interact with a variety of toys and conspecifics. Exposure of animals to the novel enriched environments improves memory by altering neural plasticity during natural sleep, a process called memory consolidation. The hippocampus, a pivotal brain region for learning and memory, generates high-frequency oscillations called ripples during sleep, which is required for memory consolidation. Naturally occurring sleep shares characteristics in common with general anesthesia in terms of extracellular oscillations, guaranteeing anesthetized animals suitable to examine neural activity in a sleep-like state. However, it is poorly understood whether the preexposure of animals to the novel enriched environment modulates neural activity in the hippocampus under subsequent anesthesia. To ask this question, we allowed mice to freely explore the novel enriched environment or their standard environment, anesthetized them, and recorded local field potentials in the hippocampal CA1 area. We then compared the characteristics of hippocampal ripples between the two groups and found that the amplitude of ripples and the number of successive ripples were larger in the novel enriched environment group than in the standard environment group, suggesting that the afferent synaptic input from the CA3 area to the CA1 area was higher when the animals underwent the novel enriched environment. These results underscore the importance of prior experience that surpasses subsequent physical states from the neurophysiological point of view.

Topological analysis of sharp-wave ripple waveforms reveals input mechanisms behind feature variations

The reactivation of experience-based neural activity patterns in the hippocampus is crucial for learning and memory. These reactivation patterns and their associated sharp-wave ripples (SWRs) are highly variable. However, this variability is missed by commonly used spectral methods. Here, we use topological and dimensionality reduction techniques to analyze the waveform of ripples recorded at the pyramidal layer of CA1. We show that SWR waveforms distribute along a continuum in a low-dimensional space, which conveys information about the underlying layer-specific synaptic inputs. A decoder trained in this space successfully links individual ripples with their expected sinks and sources, demonstrating how physiological mechanisms shape SWR variability. Furthermore, we found that SWR waveforms segregated differently during wakefulness and sleep before and after a series of cognitive tasks, with striking effects of novelty and learning. Our results thus highlight how the topological analysis of ripple waveforms enables a deeper physiological understanding of SWRs.

Theta-band phase locking during encoding leads to coordinated entorhinal-hippocampal replay

Precisely timed interactions between hippocampal and cortical neurons during replay epochs are thought to support learning. Indeed, research has shown that replay is associated with heightened hippocampal-cortical synchrony. Yet many caveats remain in our understanding. Namely, it remains unclear how this offline synchrony comes about, whether it is specific to particular behavioral states, and how-if at all-it relates to learning. In this study, we sought to address these questions by analyzing coordination between CA1 cells and neurons of the deep layers of the medial entorhinal cortex (dMEC) while rats learned a novel spatial task. During movement, we found a subset of dMEC cells that were particularly locked to hippocampal LFP theta-band oscillations and that were preferentially coordinated with hippocampal replay during offline periods. Further, dMEC synchrony with CA1 replay peaked ∼10 ms after replay initiation in CA1, suggesting that the distributed replay reflects extra-hippocampal information propagation and is specific to "offline" periods. Finally, theta-modulated dMEC cells showed a striking experience-dependent increase in synchronization with hippocampal replay trajectories, mirroring the animals' acquisition of the novel task and coupling to the hippocampal local field. Together, these findings provide strong support for the hypothesis that synergistic hippocampal-cortical replay supports learning and highlights phase locking to hippocampal theta oscillations as a potential mechanism by which such cross-structural synchrony comes about.

Associative and predictive hippocampal codes support memory-guided behaviors

Episodic memory involves learning and recalling associations between items and their spatiotemporal context. Those memories can be further used to generate internal models of the world that enable predictions to be made. The mechanisms that support these associative and predictive aspects of memory are not yet understood. In this study, we used an optogenetic manipulation to perturb the sequential structure, but not global network dynamics, of place cells as rats traversed specific spatial trajectories. This perturbation abolished replay of those trajectories and the development of predictive representations, leading to impaired learning of new optimal trajectories during memory-guided navigation. However, place cell assembly reactivation and reward-context associative learning were unaffected. Our results show a mechanistic dissociation between two complementary hippocampal codes: an associative code (through coactivity) and a predictive code (through sequences).

