Preexisting hippocampal network dynamics constrain optogenetically induced place fields

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.

Signatures of rapid plasticity in hippocampal CA1 representations during novel experiences

Neurons in the hippocampus exhibit a striking selectivity for specific combinations of sensory features, forming representations that are thought to subserve episodic memory. Even during completely novel experiences, hippocampal "place cells" are rapidly configured such that the population sparsely encodes visited locations, stabilizing within minutes of the first exposure to a new environment. What mechanisms enable this fast encoding of experience? Using virtual reality and neural population recordings in mice, we dissected the effects of novelty and experience on the dynamics of place field formation. During place field formation, many CA1 neurons immediately modulated the amplitude of their activity and shifted the location of their field, rapid changes in tuning predicted by behavioral timescale synaptic plasticity (BTSP). Signatures of BTSP were particularly enriched during the exploration of a novel context and decayed with experience. Our data suggest that novelty modulates the effective learning rate in CA1, favoring rapid mechanisms of field formation to encode a new experience.

Once is enough for hippocampal replay

In this issue of Neuron, Berners-Lee et al. (2022) reveal how neural dynamics in the hippocampus change after a single experience, offering a candidate mechanism for how hippocampal plasticity supports episodic memory.

Impact of optogenetic pulse design on CA3 learning and replay: A neural model

Optogenetic manipulation of hippocampal circuitry is an important tool for investigating learning in vivo. Numerous approaches to pulse design have been employed to elicit desirable circuit and behavioral outcomes. Here, we systematically test the outcome of different single-pulse waveforms in a rate-based model of hippocampal memory function at the level of mnemonic replay extension and de novo synaptic weight formation in CA3 and CA1. Lower-power waveforms with long forward or forward and backward ramps yield more natural sequence replay dynamics and induce synaptic plasticity that allows for more natural memory replay timing, in contrast to square or backward ramps. These differences between waveform shape and amplitude are preserved with the addition of noise in membrane potential, light scattering, and protein expression, improving the potential validity of predictions for in vivo work. These results inform future optogenetic experimental design choices in the field of learning and memory.

Aluminium oxide nanoparticles compromise spatial memory performance and proBDNF-mediated neuronal function in the hippocampus of rats

Background

Alumina nanoparticles (aluminaNPs), which are widely used in a range of daily and medical fields, have been shown to penetrate blood-brain barrier, and distribute and accumulate in different brain areas. Although oral treatment of aluminaNPs induces hippocampus-dependent learning and memory impairments, characteristic effects and exact mechanisms have not been fully elucidated. Here, male adult rats received a single bilateral infusion of aluminaNPs (10 or 20 µg/kg of body weight) into the hippocampal region, and their behavioral performance and neural function were assessed.

Results

The results indicated that the intra-hippocampus infusions at both doses of aluminaNPs did not cause spatial learning inability but memory deficit in the water maze task. This impairment was attributed to the effects of aluminaNP on memory consolidation phase through activation of proBDNF/RhoA pathway. Inhibition of the increased proBDNF by hippocampal infusions of p75^NTR antagonist could effectively rescue the memory impairment. Incubation of aluminaNPs exaggerated GluN2B-dependent LTD induction with no effects on LTD expression in hippocampal slices. AluminaNP could also depress the amplitude of NMDA-GluN2B EPSCs. Meanwhile, increased reactive oxygen specie production was reduced by blocking proBDNF-p75^NTR pathway in the hippocampal homogenates. Furthermore, the neuronal correlate of memory behavior was drastically weakened in the aluminaNP-infused groups. The dysfunction of synaptic and neuronal could be obviously mitigated by blocking proBDNF receptor p75^NTR, implying the involvement of proBDNF signaling in aluminaNP-impaired memory process.

Conclusions

Taken together, our findings provide the first evidence that the accumulation of aluminaNPs in the hippocampus exaggeratedly activates proBDNF signaling, which leads to neural and memory impairments.

Inhibition allocates spikes during hippocampal ripples

Sets of spikes emitted sequentially across neurons constitute fundamental pulse packets in neural information processing, including offline memory replay during hippocampal sharp-wave ripples (SWRs). The relative timing of neuronal spikes is fine-tuned in each spike sequence but can vary between different sequences. However, the microcircuitry mechanism that enables such flexible spike sequencing remains unexplored. We recorded the membrane potentials of multiple hippocampal CA1 pyramidal cells in mice and found that the neurons were transiently hyperpolarized prior to SWRs. The pre-SWR hyperpolarizations were spatiotemporally heterogeneous, and larger hyperpolarizations were associated with later spikes during SWRs. Intracellular blockade of Cl--mediated inhibition reduced pre-SWR hyperpolarizations and advanced spike times. Single-unit recordings also revealed that the pre-SWR firing rates of inhibitory interneurons predicted the SWR-relevant spike times of pyramidal cells. Thus, pre-SWR inhibitory activity determines the sequential spike times of pyramidal cells and diversifies the repertoire of sequence patterns.

