Preexisting hippocampal network dynamics constrain optogenetically induced place fields

Parallel processing of past and future memories through reactivation and synaptic plasticity mechanisms during sleep

Every day, we experience new episodes and store new memories. Although memories are stored in corresponding engram cells, how different sets of engram cells are selected for current and next episodes, and how they create their memories, remains unclear. Here we show that in male mice, hippocampal CA1 neurons show an organized synchronous activity in prelearning home cage sleep that correlates with the learning ensembles only in engram cells, termed preconfigured ensembles. Moreover, after learning, a subset of nonengram cells develops population activity, which is constructed during postlearning offline periods, and then emerges to represent engram cells for new learning. Our model suggests a potential role of synaptic depression and scaling in the reorganization of the activity of nonengram cells. Together, our findings indicate that during offline periods there are two parallel processes occurring: conserving of past memories through reactivation, and preparation for upcoming ones through offline synaptic plasticity mechanisms.

Shapley Fields Reveal Chemotopic Organization in the Mouse Olfactory Bulb Across Diverse Chemical Feature Sets

Representations of chemical features in the neural activity of the olfactory bulb (OB) are not well-understood, unlike the neural code for stimuli of the other sensory modalities. This is because the space of olfactory stimuli lacks a natural coordinate system, and this significantly complicates characterizing neural receptive fields (tuning curves), analogous to those in the other sensory modalities. The degree to which olfactory tuning is spatially organized across the OB, often referred to as chemotopy, is also not well-understood. To advance our understanding of these aspects of olfactory coding, we introduce an interpretable method of Shapley fields, as an olfactory analog of retinotopic receptive fields. Shapley fields are spatial distributions of chemical feature importance for the tuning of OB glomeruli. We used this tool to investigate chemotopy in the OB with diverse sets of chemical features using widefield epifluorescence recordings of the mouse dorsal OB in response to stimuli across a wide range of the chemical space. We found that Shapley fields reveal a weak chemotopic organization of the chemical feature sensitivity of dorsal OB glomeruli. This organization was consistent across animals and mostly agreed across very different chemical feature sets: (i) the expert-curated PubChem database features and (ii) features derived from a Graph Neural Network trained on human olfactory perceptual tasks. Moreover, we found that the principal components of the Shapley fields often corresponded to single commonly accepted chemical classification groups, that therefore could be "recovered" from the neural activity in the mouse OB. Our findings suggest that Shapley fields may serve as a chemical feature-agnostic method for investigating olfactory perception.

Hippocampal neuronal activity is aligned with action plans

Neurons in the hippocampus are correlated with different variables, including space, time, sensory cues, rewards and actions, in which the extent of tuning depends on ongoing task demands1-8. However, it remains uncertain whether such diverse tuning corresponds to distinct functions within the hippocampal network or whether a more generic computation can account for these observations9. Here, to disentangle the contribution of externally driven cues versus internal computation, we developed a task in mice in which space, auditory tones, rewards and context were juxtaposed with changing relevance. High-density electrophysiological recordings revealed that neurons were tuned to each of these modalities. By comparing movement paths and action sequences, we observed that external variables had limited direct influence on hippocampal firing. Instead, spiking was influenced by online action plans and modulated by goal uncertainty. Our results suggest that internally generated cell assembly sequences are selected and updated by action plans towards deliberate goals. The apparent tuning of hippocampal neuronal spiking to different sensory modalities might emerge due to alignment to the afforded action progression within a task rather than representation of external cues.

Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3

Apical and basal dendrites of pyramidal neurons receive anatomically and functionally distinct inputs, implying compartment-level functional diversity during behavior. To test this, we imaged in vivo calcium signals from soma, apical dendrites, and basal dendrites in mouse hippocampal CA3 pyramidal neurons during head-fixed navigation. To capture compartment-specific population dynamics, we developed computational tools to automatically segment dendrites and extract accurate fluorescence traces from densely labeled neurons. We validated the method on sparsely labeled preparations and synthetic data, predicting an optimal labeling density for high experimental throughput and analytical accuracy. Our method detected rapid, local dendritic activity. Dendrites showed robust spatial tuning, similar to soma but with higher activity rates. Across days, apical dendrites remained more stable and outperformed in decoding of the animal's position. Thus, population-level apical and basal dendritic differences may reflect distinct compartment-specific input-output functions and computations in CA3. These tools will facilitate future studies mapping sub-cellular activity and their relation to behavior.

Idiothetic representations are modulated by availability of sensory inputs and task demands in the hippocampal-septal circuit

The hippocampus is a higher-order brain structure responsible for encoding new episodic memories and predicting future outcomes. In the absence of external stimuli, neurons in the hippocampus track elapsed time, distance traveled, and other idiothetic variables. To this day, the exact determinants of idiothetic representations during free navigation remain unclear. Here, we developed unsupervised approaches to extract population and single-cell properties of more than 30,000 CA1 pyramidal neurons in freely moving mice. We find that spatiotemporal representations are composed of a mixture of idiothetic and allocentric information, the balance of which is dictated by task demand and environmental conditions. Additionally, a subset of CA1 pyramidal neurons encodes the spatiotemporal distance to rewards. Finally, distance and time information is integrated postsynaptically in the lateral septum, indicating that these high-level representations are effectively integrated in downstream neurons.