Hippocampal sharp-wave ripples and their spike assembly content are regulated by the medial entorhinal cortex

Hippocampal sharp-wave ripples (SPW-Rs) are critical for memory consolidation and retrieval. The neuronal content of spiking during SPW-Rs is believed to be under the influence of neocortical inputs via the entorhinal cortex (EC). Optogenetic silencing of the medial EC (mEC) reduced the incidence of SPW-Rs with minor impacts on their magnitude or duration, similar to local CA1 silencing. The effect of mEC silencing on CA1 firing and field potentials was comparable to the effect of transient cortex-wide DOWN states of non-REM (NREM) sleep, implying that decreased SPW-R incidence in both cases is due to tonic disfacilitation of hippocampal circuits. The neuronal composition of CA1 pyramidal neurons during SPW-Rs was altered by mEC silencing but was restored immediately after silencing. We suggest that the mEC provides both tonic and transient influences on hippocampal network states by timing the occurrence of SPW-Rs and altering their neuronal content.

Hippocampal memory reactivation during sleep is correlated with specific cortical states of the retrosplenial and prefrontal cortices

Episodic memories are thought to be stabilized through the coordination of cortico-hippocampal activity during sleep. However, the timing and mechanism of this coordination remain unknown. To investigate this, we studied the relationship between hippocampal reactivation and slow-wave sleep up and down states of the retrosplenial cortex (RTC) and prefrontal cortex (PFC). We found that hippocampal reactivations are strongly correlated with specific cortical states. Reactivation occurred during sustained cortical Up states or during the transition from up to down state. Interestingly, the most prevalent interaction with memory reactivation in the hippocampus occurred during sustained up states of the PFC and RTC, while hippocampal reactivation and cortical up-to-down state transition in the RTC showed the strongest coordination. Reactivation usually occurred within 150-200 msec of a cortical Up state onset, indicating that a buildup of excitation during cortical Up state activity influences the probability of memory reactivation in CA1. Conversely, CA1 reactivation occurred 30-50 msec before the onset of a cortical down state, suggesting that memory reactivation affects down state initiation in the RTC and PFC, but the effect in the RTC was more robust. Our findings provide evidence that supports and highlights the complexity of bidirectional communication between cortical regions and the hippocampus during sleep.

Dual memory model for experience-once task-incremental lifelong learning

Experience replay (ER) is a widely-adopted neuroscience-inspired method to perform lifelong learning. Nonetheless, existing ER-based approaches consider very coarse memory modules with simple memory and rehearsal mechanisms that cannot fully exploit the potential of memory replay. Evidence from neuroscience has provided fine-grained memory and rehearsal mechanisms, such as the dual-store memory system consisting of PFC-HC circuits. However, the computational abstraction of these processes is still very challenging. To address these problems, we introduce the Dual-Memory (Dual-MEM) model emulating the memorization, consolidation, and rehearsal process in the PFC-HC dual-store memory circuit. Dual-MEM maintains an incrementally updated short-term memory to benefit current-task learning. At the end of the current task, short-term memories will be consolidated into long-term ones for future rehearsal to alleviate forgetting. For the Dual-MEM optimization, we propose two learning policies that emulate different memory retrieval strategies: Direct Retrieval Learning and Mixup Retrieval Learning. Extensive evaluations on eight benchmarks demonstrate that Dual-MEM delivers compelling performance while maintaining high learning and memory utilization efficiencies under the challenging experience-once setting.