Local feedback inhibition tightly controls rapid formation of hippocampal place fields

Hippocampal place cells underlie spatial navigation and memory. Remarkably, CA1 pyramidal neurons can form new place fields within a single trial by undergoing rapid plasticity. However, local feedback circuits likely restrict the rapid recruitment of individual neurons into ensemble representations. This interaction between circuit dynamics and rapid feature coding remains unexplored. Here, we developed "all-optical" approaches combining novel optogenetic induction of rapidly forming place fields with 2-photon activity imaging during spatial navigation in mice. We find that induction efficacy depends strongly on the density of co-activated neurons. Place fields can be reliably induced in single cells, but induction fails during co-activation of larger subpopulations due to local circuit constraints imposed by recurrent inhibition. Temporary relief of local inhibition permits the simultaneous induction of place fields in larger ensembles. We demonstrate the behavioral implications of these dynamics, showing that our ensemble place field induction protocol can enhance subsequent spatial association learning.

Extrinsic control and intrinsic computation in the hippocampal CA1 circuit

In understanding circuit operations, a key problem is the extent to which neuronal spiking reflects local computation or responses to upstream inputs. We addressed this issue in the hippocampus by performing combined optogenetic and pharmacogenetic local and upstream inactivation. Silencing the medial entorhinal cortex (mEC) largely abolished extracellular theta and gamma currents in CA1 while only moderately affecting firing rates. In contrast, CA3 and local CA1 silencing strongly decreased firing of CA1 neurons without affecting theta currents. Each perturbation reconfigured the CA1 spatial map. However, the ability of the CA1 circuit to support place field activity persisted, maintaining the same fraction of spatially tuned place fields and reliable assembly expression as in the intact mouse. Thus, the CA1 network can induce and maintain coordinated cell assemblies with minimal reliance on its inputs, but these inputs can effectively reconfigure and assist in maintaining stability of the CA1 map.

Probing subthreshold dynamics of hippocampal neurons by pulsed optogenetics

Understanding how excitatory (E) and inhibitory (I) inputs are integrated by neurons requires monitoring their subthreshold behavior. We probed the subthreshold dynamics using optogenetic depolarizing pulses in hippocampal neuronal assemblies in freely moving mice. Excitability decreased during sharp-wave ripples coupled with increased I. In contrast to this "negative gain," optogenetic probing showed increased within-field excitability in place cells by weakening I and unmasked stable place fields in initially non-place cells. Neuronal assemblies active during sharp-wave ripples in the home cage predicted spatial overlap and sequences of place fields of both place cells and unmasked preexisting place fields of non-place cells during track running. Thus, indirect probing of subthreshold dynamics in neuronal populations permits the disclosing of preexisting assemblies and modes of neuronal operations.

Behind the scenes: Are latent memories supported by calcium independent plasticity?

N-methyl-D-aspartate receptors (NMDARs) can be considered to be the de facto "plasticity" receptors in the brain due to their central role in the activity-dependent modification of neuronal morphology and synaptic transmission. Since the 1980s, research on NMDARs has focused on the second messenger properties of calcium and the downstream signaling pathways that mediate alterations in neural form and function. Recently, NMDARs were shown to drive activity-dependent synaptic plasticity without calcium influx. How this "nonionotropic" plasticity occurs in vitro is becoming clearer, but research on its involvement in behavior and cognition is in its infancy. There is a partial overlap in the downstream signaling molecules that are involved in ionotropic and nonionotropic NMDAR-dependent plasticity. Given this, and prior studies of the cognitive impacts of ionotropic NMDAR plasticity, a preliminary model explaining how NMDAR nonionotropic plasticity affects learning and memory can be established. We hypothesize that nonionotropic NMDAR plasticity takes part in latent memory encoding in immature rodents through nonassociative depression of synaptic efficacy, and possibly shrinking of dendritic spines. Further, the late postnatal alteration in NMDAR composition in the hippocampus appears to reduce nonionotropic signaling and remove a restriction on memory retrieval. This framework substantially alters the canonical model of NMDAR involvement in spatial cognition and hippocampal maturation and provides novel and exciting inroads for future studies.