Early and late place cells during postnatal development of the hippocampus

A proportion of hippocampal CA1 neurons function as place cells from the onset of navigation, which are referred to as early place cells. It is not clear whether this subset of neurons is predisposed to become place cells during early stages, or if all neurons have this potential. Here, we longitudinally imaged the activity of CA1 neurons in developing male rats during navigation with both one-photon and two-photon microscopy. Our results suggested that a largely consistent population of cells functioned as early place cells, demonstrating higher spatial coding abilities across environments and a tendency to form more synchronous cell assemblies. Early place cells were present in both deep and superficial layers of CA1. Cells in the deep layer exhibited greater synchrony than those in the superficial layer during early ages. These results support the theory that an initial cognitive map is primarily shaped by a predetermined set of hippocampal cells.

Functional networks of inhibitory neurons orchestrate synchrony in the hippocampus

Inhibitory interneurons are pivotal components of cortical circuits. Beyond providing inhibition, they have been proposed to coordinate the firing of excitatory neurons within cell assemblies. While the roles of specific interneuron subtypes have been extensively studied, their influence on pyramidal cell synchrony in vivo remains elusive. Employing an all-optical approach in mice, we simultaneously recorded hippocampal interneurons and pyramidal cells and probed the network influence of individual interneurons using optogenetics. We demonstrate that CA1 interneurons form a functionally interconnected network that promotes synchrony through disinhibition during awake immobility, while preserving endogenous cell assemblies. Our network model underscores the importance of both cell assemblies and dense, unspecific interneuron connectivity in explaining our experimental findings, suggesting that interneurons may operate not only via division of labor but also through concerted activity.

Perpetual step-like restructuring of hippocampal circuit dynamics

Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single-cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we find that CA1 population vectors decorrelate gradually within a session. In contrast, individual neurons exhibit predominantly step-like emergence and disappearance of place fields or sustained changes in within-field firing. The changes are not restricted to particular parts of the maze or trials and do not require apparent behavioral changes. The same place fields emerge, disappear, and reappear across days, suggesting that the hippocampus reuses pre-existing assemblies, rather than forming new fields de novo. Our results suggest an internally driven perpetual step-like reorganization of the neuronal assemblies.

Hippocampal neuronal activity is aligned with action plans

Neurons in the hippocampus are correlated with different variables, including space, time, sensory cues, rewards, and actions, where the extent of tuning depends on ongoing task demands. However, it remains uncertain whether such diverse tuning corresponds to distinct functions within the hippocampal network or if a more generic computation can account for these observations. To disentangle the contribution of externally driven cues versus internal computation, we developed a task in mice where space, auditory tones, rewards, and context were juxtaposed with changing relevance. High-density electrophysiological recordings revealed that neurons were tuned to each of these modalities. By comparing movement paths and action sequences, we observed that external variables had limited direct influence on hippocampal firing. Instead, spiking was influenced by online action plans modulated by goal uncertainty. Our results suggest that internally generated cell assembly sequences are selected and updated by action plans toward deliberate goals. The apparent tuning of hippocampal neuronal spiking to different sensory modalities might emerge due to alignment to the afforded action progression within a task rather than representation of external cues.

A hippocampal circuit mechanism to balance memory reactivation during sleep

Memory consolidation involves the synchronous reactivation of hippocampal cells active during recent experience in sleep sharp-wave ripples (SWRs). How this increase in firing rates and synchrony after learning is counterbalanced to preserve network stability is not understood. We discovered a network event generated by an intrahippocampal circuit formed by a subset of CA2 pyramidal cells to cholecystokinin-expressing (CCK+) basket cells, which fire a barrage of action potentials ("BARR") during non-rapid eye movement sleep. CA1 neurons and assemblies that increased their activity during learning were reactivated during SWRs but inhibited during BARRs. The initial increase in reactivation during SWRs returned to baseline through sleep. This trend was abolished by silencing CCK+ basket cells during BARRs, resulting in higher synchrony of CA1 assemblies and impaired memory consolidation.

Dynamics of spike transmission and suppression between principal cells and interneurons in the hippocampus and entorhinal cortex

Synaptic excitation and inhibition are essential for neuronal communication. However, the variables that regulate synaptic excitation and inhibition in the intact brain remain largely unknown. Here, we examined how spike transmission and suppression between principal cells (PCs) and interneurons (INTs) are modulated by activity history, brain state, cell type, and somatic distance between presynaptic and postsynaptic neurons by applying cross-correlogram analyses to datasets recorded from the dorsal hippocampus and medial entorhinal cortex (MEC) of 11 male behaving and sleeping Long Evans rats. The strength, temporal delay, and brain-state dependency of the spike transmission and suppression depended on the subregions/layers. The spike transmission probability of PC-INT excitatory pairs that showed short-term depression versus short-term facilitation was higher in CA1 and lower in CA3. Likewise, the intersomatic distance affected the proportion of PC-INT excitatory pairs that showed short-term depression and facilitation in the opposite manner in CA1 compared with CA3. The time constant of depression was longer, while that of facilitation was shorter in MEC than in CA1 and CA3. During sharp-wave ripples, spike transmission showed a larger gain in the MEC than in CA1 and CA3. The intersomatic distance affected the spike transmission gain during sharp-wave ripples differently in CA1 versus CA3. A subgroup of MEC layer 3 (EC3) INTs preferentially received excitatory inputs from and inhibited MEC layer 2 (EC2) PCs. The EC2 PC-EC3 INT excitatory pairs, most of which showed short-term depression, exhibited higher spike transmission probabilities than the EC2 PC-EC2 INT and EC3 PC-EC3 INT excitatory pairs. EC2 putative stellate cells exhibited stronger spike transmission to and received weaker spike suppression from EC3 INTs than EC2 putative pyramidal cells. This study provides detailed comparisons of monosynaptic interaction dynamics in the hippocampal-entorhinal loop, which may help to elucidate circuit operations.

