Phase Precession Research Articles

Theta phase precession supports memory formation and retrieval of naturalistic experience in humans.

Associating different aspects of experience with discrete events is critical for human memory. A potential mechanism for linking memory components is phase precession, during which neurons fire progressively earlier in time relative to theta oscillations. However, no direct link between phase precession and memory has been established. Here we recorded single-neuron activity and local field potentials in the human medial temporal lobe while participants (n = 22) encoded and retrieved memories of movie clips. Bouts of theta and phase precession occurred following cognitive boundaries during movie watching and following stimulus onsets during memory retrieval. Phase precession was dynamic, with different neurons exhibiting precession in different task periods. Phase precession strength provided information about memory encoding and retrieval success that was complementary with firing rates. These data provide direct neural evidence for a functional role of phase precession in human episodic memory.

Firing rate adaptation affords place cell theta sweeps, phase precession, and procession

Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here, we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between ‘bimodal cells’ showing interleaved phase precession and procession, and ‘unimodal cells’ in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells’ firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.

Firing rate adaptation affords place cell theta sweeps, phase precession, and procession.

Hippocampal place cells in freely moving rodents display both theta phase precession and procession, which is thought to play important roles in cognition, but the neural mechanism for producing theta phase shift remains largely unknown. Here, we show that firing rate adaptation within a continuous attractor neural network causes the neural activity bump to oscillate around the external input, resembling theta sweeps of decoded position during locomotion. These forward and backward sweeps naturally account for theta phase precession and procession of individual neurons, respectively. By tuning the adaptation strength, our model explains the difference between 'bimodal cells' showing interleaved phase precession and procession, and 'unimodal cells' in which phase precession predominates. Our model also explains the constant cycling of theta sweeps along different arms in a T-maze environment, the speed modulation of place cells' firing frequency, and the continued phase shift after transient silencing of the hippocampus. We hope that this study will aid an understanding of the neural mechanism supporting theta phase coding in the brain.

Segmenting and Predicting Musical Phrase Structure Exploits Neural Gain Modulation and Phase Precession.

Music, like spoken language, is often characterized by hierarchically organized structure. Previous experiments have shown neural tracking of notes and beats, but little work touches on the more abstract question: how does the brain establish high-level musical structures in real time? We presented Bach chorales to participants (20 females and 9 males) undergoing electroencephalogram (EEG) recording to investigate how the brain tracks musical phrases. We removed the main temporal cues to phrasal structures, so that listeners could only rely on harmonic information to parse a continuous musical stream. Phrasal structures were disrupted by locally or globally reversing the harmonic progression, so that our observations on the original music could be controlled and compared. We first replicated the findings on neural tracking of musical notes and beats, substantiating the positive correlation between musical training and neural tracking. Critically, we discovered a neural signature in the frequency range ∼0.1 Hz (modulations of EEG power) that reliably tracks musical phrasal structure. Next, we developed an approach to quantify the phrasal phase precession of the EEG power, revealing that phrase tracking is indeed an operation of active segmentation involving predictive processes. We demonstrate that the brain establishes complex musical structures online over long timescales (>5 s) and actively segments continuous music streams in a manner comparable to language processing. These two neural signatures, phrase tracking and phrasal phase precession, provide new conceptual and technical tools to study the processes underpinning high-level structure building using noninvasive recording techniques.

Predictive sequence learning in the hippocampal formation

The hippocampus receives sequences of sensory inputs from the cortex during exploration and encodes the sequences with millisecond precision. We developed a predictive autoencoder model of the hippocampus including the trisynaptic and monosynaptic circuits from the entorhinal cortex (EC). CA3 was trained as a self-supervised recurrent neural network to predict its next input. We confirmed that CA3 is predicting ahead by analyzing the spike coupling between simultaneously recorded neurons in the dentate gyrus, CA3, and CA1 of the mouse hippocampus. In the model, CA1 neurons signal prediction errors by comparing CA3 predictions to the next direct EC input. The model exhibits the rapid appearance and slow fading of CA1 place cells and displays replay and phase precession from CA3. The model could be learned in a biologically plausible way with error-encoding neurons. Similarities between the hippocampal and thalamocortical circuits suggest that such computation motif could also underlie self-supervised sequence learning in the cortex.