Postnatal Maturation of Membrane Potential Dynamics during in Vivo Hippocampal Ripples

Sharp-wave ripples (SWRs) are transient high-frequency oscillations of local field potentials (LFPs) in the hippocampus and play a critical role in memory consolidation. During SWRs, CA1 pyramidal cells exhibit rapid spike sequences that often replay the sequential activity that occurred during behavior. This temporally organized firing activity gradually emerges during 2 weeks after the eye opening; however, it remains unclear how the organized spikes during SWRs mature at the intracellular membrane potential (Vm) level. Here, we recorded Vm of CA1 pyramidal cells simultaneously with hippocampal LFPs from anesthetized immature mice of either sex after the developmental emergence of SWRs. On postnatal days 16 and 17, Vm dynamics around SWRs were premature, characterized by prolonged depolarizations without either pre- or post-SWR hyperpolarizations. The biphasic hyperpolarizations, features typical of adult SWR-relevant Vm, formed by approximately postnatal day 30. This Vm maturation was associated with an increase in SWR-associated inhibitory inputs to pyramidal cells. Thus, the development of SWR-relevant inhibition restricts the temporal windows for spikes of pyramidal cells and allows CA1 pyramidal cells to organize their spike sequences during SWRs.SIGNIFICANCE STATEMENT Sharp-wave ripples (SWRs) are prominent hippocampal oscillations and play a critical role in memory consolidation. During SWRs, hippocampal neurons synchronously emit spikes with organized temporal patterns. This temporal structure of spikes during SWRs develops during the third and fourth postnatal weeks, but the underlying mechanisms are not well understood. Here, we recorded in vivo membrane potentials from hippocampal neurons in premature mice and suggest that the maturation of SWR-associated inhibition enables hippocampal neurons to produce precisely controlled spike times during SWRs.

Dissecting cell-type-specific pathways in medial entorhinal cortical-hippocampal network for episodic memory

Episodic memory, which refers to our ability to encode and recall past events, is essential to our daily lives. Previous research has established that both the entorhinal cortex (EC) and hippocampus (HPC) play a crucial role in the formation and retrieval of episodic memories. However, to understand neural circuit mechanisms behind these processes, it has become necessary to monitor and manipulate the neural activity in a cell-type-specific manner with high temporal precision during memory formation, consolidation, and retrieval in the EC-HPC networks. Recent studies using cell-type-specific labeling, monitoring, and manipulation have demonstrated that medial EC (MEC) contains multiple excitatory neurons that have differential molecular markers, physiological properties, and anatomical features. In this review, we will comprehensively examine the complementary roles of superficial layers of neurons (II and III) and the roles of deeper layers (V and VI) in episodic memory formation and recall based on these recent findings.

Experience alters hippocampal and cortical network communication via a KIBRA-dependent mechanism

Synaptic plasticity is hypothesized to underlie "replay" of salient experience during hippocampal sharp-wave/ripple (SWR)-based ensemble activity and to facilitate systems-level memory consolidation coordinated by SWRs and cortical sleep spindles. It remains unclear how molecular changes at synapses contribute to experience-induced modification of network function. The synaptic protein KIBRA regulates plasticity and memory. To determine the impact of KIBRA-regulated plasticity on circuit dynamics, we recorded in vivo neural activity from wild-type (WT) mice and littermates lacking KIBRA and examined circuit function before, during, and after novel experience. In WT mice, experience altered population activity and oscillatory dynamics in a manner consistent with incorporation of new information content in replay and enhanced hippocampal-cortical communication. While baseline SWR features were normal in KIBRA conditional knockout (cKO) mice, experience-dependent alterations in SWRs were absent. Furthermore, intra-hippocampal and hippocampal-cortical communication during SWRs was disrupted following KIBRA deletion. These results indicate molecular mechanisms that underlie network-level adaptations to experience.

Extracting electromyographic signals from multi-channel LFPs using independent component analysis without direct muscular recording

Electromyography (EMG) has been commonly used for the precise identification of animal behavior. However, it is often not recorded together with in vivo electrophysiology due to the need for additional surgeries and setups and the high risk of mechanical wire disconnection. While independent component analysis (ICA) has been used to reduce noise from field potential data, there has been no attempt to proactively use the removed "noise," of which EMG signals are thought to be one of the major sources. Here, we demonstrate that EMG signals can be reconstructed without direct EMG recording using the "noise" ICA component from local field potentials. The extracted component is highly correlated with directly measured EMG, termed IC-EMG. IC-EMG is useful for measuring an animal's sleep/wake, freezing response, and non-rapid eye movement (NREM)/REM sleep states consistently with actual EMG. Our method has advantages in precise and long-term behavioral measurement in wide-ranging in vivo electrophysiology experiments.