Cross-strata co-occurrence of ripples with theta-frequency oscillations in the hippocampus of foraging rats

Brain rhythms have been postulated to play central roles in animal cognition. A prominently reported dichotomy of hippocampal rhythms links theta-frequency oscillations (4-12 Hz) and ripples (120-250 Hz) exclusively to preparatory and consummatory behaviours, respectively. However, because of the differential power expression of these two signals across hippocampal strata, such exclusivity requires validation through analyses of simultaneous multi-strata recordings. We assessed co-occurrence of theta-frequency oscillations with ripples in multi-channel recordings of extracellular potentials across hippocampal strata from foraging rats. We detected all ripple events from an identified stratum pyramidale (SP) channel. We then defined theta epochs based on theta oscillations detected from the stratum lacunosum-moleculare (SLM) or the stratum radiatum (SR). We found ∼20% of ripple events (in SP) to co-occur with theta epochs identified from SR/SLM channels, defined here as theta ripples. Strikingly, when theta epochs were instead identified from the SP channel, such co-occurrences were significantly reduced because of a progressive reduction in theta power along the SLM-SR-SP axis. Behaviourally, we found most theta ripples to occur during immobile periods, with comparable theta power during exploratory and immobile theta epochs. Furthermore, the progressive reduction in theta power along the SLM-SR-SP axis was common to exploratory and immobile periods. Finally, we found a strong theta-phase preference of theta ripples within the fourth quadrant [3π/2 - 2π] of the associated theta oscillation. The prevalence of theta ripples expands the potential roles of ripple-frequency oscillations to span the continuum of encoding, retrieval and consolidation, achieved through interactions with theta oscillations. KEY POINTS: The brain manifests oscillations in recorded electrical potentials, with different frequencies of oscillation associated with distinct behavioural states. A prominently reported dichotomy assigns theta-frequency oscillations (4-12 Hz) and ripples (120-250 Hz) recorded in the hippocampus to be exclusively associated with preparatory and consummatory behaviours, respectively. Our multi-strata recordings from the rodent hippocampus coupled with cross-strata analyses provide direct quantitative evidence for the occurrence of ripple events nested within theta oscillations. These results highlight the need for an analysis pipeline that explicitly accounts for the specific strata where individual oscillatory power is high, in analysing simultaneously recorded data from multiple strata. Our observations open avenues for investigations involving cross-strata interactions between theta oscillations and ripples across different behavioural states.

Development of wafer-scale multifunctional nanophotonic neural probes for brain activity mapping

Optical techniques, such as optogenetic stimulation and functional fluorescence imaging, have been revolutionary for neuroscience by enabling neural circuit analysis with cell-type specificity. To probe deep brain regions, implantable light sources are crucial. Silicon photonics, commonly used for data communications, shows great promise in creating implantable devices with complex optical systems in a compact form factor compatible with high volume manufacturing practices. This article reviews recent developments of wafer-scale multifunctional nanophotonic neural probes. The probes can be realized on 200 or 300 mm wafers in commercial foundries and integrate light emitters for photostimulation, microelectrodes for electrophysiological recording, and microfluidic channels for chemical delivery and sampling. By integrating active optical devices to the probes, denser emitter arrays, enhanced on-chip biosensing, and increased ease of use may be realized. Silicon photonics technology makes possible highly versatile implantable neural probes that can transform neuroscience experiments.

Perpetual step-like restructuring of hippocampal circuit dynamics

Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we found that CA1 population vectors decorrelated gradually within a session. In contrast, individual neurons exhibited predominantly step-like emergence and disappearance of place fields or sustained change in within-field firing. The changes were not restricted to particular parts of the maze or trials and did not require apparent behavioral changes. The same place fields emerged, disappeared, and reappeared across days, suggesting that the hippocampus reuses pre-existing assemblies, rather than forming new fields de novo. Our results suggest an internally-driven perpetual step-like reorganization of the neuronal assemblies.

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

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

Silencing CA1 pyramidal cells output reveals the role of feedback inhibition in hippocampal oscillations

The precise temporal coordination of neural activity is crucial for brain function. In the hippocampus, this precision is reflected in the oscillatory rhythms observed in CA1. While it is known that a balance between excitatory and inhibitory activity is necessary to generate and maintain these oscillations, the differential contribution of feedforward and feedback inhibition remains ambiguous. Here we use conditional genetics to chronically silence CA1 pyramidal cell transmission, ablating the ability of these neurons to recruit feedback inhibition in the local circuit, while recording physiological activity in mice. We find that this intervention leads to local pathophysiological events, with ripple amplitude and intrinsic frequency becoming significantly larger and spatially triggered local population spikes locked to the trough of the theta oscillation appearing during movement. These phenotypes demonstrate that feedback inhibition is crucial in maintaining local sparsity of activation and reveal the key role of lateral inhibition in CA1 in shaping circuit function.

Local activation of CA1 pyramidal cells induces theta-phase precession

Hippocampal theta-phase precession is involved in spatiotemporal coding and in generating multineural spike sequences, but how precession originates remains unresolved. To determine whether precession can be generated directly in hippocampal area CA1 and disambiguate multiple competing mechanisms, we used closed-loop optogenetics to impose artificial place fields in pyramidal cells of mice running on a linear track. More than one-third of the CA1 artificial fields exhibited synthetic precession that persisted for a full theta cycle. By contrast, artificial fields in the parietal cortex did not exhibit synthetic precession. These findings are incompatible with precession models based on inheritance, dual-input, spreading activation, inhibition-excitation summation, or somato-dendritic competition. Thus, a precession generator resides locally within CA1.