Theta Phase Precession and the Dynamics of Spatiotemporal Asymmetry in Hippocampal Place Fields

A consistently observed characteristic of hippocampal place fields is the shifting of the field's center of mass and the subsequent development of asymmetry. This is evidenced by the expansion of the place field in an asymmetric manner over repeated traversals, wherein a rat's initial entry into the field prompts a low firing rate that substantially increases as it exits. Our study delves deeper into these spatiotemporal asymmetries of place field spiking, specifically examining their relationship with theta oscillations and disentangling the effects from environmental factors. Analysis of neuronal data from a T-maze alternation task revealed a distinct non-uniform firing pattern of place cells. This pattern was markedly skewed in relation to the phases of theta cycles, indicating a phase precession effect. We found that as the rat navigates through the place field, there is a systematic advancement of spike timing, with action potentials tending to cluster in the early phases of theta during the exit phase of the field. Such temporal coordination of spikes suggests that the timing of neural activity within theta cycles is as integral as spatial location, influencing the dynamics of place field expansion and potentially affecting the hippocampal local field potential. This discovery underscores the role of theta phase precession in spatial encoding, proposing a novel temporal component that could underpin the cognitive map within the hippocampus. R01 MH126236 R01 AG055544. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

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.

Induced neural phase precession through exogenous electric fields

The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.

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.

Algebraic approach to spike-time neural codes in the hippocampus.

Although temporal coding through spike-time patterns has long been of interest in neuroscience, the specific structures that could be useful for spike-time codes remain highly unclear. Here, we introduce an analytical approach, using techniques from discrete mathematics, to study spike-time codes. As an initial example, we focus on the phenomenon of "phase precession" in the rodent hippocampus. During navigation and learning on a physical track, specific cells in a rodent's brain form a highly structured pattern relative to the oscillation of population activity in this region. Studies of phase precession largely focus on its role in precisely ordering spike times for synaptic plasticity, as the role of phase precession in memory formation is well established. Comparatively less attention has been paid to the fact that phase precession represents one of the best candidates for a spike-time neural code. The precise nature of this code remains an open question. Here, we derive an analytical expression for a function mapping points in physical space to complex-valued spikes by representing individual spike times as complex numbers. The properties of this function make explicit a specific relationship between past and future in spike patterns of the hippocampus. Importantly, this mathematical approach generalizes beyond the specific phenomenon studied here, providing a technique to study the neural codes within precise spike-time sequences found during sensory coding and motor behavior. We then introduce a spike-based decoding algorithm, based on this function, that successfully decodes a simulated animal's trajectory using only the animal's initial position and a pattern of spike times. This decoder is robust to noise in spike times and works on a timescale almost an order of magnitude shorter than typically used with decoders that work on average firing rate. These results illustrate the utility of a discrete approach, based on the structure and symmetries in spike patterns across finite sets of cells, to provide insight into the structure and function of neural systems.

Positive and biphasic extracellular waveforms correspond to return currents and axonal spikes

Multiple biophysical mechanisms may generate non-negative extracellular waveforms during action potentials, but the origin and prevalence of positive spikes and biphasic spikes in the intact brain are unknown. Using extracellular recordings from densely-connected cortical networks in freely-moving mice, we find that a tenth of the waveforms are non-negative. Positive phases of non-negative spikes occur in synchrony or just before wider same-unit negative spikes. Narrow positive spikes occur in isolation in the white matter. Isolated biphasic spikes are narrower than negative spikes, occurring right after spikes of verified inhibitory units. In CA1, units with dominant non-negative spikes exhibit place fields, phase precession, and phase-locking to ripples. Thus, near-somatic narrow positive extracellular potentials correspond to return currents, and isolated non-negative spikes correspond to axonal potentials. Identifying non-negative extracellular waveforms that correspond to non-somatic compartments during spikes can enhance the understanding of physiological and pathological neural mechanisms in intact animals.

Simulations predict differing phase responses to excitation vs. inhibition in theta-resonant pyramidal neurons.