Edges in brain networks: Contributions to models of structure and function

Network models describe the brain as sets of nodes and edges that represent its distributed organization. So far, most discoveries in network neuroscience have prioritized insights that highlight distinct groupings and specialized functional contributions of network nodes. Importantly, these functional contributions are determined and expressed by the web of their interrelationships, formed by network edges. Here, we underscore the important contributions made by brain network edges for understanding distributed brain organization. Different types of edges represent different types of relationships, including connectivity and similarity among nodes. Adopting a specific definition of edges can fundamentally alter how we analyze and interpret a brain network. Furthermore, edges can associate into collectives and higher order arrangements, describe time series, and form edge communities that provide insights into brain network topology complementary to the traditional node-centric perspective. Focusing on the edges, and the higher order or dynamic information they can provide, discloses previously underappreciated aspects of structural and functional network organization.

Neurophysiology of Remembering

By linking the past with the future, our memories define our sense of identity. Because human memory engages the conscious realm, its examination has historically been approached from language and introspection and proceeded largely along separate parallel paths in humans and other animals. Here, we first highlight the achievements and limitations of this mind-based approach and make the case for a new brain-based understanding of declarative memory with a focus on hippocampal physiology. Next, we discuss the interleaved nature and common physiological mechanisms of navigation in real and mental spacetime. We suggest that a distinguishing feature of memory types is whether they subserve actions for single or multiple uses. Finally, in contrast to the persisting view of the mind as a highly plastic blank slate ready for the world to make its imprint, we hypothesize that neuronal networks are endowed with a reservoir of neural trajectories, and the challenge faced by the brain is how to select and match preexisting neuronal trajectories with events in the world.

The Hippocampal Horizon: Constructing and Segmenting Experience for Episodic Memory

How do we recollect specific events that have occurred during continuous ongoing experience? There is converging evidence from non-human animals that spatially modulated cellular activity of the hippocampal formation supports the construction of ongoing events. On the other hand, recent human oriented event cognition models have outlined that our experience is segmented into discrete units, and that such segmentation can operate on shorter or longer timescales. Here, we describe a unification of how these dynamic physiological mechanisms of the hippocampus relate to ongoing externally and internally driven event segmentation, facilitating the demarcation of specific moments during experience. Our cross-species interdisciplinary approach offers a novel perspective in the way we construct and remember specific events, leading to the generation of many new hypotheses for future research.

Excitatory-inhibitory balance modulates the formation and dynamics of neuronal assemblies in cortical networks

Repetitive activation of subpopulations of neurons leads to the formation of neuronal assemblies, which can guide learning and behavior. Recent technological advances have made the artificial induction of these assemblies feasible, yet how various parameters of induction can be optimized is not clear. Here, we studied this question in large-scale cortical network models with excitatory-inhibitory balance. We found that the background network in which assemblies are embedded can strongly modulate their dynamics and formation. Networks with dominant excitatory interactions enabled a fast formation of assemblies, but this was accompanied by recruitment of other non-perturbed neurons, leading to some degree of nonspecific induction. On the other hand, networks with strong excitatory-inhibitory interactions ensured that the formation of assemblies remained constrained to the perturbed neurons, but slowed down the induction. Our results suggest that these two regimes can be suitable for computational and cognitive tasks with different trade-offs between speed and specificity.

Rapid synaptic plasticity contributes to a learned conjunctive code of position and choice-related information in the hippocampus

To successfully perform goal-directed navigation, animals must know where they are and what they are doing-e.g., looking for water, bringing food back to the nest, or escaping from a predator. Hippocampal neurons code for these critical variables conjunctively, but little is known about how this "where/what" code is formed or flexibly routed to other brain regions. To address these questions, we performed intracellular whole-cell recordings in mouse CA1 during a cued, two-choice virtual navigation task. We demonstrate that plateau potentials in CA1 pyramidal neurons rapidly strengthen synaptic inputs carrying conjunctive information about position and choice. Plasticity-induced response fields were modulated by cues only in animals previously trained to collect rewards based on available cues. Thus, we reveal that gradual learning is required for the formation of a conjunctive population code, upstream of CA1, while plateau-potential-induced synaptic plasticity in CA1 enables flexible routing of the code to downstream brain regions.

