Flexible theta sequence compression mediated via phase precessing interneurons

Distinct roles of dentate gyrus and medial entorhinal cortex inputs for phase precession and temporal correlations in the hippocampal CA3 area

The hippocampal CA3 subregion is a densely connected recurrent circuit that supports memory by generating and storing sequential neuronal activity patterns that reflect recent experience. While theta phase precession is thought to be critical for generating sequential activity during memory encoding, the circuit mechanisms that support this computation across hippocampal subregions are unknown. By analyzing CA3 network activity in the absence of each of its theta-modulated external excitatory inputs, we show necessary and unique contributions of the dentate gyrus (DG) and the medial entorhinal cortex (MEC) to phase precession. DG inputs are essential for preferential spiking of CA3 cells during late theta phases and for organizing the temporal order of neuronal firing, while MEC inputs sharpen the temporal precision throughout the theta cycle. A computational model that accounts for empirical findings suggests that the unique contribution of DG inputs to theta-related spike timing is supported by targeting precisely timed inhibitory oscillations. Our results thus identify a novel and unique functional role of the DG for sequence coding in the CA3 circuit.

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.

Significance Statement

Fragile X Syndrome (FXS) is a neurodevelopmental disorder that can cause impaired memory and atypical spatial behaviors such as "elopement" (i.e., wandering off and becoming lost). Activity in the CA1 subregion of the hippocampus supports spatial memory and spatial cognition, making it an important candidate to study in the context of FXS; however, how neuronal population activity in CA1 is affected by FXS is poorly understood. In this study, we found that the coordination of populations of CA1 neurons during active behavior and waking rest was impaired in a rat model of FXS. These results reveal hippocampal physiological deficits that may contribute to cognitive impairments in FXS.

Hippocampal cholecystokinin-expressing interneurons regulate temporal coding and contextual learning

Cholecystokinin-expressing interneurons (CCKIs) are hypothesized to shape pyramidal cell-firing patterns and regulate network oscillations and related network state transitions. To directly probe their role in the CA1 region, we silenced their activity using optogenetic and chemogenetic tools in mice. Opto-tagged CCKIs revealed a heterogeneous population, and their optogenetic silencing triggered wide disinhibitory network changes affecting both pyramidal cells and other interneurons. CCKI silencing enhanced pyramidal cell burst firing and altered the temporal coding of place cells: theta phase precession was disrupted, whereas sequence reactivation was enhanced. Chemogenetic CCKI silencing did not alter the acquisition of spatial reference memories on the Morris water maze but enhanced the recall of contextual fear memories and enabled selective recall when similar environments were tested. This work suggests the key involvement of CCKIs in the control of place-cell temporal coding and the formation of contextual memories.

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.

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.

Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics

During spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during 'offline' resting periods, brief neuronal population bursts can 'replay' sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity and spike rate adaptation, as well as associative synaptic connectivity, enable additional emergent properties, including variable offline memory replay. In an online stimulus-driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behaviour. KEY POINTS: A recurrent spiking network model of hippocampal area CA3 was optimized to recapitulate experimentally observed network dynamics during simulated spatial exploration. During simulated offline rest, the network exhibited the emergent property of generating flexible forward, reverse and mixed direction memory replay events. Network perturbations and analysis of model diversity and degeneracy identified associative synaptic connectivity and key features of network dynamics as important for offline sequence generation. Network simulations demonstrate that population over-representation of salient positions like the site of reward results in biased memory replay.

Computational models for state-dependent traveling waves in hippocampal formation

Hippocampal theta (4-10 Hz) oscillations have been identified as traveling waves in both rodents and humans. In freely foraging rodents, the theta traveling wave is a planar wave propagating from the dorsal to ventral hippocampus along the septotemporal axis. Motivated from experimental findings, we develop a spiking neural network of excitatory and inhibitory neurons to generate state-dependent hippocampal traveling waves to improve current mechanistic understanding of propagating waves. Model simulations demonstrate the necessary conditions for generating wave propagation and characterize the traveling wave properties with respect to model parameters, running speed and brain state of the animal. Networks with long-range inhibitory connections are more suitable than networks with long-range excitatory connections. We further generalize the spiking neural network to model traveling waves in the medial entorhinal cortex (MEC) and predict that traveling theta waves in the hippocampus and entorhinal cortex are in sink.