Rhythmic activity is ubiquitous in neural systems, with theta-resonant pyramidal neurons integrating rhythmic inputs in many cortical structures. Impedance analysis has been widely used to examine frequency-dependent responses of neuronal membranes to rhythmic inputs, but it assumes that the neuronal membrane is a linear system, requiring the use of small signals to stay in a near-linear regime. However, postsynaptic potentials are often large and trigger nonlinear mechanisms (voltage-gated ion channels). The goals of this work were to 1) develop an analysis method to evaluate membrane responses in this nonlinear domain and 2) explore phase relationships between rhythmic stimuli and subthreshold and spiking membrane potential (Vmemb) responses in models of theta-resonant pyramidal neurons. Responses in these output regimes were asymmetrical, with different phase shifts during hyperpolarizing and depolarizing half-cycles. Suprathreshold theta-rhythmic stimuli produced nonstationary Vmemb responses. Sinusoidal inputs produced "phase retreat": action potentials occurred progressively later in cycles of the input stimulus, resulting from adaptation. Sinusoidal current with increasing amplitude over cycles produced "phase advance": action potentials occurred progressively earlier. Phase retreat, phase advance, and subthreshold phase shifts were modulated by multiple ion channel conductances. Our results suggest differential responses of cortical neurons depending on the frequency of oscillatory input, which will play a role in neuronal responses to shifts in network state. We hypothesize that intrinsic cellular properties complement network properties and contribute to in vivo phase-shift phenomena such as phase precession, seen in place and grid cells, and phase roll, also observed in hippocampal CA1 neurons.NEW & NOTEWORTHY We augmented electrical impedance analysis to characterize phase shifts between large-amplitude current stimuli and nonlinear, asymmetric membrane potential responses. We predict different frequency-dependent phase shifts in response excitation vs. inhibition, as well as shifts in spike timing over multiple input cycles, in theta-resonant pyramidal neurons. We hypothesize that these effects contribute to navigation-related phenomena such as phase precession and phase roll. Our neuron-level hypothesis complements, rather than falsifies, prior network-level explanations of these phenomena.

Theta and gamma rhythmic coding through two spike output modes in the hippocampus during spatial navigation

Hippocampal CA1 neurons generate single spikes and stereotyped bursts of spikes. However, it is unclear how individual neurons dynamically switch between these output modes and whether these two spiking outputs relay distinct information. We performed extracellular recordings in spatially navigating rats and cellular voltage imaging and optogenetics in awake mice. We found that spike bursts are preferentially linked to cellular and network theta rhythms (3-12Hz) and encode an animal's position via theta phase precession, particularly as animals are entering a place field. In contrast, single spikes exhibit additional coupling to gamma rhythms (30-100Hz), particularly as animals leave a place field. Biophysical modeling suggests that intracellular properties alone are sufficient to explain the observed input frequency-dependent spike coding. Thus, hippocampal neurons regulate the generation of bursts and single spikes according to frequency-specific network and intracellular dynamics, suggesting that these spiking modes perform distinct computations to support spatial behavior.

Hippocampal phase precession is preserved under ketamine, but the range of precession across a theta cycle is reduced.

Hippocampal phase precession, which depends on the precise spike timing of place cells relative to local theta oscillations, has been proposed to underlie sequential memory. N-methyl-D-asparate (NMDA) receptor antagonists such as ketamine disrupt memory and also reproduce several schizophrenia-like symptoms, including spatial memory impairments and disorganized cognition. It is possible that these impairments result from disruptions to phase precession. We used an ABA design to test whether an acute, subanesthetic dose (7.5 mg/kg) of ketamine disrupted phase precession in CA1 of male rats as they navigated around a rectangular track for a food reward. Ketamine did not affect the ability of CA1 place cells to precess despite changes to place cell firing rates, local field potential properties and locomotor speed. However, ketamine reduced the range of phase precession that occurred across a theta cycle. Phase precession is largely robust to acute NMDA receptor antagonism by ketamine, but the reduced range of precession could have important implications for learning and memory.

Homogeneous inhibition is optimal for the phase precession of place cells in the CA1 field.

Place cells are hippocampal neurons encoding the position of an animal in space. Studies of place cells are essential to understanding the processing of information by neural networks of the brain. An important characteristic of place cell spike trains is phase precession. When an animal is running through the place field, the discharges of the place cells shift from the ascending phase of the theta rhythm through the minimum to the descending phase. The role of excitatory inputs to pyramidal neurons along the Schaffer collaterals and the perforant pathway in phase precession is described, but the role of local interneurons is poorly understood. Our goal is estimating of the contribution of field CA1 interneurons to the phase precession of place cells using mathematical methods. The CA1 field is chosen because it provides the largest set of experimental data required to build and verify the model. Our simulations discover optimal parameters of the excitatory and inhibitory inputs to the pyramidal neuron so that it generates a spike train with the effect of phase precession. The uniform inhibition of pyramidal neurons best explains the effect of phase precession. Among interneurons, axo-axonal neurons make the greatest contribution to the inhibition of pyramidal cells.