Between-subject prediction reveals a shared representational geometry in the rodent hippocampus

The rodent hippocampus constructs statistically independent representations across environments ("global remapping") and assigns individual neuron firing fields to locations within an environment in an apparently random fashion, processes thought to contribute to the role of the hippocampus in episodic memory. This random mapping implies that it should be challenging to predict hippocampal encoding of a given experience in one subject based on the encoding of that same experience in another subject. Contrary to this prediction, we find that by constructing a common representational space across rats in which neural activity is aligned using geometric operations (rotation, reflection, and translation; "hyperalignment"), we can predict data of "right" trials (R) on a T-maze in a target rat based on (1) the "left" trials (L) of the target rat and (2) the relationship between L and R trials from a different source rat. These cross-subject predictions relied on ensemble activity patterns, including both firing rate and field location, and outperformed a number of control mappings, such as those based on permuted data that broke the relationship between L and R activity for individual neurons and those based solely on within-subject prediction. This work constitutes proof of principle for successful cross-subject prediction of ensemble activity patterns in the hippocampus and provides new insights in understanding how different experiences are structured, enabling further work identifying what aspects of experience encoding are shared versus unique to an individual.

Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations

Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms - including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity - towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.

Spatial information transfer in hippocampal place cells depends on trial-to-trial variability, symmetry of place-field firing, and biophysical heterogeneities

The relationship between the feature-tuning curve and information transfer profile of individual neurons provides vital insights about neural encoding. However, the relationship between the spatial tuning curve and spatial information transfer of hippocampal place cells remains unexplored. Here, employing a stochastic search procedure spanning thousands of models, we arrived at 127 conductance-based place-cell models that exhibited signature electrophysiological characteristics and sharp spatial tuning, with parametric values that exhibited neither clustering nor strong pairwise correlations. We introduced trial-to-trial variability in responses and computed model tuning curves and information transfer profiles, using stimulus-specific (SSI) and mutual (MI) information metrics, across locations within the place field. We found spatial information transfer to be heterogeneous across models, but to reduce consistently with increasing levels of variability. Importantly, whereas reliable low-variability responses implied that maximal information transfer occurred at high-slope regions of the tuning curve, increase in variability resulted in maximal transfer occurring at the peak-firing location in a subset of models. Moreover, experience-dependent asymmetry in place-field firing introduced asymmetries in the information transfer computed through MI, but not SSI, and the impact of activity-dependent variability on information transfer was minimal compared to activity-independent variability. We unveiled ion-channel degeneracy in the regulation of spatial information transfer, and demonstrated critical roles for N-methyl-d-aspartate receptors, transient potassium and dendritic sodium channels in regulating information transfer. Our results demonstrate that trial-to-trial variability, tuning-curve shape and biological heterogeneities critically regulate the relationship between the spatial tuning curve and spatial information transfer in hippocampal place cells.

Neuronal ensembles in memory processes

A neuronal ensemble represents the concomitant activity of a specific group of neurons that could encompass a broad repertoire of brain functions such as motor, perceptual, memory or cognitive states. On the other hand, a memory engram portrays the physical manifestation of memory or the changes that enable learning and retrieval. Engram studies focused for many years on finding where memories are stored as in, which cells or brain regions represent a memory trace, and disregarded the investigation of how neuronal activity patterns give rise to such memories. Recent experiments suggest that the association and reactivation of specific neuronal groups could be the main mechanism underlying the brain's ability to remember past experiences and envision future actions. Thus, the growing consensus is that the interaction between neuronal ensembles could allow sequential activity patterns to become memories and recurrent memories to compose complex behaviors. The goal of this review is to propose how the neuronal ensemble framework could be translated and useful to understand memory processes.

Shining a light on hippocampal remapping

In this issue of Neuron, McKenzie et al. (2021) test the degree to which pre-existing biases in hippocampal circuits constrict the encoding of new information via artificial induction of place cell remapping. Their results suggest that the hippocampal spatial map encodes new information via pre-existing latent place fields.

Behavioral Time Scale Plasticity of Place Fields: Mathematical Analysis

Traditional synaptic plasticity experiments and models depend on tight temporal correlations between pre- and postsynaptic activity. These tight temporal correlations, on the order of tens of milliseconds, are incompatible with significantly longer behavioral time scales, and as such might not be able to account for plasticity induced by behavior. Indeed, recent findings in hippocampus suggest that rapid, bidirectional synaptic plasticity which modifies place fields in CA1 operates at behavioral time scales. These experimental results suggest that presynaptic activity generates synaptic eligibility traces both for potentiation and depression, which last on the order of seconds. These traces can be converted to changes in synaptic efficacies by the activation of an instructive signal that depends on naturally occurring or experimentally induced plateau potentials. We have developed a simple mathematical model that is consistent with these observations. This model can be fully analyzed to find the fixed points of induced place fields and how these fixed points depend on system parameters such as the size and shape of presynaptic place fields, the animal's velocity during induction, and the parameters of the plasticity rule. We also make predictions about the convergence time to these fixed points, both for induced and pre-existing place fields.