Hippocampal Sequencing Mechanisms Are Disrupted in a Maternal Immune Activation Model of Schizophrenia Risk

Episodic memory requires information to be stored and recalled in sequential order, and these processes are disrupted in schizophrenia. Hippocampal phase precession and theta sequences are thought to provide a biological mechanism for sequential ordering of experience at timescales suitable for plasticity. These phenomena have not previously been examined in any models of schizophrenia risk. Here, we examine these phenomena in a maternal immune activation (MIA) rodent model. We show that while individual pyramidal cells in the CA1 region continue to precess normally in MIA animals, the starting phase of precession as an animal enters a new place field is considerably more variable in MIA animals than in controls. A critical consequence of this change is a disorganization of the ordered representation of experience via theta sequences. These results provide the first evidence of a biological-level mechanism that, if it occurs in schizophrenia, may explain aspects of disorganized sequential processing that contribute to the cognitive symptoms of the disorder.SIGNIFICANCE STATEMENT Hippocampal phase precession and theta sequences have been proposed as biophysical mechanisms by which the sequential structure of cognition might be ordered. Disturbances of sequential processing have frequently been observed in schizophrenia. Here, we show for the first time that phase precession and theta sequences are disrupted in a maternal immune activation (MIA) model of schizophrenia risk. This is a result of greater variability in the starting phase of precession, indicating that the mechanisms that coordinate precession at the assembly level are disrupted. We propose that this disturbance in phase precession underlies some of the disorganized cognitive symptoms that occur in schizophrenia. These findings could have important preclinical significance for the identification and treatment of schizophrenia risk factors.

Synaptic learning rules for sequence learning

Remembering the temporal order of a sequence of events is a task easily performed by humans in everyday life, but the underlying neuronal mechanisms are unclear. This problem is particularly intriguing as human behavior often proceeds on a time scale of seconds, which is in stark contrast to the much faster millisecond time-scale of neuronal processing in our brains. One long-held hypothesis in sequence learning suggests that a particular temporal fine-structure of neuronal activity - termed 'phase precession' - enables the compression of slow behavioral sequences down to the fast time scale of the induction of synaptic plasticity. Using mathematical analysis and computer simulations, we find that - for short enough synaptic learning windows - phase precession can improve temporal-order learning tremendously and that the asymmetric part of the synaptic learning window is essential for temporal-order learning. To test these predictions, we suggest experiments that selectively alter phase precession or the learning window and evaluate memory of temporal order.

Alterations of Neuronal Dynamics as a Mechanism for Cognitive Impairment in Epilepsy

Epilepsy is commonly associated with cognitive and behavioral deficits that dramatically affect the quality of life of patients. In order to identify novel therapeutic strategies aimed at reducing these deficits, it is critical first to understand the mechanisms leading to cognitive impairments in epilepsy. Traditionally, seizures and epileptiform activity in addition to neuronal injury have been considered to be the most significant contributors to cognitive dysfunction. In this review we however highlight the role of a new mechanism: alterations of neuronal dynamics, i.e. the timing at which neurons and networks receive and process neural information. These alterations, caused by the underlying etiologies of epilepsy syndromes, are observed in both animal models and patients in the form of abnormal oscillation patterns in unit firing, local field potentials, and electroencephalogram (EEG). Evidence suggests that such mechanisms significantly contribute to cognitive impairment in epilepsy, independently of seizures and interictal epileptiform activity. Therefore, therapeutic strategies directly targeting neuronal dynamics rather than seizure reduction may significantly benefit the quality of life of patients.