Wired together, change together: Spike timing modifies transmission in converging assemblies

The precise timing of neuronal spikes may lead to changes in synaptic connectivity and is thought to be crucial for learning and memory. However, the effect of spike timing on neuronal connectivity in the intact brain remains unknown. Using closed-loop optogenetic stimulation in CA1 of freely moving mice, we generated unique spike patterns between presynaptic pyramidal cells (PYRs) and postsynaptic parvalbumin (PV)-immunoreactive cells. The stimulation led to spike transmission changes that occurred together across all presynaptic PYRs connected to the same postsynaptic PV cell. The precise timing of all presynaptic and postsynaptic cell spikes affected transmission changes. These findings reveal an unexpected plasticity mechanism, in which the spike timing of an entire cell assembly has a more substantial impact on effective connectivity than that of individual cell pairs.

Simultaneous electrophysiology and optogenetic perturbation of the same neurons in chronically implanted animals using μLED silicon probes

Micro-light-emitting-diode (μLED) silicon probes feature independently controllable miniature light-emitting-diodes (LEDs) embedded at several positions in each shank of a multi-shank probe, enabling temporally and spatially precise optogenetic neural circuit interrogation. Here, we present a protocol for performing causal and reproducible neural circuit manipulations in chronically implanted, freely moving animals. We describe steps for introducing optogenetic constructs, preparing and implanting a μLED probe, performing simultaneous in vivo electrophysiology with focal optogenetic perturbation, and recovering a probe following termination of an experiment. For complete details on the use and execution of this protocol, please refer to Watkins de Jong et al. (2023).1.

The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across Experience

Although much is known about how single neurons in the hippocampus represent an animal's position, how circuit interactions contribute to spatial coding is less well understood. Using a novel statistical estimator and theoretical modeling, both developed in the framework of maximum entropy models, we reveal highly structured CA1 cell-cell interactions in male rats during open field exploration. The statistics of these interactions depend on whether the animal is in a familiar or novel environment. In both conditions the circuit interactions optimize the encoding of spatial information, but for regimes that differ in the informativeness of their spatial inputs. This structure facilitates linear decodability, making the information easy to read out by downstream circuits. Overall, our findings suggest that the efficient coding hypothesis is not only applicable to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain.SIGNIFICANCE STATEMENT Local circuit interactions play a key role in neural computation and are dynamically shaped by experience. However, measuring and assessing their effects during behavior remains a challenge. Here, we combine techniques from statistical physics and machine learning to develop new tools for determining the effects of local network interactions on neural population activity. This approach reveals highly structured local interactions between hippocampal neurons, which make the neural code more precise and easier to read out by downstream circuits, across different levels of experience. More generally, the novel combination of theory and data analysis in the framework of maximum entropy models enables traditional neural coding questions to be asked in naturalistic settings.

Aversive stimulus-tuned responses in the CA1 of the dorsal hippocampus

Throughout life animals inevitably encounter unforeseen threatening events. Activity of principal cells in the hippocampus is tuned for locations and for salient stimuli in the animals' environment thus forming a map known to be pivotal for guiding behavior. Here, we explored if a code of threatening stimuli exists in the CA1 region of the dorsal hippocampus of mice by recording neuronal response to aversive stimuli delivered at changing locations. We have discovered a rapidly emerging, location independent response to innoxious aversive stimuli composed of the coordinated activation of subgroups of pyramidal cells and connected interneurons. Activated pyramidal cells had higher basal firing rate, more probably participated in ripples, targeted more interneurons than place cells and many of them lacked place fields. We also detected aversive stimulus-coupled assemblies dominated by the activated neurons. Notably, these assemblies could be observed even before the delivery of the first aversive event. Finally, we uncovered the systematic shift of the spatial code from the aversive to, surprisingly, the reward location during the fearful stimulus. Our results uncovered components of the dorsal CA1 circuit possibly key for re-sculpting the spatial map in response to abrupt aversive events.

Unique potential of immature adult-born neurons for the remodeling of CA3 spatial maps

Mammalian hippocampal circuits undergo extensive remodeling through adult neurogenesis. While this process has been widely studied, the specific contribution of adult-born granule cells (aGCs) to spatial operations in the hippocampus remains unknown. Here, we show that optogenetic activation of 4-week-old (young) aGCs in free-foraging mice produces a non-reversible reconfiguration of spatial maps in proximal CA3 while rarely evoking neural activity. Stimulation of the same neuronal cohort on subsequent days recruits CA3 neurons with increased efficacy but fails to induce further remapping. In contrast, stimulation of 8-week-old (mature) aGCs can reliably activate CA3 cells but produces no alterations in spatial maps. Our results reveal a unique role of young aGCs in remodeling CA3 representations, a potential that can be depleted and is lost with maturation. This ability could contribute to generate orthogonalized downstream codes supporting pattern separation.

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.

Spontaneous dynamics of hippocampal place fields in a model of combinatorial competition among stable inputs

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

Significance Statement

In both AI and theoretical neuroscience, learning systems often rely on the asymptotic convergence of slow-acting learning rules applied to input spaces that are presumed to be sampled repeatedly, for example over developmental timescales. Place cells of the hippocampus testify to a neural system capable of rapidly encoding cognitive variables-such as the animal's position in space-from limited experience. These internal representations undergo "spontaneous" changes over time, spurring much interest in their cognitive significance and underlying mechanisms. We investigate a model suggesting that some of these changes could be a tradeoff of rapid learning.