Sleep sharp wave ripple and its functions in memory and synaptic plasticity

Memory is one of the fundamental cognitive functions of brain. The formation and consolidation of memory depend on the hippocampus and sleep. Sharp wave ripple (SWR) is an electrophysiological event which is most frequently observed in the hippocampus during sleep. It represents a highly synchronized neuronal activity pattern which modulates numerous brain regions including the neocortex, subcortical areas, and the hippocampus itself. In this review, we discuss how SWRs link experiences to memories and what happens in the hippocampus and other brain regions during sleep by focusing on synaptic plasticity.

How our understanding of memory replay evolves

Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.

CA2 orchestrates hippocampal network dynamics

The hippocampus is composed of various subregions: CA1, CA2, CA3, and the dentate gyrus (DG). Despite the abundant hippocampal research literature, until recently, CA2 received little attention. The development of new genetic and physiological tools allowed recent studies characterizing the unique properties and functional roles of this hippocampal subregion. Despite its small size, the cellular content of CA2 is heterogeneous at the molecular and physiological levels. CA2 has been heavily implicated in social behaviors, including social memory. More generally, the mechanisms by which the hippocampus is involved in memory include the reactivation of neuronal ensembles following experience. This process is coordinated by synchronous network events known as sharp-wave ripples (SWRs). Recent evidence suggests that CA2 plays an important role in the generation of SWRs. The unique connectivity and physiological properties of CA2 pyramidal cells make this region a computational hub at the core of hippocampal information processing. Here, we review recent findings that support the role of CA2 in coordinating hippocampal network dynamics from a systems neuroscience perspective.

Hippocampal-medial entorhinal circuit is differently organized along the dorsoventral axis in rodents

The general understanding of hippocampal circuits is that the hippocampus and the entorhinal cortex (EC) are topographically connected through parallel identical circuits along the dorsoventral axis. Our anterograde tracing and in vitro electrophysiology data, however, show a markedly different dorsoventral organization of the hippocampal projection to the medial EC (MEC). While dorsal hippocampal projections are confined to the dorsal MEC, ventral hippocampal projections innervate both dorsal and ventral MEC. Further, whereas the dorsal hippocampus preferentially targets layer Vb (LVb) neurons, the ventral hippocampus mainly targets cells in layer Va (LVa). This connectivity scheme differs from hippocampal projections to the lateral EC, which are topographically organized along the dorsoventral axis. As LVa neurons project to telencephalic structures, our findings indicate that the ventral hippocampus regulates LVa-mediated entorhinal-neocortical output from both dorsal and ventral MEC. Overall, the marked dorsoventral differences in hippocampal-entorhinal connectivity impose important constraints on signal flow in hippocampal-neocortical circuits.

Alterations in theta-gamma coupling and sharp wave-ripple, signs of prodromal hippocampal network impairment in the TgF344-AD rat model

Alzheimer's disease (AD) is a severe neurodegenerative disorder caused by the accumulation of toxic proteins, amyloid-beta (Aβ) and tau, which eventually leads to dementia. Disease-modifying therapies are still lacking, due to incomplete insights into the neuropathological mechanisms of AD. Synaptic dysfunction is known to occur before cognitive symptoms become apparent and recent studies have demonstrated that imbalanced synaptic signaling drives the progression of AD, suggesting that early synaptic dysfunction could be an interesting therapeutic target. Synaptic dysfunction results in altered oscillatory activity, which can be detected with electroencephalography and electrophysiological recordings. However, the majority of these studies have been performed at advanced stages of AD, when extensive damage and cognitive symptoms are already present. The current study aimed to investigate if the hippocampal oscillatory activity is altered at pre-plaque stages of AD. The rats received stereotactic surgery to implant a laminar electrode in the CA1 layer of the right hippocampus. Electrophysiological recordings during two consecutive days in an open field were performed in 4-5-month-old TgF344-AD rats when increased concentrations of soluble Aβ species were observed in the brain, in the absence of Aβ-plaques. We observed a decreased power of high theta oscillations in TgF344-AD rats compared to wild-type littermates. Sharp wave-ripple (SWR) analysis revealed an increased SWR power and a decreased duration of SWR during quiet wake in TgF344-AD rats. The alterations in properties of SWR and the increased power of fast oscillations are suggestive of neuronal hyperexcitability, as has been demonstrated to occur during presymptomatic stages of AD. In addition, decreased strength of theta-gamma coupling, an important neuronal correlate of memory encoding, was observed in the TgF344-AD rats. Theta-gamma phase amplitude coupling has been associated with memory encoding and the execution of cognitive functions. Studies have demonstrated that mild cognitive impairment patients display decreased coupling strength, similar to what is described here. The current study demonstrates altered hippocampal network activity occurring at pre-plaque stages of AD and provides insights into prodromal network dysfunction in AD. The alterations observed could aid in the detection of AD during presymptomatic stages.