Efficient phase coding in hippocampal place cells

Neural codes have been postulated to build efficient representations of the external world. The hippocampus, an encoding system, employs neuronal firing rates and spike phases to encode external space. Although the biophysical origin of such codes is at a single neuronal level, the role of neural components in efficient coding is not understood. The complexity of this problem lies in the dimensionality of the parametric space encompassing neural components, and is amplified by the enormous biological heterogeneity observed in each parameter. A central question that spans encoding systems therefore is how neurons arrive at efficient codes in the face of widespread biological heterogeneities. To answer this, we developed a conductance-based spiking model for phase precession, a phase code of external space exhibited by hippocampal place cells. Our model accounted for several experimental observations on place cell firing and electrophysiology: the emergence of phase precession from exact spike timings of conductance-based models with neuron-specific ion channels and receptors; biological heterogeneities in neural components and excitability; the emergence of subthreshold voltage ramp, increased firing rate, enhanced theta power within the place field; a signature reduction in extracellular theta frequency compared to its intracellular counterpart; and experience-dependent asymmetry in firing-rate profile. We formulated phase-coding efficiency, using Shannon's information theory, as an information maximization problem with spike phase as the response and external space within a single place field as the stimulus. We employed an unbiased stochastic search spanning an 11-dimensional neural space, involving thousands of iterations that accounted for the biophysical richness and neuron-to-neuron heterogeneities. We found a small subset of models that exhibited efficient spatial information transfer through the phase code, and investigated the distinguishing features of this subpopulation at the parametric and functional scales. At the parametric scale, which spans the molecular components that defined the neuron, several nonunique parametric combinations with weak pairwise correlations yielded models with similar high phase-coding efficiency. Importantly, placing additional constraints on these models in terms of matching other aspects of hippocampal neural responses did not hamper parametric degeneracy. We provide quantitative evidence demonstrating this parametric degeneracy to be a consequence of a many-to-one relationship between the different parameters and phase-coding efficiency. At the functional scale, involving the cellular-scale neural properties, our analyses revealed an important higher-order constraint that was exclusive to models exhibiting efficient phase coding. Specifically, we found a counterbalancing negative correlation between neuronal gain and the strength of external synaptic inputs as a critical functional constraint for the emergence of efficient phase coding. These observations implicate intrinsic neural properties as important contributors in effectuating such counterbalance, which can be achieved by recruiting nonunique parametric combinations. Finally, we show that a change in afferent statistics, manifesting as input asymmetry onto these neuronal models, induced an adaptive shift in the phase code that preserved its efficiency. Together, our analyses unveil parametric degeneracy as a mechanism to harness widespread neuron-to-neuron heterogeneity towards accomplishing stable and efficient encoding, provided specific higher-order functional constraints on the relationship of neural gain to external inputs are satisfied.

Cooling of Medial Septum Reveals Theta Phase Lag Coordination of Hippocampal Cell Assemblies

Hippocampal theta oscillations coordinate neuronal firing to support memory and spatial navigation. The medial septum (MS) is critical in theta generation by two possible mechanisms: either a unitary "pacemaker" timing signal is imposed on the hippocampal system, or it may assist in organizing target subcircuits within the phase space of theta oscillations. We used temperature manipulation of the MS to test these models. Cooling of the MS reduced both theta frequency and power and was associated with an enhanced incidence of errors in a spatial navigation task, but it did not affect spatial correlates of neurons. MS cooling decreased theta frequency oscillations of place cells and reduced distance-time compression but preserved distance-phase compression of place field sequences within the theta cycle. Thus, the septum is critical for sustaining precise theta phase coordination of cell assemblies in the hippocampal system, a mechanism needed for spatial memory.

Constant Sub-second Cycling between Representations of Possible Futures in the Hippocampus

Cognitive faculties such as imagination, planning, and decision-making entail the ability to represent hypothetical experience. Crucially, animal behavior in natural settings implies that the brain can represent hypothetical future experience not only quickly but also constantly over time, as external events continually unfold. To determine how this is possible, we recorded neural activity in the hippocampus of rats navigating a maze with multiple spatial paths. We found neural activity encoding two possible future scenarios (two upcoming maze paths) in constant alternation at 8 Hz: one scenario per ∼125-ms cycle. Further, we found that the underlying dynamics of cycling (both inter- and intra-cycle dynamics) generalized across qualitatively different representational correlates (location and direction). Notably, cycling occurred across moving behaviors, including during running. These findings identify a general dynamic process capable of quickly and continually representing hypothetical experience, including that of multiple possible futures.