Linking temporal coordination of hippocampal activity to memory function

Oscillations in neural activity are widespread throughout the brain and can be observed at the population level through the local field potential. These rhythmic patterns are associated with cycles of excitability and are thought to coordinate networks of neurons, in turn facilitating effective communication both within local circuits and across brain regions. In the hippocampus, theta rhythms (4-12 Hz) could contribute to several key physiological mechanisms including long-range synchrony, plasticity, and at the behavioral scale, support memory encoding and retrieval. While neurons in the hippocampus appear to be temporally coordinated by theta oscillations, they also tend to fire in sequences that are developmentally preconfigured. Although loss of theta rhythmicity impairs memory, these sequences of spatiotemporal representations persist in conditions of altered hippocampal oscillations. The focus of this review is to disentangle the relative contribution of hippocampal oscillations from single-neuron activity in learning and memory. We first review cellular, anatomical, and physiological mechanisms underlying the generation and maintenance of hippocampal rhythms and how they contribute to memory function. We propose candidate hypotheses for how septohippocampal oscillations could support memory function while not contributing directly to hippocampal sequences. In particular, we explore how theta rhythms could coordinate the integration of upstream signals in the hippocampus to form future decisions, the relevance of such integration to downstream regions, as well as setting the stage for behavioral timescale synaptic plasticity. Finally, we leverage stimulation-based treatment in Alzheimer's disease conditions as an opportunity to assess the sufficiency of hippocampal oscillations for memory function.

Backbone spiking sequence as a basis for preplay, replay, and default states in human cortex

Sequences of spiking activity have been heavily implicated as potential substrates of memory formation and retrieval across many species. A parallel line of recent evidence also asserts that sequential activity may arise from and be constrained by pre-existing network structure. Here we reconcile these two lines of research in the human brain by measuring single unit spiking sequences in the temporal lobe cortex as participants perform an episodic memory task. We find the presence of an average backbone spiking sequence identified during pre-task rest that is stable over time and different cognitive states. We further demonstrate that these backbone sequences are composed of both rigid and flexible sequence elements, and that flexible elements within these sequences serve to promote memory specificity when forming and retrieving new memories. These results support the hypothesis that pre-existing network dynamics serve as a scaffold for ongoing neural activity in the human cortex.

A computational view of short-term plasticity and its implications for E-I balance

Short-term plasticity (STP) and excitatory-inhibitory balance (EI balance) are both ubiquitous building blocks of brain circuits across the animal kingdom. The synapses involved in EI are also subject to short-term plasticity, and several experimental studies have shown that their effects overlap. Recent computational and theoretical work has begun to highlight the functional implications of the intersection of these motifs. The findings are nuanced: while there are general computational themes, such as pattern tuning, normalization, and gating, much of the richness of these interactions comes from region- and modality specific tuning of STP properties. Together these findings point towards the STP-EI balance combination as being a versatile and highly efficient neural building block for a wide range of pattern-specific responses.

Effects of theta phase precessing optogenetic intervention on hippocampal neuronal reactivation and spatial maps

As animals explore environments, hippocampal place cells sequentially fire at progressively earlier phases of theta oscillations in hippocampal local field potentials. In this study, we evaluated the network-level significance of theta phase-entrained neuronal activity in organizing place cell spike patterns. A closed-loop system was developed in which optogenetic stimulation with a temporal pattern replicating theta phase precession is delivered to hippocampal CA1 neurons when rats traversed a particular region on a linear track. Place cells that had place fields during phase precessing stimulation, but not random phase stimulation, showed stronger reactivation during hippocampal sharp-wave ripples in a subsequent rest period. After the rest period, place cells with place fields that emerged during phase precessing stimulation showed more stable place fields. These results imply that neuronal reactivation and stability of spatial maps are mediated by theta phase precession in the hippocampus.

Rethinking the hippocampal cognitive map as a meta-learning computational module

A hallmark of biological intelligence is the ability to adaptively draw on past experience to guide behaviour under novel situations. Yet, the neurobiological principles that underlie this form of meta-learning remain relatively unexplored. In this Opinion, we review the existing literature on hippocampal spatial representations and reinforcement learning theory and describe a novel theoretical framework that aims to account for biological meta-learning. We conjecture that so-called hippocampal cognitive maps of familiar environments are part of a larger meta-representation (meta-map) that encodes information states and sources, which support exploration and provides a foundation for learning. We also introduce concrete hypotheses on how these generic states can be encoded using a principle of superposition.

Emergence of a predictive model in the hippocampus

The brain organizes experiences into memories that guide future behavior. Hippocampal CA1 population activity is hypothesized to reflect predictive models that contain information about future events, but little is known about how they develop. We trained mice on a series of problems with or without a common statistical structure to observe how memories are formed and updated. Mice that learned structured problems integrated their experiences into a predictive model that contained the solutions to upcoming novel problems. Retrieving the model during learning improved discrimination accuracy and facilitated learning. Using calcium imaging to track CA1 activity during learning, we found that hippocampal ensemble activity became more stable as mice formed a predictive model. The hippocampal ensemble was reactivated during training and incorporated new activity patterns from each training problem. These results show how hippocampal activity supports building predictive models by organizing new information with respect to existing memories.

Progress on the hippocampal circuits and functions based on sharp wave ripples

Sharp wave ripples (SWRs) are high-frequency synchronization events generated by hippocampal neuronal circuits during various forms of learning and reactivated during memory consolidation and recall. There is mounting evidence that SWRs are essential for storing spatial and social memories in rodents and short-term episodic memories in humans. Sharp wave ripples originate mainly from the hippocampal CA3 and subiculum, and can be transmitted to modulate neuronal activity in cortical and subcortical regions for long-term memory consolidation and behavioral guidance. Different hippocampal subregions have distinct functions in learning and memory. For instance, the dorsal CA1 is critical for spatial navigation, episodic memory, and learning, while the ventral CA1 and dorsal CA2 may work cooperatively to store and consolidate social memories. Here, we summarize recent studies demonstrating that SWRs are essential for the consolidation of spatial, episodic, and social memories in various hippocampal-cortical pathways, and review evidence that SWR dysregulation contributes to cognitive impairments in neurodegenerative and neurodevelopmental diseases.