Hippocampal non-theta state: The "Janus face" of information processing

The vast majority of studies on hippocampal rhythms have been conducted on animals or humans in situations where their attention was focused on external stimuli or solving cognitive tasks. These studies formed the basis for the idea that rhythmical activity coordinates the work of neurons during information processing. However, at rest, when attention is not directed to external stimuli, brain rhythms do not disappear, although the parameters of oscillatory activity change. What is the functional load of rhythmical activity at rest? Hippocampal oscillatory activity during rest is called the non-theta state, as opposed to the theta state, a characteristic activity during active behavior. We dedicate our review to discussing the present state of the art in the research of the non-theta state. The key provisions of the review are as follows: (1) the non-theta state has its own characteristics of oscillatory and neuronal activity; (2) hippocampal non-theta state is possibly caused and maintained by change of rhythmicity of medial septal input under the influence of raphe nuclei; (3) there is no consensus in the literature about cognitive functions of the non-theta-non-ripple state; and (4) the antagonistic relationship between theta and delta rhythms observed in rodents is not always observed in humans. Most attention is paid to the non-theta-non-ripple state, since this aspect of hippocampal activity has not been investigated properly and discussed in reviews.

Fast network oscillations during non-REM sleep support memory consolidation

The neocortex is disconnected from the outside world during sleep, which has been hypothesized to be relevant for synaptic reorganization involved in memory consolidation. Fast network oscillations, such as hippocampal sharp-wave ripples, cortical ripples, and amygdalar high-frequency oscillations, are prominent during non-REM sleep. Although these oscillations are thought to be generated by local circuit mechanisms, their occurrence rates and amplitudes are modulated by thalamocortical spindles and neocortical slow oscillations during non-REM sleep, suggesting that fast network oscillations and slower oscillations cooperatively work to facilitate memory consolidation. This review discusses the recent progress in understanding the generation, coordination, and functional roles of fast network oscillations. Further, it outlines how fast network oscillations in distinct brain regions synergistically support memory consolidation and retrieval by hosting cross-regional coactivation of memory-related neuronal ensembles.

Compositional Sequence Generation in the Entorhinal-Hippocampal System

Neurons in the medial entorhinal cortex exhibit multiple, periodically organized, firing fields which collectively appear to form an internal representation of space. Neuroimaging data suggest that this grid coding is also present in other cortical areas such as the prefrontal cortex, indicating that it may be a general principle of neural functionality in the brain. In a recent analysis through the lens of dynamical systems theory, we showed how grid coding can lead to the generation of a diversity of empirically observed sequential reactivations of hippocampal place cells corresponding to traversals of cognitive maps. Here, we extend this sequence generation model by describing how the synthesis of multiple dynamical systems can support compositional cognitive computations. To empirically validate the model, we simulate two experiments demonstrating compositionality in space or in time during sequence generation. Finally, we describe several neural network architectures supporting various types of compositionality based on grid coding and highlight connections to recent work in machine learning leveraging analogous techniques.