Characterizing Speed Cells in the Rat Hippocampus

Spatial navigation relies on visual landmarks as well as on self-motion information. In familiar environments, both place and grid cells maintain their firing fields in darkness, suggesting that they continuously receive information about locomotion speed required for path integration. Consistently, "speed cells" have been previously identified in the hippocampal formation and characterized in detail in the medial entorhinal cortex. Here we investigated speed-correlated firing in the hippocampus. We show that CA1 has speed cells that are stable across contexts, position in space, and time. Moreover, their speed-correlated firing occurs within theta cycles, independently of theta frequency. Interestingly, a physiological classification of cell types reveals that all CA1 speed cells are inhibitory. In fact, while speed modulates pyramidal cell activity, only the firing rate of interneurons can accurately predict locomotion speed on a sub-second timescale. These findings shed light on network models of navigation.

Hippocampal Sequences During Exploration: Mechanisms and Functions

Although the hippocampus plays a critical role in spatial and episodic memories, the mechanisms underlying memory formation, stabilization, and recall for adaptive behavior remain relatively unknown. During exploration, within single cycles of the ongoing theta rhythm that dominates hippocampal local field potentials, place cells form precisely ordered sequences of activity. These neural sequences result from the integration of both external inputs conveying sensory-motor information, and intrinsic network dynamics possibly related to memory processes. Their endogenous replay during subsequent sleep is critical for memory consolidation. The present review discusses possible mechanisms and functions of hippocampal theta sequences during exploration. We present several lines of evidence suggesting that these neural sequences play a key role in information processing and support the formation of initial memory traces, and discuss potential functional distinctions between neural sequences emerging during theta vs. awake sharp-wave ripples.

Synaptic integrative mechanisms for spatial cognition

Synaptic integrative mechanisms have profound effects on electrical signaling in the brain that, although largely hidden from recording methods that observe the spiking activity of neurons, may be critical for the encoding, storage and retrieval of information. Here we review roles for synaptic integrative mechanisms in the selection, generation and plasticity of place and grid fields, and in related temporal codes for the representation of space. We outline outstanding questions and challenges in the testing of hypothesized models for spatial computation and memory.

Combining Theory, Model, and Experiment to Explain How Intrinsic Theta Rhythms Are Generated in an In Vitro Whole Hippocampus Preparation without Oscillatory Inputs

Scientists have observed local field potential theta rhythms (3-12 Hz) in the hippocampus for decades, but understanding the mechanisms underlying their generation is complicated by their diversity in pharmacological and frequency profiles. In addition, interactions with other brain structures and oscillatory drives to the hippocampus during distinct brain states has made it difficult to identify hippocampus-specific properties directly involved in theta generation. To overcome this, we develop cellular-based network models using a whole hippocampus in vitro preparation that spontaneously generates theta rhythms. Building on theoretical and computational analyses, we find that spike frequency adaptation and postinhibitory rebound constitute a basis for theta generation in large, minimally connected CA1 pyramidal (PYR) cell network models with fast-firing parvalbumin-positive (PV⁺) inhibitory cells. Sparse firing of PYR cells and large excitatory currents onto PV⁺ cells are present as in experiments. The particular theta frequency is more controlled by PYR-to-PV⁺ cell interactions rather than PV⁺-to-PYR cell interactions. We identify two scenarios by which theta rhythms can emerge, and they can be differentiated by the ratio of excitatory to inhibitory currents to PV⁺ cells, but not to PYR cells. Only one of the scenarios is consistent with data from the whole hippocampus preparation, which leads to the prediction that the connection probability from PV⁺ to PYR cells needs to be larger than from PYR to PV⁺ cells. Our models can serve as a platform on which to build and develop an understanding of in vivo theta generation.