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.

No evidence that acute clozapine administration alters CA1 phase precession in rats

Hippocampal phase precession, wherein there is a systematic shift in the phase of neural firing against the underlying theta activity, is proposed to play an important role in the sequencing of information in memory. Previous research shows that the starting phase of precession is more variable in rats following maternal immune activation (MIA), a known risk factor for schizophrenia. Since starting phase variability has the potential to disorganize the construction of sequences of information, we tested whether the atypical antipsychotic clozapine, which ameliorates some cognitive deficits in schizophrenia, alters this aspect of phase precession. Either saline or clozapine (5 mg/kg) was administered to rats and then CA1 place cell activity was recorded from the CA1 region of the hippocampus as the animals ran around a rectangular track for food reward. When compared to saline trials, acute administration of clozapine did not affect any place cell properties, including those related to phase precession, in either control or MIA animals. Clozapine did, however, produce a reduction in locomotion speed, indicating that its presence had some effect on behaviour. These results help to constrain explanations of phase precession mechanisms and their potential role in sequence learning deficits.

Hippocampal place cells exhibit impairments in spatial information coding in an APP‐knock in model of Alzheimer’s Disease

AbstractBackgroundThe hippocampus is one of the first cortical regions to exhibit Alzheimer’s Disease (AD) pathology. The spatially‐related firing of hippocampal place cells provides the cellular basis for spatial memory and this is impaired relatively early in AD, yet few studies examine place cell activity in AD mouse models. We undertook an in‐depth characterisation of hippocampal pyramidal cell activity in an APP knock‐in model of AD.MethodMicrodrives carrying 8 tetrodes were implanted into the left CA1 hippocampal subfield of 14‐month female mice (four APPNL‐G‐F, four wild‐type littermates). Mice undertook daily foraging sessions in an open field and ran on a linear track as CA1 activity was recorded. On completion of experiments, 40µm coronal sections of fixed brain tissue were stained using Cresyl Violet to verify tetrode placement and Thioflavin‐S to quantify amyloid β plaque burden.Result270 cells were recorded (119 wild‐type, 151 APPNL‐G‐F). CA1 pyramidal cells were classified as “place cells” or “non‐place cells” based on their spatial information content (bits/spike). Pyramidal cells recorded in wild‐type mice had significantly greater spatial information content than APPNL‐G‐F pyramidal cells (Figure 1), and a higher proportion were classified as place cells. Wild‐type place cells had significantly greater spatial information content than APPNL‐G‐F place cells. Corresponding differences were identified in place field size (Figures 2, 3). A positive correlation was identified between Aβ plaque burden and pyramidal cell spatial information content in the four APPNL‐G‐F mice (Figure 4).Coordination of place cell firing by the hippocampal theta rhythm was disrupted in APPNL‐G‐F mice; phase‐locking of pyramidal cells and place cells was significantly reduced (Figure 5), there was less coherence in the preferred theta phase across the pyramidal cell population, and a reduction in theta phase precession was observed.ConclusionAPPNL‐G‐F CA1 place cells exhibited deficits in both rate coding and temporal coding of spatial information indicating that amyloid β pathology, in the absence tau tangles, was associated with a disruption of hippocampal place cell function. These results provide preliminary support for the hypothesis that disruption of hippocampal function by AD pathology manifests as altered place cell activity and spatial behaviour.

Grid cell disruption in a mouse model of early Alzheimer’s disease reflects reduced integration of self-motion cues

Converging evidence from human and rodent studies suggests that disrupted grid cell coding in the medial entorhinal cortex (MEC) underlies path integration behavioral deficits during early Alzheimer's disease (AD). However, grid cell firing relies on both self-motion cues and environmental features, and it remains unclear whether disrupted grid coding can account for specific path integration deficits reported during early AD. Here, we report in the J20 transgenic amyloid beta (Aβ) mouse model of early AD that grid cells were spatially unstable toward the center of the arena, had qualitatively different spatial components that aligned parallel to the borders of the environment, and exhibited impaired integration of distance traveled via reduced theta phase precession. Our results suggest that disrupted early AD grid coding reflects reduced integration of self-motion cues but not environmental information via geometric boundaries, providing evidence that grid cell impairments underlie path integration deficits during early AD.