Self-organization of songbird neural sequences during social isolation

Behaviors emerge via a combination of experience and innate predispositions. As the brain matures, it undergoes major changes in cellular, network, and functional properties that can be due to sensory experience as well as developmental processes. In normal birdsong learning, neural sequences emerge to control song syllables learned from a tutor. Here, we disambiguate the role of tutor experience and development in neural sequence formation by delaying exposure to a tutor. Using functional calcium imaging, we observe neural sequences in the absence of tutoring, demonstrating that tutor experience is not necessary for the formation of sequences. However, after exposure to a tutor, pre-existing sequences can become tightly associated with new song syllables. Since we delayed tutoring, only half our birds learned new syllables following tutor exposure. The birds that failed to learn were the birds in which pre-tutoring neural sequences were most 'crystallized,' that is, already tightly associated with their (untutored) song.

Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3

Anatomically segregated apical and basal dendrites of pyramidal neurons receive functionally distinct inputs, but it is unknown if this results in compartment-level functional diversity during behavior. Here we imaged calcium signals from apical dendrites, soma, and basal dendrites of pyramidal neurons in area CA3 of mouse hippocampus during head-fixed navigation. To examine dendritic population activity, we developed computational tools to identify dendritic regions of interest and extract accurate fluorescence traces. We identified robust spatial tuning in apical and basal dendrites, similar to soma, though basal dendrites had reduced activity rates and place field widths. Across days, apical dendrites were more stable than soma or basal dendrites, resulting in better decoding of the animal's position. These population-level dendritic differences may reflect functionally distinct input streams leading to different dendritic computations in CA3. These tools will facilitate future studies of signal transformations between cellular compartments and their relation to behavior.

A local circuit-basis for spatial navigation and memory processes in hippocampal area CA1

The hippocampus is a multi-stage neural circuit that is critical for memory formation. Its distinct anatomy has long inspired theories that rely on local interactions between neurons within each subregion in order to perform serial operations important for memory encoding and storage. These local computations have received less attention in CA1 area, the primary output node of the hippocampus, where excitatory neurons are thought to be only very sparsely interconnected. However, recent findings have demonstrated the power of local circuitry in CA1, with evidence for strong functional interactions among excitatory neurons, regulation by diverse inhibitory microcircuits, and novel plasticity rules that can profoundly reshape the hippocampal ensemble code. Here we review how these properties expand the dynamical repertoire of CA1 beyond the confines of feedforward processing, and what implications they have for hippocampo-cortical functions in memory formation.

Organization of hippocampal CA3 into correlated cell assemblies supports a stable spatial code

Hippocampal subfield CA3 is thought to stably store memories in assemblies of recurrently connected cells functioning as a collective. However, the collective hippocampal coding properties that are unique to CA3 and how such properties facilitate the stability or precision of the neural code remain unclear. Here, we performed large-scale Ca2+ imaging in hippocampal CA1 and CA3 of freely behaving mice that repeatedly explored the same, initially novel environments over weeks. CA3 place cells have more precise and more stable tuning and show a higher statistical dependence with their peers compared with CA1 place cells, uncovering a cell assembly organization in CA3. Surprisingly, although tuning precision and long-term stability are correlated, cells with stronger peer dependence exhibit higher stability but not higher precision. Overall, our results expose the three-way relationship between tuning precision, long-term stability, and peer dependence, suggesting that a cell assembly organization underlies long-term storage of information in the hippocampus.

Simultaneous Electrophysiology and Optogenetic Perturbation of the Same Neurons in Chronically Implanted Animals using μLED Silicon Probes

Optogenetics are a powerful tool for testing how a neural circuit influences neural activity, cognition, and behavior. Accordingly, the number of studies employing optogenetic perturbation has grown exponentially over the last decade. However, recent studies have highlighted that the impact of optogenetic stimulation/silencing can vary depending on the construct used, the local microcircuit connectivity, extent/power of illumination, and neuron types perturbed. Despite these caveats, the majority of studies employ optogenetics without simultaneously recording neural activity in the circuit that is being perturbed. This dearth of simultaneously recorded neural data is due in part to technical difficulties in combining optogenetics and extracellular electrophysiology. The recent introduction of μLED silicon probes, which feature independently controllable miniature LEDs embedded at several levels of each of multiple shanks of silicon probes, provides a tractable method for temporally and spatially precise interrogation of neural circuits. Here, we provide a protocol addressing how to perform chronic recordings using μLED probes. This protocol provides a schematic for performing causal and reproducible interrogations of neural circuits and addresses all phases of the recording process: introduction of optogenetic construct, implantation of the μLED probe, performing simultaneous optogenetics and electrophysiology in vivo , and post-processing of recorded data.

SUMMARY

This method allows a researcher to simultaneously perturb neural activity and record electrophysiological signal from the same neurons with high spatial specificity using silicon probes with integrated μLEDs. We outline a procedure detailing all stages of the process for performing reliable μLED experiments in chronically implanted rodents.