Interneuronal network model of theta-nested fast oscillations predicts differential effects of heterogeneity, gap junctions and short term depression for hyperpolarizing versus shunting inhibition

Theta and gamma oscillations in the hippocampus have been hypothesized to play a role in the encoding and retrieval of memories. Recently, it was shown that an intrinsic fast gamma mechanism in medial entorhinal cortex can be recruited by optogenetic stimulation at theta frequencies, which can persist with fast excitatory synaptic transmission blocked, suggesting a contribution of interneuronal network gamma (ING). We calibrated the passive and active properties of a 100-neuron model network to capture the range of passive properties and frequency/current relationships of experimentally recorded PV+ neurons in the medial entorhinal cortex (mEC). The strength and probabilities of chemical and electrical synapses were also calibrated using paired recordings, as were the kinetics and short-term depression (STD) of the chemical synapses. Gap junctions that contribute a noticeable fraction of the input resistance were required for synchrony with hyperpolarizing inhibition; these networks exhibited theta-nested high frequency oscillations similar to the putative ING observed experimentally in the optogenetically-driven PV-ChR2 mice. With STD included in the model, the network desynchronized at frequencies above ~200 Hz, so for sufficiently strong drive, fast oscillations were only observed before the peak of the theta. Because hyperpolarizing synapses provide a synchronizing drive that contributes to robustness in the presence of heterogeneity, synchronization decreases as the hyperpolarizing inhibition becomes weaker. In contrast, networks with shunting inhibition required non-physiological levels of gap junctions to synchronize using conduction delays within the measured range.

Sharp-wave ripple doublets induce complex dendritic spikes in parvalbumin interneurons in vivo

Neuronal plasticity has been shown to be causally linked to coincidence detection through dendritic spikes (dSpikes). We demonstrate the existence of SPW-R-associated, branch-specific, local dSpikes and their computational role in basal dendrites of hippocampal PV+ interneurons in awake animals. To measure the entire dendritic arbor of long thin dendrites during SPW-Rs, we used fast 3D acousto-optical imaging through an eccentric deep-brain adapter and ipsilateral local field potential recording. The regenerative calcium spike started at variable, NMDA-AMPA-dependent, hot spots and propagated in both direction with a high amplitude beyond a critical distance threshold (~150 µm) involving voltage-gated calcium channels. A supralinear dendritic summation emerged during SPW-R doublets when two successive SPW-R events coincide within a short temporal window (~150 ms), e.g., during more complex association tasks, and generated large dSpikes with an about 2.5-3-fold amplitude increase which propagated down to the soma. Our results suggest that these doublet-associated dSpikes can work as a dendritic-level temporal and spatial coincidence detector during SPW-R-related network computation in awake mice.

Impaired sharp-wave ripple coordination between the medial entorhinal cortex and hippocampal CA1 of knock-in model of Alzheimer’s disease

Clinical evidence suggests that the entorhinal cortex is a primary brain area triggering memory impairments in Alzheimer’s disease (AD), but the underlying brain circuit mechanisms remain largely unclear. In healthy brains, sharp-wave ripples (SWRs) in the hippocampus and entorhinal cortex play a critical role in memory consolidation. We tested SWRs in the MEC layers 2/3 of awake amyloid precursor protein knock-in (APP-KI) mice, recorded simultaneously with SWRs in the hippocampal CA1. We found that MEC→CA1 coordination of SWRs, found previously in healthy brains, was disrupted in APP-KI mice even at a young age before the emergence of spatial memory impairments. Intriguingly, long-duration SWRs critical for memory consolidation were mildly diminished in CA1, although SWR density and amplitude remained intact. Our results point to SWR incoordination in the entorhinal-hippocampal circuit as an early network symptom that precedes memory impairment in AD.

Optogenetics at the presynapse

Optogenetic actuators enable highly precise spatiotemporal interrogation of biological processes at levels ranging from the subcellular to cells, circuits and behaving organisms. Although their application in neuroscience has traditionally focused on the control of spiking activity at the somatodendritic level, the scope of optogenetic modulators for direct manipulation of presynaptic functions is growing. Presynaptically localized opsins combined with light stimulation at the terminals allow light-mediated neurotransmitter release, presynaptic inhibition, induction of synaptic plasticity and specific manipulation of individual components of the presynaptic machinery. Here, we describe presynaptic applications of optogenetic tools in the context of the unique cell biology of axonal terminals, discuss their potential shortcomings and outline future directions for this rapidly developing research area.