All-optical physiology resolves a synaptic basis for behavioral timescale plasticity

Learning has been associated with modifications of synaptic and circuit properties, but the precise changes storing information in mammals have remained largely unclear. We combined genetically targeted voltage imaging with targeted optogenetic activation and silencing of pre- and post-synaptic neurons to study the mechanisms underlying hippocampal behavioral timescale plasticity. In mice navigating a virtual-reality environment, targeted optogenetic activation of individual CA1 cells at specific places induced stable representations of these places in the targeted cells. Optical elicitation, recording, and modulation of synaptic transmission in behaving mice revealed that activity in presynaptic CA2/3 cells was required for the induction of plasticity in CA1 and, furthermore, that during induction of these place fields in single CA1 cells, synaptic input from CA2/3 onto these same cells was potentiated. These results reveal synaptic implementation of hippocampal behavioral timescale plasticity and define a methodology to resolve synaptic plasticity during learning and memory in behaving mammals.

Neural ensembles in navigation: From single cells to population codes

The brain can represent behaviorally relevant information through the firing of individual neurons as well as the coordinated firing of ensembles of neurons. Neurons in the hippocampus and associated cortical regions participate in a variety of types of ensembles to support navigation. These ensemble types include single cell codes, population codes, time-compressed sequences, behavioral sequences, and engrams. We present the physiological basis and behavioral relevance of ensemble firing. We discuss how these traditional definitions of ensembles can constrain or expand potential analyses due to the underlying assumptions and abstractions made. We highlight how coding can change at the ensemble level while underlying single cell codes remain intact. Finally, we present how ensemble definitions could be broadened to better understand the full complexity of the brain.

The two tales of hippocampal sharp-wave ripple content: The rigid and the plastic

Sharp-wave ripples, prominently in the CA1 region of the hippocampus, are short oscillatory events accompanied by bursts of neural firing. Ripples and associated hippocampal place cell sequences communicate with cortical ensembles during slow-wave sleep, which has been shown to be critical for systems consolidation of episodic memories. This consolidation is not limited to a newly formed memory trace; instead, ripples appear to reactivate and consolidate memories spanning various experiences. Despite this broad spanning influence, ripples remain capable of producing precise memories. The underlying mechanisms that enable ripples to consolidate memories broadly and with specificity across experiences remain unknown. In this review, we discuss data that uncovers circuit-level processes that generate ripples and influence their characteristics during consolidation. Based on current knowledge, we propose that memory emerges from the integration of two parallel consolidation pathways in CA1: the rigid and plastic pathways. The rigid pathway generates ripples stochastically, providing a backbone upon which dynamic plastic pathway inputs carrying novel information are integrated.

Neurodynamical Computing at the Information Boundaries of Intelligent Systems

Artificial intelligence has not achieved defining features of biological intelligence despite models boasting more parameters than neurons in the human brain. In this perspective article, we synthesize historical approaches to understanding intelligent systems and argue that methodological and epistemic biases in these fields can be resolved by shifting away from cognitivist brain-as-computer theories and recognizing that brains exist within large, interdependent living systems. Integrating the dynamical systems view of cognition with the massive distributed feedback of perceptual control theory highlights a theoretical gap in our understanding of nonreductive neural mechanisms. Cell assemblies-properly conceived as reentrant dynamical flows and not merely as identified groups of neurons-may fill that gap by providing a minimal supraneuronal level of organization that establishes a neurodynamical base layer for computation. By considering information streams from physical embodiment and situational embedding, we discuss this computational base layer in terms of conserved oscillatory and structural properties of cortical-hippocampal networks. Our synthesis of embodied cognition, based in dynamical systems and perceptual control, aims to bypass the neurosymbolic stalemates that have arisen in artificial intelligence, cognitive science, and computational neuroscience.

Memory reactivations during sleep

Neuronal activities that occur during awake periods are often reactivated again during sleep, to consolidate recently encoded memories, a process known as consolidation. In recent years, advanced tools, specially optical techniques and in-vivo live Ca²⁺ imaging, have revealed a deeper understanding to the offline periods' neuronal activities and their correspondence to later awake behavioral outputs. Recently, there is a growing consensus that sleep is more of an active process. Sleep has been associated with various functions, memory updating, future imaginations of possible familiar scenarios, decision making and planning by replaying past memories. Also, boosting insightful thoughts, creative thinking and problem solving by forming new associations and connections that were not present in awake states. Sleep activities have been directly associated with many "EUREKA" or "AHA" moments. Here, we describe recent views on memory reactivations during sleep and their implications on learning and memory.

On the Role of Speed in Technological and Biological Information Transfer for Computations

In all kinds of implementations of computing, whether technological or biological, some material carrier for the information exists, so in real-world implementations, the propagation speed of information cannot exceed the speed of its carrier. Because of this limitation, one must also consider the transfer time between computing units for any implementation. We need a different mathematical method to consider this limitation: classic mathematics can only describe infinitely fast and small computing system implementations. The difference between mathematical handling methods leads to different descriptions of the computing features of the systems. The proposed handling also explains why biological implementations can have lifelong learning and technological ones cannot. Our conclusion about learning matches published experimental evidence, both in biological and technological computing.

Learning from inhibition: Functional roles of hippocampal CA1 inhibition in spatial learning and memory

Hippocampal inhibitory interneurons exert a powerful influence on learning and memory. Inhibitory interneurons are known to play a major role in many diseases that affect memory, and to strongly influence brain functions required for memory-related tasks. While previous studies involving genetic, optogenetic, and pharmacological manipulations have shown that hippocampal interneurons play essential roles in spatial and episodic learning and memory, exactly how interneurons affect local circuit computations during spatial navigation is not well understood. Given the significant anatomical, morphological, and functional heterogeneity in hippocampal interneurons, one may suspect cell-type specific roles in circuit computations. Here, we review emerging evidence of CA1 hippocampal interneurons' role in local circuit computations that support spatial learning and memory and discuss open questions about CA1 interneurons in spatial learning.