UP-DOWN states and ripples differentially modulate membrane potential dynamics across DG, CA3, and CA1 in awake mice

Hippocampal ripples are transient population bursts that structure cortico-hippocampal communication and play a central role in memory processing. However, the mechanisms controlling ripple initiation in behaving animals remain poorly understood. Here we combine multisite extracellular and whole-cell recordings in awake mice to contrast the brain state and ripple modulation of subthreshold dynamics across hippocampal subfields. We find that entorhinal input to the dentate gyrus (DG) exhibits UP and DOWN dynamics with ripples occurring exclusively in UP states. While elevated cortical input in UP states generates depolarization in DG and CA1, it produces persistent hyperpolarization in CA3 neurons. Furthermore, growing inhibition is evident in CA3 throughout the course of the ripple buildup, while DG and CA1 neurons exhibit depolarization transients 100 ms before and during ripples. These observations highlight the importance of CA3 inhibition for ripple generation, while pre-ripple responses indicate a long and orchestrated ripple initiation process in the awake state.

Multiple-Timescale Representations of Space: Linking Memory to Navigation

When navigating through space, we must maintain a representation of our position in real time; when recalling a past episode, a memory can come back in a flash. Interestingly, the brain's spatial representation system, including the hippocampus, supports these two distinct timescale functions. How are neural representations of space used in the service of both real-world navigation and internal mnemonic processes? Recent progress has identified sequences of hippocampal place cells, evolving at multiple timescales in accordance with either navigational behaviors or internal oscillations, that underlie these functions. We review experimental findings on experience-dependent modulation of these sequential representations and consider how they link real-world navigation to time-compressed memories. We further discuss recent work suggesting the prevalence of these sequences beyond hippocampus and propose that these multiple-timescale mechanisms may represent a general algorithm for organizing cell assemblies, potentially unifying the dual roles of the spatial representation system in memory and navigation.

Rapid Spectral Dynamics in Hippocampal Oscillons

Neurons in the brain are submerged into oscillating extracellular potential produced by synchronized synaptic currents. The dynamics of these oscillations is one of the principal characteristics of neurophysiological activity, broadly studied in basic neuroscience and used in applications. However, our interpretation of the brain waves' structure and hence our understanding of their functions depend on the mathematical and computational approaches used for data analysis. The oscillatory nature of the wave dynamics favors Fourier methods, which have dominated the field for several decades and currently constitute the only systematic approach to brain rhythms. In the following study, we outline an alternative framework for analyzing waves of local field potentials (LFPs) and discuss a set of new structures that it uncovers: a discrete set of frequency-modulated oscillatory processes—the brain wave oscillons and their transient spectral dynamics.

Spatial maps and oscillations in the healthy hippocampus of Octodon degus, a natural model of sporadic Alzheimer's disease

The Octodon degus is a South American rodent that is receiving increased attention as a potential model of aging and sporadic late-onset Alzheimer’s disease (AD). Impairments in spatial memory tasks in Octodon degus have been reported in relation to either advanced AD-like disease or hippocampal lesion, opening the way to investigate how the function of hippocampal networks affects behavior across AD stages. However, no characterization of hippocampal electrophysiology exists in this species. Here we describe in young, healthy specimens the activity of neurons and local field potential rhythms during spatial navigation tasks with and without objects. Our findings show similarities between the Octodon degus and laboratory rodents. First, place cells with characteristics similar to those found in rats and mice exist in the CA1 subfield of the Octodon degus. Second, the introduction of objects elicits novelty-related exploration and an increase in activity of CA1 cells, with location specific and unspecific components. Third, oscillations of the local field potential are organized according to their spectral content into bands similar to those found in laboratory rodents. These results suggest a common framework of underlying mechanisms, opening the way to future studies of hippocampal dysfunction in this species associated to aging and disease.