High-resolution optogenetics in space and time

To understand the neural mechanisms of behavior, it is necessary to both monitor and perturb the activity of ensembles of neurons with high specificity. While neural ensemble recordings have been available for decades, progress in high-resolution manipulation techniques has lagged behind. Optogenetics has enabled the manipulation of genetically defined cell types in behaving animals, and recent developments, including multipoint nanofabricated light sources, provide spatiotemporal resolution on a par with that of physiological recordings. Here we review current advances in optogenetic methods for cellular-resolution stimulation and intervention, as well as their integration with real-time neural recordings for closed-loop experimentation. We discuss how these approaches open the door to new kinds of experiments aimed at dissecting the role of specific neural patterns and discrete cellular populations in orchestrating the activity of brain circuits that support behavior and cognition.

Preconfigured dynamics in the hippocampus are guided by embryonic birthdate and rate of neurogenesis

The incorporation of new information into the hippocampal network is likely to be constrained by its innate architecture and internally generated activity patterns. However, the origin, organization and consequences of such patterns remain poorly understood. In the present study we show that hippocampal network dynamics are affected by sequential neurogenesis. We birthdated CA1 pyramidal neurons with in utero electroporation over 4 embryonic days, encompassing the peak of hippocampal neurogenesis, and compared their functional features in freely moving adult mice. Neurons of the same birthdate displayed distinct connectivity, coactivity across brain states and assembly dynamics. Same-birthdate neurons exhibited overlapping spatial representations, which were maintained across different environments. Overall, the wiring and functional features of CA1 pyramidal neurons reflected a combination of birthdate and the rate of neurogenesis. These observations demonstrate that sequential neurogenesis during embryonic development shapes the preconfigured forms of adult network dynamics.

Inhibitory conductance controls place field dynamics in the hippocampus

Hippocampal place cells receive a disparate collection of excitatory and inhibitory currents that endow them with spatially selective discharges and rhythmic activity. Using a combination of in vivo intracellular and extracellular recordings with opto/chemogenetic manipulations and computational modeling, we investigate the influence of inhibitory and excitatory inputs on CA1 pyramidal cell responses. At the cell bodies, inhibition leads and is stronger than excitation across the entire theta cycle. Pyramidal neurons fire on the ascending phase of theta when released from inhibition. Computational models equipped with the observed conductances reproduce these dynamics. In these models, place field properties are favored when the increased excitation is coupled with a reduction of inhibition within the field. As predicted by our simulations, firing rate within place fields and phase locking to theta are impaired by DREADDs activation of interneurons. Our results indicate that decreased inhibitory conductance is critical for place field expression.

Valero et al. examine the influence of inhibition on place fields. They show that hippocampal neurons are dominated by inhibitory conductances during theta oscillations. A transient increase of excitation and drop of inhibition mediates place field emergence in simulations. Consistently, chemogenetic activation of interneurons deteriorates place cell properties in vivo.

Towards Generalizing the Information Theory for Neural Communication

Neuroscience extensively uses the information theory to describe neural communication, among others, to calculate the amount of information transferred in neural communication and to attempt the cracking of its coding. There are fierce debates on how information is represented in the brain and during transmission inside the brain. The neural information theory attempts to use the assumptions of electronic communication; despite the experimental evidence that the neural spikes carry information on non-discrete states, they have shallow communication speed, and the spikes' timing precision matters. Furthermore, in biology, the communication channel is active, which enforces an additional power bandwidth limitation to the neural information transfer. The paper revises the notions needed to describe information transfer in technical and biological communication systems. It argues that biology uses Shannon's idea outside of its range of validity and introduces an adequate interpretation of information. In addition, the presented time-aware approach to the information theory reveals pieces of evidence for the role of processes (as opposed to states) in neural operations. The generalized information theory describes both kinds of communication, and the classic theory is the particular case of the generalized theory.

A synaptic signal for novelty processing in the hippocampus

Episodic memory formation and recall are complementary processes that rely on opposing neuronal computations in the hippocampus. How this conflict is resolved in hippocampal circuits is unclear. To address this question, we obtained in vivo whole-cell patch-clamp recordings from dentate gyrus granule cells in head-fixed mice trained to explore and distinguish between familiar and novel virtual environments. We find that granule cells consistently show a small transient depolarisation upon transition to a novel environment. This synaptic novelty signal is sensitive to local application of atropine, indicating that it depends on metabotropic acetylcholine receptors. A computational model suggests that the synaptic response to novelty may bias granule cell population activity, which can drive downstream attractor networks to a new state, favouring the switch from recall to new memory formation when faced with novelty. Such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Memory formation and recall are complementary processes within the hippocampus. Here the authors demonstrate a synaptic signal of novelty in the hippocampus and provide a computational framework for how such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

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.

Action-driven remapping of hippocampal neuronal populations in jumping rats

The current dominant view of the hippocampus is that it is a navigation "device" guided by environmental inputs. Yet, a critical aspect of navigation is a sequence of planned, coordinated actions. We examined the role of action in the neuronal organization of the hippocampus by training rats to jump a gap on a linear track. Recording local field potentials and ensembles of single units in the hippocampus, we found that jumping produced a stereotypic behavior associated with consistent electrophysiological patterns, including phase reset of theta oscillations, predictable global firing-rate changes, and population vector shifts of hippocampal neurons. A subset of neurons ("jump cells") were systematically affected by the gap but only in one direction of travel. Novel place fields emerged and others were either boosted or attenuated by jumping, yet the theta spike phase versus animal position relationship remained unaltered. Thus, jumping involves an action plan for the animal to traverse the same route as without jumping, which is faithfully tracked by hippocampal neuronal activity.